Handbook of Combustion, Volume 2 (Combustion Diagnostics and Pollutants) [1 ed.] 3527324496, 9783527324491

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1 An Overview of Combustion Diagnostics Alfred Leipertz, Sebastian Pfadler, and Robert Schießl 1.1 Introduction

During the past thirty years, tremendous progress has been made in the development of diagnostic tools for combustion research. The results obtained by applying these diagnostic techniques has contributed greatly to the current understanding of combustion, to the improvement of practical combustion devices with a lesser impact on the environment, and to the development of new combustion processes. The field has grown quickly, especially during the past two decades, such that today combustion diagnostics are used for manifold purposes that include fundamental research in academia, power plant control (for diagnosing pollutant emissions and ensuring reliable operation), or production technology (to optimize the production processes for commercial goods). As it is difficult to provide a brief overview that fully meets the requirements of all these groups, this chapter need not include a complete and detailed overview. Rather, it includes the details of dedicated techniques and their use in both scientific and technical applications. Consequently, only the essential properties of particular diagnostic techniques, together with some examples of their uses, are discussed here. Hence, a more general discussion of the role of diagnostics within the field of combustion science and technology is provided. First, those quantities and phenomena that are relevant to combustion processes, and which are therefore targets for diagnostic approaches, are outlined. It is also shown that the appropriate choice of suitable measurement techniques depends heavily on the particular properties of the combustion process to be investigated. Based on these general aspects, several diagnostic techniques are described that are commonly used to investigate combustion phenomena. These techniques can be split into two classes, namely those based on mechanical probing, and those which utilize optical diagnostics. The discussion of each technique includes a short treatment of the underlying physics, an assessment of the applicability of the method in combustion processes at both laboratory and technical scale, and of the ability of

Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright Ó 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

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the method to fulfill the needs for spatial and temporal resolution, nonintrusiveness, and robustness. A further section is dedicated to imaging and multidimensional diagnostics and, in describing the simultaneous use of the different measurement techniques, the state of the art of laser diagnostics in combustion research is highlighted. Finally, the potential of laser-diagnostics to validate those approaches used in numerical simulations is discussed. The overview is completed by the provision of accessible quantities and relevant diagnostic techniques, detailing comprehensive information relating to the application of different combustion diagnostic techniques. The advent of lasers may be regarded as the main starting point for the tremendous development of spectroscopic methods for combustion diagnostics. Previously, both emission and absorption spectroscopy had contributed to the combustion sciences well before the onset of laser technologies. Indeed, the existence in flames of important intermediate species such as OH, CH, HCO, NH or C2 had been proven by using spectroscopic methods. Yet, spectroscopy based on lasers offered novel, vastly refined ways in which the combustion phenomena could be observed. By employing the small spectral bandwidth of laser light, it became possible to distinguish or to isolate different spectral features of atoms and molecules at much greater resolution than in the absence of a coherent light source, while the ability to produce ultra-short laser pulses made possible the resolution and analysis of very rapid and transient processes. Notably, laser beams can be formed very easily into well-defined, sharp geometric shapes that are more point like, line-like and plane-like than is possible with conventional light sources, whilst the direction of propagation of laser light can be controlled with great precision. Consequently, it became possible to define irradiated (probed) volumes with great accuracy, and over very large distances. Taken together, this collection of unique properties led to laser diagnostics becoming the most widely used procedures, not only in fundamental and applied combustion research but also for the investigation and control of practical combustion systems.

1.2 Diagnostics in Combustion: Tasks and Requirements

As it is difficult to understand the tasks and needs of combustion diagnostics without any prior knowledge of the properties of combustion, a brief description of such properties should help to explain how certain requirements are imposed on diagnostic techniques. The desired temporal and spatial resolution of a measurement depends on the governing time and length scales of the system to be characterized. An estimate of these scales for a small collection of different combustion applications is shown in Table 1.1. Combustion often occurs as a spatially extremely inhomogeneous process in thin, sheet-like regions (flames). Since, in most realistic combustion systems, the thickness of these layers is on the order of some ten to hundred micrometers, an

1.2 Diagnostics in Combustion: Tasks and Requirements Table 1.1 Time and length scales of some different combustion systems [1].

Application

Time scale (ms)

Length scale (m)

Flame measurement – laminar Flame measurement – turbulent Fire research Jet engine; compressor inlet Gas turbine burner Afterburner

105–106 10 2–102 102–103 103–104 10 1–101 10 1–100

10 10 10 10 10 10

4

–10 –10 5 –10 4 –10 5 –10 5 –10 5

2 2 2 1 4 4

investigation of these tiny structures will require a high spatial resolution, a precise alignment, and an accurate definition of the measurement volume. Figure 1.1 shows, for an additional illustration of the length scales, the complex structure of a steady laminar flame (taken from a numerical simulation) by species mass fraction and temperature profiles across the flame front. Combustion also involves a wide range of time scales; some relevant chemical reactions occur within a few nanoseconds, while many chemical species that play key roles in combustion chemistry exist for only very short time intervals, in the range of hundreds of nanoseconds or microseconds. An inability to resolve these short time scales means that many of the essential aspects of combustion measurements may be missed. However, the use of lasers allows the temporal resolution or short measurement times required to observe these rapid processes to be achieved, one example being the structures hidden in a flame (Figure 1.2). Other aspects of combustion that impose high demands on diagnostic techniques include the complexity and high parametric sensitivity of many combustion processes. Due to the strong nonlinearity of the equations (mostly the chemical source

Figure 1.1 (a) Structure of a premixed methane/air flame at 20 bar (simulation). The spatial extent of the scene shown is 0.1 mm; (b) Sketch of the temporal and spatial scales relevant in combustion.

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Figure 1.2 Temperature structure of a turbulent flame taken by two-dimensional Rayleigh scattering (false color representation, top right) which is hidden in flame photography (bottom left) [2].

term) that govern the dynamics of a combustion system, those species that exist in tiny amounts [down to mass fractions in the parts-per-million (ppm) scale] may exert a greater influence on the system’s behavior than those which are abundantly present, in the percent range. The ability to detect and measure these “key” species (e.g., OH, CH in Figure 1.1), without interference from the much more abundant “bath” of hundreds or thousands of other species, represents a major requirement for the successful experimental analysis of combustion. The potentially high sensitivity of combustion with respect to variations in physical boundary conditions can render prohibitive the use of measurement techniques that greatly alter the physical conditions during an experiment. Clearly, a diagnostic technique should not alter the system that it is attempting to measure; indeed, a major indicator for the quality of a diagnostic technique in this respect would be its level of nonintrusiveness. Recognized diagnostic techniques can be quite sharply separated, based on their level of intrusion, with most optical techniques considered nonintrusive, and those involving mechanical probes highly intrusive. Finally, major constraints exist when a diagnostic technique is to be used within a technical combustion environment. Unlike laboratory systems, most practical environments are not designed specifically to allow or alleviate diagnostic procedures to be carried out. Hence, diagnostic techniques must often be applied under conditions that are not optimally suited to the underlying measuring principles. An important property of a diagnostic technique is, therefore, its “robustness” – that is, its ability to function reasonably well under conditions that may deviate strongly from those for

1.3 Invasive Techniques

which the technique was originally designed. Robustness also implies that the instruments used for diagnostics can operate under the adverse conditions (e.g., high temperatures and pressures, presence of highly reactive substances) encountered in combustions. The ideal diagnostic technique must be sufficiently robust enough to survive hostile environments, and to provide a large amount of combustion-related information.

1.3 Invasive Techniques

Traditional approaches for combustion diagnostics are typically based on techniques where a mechanical probe is inserted directly into a region of interest. This may be either a sensitive part of the measurement system, or a device that samples the medium of interest (either continuously or batchwise) at the measurement point for a subsequent ex situ analysis. Although the following approaches are often used for measurements under practical conditions, the most undesirable property of invasive probes – that is, a local interaction with the measurement system to be analyzed – remains unavoidable, and the often non-negligible inherent systematic errors must be carefully weighed if the measured quantity is to be rated. The relevance of the problems caused by mechanical probes depends on the mechanical size of the probe relative to the size of the combustion field under investigation. 1.3.1 Temperature

For technical applications, the temperature inside a combustion chamber is probably the most important state variable to be measured. The same holds for fundamental investigations in downscaled model flames, where tremendous progress has recently been made with regards to the analysis of temperature distributions. 1.3.1.1 Thermocouples By far the most widely used devices for determining temperatures in combustion systems are thermocouples. Here, the underlying physical principle is the Seebeck effect, which describes the occurrence of a material-dependent electric voltage when a temperature difference exists between the junction points of two different conductor materials that form a closed loop. In practice, the two different materials provide standardized (albeit nonlinear) voltage–temperature characteristics over the applicable temperature ranges. The details of some different material pairs of thermocouples and their application range, that can be used in combustion systems are listed in Table 1.2. Depending on the temperature range encountered, the measurement accuracy is 0.5–0.75% of the indicated temperature, although at least 2 K [3] can be improved upon by using an appropriate calibration. As with all invasive techniques, the main drawback of thermocouples is that the probe(s) must be placed directly into the measurement volume, where it can

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Pairs of thermocouple materials and their application ranges (types J, K, R, B after Ref. [3]; type D after Ref. [5]). Table 1.2

International code letter

Material

Application range ( C)

J K R B D

Fe/Constantan Ni-Cr/Ni-Al Pt-(13%)Rh/Pt Pt-(30%)Rh/Pt-(6%)Rh W-(26%)Re/W-(5%)Re

210–1200 270–1372 0–50–1768 000–1820 00-0–2315

influence the flame via a number of mechanisms. However, in view of the robust measurement principle these well-known disadvantages are often accepted for many applications. Depending on the dimensions of the probe and the flow conditions of the measurement object, the local flow field in the probed volume can be greatly influenced; the mixing of fuel and oxidizer or the turbulence–chemistry interaction can also be affected by such nonisokinetic sampling. Furthermore, the heat balance of the flame may be affected by heat conduction and radiation, mainly from the surrounding burning chamber walls. In addition, certain materials on the sensor surface are known to act as chemical catalysts, and this must be differentiated against the reaction of the thermocouple material (mostly platinum; see Table 1.2) by using chemically active species that increase the decomposition of the normally stable refractory ceramics which, in most cases, serve as an insulation material in the flames or at high-temperature atmospheres. Heitor and Moreira [4] have provided an excellent overview of the drawbacks and successful applications of these sensors in the field of combustion diagnostics. 1.3.1.2 Resistance Thermometry Resistance thermometry represents another invasive technique for temperature measurements, in which temperature-dependent changes in the electrical resistance of a conductor material are used to determine local temperatures with point-wise precision. Despite the perfect linearity of resistance-based thermometers and the availability of standardized types (e.g., with platinum; Pt100), the main drawback of resistance thermometry, when compared to thermocouples, is its limited application range of up to about 1300 K and the long response times required. The accuracy of the technique exceeds that of the thermocouple, however [6]. 1.3.1.3 Thermochrome Paintings In recent years, thermochrome paintings have become popular for providing a more crude estimation of, for example, the surface temperatures of components. The basic principle behind such color formation is the ability of certain materials to reversibly change their color as a function of the ambient temperature, this being due to changes in the materials’ crystalloid or molecular structures. An additional, recently developed method of temperature measurement employs temperature-sensitive paints (TSPs); this is based on the sensitivity of the luminescent molecules to their

1.3 Invasive Techniques

thermal environment following (ultraviolet) excitation [7]. A rise in temperature of the luminescent molecule raises the probability that the molecule will return to ground state via a nonradiation process, rather than emit a photon. This thermally induced phosphorescence quenching forms the basis of the temperature measurement via a quantitative detection of the emission attenuation. 1.3.2 Flow Velocity 1.3.2.1 Pitot Tubes Traditionally, Pitot tubes have been used to measure the total pressure of moving fluids; by combining the information acquired with that relating to the surrounding static pressure, the flow velocity can be deduced from the dynamic pressure (which is the difference between the total and static pressures). Prandtl tubes (Pitot static tubes) are used to measure the total and dynamic pressure simultaneously. Whereas, Pitot static tubes are still used in modern airplanes to measure the pressure and pressure differences simultaneously to determine both altitude and airspeed, the invasive probing techniques used to measure flow velocity on a pointwise basis have been largely superseded by the advent of noninvasive laser diagnostics. Dibble et al. [8] have compared the velocities measured by laser Doppler anemometry (LDA; see Section 1.4.6.1) with Pitot tube measurements, in a nonreacting jet flow and nonpremixed jet flames. The discrepancies between the Pitot probe and LDA measurements were within the range of 5% for the jet flow. However, an additional systematic error was observed in the turbulent flame when measuring the dynamic pressure that is attributed to heat transfer to the Pitot tube. Despite these problems, Pitot-type sensors are still used today in a variety of applications, one such example being to support the numerical simulations of dust explosions [9]. In this case, dust- and temperature-resistant Pitot-type anemometers used to measure turbulence intensities were combined with a high-speed camera to visualize flame displacement and simultaneously access the ratio between turbulent flame speed and turbulence intensity under different operating conditions 1.3.2.2 Hot Wire Anemometry The basic principle of hot wire anemometry (HWA) can be used to determine flow velocities by measuring the cooling of heated wires by forced convection in a flow that is dependent on the flow velocity (e.g., Ref. [10]). Although HWA is recognized as a classic diagnostic method for turbulence research, it can only be used to investigate combustion systems in the unburned region of the flame to be analyzed. This is mainly due to the fact that, even if the anemometer material were able to withstand the high temperatures in the flames, the required temperature corrections would be impracticable. Nevertheless, HWA is often used to characterize the turbulence conditions of combustion systems pointwise in the reactant zone. For example, HWA has been used for in-cylinder measurements in an internal combustion engine in a car [11], as well as to study the propagation of premixed natural gas air flames in a rectangular duct which was closed at one end [12].

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1.3.2.3 Ionization Probes An alternative invasive approach for the examination of flame-relevant velocities is that of ionization (also Langmuir) probes, where an electrical field is applied across the flame. The subsequently measured currents and potentials can then be used to measure ion concentrations (e.g., Ref. [13]), flame positions (e.g., Ref. [14]), or flame propagation speeds (e.g., Ref. [15]). Alternatively, for engine diagnostics a spark plug has been used as the probe [16]. 1.3.3 Species Concentrations

Measurement of the concentrations of minority and majority species prior to, during, and/or after the actual combustion process, is essential not only for investigating fundamental combustion phenomena but also for process control applications. Different probing strategies are applied in general, mainly depending on the measurement principle, and due in part also to the regularized or historically established method of sampling. For example, constant volume sampling (CVS) has been used for many decades to support the testing of vehicle emissions, whereby a constant total flow rate of a vehicle exhaust plus dilution air is maintained. In order for this to occur, as the exhaust flow increases, the dilution air must be automatically decreased. In this case, a bag measurement of the emissions represents the key method for legislative purposes, as it provides a single value for the major exhaust species of a complete test cycle, including the different phases of acceleration and constant speed. Although the sampling may be conducted in a continuous manner by using a suitable ejector or probing device (e.g., Pitot tube or low-pressure sampling), followed by additional dilution stages, the quantitative analysis of the species concentration can be performed batchwise in the case of some diagnostic techniques. An example of this is the gas-chromatographic measurement of species in engine exhaust gases, although this is also often applied to an analysis of basic properties such as heating value and the composition of gaseous hydrocarbon fuels for combustion in stationary gas turbines. 1.3.3.1 Flame Ionization Detectors Traditionally, flame ionization detectors (FIDs) [17] are used to measure the concentrations of hydrocarbons downstream in coiled columns that separate the inflowing species to be analyzed on the basis of their different retention times on the column surface [18]. For exhaust gas analysis, these detectors can be used as stand-alone systems in order to quantify the amounts of unburned hydrocarbons (UHCs) as a composite. The physical principle of FIDs depends on the fact that a pure hydrogen flame produces very little ionization of the involved species, whereas the addition of traces of hydrocarbons causes a drastic increase in the degree of ionization. Consequently, FIDs are composed of a hydrogen diffusion flame into which the gas to be analyzed is inserted; this results in a measurable direct current (DC) signal of an applied electrostatic field in close vicinity to the flame in the presence of UHCs.

1.3 Invasive Techniques

1.3.3.2 Chemiluminescence Detectors The analysis of oxides of nitrogen (NOx) in exhaust gases is typically conducted using chemiluminescence detectors, where the primary principle is a photo-physical detection of the signal emitted as electronically excited NO2 decays to the ground state following the chemical reaction of NO with ozone. The NO2 concentrations are acquired indirectly via an additional measurement of the concentration of NO after a preceding total conversion of the complete NOx-load to NO; this is followed by a simultaneous measurement of the NO concentration, without conversion and subtraction of the obtained concentrations. 1.3.3.3 Nondispersive Infrared Analysis The nondispersive infrared (NDIR) analyzer is a robust device which is used to measure carbon monoxide (CO) concentrations in exhaust gases, by making use of the strong broadband absorption near 4.7 mm. The device typically consists of a reference and a probe cuvette, both of which are irradiated with IR light. The use of a chopper wheel permits an alternating IR radiation of both the gas to be analyzed and the reference gas mixture, such that no absorption occurs at the probed band of the spectrum. Often, an opto-pneumatic detector is applied that measures the flow between two additional absorption chambers located beneath the probe and the reference cell. Due to the different absorption rates in the latter cells, the IR-absorbing gases in the detector chambers feature different heating rates (and thus volumetric expansions) which are balanced by the flow through a microchannel. The latter effect is converted to an electric current that is proportional to the CO concentration in the probe volume. With this apparatus it is also possible to monitor CO2, SO2, NH3, H2O and other exhaust gas components, by using appropriate absorption wavelengths (see Section 1.4.3). Concentrations of oxygen can be measured by making use of the electrochemical or paramagnetic properties of the dimer. The electrochemical approach is utilized in the exhaust ducts of almost all Otto engines with integrated three-way catalysts, for measuring and controlling the composition of the fuel–air mixture. The principle of the potentiometric lambda oxygen sensor (see also Vol. 2, Ch. 4) is based on the oxygen ion conductivity of a ZrO2-membrane with exhaust gas passing by on one side (outer Pt electrode) and ambient air on the other side as a reference (the “inner Pt-electrode”). The paramagnetic approach to measuring oxygen concentrations is based on the strong magnetic susceptibility. In this case, a magnetomechanical principle is implemented that is based on a sensor in which a rotator comprising two nitrogen-filled spheres (diamagnetic) is arranged within a symmetric magnetic field. If an oxygen-containing gas passes through the sensor, the oxygen is drawn into the magnetic field due to its paramagnetic property, thus strengthening the field. In contrast, any nitrogen inside the glass spheres will have an opposite magnetic polarization and be forced out of the field, causing a rotation. The degree of deflection thus caused is proportional to the oxygen concentration.

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1.3.3.4 Gas Chromatography/Mass Spectrometry In addition to the above-mentioned species-specific diagnostic techniques that are used widely in commercial sensor systems to characterize species concentrations under technically relevant conditions, gas chromatography (GC) and mass spectrometry (MS) are each applied to investigate fundamental phenomena (see also Vol. 2, Ch. 2). Both, GC and MS systems offer the opportunity of quantitative trace analysis for a large number of species, based on a single-sensor system. Axford et al. [19] have applied MS to the sampling of ions from atmospheric flames to study the effects of applied electric fields. The kinetic aspects [20] or special issues in the analysis of exhaust gas composition of internal combustion engines have each also been investigated using MS concentration measurements, an example being that of oil emissions [21]. Flame studies have been performed using GC alone (e.g., Ref. [22]) or in combination with MS [23]. 1.3.4 Pressure

In the case of technical applications, measurement of the burning chamber pressures (respectively the pressure at firing conditions as a variable of state) plays an important role, not only with regards to stability issues but also to security issues. Moreover, knowledge of the lower and upper process pressures, for example of the ideal Joule cycle, would provide direct information on the thermal efficiency. In the case of automotive applications in particular, the measurement of engine and compressor cylinder pressures can provide a decisive indication of complete engine performance, since it can be related to the engine’s power, efficiency, throughput, and leak status. The time-based evolution of cylinder pressure is also indicative of the “health” of a machine, and enables condition-based maintenance. Depending on the apparent temperature range, working atmosphere and pressure, and also on the temporal resolution, different types of pressure measurement methods may be used. For almost all pressure ranges and low sample frequencies, a simple manometer-type pressure gauge can be used in conjunction with resistive, capacitive, or inductive transducers. A good example of the application of this sensor type is in the measurement of fuel pressure in the supply lines of a domestic gas or oil burner. Piezoelectric or thin-film strain gauge-type pressure sensors are often used when high sampling frequencies are necessary. This may apply especially to in-cylinder measurements, where the sensors may be integrated into the spark or glow plug (e.g., Ref. [24]). Another specific application for pressure measurements within harsh environments is in the investigation of combustion-driven pressure oscillations in lean premixed gas turbines, where a feedback between heat release fluctuations and the burning chamber acoustics can result in severe combustion noise, with pressure amplitudes of several hundreds of millibars. In this case, piezoelectric pressure sensors are best suited for detecting and measuring the dynamic pressure

1.4 Noninvasive Techniques

phenomena in the presence of high static pressures. It should be noted, however, that an additional cooling of the sensor would be necessary when the measurement point has to be located close to the burner system. Recently, low-cost fiber-optic pressure sensors have also been introduced, for example, in engine diagnostics (e.g., Refs [25, 26]). In this case, pressure-sensitive paints (PSPs) have been developed which feature a pressure-dependent quenching behavior, that allows precise pressure measurements to be made (e.g., Ref. [7]). 1.3.5 Particulates

One largely undesired byproduct of combustion is the emission of particles in liquid or solid form, of which soot is the most important. While the emission of gaseous species is often characterized by mass concentration, particulate emission can additionally also be described by the average diameter of the primary particles and/or of the aggregates being formed from the primary particles. This is of crucial importance as the hazardous potential of soot particles is closely linked with the respirability and the surface-to-volume ratio. Details on particle properties measurement are provided in Vol. 2 Ch. 9 of this handbook, and details on soot and soot diagnostics in Vol. 2 Ch. 15. A special issue for the characterization of particulate emissions is the method of sampling from the gas phase. Here, thermophoretic sampling is regarded as one of the most gentle approaches as it allows off-line analysis under quasi-in situ conditions [27, 28].

1.4 Noninvasive Techniques

The introduction and further development of noninvasive methods in combustion diagnostics was mainly motivated by need to overcome the disadvantages of the above-mentioned diagnostic tools, such as the significant disturbance of the system being probed. This problem area may be clarified by comparing photographic images that show pointwise concentration measurements, using either a mechanical or a laser probe in a laminar premixed flame (Figure 1.3). For the mechanical probe, a distinct disturbance of the flame shape is seen that is attributable to a local perturbation of the energy and momentum balance, and which results in a dislocation of the flame front. In contrast, the flame shape using the laser probe seems to be unaffected and to show the same symmetry as if no probe had been applied. A similar comparison was performed on a more quantitative basis for oxygen concentration measurements in the laminar premixed methane/air flame shown in Figure 1.3. Here, a Q-switched ruby laser and a continuous-wave laser Raman probe were used to measure concentration and temperature profiles from selected intensities of the Raman–Stokes vibrational Q-branch (molecular rotational–vibrational

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Figure 1.3 Concentration measurement in a laminar flame. (a) The mechanical probe causes disturbances of the reaction zone; (b) No influence of the noninvasive laser probe can be observed [29].

transition with constant rotational quantum number J) [30]. The differences in O2concentration measurements, taken with a quartz-suction probe, are plotted for two downstream positions in Figure 1.4. Even at large downstream positions located outside the field of view in Figure 1.3, the differences in the radial profiles were considerable [30]. It was asserted, that deviations between the invasive and noninvasive techniques were mainly due to a worse local resolution of the mechanical probe, which also tended to dislocate the reaction zone, leading in turn to both a squeezed reaction zone

Figure 1.4 Radial profiles of the O2 concentration measured in premixed laminar methane/air flame. Comparison between mechanical probe and laser Raman measurements at a downstream position of 1 d (a) and of 6.5 d (b) [30].

1.4 Noninvasive Techniques

Figure 1.5 Schematic of different interaction processes between an irradiated laser beam and matter present in the sample volume. The table lists the differential interaction cross-sections of some of these processes.

and a less-deep gradient at the outer parts of the flame. In the case of temperature measurements it is also necessary to consider the radiation effects [1] which in some cases will depict an uncorrectable error source, as has been observed during gas temperature measurements above a porous radiant burner [31]. During the past few decades, many detailed reviews and books have provided an overview of nonintrusive laser diagnostics in combustion, and have also described their basic principles and recent experimental results (see, e.g., Refs. [32–34]). The principle of optical measurement techniques is shown schematically in Figure 1.5, where different processes are depicted and compared in terms of achievable signal intensities by the magnitude of the interaction cross-sections. In addition to the emission of radiation due to chemiluminescence (emission spectroscopy; see Section 1.4.2.), different laser-based processes can be distinguished. Upon irradiating a laser beam with frequency n0 into a gas sample, an interaction takes place between the irradiated photons and the matter present in the probe volume, such as solid or liquid particles or gaseous molecules. This interaction gives rise to different forms of physical processes that can be distinguished by the laser beam attenuation using extinction processes (absorption plus scattering), or by the emission of radiation with a frequency that is different for different processes. Typically, it is equal to the irradiated frequency for Mie and Rayleigh scattering, or it is frequency-shifted for fluorescence or Raman scattering. By assuming the same experimental conditions for all different processes, in a first approximation the emission intensities of the different processes will be directly dependent on the magnitude of the interaction cross-section (this is also shown in Figure 1.5 for the scattering and fluorescence techniques). As a result, the magnitude of the crosssection provides direct information on the signal strength achievable, and this often forms the basis for the choice of the best-suited technique. The very special qualities of the weakest Rayleigh and Raman processes have led to their becoming important measurement tools in several combustion investigations. In Table 1.3 an overview is given on different optical techniques and the quantities which can be probed by these

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Table 1.3 Tabulation of optical techniques and the measurable quantities.

Measurable quantities Flowfield Velocity ui, turbulent fluctuations u0 2i and stresses u0 i u0 j Mass- and momentum flow ru, ru2 and scalarvector correlations r0 u0i Combustion field Temperature

Major species concentration Minor species and intermediate products Species detection Thermal non-equilibrium scalar-vector correlations

Metrology

Mie (LDA, PIV) Mie þ Rayleigh (Raman), Filtered Rayleigh (FRS) Pyrometer/Raman/CARS/Fluorescence/ Phosphorescence Rayleigh/Absorption Absorption/Raman/CARS Absorption/Fluorescence Emission Raman/CARS Mie þ Rayleigh/Raman/Fluorescence

r0 u0 i , T 0 u0 i , c 0 u0 i Particle size Diameter d (distribution) of primary particles, aggregates, and droplets 2D distribution Temperature T Concentration c Density r Liquid fuel Vapor fuel Fuel/air ratio Velocity Soot

LII, Mie (PDA), LII þ Rayleigh (RAYLIX)

Rayleigh/Raman/Fluorescence Raman/Fluorescence (/Mie) Rayleigh Mie Fluorescence þ Mie/Exciplex fluorescence Raman (Rayleigh)/Tracer fluorescence PIV LII/Emission

techniques. Each of these different optical diagnostics techniques is described in greater detail in the following sections, starting with the visualization techniques that are not depicted in Figure 1.5, but which utilize any changes in the refraction index of the sample volume during the investigation. 1.4.1 Visualization Techniques

Flow visualization differs from other experimental methods in that it renders certain properties of a flow field directly accessible to visual perception [35]. Although these techniques can be applied to combustion systems in particular (albeit only qualitatively), they have made a significant contribution to the understanding of combustion phenomena since the advent of modern diagnostics techniques. Weinberg [36] has provided an excellent overview of the study of refractive index fields in combustion and aerodynamics, and the most important approaches in this field, including

1.4 Noninvasive Techniques

Schlieren techniques and shadowgraphy, are reviewed with regards to their application in combustion systems in the following sections. Unlike some approaches, that allow the investigation of three-dimensional (3-D) structures (e.g., holographic interferometry, which has also been demonstrated for application in combustion; see Refs [37], [38]), the 3-D information obtained from fluids under investigation may be reproduced only by using these techniques in an integrative manner, if a projection of the scalar field is to be imaged effectively. 1.4.1.1 Schlieren Techniques Schlieren techniques represent one of the oldest diagnostic tools for investigating flows in a two-dimensional (2-D) manner, and especially for visualizing flow structures as they appear. The (German) term “Schliere” denotes a certain area of an otherwise homogeneous, transparent medium which features inhomogeneities in terms of its chemical composition, density, temperature, or pressure, all of which result in local differences in the refractive index. In a classical set-up (commonly referred to as the Toepler method), collimated light is transmitted through the test section of the fluid under investigation [39], such that an image of the light source is formed in the plane of a knife edge located at the focal point of a spherical lens placed behind the test object. A camera lens behind the knife edge forms an image of the test section in the recording plane. The knife edge is then aligned in such a way that a portion of the light emitted from the light source is cut, which effectively reduces the total recordable intensity. If special points in the test section deflect the incident light, then the images of these spots will appear either brighter or darker in the recording plane, depending on the direction of deflection. As a result, the first spatial derivative of the index of refraction field can be visualized. Several combustion studies using Schlieren techniques have been reported, including their application in combination with laser-induced fluorescence (OH-LIF) to study the structure of a propane/air premixed flame as a function of different fuel air ratios and flame stabilization processes [40]. Alternatively, these techniques have been used to investigate the influence of pressure on the structure of turbulent premixed Bunsen flames [41]. The recorded images taken at different pressures provided an impressive visualization of the governing length-scales (Figure 1.6).

Figure 1.6 Instantaneous Schlieren photographs of turbulent Bunsen flames for pressures between 0.1 and 1.0 MPa [41].

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A demonstration of the tomographic algorithms as applied to the reconstruction of quantitative temperature fields in gas flames has been presented in Ref. [42]. 1.4.1.2 Shadowgraphy Although the casting of a shadow from an object located in the optical path of a light source was first utilized by Marat [43] to study fires, it was Dvorak [44] who first analyzed the shadow effect for scientific flow visualization. Typically, point shaped light sources are used to illuminate the fluid to be analyzed. The individual light rays passing through the test section are refracted due to density gradients, such that the detectable intensity distribution at the recording plane is altered in comparison with the undisturbed case (i.e., a homogeneous index of the refraction field). Further analysis reveals that the attainable shadowgram depicts the mapping of the second derivatives of the index of refraction field. Consequently, a quantitative measurement of the index of refraction field requires a double integration on the recorded intensity distribution, which is rarely performed. This technique is mainly applied to obtain a quick but simply feasible impression of the flow conditions, rather than quantitative results. Examples of such applications include: (i) the high-speed imaging of a gas-fired pulse combustor to characterize the time dependence of the spatial characteristics of the combustion process [45]; and (ii) the investigation of flame kernel formation in a spark ignition engine by high-speed shadowgraphy [46]. 1.4.2 Emission Spectroscopy

The analysis of radiation spectra directly emitted by a flame, or from involved auxiliary facilities, may be regarded as the most passive approach to optical combustion diagnostics, since only a signal collection unit in combination with a spectrally resolving detector is required. The different colors of flames into which metal salts were introduced was first studied by Kirchhoff and Bunsen [47], who established the link between spectral emission lines and certain elements. However, unlike these early qualitative studies on thermally excited atoms, most combustionrelated emission spectroscopy of the gas phase is based on the chemiluminescence of molecules rather than the simple excitement of atoms. The bands of light determined by this mechanism result from molecular emissions, and are therefore broader and more complex than bands that originate from atomic spectra. As many of the kinetic reaction rates involved in hydrocarbon combustion are temperature-dependent, and the rate at which a chemically excited molecule or radical is produced is also temperature-dependent, the detectable radiation of the characteristic spectra of the intermediate radicals (such as OH. CH. , C2. , CN. , and NH. ; see Ref. [48]) (Figure 1.7) and of molecules such as CO2 [49] and H2O [50] from hydrocarbon flames, is effectively a product of both thermal and chemical excitation. Due to a lack of thermal equilibrium in the population of different excited molecular states in general, no quantitative measurements are possible by emission spectroscopy in flames. Consequently, for many applications emission spectroscopy

1.4 Noninvasive Techniques

Figure 1.7 Emission spectrum from an ammonia-doped, fuel-rich premixed butane–air flame [48].

has been superseded by laser absorption methods (see Section 1.4.3) that provide quantitative data relating to temperatures and concentrations. An early fundamental characterization of flame structures that employed the species-selective chemiluminescence of flame radicals has been reported by Gaydon and Wolfhard [51]. Emission spectroscopy has long been used for detecting flame radicals; examples include the investigation of periodic mixing in pulsating combustors [45] or, more fundamentally, the tomographic reconstruction of radical fields in premixed flames [52]. Previously, flame luminescence has been applied, within an academic environment, to the investigation of flame front movements [53], and to measure radical concentrations in low-pressure flames with the aim of deriving rate constants for the main radical source reactions [54]. However, based on its robust and simple principles, the emission spectroscopy of flame radicals has since expanded into industrial measurement applications (e.g., Ref. [55]). Most flame detectors used to monitor the binary (on/off) flame status for safety purposes in technical furnaces are based on the detection of chemiluminescence emitted from the flame radicals. However, the viability of OH. chemiluminescence as an active-feedback-control parameter for equivalence ratio disturbances of high-pressure, premixed flames has also been investigated [56]. In the latter context, the control of thermoacoustic instabilities in a gas-turbine combustor using a combination of microphone and OH. emission sensors to monitor the combustion process and to provide input to the control system, has also been demonstrated [57]. Unlike chemiluminescence of the gas phase, the solid components involved in a combustion reaction, such as soot particles or the burning chamber walls, emit blackbody (Planck) radiation; this is a fairly widespread emission type that can be used for

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temperature measurements in industrial applications [55]. Depending on the temperature range of the measurements to be made, several approaches have been established as a form of pyrometry for which also different types of pyrometer are commercially available. By following Planck’s radiation law, the temperature can be effectively calculated from a direct measurement of the radiation intensity within a certain band of the emitted black-body radiation spectrum, when the emission coefficient of the radiation source to be measured, describing the nonideal blackbody behavior, is known. As the quantitative measurement of the radiation intensity is a delicate task in practice, and an accurate determination of the wavelengthdependent emission coefficient may be connected to a large number of error sources, distribution pyrometry is often applied where the radiation intensity is measured for two (ideally almost adjacent) emission bands. Under the assumption that the emission coefficient at both bands is identical, the temperature can be measured without any need to measure (quantitatively) the radiation intensity or the emission coefficient. In the case that the emission coefficient is heavily wavelength-dependent, however, knowledge of the emission properties of the probed spectral band would be highly desirable. Whereas, pyrometry is often applied as a pointwise measurement technique, the advent of IR-sensitive cameras has allowed a spatially resolved temperature estimations to be made if the emission properties of the measurement object are well characterized. One-dimensional (1-D) emission spectroscopy temperature measurements in a sooting flame have recently been validated using coherent anti-Stokes Raman spectroscopy [58]. 1.4.3 Absorption Spectroscopy

Due to its generally robust measurement principles, absorption spectroscopy may be regarded as one of the most well-established nonintrusive line-of-sight techniques for the quantitative measurement of species concentrations of transparent media, and especially for industrial analytical systems. The basic mechanism relates to the concentration-dependent attenuation of light emerging from a radiation source during passage through the fluid to be analyzed, due to partial absorbance. If the emission spectrum of the radiation source (partly) overlaps with the absorption spectrum of the atom or molecule to be probed, then after propagating through the medium the transmitted intensity can be calculated using the Lambert–Beer law, which describes macroscopically the absorption process. Detailed overviews of the technique are available elsewhere [59–61]. The discrete electronic, vibrational, and rotational energy levels of atoms and molecules are describable by quantum mechanics, which in turn permits the absorption spectra to be calculated. The pressure, temperature, and chemical composition which form the boundary conditions of the absorption process can exert a significant influence on the absorption spectra by modifying the line width and shape. In contrast, especially the position of the absorption lines is an intrinsic property of the species to be probed. Depending on the measurement task and the amount of investment provided, either narrow- or broadband light sources can be used. Whereas, the latter approach

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has typically been followed for industrial sensor solutions, the introduction of laser light sources has simultaneously facilitated completely new application fields such as temperature measurements based on two-line absorption techniques [62], together with a strong increase in the signal-to-noise ratio (SNR) and the sensitivity. One fairly widespread example of broadband excitation is that of NDIR analyzers, which can be used for the continuous, noninvasive measurement of CO, CO2 and other components for exhaust gas analysis (see Section 1.3.3). The most severe drawback of such a broadband technique is the possible crosstalk with other species which may also absorb in the IR region. Another, more sophisticated, application is that of absorption-based spark plug sensors, which allow the in-cylinder, on-line monitoring of gaseous hydrocarbon fuels either using an incandescent lamp [63] or a laser source [64]. For this, the light is coupled into an optical fiber and fed into the spark plug which provides direct access to measurements within the cylinder volume. For quantitative, and especially specific, absorption-based analysis in combustion, narrow-band light sources are highly desirable. In this context, the advent of tunable diode lasers as a light source for absorption spectroscopy (TDLAS) has dramatically pushed the applicability of laser-based absorption sensors towards online process monitoring, as well as for combustion diagnostics [65–67]. Diode lasers offer, at low cost, the opportunity for simple wavelength tuning via either temperature or current control. If, in addition, the laser active material features a periodic corrugation which effectively forms a diffraction grating (distributed feedback laser; DFB), then the emitted line widths can be reduced considerably. The typical emission line widths of DFB lasers are much narrower than molecular absorption lines, which makes them an ideal tool for absorption spectroscopy. Due to their rapid response times on varied electric currents, tunable diode lasers are easily adaptable for either wavelength modulation spectroscopy (WMS) [68] or frequency modulation spectroscopy (FMS) [69], both of which allow a significant increase in the SNR of the measurement by off- or on-resonant probing of the absorption band of the species under investigation. This is important for practical considerations, since varying background signals and fouling of the viewing port windows can have a negative effect on the measurement results. Nearly all combustion-relevant species, such as CH4, O2, H2O, CO, CO2, NO, and NO2, can be probed using commercially available diode laser systems. For example, TDLAS has been applied to characterize low-pressure premixed CH4/O2/Ar flames inhibited with different fire-suppression compounds, by measuring the temperature and species concentration of a large number of flame species, including reactive intermediates [70]. One currently promising area of research is the development of wavelength-agile light sources, and their application to time-resolved multispecies absorption spectroscopy in combustion. As an example, Kranendonk et al. [71] have reported on a tunable external-cavity diode laser (ECDL) which scans from 1374 to 1472 nm for crank angle resolved gas temperature and H2O mole fraction measurements in an engine operating in homogeneous charge compression ignition (HCCI) mode. Such an approach may represent an interesting strategy for quasi-simultaneous multispecies analysis, offering a new diagnostic approach for a wide range of combustion applications. The recording of ultrahigh-speed absorption spectra of several species

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simultaneously with high-brightness supercontinuum radiation sources employing photonic crystal fibers, should lead to the establishment of a new generation of absorption spectroscopy instrumentation [72, 73]. 1.4.4 Laser-Induced Fluorescence

Laser-induced fluorescence (LIF) is a resonant absorption–emission process between laser photons and atoms or molecules [74]. Due to the resonant character of the excitation, with its typically large cross-sections, LIF signals are usually several orders of magnitude stronger than those obtained from nonresonant techniques (e.g., Rayleigh scattering and Raman scattering; see Figure 1.5). The physical principle of LIF signal generation has further important implications for use of the technique in combustion diagnostics. Different species can be discriminated by the selection of an appropriate excitation wavelength. When the discrimination of species based on their absorption features is hindered by a strong spectral overlap, differentiation may still be possible on the detection side by blocking signals from the undesired species with spectral filters. This contributes to a good selectivity, such that LIF can often allows one particular species to be “picked out” from a mixture of hundreds or even thousands of species involved in a combustion process. There is also a potentially large sensitivity, with species having concentrations of about 10 5 mol m 3 and below having been measured; for an ideal gas at 1 bar and 2000 K, this corresponds to a molar fraction of 10 5 and below. More recently, LIF has also been used for temperature measurements by probing the population distribution of the molecules. The wavelength shift of the fluorescence relative to the excitation light can be exploited for the spectral separation of signal and scattered excitation light. The combination of a high signal strength and good spectral discrimination between the signal and undesired stray light provides the technique with a certain robustness. Its application is not limited to laboratory experiments, however, and it has been extended to systems of semi-technical or full technical scale. Notably, LIF measurements have been carried out at locations difficult to access by other diagnostic devices, such as the combustion chambers of piston engines or of gas turbines. The fundamentals and potential applications of LIF for combustion research are detailed elsewhere [75–78]. A more detailed discussion is also provided in Chapter 8 of this volume of the Handbook. 1.4.5 Laser-Induced Phosphorescence

Similar to LIF, laser-induced phosphorescence also involves the emission of radiation during the relaxation of excited electronic states inside a molecule or atom to a lower energy level, after previous excitation by an irradiated laser photon. It can be delimited phenomenologically from fluorescence processes mainly by the governing

1.4 Noninvasive Techniques

radiation time scales. Whilst fluorescence decays are mostly terminated within less than 1 ms, phosphorescence lifetimes are typically significantly longer. Phosphorescence phenomena based on noncoherent excitation sources can be observed for different applications in daily life, whereas laser-induced phosphorescence offers a number of features that have contributed to an increased investigation of the technique for applications in combustion diagnostics during the past two decades. Here, especially the sensitivity of the detectable signals on temperature variations in combination with high SNRs has encouraged the development of laserinduced phosphorescence thermography [79]. In contrast to LIF thermometry, which may suffer severely from difficulties in the quantification of quenching behavior due to missing data relating to spatially resolved boundary conditions, thermographic phosphors show a degree of independence on the bath gas composition. The reason for this may be attributed to the fact that the luminescent activator material (e.g., a rare earth element), is doped into a host material (often a ceramic), where it is shielded from any ambient influences. However, it must be noted, that the luminescence behavior of some materials can feature also a distinct dependency on pressure. Meanwhile, several material combinations have been identified which, due to their high signal sensitivity within a certain temperature range, have been applied successfully also under combustion relevant conditions [79]. At this point, two different approaches to temperature determination based on luminescent materials must be distinguished. The first approach – the so-called “lifetime method” – utilizes the temperature-dependent decay of the detectable phosphoresce signal. In this case, the temperature can be measured pointwise by using fast photodiodes, or in 2-D format by at least two (intensified) charge-coupled device (CCD) cameras, with a subsequent comparison to a calibrated signal decay library. This approach has been used to film cooling processes in gas turbine combustors [80], and for temperature measurements on rotating turbine blades [81] and on piston surfaces in diesel engines [82]. The details of some initial feasibility studies for spray temperature measurements have also been reported [83]. The second approach is the “intensity ratio method,” where the signal ratio of different temperature-dependent emission bands is evaluated for temperature measurements. Also in relation to combustion applications, 2-D surface temperature measurements at the outlet nozzle of the afterburner of an aircraft engine have also been reported [84]. The gas-phase temperatures during combustion in a diesel engine running in HCCI-mode have also been estimated, using a similar approach [85]. 1.4.6 Scattering Techniques

Laser scattering techniques comprise frequency-unshifted Mie and Rayleigh scattering, and frequency-shifted Raman scattering. The data in Figure 1.5 indicate that the achievable signal intensities of these different scattering processes vary tremendously in magnitude, such that the simultaneous application of several of

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these techniques may be difficult, or even impossible. This holds true especially for Mie and Rayleigh scattering, which feature the same emission frequency. 1.4.6.1 Mie Scattering Mie scattering, as the strongest scattering process, is the result of an interaction between irradiated light and phase boundaries. It can thus be used to detect the location of the existence of different phases, for example, gas-phase bubbles in liquids or liquid-phase droplets or solid-phase particles in a gas-phase environment, which also could be a combustion environment. As an example, Figure 1.8 shows the typical mushroom-like structure of a diesel jet in the primary break-up region a few microseconds after leaving the injection nozzle (start of injection). The figure shows the liquid intact-core being surrounded by a two-phase flow, and the gas phase being generated by cavitation inside the nozzle [86]. Here, a laser sheet has been directed into the center of the diesel jet of a mini sac hole nozzle, using a long-distance microscope for signal detection. By recording two frames with a defined temporal delay, the jet velocity can then be calculated. The same technique is commonly used for a more macroscopic characterization of the direct injection of diesel and gasoline fuel, either directly in engines or under engine-like conditions in injection chambers [87–91]. For particle Mie scattering, the size of the scattering object should be of the same order of magnitude as the wavelength of the incident light. The detectable intensity is a function of the particle diameter dp, the particle number density N, and of the observation angle relative to the direction of the incident laser beam H: I ¼ f ðdp ; N; HÞ. A fundamental analysis of the underlying theory of the scattering mechanisms can be found elsewhere [92, 93]. For an experimental situation of an

Figure 1.8 Diesel jet primary spray break-up a few microseconds after the start of the injection [86].

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appropriately particle seeded flow, where the observation angle and the mean particle diameter are in good approximation constant, the detectable signal intensity is directly proportional to the number of particles, and thus to the concentration of the seeded gas component which can be used for gas concentration imaging in the flow [94]. An alternative seeding technique has been developed by Chen and Roquemore [95] for flame investigations, in which propane–air jet diffusion flames were analyzed with respect to the flame structure and the zone of reaction. For this, a 2-D visualization of TiO2 particles was performed that had been formed in the reaction zone by the reaction of fuel gas-seeded TiCl4 with the in situ-generated water derived from the combustion reaction. The TiO2 appears as submicron particles which serve as the Mie scattering center. A related approach is the direct seeding of reactant gases with oil droplets or TiO2 as a flame-front marker. This is possible for premixed flames in the flamelet regime, where the reaction zone has a thickness of only some 100 mm. In the case of seeded oil, the flame front is visualized by the disappearance of Mie scattering at the entrance of the reaction zone as the oil evaporates. Based on the observable intensity distribution, the flame contour and curvature characteristics are frequently determined [96–99]. A direct seeding of TiO2, which also exists downstream of the reaction zone, offers the opportunity to measure flow velocities in both the unburned and burned regions of the flame. In this case, transition from the reactant to the product zone can be deduced from the different seeding densities that result from the temperature-related gas density difference, and this can be utilized for a conditioned evaluation of the turbulence characteristics [100, 101]. Mie scattering is also considered to form the physical basis of laser Doppler anemometry (LDA), where the Doppler-shift frequency of the Mie-scattered light from particles moving through a fringe pattern generated by the crossed sub-beams of a continuous-wave laser is collected by a photosensor for velocity measurement [102] (see Chapter 7, which also provides detailed aspects of seeding). Such an early characterization of pointwise turbulence quantities inside combustion systems has been reported in a premixed, town gas–air flame [103]. The supplementation of an LDA system by at least one equidistantly spaced additional detector unit to collect the Mie-scattered light under a different viewing angle enables simultaneous probing of the mean diameter of spherical particles. The particle diameter can be calculated from the observable phase shift of the Doppler signals detected by the different sensor; this technique is known as phase Doppler anemometry (PDA) [104, 105]. As an example, PDA has been used in spray flames to measure the mean droplet diameter in a gas-supported, swirlstabilized kerosene flame so as to determine the location of the maximum burning fraction of the droplets, together with temperature measurements [106]. In another example, the influence of different electrical field strengths and geometries on the atomization process of electrostatically charged hydrocarbon fuel sprays has been investigated [107]. Within the past few years, LDA as a pointwise and especially widely used metrology for velocity measurements in combustion systems, has gradually been overtaken by

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the advance of particle image velocimetry (PIV). Whereas, comparable turbulence characteristics were difficult to identify during the early days of PIV (due to problems of photographic imaging and the elaborate correlation of two adjacently recorded exposures), the historical advance of LDA has been overtaken by the digital imaging of Mie-scattered light on CCD chips, followed by digital image processing. In addition, recent advances in computer hardware to speed up data acquisition and evaluation, coupled with large and cheap memory space, have led to a significant rise in the number of reports of whole-field velocity measurements using PIV. One of the first successful applications of PIV in combustion was to measure the in-cylinder flow of a motor car engine [108], where vector maps over a 12  32 mm area parallel to the piston were recorded. Recently, high-speed flow field diagnostics in combustion systems by PIV have offered the opportunity to investigate time-dependent phenomena, such as combustion-induced vortex breakdowns in swirl-stabilized flames [109]. As a 2-D measurement technique, Malarski et al. [110] have proposed an imaging metrology for the measurement of droplet diameters by simultaneously applying 2-D Raman and Mie scattering. In this approach, the ratio between the volume-dependent Raman signal and the surface area-proportional Mie signal is used to generate frozen images of the droplet diameter. 1.4.6.2 Rayleigh Scattering In Rayleigh scattering, the energy of the incident photon is not adequate for the excitation of a higher quantum state of the investigated molecule (see Figure 1.5). Instead, the molecule is excited to a higher “virtual” energetic state, with an immediate fallback to a real molecular energy level. If this final level is identical to the initial level, then in effect no energy exchange has occurred between the photon and molecule. Thus, independently of the scattering molecule, the emitted photon has the same frequency as the incident laser. Consequently, it is normally not possible to detect selectively one individual species in a combustion system by Rayleigh scattering, as the signal will have resulted from all species in the gas mixture. Likewise, discrimination between the Rayleigh signal from otherwise scattered laser light (e.g., Mie scattering from droplets or particles) and stray light of the environment is not possible, unless additional measures are taken to block any undesired light, perhaps by using a molecular filter to absorb the laser stray light and the narrow-band Mie scattering (filtered Rayleigh scattering) [111]. The strength I of the scattered light from one individual species is proportional to its number density c, multiplied by a species-specific, approximately temperatureindependent Rayleigh scattering cross-section s [112]: I1c
s

In a mixture of species, the Rayleigh signal results from a superposition of the contributions of all species I/

n X i¼1

ci
si

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where the index i runs over all n components in the mixture. For a mixture of ideal gases, the number density ci can be expressed by the species’ molar fraction xi, P xi
s i . pressure p, and temperature T as ci ¼ xi p=ðRTÞ, such that I / p=ðRTÞ
Using this formula, temperatures can be inferred from Rayleigh signals, provided that information about the pressure and the mixture-averaged Rayleigh cross-section P ci
si is available (see Refs [112–115]). This requires, however, that the mixtureaveraged Rayleigh cross-section does not vary significantly with chemical composition, nor that it can explicitly be determined or at least estimated [116]. An alternative approach for temperature measurements based on Rayleigh scattering is to exploit the effect of the temperature-dependent Doppler broadening of Rayleigh light [117]. In the most recent applications, planar Rayleigh scattering has been employed using a light sheet technique, with temperature information being collected simultaneously inside a 2-D plane crossing the combustion field [115, 118, 119]. Likewise, 3-D temperature field information is (in principle) available, when in a 2-D approach two different wavelengths are irradiated simultaneously to form two parallel adjacent planes, with the signals being collected on two separate CCD cameras [120]. Rayleighexperiments in crossed-plane configurations have also been performed, often in combination with additional diagnostic approaches, for obtaining 3-D information along a line [121, 122]. Besides fundamental flame studies, Rayleigh scattering has also been applied to sooting flames by using the filtered Rayleigh technique [111, 123], in practical systems such as combustors [119, 124], or to investigate fuel vapor distribution in a heavy-duty direct injection (DI) diesel engine [125]. An alternative approach has also been taken to separately detect the polarized and depolarized components of the Rayleigh signal in turbulent nonpremixed flames, thus allowing measurement of the 2-D distribution of fuel concentrations [126]. This was later combined with LIF of OH and CO [127] to infer four important quantities (mixture fraction, temperature, scalar dissipation rate, and the rate of the reaction CO þ OH ! CO2 þ H) in turbulent partially premixed flames. Data from polarized/depolarized Rayleigh measurements have also been used as a test case for applying the reduced state space concept to multiscalar measurements in combustion [128]. A combination of Rayleigh scattering with other techniques has provided important additional information on the combustion process, as well as for the validation of numerical simulations. This has been achieved for example by the simultaneous use of planar Rayleigh and OH-LIF [129–131], or planar Rayleigh with PIV, collecting at the same time temperature and flow velocity field information and allowing the direct determination of turbulent flux [132, 133]. The application of elastic scattering, combined with absorption in the form of extinction measurements, led to the first in situ characterization of soot particles in flames using nonintrusive optical diagnostics over forty years ago [134]. More recently, D’Alessio et al. [135] have measured mean particle diameters in a sooting flame via the detection of scattered light under different angles, and this remains an important technique that occasionally is combined with extinction measure-

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ments [136–138]. The detection of Rayleigh scattered light from soot particles represents one part of the RAYLIX technique [139] for characterizing soot volume fractions and particle size distributions in flames (see Section 1.4.7). 1.4.6.3 Raman Scattering 1.4.6.3.1 Linear Raman Scattering Following the nonresonant excitation of a molecule to a virtual state (as for Rayleigh scattering) by using a laser photon with a toolow energy to excite an electronic state, the fallback ends in a final state that is different from the initial state. The probability for this type of transition is about three orders of magnitude smaller than for Rayleigh scattering, and this results in an elastic Raman scattering process in which the emitted photon experiences a frequency shift given by the difference between the initial and final molecular energy levels probed in the process. When the final energy level is higher than the initial level, the molecule remains in a higher energy state after the interaction, and the emitting photon will feature a smaller frequency than the irradiated photon. This effect is due to the Stokes–Raman scattering being red-shifted relative to the exciting frequency. In the case that the final state is energetically lower than the initial state, the emitted photons gain energy relative to the irradiated photons, such that the so-called anti-Stokes– Raman signals will be blue-shifted relative to the exciting frequency. Details on Raman scattering and its application are available elsewhere [1, 32, 140–142], and also in Chapter 5 of this volume of the Handbook. One of the special qualities of Raman scattering is the simultaneous excitation of all molecules in the sample volume, without any restriction of excitation frequency. As nearly all molecules of interest in combustion have at least one Raman-active molecular energy transition, a direct relative concentration measurement is possible by simultaneously collecting the Raman signals of all species in the probe volume, if the relative Raman cross-sections of all species are known. The Raman scattering cross-section – and thus the signal intensity – scales with the fourth power of the excitation laser frequency. Therefore, high-frequency radiation is favorable for Raman excitation, and Raman experiments with laser excitation at short wavelengths (ultraviolet; UV) have been carried out [143, 144]. In most combustion systems, however, the presence of species that fluoresce when exposed to UV radiation sets a limit to the shortest practically feasible excitation wavelength in Raman experiments. Present knowledge suggests that the KrF-excimer excitation at 248 nm is the shortest wavelength yet to be used for Raman experiments in combustion [144]. Different possible approaches for temperature determination from Raman signals can be deduced from Figure 1.9, by using temperature-dependent intensity distributions in the pure rotational or vibrational bands [1, 140]. Concentration information can be obtained from the integrated line intensities of the vibrational branches, or of single rotational lines. As absolute measurements are difficult to perform, calibration at room temperature will simplify the procedure [146]. The (freely available) computer Code RAMSES [143] can be used to simulate Raman spectra for a given temperature, chemical composition and experimental parameters;

1.4 Noninvasive Techniques

Figure 1.9 Schematic of the temperature dependence of the Raman spectrum in the pure rotational and the rotational–vibrational bands. This example shows oxygen excited by a ruby laser [145].

it may also be useful for the opposite task, namely extracting species and temperature from a given Raman spectrum. In combustion, the Raman technique was used for concentration measurements at a quite early stage of laser diagnostics development in combustion (see Figure 1.4), often in combination with temperature measurements [30, 147–150]. However, since then linear Raman scattering has been applied widely to flame studies [143, 151–155], with both 1-D [156, 157] and 2-D [158, 159] spatial resolution having been achieved. Despite the difficulties associated with the extremely weak signals, Raman measurements have also been performed in practical systems, such as in engines [160, 161]. 1.4.6.3.2 Polarization- Resolved Linear Raman Scattering The application of linear Raman scattering in hostile environments such as sooting flames or practical combustion systems is often hindered (or may even be impossible) due to disturbances caused by chemiluminescence emissions, hydrocarbon fuel fluorescence interferences, particle Mie scattering, laser light reflection, or stray light. One method for obtaining undisturbed Raman signals under these conditions is to use the polarization properties of the Raman effect [162]. In this polarization procedure, which was proposed by Leipertz [1], the depolarized emissions can be completely suppressed from the highly polarized Raman signals by collecting separately the horizontally and vertically polarized signal components, followed by subtraction of the horizontal from the vertical polarization. By using this technique, Raman measurements have successfully been executed in systems which never would be accessible for the regular Raman technique, in sooting flames [163, 164], inside fuel jets [165, 166], and for in-cylinder engine measurements [167–169]. The 2-D distributions of several different combustion species, and also of the gas temperature, are displayed in Figure 1.10. These have been determined via 1-D Raman measurements in a highly sooting, nonpremixed flame (which is also shown in the figure).

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Figure 1.10 Two-dimensional distribution of combustion species concentration and flame temperature within the indicated field of view (left) in a sooting, nonpremixed methane flame

with bluff body taken by 1-D polarizationresolved linear Raman scattering (the distributions of C2H2, CO2, CO and H2 are not shown here) [163].

1.4.6.3.3 Coherent Anti-Stokes–Raman Scattering Among nonlinear Raman techniques, coherent anti-Stokes–Raman scattering (CARS) is the most widely employed. The CARS method involves a four-wave-mixing process in which, during the interaction of three irradiated laser beams in the interaction area, a fourth beam is generated that is emitted laser-like in one particular direction that is governed by momentum conservation. The frequency of the CARS beam follows from energy conservation, and is thus dependent on the frequencies of the three irradiated beams and the energy difference between both molecular states of the studied species probed by the CARS process [170]. If these are vibrational states, this will result in a vibrational CARS spectrum, whereas if only rotational states within one vibrational molecular state are involved then a pure rotational CARS spectrum is obtained. Details on CARS are available elsewhere [1, 32, 141, 142, 145], and also in Chapter 6 of this volume of the Handbook. .

Vibrational CARS: This is a well-established technique for concentration and temperature measurements [171–181], and is superior pure rotational CARS at higher temperatures [182, 183]. Originally, only a single species could be investigated at the same time, but during recent years several approaches have been developed providing multispecies capability. The relatively high signal strength compared to linear Raman scattering allows the technique to be used also in hostile and industrial environments. Notably, it was used during the early investigations of turbulent sooting and propellant flames [184–186], as well as in

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.

technical combustion systems, such as internal combustion engines [171, 187– 189] and combustors and furnaces [190]. Pure rotational CARS: The fundamentals and applications of pure rotational CARS have been described in detail [191], together with investigations of selected aspects of engine combustion [192, 193]. This technique provides more accurate results at lower temperatures than vibrational CARS [182, 183, 194, 195], and was first used for temperature measurements in flames in 1984 [196]. Since then, several improvements have been made with regards to signal separation [197, 198], Raman line width information [199, 200], measurement accuracy [201, 202], and stray light suppression [203–206]. As a result of these improvements, measurements can today be executed in technical environments not previously accessible, such as highly sooting flames [164, 207, 208], inside evaporating engine sprays [209, 210], and inside internal combustion engines [211, 212]. Several of these applications became accessible only by the use of polarizationresolved rotational CARS [213].

1.4.7 Laser-Induced Incandescence

Laser-induced incandescence (LII) is the only measurement techniques which can be applied for nonintrusive, online and in situ particle diagnostics. In contrast to scattering techniques, which also allow a nonintrusive characterization of soot, LII offers the opportunity for the simultaneous determination of soot mass concentration and the specific surface area of the soot primary particles, which represents a measure of the particle size. In combination with soot formation, LII is described in greater detail for soot diagnostics in Chapter 15 of this volume of the Handbook. LII is based on the Planck radiation emitted from particles during and after irradiation with high-energetic laser pulses. As the detectable signal intensity is mainly proportional to the amount of absorbed energy, the signal represents a good approximation to a function of the soot concentration or volume fraction. During the short heating period of the laser pulse (typically in the range of some nanoseconds), the particle temperature reaches values in the order of the vaporization (sublimation) temperature of the solid material. Below a characteristic threshold energy level, the LII signal is heavily dependent on the particles’ temperature; hence, for quantitative measurements a laser fluence larger than the threshold level is aimed for. The experimental procedure is often based on a preceding signal calibration step where soot volume fraction measurements are carried out based on extinction or probing techniques in order to incorporate the influence of different detection optics and viewing angles. In addition to measuring soot volume concentrations, the signal decay due to particle cooling by heat transfer to the ambient after irradiation allows the surface area of the primary particle, and thus also the particle diameter, to be determined. In this time-resolved LII approach (TIRE-LII) [214], the detected signal decay time is compared to simulated cooling rates, and is calculated from the heat balance of a

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single particle. Here, the absorption of laser irradiation and energy losses due to heat conduction to the ambient medium, sublimation and radiation are considered to result in a change of the internal energy of the particle. Thus, a parallel measurement of the ambient temperature is also required. Whereas, for point-wise measurements the complete signal decay can be measured via photodiodes with fast sampling rates and compared to simulated decay times, the imaging analysis of the primary particle diameters requires a 2-D measurement of the LII signal on at least two different occasions after irradiation. As only normalized signal decay times are compared, no extra calibration is necessary here. In an alternative approach, the signal ratio between different bands during the heating phase of the laser pulse was used to estimate the primary particle diameter via two-color pyrometry [215]. Another advanced approach that allows the simultaneous determination of soot volume fraction and mean particle diameter is the so-called RAYLIX technique [216] (combined measurement of Rayleigh scattering, laser-induced incandescence and extinction). Here, the 2-D distribution of the particle volume fraction is derived from LII signals via an online calibration from integral soot volume fraction measurement using extinction techniques. In combination with 2-D Rayleigh scattering measurements and previous comparisons to identify the conditions for quantifying the intensity of scattered light, the primary particle diameter can be calculated from the ratio between the scattered light intensity and soot volume concentration. The LII technique has been applied successfully in fundamental research, for example, to support the analysis of soot growth mechanisms in laminar premixed [217, 218] and nonpremixed flames [219], as well as to identify any problems associated with practical combustion systems (see Refs [220–222]). Whereas, very few reports were made on this technique before 1990, a number of excellent reviews has subsequently become available, including overviews of recent trends and current questions [223], current modeling issues [224] or, more specifically, a discussion of optical diagnostics for soot and temperature measurements in diesel engines [225]. 1.4.8 Miscellaneous Techniques

Several diagnostic approaches are described in the following sections which, due to their operating principles, are mainly restricted to applications of fundamental character. Resonance-enhanced multiphoton ionization (REMPI) incorporates a (multiphoton) absorption process with a laser-induced ionization step. REMPI features a good sensitivity for the detection of minor species, and a major advantage that it can be used for nonfluorescing but excitable gases [226]. The main drawback of REMPI is that any quantification of species concentration is typically achieved by inserting an anode into the flame so as to measure ion currents on a pointwise basis (see Ref. [227] for a discussion on detection efficiencies). Cavity ringdown (CRD) spectroscopy, a linear absorption-based technology used for the accurate measurement of combustion-relevant species, is based on a

1.4 Noninvasive Techniques

line-of-sight method and was developed as an alternative to the widely used LIF and the more complex coherent techniques. Here, the concentration of minority species is deduced from the signal decay of laser light being tuned to the absorption band of the species to be analyzed inside a cavity. With a higher inner-cavity concentration of the probe gas, cavity losses due to absorption are increased and the decay time decreased. For a known absorption cross-section and a precisely measured cavity geometry, absolute concentration measurements are possible without calibration. A recent review on CRD as applied to combustion is available in Ref. [228]. Besides CARS-spectroscopy (see Chapter 6 of this volume for details), various other coherent techniques may be adapted as diagnostic tools in combustion, if the measurement object requires the adoption of very robust measurement principles. In this context, degenerate four-wave mixing (DFWM) techniques may be used for species (and temperature) measurements if the traditional (linear) approaches cannot be applied, perhaps due to unacceptable interferences with background signals [229]. Both, laser-induced (thermal) grating spectroscopy (LIGS) and polarization spectroscopy (PS), by principle, produce coherent signals, but their current development status partly restricts their application to special surroundings. Thus, whilst LIGS (see Refs [230, 231]) is considered to be a promising tool for highpressure applications, PS – based on its inherent mechanism [232, 233] – can be used only for strongly depolarizing systems, that is, for real technical applications. 1.4.9 Simultaneous Multidimensional and Multiparameter Laser Diagnostics

The benefits of the individual techniques can be improved drastically if two or more diagnostic tools are combined to form advanced sensor systems. This may be either the parallel application of several different sensor types for process control, or the simultaneous use of nonintrusive tools in fundamental research. The latter aspect, in particular, is outlined in the following sections. The combination of advanced diagnostic tools is mainly motivated by two different problems. First, fundamental questions concerning the nature of turbulent combustion are to be solved, including investigations of turbulence–chemistry interaction, both for premixed and nonpremixed flames. In this case, the detailed structure of turbulent flames must be analyzed under the influence of different parameters such as varied mixture compositions and turbulence ratios. Based on the results of these studies, technically relevant conditions such as flame instability, flame flashback, local extinction phenomena and pollutant formation, would be better understood. Second, it is the current aim of the research community to facilitate the numerical modeling of combustion phenomena, and in order to support computational fluid dynamics (CFD) studies, experimental effort has been directed towards providing suitable data to validate and improve the current numerical approaches. Due to their inherent nature, the experimental strategies used for investigating premixed and nonpremixed flames differ widely. The most important quantity when describing the local state of non-premixed flames is expressed by the mixture fraction,

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f, which describes the multispecies composition of the local mixture (see the definition by Bilger [234], which is based on the fundamental studies of Burke and Schuhmann [235]). As the mixing process itself dominates the combustion, the state of the combustion reaction is also captured in the mixture fraction approach for many cases, if an assumption of short chemical time scales compared to the time scales of mixing holds true. Thus, the accurate measurement of a mixture fraction may be regarded as the main key to improving the understanding and modeling of nonpremixed flames. In an early attempt to acquire a more fundamental understanding of nonpremixed flames, Dibble et al. [236] reported on the pointwise characterization of the scalar field inside a ducted hydrogen flame by Raman scattering, together with laser Doppler anemometry for the simultaneous measurement of velocities. Subsequently, the major species were found to reach equilibrium concentrations, unlike some radicals which had been observed to exceed the equilibrium concentrations by more than threefold. In the meantime, a library-like experimental data archive has been established for simple, piloted, bluff-body and swirl-stabilized nonpremixed flames; this was aimed at providing a state-of the art collection of appropriate data-sets for validating and developing combustion models. (Note: see the Proceedings of the Turbulent Nonpremixed Flames workshops (TNF) 1996–2008 [237].) As a representative of the excessive efforts made in this field, the study of Nooren et al. [238] is detailed here, wherein piloted hydrogen jet diffusion flame time-resolved simultaneous measurements of NO, major species, mixture fraction, temperature, and OH were obtained using not only linear Raman and Rayleigh scattering but also laser-induced fluorescence. The influences of different helium concentrations, as well as the effects of partially premixing, diluting with nitrogen or adding methane, are also presented. Simultaneous imaging techniques have been developed to acquire a deeper understanding of the fundamental processes in nonpremixed combustion. For this, Carter et al. [239] demonstrated the applicability of a combined diagnostics approach to locate the flame front via single-shot-based CH-LIF, and to characterize the flowfield simultaneously by PIV. The study results showed the CH-layer to be typically 1 mm smaller than the investigated jet flame, while simultaneous PIV measurements allowed an evaluation of the instantaneous flame front strain rates for which the flame was uninfluenced by flow-induced extinction. Another elaborate study to investigate the structure of nonpremixed flames was conducted by Joedicke et al. [240], in which a set of turbulent lifted hydrocarbon flames was investigated using several imaging techniques so as to access the stabilization criterion and the triple flame structure in close vicinity to the stabilization point. Close to the flame base, the lifted flames featured a tribrachial structure that was composed of a lean premixed flame, a rich premixed flame, and a diffusion flame that extended downstream from the same point [241].The geometric structure of the reaction zones was probed by Rayleigh scattering for fuel mass fraction measurement, laser-induced predissociation fluorescence (LIPF) of OH to detect the diffusion reaction zone, together with the LIF of polyaromatic hydrocarbons (PAH)

1.4 Noninvasive Techniques

and CH2O to monitor the rich and lean reaction zones, respectively. In addition, the flow field structure was characterized by applying PIV. In contrast, the characterization of premixed flames is often achieved in the frame of the reaction progress variable approach, which defines a dimensionless, normalized temperature [242]. Frequently, a flamelet assumption is applied for the numerical modeling of premixed flames, as this allows a decoupled treatment of the turbulence and the locally laminar-like chemistry field (see Ref. [243]). Thus, in addition to knowledge of the scalar field, the provision of flow field characteristics is essential if premixed flames are investigated with the aim of obtaining a deeper fundamental understanding of numerical modeling. In this context, Ferrao and Heitor [244] have developed a combined LDA/Rayleigh system based on a single continuous-wave light source for the simultaneous time-resolved measurement of velocity and temperature. Their approach enabled a direct evaluation along radial profiles of two components of the turbulent heat flux in baffle-stabilized premixed flames. Aimed at achieving a better characterization of the turbulent flux of the reaction progress variable in a piloted natural gas–air flame, Frank et al. [245] have developed a strategy for the imaging measurement of velocity fields and the relative distribution of the OH radical. As based on the Bray–Moss–Libby model [242], this abstract term can be related to the conditioned velocities of the unburned and burned gas mixture, while the OH radical distribution has been used to determine conditioned velocities that have been used to calculate local values of the turbulent flux term. The study results revealed the direction of turbulent transport to be a function of the ratio between turbulent velocity fluctuation and laminar flame speed. Recently, Filatyev et al. [246] have simultaneously applied acetone-LIF to estimate the flame-front position, together with stereo-PIV. The application of two temporally separated acetone-LIF systems allowed a statistical study of the flame movement, in addition to the direct measurement of 3-D turbulent fluxes. The following example highlights the fact that not all experimental techniques may be combined directly, as the physical measurement principles may be partially exclusive or may hamper any parallel applicability. Motivated by the fact that the simultaneous knowledge of density, temperature, and velocity fields is highly desirable in order to acquire a deeper fundamental understanding of premixed flames, Most et al. [247] have developed a metrology for the simultaneous application of planar Rayleigh scattering and PIV based on filtered Rayleigh scattering (FRS; see Section 1.4.6.2). For this, the Mie scattering of the seeding particles must be strongly suppressed by a molecular filter, such that the remaining Doppler-broadened region of the spectrum can be used for temperature measurements. Subsequently, this combination was used successfully for a direct determination of the Favre-averaged (density-weighted) turbulent flux term in a highly turbulent bluff-body and moderately turbulent wire-stabilized flames [133]. To obtain a deeper insight into the flame structure of premixed flames, Tanahashi et al. [248] proposed a two-radical concentrations and three-component velocity measurement in one common measurement plane based on CH/OH-LIF and stereo-PIV, which was applied to swirl-stabilized methane–air flames. The first simultaneous measurements of the detailed flame structure were acquired by

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simultaneously applying planar Rayleigh scattering and OH-LIF [129–131, 249]. These investigations have mainly been stimulated by discussions of the validity of different combustion regimes as a function of different turbulence and length scales. Whereas, the detection of the reaction front derived from temperature fields, tracer or radical distributions depicts only an indirect means of locating the reaction zone, the approach first described by Paul and Najm [250] was more straightforward as the heat release field could be imaged directly via simultaneous OH/CH2O-LIF. This socalled “heat-release imaging” has also been applied for different purposes [251–253] (Figure 1.11). In order to overcome the main restriction of the above-discussed metrology combinations (that only limited 3-D information is produced), Yip and Long [254] introduced a multiplane technique that allowed the calculation of all three instantaneous components of the gradient vector. The system was first demonstrated on a turbulent gas jet by taking simultaneous gas concentrations measurements from two closely spaced parallel cross-sections, using laser Rayleigh scattering in two illumination sheets of different wavelength. The approach was subsequently developed further by Chen and Bilger [121], who added OH-LIF measurements for application in petroleum gas and compressed natural gas (CNG)–air flames to determine the complete 3-D gradient of the reaction progress variable. Besides a detailed 3-D analysis of the flame-front location, a correlation between normalized OH radical concentrations and normalized 3-D gradients of the reaction progress variable was also provided. The 3-D temperature gradients could also be accessed from temperature measurements in two crossed laser light sheets [122]. The 3-D characterization of the velocity field distribution obtained from a double-light sheet approach was utilized by Pfadler et al. [255] for an experimentally based a priori test of subgrid scale

Figure 1.11 Single-shot image of the simultaneous measurement of flow and heat release field in a turbulent premixed V-shaped methane–air flame [253].

1.5 Interaction of Combustion Diagnostics, Theory, and Modeling

(SGS) models for the SGS scalar flux which appeared in a large-eddy simulation (LES) of turbulent premixed flames. Recent trends in laser-based combustion diagnostics have been clearly directed towards the high-speed analysis of the governing phenomena, where the general aim is to develop an analysis of time-dependent phenomena such as flame–vortex interaction and local flame extinction [256–258]. High-speed laser metrology has also been shown applicable in engine diagnostics [259] for in-cylinder velocity field measurements in a spray-guided spark-ignition engine, just before fuel injection and through the early stages of combustion, by using PIV at a frame rate of 16 kHz.

1.5 Interaction of Combustion Diagnostics, Theory, and Modeling

The field of combustion diagnostics cannot be seen as a productive tool for science and technology if it is considered in isolation from other disciplines related to combustion, such as theory and modeling. Rather, it is mostly the interaction between these fields that triggers major progress in science. At least two interactions have been identified between diagnostics and theory/ modeling. On the one hand, theory often provides the motivation for performing measurements in combustion systems, by identifying important open questions and relating them to quantities that should be investigated experimentally to help answer these questions. On the other hand, diagnostic results often attain their full significance only when interpreted on a theoretical background. As a consequence, the results obtained using combustion diagnostics may then be used either to validate combustion models, or to assess their limitations. There may, however, be other somewhat less obvious links. Knowledge of theory may also help to evaluate the validity of diagnostic approaches in combustion research, or to identify their limits. The applicability (or nonapplicability) of a certain diagnostic technique in a combustion process is normally not an inherent property of the diagnostic technique, but rather results from the particular properties of the combustion process under investigation. In fact, it is often the physical laws that underlie a combustion process that allow diagnostic techniques to function correctly. As an example of this, the Rayleigh technique (see Section 1.4.6.2) is frequently used for temperature measurements in combustion processes. It is known, however, that this method is not applicable for all types of system, as the mixture-averaged Rayleigh scattering cross-section of a reacting gas sample may be greatly altered during the reaction, thus “perturbing” the simple reciprocal dependence between the temperature and the Rayleigh signal. Figure 1.12 shows, as an example, the computed relationship between the Rayleigh signal (R) and temperature, for a large number of thermochemical states. The temperatures and chemical composition (molar fractions) of these states were generated randomly, the only restriction being that they fulfill the conservation laws of energy and element composition. The states are therefore physically “meaningful”

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Figure 1.12 Computed correlation between the Rayleigh signal strength and temperature in a reacting methane–air system. (a) Random, but physically “allowed” initial states; (b) After the initial states have undergone combustion reactions for 100 ms.

and could, in principle, appear in a combustion system. A theoretical Rayleigh signal was computed from these initial states. Figure 1.12a shows the resulting dataset in Rayleigh signal/temperature space, where each scatter point represents the temperature of a random state and the corresponding computed (temperature and composition-dependent) Rayleigh signal. The resulting rather “thick” point cloud showed that the signal–temperature relationship was very blurred: if the gas composition were random, it would not be possible to infer a temperature from a Rayleigh signal with reasonable accuracy. Mostly, the uncertainty of temperature for a given value of the signal (determined by the “width” of the scattered cloud of data) was several hundred Kelvin. However, the picture was greatly changed when processes associated with combustion came into play. In a simulation, the random states from Figure 1.12a were allowed to undergo combustion reactions for 100 ms, thus changing their temperature and chemical composition. When the Rayleigh signals were re-computed for the resulting new states, and plotted versus the “new” temperatures, a much sharper correlation between signal and temperature resulted (Figure 1.12b), and the determination of temperature from the Rayleigh signal was now possible with reasonable accuracy. The remaining uncertainty of temperature for a given signal was mostly below 50 K. The process of combustion had modified the initially random thermochemical states, resulting in a much stronger correlation. As a consequence, the Rayleigh technique could then be used to investigate the combustion process (namely to determine its temperature with reasonable accuracy). While this example is based on a simple, synthetic model, it highlights an important phenomenon, namely that the use of diagnostic techniques in combustion often requires – or at least is supported by – knowledge relating to particular properties of combustion. This is another mechanism which shows that information about combustion theory helps to interpret the experimentally observed signals. Therefore, combustion diagnostics can barely be reduced to the chemical analysis and temperature determination of a gas sample, combined possibly with velocimetry and a droplet or particle size measurements. Few of the known diagnostic techniques would achieve any results if no additional information about the system was available.

References

Figure 1.13 Some interaction mechanisms between diagnostics, theory, and modeling in combustion.

Such information may derive from either experience (gained in previous experiments conducted with the same, or similar, systems), or from theory. Some possible interactions between diagnostics, theory, and modeling in combustion are illustrated schematically in Figure 1.13. One excellent example of the interaction between diagnostics and modeling is the workshop series on Turbulent Nonpremixed Flames (TNF) [237]. This workshop maintains and encourages an interaction of modeling and diagnostics, for example, by providing databases of detailed diagnostic results obtained in a set of flames that can be used to check the predictions of combustion models. The increasing availability of computer codes that allow the theoretical computation of signals obtained in diagnostic techniques, such as LIFSIM [260], LASKIN [261], LIFBASE [262] for LIF signals, or the RAMSES Code [143] for Raman spectra, may also be interpreted as a step towards a closer link between theory and diagnostics.

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radii in turbulent diffusion flames. Environ. Combust. Technol., 2, 169–190. Axelsson, B., Collin, R., and Bengtsson, P.E. (2000) Laser-induced incandescence for soot particle size measurements in premixed flat flames. Appl. Opt., 39, 3683–3690. Tsurikov, M.S., Geigle, K.P., Kruger, V., Schneider-Kuhnle, Y., Stricker, W., Luckerath, R., Hadef, R., and Aigner, M. (2005) Laser-based investigation of soot formation in laminar premixed flames at atmospheric and elevated pressures. Combust. Sci. Technol., 177, 1835–1862. Shaddix, C.R. and Smyth, K.C. (1996) Laser-induced incandescence measurements of soot production in steady and flickering methane, propane and ethylene diffusion flames. Combust. Flame, 107, 418–452. Schraml, S., Will, S., and Leipertz, A. (1999) Simultaneous measurement of soot mass concentration and primary particle size in the exhaust of a DI diesel engine by time-resolved laser-induced incandescence (TIRE-LII), SAE Technical Paper Series 1999-01-0146. Snelling, D.R., Smallwood, G.J., Sawchuk, R., Neill, W.S., Gareau, D., Chippior, W.L., Liu, F., and G€ ulder, Ö.L. (1999) Particulate matter measurements in a diesel engine exhaust by laserinduced incandescence and the standard gravimetric procedure, SAE Technical Paper Series 1999-01-3653. Dankers, S., Leipertz, A., Will, S., Arndt, J., Vogel, K., Schraml, S., and Hemm, A. (2003) In-situ measurement of primary particle size during carbon black production. Chem. Eng. Technol., 26, 966–969. Schulz, C., Kock, B.F., Hofmann, M., Michelsen, H., Will, S., Bougie, B., Suntz, R., and Smallwood, G. (2006) Laserinduced incandescence: recent trends and current questions. Appl. Phys. B, 83, 333–354. Michelsen, H.A., Liu, F., Kock, B.F., Bladh, H., Boiarciuc, A., Charwath, M., Dreier, T., Hadef, R., Hofmann, M., Reimann, J., Will, S., Bengtsson, P.E., Bockhorn, H., Foucher, F., Geigle, K.P., Mouna€ım-Rousselle, C., Schulz, C., Stirn,

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2 GC/MS for Combustion and Pyrolysis Research James Cizdziel and Wei-Yin Chen

2.1 Introduction

Gas chromatography/mass spectrometry (GC/MS) is a powerful analytical tool used to separate complex mixtures of volatile or semi-volatile organic compounds, and to identify and quantify the individual components. Because combustion (a sequence of exothermic reactions involving a fuel and an oxidant, typically oxygen) and pyrolysis (the thermal decomposition of matter in the absence of oxygen, typically in an inert environment such as helium) often yield molecular products or fragments that are volatile, GC/MS is ideally suited for combustion and pyrolysis research. Indeed, pyrolysis (Py) is commonly used as a sample introduction device for GC/MS, and is generally applied to materials that, when vaporized, undergo decomposition (e.g., polymers). Specifically, Py-GC/MS involves the thermal decomposition of organic samples into smaller molecules, followed by the separation and detection of molecular fragments. When sufficient heat is applied to samples in a uniform and consistent fashion, the bonds within the material’s molecules may be broken in a reproducible manner. The resultant chromatogram is referred to as a pyrogram, which can be used to garner qualitative and quantitative information for the sample. Because the decomposition products are representative of the parent molecule, much can be learned about the degradation process and the structure of the original molecule. An excellent and recently published handbook on applied pyrolysis [1] includes an overview of the technique, together with the instrumentation fundamentals and details of its various applications. In contrast to pyrolysis, combustion research is generally performed offline, whereby combustion products are collected and subsequently analyzed using GC/MS. For example, condensates from a combustion may either be injected directly into a GC/MS, or injected following extraction into a suitable solvent. Solid combustion products may also be captured and analyzed with Py-GC/MS. In this chapter, details of both approaches are included. Within combustion and pyrolysis research, GC/MS has been widely employed for: (i) the structural characterization of natural organic matter found in waters [2], sediments [3], and soil [4, 5]; (ii) in the study of Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright Ó 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

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microorganisms [6] and biomass [7]; (iii) in the analysis of rubber [8], resins [9–12], inks [11, 12], paints [13], coal [14], wood [15] and, more recently, also nanomaterials [16–18], to name just a few applications. Following an initial section on the theory and principles, the chapter continues with a review of recent peer-reviewed publications, demonstrating the applications of the technique in both research and industry, and concludes with some of the present authors’ recent investigations into the role of mineral matter in the early stages of coal combustion. The review section includes several recent examples (post-2006) of studies that involve both qualitative (fingerprinting) and quantitative measurements.

2.2 Theory

Gas chromatography, for the separation of a mixture of molecules, and mass spectrometry, for the detection and identification of those species, has long been a powerful tool in academic, government, and commercial laboratories. Gas chromatography, using a liquid stationary phase, was first commercialized in 1955, and today many instrument companies either produce or sell GC/MS equipment. Modern GC/MS systems are user-friendly and employ powerful computers that control the system and readily process huge amounts of data. The principles of gas chromatography and mass spectrometry are detailed in many textbooks on analytical chemistry and instrumental analysis (e.g., Ref. [19]), whilst a practical user’s guide on GC/MS has also been recently updated [20]. Briefly, gas chromatography is used to separate the components of a vaporized sample, based on their being partitioned between a mobile (inert) gaseous phase and a liquid or solid stationary phase contained within a chromatographic column. For GC/MS, the column typically is a long, coiled capillary tube of silica with an internal coating of a viscous liquid such as Carbowax or a wall-bonded organic phase [20]. The major components of a gas chromatograph are shown schematically in Figure 2.1. The mobile phase, called the carrier gas, is usually helium, although hydrogen and to a lesser extent nitrogen, may also be used. The sample is vaporized, often within the injector, and introduced to the head of the column. The separation that occurs within the column is a function of the carrier gas properties and its flow rate, the column temperature, the stationary phase chemistry and thickness, and the column length and diameter. The way in which these variables affect separation is beyond the scope of this chapter, however. The coupling of gas chromatography with mass spectrometry (GC/MS) provides one of the most powerful tools available for the analysis of complex organic mixtures. In GC/MS, the molecules exiting the gas chromatograph are ionized, typically through electron bombardment or chemical ionization, before being focused into the mass analyzer. The ions are separated based on their mass-to-charge (m/z) ratio in the mass analyzer (Figure 2.2). Quadrupole mass analyzers are the most common because of their low cost, fast scanning capability, and general ruggedness. Time-of-flight and ion-trap mass analyzers are also common. Electron

2.2 Theory

Figure 2.1 A schematic diagram of a gas chromatograph. Reproduced with permission from Ref. [20]; Ó 2008, John Wiley & Sons, Inc.

multiplier detectors are then used to convert the ion beam reaching the detector to an electrical signal, which is amplified and processed by the data analysis system. The data can be recorded in two ways: (i) as a total ion chromatogram, which sums the ion abundances in the mass scans and plots this as a function of time; or (ii) as a single ion

Figure 2.2 A schematic representation of a typical GC/MS system. Reproduced with permission from Ref. [20]; Ó 2008, John Wiley & Sons, Inc.

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chromatogram, monitoring a single m/z ratio during the analysis. Although standard “cook-book” GC/MS methods are available for a variety of analytes, sample matrices, and applications, if certain pitfalls are to be avoided and quality results obtained it is essential that the analyst has not only a knowledge of chromatography and mass spectrometry but also analytical skills. Coupling a separate pyrolysis unit to a GC/MS allows the direct analysis of samples that previously required time-consuming extractions and derivations. As discussed above, pyrolysis includes the evaporation of volatile molecules and the thermal cracking of nonvolatile molecules into volatile fragments which can be analyzed with GC/MS. Whilst a detailed theory of molecular pyrolysis is beyond the scope of this chapter, the reader is referred to the handbook by Wampler [1]. With regards to commercial pyrolysis instrumentation and accessories, a variety of manufacturers produce thermal sample preparation equipment designed specifically for GC/MS (e.g., CDS Analytical, Inc.; ATAS GL Sciences Co.). In these systems, platinum or other types of filament are used for the rapid heating or slow controlled (programmed) heating of samples which may be placed in specialized sample holders or pyrotubes. The systems may be configured with trapping features to collect analytes from the pyrolysis, including reactant gas pyrolysis such that, ultimately, the products are introduced into the GC/MS. Software features allow the analyst to customize the heating rates, gas flow rates, and other variables that might impact upon the analysis.

2.3 Literature Review

The histogram in Figure 2.3 shows the number of publications per year (226 in total) containing the research topic “combustion GC/MS” using the American Chemical Society (ACS) Chemical Abstract Service (CAS) database “SciFinder” (searched 8 December 2008). The trend reflects the growth and apparent maturation of the method, starting in the mid 1990s. As Py-GC/MS is considered to be a technique with somewhat broader applications, it is not surprising that a similar search using “pyrolysis-GC/MS” yielded a much larger number of publications (1881 in total; data not shown). Narrowing the search to the period of 2006 through 2008, and using the same information as above, gave 94 and 36 references for “pyrolysis-GC/MS” and “combustion-GC/MS,” respectively. In this chapter, articles from the past three years were selected specifically to demonstrate the diversity of applications using GC/MS for combustion or pyrolysis research. The other criteria were that the journal be relatively well-known, and written in the English language. A breakdown of the reports based on arbitrary subject areas selected by the present authors is shown in Table 2.1. The reports were loosely classified based on the type of sample and/or the objective of the analyses, and show the diversity of applications for which GC/MS is currently being used within combustion and pyrolysis research. At least one-third of the Py-GC/MS papers relate to natural organic matter (NOM), including NOM in soil, sediment, sludge, wood, or wood derivatives. Another

2.4 Recent Applications of GC/MS in Combustion and Pyrolysis Research

Figure 2.3 Histogram showing the number of publications per year containing the research topic “combustion GC/MS”; the total number of hits was 226. The search was conducted using SciFinder (8 December 2008).

prominent area of interest using Py-GC/MS is the characterization of microorganisms and microbial agents, and the thermal degradation of biomass. Given the importance of – and recent emphasis on – energy, coal, and fuels, it is not surprising that a relatively large number of reports was found on those subjects. Carbohydrates and food also continue to be analyzed by GC/MS after combustion or pyrolysis. Earlier combustion (and pyrolysis) GC/MS reviews include: coal pyrolysis [21], which is considered a landmark development on the subject; analytical pyrolysis in art and archeology [22]; fingerprinting of environmental samples [23]; Py-GC in forensic science [24] and, more recently, the multiple reviews found within the handbook by Wampler [1].

2.4 Recent Applications of GC/MS in Combustion and Pyrolysis Research

Any methods and study details not described in the following sections may be found in the original publications. 2.4.1 Motored Engine Study of Diesel Fuel-Relevant Compounds and Premixed Ignition Behavior

Biodiesel and synthetic diesel fuels have been studied extensively as possible alternatives to diesel fuel. Szybist et al. [25] conducted a study to identify differences

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Table 2.1 Survey of the scientific literature (2006–2008) featuring Combustion-GC/MS and/or Py-GCM/S analysis.

Subject area

No. of reports

Combustion-GC/MS or Py-GCM/S analysis Soil, sediment, sludge Lignin, wood, peat Microbial, fungal Natural organic matter Rubber Energy, fuels Flame retardants Nanoparticles, nanotubes Black carbon Forensics, fingerprinting Ink, art Resins Carbohydrates, sugars Miscellaneous

12 12 11 8 7 7 5 5 4 4 4 3 3 9

Combustion-GC/MS analysis Biomass, microbes Food, glucose Coal Fuels Emissions, exhaust PAHs Miscellaneous

7 5 4 4 3 2 11

PAHs: polycyclic hydrocarbons.

in the autoignition process between these fuels by studying their behavior under premixed conditions in a motored engine. The experiments were conducted with different fuels, fuel–air mixtures and cylinder compression ratios, while monitoring the exhaust composition. A sample line heated to 190
C was used to transfer 3 l min1 of exhaust gas to a cell of an Fourier transform infrared (FT-IR) spectrometer. A dry impinger submerged in an ice bath was used to collect condensable species, which were also present in significant amounts. Methylene chloride was subsequently used to separate the organic species from the aqueous phase. The solvent was later evaporated under nitrogen “. . .so that the sample could be weighed and reblended in methylene chloride at the desired concentration.” A Shimadzu GC/MS system was used to analyze the organic species in the exhaust condensate. Each fuel demonstrated a two-stage ignition process, with a low-temperature heat release (LTHR) event followed by the main combustion. The LTHR produced high concentrations of aldehydes and CO while producing only negligible amounts of CO2. Another finding was that the aliphatic chain acted similarly to n- paraffins during LTHR, while the ester group remained intact. Whereas, the FT-IR data showed that decarboxylation occurred at significant levels for methyl decanoate, it was

2.4 Recent Applications of GC/MS in Combustion and Pyrolysis Research

concluded that this occurred after the aliphatic chain has been mostly consumed by other LTHR reactions. GC/MS was crucial in determining the sequence of reactions occurring under the experimental conditions used for combustion. 2.4.2 Alteration of Organic Matter in Response to Ionizing Radiation: Implications for Extraterrestrial Sample Analysis

Py-GC/MS was used to study the effects of ionizing radiation on a set of ten naturally occurring, terrestrial organic assemblages (bitumens) [26]. According to these authors, a full understanding of the radiolytic formation and evolution of organic matter is essential to appreciate the budget of organic chemicals that exist in cometary and interstellar ices, carbonaceous meteorites, and to understand the results of analyzes of irradiated extraterrestrial organic matter, such as that in cometary nuclei. For the experiment, the group used a CDS Pyroprobe 1000, fitted with a 1500 valve interface and coupled to an Agilent Technology 6890 gas chromatograph and a 5973 mass-selective detector (MSD). During pyrolysis, the samples were heated at 20
C ms1 to 610
C, and held at this temperature for 15 s under a flow of helium. Meanwhile, the temperature of the gas chromatograph oven was held at 50
C for 1 min, and then increased at 5
C min1 up to 300
C, and held at that temperature for 9 min. A SGE BPX5 column with He carrier gas flowing at 1.1 ml min1 was used for the separations. The compounds were identified by comparison to the National Institute of Standards and Technology (NIST) 98 mass spectral database, elution orders, and published data. Any co-eluting peaks were decomposed by integrations based upon selected mass fragments. The pyrolysis products of the nonirradiated group (complex-hydrocarbon mixtures) were found to be dominated by alkene–alkane couplets, whereas the bitumens containing uranium and thorium yielded products dominated by polycyclic hydrocarbons (PAHs). Several samples produced some oxygen-containing compounds such as benzoic acid and benzaldehyde. Among the study conclusions, it was suggested that radiolytic alteration may cause the mean combustion temperature of the organic matter to increase, due to a progressive loss of H that caused the atomic H/C ratio to decrease. In addition, the combustion behavior of the cometary organic matter was likely related to the radiation dose. 2.4.3 Identification of Historical Ink Ingredients

Pyrograms were collected for a series of substances that were commonly used in past centuries during the course of ink preparation [12]. The study was aimed at providing a basic chemical characterization of ingredients, such as the seeds and peel of pomegranate, gum Arabic, apricot gum, saffron, henna, and mustard. Pyrolysis was carried out at 500
C using an SGE Pyrojector II microfurnace, which was connected directly to a CLARUS 500 GC/MS system (Perkin-Elmer). Helium carried the pyrolysis products to a 30 m  0.25 mm internal diameter (i.d.) fused-silica column

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coated with a 0.25 mm film of RTXÒ 5 (cross-bonded 5% diphenyl, 95% dimethyl polysiloxane). The oven temperature was set to 45
C for the first 3 min, and then increased at 10
C min1 to 250
C, which was held for 20 min. The electron impact mass spectrometer was scanned from m/z 25 to m/z 1200 in 0.2 s. The structural assignment of compounds was based on spectral matching with the NIST 2002 library. A variety of compounds was identified in the programs, some of which were characteristic of the particular ingredient. For example, the pyrogram was found for white mustard (Sinapis alba L.), a perennial plant the seeds of which are yellow to light brown in color (despite the name) and consist mostly of proteins and fatty oils. The seeds were also rich in oleic acid, and contained a variety of aromatic compounds, as well as phenol and 4-methyl-phenol. However, it was noted that further investigations would be required to identify the best analytical approach for these aged ingredients, and also how other constituents of the inks might influence the pyrolysis process, before examining any original artworks. 2.4.4 Analysis of Deteriorated Rubber-Based, Pressure-Sensitive Adhesives

A variety of rubber-based, pressure-sensitive adhesives (RBPSAs) commonly found in packing tapes have been analyzed using Py-GC/MS. In a study by Kumooka [27], with implications for forensic investigations, packing tapes were exposed to sunlight for six months in order to accelerate oxidation of the adhesives. Pyrograms were collected on the exposed and unexposed adhesives, using a PY2020D pryolyzer equipped with a SS-1010E selective sampler (Frontier Laboratories, Koriyama, Japan). The pyrolysis was conducted at 500
C with the pyrolysis–gas chromatograph interface set at 320
C. The gas chromatograph was a model 6890 and the MSD a 5973N (both from Agilent). The pyrolysis products were separated on a 30 m Ultra alloy-5 þ metal capillary column (0.25 mm i.d., film thickness 0.25 mm). The temperature programming consisted of 40
C for 2 min, followed by a heating rate of 10
C min–1 to 200
C, then 20
C min–1 to 300
C, and finally held constant at this temperature for 5 min. The MSD was operated in scan mode with a range of 29–450 (m/z). Approximately 0.2 g of the unexposed RBPSA or 1 mg of the other samples was analyzed. Both, isoprene and limonene – the main pryolyzates of natural rubbers – disappeared from the programs of the adhesives following the exposure period, and the elastomer of each adhesive was oxidized. Other differences were observed between packing tapes and between exposed and unexposed adhesives, including a pyrolyzate peak of b-pinene resin (used as a tackifier) found in the exposed product but not in the unexposed product, although this may have been due to masking by the limonene peak. Because forensic chemists use both Py-GC/MS and FT-IR spectroscopy to discriminate adhesives, the research group also collected IR absorption spectra. Such spectra for the adhesives were changed so drastically after exposure that it was difficult to identify the constituents. In comparison to FT-IR, these authors concluded that Py-GC/MS would be more suitable for the examination of RBPSAs. They also found that natural rubbers and aliphatic petroleum resins decomposed completely during the course of deterioration. However, the tackifiers, which were

2.4 Recent Applications of GC/MS in Combustion and Pyrolysis Research

mostly coumarone resins, aromatic petroleum resins and b-pinene resins, could be identified by Py-GC/MS, even after deterioration. 2.4.5 Determination of Ergosterol as an Indicator of Fungal Biomass

The detection and analysis of fungi is important in a number of fields, including biology, nutrition, and medicine. Substances that have been used as markers of fungal contamination include chitin (a component of the fungal cell wall) and ergosterol (a major sterol constituent of most fungi). Efforts have been made to develop techniques for the rapid screening of fungal samples; classical methods may require incubation periods and rely on morphology and biochemical reactivity studies [28]. Parsi and Gorecki [7] presented a new rapid and robust method for ergosterol detection based on the combination of nondiscriminating flash pyrolysis with GC/MS detection. This method, which is further described by Parsi et al. [29], minimizes loss of the less-volatile pyrolyzates by modifying the pyrolyzer (essentially eliminating the pyrolysis–gas chromatograph injector interface). By reducing the dead volume and forcing the flow of the carrier gas through the pyrolyzed sample, it was possible to provide a more efficient transfer of high-molecular-weight compounds (e.g., ergosterol) to the GC/MS system. By using this set-up, the authors determined the presence of ergosterol – and thus the presence of fungi in the pyrolyzed sample – in a variety of matrices, including baker’s yeast, moldy bread, indoor dust, and a leaf infected with powdery mildew. Ergosterol was detected in all samples, ranging from approximately 6 mg g1 for the indoor dust to 4000 mg g1 for the baker’s yeast. The primary advantages of the method over conventional extraction schemes were that only a very small sample was required, and this needed no preparation prior to the analysis. 2.4.6 Characterization and Evaluation of Smoke Tracers in Particulate Matter from Wildfires

During the 2003 wildfire season, western Montana was heavily impacted by smoke. Ward et al. [30] collected 24 h samples of 2.5 mm-diameter particulate matter (PM2.5) during significant smoke events, and analyzed the filter samples using high-performance liquid chromatography (HPLC) and GC/MS. The purpose was to quantify the concentrations of several chemical markers of wood smoke generated under natural combustion conditions. The filter samples were extracted and analyzed for levoglucosan, following a derivatization procedure, and for methoxyphenols by using a recovery standard with the label in methoxy group (CD3). A HP5890 gas chromatograph and a HP5970 mass spectrometer were used, and several characteristic ions monitored in selected ion monitoring mode for quantification. It was concluded that, of all the potential markers for wood smoke derived from PM, levoglucosan was the most useful as it was found in all samples when using GC/MS, and it had the strongest correlation with PM. The anhydrosugars galactosan

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and mannosan were also detected, but at lower levels than levoglucosan; HPLC was unable to detect the former biomarkers. Interestingly, the ratios of the markers (levoglucosan to mannosan, and guaiacol derivatives to syringol derivatives) were indicative of softwood (major tree) combustion. It was suggested that the source profiles may be used to apportion forest fire smoke PM2.5 in northern Rocky Mountain airsheds during forest fire events such as the one studied. 2.4.7 Trace Organic Species Emitted from Biomass Combustion and Meat Charbroiling Relative to Particle Size

When introducing the subject of size-resolved PM emissions from cigarette smoke, meat cooking, and the combustion of pine, oak, eucalyptus, and rice straw [31], these authors addressed the magnitude of fine particulates stemming from biomass combustion in the US (approximately one third of the total), and the potential risk to human health associated with the inhalation of fine (PM2.5) and ultrafine (PM0.1) particulates. (Epidemiological studies cited by the authors indicated a relationship between increased fine PM in the atmosphere and increased mortality [32].) Because fine and ultrafine particles found in the atmosphere are often composed of primarily organic compounds (e.g., Ref. [33]), it would be of major interest to develop source profiles for the ultrafine size fraction in particular, with the intention of apportioning the sources of PM0.1 in a sample. To that end, the authors reported the concentration of organic molecules detected in emissions from the materials listed above in six size fractions between 0.056 and 1.8 mm particle diameter, including PAHs and other molecules useful for source apportionment. The PM emissions were collected using denuder-filter-polyurethane foam (PUF) sampling trains and Micro-Orifice Uniform Deposit Impactors (MOUDIs). Each sample was spiked with two deuterated internal standard solutions, extracted into dichloromethane (DCM), and concentrated to 100 ml; the extracts were then analyzed using GC/MS (Agilent or Varian systems). Two groups of compounds were quantified: (i) PAHs, for their applicability as biomass combustion source tracers; and (ii) a second group of 25 compounds ranging in molecular weight from 124.1 to 412.7 g mol1. Fourteen PAHs were detected in the ultrafine size fraction of rice straw smoke, with the most abundant compound (benzo[a]pyrene) being emitted at a rate of 0.2–0.4 (mg kg1 wood burned). In cigarette smoke, benzo[ghi]fluoranthene (0.07 mg per cigarette) dominated, followed closely by chrysene/triphenylene (0.6 mg per cigarette). The most abundant organic species measured in meat cooking smoke was cholesterol; together with levoglucosan, these compounds should prove to be useful tracers for meat cooking and wood smoke emissions in the ultrafine size range. 2.4.8 Conversion of Rice Husks and Sawdust to Liquid Fuel via Pyrolysis

This report focused on the conversion of rice husks and sawdust into liquid fuel [34]. The authors suggested that a practical method to utilize rice husks and sawdust,

2.4 Recent Applications of GC/MS in Combustion and Pyrolysis Research

which are abundant in China and other areas as waste products of the agriculture and wood industries, would be beneficial. Traditional composting, due to a relatively poor nitrogen content, and incineration, based on concerns of atmospheric pollution by smoke, are each unsuitable for these materials. When the rice husks and sawdust were pyrolyzed at between 420 and 540
C in the absence of oxygen, a volatile gas (which could be partially condensed into liquid fuel) and charcoal were produced. A portion of the “uncondensable” gas could be used as fuel gas, while the crude oil could be refined into a vehicle fuel. These authors used GC/MS to show that the liquid fuel contained a complex mixture of organic compounds that had a low caloric value but could be used directly as a fuel oil for combustion in a boiler or a furnace, without any upgrading. Other conclusions from the study were that there was an optimal temperature for the thermal conversion of rice husks and sawdust into liquid fuel (the yield first increased but then decreased as a function of temperature). Yields attained ranged from 56 to 61%. Notably, the cost of the conversion could be reduced by replacing electric heating and the carrier gas nitrogen with charcoal combustion and its hot flue gas, respectively. Additional results and discussions are available in the original report. 2.4.9 Coal Pyrolysis and Hydropyrolysis

GC/MS is an indispensable instrument for the analysis and characterization of fossil fuels, their reaction products, and reaction mechanisms. As the thermal decomposition of coal takes place during the initial stage of many coal-utilization processes, extensive efforts have been devoted to the GC/MS analysis of the products of coal pyrolysis under different conditions [21]. The experimental parameters normally included in pyrolysis are temperature, heating rate, pressure, particle size, and coal type. Major products from coal pyrolysis contain H2, H2O, CO, CO2, N2, H2S, CH4, C2H4, C2H6, C3H8, C6H6, C6H5CH3, C6H4(CH3)2, tar, and char. The analysis of product distribution has led to species-based kinetic models [21, 35] which, in turn, have offered insights into the characteristics of the macromolecular structure of coal. Chen et al. [36] identified pyrolysis products with molecular weight up to 200 atomic mass units (amu). The thermal treatment of coal in hydrogen at high pressure, termed hydropyrolysis, attracted much attention during the energy crisis of the 1970s, not only because it produces more volatiles than pyrolysis in an inert gas, but also that the technology used to separate pollutants in the gas phase was more accessible than that used for the solid phase. When both Graff et al. [37] and Dobner et al. [38] investigated the product distribution of coal hydropyrolysis, their analysis of volatile species demonstrated the correlation between the yields of coal pyrolysis and hydropyrolysis and the properties of various coals [39, 40]. For example, the organic oxygen and aliphatic hydrogen contents in coal were found to govern the volatile yields. Moreover, the reactivity was much better correlated with the petrographic composition than with the rank of coal. Exinite, a minor maceral constituent in coal, appeared to offer synergistic effects on the reactivity of other macerals in coal.

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2.4.10 Soot Formation in Combustion

Soot consists of carbon particles formed in the gas phase of a combustion process, due to the incomplete oxidation of hydrocarbons. Soot formation in hydrocarbon
flames occurs within a very short time period; soot particles of 500 A will be formed in 1 to 10 ms. In the past, PAHs (see Chapter ) have often been considered as important intermediates in particle growth. These species, which are found in all sooting, hydrocarbon flames, have structures similar to soot’s graphic morphology, and possess C : H ratios between those of most starting fuels (5). Preparticle chemistry and particle growth follow a reaction network that involves acetylene, C3H3 radicals, free radicals of PAH, and monatomic and diatomic hydrogen. The PAHs in soot are known mutagens, and probable human carcinogens. Mass spectrometry has been used extensively for probing soot formation mechanisms and kinetics in various flames, by directly quantifying the reaction intermediates and products. For instance, Westmoreland et al. [41] investigated benzeneformation mechanisms in a C2H2/O2/Ar flat flame by using molecular-beam mass spectrometry, and concluded that benzene was formed via a chemically activated addition and isomerization. Boyle and Pfefferle [42] and Pfefferle et al. [43] each investigated PAH formation during ethylacetylene and allene (C3H4) pyrolysis, by using vacuum ultraviolet (VUV) photoionization time-of-flight mass spectrometry. Single-photon VUV ionization with energies just above the ionization potential allows the nondestructive analysis of free-radicals in the reacting system. Molecular-beam mass spectrometry has been widely adopted in the analysis of stable species and free radicals in the early stages of soot formation, prior to the formation of particles. This technique has generated valuable mechanistic information of soot formation and growth. For instance, Bittner et al. [44] identified the stable and intermediate species up to 202 amu in flat, low-pressure flames of benzene/Ar, and discovered CO, C6H6O and C5H6 to be the major species in the flame; acetylene was not significant in the flame. Numerous hydrocarbon species have been observed that exhibit concentration maxima indicative of intermediates in the overall reaction scheme. To discern whether this type of progression or sequential growth might lead to soot in sooting flames, Howard and Bittner [45] analyzed species larger than 200 amu. This was achieved by shutting off the DC voltage on the quadrupole, thus transmitting all and only ions with a m/z ratio greater than a specified value. Indeed, the maxima concentrations were observed for species up to 750 amu. The growth rates of these species in different hydrocarbon flames were also investigated. The results of these studies led subsequently to a comprehensive review [46]. 2.4.11 Desorption of Surface Oxides up to 1100
C

The desorption of surface oxides from a char surface has been considered to be the rate-controlling step of carbon gasification; hence, the distribution of surface oxides of different strengths has long been a subject of investigation. In the past, a variety of desorption techniques has been adopted to characterize the abundance and strength

2.4 Recent Applications of GC/MS in Combustion and Pyrolysis Research

of surface oxides, with mass spectrometry having been used extensively to analyze the desorption products. Indeed, when combined with isotope-labeling techniques, mass spectrometry represents a powerful method for elucidating oxygen shuttling on the char surface. When desorption was conducted at up to 1100
C, Lizzio [47], Lizzio et al. [48], and Radovic et al. [49] each discovered surface oxides of two major different strengths: the surface area of the char covered by the labile complexes [C(O)] was termed the reactive surface area (RSA), while the surface area covered by both the labile [C(O)] and stable complexes [C–O] was termed the active surface area (ASA). Desorption techniques, including transient kinetics (TK) and temperature-programmed desorption (TPD), were subsequently developed to quantify the surface areas covered by labile and stable oxides. Notably, TK was designed for measuring the labile oxides, or the RSA. Following the partial gasification of char to a certain conversion level at temperatures up to 1153 K, the flow of reactive gas (either O2 or CO2) was switched to an inert gas (such as N2), and the desorption of surface oxides as CO monitored. The integrated area under the CO concentration versus time curve was used to calculate the RSA, by assuming a value of 0.08 nm2 for each oxygen atom. Interestingly, Lizzio et al. [48] found that the RSA determined by TK was in remarkably good accord with the difference of ASA and stable C–O determined with the two TPD procedures. It was also shown experimentally that the surface area occupied by the labile oxides, or ASA, was a better normalization parameter of the oxidation rates of chars derived from lignite and bituminous coal during CO2-gasification [48]. These authors also reported that lignite char had a higher RSA than bituminous coal char – an observation which explained the higher reactivity of lignite char in both oxidation and NO reduction. As coal-derived chars contain heterogeneous surfaces, the two-site approach in modeling the surface oxides is bound to have its limitations. Calo and Hall [50] suggested that there were many surface oxides of continuous and varying strengths on the heterogeneous char surface, and determined the probability density functions of desorption activation energies by TPD and mass spectrometry. They also revealed the controlling phenomena through deconvolution of the TPD spectra, and the correlations between these results and char reactivities. 2.4.12 Temperature-Programmed Desorption of Young Chars up to 1650
C

Research into the correlation of reactivity with the characteristics of chars has traditionally been centered on old chars, or the “clean” chars that have been pyrolyzed with a long residence time, typically 1–3 h. Nevertheless, it was shown recently that the reactivity of coal-derived char decreased rapidly and substantially in the flame. In order to obtain the more representative reactivity of young chars in the flames, Chen et al. [51–53] recently applied TPD/MS to the chars produced from pyrolysis and combustion with a residence time in an order of seconds. For this, the TPD was conducted up to 1650
C. Young chars oxidized at 1000
C with less than 0.3 s residence time showed CO desorption peaks during TPD at three distinct temperatures: 730, 1280, and 1560
C.

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A comparison of the TPD profiles of oxidized chars with those from pyrolyzed chars and ashes suggested that early-stage char oxidation was profoundly influenced by oxygen from three sources: organics oxygen, mineral matters, and gas phase O2 [49]. The peaks at 730
C were mainly caused by an incomplete devolatilization due to a short oxidation time, while the peaks at 1280
C represented mainly the desorption of stable surface oxides and an incomplete devolatilization. The broad peaks between 1400 and 1650
C were attributed to the reactions of oxidants decomposed from minerals and carbon in the char or SiC tube. The extensive emissions of CO from lignite chars during TPD suggested that either O2 or minerals could promote oxygen transfer on the char surface, and subsequent carbon oxidation. Conflicting reports have been made concerning the existence of such “stable” surface oxides on coal-derived chars that desorb only above 1000
C. The TPD profiles reported by Chen et al. [52] supported the existence of stable surface oxides on young, coal-derived chars in flame conditions. The desorption of these stable surface oxides had much higher activation energies than those of surface oxides that desorbed below 1000
C, and which have been studied extensively over the past four decades. Therefore, it is most likely a rate-controlling step of char oxidation. Moreover, several known mechanistic conclusions that have been reported, such as CO scavenging of surface oxides, have been based on the assumption that all surface oxides desorb below 900
C, despite the fact that in their TPD/MS experiments, Pan and Yang [54] reported the existence of stable oxides on graphite that desorbed at 1500
C. In an attempt to isolate the effects of minerals, demineralized coals (DMC) were oxidized in O2 with a contact time of less than 1 s, and the amount and strength of stable surface oxides were characterized by TPD/MS up to 1650
C [53]. Young chars derived from both demineralized lignite and bituminous coal showed low and flat TPD profiles over a wide temperature range (see Figure 2.4) for the TPD profiles for chars derived from bituminous coal. The oxidized and pyrolyzed DMC chars had very similar TPD profiles. For the demineralized bituminous coal, the CO emissions from oxidized DMC char were slightly higher than those from pyrolyzed DMC char below 1100
C, but held remarkably similar TPD profiles above that temperature. This observation indicated that the peaks at 730
C could be mainly attributed to the incomplete devolatilization, and only a small fraction of them were contributed by the oxidants in the gas phase. The chars from demineralized bituminous coal exhibited no obvious valleys at about 900
C, which suggested that the presence of minerals in raw coals may activate carbon gasification and shift part of the devolatilization to lower temperatures. The flattening of the CO emissions at 1280
C was even more visible, and reflected the significant role of minerals in carbon gasification at flame temperature. These TPD/MS results suggested that minerals in coals catalyzed the early-stage carbon gasification in the following ways: .

.

Minerals are a controlling factor during not only lignite oxidation but also the oxidation of bituminous coal, although the latter takes place to a lesser extent. Minerals are a controlling factor of carbon gasification reactions during oxidation over a wide range of temperatures, from 600 to 1650
C.

2.4 Recent Applications of GC/MS in Combustion and Pyrolysis Research

Figure 2.4 TPD profiles of pyrolyzed and partially oxidized chars derived from demineralized bituminous coal (DMC) compared to those of derivatives of raw coal [53]. The concentrations are normalized to 1 mg carbon at the start of the TPD experiment.

These results were rather unexpected. It is known that minerals in lignite catalyze char oxidation, but it is not yet known that minerals in bituminous coal also catalyze char oxidation. 2.4.13 Isotope-Labeling Techniques

The ability of mass spectrometry to quantify species of different masses renders it a highly versatile and powerful instrument for revealing reaction pathways that involve elements from two different sources, when used in conjunction with isotopes. The applications of this technique in combustion are summarized in Table 2.2. Both, Miura and Nakagawa [55] and Crick et al. [56] have investigated the carbonoxidation mechanisms by using alternative 18 O2 and 16 O2 . This method allows the measurement of both the adsorption rate and the carbon gasification rate. The results showed that the part of the oxygen adsorbed below 500
C does not desorb below 900
C in inert gas; rather, these surface oxides react with gas-phase oxygen and form CO2. These findings suggested that the thermal stability of surface oxides in inert gas is much lower than that in a gas containing oxygen, and led to a reaction mechanism of carbon oxidation that included interactions between the surface oxides and gaseous oxygen. Zhuang et al. [57] conducted char oxidation by switching 18 O2 to 16 O2 and 16 O2 to He, followed by TK and TPD. The results also showed that oxygen in the gas phase accelerated the gasification of surface oxides, and that traditional TPD does not reflect the actual gasification rate; moreover, gas-phase oxygen activated

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4 mm i.d., 30 cm length, quartz fixed-bed

TK/MS

TK/MS

TK/TPD/MS

TK/TPD/MS

TPD/GC/MS

TPD/MS

TK/TPD/ GC/MS

MS

[55]

[56]

[57]

[58]

[59]

[60]

[61]

[62]

Silica tube

Fixed-bed

Fixed-bed

Quartz fixed-bed

TGA

Quartz fixed-bed, 10 mm i.d.

TGA, packed bed (pb)

Reactor

10 K min–1

18

927

500–600

10 K min–1 1273 K, 30 min 410
C, 30 min

CO2 þ Ca þ PF resin char 13

Organic matters and sediment carbonates

CO2 þ C18 O2 þ Ar þ K

20 K min–1 1223 K

13

300, 500

627

10 K min–1 1300 K, 30 min

18 O2 þ Ca þ graphite

1100

15 K min–1 1373 K

16

950

200–500

550–600

Temp. (
C)

O2 , Ar, O2 Spherocarb

18

1223 K, 30 min

NA

18 O2 , or 16 O2, He, coals, carbon black

O2 (or 18 O2 ) þ He phenol-formaldehyde (PF) resin char

NA

Heating rate

Mineral-free carbon black, 18 O2 , or 16 O2, He

Reactants

Selected publications on isotope-labeled reactants in combustion research.

Reference Method

Table 2.2

1–2 mg/NA

100 mg/ 0.15–0.3 mm

13 C=12 C ratio as a fingerprint of the natural carbon origin

Mechanism of K-catalyzed gasification of carbon with CO2

Catalytic mechanism of carbon gasification by CO2

Catalytic carbon gasification by Ca during oxidation by 18 O2

8  16  2 mm3/ NA NA

Correlation between surface oxides stability and reactivity with O2

Oxygen shuttling during desorption of surface oxides

18 O2 and 16 O2 pulse for adsorption and oxidation rates

Alternating (carbon þ 18 O2 ) and (carbon þ 16 O2 ) gasification for establishing mechanisms of oxygen shuttling

Objectives

40–60 mg/ 0.12 mm

200 mg/ 100–200 mesh

2–30 mg (pb)/ 74–149 mm

3–12 mg/NA

Sample/ particle sizes

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NO, TPD/ MS

GC/MS

[64]

15

NO isotope/MS

GC/MS

[66]

[67]

NA: not available.

15

[65]

N 18 O; MS

15

[63]

Batch reactor

Fixed-bed quartz 28 mm i.d., 1000 mm length

Step response exp, 15 N 18 O to NO in fixed-bed

Flow reactor

Quartz fixed-bed

1073 K, 1 h

NA

15 NH3 þ NO (or NH3 þ 15 NO) þ Ar þ Pt

3 K min–1

bit. coal 15 NO, CO, O2, Ar

N 18 O þ 5%O2 þ He þ PF resin char, or amorphous 13 C

15

200–250

800

950, 600

1100

NA

15

NO/coal/O2/CO2 (simulated reburn)

500, 900

15 NO þ 5% O2 þ Ar 10, 20 K min–1 lignite and sub500, 700, bituminous coals 900
C, 1 h

NA

15, 100 mg/0.5, 0.17 mm

200 mg/NA

27 mg/200– 270 mesh

NA

(NO þ NH3) reaction on Pt

Roles of char-N and gas NO in N2O formation in fluidizedbed coal combustion

NO reaction with nitrogen trapped on char

Conversion of fuel-N to NO in reburn zone

15 NO reduction by chars of a low-rank coal

2.4 Recent Applications of GC/MS in Combustion and Pyrolysis Research

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more stable surface oxides on the char surface. Taken together, these observations pointed to the following general reaction: Cð18 OÞ þ 16 O2 ! Cð16 OÞ þ C18 O; C16 O 18 O

ð2:1Þ

Haynes and Newbury [58] confirmed these results experimentally, and suggested that the desorption of surface oxides had a probabilistically distributed activation energy, which made possible an estimation of the rate constants of the above reaction between surface oxides and gas-phase oxygen. Their model suggested that the contribution of the above reaction to the overall rate of gasification of carbon ranged from 45% at 873 K to 4% at 1073 K. Thus, its contribution would be diminished in the actual flame. It should be mentioned that none of these studies took into account the stable surface oxides that desorb only above 1000
C, as observed by Chen et al. [52, 53] and shown in Figure 2.4. The combined use of isotope-labeled compounds and mass spectrometry has also been applied to the studies of catalysis mechanisms during carbon oxidation. Kyotani et al. [59] investigated the calcium-catalyzed graphite oxidation by 18 O2. Their experiments involved three steps: oxidation with MS analysis; TPD/MS; and a secondary ion MS (SIMS) for the surface analysis. The sample was transported from the oxidation and TPD reactor to a vacuum chamber for bombardment by an Ar þ primary ion gun; this was carried out by using a moving rod, such that the sample was not exposed to the air. The results showed that CaO could serve as an oxygen shuttling agent, and that a carbon atom was gasified after it had acquired two oxygen atoms sequentially. Cazorla-Amoros et al. [60] investigated the calciumcatalyzed oxidation of a carbon sample by 13 CO2. The sample was a phenolformaldehyde (PF) resin oxidized by HNO3, and the 13 CO2 oxidized sample was then characterized using TPD/MS. The study results showed that two types of CO were produced after CO2 had attacked the CaO–C interface: (i) dissociation of CO2 from the decomposition of CaCO3; and (ii) desorption of the surface oxide on carbon. When Kapteijn et al. [61] conducted transient kinetics studies of uncatalyzed and potassium-catalyzed gasification of peat char by labeled CO2, their data suggested that, in both cases, there were at least two types of surface oxide – one which decayed in seconds, and one which decayed in a minute. Different sources of carbon, such as coal, petroleum, plants, and atmospheric CO2, have slightly differing natural abundances of 13 C. Bartle et al. [63] used the 13 C=12 C ratio in the combustion gases determined by mass spectrometry, and successfully identified the contributions of the different carbon origins. 15 NO and 15 N 18 O have each been used in studies of NO reduction by carbon. IllanGomez et al. [63] oxidized low-rank coals by 15 NO/Ar, O2/Ar and 15 NO/O2/Ar in a temperature-programmed reaction with online mass spectrometry measurement, following the TPD/MS analysis of char. The study results demonstrated the catalytic activities of both K and Na. Subsequently, in an effort to study NO reduction in a single, simulated reburning stage, Burch et al. [64] used 15 NO to differentiate the two oxygen sources, namely NO from the primary stage, and nitrogen from the reburning fuel. The results suggested that the fuel nitrogen contribution to NO was almost

2.5 Outlook

negligible in the reburning stage. Chambrion et al. conducted a series of stepresponse experiments by switching NO to 15 N 18 O in their fixed-bed, and showed that a large amount of nitrogenous species become trapped on the carbon surfaces. Moreover, the N2 formation rate was correlated with NO concentration and the amount of surface nitrogen species. N2 was mainly formed by the first-order reaction between C(N) and NO. In his study of N2O formation mechanism during fluidized coal combustion, Miettinen [66] used 15 NO to differentiate between the nitrogen in coal and that in NO. Both, 15 N 14 NO and 15 N 15 NO were formed in the products, with their distribution depending on the feed concentration of 15 NO and the residence time. Otto et al. [67] investigated the (NO þ NH3) reaction on Pt (an undesirable side reaction in the oxidation of NH3 to nitric acid), and an important selective reaction for the removal of NO in the combustion flue gas. Their results revealed two generalized sets of reactions. In the first set, either 15 N 14 N or 15 N 14 NO is formed, while chemisorbed hydrogen, liberated thereby, is consumed in the second set of reactions to reduce 14 NO to 14 N2 O or 14 N2. 2.4.14 Mass Spectrometry in the Study of Fullerene

Rohlfing et al. [68] reported the presence of single fullerene molecules, C50, C60, and C70, in the mass spectra of the products from the laser-vaporization of graphite. Gerhardt et al. [69] reported the presence of C50 in low-pressure flames of certain hydrocarbons. Richter et al. [70] reported the presence of fullerenes up to C116 in the condensable material from a benzene/oxygen flame. The flame material was Soxhletextracted with toluene, and fractionated by means of a HPLC column coupled to a mass spectrometer via a heated nebulizer interface.

2.5 Outlook

Today, humankind is facing unprecedented challenges in terms of energy production/consumption and the environment. Uncertainties in both the supply and quality of crude oil have caused fluctuations in energy costs that have led to concerns of economic “meltdown.” Moreover, the US at present lacks any desirable energy infrastructures and consensus with regards to alternative energy options. Concerns relating to climate change have led to renewed interests in reducing the use of fossil fuels and developing technologies based on alternative energy resources and, as a consequence, biomass conversion – both thermal and biochemical – has emerged as an option under such circumstances. Alternative approaches for the utilization of fossil fuels, including oxy-fuel combustion, gasification, chemical looping and hydrogen production, each represent attractive routes for supplying energy needs whilst simultaneously reducing carbon emissions into the atmosphere. On the homeland security front, the development of advanced materials that are able to withstand blast while not posing any health threat has emerged as an important

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research area for the future. During the development of these technologies, the use of GC/MS in combustion research, in relation to energy and nanotechnological applications, is expected to grow. With regards to methodology and instrumentation, speciated isotope dilution mass spectrometry (SIDMS) via GC/MS may in the future play a greater role in determining combustion pathways and associated molecular transitions, despite its use being limited because of the great expense associated with the preparation of stable isotope molecular tracers. Nonetheless, as with other analytical instrumentation, the recent trend has been towards a better resolution, a lower limit of detection, an increased throughput, miniaturization, and more defensible results. McMaster [20] has identified several recent innovations and future trends in GC/MS, including: (i) the use of microfluidic control valves for miniaturization and the rapid changing of columns and separation conditions; (ii) resistance column heating to reduce the overall size of the system, with the ultimate goal of field portability; (iii) new monolith columns in which the internal porous media, unlike packed columns, is prepared in situ; and (iv) ultra-small-diameter micro-wall-coated open tubular (WCOT) columns which provide high separation efficiencies. Recent commercial instrumental developments have included: .

.

.

The DFS, a high-resolution double-focusing magnetic sector GC/MS introduced by the Thermo Electron Corporation. The QP2010 Plus, a GC/MS system with expanded mass range and increased sensitivity, manufactured by the Shimadzu Corporation. A GC/MS system using a Fourier transform mass spectrometer developed by Varian Inc.

The features and details of these products can be found at each of these companys’ websites.

2.6 Summary

Today, GC/MS forms an integral part of combustion and pyrolysis research, allowing for the qualitative, and often quantitative, determination of combustion and pyrolysis products in the sub-nanogram range, with minimal sample preparation. A wide variety of applications have demonstrated the capability of GC/MS for the measurement of trace organic species from the combustion of fuels and biomass, and use of the technique in those areas will undoubtedly increase. As always, however, steps must be taken to assure the accuracy of analytical results, and Py-GC/MC is no exception, with matrix effects in particular needing to be monitored via the use of internal standards or other means. Likewise, analyst training and experience can be critical in order to produce reliable and meaningful results. Despite these minor failings, GC/MS will continue to be the primary analytical method used to scrutinize samples that contain complex mixtures of organic compounds and which often are key to understanding combustion and related environmental processes.

References

Acknowledgments

Wei-Yin Chen acknowledges the financial support of the National Science Foundation under grant CTS-0122504.

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3 Combustion Characteristics of Fossil Fuels by Thermal Analysis Methods Mustafa Versan Kok In recent years the application of thermal analysis techniques to study the combustion behavior and kinetics of fossil fuels has gained a wide acceptance among research workers, and this is of exceptional significance both for industry and for the economy. To date, many investigations have been conducted to study the combustion processes that take place in fossil fuels, using thermal analysis techniques. The majority of the state-of-art conversion technologies for processing coals, oil shales, and oil sands utilize the application of heating one form or the other. Thus, in the case of coals and oil shales, pyrolysis and combustion are the primary routes for the conversion of the energy-rich organic constituents to gases and liquids. In the case of oil sands, heat is applied to reduce the viscosity of the indigenous bitumen and to permit its subsequent extraction [1].

3.1 DSC, TG/DTG and DTA Studies on Coal Samples

Coal contains mineral components that are present in varying amounts and which, in general, are intimately mixed with combustible organic material. During the pyrolysis of coal, its mineral matter can contribute thermal effects which are worthy of investigation. The behavior of coal minerals during combustion and gasification is governed by several factors, including the chemical composition, the initial distribution of minerals within the fuel particles, the degree of mixing of minerals within the fuel particles, and the degree of mixing of the different constituents that may occur as the reaction proceeds. Historically, differential thermal analysis (DTA) was the first thermoanalytical tool to be used in the study of coal samples. In fact, a large majority of studies on the thermal analysis of coal samples was directed towards the correlation between thermal behavior and rank, or towards the characterization of various stages in the carbonization process.

Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright Ó 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

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Figure 3.1 Thermogravimetry/differential thermogravimetry curves of a coal sample.

In theory, the combustion of a coal begins whenever it comes into contact with oxygen, with the combination of fuel, oxygen availability and temperature controlling the nature of the reaction. In the thermogravimetry (TG)/differential thermogravimetry (DTG) analysis of coal sample, three reaction regions have been observed at different temperature intervals: the first region was due to the evaporation of moisture in the sample; the second region to the release of volatile matter and the burning of carbon (this is termed the primary reaction region), and the third region to the decomposition of mineral matter in the coal. The main weight loss occurs in the second region, which includes combustion of the carbonaceous part of the sample (Figure 3.1). Ratcliffe and Pap [2] have investigated the reactivity of lignite and different ranks of coal samples. In all of the coal samples studied, the reaction occurred in two distinct stages: (i) a rapid initial stage, controlled primarily by the devolatilization rate of the coal; and (ii) a second stage which limited the overall rate and was controlled by the surface properties of the coal. Subsequently, Gold [3] demonstrated the occurrence of exothermic processes associated with the production of volatile matter in or near the plastic region of the coal samples studied (using TG/DTG). In this case, it was observed that the temperature and magnitude of the exothermic peak was strongly affected by the heating rate, sample mass, and particle size. Cumming [4] later developed a method for describing the reactivity or combustibility of solid fuels, such as lignite, bituminous coals and petroleum coke, in terms of a weighted mean apparent activation energy; this was derived from simultaneous TG/DTG readings on a 20 mg sample heated at a constant rate in a flowing air atmosphere. Cumming proposed that the mean activation energy method be the established technique, which involves recording the overall temperatures on the burning profile curve. Smith and Neavel [5] carried out coal combustion experiments in the temperature range of 25 to 900
C, using air at atmospheric pressure in a derivative thermogravimetric analysis (TGA) system (TG/DTG). In this way, a total of 66 coals that were

3.1 DSC, TG/DTG and DTA Studies on Coal Samples

high in vitrinite and low in inorganic were examined as part of a coal characterization program. When the rate data were fitted to an Arrhenius equation, the plots showed four distinct regions of combustion. The calculated apparent activation energies were of the correct orders of magnitude to describe combustion regions corresponding to both chemical-reaction-controlled and diffusion-controlled processes. Smith et al. [6] investigated the burning process of different coal samples (with TG/DTG), from lignite to black coal, and found that the burning temperature for half of these coal types had a linear dependence on their concentration. Seragaldin and Pan [7] later developed a linear relationship between activation energy and the heat of reaction using TG/DTG. When the effects of alkali metal salts on the decomposition of coal under three different atmospheres (nitrogen, CO2, and air) were also investigated, the effect of the catalysts on coal conversion and CH4, CO2 and CO emissions was related to observed changes in the activation energy. Morgan and Robertson [8] determined coal-burning profiles by TGA (TG/DTG), and claimed that the kinetic parameters from Arrhenius plots of the profiles could not readily be related to any specific stage of combustion. However, some features of the profiles were clearly related to the coal properties, and a correlation was seen to exist between the unburned carbon loss (as predicted from high-temperature oxidation rates) and a characteristic temperature of the TG profile. This suggested that the burning profiles could provide a valuable, rapid laboratory-based method for ranking coals in terms of their burnout performance. Patel et al. [9] measured the rate of combustion of lignite char using TG/DTG over a range of oxygen concentrations (5–20%), and at temperatures between 325 and 650
C. In this case, the activation energy in the chemical rate-controlled zone was 120 kJ mol1, and the transition to film diffusion control occurred at 430
C. The Arrhenius plots indicated no region of pore diffusion control. Janikowski et al. [10] analyzed 10 different coals (four lignite, four sub-bituminous and two bituminous) in argon and hydrogen atmospheres, using thermogravimetry (TG/DTG). Upon heating the coals in an inert atmosphere up to 500
C, a weight loss of 30.8–43.7% occurred. Consequently, two distinct temperature regions of increased chemical reactivity were identified, with the first at 75–118
C and the second at 375–415
C. Crelling et al. [11] determined the combustion properties of separated single coal maceral fractions from a rank series of coals, and attempted to predict the combustion behavior of various whole coals on the basis of their maceral composition and rank (using DTA). The results of this study indicated that most of the reactivity and combustion profile parameters varied significantly with the coal rank. Morris [12] carried out pyrolysis runs (TG/DTG) in the temperature range from ambient to 900
C and with a particle size þ 38 to 2360 mm on a low-ash coal. Empirical correlations were established for the evaluation rates of hydrogen, CO and CH4 as a function of particle size and instantaneous temperature. The observations suggested that the tar deposition was rate-determining, while observations for the rate of evaluation suggested that this was governed by several complex reactions, of which methanation and secondary cracking of tar were possibilities. Kok et al. [13] studied the effect of particle size on the combustion properties of coal sample. In this case, non-isothermal thermogravimetry (TG/DTG) experiments were carried out for 12 different size fractions on the coal sample. The TG/DTG experiments were

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performed from ambient to 900
C in an air atmosphere, and the data analyzed using an Arrhenius-type reaction model, assuming a first-order reaction. The kinetic parameters of the samples were determined and the results discussed. When Huang et al. [14] investigated a wide range of coal ranks from lignite to anthracite, using TGA (TG/DTG), the derivative peak maximum for volatile matter evolution showed a strong correlation with vitrinite reflectance, thus providing a convenient measure of the degree of coalification (coal rank), without any need for equipment of and timeconsuming petrographic analysis. The value of Tmax, as determined using the rock evaluation method, also showed a positive correlation with vitrinite reflectance. TGA also reproduced the components of the proximate analysis of coal. Pranda et al. [15] performed combustion experiments in air using TG/DTA analysis, which served for ignition temperature and kinetics data determination. In this case, fly-ash carbon was treated with carbonates and hydroxides, and the ignition temperature-dependence on alkali metal salt concentration investigated. The results showed that the ignition temperature decreased for treated samples, and that the activation energy of impregnated samples was decreased. Kok [16] studied the effect of particle size on the oxidation mechanisms of lignites by performing non-isothermal thermogravimetry (TG/DTG) experiments on 12 different size fractions. The data obtained were converted into dimensionless size versus dimensionless time to show the progress of oxidation mechanisms of lignites. As a consequence, the lignites were seen to show linear behavior at elevated temperatures, thereby justifying the assumption that the chemical reaction is the controlling step. Benfell et al. [17] used thermogravimetry (TG/DTG) to characterize the effects of rank and maceral variations of coal combustion behavior. Here, the coals showed an increase in char burnout temperature with rank for both dull, inertinite-rich and bright, vitrinite-rich coals. Moreover, the maximum rates of combustion observed for dull coals were less than for their bright counterparts, with the difference between the two varying with rank. Ozbas et al. [18] later reported the results of a study investigating the combustion characteristics of lignite, before and after the cleaning process. For this, non-isothermal thermogravimetry (TG/DTG) experiments were carried out for four different size fractions, whereupon the TG/DTG curves revealed three reaction regions which related to: (i) the evaporation of moisture in the coal; (ii) the primary reaction region; and (iii) the decomposition of mineral matter in the lignite. Iordanidis et al. [19] subsequently carried out thermogravimetry (TG/DTA) experiments with seven lignite samples chosen to represent the vertical distribution of the lignite beds in the entire deposit. The burning profiles of the samples studied, combined with proximate analysis and calorimetry results, contributed to a clearer identification of the lignite structure and a better understanding of the coalification process. Seven thermal effects were distinguished, and a good correlation between the results of proximate and calorimetry analyses and the DTA and TG data was noted. Biswas et al. [20] studied the combustion behavior of two coals of the same rank but with a wide variation in mineral matter content by using TG. In this case, the burn-out temperature and peak temperature each showed a linearly decreasing trend with the increasing proportion of high-ash coal. It was noted that a higher TG reactivity might arise from the combined effect of mineral matter and the nature and distribution of

3.2 DSC, TG/DTG and DTA Studies on Crude Oil Samples

the maceral, particularly those of the inertinite group. Kaljuvee et al. [21] utilized a coupled TG-Fourier transform infrared (FT-IR) technique to identify the gaseous compounds evolved in the thermal treatment of six coal samples from different deposits. These experiments were carried out under dynamic heating conditions up to 900
C, at heating rates of 5, 10, or 50 K min1, in a stream of dry air. The emission of CO2, H2O, CO, SO2, COS, methane, methanol, formic acid, formaldehyde, acetaldehyde, and chlorobenzene was clearly identified in the FT-IR spectra of the samples studied. When Sun et al. [22] studied the pyrolysis of coal maceral using TG, the volatile matter evolved in the primary and secondary devolatilizations and kinetics were studied. Notably, the percentage of volatile matter evolved during the primary and secondary devolatilization suggested that the inertinite had a higher thermal stability. Yet, although the heating rate may affect the percentage of volatile matter evolved during primary and secondary devolatilization, the order of volatile matter in all the temperature range was the same. Haykırı et al. [23] investigated the combustion characteristics of coking, semi-coking, and noncoking bituminous coal samples by applying DTA and DTG techniques. The thermal data from both techniques showed some differences, depending on the proximate analyses of the samples, with the noncombustible components of the volatile matter leading to important changes in thermal behavior. When the data front methods were evaluated jointly, some thermal properties were interpreted by considering these methods as a complementary combination.

3.2 DSC, TG/DTG and DTA Studies on Crude Oil Samples

Differential thermal analysis was the first thermoanalytical tool to be used in crude oil characterization, with many of the studies with crude oils being directed towards identifying a correlation between the thermal behavior of the samples and kinetic studies. The effect of different metallic additives on the combustion properties of crude oils has also been investigated. In combustion with air, a series of reactions was observed during the oxidation of crude oil in porous media by air injection; these were termed low-temperature oxidation (LTO), fuel deposition (FD), and high-temperature oxidation (HTO). In thermogravimetric experiments (TG/DTG), a reaction at up to 380
Cwas the first to be termed LTO, with the reaction rate being proportional to the specific surface area of the matrix. In the second reaction region – termed FD – which takes place between 380–500
C, the crude oil iscokedand deposited on the solid matrixasfuel. The initial oilsaturation,the specific surface area of the rock, as well as its permeability and porosity, represent the main properties affecting fuel deposition. The final reaction – termed HTO – takes place at 500–600
C (Figure 3.2), and makes the greatest contribution to the exothermic heat of reaction when crude oil/limestone is heated in an oxidizing environment. Although the individual activation energies for each reaction region can be attributed to the different reaction mechanisms, they do not provide any indication of the contribution of each region to the overall reactivity of the crude oils.

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Figure 3.2 Thermogravimetry/differential thermogravimetry curves of a crude oil sample.

Burger and Sahuquet [24] used DTA not only to illustrate the catalytic effect of some metallic derivatives, but also to investigate how the properties of both the oil and porous media influence crude oil combustion. Three successive oxidation regions were observed in the DTA curves, namely low-temperature partial oxidation, the combustion of crude oil fractions and, finally, coke combustion. When Bae [25] investigated the thermo-oxidative behavior and fuel-forming properties of various crude oils using thermogravimetry (TG/DTG), the results indicated that oils could be classified according to their oxidation characteristics. However, no complete correlation could be established between the viscosity, composition or density of the crude oil and its thermo-oxidative characteristics. Subsequently, Drici and Vossoughi [26] applied differential scanning calorimetry (DSC) and thermogravimetry (TG/DTG) to crude oil combustion in the presence and absence of metal oxides. In this case, vanadium, nickel and ferric oxides each behaved in similar fashion by enhancing the endothermic reactions. However, in the presence of a large surface area (e.g., as on silica), the surface reactions were predominant and unaffected by the small amount of metal oxide present. Vossoughi and Bartlett [27] have developed a kinetic model of the in situ combustion process from data obtained from thermogravimetry (TG/ DTG) and DSC. For this, the kinetic model was used to predict the rates of fuel deposition and combustion in a combustion tube, with a good agreement being obtained between the two parameters. Vossoughi [28] has since used thermogravimetry (TG/DTG) and DSC techniques to study the effect of clay and surface area on the combustion of selected oil samples. The results showed that there was a significant reduction in the activation energy of the combustion reaction, regardless of the chemical composition of any additives. Moreover, the LTO of the oil – and also most likely the coke deposition – were strongly affected by the specific surface area of the solid matrix. Yoshiki and Philips [29] examined the thermo-oxidative and thermal cracking reactions of Athabasca bitumen, both qualitatively and quantitatively, using DTA. Here, the reaction kinetics of the low-temperature oxidation and high-temperature cracking were determined, in addition to the effects of the

3.2 DSC, TG/DTG and DTA Studies on Crude Oil Samples

atmosphere, pressure, heating rate and support material on the thermal reactions of bitumen. Notably, low linear heating rates (2.8
C min1) were found to favor LTO addition and fission reactions. When Verkocy and Kamal [30] performed thermogravimetric (TG/DTG) and pressurized differential scanning calorimetry (PDSC) investigations on Saskatchewan heavy oils collected from wells under primary, steam flood and fire-flood production, and on cores, the estimated kinetic and thermochemical data for thermolysis, LTO and combustion reaction rates were seen to depend nonlinearly on the heating rate. Kamal and Verkocy [31] used thermogravimetry (TG/DTG) and DSC on two Lloydminster-region, heavy-oil cores, and extracted both oils and mineral matter. In this case, the TG/DTG and DSC thermograms of the two Lloydminster-region cores, and of the extracted oils obtained in helium and air atmospheres, demonstrated at least three groups of chemical reactions occurring in three temperature regimes. The reactions in zone 1 were attributed to evaporation, distillation, thermolysis, and LTO; those in zone 2 to distillation and thermal alteration of minerals, LTO, and combustion; and those in zones 3 and/or 4 to pyrolysis, coking, polymerization, mineral matter decomposition and combustion. Ranjar and Pusch [32] later studied the effect of the oil composition (characterized on the basis of light hydrocarbon, resin and asphaltene contents) on the pyrolysis kinetics of the oil and the combustion kinetics of the fuel by using thermogravimetry (TG/DTG) and DSC. Their results showed that not only the colloidal composition of oil but also the transferability and heat transfer characteristics of the pyrolysis medium had a pronounced influence on fuel formation and composition. When Ranjbar [33] investigated the influence of the reservoir rock composition on the pyrolysis and combustion behavior of crude oils in porous media, they conducted pyrolysis and combustion tests to determine how clays might affect the amount of fuel and its reactivity. From the results obtained, Ranjbar concluded that any clay minerals present in the matrix would enhance fuel deposition during the pyrolysis process, and also catalyze the oxidation of the fuel. Subsequently, Kok [34] characterized the pyrolysis and combustion properties of two heavy crude oils. On combustion in air, three different reaction regions were identified, known as LTO, FD, and HTO. The DSC-TG/DTG curves were also used to determine the heat values and reaction parameters of crude oil. Kinetic data were obtained from the HTO region of the DSC and DTG curves, while higher activation energy values were found as the API (American Petroleum Institute) gravity of the crude oil decreased. When Lukyaa et al. [35] used PDSC to study the effects of sand particle size, pressure and oxygen partial pressure on heat evolution during the combustion of North Sea crude oil–sand mixtures, they showed that a decreased particle size and an increased pressure raised the extent of LTO and thus favored fuel lay-down. Kok et al. [36] also used PDSC to obtain information on the combustion characteristics of crude oils and their mixtures in two chemically different matrix materials, namely sand and limestone. With a crude oil content of 10 wt% within the matrix, the PDSC curve showed two distinct transitional stages, namely the combustion of liquid hydrocarbons and the combustion of coke. As the kinetics phase of this study was concerned with only one peak (namely coke combustion), two different kinetic models were used to analyze the data acquired, and the results obtained were

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discussed. Goncalves et al. [37] investigated the thermal behavior of asphaltenes from crude oil using thermal analysis techniques (TG-DTA/GC/MS). This approach involved kinetic studies of the thermal decomposition of asphaltenes under controlled conditions by using thermogravimetry (TG/DTG), as well as the characterization of volatile fractions recovered by using thermogravimetry and DTA coupled with gas chromatography/mass spectrometry (GC/MS). The coke formed was also studied after it had been decomposed into smaller molecules by selective oxidation. When Kok and Iscan [38] applied DSC to a crude oil combustion in the presence and absence of metal chlorides they showed that, in the presence of a lower ratio of metallic additive, the surface reactions were predominant and the catalyst had only a minimal effect on the reactions. The three different reaction regions were identified as LTO, FD and HTO in all of the samples studied. Kok and Acar [39] also investigated the thermal characterization and kinetics of a light crude oil in the presence of limestone matrix. For this, TG/DTG was used to characterize the crude oil in the temperature range of 20 to 900
C, at a heating rate of 10
C min1, and with an air flow rate of 20 ml min1. On combustion in air three distinct reaction regions were identified as LTO, FD and HTO; subsequently, when five different kinetic methods were used to analyze the TG/DTG data (the aim being to identify the reaction parameters of activation energy and Arrhenius constant), the HTO activation energy of light crude oil varied between 54.1 and 86.1 kJ mol1, while the LTO activation energy varied between 6.9 and 8.9 kJ mol1. Li et al. [40] examined the oxidation behavior of three crude oils (light oil, medium oil, and Athabasca bitumen) by using PDSC at pressures from ranging 110 to 6894 kPa. When pure hydrocarbon aromatics and paraffin samples were selected for study, the increased pressure caused a rise in the oxidation reaction rate, and the release of much more heat. The PDSC heat flow curves also showed clearly the effect of the samples’ chemical structure on their oxidation behavior. Goncalves et al. [41] applied thermogravimetry to evaluate the heavy distillation residues of different Brazilian crude oils. Despite being able to study the thermal characteristics of these samples in only one way, linear correlations could be identified among the results obtained from the TG curves and by the patterned methodologies. This anticipated the formation of volatile and carbonaceous materials (coke) during the thermal cracking. Although these correlations were observed only for a short period of time, they provided comparisons among the petroleum fractions.

3.3 DSC, TG/DTG and DTA Studies on Oil Shale Samples

Oil shales are broadly defined as petroleum source rocks that contain a sufficiently high content of organic matter so as to make their practical use feasible. Like coal, the world’s reserves of oil shales are vast, being many times larger than those recognized for crude oil. More recently, the use of oil shale has attracted renewed attention as a source of transport fuels and chemical feed stocks, due to long-term uncertainties over crude oil supplies. Indeed, the past twenty years has seen the development of a

3.3 DSC, TG/DTG and DTA Studies on Oil Shale Samples

Figure 3.3 Thermogravimetry/differential thermogravimetry curves of an oil shale sample.

number of innovative processes such as fluidized bed pyrolysis, combustion and hydroretorting, each of which has enabled considerably higher oil yields to be obtained than by any of the previously developed classic retorting procedures. The most widespread use of thermal analysis methods has, most likely, been applied to studies of the decomposition kinetics of the oil shale, kerogen. Indeed, the combustion of indigenous organic matter has been shown to be a complex, multistage process, as the thermal behavior of oil shale in dynamic air atmospheres can exhibit characteristics of both the inorganic (mineral) and organic (kerogen þ bitumen) components. Whilst the low-temperature portion of the thermal curves may represent a thermal decomposition identical to that observed in an inert atmosphere, at higher temperatures the oxidative characteristics of the organic component generally predominate. Many of the investigations conducted on the thermal analysis of oil shale samples have been directed towards not only their characterization but also their pyrolysis–combustion kinetics (Figure 3.3). Kok and Pamir [42] have used DSC to determine the combustion kinetics of oil shale samples using the ASTM (American Society for Teaching and Materials) method. The higher heating rates were seen to result in higher reaction temperatures and heats of reaction, while the distinguishing peaks were shifted to higher temperatures with an increase in the heating rate. The activation energy values were found to lie in the range of 131.8 to 185.3 kJ mol1. Lisboa and Watkinson [43] used a standard thermogravimetric apparatus to study the chemical kinetics of oil shale pyrolysis and combustion, such as a controlled temperature and the simultaneous weighing of samples. These thermogravimetric analyses must be carried out under conditions such that the observed reaction rate is identical to the rate of the chemical kinetics. Consequently, Lisboa and Watkinson investigated the effects of key parameters which might affect this identity, which included the flow rate, purity and nature of the gas, the particle sizes, and the sample sizes. Later, Jaber and Probert [44] studied two oil shale samples nonisothermally, using TGA, whereby their controlling parameters included the final temperature and the influence of

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particle size, as well as the heating rate employed during thermal degradation of the oil shale sample. An integral method was used in the analysis of weight loss data to determine the pyrolysis and gasification kinetics. Gasification and pyrolysis of the investigated shales complied with first-order kinetics, and the activation energy decreased slightly as the shale-particle size was reduced. Karabakan and Y€ ur€ um [45] investigated the effect of the mineral matrix of oil shales and air diffusion on the conversion of organic material in oxidation reactions. Based on the kinetic analysis, the overall reaction orders were shown to be pseudo first-order, and the magnitude of the activation energies of oxidation reactions at equal heating rates were changed. Subsequently, the rate of reaction was found to depend on the rate of transport of the gas into the zone of reaction by diffusion. The diffusion of oxygen into the organic matrix was also seen to be the main factor controlling the rate of oxidation reactions. In a follow-up study, Berkovich et al. [46] developed a novel technique for the thermal characterization of oil shale which involved a separation of the unique components of oil shale, the kerogen, and the clay minerals, by using chemical and physical techniques. For this, the heat capacity and enthalpy changes for the kerogen and clay minerals were measured using nonisothermal modulated DSC, from 25 to 500
C. Enthalpy data for the dehydration and pyrolysis of kerogen were also determined. Subsequently, Williams and Ahmad [47] pyrolyzed oil shale samples using TGA, in relation to heating rate and temperature, using nonisothermal and isothermal analysis, respectively. The main region of weight loss, which corresponded to the hydrocarbon oil and gas release, was between 200–620
C, whereas at higher temperatures any significant weight loss was attributed to carbonate decomposition. For all oil shale samples analyzed, increasing the heating rate caused the reaction to shift to a higher temperature. When the kinetic data were analyzed using the Arrhenius and Coats and Redfern methods, there appeared to be no clear relationship between the activation energy and the heating rate. When Torrente and Galan [48] studied the kinetics of thermal decomposition of oil shale using thermogravimetry (TG/DTG), the rate of thermal decomposition of oil shale could be suitably described by an overall first-order kinetics, and no mass and heat transfer resistance was observed for the different particle sizes studied. De girmenci and Durusoy [49] investigated the pyrolysis kinetics of (210 þ 149), (250 þ 210) and (420 þ 250) mm particle-size oil shales under nonisothermal conditions and an argon atmosphere, with the pyrolysis characteristics of the samples being analyzed using TG/DTG curves. When the differential thermogravimetric data were analyzed by a model which assumed first-order kinetics, the minimum activation energy was obtained as 0.6 kJ mol1 with 60 K min1 in (210 þ 149) mm. It appeared from these results that a higher heating rate would have a limiting effect on the behavior of the pyrolysis reaction. Han et al. [50] conducted both combustion and pyrolysis experiments on Huadian oil shale, again using TGA, in order to study the effects of various factors on its combustion. The particle size was seen to have very little effect on the combustion process; typically, the starting temperature of combustion mass loss and the ignition temperature of the oil shale decreased as the oxygen concentration of the ambient gas increased. Notably, an increase in the heating rate could result in an ignition temperature, a burn-out temperature, and an increase in the

References

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3.4 Conclusions

A survey of the literature has revealed that thermal methods are finding increasing applications in the studies of fossil fuels, and that thermal analysis techniques have been applied very successfully to investigating the interaction of fossil fuels with nitrogen and other gases, such as air and oxygen. The use of these techniques has considerable significance in terms of determining changes in properties such as composition, decomposition characteristics, calorific effects, kinetics, and proximate analysis. The data acquired showed clearly that thermal analysis is a well-established technique used in the area of fossil fuel research. An examination of the available reports also showed that thermal methods are important from both theoretical and practical points of view.

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(1988) Combustion rates of lignite char by TGA. Fuel, 67, 165–169. Janikowski, S.K. and Stenberg, V.I. (1989) Thermal analysis of coals using differential scanning calorimetry and thermogravimetry. Fuel, 68, 95–99. Crelling, J.C., Hippo, E.J., Woerner, A., and West, D.P. (1992) Combustion characteristics of selected whole coals and macerals. Fuel, 71, 151–158. Morris, R.M. (1993) Effect of particle size and temperature on the evaluation rate of volatiles from coal. J. Anal. Appl. Pyrolysis, 27, 97–107. Kok, M.V., Ozbas, E., Hicyilmaz, C., and Karacan, O. (1997) Effect of particle size on the thermal and combustion properties of coal. Thermochim. Acta, 302, 125–130. Huang, H., Wang, S.J., Wang, K.Y., Klein, M.T., Calkins, W.H., and Davis, A. (1999) Thermogravimetric and Rock-Eval studies of coal properties and coal rank. Energy Fuels, 13, 396–400.

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Jordanian oil-shales. Appl. Energy, 63 (4), 269–286. Karabakan, A. and Yurum, Y. (2000) Effect of the mineral matrix in the reactions of shales. Fuel, 79 (7), 785–792. Berkovich, A.J., Levy, J.H., Schmidt, S.J., and Young, B.R. (2000) Heat capacities and enthalpies for some Australian oil shales from non-isothermal modulated DSC. Thermochim. Acta, 357, 41–45. Williams, P.T. and Ahmad, N. (2000) Investigation of oil-shale pyrolysis processing conditions using thermogravimetric analysis. Appl. Energy, 66 (2), 113–133. Torrento, M.C. and Galan, M.A. (2001) Kinetics of the thermal decomposition of oil shale from Puertollano. Fuel, 80 (3), 327–334. Degirmenci, L. and Durusoy, T. (2005) Effect of heating rate and particle size on the pyrolysis of Goynuk oil shale. Energy Sources, 27 (9), 787–794. Han, X.X., Jiang, X.M., and Cui, Z.G. (2006) Thermal analysis studies on combustion mechanism of oil shale. J. Therm. Anal. Calorim., 84 (3), 631–637.

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4 Gas Potentiometry: Oxygen-Based Redox Process Diagnostics in High-Temperature Environments Eyck Schotte, Bert Lemin, Heike Lorenz, and Helmut Rau 4.1 Introduction

The development of gas potentiometry as a method of analysis originated over fifty years ago. In this technique, solid electrolytes are used which, although incapable of conducting electrons, are able to conduct ions with which the gas being analyzed may interact [1]. Also pursued at an early stage, measurement of the oxygen partial pressure in a gas led to the emergence of gas potentiometric analysis with solid electrolyte oxygen probes, and this has since evolved into an established method of measuring oxygen concentration in gases [2, 3]. Today, millions of lambda oxygen sensors are used in motor vehicles and as exhaust gas probes in industrial furnaces to control and regulate combustion processes. Combustion processes are extremely complex, and can be fully described when the different parameters of an investigated system, such as the velocity, pressure, temperature, density and chemical composition, are known [4, 5]. Intensive research projects have concentrated on both theoretical modeling and improving the means of measurement in order to describe complex combustion processes [6–8]. Laser spectroscopic techniques (see Chapters 5, 6, and 8) have been developed over the past few decades, which allow the highly sensitive detection of single atoms and molecules in the zone of reaction, and the determination of the concentrations, temperature, and velocity of the reacting species [9]. Unfortunately, as this type of technology is very expensive it is applied exclusively to gaseous targets, and especially to gas flames. The application of oxygen probes with stabilized zirconia (ZrO2) as a solid electrolyte to directly analyze combustion processes is less familiar [10]. The concept is based on oxygen’s role as a main reaction component in conventional combustion. Measurement of the oxygen concentration provides information on the combustion process itself. The ability to make in situ measurements directly in the reaction zone of a combustion chamber is extremely advantageous. Unlike other well-known methods of exhaust gas analysis, in situ oxygen measurements can be taken in the

Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright Ó 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

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furnace combustion zone without any problems, because stabilized zirconia probes will only function correctly at high temperatures (>600  C). Relevant studies have revealed that high-resolution measurements of oxygen concentration may be taken in the reaction fronts of flames. The measurability of free molecular oxygen under oxidizing conditions, and bonded (“equilibrium”) oxygen under reducing conditions, facilitates the quantitative analysis of combustion processes [11, 12]. This basic knowledge led in turn to the development of methods of gas potentiometric analysis, which describe the progress of processes of thermochemical conversion of fuel gases (combustion, reforming) and solids (combustion, gasification) and facilitate the characterization of solid fuels, among others, by kinetic parameters of oxygen conversion (k, EA) [13, 14]. The aim of this chapter is to provide an overview of the diverse potential applications of gas potentiometry as a diagnostic method in combustion engineering. Gas potentiometry is employed both in engineering research to characterize oxidizing and reducing atmospheres and to analyze thermochemical processes, and also in industry to monitor and control combustion plant systems and components. Rather than provide an extensive literature review, an in-depth description is provided of established and novel applications, and of the emerging trends in the use of gas potentiometry for in situ diagnostics. The aim is to provide not only those working in applied research but also plant and process engineers in industry, with a series of stimulating ideas and practical approaches that will permit them to take advantage of innovative in situ gas potentiometry diagnostics for their own purposes and projects.

4.2 Theoretical Foundations of Gas Potentiometry

Gas potentiometric oxygen probes (GOPs) belong to the large class of electrochemical measuring cells that apply potentiometry as their measuring principle. Unlike related measuring methods such as amperometry, potentiometric measurements are taken at zero current. 4.2.1 Physico-Chemical Measuring Principle

The measuring principle of the GOP is to apply an oxide ion-conducting solid electrolyte so as to establish a galvanic oxygen concentration chain. The provided cell voltage depends only on the analytically captured ratio of O2 concentrations. Coating the opposing surfaces of the body of a ceramic solid electrolyte with a porous precious metal causes a galvanic oxygen concentration chain to form, with the oxygen-containing gas phases in contact on every side (Figure 4.1a). The galvanic chain’s two electrodes span the three-phase ranges: gas, precious metal, and solid

4.2 Theoretical Foundations of Gas Potentiometry

Figure 4.1 (a) Functional principle and (b) a schematic representation of a gas potentiometric oxygen probe three-phase reaction, in an oxidizing atmosphere.

electrolyte (SE). Since it is highly chemically and thermally stable, platinum is primarily used as the precious metal. When one gas phase consists of a reference gas with a constant O2 content (generally air), and the other of a measuring gas with an unknown O2 concentration, then the galvanic oxygen concentration chain can be described with the following cell symbol [15]: measuring gas ðp0 O2 Þ=Pt=Zr0;85 Ca0;15 O1;85 =Pt=reference gasðp00 O2 Þ:

Here, CaO-stabilized ZrO2 (15 mol% Ca) may be used as the solid electrolyte. According to M€obius [15], the decisive electrode reaction can be described by the overall equilibrium (Equation 4.1) (see also Figure 4.1b for a schematic representation): O2 ðgas phaseÞ þ 4e ðPtÞ K 2O2 ðsolid electrolyteÞ

ð4:1Þ

The level of electrochemical potentials adjusts as a function of O2 fugacity (O2 concentration) in the particular electrode. Designated as the equilibrium cell voltage Ueq, the difference of the oxygen concentration chain’s different electrochemical potentials yields the O2 concentration in the measuring gas over a temperature range of approximately 600 to 1600  C when the Nernst equation is followed [16]: Ueq ¼

R
T p0 O2 ln : 4
F p00 O2

ð4:2Þ

where R and F are the Universal gas and Faraday constants, respectively. Since gases with a high temperature behave like an ideal gas, the equation replaces the inherently effective oxygen fugacities by partial pressures p0 O2 and p00 O2 [17]. Studies conducted by Hartung [18, 19] have shown that GOPs function ideally only within a given temperature range (see above). The upper limit of the temperature range is determined by the electrolytes’ oxygen permeability, and the lower limit by its

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ion conductivity (electrode reversibility). For gases that contain oxidizable substances, primarily the catalytic activity of the electrode material at the electrolyte is crucial to the GOPs lower operating temperature. Pt, Pd, and Rh electrodes are catalytically active, whereas Au, Ag and “poisoned” (e.g., with Pb or S) platinum electrodes are catalytically inactive. The effects that deserve attention when working with GOPs are electrochemical side reactions such as corrosion, the build-up of a thermoelectromotive force by a temperature gradient over the solid electrolyte, and the electron conductivity of the ceramic and kinetic inhibitions when establishing thermodynamic and electrochemical equilibria in the gas. These accumulate to the so-called asymmetric voltage, which is largely quantifiable by measuring a sample gas identical to the reference gas as a function of temperature. Given the logarithmic relationship between the equilibrium cell voltage and concentration (Equation 4.2), the sensor’s sensitivity and accuracy of measurement is greatest for small O2 concentrations, and relatively low for larger concentrations. At an assumed accuracy of 0.1 mV and 1 K, an error of approximately 1% is specified for cell voltage, whereas it is approximately 10% for accuracies of 2 mV and 5 K [16]. Usually, GOPs are operated with an air reference electrode (O2 content of the air: 20.912 vol%). Then, by replacing R and F with the appropriate numbers, and with a known air pressure p and known operating temperature T, the Nernst equation is transformed into Equation 4.3:   0  p Ueq T
: ¼ 0:0336 þ 0:0496
lg O2 K p mV

ð4:3Þ

With a measured cell voltage, the oxygen content in the measuring gas can be determined using Equation 4.4: Ueq ½mVŠ=T½KŠ p0O2 0:0496 ¼ 10 p

0:0336

:

ð4:4Þ

According to Schmalzried [21], the effective range of a GOP extends from approximately 10 20 to 1 bar oxygen. The lower limit value of the O2 partial pressure as the absolute content in the gas atmosphere is generally equivocal in terms of its measurability (10 20 bar is equal to less than one molecule of oxygen per cm3) [23]. On the other hand, the chemical equilibria of oxide pairs, for example H2O/H2 and CO2/CO, have very low O2 partial pressures. If an equilibrium is established in the electrode, then at a sufficiently high forward and reverse reaction rate a mechanism different to that in Equation 4.1 will directly deliver enough oxygen ions for an electrochemical conversion – that is, without forming molecular oxygen [22]. Hence, the oxygen partial pressure is directly related to the dissociation pressure between the complementary gas components. This allows to determine their redox ratio in the surrounding gas [23–25]. For example, the electrode reactions for a CO/CO2 atmosphere can be described by the overall equilibrium: CO2 ðgas phaseÞ þ 2e ðPtÞK CO ðgas phaseÞ þ O2 ðsolid electrolyteÞ

ð4:5Þ

4.2 Theoretical Foundations of Gas Potentiometry

Figure 4.2 Schematic representation of a gas potentiometric oxygen probe three-phase reaction in a reducing atmosphere with (a) CO/CO2 and (b) H2/H2O mixtures.

Figure 4.2 illustrates the three-phase reactions in a reducing atmosphere for the examples of CO2/CO and H2O/H2 mixtures. As no free oxygen is present, Equation 4.2 cannot describe the equilibrium cell voltage generated by the GOP. However, other cell voltage equations can be derived from it, which describe the quantitative correlation between the cell voltage and the concentration of the respective fuel and exhaust gases [16]. A selection of such cell voltage equations is listed in Table 4.1. Consequently, when the equations analogous to the range of validity of the equilibria in the gas phase are applied correctly, the redox ratio can be directly determined from the measured cell voltage, Ueq. The redox ratio (also called the redox quotient) denotes the relationship of the relevant oxidized gas components to their reduced gas components. Furthermore, established input mass flows and plant parameters can be additionally balanced to calculate individual gas concentrations. Partial derivatives of the cell voltage equations facilitate a qualitative evaluation of the influence of temperature on the equilibrium cell voltage. These show that lower absolute values of Ueq are produced in reducing atmospheres when the temperature T increases (dUeq/dT < 0) and the redox ratio is constant. However, the opposite effect manifests itself in atmospheres with free, molecular oxygen (derivative of Equation 4.2); that is, the absolute Ueq values increase (dUeq/dT > 0). 4.2.2 Solid Electrolytes

Virtually pure oxygen ion conduction is the prerequisite to utilizing solid electrolytes in GOPs to determine O2 concentrations. Ions can only be conducted in solid bodies when they migrate through vacancies. Ion conductivity and mobility is determined by the concentration of lattice imperfections.

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Reaction equilibrium

H2O $ H2 þ 1/2O2 CO2 $ CO þ 1/2O2 CO þ H2O $ CO2 þ H2 C(s) þ H2O $ CO þ H2 CH4 þ H2O $ CO þ 3H2

H2O, H2

CO2, CO

H2O, CO2, H2, CO

H2O, CO2, H2, CO, C(s)

H2O, CO2, H2, CO, C(s), CH4

Cell voltage equations with corresponding gas atmosphere and reaction.

Measuring gas atmosphere

Table 4.1

¼

¼

¼

¼

¼

Ueq mV

Ueq mV

Ueq mV

Ueq mV

Ueq mV

    pH2 O 1290 þ 0:326 þ 0:0992
lg 0:0496
lg p
KT pH2     pCO2 1458 þ 0:481 þ 0:0992
lg 0:0496
lg p
KT pCO     pH2 O pCO2 0:0496
lg p
KT 1374 þ 0:403 þ 0:0496
lg pH2 pCO     pH2 O pCO 911:4 þ 0:1626 þ 0:0496
lg 0:0496
lg p
KT pH2 " ! # p5 pCO 1080:5 þ 0:1937 þ 0:0166
lg H2 O 3 0:0496
lg p KT pCH4 pH2

Cell voltage equation Ueq [mV]

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4.3 GOP Applications in Research and Industry

M€obius [23] has attached great importance to ion disorder and its temperature dependence. This disorder manifests itself in the same way as for doped semiconductors; hence, a lower-valence metal oxide (e.g., Y2O3, CaO) is incorporated into a quadrivalent base oxide (e.g., ZrO2), with the cations of differing valence dispersing statistically throughout the possible positions. In order to maintain electroneutrality, vacancies that also are distributed homogeneously among the anion positions are formed in the anion lattice (partial O2 lattice) as a function of the concentration and valence of the foreign cations (Y3 þ - or Ca2 þ -ions) [20]. While the vacancies are a necessary condition, they alone do not suffice for ion conductivity; rather, the requisite mobility must additionally be assured. In mixedphase oxides, such mobility is grounded in their lattice structure (fluorite lattice). In the concrete case of zirconium oxide (ZrO2), which occurs naturally as the monoclinic mineral baddeleyite, a phase transition to the tetragonal modification occurs above 1000  C, and to the cubic fluorite structure at 2300  C. By adding calcium oxide (CaO) and heating to 1600  C, the cubic lattice structure can be converted into a new phase that is stable in ceramic at room temperature. With a CaO content of between 15 and 28 mol%, CaO-stabilized zirconium oxide is the only phase that appears. This also applies to the mixed-phase oxide called the Nernst mass (85 mol% ZrO2 þ 15 mol% Y2O3) [20]. The initial tests of this mixed-phase oxide, which were conducted by Baur and Preis [26] back in 1937, demonstrated the ionic nature of its conductivity. A minimal gas solubility and permeability under measurement conditions are the other basic prerequisites for the utilization of solid electrolytes to determine O2 concentrations [17]. Ceramic processes and sintering at 1800  C are applied to produce gas-tight ceramic bodies shaped as plates and tubes [27]. According to the studies of M€obius and colleagues [17, 28, 29], and the group of Rau [16, 30–32], Y2O3-stabilized ZrO2 (YSZ) in particular, and also MgO-stabilized mixed-phase oxides to a limited extent, have truly proven themselves for use in gas potentiometric measuring cells. 4.2.3 Resume

To summarize, the high sensitivity of a GOP not only enables the measurement of free molecular oxygen under oxidizing conditions, but also of so-called equilibrium oxygen in reducing gas atmospheres. The rapid establishment of an equilibrium in a GOP is a fundamental prerequisite for in situ measurement applications.

4.3 GOP Applications in Research and Industry

During the past few decades, gas potentiometric oxygen solid electrolyte sensors have experienced widespread use in industry and, as lambda oxygen sensors and exhaust gas probes, have become the standard part of many systems. Typically, they are used

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in the emissions control systems of motor vehicles, or in the monitoring systems of power plants, primarily to characterize gases but notably to determine absolute oxygen contents. However, in many in situ applications the GOPs perform much more than simple determinations of oxygen concentrations. Rather, they support the analysis of conversion processes, as the basis for potential control and also in the applied characterization of fuels. Hence, the design of the GOPs merit closer examination. 4.3.1 Materials, Design, and Systems

When GOPs are primarily implemented directly in a reaction chamber as in situ measuring devices, they are continually subjected to thermal and mechanical stresses. Although, in general, GOPs are rugged measuring devices the material selected and the details of their design play key roles in the assembly of an optimally configured measurement system. 4.3.1.1 Sensor Materials A GOP measuring unit consists of the actual potentiometric oxygen concentration measuring chain (measuring gas electrode, solid electrolyte, reference gas electrode) and a thermocouple to measure the sensor temperature. 4.3.1.1.1 Potentiometric Oxygen Concentration Measuring Chain A partially (but preferably fully) stabilized zirconia doped with Y2O3 (YSZ) is primarily employed as the ceramic solid electrolyte material. A solid electrolyte is oxygen ion-conductive over a temperature range of about 600 to 1600  C that is customary in combustion plant; hence, it is a virtually ideal sensor component. YSZ ceramics are characterized by their high thermostability and thermal shock resistance, as well as their overall chemical stability. Although a variety of material options has been tested and refined to improve the range of applications with regards to a lower temperature range and oxygen ion conductivity, YSZ has been shown to be best suited for use in combustion plants. Other possible combinations of solid electrolyte materials have been described in greater detail elsewhere [33]. The measuring gas electrode, which consists of a measuring gas, the electrode metal and a solid electrolyte, forms the three-phase boundary where the electrode reaction proceeds. Precious metals such as Pt, Pd, Au, Ag, or even mixed oxides, perovskites and alloys, are often used as the electrode materials. These materials must be redoxstable and thermostable in the particular sample gas atmosphere, and also possess the catalytic activity required to establish chemical equilibrium. The size of the electrode is selected as a function of the requisite spatiotemporal signal resolution. A small electrode surface area allows for a particularly short response time, and can reflect gas quality with pinpoint accuracy (point electrode). The larger the electrode surface area, the more integrally are the signals generated. If

4.3 GOP Applications in Research and Industry

required, the signal can additionally be damped by an upstream measuring gas chamber filled with ceramic wool. Different metals on the electrodes’ measuring and reference side generate thermoelectromotive forces that result in asymmetric voltages. The application of identical gases to the measuring and reference side makes it possible to determine the asymmetric voltage as a function of temperature, and to allow for it as an offset (see also Section 4.2). The reference gas electrode delivers a known and constant oxygen potential for the measuring chain. A simple option for providing a constant O2 partial pressure is to purge the reference chamber with gases, and for this technical gases with known oxygen concentrations (e.g., pure oxygen or blends with nitrogen as the inert gas fraction) are used. One particularly simple option is to use (ambient) air as the reference medium; however, the water vapor content of the ambient air must be allowed for in the measurement, since for precision measurements any further impurities must have been eliminated. If a GOP cannot be purged with gas, the reference electrode can be equipped with a metal/metal oxide mixture, which then provides a temperature-dependent oxygen partial pressure in the reference chamber. Tests have been conducted on the metal/ metal oxide pairs of Pd/PdO, Ni/NiO, Fe/FeO, Cu/CuO, Cr/CrO3, and In/In2O3, among others [34]. Hartung et al. described a practical application in which Cu/CuO reference electrodes were employed in vacuum [35], while Barin provided a comprehensive compilation of thermodynamic data for metal oxide reference systems [36]. The metal/metal oxide mixtures are normally used in powder form, as the different expansions of the material induced by temperature may cause problems in sealing the reference chamber. The range of applications for this sensor configuration is limited primarily by the sintering temperature of the mixtures, but blending in a finely dispersed solid electrolyte powder can solve the problem of thermal material stress and sintering [35]. Thus, the requisite material combination must be adapted to the gas atmosphere and the expected operating temperature, so that the service life of the sensors matches the operational requirements. 4.3.1.1.2 Thermocouples Determining gas concentrations from measured cell voltage requires that the electrode temperature is measured on the measuring gas side, or on the reference side. If Pt is used as the electrode material, a rugged precious metal thermocouple (R, S, B) can be installed by contacting a platinum/rhodium wire. If an oxygen carrier (air) is used to purge the reference gas side, then commercially available extremely fine precious metal-free thermocouples (e.g., K, N) can be applied up to approximately 1300  C, according to the manufacturers’ specifications. If the thermocouples are implemented on the measuring gas side, their protective metal sheathing must be capable of withstanding the harsh operating conditions. Consequently, precious metal thermocouples are usually reverted when operating at an extremely high temperature (>1000  C) or in a reducing atmosphere. If the potentiometric measuring chain does not exhibit ideal isothermal properties, then precision measurements will require the use of a second thermocouple to

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Figure 4.3 Scheme of a classical gas potentiometric oxygen probe (GOP) (a), the sensor element in magnification (b/), and a protected GOP (c).

measure and correct the thermoelectromotive forces that appear between the sensors’ electrodes. M€obius has identified a way to implement this [37]. When connecting the thermocouples to the measuring device, extension wires are preferable compensation wires in order to minimize any errors in the temperature measurements. 4.3.1.2 GOP Designs Depending on the case of application, probes can either be miniaturized to a few centimeters in size, or they may be several meters long. In principle, two types of sensor have proven to be practicable, namely the tubular semi-closed and planar forms. Tubular GOPs represent the classical design in which, as the sensor, the potentiometric measuring chain is installed on the end of a semi-closed solid electrolyte tube. A typical configuration, with air-purging of the reference gas chamber, is shown in Figure 4.3. Several electrodes can be applied to the solid electrolytes, which in turn expands the options for the evaluation of captured signals. Electrodes of the same or different materials – and thus different catalytic activity – may be used as variants of multiple electrodes. Multiple electrodes with identical material configuration are ideal for locally resolved signal evaluation, whereas a combination of different materials facilitates the qualitative evaluation of gas equilibria at the measuring electrode (the varying catalytic activity allows a selective adjustment of the particular gas equilibria). Some examples of sensors with electrodes of different configurations and materials are shown in Figure 4.4.

4.3 GOP Applications in Research and Industry

Figure 4.4 Water-cooled GOP (a); a turbulence GOP with a point electrode (b); a gradient GOP (c); and GOPs with combinations of gold and perovskite electrodes (d).

Planar sensors are a low-cost design option [38] in which thick- or thin-film technology can be used to apply the surfaces of the probes to a ceramic carrier. Heating can be implemented either on the back of the carrier, or in interlayers, while the reference and sample gas electrode can be laminated onto the oxygen-ion conductor (usually YSZ) either adjacent to or atop one another. A Me/MeO mixture or pump electrode can be used to produce the reference. This design may be used directly in combustion chambers. 4.3.1.2.1 Mechanical Barriers (Plates, Tubes, Meshes) and Sensor Mounting If GOPs are subjected to mechanical stresses, such as in fluidized beds, the ceramic tubes and the electrodes must be protected. The GOPs may have differently designed baffle plates that protect sensors from mechanical abrasion (see Figure 4.5), whilst thermostable and rustproof stainless steel (Inconel, Hastelloy) plates and tubes may provide mechanical protection. Some examples of commercial GOP probes have been described [39]. The electrodes may also be protected by meshes or porous ceramic coats applied to the measuring electrodes. 4.3.1.2.2 Heating When the measuring gas temperatures are low, the sensor must be heated to achieve its optimal working temperature. The heat source can be installed either inside the sensor, or outside as radiant heating.

Figure 4.5 Gas potentiometric oxygen probes, fully closed (a) and protected by baffle plates (b, c).

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4.3.1.2.3 Facilitating the Establishment of Equilibrium Taking measurements in reactive gas mixtures complicates the establishment of a chemical equilibrium in the measuring electrode. To overcome this problem, the electrodes can be surrounded by catalysts so as to facilitate the establishment of an equilibrium, such that the gas is brought into chemical equilibrium before it reaches the electrode. An example of the design and a selection of catalysts for the analysis of water gas equilibrium has been provided by Hartung [40]. The equilibrium may also be incompletely established when the measuring gas has a high flow rate; however, the gas velocity can be reduced considerably by using certain design measures, such as electrode sheathing. In this case, the longer the residence time of the measuring gas on the electrode surface, the greater the improvement in the relationship between the reaction rate and flow rate. 4.3.1.2.4 Protection Against Carburization When analyzing reducing atmospheres that contain fractions of hydrocarbons, carbon may often be deposited on the catalytically active electrode. Subsequent incorporation of the carbon into the electrode metal produces metal–carbon alloys that can lead to the destruction of a measuring electrode. The protection of electrodes with carbon traps (e.g., mineral wool, porous ceramic coats) will delay this process and so prolong the electrode’s operating life. The selection of a suitable electrode material, such as perovskite, can also prevent such carbon inclusions. 4.3.1.2.5 Explosion Protection Since a GOP can constitute an ignition source in atmospheres at risk of explosion, in such cases the sensors must be equipped with explosion protection. This usually involves the installation of a wire mesh that is stretched around the sensors so as to prevent flame propagation. 4.3.1.3 Electrical Metrology GOP sensors generate voltages between 0 and 350 mV in oxidizing atmospheres, and up to approximately 1600 mV in reducing atmospheres. These voltages must be picked up at zero current – that is, at high resistance with at least 1 MV. The signals must first be converted in order to be conducted to the measuring device over long distances, and the converter must meet the same criteria as the instrument. Cables that transmit cell voltage and thermal voltage must be shielded to prevent any misinterpretations caused by electric fields. Although the sampling rate may be very low (in the lower Hz range) for general applications, higher sampling rates (in the kHz range) are required for dynamic measurements. An example of the latter is in the analysis of turbulences or hydrodynamic fluctuations in flames or fluidized beds [41]. 4.3.1.4 Response Time Describing combustion processes that are completed in the range of a few seconds (gas ignition and combustion) places high demands on the measuring equipment used. Clearly, a sensor system must ensure high dynamics, with a minimal response time.

4.3 GOP Applications in Research and Industry

Figure 4.6 Response times of a classical gas potentiometric oxygen probe [42].

The GOP response time depends on the design (electrode size, barriers) and the gas characteristics (oxidizing/reducing atmosphere, basic voltage value, intensity of variation). Test findings of the response time and the dynamics of GOP measurements taken in oxidizing atmospheres are represented in Figure 4.6 as potential build-up curves at four different temperatures. Here, a classical GOP (as shown in Figure 4.3a) has been applied. The 90% value (the time, when 90% of the final cell voltage is given by the sensor after a change; also referred to as the t90-value) is less than 15 ms for temperatures higher than 800  C that are characteristic for technical combustion processes [42]. 4.3.2 Analysis and Characterization of Gaseous and Liquid Fuel Combustion

The combustion process of gaseous fuels (see Vol. 3 Ch. 1) and liquid fuels (Vol. 3 Ch. 10) can be analyzed whether in-flame (in situ) at temperatures between 600 and 1500  C by using a GOP, or off-flame at temperatures below 600  C or exceeding 1500  C by sampling their flame gases (on line/off line) [10, 16]. An overview of methods of gas potentiometric flame analysis (GPFA) is provided in Table 4.2. 4.3.2.1 In Situ Measurement When a flame is scanned with a GOP, characteristic cell voltage signals are always obtained, depending on the probe’s position within the flame. Figure 4.7 presents an example of a schematic temporal signal curve of a free jet flame. As expected, free molecular oxygen (2.1 vol%) – that is, an oxidizing atmosphere – is measured at the end of the flame with a mean cell voltage of about 40 mV. Turbulent mixing of the surrounding air with the fuel gas causes the measured cell voltage to fluctuate strongly in the center of the flame. The signal fluctuations of the cell

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Table 4.2 Overview of the methods of gas potentiometric flame analysis.

In-flame analysis

Off-flame analysis

Performance Use of flame GOPs with burn-out and turbulence sensors Measurements without gas sampling (in situ measurement) Measurement at particular flame temperature (operating temperature, establishment of equilibrium): Thermal and mechanical stress in solid electrolyte.

Use of flow measuring cells Measurement with sampling of flame gas (on line/off line measurement) Measurement at optimal sensor operating temperature (external sensor heating): Minimal stress of the solid electrolyte

Results Flame body geometry: Contour, length, degree of burn-out Degree of mixing Analysis of turbulent flame structure Fuel gas analyses: stoichiometric air requirement, determination of heating value New concepts to optimize and regulate combustion

voltage correspond to the oxidizing and reducing conditions, thus representing the heterogeneous structure of the body of the flame. The highly negative cell voltage values of around 900 mV (i.e., 9.2  10 16 vol% O2 at T ¼ 850  C) indicate a high fuel gas surplus and, consequently, strongly reducing conditions at the root of the flame. Special functions of Ueq derived from the classical Nernst equation can describe the quantitative correlation between the cell voltage and the corresponding concentrations of the flame gases, for example, H2, CH4, CO, CO2, H2O, O2, and N2, (see Table 4.1). These equations make it possible to quantitatively evaluate the combustion conditions in the body of the flame from the measured data of the Ueq and the cell temperature. Thus, the high absolute cell voltage values near the burner characterize the fuel gas region of the flame, followed by the water gas region. The zone of stoichiometric conditions corresponds to the sharp potential decline where the exact end of the flame can be determined at the point of inflection. Finally, the exhaust gas-air range follows, indicated by low absolute cell voltage values. Figure 4.8 presents the values of the Ueq and the sensor temperature TZ (measured gas potentiometrically), together with the corresponding concentrations of H2, CH4, CO, CO2, H2O, O2, and N2 (analyzed gas chromatographically) as a function of the main axis of a flame body. This provides a basis to calculate important flame parameters such as the degree of burn-out and mixing, simply by using the data measured using gas potentiometry [16]. The strong fluctuations of the cell voltage in the stoichiometric zone represent an extremely interesting expression of the turbulence mechanism that alters the gas composition in the flame region by intensively mixing the air with the fuel gas. The specially constructed probe (turbulence GOP; see Figure 4.4) allows the detection of bales of fuel gas and air, as well as the frequency distribution of Ueq for a defined

4.3 GOP Applications in Research and Industry

Figure 4.7 Sensor signals in different positions of a free jet flame.

Figure 4.8 Concentration distribution of equilibrium gases, cell voltage (Ueq), sensor temperature (TZ) and gas temperature (TG) in the x-axis of a free jet city gas flame.

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Figure 4.9 Cell voltage–time curve and a corresponding eddy structure.

position in the flame [43]. Figure 4.9 shows a possible flame eddy and the corresponding GOP signal. The temporal resolution of Ueq delivers the structure of the eddy (see Vol. 1 Ch. 8). The aforementioned correlations between the values of the cell voltage and the burn-out of the fuel gas apply here also. Any passage of the point of inflection with Ueq between 300 and 400 mV corresponds to a flame front that locally separates oxidizing and reducing structural elements one from another. The quantity of such flame fronts – that is, the number of points of inflection per time unit at a defined position in the flame – is an expression of the intensity of combustion. Interesting results on the development of experimentally based models in this field have been presented in detail [44, 45]. In several other investigations, GOPs have been applied with gradient sensors (see Figure 4.4) to measure the turbulence processes [46]. Indeed, measuring the concentration gradients rather than concentration is sufficient to indicate the turbulence in flames. Figure 4.10 illustrates, graphically, the theoretical cell voltage curve of a gradient sensor for the flame structure in Figure 4.9, where the eddy structure is derived from the conventional sensor signal, and where the flame fronts are indicated by peaks instead of points of inflection. Figure 4.11 compares the cell voltage–time curves of conventional and gradient sensor measurements, recorded near the tip of a free jet flame. The temporal correlation between the different peaks of both curves and the gradient sensor’s improved resolution due to its minimized geometry can easily be derived.

4.3 GOP Applications in Research and Industry

Figure 4.10 Theoretical cell voltage curve of a gradient sensor for the structure shown in Figure 4.9.

Similar investigations have been carried out on oil flames with adapted probes [47], an example of which is shown in Figure 4.12, demonstrating the contour of a sharply twisted commercial oil burner flame. Even under the complex combustion conditions of high-boiling and cyclic carbon sprays (see Chapter 11), parameters such as contour, burn-out and degree of mixing can be determined with assistance from the GOP.

Figure 4.11 Cell voltage–time curves measured by a conventional (a) and a gradient sensor (b).

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Figure 4.12 Outline of an oil flame studied with a gas potentiometric oxygen probe.

4.3.2.2 On-Line Measurement (Off-Flame Gas Potentiometric Measurement) In a measuring set-up of off-flame (on-line) gas potentiometric analysis, the gas is sampled by a silica glass suction probe positioned in the flame, which has been tempered to over 80  C so as to prevent water separation. The gas sample from a point in space selected with a coordinate device is then rapidly conveyed through tempered gas ducts into the measuring chamber of a gas potentiometric flow measuring cell. The establishment of Ueq is awaited at the cell temperature chosen. The flow cell is constructed from one of two variants, depending on the task to be performed. These differ in their use of either a solid electrolyte tube which is open at both ends, or closed on one side. The sensor for the solid electrolyte tube cell is installed in a gas-tight manner in a silica glass tube, while the external electrode is purged with air and the internal electrode is purged with the gas sample from the flame to be measured. The GOP with the solid electrolyte tube closed on one side was primarily used for gas potentiometric titrations of fuel gas with air; a schematic of its special design is shown in Figure 4.13. The rapid and precise determination of the stoichiometric air

Figure 4.13 Schematic diagram of a gas potentiometric titration measuring cell.

4.3 GOP Applications in Research and Industry

requirements of fuel gas allows the burners to be set appropriately, and for the calorific values to be determined by using familiar statistical correlations between the calorific value of hydrocarbons and the stoichiometric air requirement (see Vol. 3 Ch. 6 and 9). Detailed information on the use of flow cells has been presented elsewhere in detail [48]. The experimental methodology of gas potentiometric flame analysis described here has been proven in tests of model flames, flames in combustion chambers under near-real conditions and in tests on burners [16], and also in investigations of the influence of gravity on flame formation under microgravity conditions [49]. 4.3.3 Analysis and Characterization of Solid Fuel Conversion

Solid fuels (see Vol. 4 Ch. 1) are combusted and gasified to generate power and produce high-calorific gases, such as synthesis gas, reduction, and fuel gas. Along with the classic fossil fuel coal (Vol. 4 Ch. 5), renewable (CO2 neutral) carbon sources (biofuels; Vol. 4 Ch. 3) and waste materials (Vol. 4 Ch. 8) are continuing to gain importance with regards to limiting greenhouse gas emissions and economizing on coal usage [50–53]. While combustion processes fundamentally operate with a defined air/oxygen excess (air ratio l > 1), gasification processes are characterized by the presence of reducing conditions (l < 1). In this context, the air ratio l should be viewed as a global value describing the overall reaction. Since reducing and oxidizing conditions occur locally in both combustion and gasification processes, the particular chemical reactions are, in principle, identical. Optimal process control requires a detailed knowledge of the combustion and gasification characteristics of a particular fuel, biofuel or waste, under process conditions that are as close to reality as possible. Unfortunately, however, a classical fuel analysis (ultimate and proximate analysis, heating value) will provide information to only a limited extent. With relevance to practice, combustion and gasification processes can be described by the in situ measurement of the redox ratios present in the reaction zone, applying a GOP for the burn-out characteristics of a particular solid and suitably modeled fuelspecific macrokinetic parameters to characterize the reactivity. 4.3.3.1 Gas Potentiometric Measurements in Combustion and Gasification Chambers At a given reactor and sensor temperature, the equilibrium cell voltage measured under combustion and gasification conditions will reflect the redox ratios existent in a combustion chamber. Figure 4.14 presents the experimentally determined correlation between measured cell voltage and related gas composition [46]. As a function of the air–fuel ratio, a characteristic combustion curve is obtained, that corresponds in principle to a titration curve of air with coal. Analogous to gas flames (see Section 4.3.2), the clearly distinguishable regions with high absolute cell voltage values between 600 and 800 mV (l < 1) and low cell voltage values below approximately 50 mV (l > 1) can be assigned to the so-called water gas region

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Figure 4.14 Gas potentiometric oxygen probe signal interpretation. Relationship between cell voltage and related gas composition as a function of the air ratio l (laboratory-scale fluidized-bed reactor, continuous conversion of brown coal with air, mean combustion temperature: 850  C).

(IUeqI > 350 mV) and the exhaust gas–air region (IUeqI < 350 mV), respectively. The strong leap at the equivalence point (l ¼ 1, IUeqI  350 mV) represents stoichiometric conditions between the fuel and air. The components of an homogeneous water gas equilibrium coexist in the water gas region, while the increase of hydrocarbons (in particular methane) begins to indicate the increasing fraction of fuel gas. Under reducing conditions, the measured cell voltage characterizes the oxygen partial pressure attributed to dissociation equilibria of the oxides in the reaction mixture (equilibrium oxygen; see Section 4.2). 4.3.3.2 Burn-Out Characteristics of Solid Fuels, Biofuels, and Waste Materials under Combustion and Gasification Conditions The burn-out characteristics of solid materials can be studied by simple batch experiments. For this purpose, a weighed solid sample is introduced into the combustion or gasification reactor, whilst a GOP positioned directly in the reaction chamber follows the burn-out through the specific oxygen conversion. Examples of GOPs positioned in fluidized-bed and fixed-bed reactors are shown in Figure 4.15. The aforementioned underlying correlations between equilibrium cell voltage and redox ratios in a combustion chamber facilitate the interpretation of the sensor signal curves obtained.

4.3 GOP Applications in Research and Industry

Figure 4.15 Investigation of the burn-out behavior of solid fuels in (a) a fluidized-bed reactor and (b) a fixed-bed reactor, with a gas potentiometric oxygen probe (positioned directly in the fluidized bed and just below the grate, respectively). A specially designed

optosensor to detect flame radiation, a slow motion camera to visualize ignition processes (see Vol. 1 Ch. 4 and Vol. 4 Ch. 4) and a thin thermocouple to quickly measure temperature have additionally been implemented in the fixed bed for special studies of ignition behavior [42].

Substance-specific cell voltage–time and oxygen concentration–time curves (burnout curves) are obtained for the combustion, which characteristically reflect the burnout behavior of a particular solid (termed a “fingerprint”). Examples of burn-out curves for a broad range of conventional fuels, biofuels and waste materials, as measured in a laboratory-scale fluidized-bed reactor, are shown in Figure 4.16. Here, the burn-out process begins with ignition of the sample, as indicated by a distinct fall in the oxygen concentration, and ends when the oxygen content of the fluidizing air used is reached again. This period corresponds to the time required for combustion of the sample (combustion time, tB), which can be determined directly from the burn-out curve as a measure for the mean combustion rate. The “gas peak” observed for the coal, biomass, and waste materials can be attributed to the processes of release, ignition, and combustion of the volatile matter (homogeneous gas combustion) that proceed at a high rate. The volatile matter can variously influence the combustion of the remaining char as a function of both their fraction and composition and the properties of the char itself. While there are distinguished phases of volatile and char combustion obtained for the combustion of semianthracite and bituminous coal, both processes occur simultaneously in the case of the brown coal, the biofuel miscanthus, and the waste materials. This increases the mean combustion rate and thus shortens the combustion times (there is a superimposition of the homogeneous and heterogeneous processes). The oscillations measured in the oxygen concentration (Figure 4.16) can be attributed to the rapidly changing redox conditions in the fluidizing bed (intensity of mixing and combustion, differences in oxygen concentration in the fluidized bed’s dense and bubble phase). Only the high measuring dynamics of the GOP sensor used make them measurable at all (see Section 4.3.4). Even fuels of the same type, such as different bituminous coals of comparable composition, can be evaluated based on differences in the gas potentiometrically measured burn-out curves [13, 54].

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Figure 4.16 Burn-out curves of different fossil fuels, biofuels and waste materials in a laboratoryscale fluidized-bed reactor.

A combination of in situ measurement systems (as shown in Figure 4.15b) additionally facilitates the description of homogeneous and heterogeneous ignition processes of solid materials in detail. The processes of heating, drying and devolatilizing, igniting and burning the volatile matter, as well as igniting the char, can be differentiated and their duration analyzed quantitatively [42]. Such studies are particularly important for the combustion of biomass and waste materials, where the overall burn-out process is dominated by the combustion of the volatile matter. Analogous to combustion, the gas potentiometric analysis of the gasification of solids (Vol. 4 Ch. 9 and 10) provides fuel-specific burn-out gasification curves as a function of the gasification agent employed, that allow a description of the gasification behavior of the particular fuel. The influence of the characteristics of the solid fuel, such as type, grain size fraction and sample quantity, on the course of burn-out can be clearly distinguished. Examples of measured cell voltage–time curves for the gasification of brown coal coke with air, CO2/ water vapor and diverse CO2 water vapor mixtures are shown in

4.3 GOP Applications in Research and Industry

Figure 4.17 Cell voltage–time curves for the conversion of different sample quantities of brown coal coke with various gasification agents in a laboratory-scale fluidized-bed reactor.

Figure 4.17. Here, different sample quantities were used to establish various fuel–gasification agent ratios. The conversion begins immediately after the fuel is charged, as indicated by a steep increase in the cell voltage to high absolute values. Subsequently, depending on the sample quantity at constant throughput of the gasification agent, different cell voltage levels are reached that characterize the present oxygen partial pressure. For gasification with air, first the combustion conditions and then the gasification conditions are observed as the sample quantity increases. The development of a stable or slightly sloping cell voltage level in the range of 600 to 800 mV is characteristic for the burn-out curves obtained during gasification. This indicates steady-state conditions with a virtually unvarying product gas composition – that is, a particular gas quality. This makes it feasible to use a GOP to monitor the quality of the product gas directly in the technical process, and also to adjust a certain product composition by integrating a GOP into a control concept. The aforementioned correlations between cell voltage and redox ratios in the reaction zone provide a basis for determining the gasification time and its part of the overall conversion time to characterize the mean conversion rate. In a comparison of the gasification media employed, the conversion rate falls significantly from air to CO2 and water vapor (Figure 4.17a–c). Detailed investigations of the gasification characteristics of solid fuels in a fluidized bed are presented in Ref. [55], and of wood pellet gasification in particular in Ref. [59].

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Table 4.3 Results of the gas potentiometric combustion analysis (GPCA).

Results

Potential information

Burn-out curve

Qualitative and quantitative information of the course of burn-out (devolatilization, char combustion, residual char burn-out ¼ burn-out of the “remaining 5 wt%”) Residence time for complete burn-out of the fuel, mean combustion rate Mean combustion rate, information on heat release per time unit, input parameters in combustion models Comparison of combustion rates of different fuels Temperature dependence of the combustion rate, makrokinetics of the overall process

Combustion time Effective reaction rate constant Relative reactivity Activation energy

4.3.3.3 Gas Potentiometric Combustion and Gasification Analysis: Burn-Out Characteristics and Fuel-Specific Makrokinetic Parameters Both, gas potentiometric combustion analysis (GPCA) and gas potentiometric gasification analysis (GPGA) represent novel alternative methods for the efficient determination of the burn-out characteristics of any solid fuel, under conditions relevant to practice (see Chapter 3). A detailed description of the methods and their application to conventional fuels, biofuels and waste materials is provided elsewhere [13, 14, 56, 57]. The burn-out curves obtained specifically reflect the burn-out behavior of the particular solid fuel. Along with qualitative and quantitative descriptions of the course of the burn-out, when appropriate models are applied they allow makrokinetic parameters to be determined, such as the effective reaction rate constant keff (a reactivity parameter) and the apparent activation energy, AE. Notably, the keff value is a fuel-specific parameter that is influenced by the particular reaction conditions. Some example results and details of the performance of GPCA are summarized in Table 4.3. Since the mixing equations common in process engineering only partially succeed in calculating combustion-specific parameters [58], the characterization of the burnout behavior in advance of the planned co-combustion of various conventional fossil fuels with biofuels or waste materials is of particular interest (see Vol. 4 Ch. 16). Some examples of the burn-out curves obtained for the combustion of brown coal, bituminous coal and a 1 : 1 mixture of both are shown in Figure 4.18. The combustion times determined, as well as the aforementioned keff values to evaluate the reactivity under given combustion conditions, are also indicated. The burn-out behavior of bituminous coal (from G€ ottelborn, Germany), characterized by ignition problems in the range of char burn-out (t ¼ 6–10 s), can be improved significantly by adding substantially more reactive brown coal [57]. Thus, in the case of mixed combustion, GPCA would be able to determine optimal mixing ratios or, when fuel composition varied, the firing operation could be quickly and inexpensively adjusted to the modified fuel quality.

4.3 GOP Applications in Research and Industry

Figure 4.18 Study of co-combustion using gas potentiometric combustion analysis (fluidized bed, 850  C, 0.1 g sample).

4.3.3.4 Modeling to Determine Fuel-Specific Makrokinetic Parameters The evaluation models developed combine the balancing of the applied gas phase (oxygen, gasification agent) established on the basis of the measured burn-out curve with a simple macrokinetic approach to determine an effective reaction rate constant. Thus, they are solely based on the cell voltage–time curves, measured gas potentiometrically, as a measure for the converted reactant gas phase, and differ from frequently employed particle-based combustion models that use particulate features such as diameter or change in density to describe the burn-out. The effective reaction rate constant obtained describes the burn-out process under given reaction conditions, and includes the influence of mass transfer processes and chemical kinetics. This can be considered a fuel/substance-specific parameter, influenced by the particular reaction conditions but modeled independently from the particulate properties. The determination of the apparent activation energy via the temperature dependence of the keff values can be used to identify the rate-determining steps. In principle, the models developed for combustion and gasification differ in the determination of the partial pressure of the reactant gas. For combustion, the GOP signal directly provides the quantity of oxygen converted. Under gasification conditions, redox ratios result, which allow quantification of the gasification agent’s partial pressure by applying cell voltage equations valid for present equilibria. Models for combustion (O2 balance model) and gasification with CO2/H2O mixtures (CO2/H2O model) are described in detail in Refs [13, 14]. 4.3.3.5 Resume The in situ measurement of redox ratios present in the reaction zone, using GOP, can be applied to monitor the complicated homogeneous and heterogeneous processes that occur during the combustion and gasification of solid materials. Suitably

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assembled GOPs allow for diagnostics in all of the reaction equipment typically used for solid–gas conversions, independent of scale. The correlation between equilibrium cell voltage and redox ratios in the reaction chamber facilitates the quantitative description of the combustion and gasification processes continuously, without any time lag and with a high degree of temporal resolution. Both, GPCA and GPGA have proven their value as alternatives for the efficient characterization of the burn-out behavior of any solid fuels, under conditions relevant to practice. 4.3.4 Applications with Potential for Development

As they cover a wide range of oxygen concentrations, from oxidizing atmospheres (100 vol% oxygen) to strongly reducing atmospheres (10 20 vol%), the applications of GOP can be implemented in many domains of the processing and energy industries. One basis for classifying GOP applications is provided by a synthesis gas production process, for each step of which the use of GOP to improve in situ monitoring is conceivable, namely fuel gas generation; cleaning and conditioning; and gas utilization. Moreover, GOPs represent an often expedient measuring device to quickly adjust and regulate fuel and oxidation agent ratios when gas concentrations are rapidly altered. The details of several recent model applications are outlined below. 4.3.4.1 The Performance of a Velocity-Oxygen Probe The velocity-oxygen probe (VOP) represents the combination of a high-temperature anemometer (HTA) and GOP. The VOP is an integrated probe for the measurement of gas velocity and oxygen content in a solid fuel furnace environment (Figure 4.19) (see Vol. 4 Ch. 2). Trials with two biomass-fired systems have demonstrated the degree of consistency and responsiveness that enables VOP to contribute to the optimization and shortterm control of furnace or boiler operation [60]. Some selected results of a test run with a VOP are shown in Figure 4.20.

Figure 4.19 Velocity-oxygen probe. (a) Schematic cross-section; (b) After application in a biomass fired boiler (10 MWth).

4.3 GOP Applications in Research and Industry

Figure 4.20 Short-term variation for velocity, temperatures and oxygen content obtained in a run of a 500 kWth pulsating combustor.

A prototype of the VOP displayed the capability for measurements at insertion depths of up to 5 m, covering the geometry of most large industrial-scale furnaces (see Chapter 12 and Vol. 4 Ch. 6). The water-cooled VOP can be operated continuously at a temperature of 1300  C, and has the ability to withstand short-term operation at 1400  C, in highly dust-laden atmospheres (e.g., 80 kg m 3) typically encountered in circulating fluidized-bed reactors. Although the performance is not clearly impaired by the deposition of ash over extended measurement periods, it is recommended that the measurement schedule be set to allow for the periodic examination and removal of ash from both sensors [61]. 4.3.4.2 Measurement of Fluid Dynamics in a Fluidized-Bed Reactor The short response time of the sensors in alternating oxidizing and reducing atmospheres means that GOP measuring systems are well-suited for mapping dynamic processes (see Sections 4.3.1.4 and 4.3.3), such as in fluidized beds (see Vol. 4 Ch. 11). The electrodes are capable of detecting any fluctuations in the gas quality almost in real-time. When two identically configured electrodes are positioned longitudinally to the direction of flow (see Figure 4.21), this allows a cross-correlation to be applied so as to determine the time difference (t ¼ t) between the electrodes’ oscillating signals. As the structural spacing (s) of the electrodes is known, the velocity (v) is easily obtained (v ¼ s t 1). This type of sensor is also suitable for characterizing a two-phase flow consisting of a bubble and dense phase. In this case, when the solids are burned or gasified in a fluidized-bed, an oxygen carrier (e.g., air) fluidizes the fuel in a reactor, where oxygen is consumed. In this way, bubbles with a high oxygen fraction that are virtually uninvolved in the reaction can easily be distinguished from the oxygendeficient dense phase. The bubble velocity can be determined when a multiple sensor is immersed in the fluidized-bed longitudinally to the direction of flow. The analysis can then be applied to individual bubbles or averaged over a longer period with a cross-correlation:

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Figure 4.21 Multiple-sensor GOP (a) and its placement in a fluidized-bed reactor (b).

1 W1;2 ðt; TÞ ¼ T

þð T=2

U1 ðtÞU2 ðt þ tÞdt

ð4:6Þ

t¼ T=2

Figure 4.22 shows examples of the signal curve of two electrodes (left upper panel), enlarged details (left middle panel) and the analysis performed both manually (left lower panel) and with a cross-correlation (right panel). 4.3.4.3 Feed Control in Solid Fuel Gasification In solid fuel gasification, a GOP can be used as a means of measurement in addition to the main gas analysis system (Vol. 4 Ch. 9 and 10), and also to control the fuel–air ratio directly in a reactor chamber. In this case, the position of the GOP is selected in such a way that it is close to the main conversion zone, whereby the GOP is contacted by the fuel gas shortly after the gas–solid-reactions (see Figure 4.23a). The signals (cell voltage and temperature) of a double-sensor GOP during repeated alternation from biomass combustion (step 1) to gasification (step 2) is shown in Figure 4.23b. The first signal peak indicates a change from combustion to gasification and subsequent bed burn-off (step 3); complete burn-off is then followed by a return to gasification (step 2). The fundamental relationship between the GOP signal and measuring gas atmosphere characteristics forms the basis for creating a control loop with a GOP as an in situ measuring instrument for solid fuel gasification. One possible type of GOP control loop, that guarantees a desired fuel gas quality by controlling the input flux of both the solid fuel and the gasification agent, could function as follows. When the gas produced passes the GOP sensor, a cell voltage is generated according to the gas composition. This GOP signal is used to determine the redox ratio by applying the

4.3 GOP Applications in Research and Industry

Figure 4.22 Measurement of bubble velocity during coke combustion in a fluidized-bed reactor.

valid cell voltage equation (see Table 4.1 in Section 4.2). The obtained redox ratio is then compared with a set value. In the case of a present variance – that is, a difference between the measured and set values – the input flux of solid fuel and gasification agent are adjusted until the measured redox ratio equals the set value, so that the desired fuel gas atmosphere is achieved in the reactor (see Figure 4.24).

Figure 4.23 (a) Gas potentiometric oxygen probe (GOP) placement in a fluidized-bed reactor; (b) GOP signals from alternating combustion (step 1), gasification (step 2), and burn-off (step 3).

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Figure 4.24 A gas potentiometric oxygen probe control loop.

4.3.4.4 O2 Concentration Distribution in a Fluidized-Bed Membrane Reactor In order to obtain both a high yield and selectivity during the partial oxidization of hydrocarbons (e.g., ethane to ethylene), a constant and equal dosage of an oxidizing medium is a prerequisite. Favorable results are obtained when the oxidizing medium – the secondary gas (e.g., air, oxygen) – is applied to the primary gas via porous membrane tubes, arranged symmetrically on the inside of the reactor. This instrumental arrangement is termed a fluidized-bed membrane reactor (FLBMR) (Figure 4.25). The advantages of an equal gas component distribution are greatest when optimal fluid dynamics in the FLMBR are achieved. The in situ-measuring GOP technique was applied to investigate fluid dynamics in a fluidized-bed reactor with implemented membranes by measuring the oxygen concentration distribution in different process modes [59]. The measurements were performed with quintuple sensor GOPs positioned in line (P1–P5) at three different levels (L1–L3) along the reactor height (Figure 4.26). In order to measure the oxygen distribution, nitrogen (primary gas) was flowed through the reactor from a sintered metal distribution plate, while four sintered metal membrane tubes through which air (secondary gas) could be added were arranged symmetrically on the inside of the reactor. The aim of these experiments was to test the flow and mixing characteristics of the membrane tubes in combination with the sintered metal distribution plate in fluidized-bed and plug-flow mode. A comparison of the signals revealed a more homogeneous gas concentration in fluidized-bed mode than in plug-flow mode, but an asymmetric oxygen profile was detected in both plant configurations (Figure 4.27). The concentration profiles in both

4.4 Outlook

Figure 4.25 Schematic cross-sections of a fluidized-bed membrane reactor FLBMR (a, b), and a set of membranes (c).

modes showed a notably higher oxygen concentration on the right-hand side, though this was shown to be due to a local plant malfunction caused by the sintering of a membrane and a defective seal on the air distribution plate. Notably, both problems could be localized with certainty only when using the GOP.

4.4 Outlook

Established oxygen-gas potentiometry applications, such as exhaust gas probes and lambda oxygen sensors for measurements in furnaces and motor vehicles, respectively, will undoubtedly be widely applied on an industrial scale in the future.

Figure 4.26 (a) Quintuple gas potentiometric oxygen probe (GOP) sensor; (b) Schematic of the GOP positioning.

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Figure 4.27 O2 concentration profiles as a result of admixing O2 through membranes (air flow ¼ 80 l min 1) into an N2 flow (40 l min 1) of plug-flow mode (a) and fluidized-bed mode (b), measured with a gas potentiometric oxygen probe.

In addition, GOPs hold considerable potential as measuring instruments in safety systems for the in situ monitoring of technical units with fuel gas atmospheres. The ability to exploit this potential will, however, necessitate further GOP developments, including perhaps solid electrolyte and electrode materials that reduce the GOP operation temperature and produce long-term stability in reducing atmospheres. The addition of metal/metal oxide mixtures on the reference electrode, replacing continuous air purging, would also increase the degree of freedom in design. It is highly likely that such developments will lead to a spread of GOP applications in engineering research, with current research investigations aimed at further developing methods of gas potentiometric analysis to determine the combustion and gasification characteristics of fuels with a high fraction of volatile matter, such as biomass.

4.5 Conclusions

Gas potentiometry with oxygen–solid electrolyte sensors is an established diagnostic procedure in combustion engineering. Given its extraordinarily rapid response time to oxygen under reaction conditions, a GOPs in situ measurement can provide detailed information on the progression of a conversion, as well as on the gas composition of oxidizing and reducing atmospheres. Together with the large range of design alternatives and materials, this information makes GOP a practicable measuring instrument to analyze the processes of thermochemical conversion of fuel gas (combustion, reforming) and solids (combustion,

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5 Spontaneous Raman Scattering Diagnostics: Applications in Practical Combustion Systems Jun Kojima and Quang-Viet Nguyen 5.1 Introduction

Practical combustion systems often require high power densities (energy per unit time per unit volume) in order to minimize the physical size and mass of the system. Aircraft gas-turbine engines achieve perhaps some of the highest power densities of any practical combustion system through the highly developed use of two basic principles: (i) turbulent mixing to decrease the effective fuel and air flow mixing time; and (ii) a high pressure to reduce both the chemical reaction time and physical size of the combustion chamber. In order to interrogate nonintrusively the chemical species concentrations and temperature (both scalars) in such systems, it becomes necessary to use an optical diagnostic technique that operates well at high pressures (in the order of 10 bar), while simultaneously being able to achieve high resolution in length (90%). If the anti-Stokes band is not of interest, then long-wave-pass filters will provide probably the best Stokes-edge steepness and highest transmission on the Stokes side. An alternative to these optical filters includes the atomic/molecular line absorption technique [43] or the use of a double-subtracting imaging spectrograph with a narrow wire optical mask [44, 45]. 5.4.2.3 Gating One of the most critical aspects of setting up a single-shot SRS diagnostic system is the temporal signal optical gating scheme. A short optical gate is necessary for weak SRS signals to be detected with a good SNR in the presence of a large amount of background optical emissions. It is clear from the data in Table 5.1 (see “Detection” data) that there are basically two options for gating: (i) an electronic means of gating using an ICCD; or (ii) an electromechanical optical chopper (rotary chopper wheels/ mechanical shutter combination). Many groups have chosen ICCDs for Raman scattering detection for their nanosecond gating capability and ease of implementation. However, the use of ICCDs for Raman diagnostics often means a compromise among image quality (or spectral resolution in spectroscopy), detector dynamic range, and noise. Because of the photon spread from proximity focusing in the internal fiber-optic coupling plate between the intensifier and the CCD array, the spatial resolution of the CCD array is compromised. Due to the image intensifier avalanche gain and space-charge effects, the dynamic range of ICCDs is limited to about 1000 : 1 (about 10 bits) for most practical applications. The SNR from photoelectron shot noise also increases with gain. It should be also considered that a smaller active imaging area (restricted by the internal fiber-optic plate, typically 18 mm diameter) or the unavailability of highresolution format ICCDs may limit the arrangement of measurements. In ICCD configurations, the anti-Stokes bands are often abandoned or sufficient spectral resolution cannot be achieved for closely spaced neighboring Raman lines such as CO2 versus O2. The relatively low actual dynamic range (or output saturation limit) of the ICCD can be problematic in cases where large differences exist in the signal intensity of one species compared to another (e.g., hydrocarbon versus CO2 in fuelrich flames). In fact, experience has shown that many that ICCDs are vulnerable to bright laser sparks or other inadvertent bright sources of light, and thus may be permanently damaged. Alternatively, a cooled and nonintensified, back-illuminated CCD (BI-CCD) detector can provide excellent detection when studying a combustion system with less optical background, especially when used in conjunction with a high-speed electromechanical shutter system to provide microsecond optical gating (see Figure 5.1). An example of such a shutter system is shown in Figure 5.5. The combination of digitally synchronized high- and low-frequency rotary optical choppers (custom 2- and 60-slot wheels) with a fast electromechanical leaf shutter can provide about 10 ms gate at repetition rates ranging from 1 Hz to 6 kHz [39]. Depending on the coupling lens optics in the shutter system and/or the wheel chopping effect, up to 60% optical transmission can be expected. With the shutter system, full advantage can be taken of

5.4 Designing and Building an SRS System

Figure 5.5 A high-speed electromechanical rotary shutter system [39]. (a) Perspective view of the assembly; (b) Timing diagram. Adapted from Patent No. US 6,937,331.

the high dynamic range (105 pe typical) and high quantum efficiency (QE; >90% typical) offered by BICCDs. When the photon counts of the Raman scattering being collected is lower than the readout noise level of the CCD (20 pe 1 typical), an electron-multiplying CCD (EMCCD) represents a superb replacement as it offers a significant all-electronic gain (up to 1000-fold) after the CCD pixel, without increasing the readout noise. This essentially permits single-photon detection similar to

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ICCDs, while preserving the high spatial resolution, dynamic range, and robustness of the BICCD. When a nonintensified CCD detection coupled with the high-speed rotary shutter is employed, the timing control of the electronics must be optimized. An example of a timing control scheme is shown in Figure 5.6. In this example, the first delay generator (master control) triggers the second delay generator, which instantly fires the Nd:YAG laser flash lamp, followed by the QS trigger for full-energy laser pulse emission after the typical QS delay (about 200 ms). This laser flash lamp trigger also enables the CCD exposure gate to open and remain so for several milliseconds, although the actual exposure is controlled by the high-speed shutter. At the same time, the master delay generator controls the mechanical shutter system by sending

Figure 5.6 Timing control of an electromechanical shutter-based Raman system. (a) Hardware connection; (b) Typical delay generator parameter setting. Note: The manufacturer names and model numbers are provided for accuracy, and are not an endorsement.

5.4 Designing and Building an SRS System

various TTL (transistor-transistor logic) signals to operate the optical chopper drivers in a phase-locked loop mode in synchronization to the master delay generator. The master delay generator also controls the electromechanical leaf shutter with optimized delay parameters, as shown in Figure 5.6b. Figure 5.7a shows a simple method for verifying and optimizing the timing overlap between the excitation laser pulse and shutter gate, and also for optimizing the shutter performance with regards to timing jitter and other effects. In this example, the pulse timing is observed by detecting laser scattering off the surface of any optics in the excitation optical train or a beam dump, while the gate signal (gate opening window) is simultaneously monitored. The temporal delay adjustment on the delay generator(s) optimizes the gate timing, such that a maximum transmission of scattering through the shutter system can be achieved. This is confirmed by monitoring all signals on a fast oscilloscope, as shown in Figure 5.7b. The above high-speed shutter timing set-up and verification process are critical to ensure maximum SRS signal temporal throughput.

Figure 5.7 Schematic of the temporal detection system showing the timing overlap between excitation laser pulse and electromechanical gating. (a) Timing overlap

validation test set-up. PD ¼ photodiode; PMT ¼ photomultiplier tube; LD ¼ laser diode; DG ¼ digital delay generator; (b) An ideal timing overlap.

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Figure 5.8 Raman spectra of room air captured by different CCD detectors. (a) Back-illuminated cooled ( 70  C) CCD with an electromechanical shutter; (b) Electron-multiplying CCD ( 70  C) with an electromechanical shutter; (c) Image-intensified CCD ( 40  C) with its electronic gating.

Figure 5.8 shows a comparison of the Raman spectra of room air (532 nm excitation at 400 mJ per pulse) captured by the three types of CCD detection system discussed above. Although this comparison does not take any optical background into account, a good potential of the mechanical shutter-based EMCCD detection for a single-shot measurement can be seen. In this particular example, the signal increase above the readout and shot noise is seen when EMCCDs for signal gain or ICCDs for image-intensifier gain are used. It should be noted that these gain settings must be optimized and set at the lowest possible gain, because further increases in the gain above the optimum level will actually not improve the SNR but only serve to sacrifice the dynamic range. Regardless of the type of gating method, the laser-generated optical background (e.g., PAH-LIF) may remain problematic if such phenomena are intense enough to interfere even within the nanosecond gating window. To this extent, “interference-free” Raman techniques have been proposed [46]. An attempt was also made to apply this principle to the real-time isolation of highly polarized Raman scattering from unpolarized LIF signals on a single-shot basis [32]. This

5.4 Designing and Building an SRS System

polarization-resolved Raman technique could potentially provide a solution to visibleRaman applications to the environment of very strong background or spray combustion. However, in this case a burden of reduced optical throughput (typically >50% loss at the polarizer) is anticipated. It is important to remember that individual requirements unique to each experiment ultimately determine the selection of a detection scheme with the trade-offs described above. One key determining factor here is the existence or nonexistence of unavoidable intense flame emissions in the background signal of the experiment. 5.4.2.4 Optical Calibration There are two calibrations necessary on the optical system for quantitative multiscalar measurements, namely wavelength calibration and spectral response calibration: .

.

A wavelength calibration of a spectrograph/CCD system can be performed routinely using a conventional Hg/Ar lamp. This calibration is absolutely necessary for a frequency-domain Raman thermometry technique to be successful [42]. For a spectral response calibration, a high-quality optical integrating sphere fitted with a traceable-standards calibration lamp (typically a halogen lamp) is most useful for accurately characterizing the spectral response of the SRS optical system in absolute spectral radiance units. A large output aperture of such an integrating sphere permits the calibration of the whole optical train, including the collection optics. If this type of setting is not accessible, then a compact calibration standard (e.g., optical fiber-coupled) can be used alternatively, albeit with reduced accuracy if the final collection lens cannot be used. This spectral calibration is especially critical for vibrational Raman thermometry using the N2 Stokes/antiStokes ratio, because there may be considerable differences in optical throughput and detector response between the anti-Stokes N2 band at 475 nm and the Stokes band at 607 nm. According to authors’ experience, differences of hundreds of Kelvin in the measured temperature could result when spectral response calibrations were omitted.

5.4.3 Data Reduction 5.4.3.1 Raman Signal Calibration As shown in Equation 5.1, the Raman scattering calibration is what essentially allows the SRS signals to provide species molecular number density information. Because of the existence of spectral crosstalk between neighboring species, an important part of the SRS calibration procedure is formulation of the calibration matrix (see Section 5.2). An example of the overall calibration procedure is shown in Figure 5.9. This process begins with the building of a spectral data library, which is effected by collecting Raman spectra (from 450–700 nm for anti-Stokes/Stokes measurements with 532 nm excitation) in “calibration-standard” burners of different fuels (H2, H2/CO, CH4, prevaporized liquid fuel, etc.) over a wide range of

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Figure 5.9 A flow chart for SRS signal calibration (example).

equivalence ratios and temperatures. From Equation 5.1, Si is defined by the signal collected over a superpixel area for each major species (H2, N2, O2, CO, CO2, H2O, and HCs). Each of these superpixel signals collected for different fuels at various conditions of fuel equivalence ratio provides the information for temperature variation. The temperatures are acquired typically from the pure-rotational or

5.4 Designing and Building an SRS System

vibrational SRS thermometry techniques (or Rayleigh thermometry if permitted). From these measurements, it is possible to obtain the temperature, T (spectroscopic), in each flame condition. This temperature can be validated or corrected later via the ideal gas law assumption (thermodynamic) with mole fractions of major species. With the experimentally measured temperature, the number density, Nj, of major species at a given equivalence ratio of a particular fuel–air mixture can be obtained by chemical equilibrium calculation, using the chemical equilibrium with applications (CEA) code or equivalent [47]. Plotting a nonlinear relationship between the number density of a molecule, j, and the SRS signal intensity of a superpixel for the molecule i (i.e., Nj/Si) over a range of T results in a temperature-dependent function (via polynomial fitting), which gives one element of the calibration matrix. This nonlinear plotting would determine diagonal (self, i.e., i ¼ j) and off-diagonal (crosstalk, i.e., i „ j) elements of the molecular species, thus completing the matrix calibration constant kij(T) used in Equation 5.1. When the calibration matrix has been successfully completed it can be applied to single-shot SRS measurements in the combustor of interest. With simultaneous measurements of Si and T, the inverse matrix, kij 1 ðTÞ will then convert the single-shot SRS signals (superpixels) into the number density (thus mole fraction) (see Ref. [23] for more details). 5.4.3.2 Calibration Burners To derive H2-related matrix elements (including its crosstalk) onto H2O or CO2 (rotational H2 lines) and other species, H2–air flames are typically used. H2/CO–air or CH4–air flames are also used to obtain carbon-containing matrix elements including O2 crosstalk onto CO2 (and vice versa) and N2 crosstalk onto CO (and vice versa). However, because of the relatively intense flame emission background (mostly CO2 chemiluminescence), stoichiometric or fuel-rich H2/CO flames may not work well with the mechanical shutter-based Raman apparatus. Most practical combustors use higher-hydrocarbon fuels (e.g., aviation fuels), the calibration parameters (including the kij elements) for which should also be measured in the calibration flames upon gas phase. The calibration experiments may require a separate optical diagnostic calibration facility, or the temporary modification of the combustor section in order to accommodate a calibration burner. With regards to the selection of a calibration burner, a water-cooled sintered-metal premixed burner (McKenna flatflame burner [51]) or a near-adiabatic-temperature staggered-array nonpremixed burner (Hencken burner [52] or simple honeycomb burner) can be used with different types of fuel. Alternatively, a back-side impingement cooled (no watercooling used), premixed matrix burner [23] could be employed, thus avoiding the problems of making major modifications of the test section. In this burner, the premixing of fuel and air takes place in a small cavity just beneath the burner nozzle. To the present authors’ knowledge, it is the only burner that enables fully premixed H2–air experiments at high pressures. Although, unfortunately, the burner run times at near-stoichiometric mixtures are limited to less than 30 s due to the threat of burner face overheating, it can be operated indefinitely at other equivalence ratios (w < 0.8 and w > 1.2). Although the temperature would be reduced, McKenna-type burners with H2–air or CH4–air mixtures are probably suitable for benchmark tests for the

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validation of Raman thermometry because of the availability of well-accepted reference data and the excellent burner reproducibility for these simple gaseous fuels. As many practical combustion systems function with nonpremixed highly turbulent flames, it is essential to have calibrations over wide temperature ranges, from the lowest to highest possible flame temperatures (i.e., adiabatic), and it is for this reason that calibration burners with a minimum heat loss to their burner surface (i.e., non-water-cooled systems) are preferred. Due to the insignificance of pressurebroadening at pressures below 30 atm [16], atmospheric pressure testing is accepted for the calibration experiments. In addition to these calibration experiments, computer simulations of Raman spectra of major species [16, 17] can be supplemental to the data library, and in some cases minimize experimental effort. 5.4.3.3 Data Processing The post-processing of measured single-shot SRS spectra often begins with data smoothing (e.g., Gaussian lowpass filter) to remove random shot noise, before subjecting to the inverse matrix calibration. Parameters (e.g., averaging over window) of smoothing algorithms should be carefully chosen so that small spectral features such as CO2 crosstalk onto O2 are not inadvertently smoothed out. Occasionally, the intense spark emission due to a laser-induced breakdown overwhelms the Raman signals, and thus disqualifies some single-shot events from further reduction process. Such data should be eliminated by setting a certain threshold at a Raman-free region of the spectrum. The background baseline of the spectrum can be defined by shot-by-shot noise in appropriate Raman-free regions. If the baseline should be described in a nonlinear form depending on the Raman apparatus employed (a mechanical shutter-based system tends to have more background), the fuel–air mixture conditions of flames, and pressure, and so on, then some spectral deconvolution and/or interpolation methods may be required. After this “clean-up” process, with the calibration inverse matrix given, the Raman signals of the major species are converted into the molecular number density vector, Ni (given in units of molecules per cm3 or mole fraction) via Equation 5.1, as illustrated in Figure 5.9. The measured mole fraction of the major species may be used in an iterative approach to feedback to the estimated ideal law-based thermodynamic temperature [20] for validation of the directly measured (spectroscopic) temperature. 5.4.3.4 Example of Multiscalar Data in Practical Combustion Systems Figure 5.10 shows a time-averaged SRS spectrum captured in a nonpremixed turbulent methane–air flame at a fuel-rich condition at elevated pressure. It is evident that there are spectral interferences or crosstalk between CO2 and O2 while N2, CH4, and H2O are separated spectrally. Hence, it is necessary to apply the calibration matrix formalism discussed in the previous section. Figure 5.11 shows an example of point-wise single-shot SRS measurements in a high-pressure (5 bar) swirl-stabilized methane–air flame. This burner platform is based on a lean-direct injection model [8] that is adaptable to a multiple-point fuel injector (e.g., nine injector cups integrated in a 3  3 format) fitted into a low-

5.4 Designing and Building an SRS System

Figure 5.10 A 200-shot averaged ro-vibrational Raman spectra (532 nm excitation), observed in a swirl-stabilized methane–air flame at global equivalence ratio of 0.56 at moderate pressure (5 atm).

emission combustor design. SRS measurements were made at various locations, including a post-flame zone and recirculation zone. As shown in Figure 5.11, three-scalar correlations of fuel (CH4), oxidizer (O2), and temperature are presented in scatterplot diagrams. From Figure 5.11, it is evident that there is distinct difference between the two scatterplots as a result of turbulent–chemistry interactions occurring in these two regions. The top scatterplot indicates relatively homogeneous, well-reacted condition of post-flame zone evidenced by fewer variations in temperature distribution and very low methane concentration. In contrast, the bottom scatterplot, measured in the region that was thought to be highly turbulent, shows a large scatter in all dimensions. These large variations in the three scalars clearly indicate the profound effect of unsteadiness of mixing and reactions in this region. In particular, low-temperature points with high oxidizer concentrations infer a significant amount of unburned fuel/air mixture (cold pockets), which suggests a large degree of incomplete combustion around the edge of this flame. These results show the details of nature of the turbulent mixing and its impact on chemical reactions in a realistic direct-injection flame at elevated pressure. It should be noted that, due to a lack of complete major species data at the time of these measurements, a simpler form of the calibration matrix was adopted using a linear non-temperature-dependent crosstalk rate with calibration factors based on cold gas flows. The temperatures were determined through a rotational Raman bandwidth method by taking advantage of the intense rotational bands in the single-shot spectra measured. A detailed discussion of these data is available in Ref. [8].

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Figure 5.11 Multiscalar scatterplots of fuel (CH4), oxidizer (O2), and temperature, analyzed from 400 single-shot data measured in a 5 atm swirl-stabilized methane–air nonpremixed flame.

5.4.4 Flow Controller System Design 5.4.4.1 Flow meters Whilst individual research and development (R&D) needs ultimately dictate the design requirements of any combustor or its model burners to be investigated, certain practical aspects must be considered when designing a flow control system to be used in research-quality high-pressure combustion systems. Such consideration is described in the following sections. The design and construction of the test burner and its associated flow control system involve many steps with many complications and trade-offs. In the past, many R&D high-pressure combustion systems have relied on the use of thermal conductivity-based mass flow controllers to regulate and meter the flow of various gases [29]. Although these systems are convenient to implement

5.4 Designing and Building an SRS System

and often function very well, they are nonetheless prone to calibration drifts and other causes of inaccuracies [25]. The biggest limitation of thermal conductivity mass flow meters relates to their limited dynamic range, with a typical 50 : 1 turndown ratio. Often, research burners must be operated over a wide range of equivalence ratios (from lean blow-out to super-fuel-rich) and flow rates in order to provide informative data. It would seem that the use of multiple parallel-flow thermal conductivity mass flow meters in staged flow paths to extend the dynamic range would solve this problem. However, the calibration drifts (which can be thought of as a bias drift) between the different mass flow meter ranges will often result in a less than optimal performance. In an effort to move away from calibration-based flow measurement methods, staged dynamic-range orifice plate-type flow meters have been successfully used on Bunsen-type flames [20]. The idea of using staged critical-flow orifice meters was successfully demonstrated on atmospheric turbulent jet flames by connecting three different ranges of critical-flow orifice meters together, using a manually selectable manifold of valves [48]. By using this type of a staged-flow controller system, a wide dynamic range up to 8000 : 1 is possible (assuming a typical 20 : 1 turn-down ratio for a single orifice, with a geometric progression of flow ranges 20 : 400 : 8000), while maintaining the inherent accuracy of the orifice meter in use (typically better than 0.5% full-scale). This type of flow controller system does not depend on thermal conductivity calibrations because it is based upon a fixed orifice diameter. A highly accurate and precise pressure measurement is common to all orifices, and a temperature measurement is also needed to fully determine the flow rate, although this is trivial when highly accurate thermocouples are placed in the flow paths. The additional advantage of this type of flow system is that the mass flow rate downstream of the orifice is independent of the burner backpressure variations, as long as the flow is maintained in a critical-flow (sonic) condition. This is an extremely important advantage from the basis of minimizing flow rate variations in high-pressure combustion systems, where the chamber backpressures are often quite variable. When developing a flow control system, a three-stage electronically switched critical-flow venturi design was used that had excellent accuracy and precision, and also was free from the electronic calibration drifts for high-pressure combustion systems that can accommodate a high-output pressure (up to 60 bar), a wide variety of gases, and a wide range of flow rates [49]. The choice of a critical-flow venturi rather than an orifice plate permitted the additional advantage of excellent pressure recovery (up to 95%) of the gas flows, which was an important consideration for high operational efficiencies when bottled cylinder gases were used. The high operational efficiencies were achieved by maximizing bottled gas usage between cylinder refills. When designing and building this type of flow control system, the selection of the pressure regulators and transducers for maintaining and measuring the upstream pressure of the flows is also an important consideration. Both of these components should be selected by careful consideration for their quality, accuracy, precision, and reliability. The other advantages of using critical-flow elements such as orifices and venturis are: (i) that the elements do not go out of calibration (assuming that there is

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no mechanical wear); (ii) when changing gases, new calibrations are not needed; and (iii) scaling factors for different gases are readily available. 5.4.4.2 Flow Control Software Another important consideration when designing flow control systems is the use of an automated software control system to operate the valves of the switching manifold, to control the electronically controlled pressure regulator, for the acquisition and data logging of the pertinent flow variables, and – most importantly – for the automatic shutdown of the flow system in the event of an emergency. Perhaps the most effective and reliable way to achieve these needs is to use an industrial-grade programmable logic controller (PLC). Although non-PLC-based data acquisition and control software packages can permit a similar level of operation, for critical applications that involve the flow of combustible gases and high-pressure combustion chamber rig operations, and where the loss of human life or damage to mission-critical assets is of major concern, the use of an industrial PLC will provide an enhanced level of safety and reliability. This is due to the fact that such controllers are designed for missioncritical 24/7 operation, and have shutdown sequences programmed internally into the firm-ware. Personal computer-based control systems that employ software are prone to lock-ups, spontaneous reboots, and other operating system errors. The flow control system used by the present authors was an industrial PLC system with over 100 possible automatic shut-down combination sequences based on sensor or transducer triggers from burner or rig over-temperature, rig over-pressure, lack of test cell ventilation, and/or detected fuel system leaks [49].

5.5 Outlook

As previously discussed [25], simultaneous measurements and imaging techniques (either one- or two-dimensional) represent a growing trend in multiscalar diagnostics for laboratory-scale flames. While this trend is becoming increasingly popular, there are other demands unique to realistic high-pressure combustion systems for which these methods are not practical. Because of the practical constraints discussed here, it is likely that point-wise single-shot multiscalar diagnostics, which are capable of providing data of the greatest accuracy and precision, will continue to serve the combustion community and play an important role in CFD code validation for practical combustion systems. It will also be interesting to develop multiscalar diagnostics including SRS and LIF (such as OH or NO), using a minimum number of excitation lasers and detection systems, while providing maximum flexibility. One alternative might be to use a single Nd:YAG laser to simultaneously pump both UV optical parametric oscillators (OPOs) for LIF and to provide excitation for SRS. This fundamental need to keep things simple for practical applications will most likely encourage advancements in fiber-coupled SRS diagnostics and the clever arrangement of multipurpose detection for monitoring the pulse-to-pulse energy variations of excitation lasers in the same Raman detection system by using a

5.6 Summary

wavelength conversion technique. Technological jumps in non-image-intensified gating systems, including faster mechanical shutters or all-electronic light gating with nanosecond-gated fast-frame transfer CCDs, will surely take SRS diagnostics for combustion to a new level. Yet, for combustion systems where particulate contamination is not a problem, a combination of point-wise single-shot SRS measurements coupled with point-wise 2-D or 3-D nonseeded spectral-shift velocimetry methods to characterize turbulent flow fields might be used [50] to truly characterize the chemical species, temperature, and flow fields at the one time. In particular, challenges remain for two-phase reacting flow applications such as aviation jet fuel combustion, where the conditions and existence of liquid fuel droplets pose a serious challenge to quantitative SRS measurements. In such two-phase combustion, the conditional sampling of multiscalar information will be necessary unless the presence of fuel droplets may be indicated, although this of course will have the effect of introducing bias to the resulting data.

5.6 Summary

In this chapter, the recent advancements and practical aspects of laser SRS diagnostics have been reviewed with regards to applications in practical combustion systems. Clearly, SRS represents a theoretically and experimentally mature diagnostic technology that has become an essential tool for multiscalar measurements in turbulent combustion at elevated pressures. Today, time-, space-, spectrally, and even polarization-resolved SRS diagnostics is at hand, with aid from recent innovations in theoretical and technological developments on electro-optical or electromechanical devices. Whilst a linear increase in SRS signals can be expected in high-pressure systems (this is perhaps one of the most important advantages for using SRS in highpressure systems), there are practical (often severe) restrictions associated with pressurized vessels, due mainly to the limited degree of optical access. This narrows the available choice of diagnostics that can be employed at any given time. Point-wise SRS diagnostics provides the highest accuracy on the chemical species and temperature measurements, and will continue to remain a vital approach for the study in such harsh environments. The practical design considerations and hands-on set-up guide for SRS diagnostics provided in this chapter are rarely presented elsewhere. Although the second-harmonic Nd:YAG pulsed laser (532 nm), combined with pulsestretching optics or the recently introduced White Cell-based laser, seems to be the most favored excitation source of choice by the research community, UV excitation will undoubtedly continue to be used on many occasions, and especially in sooting flames. Detection methods may be divided into ICCD-based nanosecondgate detection or a rotary-chopper electromechanical shutter-based CCD array detection, and the levels of background flame emission in individual cases would determine this critical design choice. Here, a process of Raman signal calibration based on the crosstalk matrix formalism was explained step-by-step. As this process may be very time-consuming and expensive, a well-planned experimental approach

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for building a transferable calibration database or library (at least within a user’s own facility over a series of different testing and runs) is vitally important. Hands-on advice on the design and construction of flow control systems for high-pressure burner facilities were also presented.

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46 Gr€ unefeld, G., Beushausen, V., and

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Andresen, P. (1995) Interference-free UV-laser-induced Raman and Rayleigh measurements in hydrocarbon combustion using polarization properties. Appl. Phys. B -Lasers Opt., 61 (5), 473–478. Gordon, S. and McBride, B.J. (1994) Computer program for calculation of complex chemical equilibrium compositions and applications – I. Analysis. NASA RP-1311. Available at: http://www.grc.nasa.gov/WWW/ CEAWeb/ceaHome.htm Muss, J.A.,California Univ., Berkeley; Dibble, R.W. (1994) A helium-hydrogen mixture for the measurement of mixture fraction and scalar gradient in nonpremixed reacting flows. AIAA-1994-612, Aerospace Sciences Meeting and Exhibit, 32nd, Reno, NV, January 10–13. Kojima, J. and Nguyen, Q.-V. (2003) Development of a High-Pressure Gaseous Burner for Calibrating Optical Diagnostic Techniques. NASA Technical Memorandum 2003-212738. Bivolaru, D. and Danehy, E.(Jan. 9–12 2006) Single-pulse multi-point multicomponent interferometric Rayleigh scattering velocimeter. AIAA-2006-836, 44th AIAA Aerospace Sciences Meeting and Exhibit, Reno, Nevada. Sutton, G., Levick, A., Edwards, G., and Greenhalgh, D. (2006) A combustion temperature and species standard for the calibration of laser diagnostic techniques. Combust. Flame, 147, 39–48. Kulatilaka, W.D., Lucht, R.P., Hanna, S.F., and Katta, V.R. (2004) Two-color, twophoton laser-induced polarization spectroscopy (LIPS) measurements of atomic hydrogen in near-adiabatic, atmospheric pressure hydrogen/air flames. Combust. Flame, 137, 523–537.

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6 CARS Spectroscopy Michele Marrocco 6.1 Introduction

Today, much of the research in science and technology relies on laser diagnostics. Indeed, among the many techniques developed over the years (see Refs. [1, 2] and Chapters 1, 5, 7, 8, 10 and 15 of this volume), coherent anti-Stokes Raman scattering (CARS) is undoubtedly one of the pillars supporting the vast and yet fairly recent field of spectroscopic applications to combustion. Within the community of this field, it is common knowledge that the popularity of CARS is ascribable to the high level of accuracy as to thermometric measurements. Such a distinguished sensitivity to temperatures has its physical roots in the statistical behavior of the molecular population occupying the energy levels probed in the spatial region where the molecules cross the focused laser beams. In other words, different temperatures result in different population distributions that are encoded in the optical response measured by means of spectroscopic techniques [1]. Despite this remarkable feature, CARS spectroscopy is less manageable than might appear at first glance, with many subtleties accounting for the difference between misleading and reliable understanding of CARS spectra. However, if a cautious approach is taken then the technique constitutes a sound tool for thermometry with unrivaled uncertainties that may be as low as 10 K at flame temperatures! The physical basis of CARS resides in two cornerstones of optics, namely Raman scattering (see Chapter 5 and Ref. [1]) and coherent emission. The former regards the spectral rearrangement of a light beam, the radiation of which is partially displaced at wavelengths that differ from those that characterize the original beam. For historical reasons, positive displacements are termed Stokes shifts, whereas negative displacements are called anti-Stokes. Coherent emission is instead responsible for the coherent properties of CARS (i.e., spatial directionality, conservation of field polarization and energy gain at the anti-Stokes wavelength). These phenomena can be explained as follows. According to the classical picture of CARS, it has to be imagined that the molecules mimic the behavior of oscillators. When a specific mixing of wavelengths (three, in case of a CARS process) occurs within a Raman medium, its

Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright Ó 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

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molecules begin to oscillate in agreement with the resultant electrical polarization induced by the field mixing. By choosing the laser wavelengths in such a manner that a Raman resonance is selected, the constructive interference at the anti-Stokes wavelength emitted by the molecules (oscillating in phase) generates the final signal. This very intuitive view of CARS has been further investigated in both books [1–4] and reviews [5–7 and M. Marrocco, unpublished results], and for this reason many aspects of optical physics required to fully understand the generation of CARS signals will not be discussed at this point. Rather, the perspective of this chapter is oriented towards practical features related to the actual measurements and their interpretation. This standpoint will be particularly appreciated by the nonspecialist (i.e., engineers, technicians and general research workers in combustion), towards whom the Handbook is mainly directed. As a consequence, the basic notions of molecular physics necessary to deal with laser spectroscopy of gas phases will be minimized. Nonetheless, it is possible to anticipate that a typical CARS set-up involves the use of three laser beams at wavelengths that can be dissimilar from each other or, more easily, with two of them obtained from the same source (referred to as “degenerate CARS”). The coupling of such wavelengths is mediated by the third-order nonlinear susceptibility xð3Þ [1, 3–7]. This quantity measures the optical response of the medium to the polarizing action exerted by the laser fields, and incorporates the fundamental dependence of the molecular population distribution on temperature. The role of xð3Þ is thus crucial, because it is the nonlinear susceptibility that makes possible the generation of a coherent signal at the antiStokes frequency vaS. In general, if the spectral outcome of a CARS measurement is dictated by the target molecule, the combination of laser frequencies makes a reasonably large choice. As noted above, the simplest solution is such that two frequencies are from a common source (a single powerful laser), whereas the third (or Stokes) frequency is taken from a spectrally broad laser system (referred to as “degenerate multiplex” or “broadband” CARS). Although sufficiently easy to implement, this solution is usually adopted to probe one constituent at a time and, in order to overcome such a disadvantage, more complex set-ups based on multicolor approaches have been introduced in the past [1]. In any case, the determination of the entire CARS spectrum can be completed within the time resolution of a single laser pulse (typically around 10 ns or even down to the femtosecond scale); this is opposed to scanning CARS, where pump and Stokes lasers are narrowband and the latter is progressively scanned across the relevant Raman shifts. Each of these aspects will be outlined in the chapter, in which the fundamental mechanism that justifies the use of CARS as a thermometer will first be revised, after which attention will be focused on some of the main elements needed to interpret the experimental data. The methods by which these are obtained is then described, and some details of possible set-ups are sketched. The basic example of nitrogen CARS is then reported and, next, the discussion broadens to conceptual advances that have paved the way for some remarkable applications. Finally, an outlook is provided of the current state and future perspectives of CARS.

6.2 Theory: Why is CARS So Sensitive to Temperature?

6.2 Theory: Why is CARS So Sensitive to Temperature?

Perhaps the first question related to combustion science that should be asked concerns the reasons why CARS is so effective with regards to the remote sensing of high gas temperatures. The answer begins with the nonlinear susceptibility that enters the CARS signal ICARS , which traditionally is written as a simple product of two degenerate monochromatic pump lasers of equal spectral intensities
1 Þ ¼ L2 ðv
2 Þ (where v
1 ¼ v
2 ), with a Stokes laser of spectral intensity LS ðv
S Þ [1]: L1 ðv
1 v
S Þj2 ½L1 ðv
1 ފ2 LS ðv
SÞ ICARS ðva Þ ¼ C jxðv

ð6:1Þ

Here, C is a proportionality constant and x is the nonlinear susceptibility
S between the pump frequency v
1
1 v depending on the frequency difference v
S (note that the superscript in the notation for the and the Stokes frequency v nonlinear susceptibility has been removed for simplicity). The squared modulus in Equation 6.1 is at the core of CARS spectra, because the molecular response is incorporated in x, whose expression, in its basic form, is xðv1 vS Þ ¼

X j

aj

1 Vj ðv1 vS Þ iCj

ð6:2Þ

The summation runs over the possible Raman transitions identified by the Raman shifts Vj and linewidths Cj (namely, the half-widths at half-height). The factor aj denotes the strength of the associated j-th transition, and takes in the dependences on the population difference and the Raman cross-section. The explicit expressions of Vj , Cj , and aj can be found in many reports [1, 3–7] and, for this reason, they are not given in this context. However, for the purpose of the present argument, it must be mentioned that the main connection to temperatures is due to the population difference drj that appears linearly in the factors aj (the secondary, less-important, connection is through the linewidths Cj ). Central to the role of drj in the detected signal ICARS is then the population distribution among the energy levels involved in the molecular transitions activated by the thermal energy kB T. Typically, the factor kB T is slightly greater than 200 cm 1 at room temperature (note that the spectroscopic energy unit of cm 1 corresponds to 1.24  10 4 eV), but the thermal excitation can be significantly higher and may reach about 700 or almost 1400 cm 1 (i.e., 0.0862 or 0.172 eV,) at flame temperatures of 1000 and 2000 K, respectively. The key fact is that these values of thermal energies are sufficiently high to match the energy differences between rovibrational levels. In other words, the temperature can reshape the partitioning of the total number of molecules among the energy levels pertaining to the quantum description of molecular oscillations and rotations. This means that oscillations and rotations in molecules of interest for combustion studies can form the basis of a thermometric diagnostics. Since drj is dominated by the lower-level , it is possible, loosely speaking, to exemplify the dependence of populations rlower j Þ2 . It should be noted ICARS in Equation 6.1 with a simple relationship ICARS / ðrlower j that this quadratic law is not strict; rather, it holds only for special cases and

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significant deviations could be found [1]. Nonetheless, it suffices to provide an intuitive picture of what happens. Having established the connection between the CARS signal and the molecular is reported for nitrogen in Figure 6.1, as a function of population, an example of rlower j the rotational level J. Three different temperatures (T ¼ 300, 1000, and 2000 K) are compared, and it is immediately evident how the general shape of the population distribution can be considerably affected by the temperature. Its increase is reflected in a spreading of the population and a simultaneous shift of the maximum toward higher energies (or higher rotational levels). This is the key point that enables CARS spectroscopy to be used as a reliable tool for thermometric applications. In other terms, what is seen in Figure 6.1 is mutated into spectra of ICARS , and it is up to the specialist to reverse the process (i.e., to extract the thermometric data from measured spectra). The way in which this is achieved is not straightforward, as the physics behind CARS is somewhat intricate and experimental data can be correctly interpreted after a careful patchwork of different pieces of information about the molecule under study. In order to provide the reader with information on this topic, the general theoretical problems posed by a CARS experiment are examined in the following sections.

Figure 6.1 Fractional population of rotational levels in nitrogen molecules at three different temperatures. Considerations of symmetry in the quantum-mechanical description of N2 make the fractional population of even-J rotational levels twofold higher than the population of odd-J levels.

6.3 Theory: Interpretation of CARS Spectra

6.3 Theory: Interpretation of CARS Spectra

The interpretation of CARS spectra deserves much attention, as it consists of a general theory that identifies the overall spectral structure of the CARS signal. However, many additions are required in order to determine the molecular parameters that best adhere to the case under consideration. Hence, the general aspects of CARS spectra will be reviewed at this point, and discussions relating to molecular parameters in a later section. First, the simplicity of Equation 6.1 would be preferred if it were possible to assume the monochromaticity of the laser beams. Although this condition is ideal, the assumption becomes acceptable for some rather sophisticated pump lasers (e.g., injection-seeded Nd : YAG lasers), the bandwidth of which is significantly smaller that the linewidth of the Raman resonances. More generally, pump lasers employed in CARS measurements have a finite linewidth, which is comparable to or larger than the Raman widths. It is then unavoidable to generalize Equation 6.1 to the reality of the laser beams. Fortunately, the detailed interpretation of spectral shapes of CARS measurements has been reported in several studies [8–14], illustrating the impact of finite laser bandwidths on CARS accuracy and reliability. The simplest reasoning would lead to the transformation of Equation 6.1 into an intuitive spectral convolution over the three laser profiles: ð ICARS ðva Þ ¼ K jxðv1 vS Þj2 L1 ðv1 ÞL2 ðv2 ÞLS ðvS Þ dðv1 þ v2 vS va Þdv1 dv2 dvS

ð6:3Þ

where the two pump lasers are still supposedly degenerate with equal central
1 ¼ v
2 , and the delta function guarantees the energy conservation, frequencies, v as summarized in Figure 6.2. The generalization in Equation 6.3 has its logic that can be followed in the extensive studies of Yuratich [8]. However, an a posteriori and straightforward evidence is that the traditional result of Equation 6.1 can be regarded as the limit of Equation 6.3 for degenerate pump lasers having very small spectral linewidths s1 and s2 . It is then not surprising that Equation 6.3 was commonly used in early CARS studies [7, 15, 16]. However, it was soon realized that interferences among the different spectral components of x had a relevant contribution to the CARS signal. This can be understood by examining the expression of the susceptibility in Equation 6.2, which incorporates the difference between the pump and the Stokes frequencies. However, the elementary CARS process of Figure 6.2 involves the action of two pumping fields and, consequently, the field mixing is complete only if the two spectral components of x are taken into consideration. One component depends on the difference v1 vS , and the other on the difference v2 vS . This heuristic argument forms the basis of a more complex convolution that was introduced during the 1980s to accurately interpret CARS measurements [9, 11]:

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Figure 6.2 Energy diagram for the transitions of a CARS process involving two excitations at pump frequencies v1 and v2, plus two disexcitations at the Stokes and anti-Stokes frequencies vS and vaS. The real molecular levels are indicated with solid lines, whereas

virtual states are represented by dashed lines. Note that virtual states do not correspond to real molecular states, in that the concept of virtual states is a commodity in the lexicon of the quantum-mechanical treatment of CARS processes [1, 3–5].

ð ICARS ðva Þ ¼ K jx12S j2 L1 ðv1 ÞL2 ðv2 ÞLS ðvS Þdðv1 þ v2 vS va Þdv1 dv2 dvS ð6:4Þ

where x12S ¼ xNR þ

1 1 x ðv1 vS Þ þ x2S ðv2 vS Þ 2 1S 2

ð6:5Þ

The first term on the right-hand side of Equation 6.5 is the so-called “nonresonant susceptibility,” which provides information about the background due to the Ramaninactive medium surrounding the target molecule. The other two terms of x12S give off the relevant CARS signal which, besides the multiplicity of vibrational–rotational Raman transitions, incorporates coherent phenomena between the spectral components accessed by v1 vS and v2 vS . At present, Equation 6.4 seems to be the most general expression for the CARS signal, and there is no evidence that the subject requires further treatment. Almost needless to say, the limit of Equation 6.4 for negligible background and degenerate pump lasers having very small spectral linewidths is once again Equation 6.1. As will become apparent shortly, the calculation of Equation 6.4 is not very easy. The customary method of devising a solution of ICARS ðva Þ is to break it up into four different pieces, as indicated below: ð ð6:6Þ I1 ¼ Kx2NR L1 ðv1 ÞL2 ðv2 ÞLS ðvS Þdðv1 þ v2 vS va Þdv1 dv2 dvS ð 1 I2 ¼ KxNR ðx1S þ x2S þ x1S þ x2S Þ 2 L1 ðv1 ÞL2 ðv2 ÞLS ðvS Þdðv1 þ v2 vS va Þdv1 dv2 dvS

ð6:7Þ

6.3 Theory: Interpretation of CARS Spectra

ð 1 I3 ¼ K ðx1S x1S þ x2S x2S Þ 4

ð6:8Þ

L1 ðv1 ÞL2 ðv2 ÞLS ðvS Þdðv1 þ v2 vS va Þdv1 dv2 dvS ð 1 I4 ¼ K ðx1S x2S þ x1S x2S Þ 4

ð6:9Þ

L1 ðv1 ÞL2 ðv2 ÞLS ðvS Þdðv1 þ v2 vS va Þdv1 dv2 dvS

where the asterisk stands for complex conjugate and x1S is given by Equation 6.2, whereas x2S is still Equation 6.2 with v2 replacing v1 . A first conclusion is that, even though the decomposition of Equation 6.4 in four pieces has simplified the problem, the integrals of Equations 6.6–6.9 cannot be solved unless the spectral shapes of the laser beams are specified. Fortunately enough, the solutions are analytical for important special cases, namely Gaussian or Lorentzian dependences [11, 13, 14]. This fortunate circumstance is very important for practical purposes, because Gaussian profiles are assumed to be very close to the lineshape of multimode lasers [6, 17]. The adjustment of this assumption to the CARS theory implies that h i Lp
p Þ2 =s2p ð6:10Þ Lp ðvp Þ ¼ pffiffiffi exp ðvp v psp


p indicates the central laser frequency, with p ¼ 1; 2 or S. In Equation 6.10, v
p =b is the normalized half-width with s
p being the actual half-width, and b sp ¼ s pffiffiffi pffiffiffiffiffiffiffi
p (i.e., b ¼ 2 or ln2). Finally, if is a constant which depends on the definition of s Lp is the laser intensity, then Lp ðvp Þ has the physical dimension of spectral intensity. The use of Equation 6.10 leads to the results h i 1
a Þ2 =s212S I1g ¼ Kx2NR L1 L2 LS pffiffiffi exp ðva v ps12S 1S I2g ¼

KxNR L1 L2 LS

ð6:11Þ

h iX 1
a Þ2 =s212S pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi exp ðva v aj Im½wðz1;j ފ 2 2 s2 s1 þ sS j

ð6:12Þ

1S ¼ I3g

h i 1 1
a Þ2 =s212S KL1 L2 LS pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi v exp ðv a 2 s2 s21 þ s2S 

X j;m

aj am Imfwðz1;j Þ=½Vm Vj þ iðCj þ Cm ފg

pffiffiffi h i 1 p
a Þ2 =s212S pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi exp ðva v I4g ¼ KL1 L2 LS 2 s1 s2 s21 þ s2S 

X j;m

aj am fRe½wðz1;m ފRe½wðz2;j ފ þ Im½wðz1;j ފIm½wðz2;m ފg

ð6:13Þ

ð6:14Þ

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with

z1;j

 2  s12S s1 þ s2S
a Þ Vj þ v
1 v
S þ iCj ðva v ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi s2 s21 þ s2S s212S

ð6:15Þ

 2  s12S s2 þ s2S


ðva va Þ Vj þ v2 vS þ iCj ð6:16Þ z2;j ¼ pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi s1 s22 þ s2S s212S pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
a ¼ v
1 þ v
2 v
S , s12S ¼ s21 þ s22 þ s2S and the subscript g refers to the where v assumption of Gaussian profiles. The function w appearing in Equations 6.12–6.14. is the complex error function wðxÞ ¼ expð x 2 Þerfcð ixÞ [18]. Note, however, that Equations 6.12 and 6.13 do not give the whole solution of Equations 6.6 and 6.7. The 1S 2S 1S 2S 2S 2S þ I2g and I3g ¼ I3g þ I3g , where I2g and I3g are complete solutions are: I2g ¼ I2g respectively obtained from Equations 6.12 and 6.13 by exchange of the indices 1 and 2 on their right-hand sides. The whole set of Equations 6.11–6.16. is very useful to understand the role played by different contributions to the CARS signal. For instance, if attention is turned towards the situation of negligible background (i.e., xNR ¼ 0), the signal is a sum of the main integral I3g plus the contribution of interference I4g , and the relevance of the latter might be questioned. In particular, it is possible to verify, by using simple algebra, that I4g is of minor importance only in the extreme of narrowband pumps (in this case I4g equals I3g ). A more advanced reasoning suggests that the condition of quasi-monochromaticity can be better viewed as the unitary limit of the function pffiffiffi ron ¼ pgj expðg2j Þerfcðgj Þ with gj ¼ Cj =s1 [19, 20]. The function establishes approximately the ratio between I4g and I3g for degenerate pumps mixed with a Stokes laser, the frequency of which is tuned to the j-th Raman resonance. From the plot of ron (see Figure 6.3), it is found that interference ceases to be problematic for gj > 5, that is for a laser linewidth that is more than five times smaller than the Raman width. In this operative range, the interference amounts to less than 2%, and is increasingly negligible for higher values of gj .

pffiffiffi Figure 6.3 The function ron ¼ pgj expðg2j Þerfcðgj Þ to determine the influence of the coherent term I4g with respect to I3g [19, 20].

6.3 Theory: Interpretation of CARS Spectra

Another delicate aspect of CARS analysis can be explored with the help of Equations 6.11–6.16., namely, the role of the Raman linewidths. In order to understand the importance of this topic, it should be emphasized that the spectral shapes are mainly dependent on the term appearing in Equation 6.13. This contains the most striking characteristics of the anti-Stokes signal. As a matter of fact, the imaginary part of wðzj Þ=½Vm Vj þ iðCj þ Cm ފ is    Im wðzj Þ= Vm Vj þ iðCj þ Cm Þ ¼

1 ðVm Vj Þ2 þ ðCj þ Cm Þ2

fðVm Vj ÞIm½wðzj ފ ðCj þ Cm ÞRe½wðzj ފg

ð6:17Þ

where Re½wðzj ފ is the well-known Voigt profile that is recurrent in laser spectroscopy. The lineshape behavior of Re½wðzj ފ is on the left side of Figure 6.4, and it is immediately clear that the CARS signature of a specific molecule is inscribed in the well-defined spectral peaks controlled by Re½wðzj ފ. Nonetheless, Equation 6.17 demonstrates that the spectral peaks of CARS measurements are not purely represented by the Voigt profile, unless they are largely spaced. Indeed, if the Raman widths are considerably smaller than the separation between the Raman shifts, then the overlap can be neglected and the terms for j 6¼ m discarded. In this case, Im½wðzj ފ does not significantly contribute to the summation of Equation 6.16. On the contrary, when there is some overlap, Im½wðzj ފ might have a meaningful contribution and the resultant profile differs from the function Re½wðzj ފ. In these circumstances, the contribution of Im½wðzj ފ deforms the symmetry of the spectral peaks because the imaginary part of the complex error function is responsible for the dispersion-like dependence displayed on the right-hand side of Figure 6.4. Finally, the other qualitative conclusion of Equations 6.11–6.16. is on the role of background appearing in Equations 6.11 and 6.12. Considering that Equation 6.11 is featureless (apart from the obvious Gaussian factor shared by all the intensities), the background in Equation 6.12 when importantly present contributes with Im½wðzj ފ, which once again introduces an additional odd symmetry (right-hand panel of Figure 6.4) in the CARS spectrum. As a conclusion, the role of background can be summarized in the dispersive character of Im½wðzj ފ that must be combined with the remaining terms of the whole signal.

Figure 6.4 Behaviors of RE[w(zj )] and Im[w(zj )] as functions of the detuning (i.e., frequency difference with respect to the jth Raman resonance).

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6.4 Molecular Parameters

Having briefly explained the spectral structure of the CARS signal ICARS ðva Þ, the problem is then faced of how to employ this to achieve an accurate reconstruction of experimental measurements. To that end, the central task is of course set by the determination of the molecular parameters, namely the Raman shifts Vj , the associated widths Cj and all of the remaining parameters included in the amplitudes aj . In general, the Raman shifts Vj are known from detailed spectroscopic calculations or measurements made for the specific CARS molecule in use. For example, Luthe et al. have revised the calculation of Raman shifts for some fundamental CARS molecules that are of interest in combustion science [21]. Another famous reference is the book of Huber and Herzberg [22]. Needless to say, the precise determination of Vj implies a deep knowledge of the molecular properties (rotational constant, vibrational frequency, high-order energy corrections such as centrifugal distortion, anharmonicities, vibrational–rotational coupling, and so on). It is, therefore, a matter of finding the most reliable source of information. Besides the Raman shifts that identify the spectral positions of the relevant spectroscopic transitions, the corresponding lineshapes are characterized by widths Cj that are not straightforwardly available. As seen in the comments about Equation 6.17, their role is fundamental in the accurate CARS modeling and, fortunately, the literature on the subject is vast. In principle, there are two prevalent mechanisms that influence the Raman linewidths. One is the Doppler broadening, that is easily determined by the Doppler effect caused by the thermal motion of the gas molecules [1, 6]. The other is the collisional (or pressure) broadening, which results from collisions between molecules of the same type, or with other constituents [1, 6]. At low pressures, the collisions are mitigated and the Doppler effect dominates the pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi line broadening. This is unambiguously determined by 2vj 2ln2kB T=m=c, with vj the jth transition frequency, m the molecular mass, T the temperature and c the speed of light. For very light molecules, however, the physical situation is not so clear, in that Doppler width is altered by Dicke narrowing as soon as the density increases [6, 23]. In contrast, at medium and high pressures the Doppler broadening becomes negligible and the spectroscopic lines are primarily collision-broadened. In this case, the physical situation is less simple than in the Doppler regime. Indeed, collisions that occur under the multiplicity of chemical species found in reactive mixtures have several contributions (as many as the number of the main constituents), and consideration should be given to all of the significant influences of collision partners. Recently, much progress has been made in this direction; for instance, the understanding of self-broadening data (caused by collisions within the same molecular species) is now available in terms of scaling laws [24–29]. These are semi-empirical models that formalize through simple relationships the dependences of self-broadening linewidth coefficients on pressure, temperature, and rovibrational state. This level of accuracy is usually sufficient to generate realistic CARS spectra of important molecules exploited for thermometric purposes, and it is not surprising that

6.4 Molecular Parameters

nitrogen, as a major constituent of air-fed combustion processes, is a very wellstudied molecule as to its pressure self-broadening [24–29]. Nonetheless, another line of research has been conducted to include the influence of other collision partners [30–33]. The case of pressure broadening is not only reduced to the calculation of linewidths. In reality, another physical phenomenon sets in whenever significant line overlap is present. The most simplistic view would erroneously lead to the thought that the linewidths would become progressively larger as long as the pressure increased. If this is true at very low pressures, then the simple correspondence between pressure and linewidths does not hold at higher pressures when line mixing effects complicate the shape of the spectral line. The phenomenon is termed collisional narrowing or motional narrowing [1, 6], and its incorporation into data analysis is important for many experimental conditions. Collisional narrowing has a pictorial explanation in terms of Fourier transform of time sequences of the fields emitted by molecules undergoing fast level jumps caused by collisions [6] the whole problem can be treated in a rigorous manner [6, 15, 27, 30, 34–38] and, in the following, the Gordon–McGinnis formalism (otherwise known as G-matrix formalism) [39] is explained, as adjusted to CARS by Koszykowski et al. [36]. According to this elegant approach, collisional narrowing results in a new form of the susceptibility [40], which can be rewritten under product of matrices, or x¼

N a G h

1

dr a

ð6:18Þ

Here, h is the Planck constant divided by 2p, N is the number density of the CARS molecule, a is the molecular polarizability, dr is the fractional population difference, and G 1 is the inverse of the matrix whose elements are Gjk ¼ djk ðVj v1 þ vS þ Dj iCj Þ þ ið1 djk Þcjk

ð6:19Þ

where djk is the Kronecker delta function, Dj is the spectral-line pressure-shift constant, and cjk indicates the linewidth parameter that contributes to the total P spectral width in accordance with Ck ¼ 2 j6¼k cjk . The key problem here is the inversion of the G matrix, but this can be achieved by rewriting the matrix as a summation of two terms, where one is the identity matrix multiplying the frequency difference, and the other encompasses what remains: G¼

ðv1 vS ÞI þ L

ð6:20Þ

At this point, the matrix L can be diagonalized by using its eigenvalues lj and eigenvectors. These are adjusted to form the matrix A and, in this fashion, the new susceptibility becomes x¼

1 N X ða AÞj ðA dr aÞj ðv1 vS Þ þ lj h j

ð6:21Þ

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and it appears immediately that by defining aj ¼ ða AÞj ðA 1 dr aÞj , vj ¼ Re½lj Š and cj ¼ Im½lj Š, an expression is obtained of the susceptibility that is formally identical to Equation 6.2. For this reason, all of the discussion developed for the interpretation of CARS spectra can be retrieved and applied to experimental cases where collision narrowing is present. On order to complete the analysis of the relevant molecular parameters, there is a need to consider what determines the amplitudes aj . Two such points are the main factors entering the amplitudes: one is the fractional population difference between the initial and final states drif ¼ ri rf , and the other is the molecular polarizability pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi related to the differential Raman cross-section, or aif ¼ ðc=vS Þ2 ðqs=qVÞ. The population difference drif takes into account the statistical partitioning of the number of molecules over their energy levels and, as anticipated in Section 6.2, this has a key role in light of the thermometric use of CARS. The important premise to calculate drif is that the Boltzmann statistics characterizes a situation of thermal equilibrium. Broadly speaking, the assumption is realistic for combustion processes, because nonequilibrium conditions are quenched very rapidly for both rotational and vibrational degrees of freedom. In this manner, vibrational and rotational populations can be evaluated according to the Boltzmann law; that is: rm ¼ gm expð Em =kB TÞ=Q

ð6:22Þ

where gm is the statistical weight of the state m of energy Em and the denominator Q is P the so-called partition function, given by Q ¼ m gm expð Em =kB TÞ. Details of these parameters are freely available, and the determination of drif is less problematic. The other crucial contribution to aj is represented by the Raman cross-section. This quantifies the response of a molecule to inelastic scattering of light, and it is composed of different terms. For diatomics and linearly polarized laser beams, the forward differential Raman cross-section is 

qs  v ! v0 4 hv4S 0 2 0 2 b < v; Jjcjv ; J> ¼ < v; Jjajv ; J> þ  J; J qV  J ! J 45 2ve c 4 M

ð6:23Þ

where Q-branch transitions have been taken in the matrix elements hv; Jjajv0 ; Ji and hv; Jjcjv0 ; J 0 i containing the polarizability tensor invariants a and c [1]. It might be recalled that Q-branch transitions are made of molecular transitions, where a change in the vibrational state is accompanied by no variation of the rotational level or DJ ¼ J 0 J ¼ 0 (note that other branches can be found in molecular spectra; for instance, P-branch and R-branch are defined by DJ ¼ J 0 J ¼ 1, or O-branch and S-branch by DJ ¼ J 0 J ¼ 2 [1]). In Equation 6.23, the Placzek–Teller coefficient bJ;J is known from various references, while ve is the vibrational wavenumber and M is the reduced mass. Additionally, the case of linearly polarized scattered light is considered through the factor 4/45. CARS is indeed a coherent process where the anti-Stokes beam tends to preserve the same polarization of the incident lasers.

6.5 Experimental Set-Ups and Phase Matching

The matrix elements in Equation 6.23 can be rearranged in such a manner that contributions of vibration–rotation interactions become manifest and the following is obtained:  0 v ;J < v; Jjajv0 ; J>2 ¼ Fv;J a2v;v0 ð6:24Þ a



0

v ;J

hv; Jjcjv0 ; Ji2 ¼ Fv;J



c

c2v;v0

ð6:25Þ

v0 ;J

where the factor Fv;J is the Herman–Wallis correction caused by the failure of the approximation of rigid rotor [41–43]. This factor has a twofold meaning, depending on its origin (i.e., whether it is derived from the isotropic component a or the anisotropy c of the polarizability). The other change in notation regards the purely vibrational matrix elements on the right-hand side of Equations 6.24 and 6.25. These have been denoted as av;v0 ¼ hvjajv0 i and cv;v0 ¼ hvjcjv0 i. By specifying the problem to the strongest band found for vibrational transitions with Dv ¼ v0 v ¼ 1, it is possible to set av;v þ 1 ¼ ðv þ 1Þa0 and cv;v þ 1 ¼ ðv þ 1Þc0 so that the differential cross-section is transformed into 

hv4S qs  v ! v þ 1 4 02 02 b a F ðJÞ þ c F ðJÞ ðv þ 1Þ ð6:26Þ ¼  a J;J c qV  J ! J 45 2v0 c4 M

where the superfluous indices of the Herman–Wallis factors have been suppressed for simplicity. On examining Equation 6.26, a first conclusion can be drawn: since a0 2 is usually of the same order of c0 2 , the variation in the differential cross-section caused by the vibration–rotation interaction is mainly due to the Herman–Wallis factor for the isotropic invariant a, that is Fa ð JÞ. This is particularly true for the highest rotational lines J, where the factor 4bJ;J =45 is close to its limit of 0.022. In this instance, it can be stated that the spectral intensity ICARS in the Q-branch rescales with the square of Fa ð JÞ only, or ICARS / Fa2 ð JÞ. This fact is fundamental to the CARS spectroscopy of hydrogen that was recently criticized in order to eliminate a source of misunderstanding about the role of the Herman–Wallis correction [41–43]. Having completed this short (and partial) summary of the theoretical framework necessary for the interpretation of CARS measurements, it might be thought that the handling of CARS data is rather difficult. Whilst this is true, there is sufficient knowledge of the various aspects to guarantee a high level of reliability. Furthermore, the information available with CARS – and especially the thermometric information – is so important in combustion science that the technical complexity cannot be made an excuse to avoid dealing with the problems that CARS raise, including the experimental difficulties that are introduced in the following section.

6.5 Experimental Set-Ups and Phase Matching

The definition of an experimental set-up suitable for CARS investigations depends very much on the specific aim of the study. In these discussions, reference will mainly

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be made to thermometry, which is the most common application of CARS to combustion science. In this instance, the typical experimental configuration consists of a single pump laser operated in conjunction with a broadband Stokes laser. However, CARS may also be useful for concentration measurements. As noted above, the susceptibility is proportional to the number density, and this fact could be used to determine simultaneously both temperature and concentration (this point will be returned to later in the chapter). In restricting these considerations to thermometry, it should be recalled that the initial CARS investigations were based on the ruby laser [44, 45], whereas the reference system of modern CARS thermometry is the frequency-doubled Nd : YAG laser [17], which can be operated in either single- or multi-mode regime with powerful pulses of about 10 ns at 532 nm in both cases. In single-mode operation the spectral purity is guaranteed by linewidths lying below 0.01 cm 1 (or 2.5  10 4 nm at a wavelength of about 500 nm). This is not the case for multimode operation, where typical linewidths are on the order of 1 cm 1. In degenerate configurations, where the second harmonic of a Nd : YAG laser is used to create two identical pump frequencies (ca. 18 797 cm 1, in wavenumber units), the Raman resonances can be easily reached by means of dye lasers [1, 46]. These are pumped by fractions of the energy of the Nd : YAG pulse at 532 nm, and the whole system can be run with repetition rates no higher than a few tens of pulses per second. Three methods are used to adjust the dye spectrum in the desired spectral range. First, the gross choice is represented by the selection of the dye, with finer adjustments being given by the choice of dye solvent and the dye concentration (occasionally, binary dye mixtures are employed to enlarge the spectral range). Depending on whether the measurement is aimed at a high spectral resolution or a fast acquisition time, the Stokes dye laser is, respectively, in narrowband or broadband configuration. In the first scheme, the Stokes emission is tuned across the Raman resonances, and the high spectral resolution is limited only by the linewidths of the laser beams. This type of operation is often referred as “scanning CARS,” and is usually adopted in those stationary combustion environments that are not altered during the acquisition time of a spectrum. Broadband Stokes radiation is instead employed in the presence of any concentration or temperature instabilities. This is self-evident, in that the generation of a CARS spectrum is made within the time frame of the Nd : YAG pulse such that, at least in principle, instantaneous measurements become possible. The laser beams do not pass straight into the interaction region, but rather pass through various optical elements. The latter might include Glan polarizers for better polarization purity (this is a necessary element in polarization-sensitive CARS), telescopes for beam resizing, dichroic mirrors for wavelength separation, and mirrors to control the direction of the laser beams. Before the interaction region, a lens focuses the beams according to geometries that are specified by the so-called phase matching. This fundamental aspect of CARS spectroscopy is discussed in the following paragraph. Beyond the spectral considerations illustrated above, it should be added that the amplitude of the CARS signal depends not only on the frequency mixing of the

6.5 Experimental Set-Ups and Phase Matching

incident fields but also on the spatial mixing of the wave vectors of the fields. (Note: a wave vector indicates the direction of propagation of an electromagnetic wave and its magnitude is set to 2p/l where l is the wavelength and the inverse of l gives the wavenumber.) A detailed explanation of this is available elsewhere [1], but the role of spatial mixing can be equally understood in terms of a qualitative analysis, as follows. The propagation of the fields is described classically in terms of plane waves. Assuming this pictorial view, the anti-Stokes field is proportional to Ep2 ðrÞES ðrÞexpð ikaS
rÞ for the common case of degenerate-pump CARS; this means that pump and Stokes field each contribute respectively as expðikp
rÞ and expðikS
rÞ. The composition of the four phases is such that the resulting anti-Stokes field propagates as expðiDk
rÞ, where Dk ¼ 2kp kS kaS . It is then easily seen that, when integration over the spatial coordinates of the Raman medium is made, the maximum constructive interference is realized for vanishing values of the wave vector mismatch, or Dk ¼ 0. This condition corresponds to the phase matching, and identifies the best experimental condition that will ensure the largest CARS emission. This condition is realized in a number of different ways. For example, the laser beams can be collinearly arranged, whereby all the wave vectors coincide in spatial directions (but not in amplitudes). Although this is the simplest way to obey the phase matching, the great disadvantage is that the anti-Stokes signal is generated along the whole optical path and the spatial resolution will be poor. However, this problem can be partially attenuated by a strong focusing of the laser beams, such that most of the signal is produced in the volume near the focus. Better combinations of the wave vectors have been realized under the so-called BOXCARS schemes [1]. In this instance, the pump beam is split into two parts that are made to cross at a certain angle, determined by the focusing lens. The optical alignment of the beams can be either coplanar – known as “planar BOXCARS” – or three-dimensional (3-D) – known as “folded BOXCARS” (Figure 6.5). Either approach will guarantee spatial resolutions as high as 1 mm, or even better. An example of this is shown in Figure 6.6, where planar BOXCARS is realized above a Bunsen burner, the exit of which is 10 mm wide. The pump (green) and Stokes (orange) beams are focused within a cell of water to emphasize their luminosity in view of a better clarity of the interaction region. In general, there exist many schemes of geometric arrangements that are needed to make the lasers intersect at specific positions [1], and the correct choice must be made on the basis of spatial resolution and the simplicity of the experimental set-up. After the interaction, the beams emerge and are collimated by a second lens that is normally selected to have the same focal length as the focusing lens. The anti-Stokes signal must be spatially filtered and directed towards the optical elements used for the actual measurements. Occasionally, a fraction of the CARS signal is split off with a beam splitter and analyzed using a Glan–Thompson polarizer set at right-angles with respect to the field polarization. In this way, only the background CARS is measured for in situ referencing (see below). In the narrowband operation of exciting laser beams (scanning CARS), the CARS signal is sent towards a monochromator equipped with a photomultiplier tube, whereas in broadband CARS the signal is instead analyzed with a spectrograph

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Figure 6.5 BOXCARS configurations for degenerate CARS (i.e., two pump lasers plus the Stokes shifted beam). Laser propagation is from the left to the right. In the planar set-up, one pump beam coincides with the Stokes laser. The CARS beam is in blue color.

Figure 6.6 Planar BOXCARS above a Bunsen burner with a diameter of 10 mm. The cell contains water to magnify the visibility of the laser beams (green corresponds to the pump

laser, orange to the Stokes laser). The second pump beam (overlapping with the Stokes laser) has been blocked in order to visualize the optical path of the Stokes beam.

6.5 Experimental Set-Ups and Phase Matching

equipped with a charge-coupled device (CCD). In the latter case, the spectral resolution is dictated by either the pump laser linewidth or the resolution of the spectrograph. All in all, resolutions on the order of 1 cm 1 are typical and, although these are much larger than the resolutions attainable with scanning CARS, the broadband operation does not hamper the diagnostic potential of CARS. At any rate, the influence of the spectrograph is quantified by its instrumental function or slit function that might play a part in the uncertainty associated with the data analysis [47]. Spectral resolution represents only one of the important details needed to clarify the conditions under which the data are acquired. Another fundamental step is the normalization, which refers to a procedure needed to account for a number of possible alterations of measured spectra. For example, it is realistic to expect alterations due to pulse-to-pulse laser variation, to spectral inhomogeneities of the broadband laser, and to optical misalignments. In principle, normalization can be made relative to reference cells that contain a known gas which is used to generate a reference CARS signal. However, the cells may prove troublesome and an alternative procedure, known as “in situ referencing,” is instead used [1]. This procedure is based on the ingenious use of the nonresonant background that is not always of no use. The elimination of background is, rather, the key to obtaining noteworthy spectral profiles. The most effective way to accomplish this goal involves the use of laser polarizations, with the necessary premise that the background originates from twophoton processes. It is for this reason that the nonresonant susceptibility does not depend on the polarization of the exciting electric fields. By contrast, the resonant CARS signal is strongly sensitive to the polarization state of the laser beams. This difference became very clear during the early stages of CARS, and it was soon realized that any background suppression could effectively take place after a specific orientation of the field polarizations [48]. Since then, this method of suppression has been considered the normal approach in all actual experiments. Finally, some comment should be made on the uncertainties that are expected in experiments aimed at accurate CARS thermometry. In general, a standard broadband vibrational CARS is known to have uncertainties on the order of 100 K for stable flames; this situation is due mainly to the statistics of the laser modes [49], and certain precautions should be taken to attenuate the problem. For example, multi-mode pump laser beams should be arranged in such a manner that they do not exactly overlap in time, whilst a time lag corresponding to a spatial separation superior to the coherence length of the radiation should be sufficient to eliminate any enhancement of nonresonant susceptibility [10]. Another approach might be to use dye lasers with optical cavities that create the largest number of laser modes, such that the spectral profile created is as smooth as possible. A more radical solution would be to use a modeless dye laser [50], which would remove the mode structure of the amplified radiation such that its spectral shape would not be prone to competition from the laser modes. To summarize, important investigations conducted by Snelling and coworkers have shown that multimode pump lasers, in conjunction with a dye laser used for CARS measurements of discrete and moderately spaced Raman transitions

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(e.g., with N2 at moderate pressure), would result in the least noise and the smallest standard deviations [51]. In contrast, if the optical signal were to lose its fine spectral details (e.g., CARS at high pressure), then a single-mode pump laser would provide a better performance [52]. Such light sources, when coupled to a modeless dye laser, would guarantee a reduction in the thermometric uncertainties encountered with single-shot measurements [50, 53, 54].

6.6 Typical Examples of Vibrational CARS Spectra: N2 and Other Simple Molecules

It is fortunate that the general characteristics of a CARS measurement are visible in nitrogen spectra. This is very convenient, because nitrogen is one of the main components of air-fed combustion environments, and is found in both cold and hot zones. On the basis of its ubiquity, nitrogen is responsible for the widespread use of CARS in a thermometric sense, and for this reason it is important that this point be illustrated in some detail. First, the analysis developed earlier shows that the interpretation of CARS measurements does, to a great extent, depend on a precise knowledge of the molecular parameters. Based on the importance of nitrogen in CARS measurements, sufficient investigations have been conducted on spectral constants and linewidth data to assist in the decoding of thermal information [6, 24, 29, 37, 38, 55]. Typical nitrogen CARS spectra, using such data, are shown in Figure 6.7 for the case of a multimode pump laser in degenerate configuration; the distinguishing features of these spectra are summarized as follows.

Figure 6.7 Theoretical spectra of nitrogen CARS with multimode pump lasers at different temperatures.

6.6 Typical Examples of Vibrational CARS Spectra: N2 and Other Simple Molecules

In general, nitrogen and other CARS molecules show intense spectral bands that are associated with isotropic Q-branch transitions, where the rotational level J is unaltered and the vibrational level v changes by one unit. In particular, Figure 6.7 shows a first (cold) band immediately below 2330 cm 1, and a second (hot) band starting from 2300 cm 1 downward. Here, the first band groups transitions from the fundamental vibrational level with v ¼ 0 to the first excited level v ¼ 1; the second band does the same, but for transitions ranging from v ¼ 1 to v ¼ 2. The two bands are finely distinguished by the rotational manifold, although this is unresolved at T ¼ 300 K due to the finite spectral bandwidth of the laser beams. In contrast, at higher temperatures the fine structure becomes visible such that increasing the temperature will results in three main effects: (i) the cold band broadens because higher rotational levels are called into action by the higher thermal energies (this was anticipated in Section 6.2; see also Figure 6.1); (ii) a shift of the maximum, which can be explained by the lower rotational levels becoming increasingly depopulated with increasing temperatures (see also Figure 6.1); and (iii) a delineation of the relative importance of the hot bands that become increasingly prominent. In Figure 6.7, the line overlap is undeniable, with each spectral peak being unresolved and its wings coalescing into those of the adjoining peaks. In this condition, the failure of the isolated lines approximation is clear, and a more elaborate approach based on the G matrix must be invoked (Equations 6.18–6.21.). The actual appearance of a measured N2 CARS spectrum is shown in Figure 6.8, where the data (symbols) were obtained using an ordinary set-up comprising a degenerate pump and a broadband Stokes source. The rotational structure of the cold band was recognizable, while the presence of the first hot band suggests that the laser probed a region of high temperatures. Contour fitting is in order if a quantitative thermometric information is required for the data of Figure 6.8. For this, the fit is plotted with a continuous line which demonstrates that, although the CARS synthesis depends on many parametric evaluations, the result is satisfactory. Notably, interference effects, collisional narrow-

Figure 6.8 Measured nitrogen CARS (symbols) and contour fit (line).

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ing, and broadening mechanisms of linewidths were each included in the physical description that contributes to the fitting procedure. This provided a temperature of approximately 2200 K, which was sufficiently close to the adiabatic temperature of the methane–air flame considered in the example (2226 K). As Figure 6.8 refers to nitrogen CARS measured with a multimode pump laser, a spectral overlap was inevitable. In single-mode operation, however, the overlap would be effectively minimized and the rotational structure so resolved that an approach with isolated lines might be appropriate. However, the role of the G-matrix approach cannot be totally disregarded, especially at high pressures. Finally, with the question of the accuracy of nitrogen CARS thermometry having been investigated by several authors [1, 56–60], general opinion suggests it to be the most reliable technique for hostile environments where combustions are supported by air. Not only have the molecular parameters been profoundly examined (especially in light of the CARS applications discussed so far), but the spectral subtleties are also well understood. Indeed, with nitrogen CARS being considered as the “benchmark” for the general modeling of CARS diagnostics for combustion processes, a plethora of studies has been undertaken to determine its general characteristics. In particular, it is agreed that thermometric accuracy is on the order of few tens of degrees Kelvin for stationary flames, with a highest value of only 9 K at approximately 2100 K [56]. Although nitrogen is widely accepted as the reference molecule in CARS, other chemical species may also be encountered in experimental investigations. Normally, the choice is limited to diatomics (i.e., molecules with two atoms) because they possess spectral features that are more easily handled for diagnostic uses. Among possible molecular targets, the ideal choice is hydrogen (H2), the main reason residing in the easy interpretation of its vibrational Q-branch spectrum that is composed of a few, well-separated spectral lines. Consequently, any problems associated with collisional narrowing can be neglected until very high pressures are reached; moreover, low background levels can provide the additional advantage of spectral purity. An example of a measured H2 CARS spectrum is shown in Figure 6.9, where the biunivocal correspondence between spectral shape and thermometric measurements is visualized in four spectra recorded at remarkably different temperatures. The plot in Figure 6.9a, which was recorded at room temperature, is characterized by a single (cold) peak, although at higher temperatures this tended to become less important in favor of the hot peaks which appeared with a progression that could conceptually be organized so as to create a thermometric marker. Beyond N2 and H2, other diatomics considered for diagnostic studies may include O2. Indeed, the spectrum of the O2 molecule so closely resembles that seen for nitrogen that those aspects peculiar to N2 CARS can be extended to O2 CARS. The reason for such similarity lies in the close numerical values of the molecular constants of nitrogen and oxygen. With so much attention having been paid to homonuclear diatomics, it may be useful at this stage to consider the case of carbon monoxide (see Chapter 13), as a heteronuclear diatomic often used in CARS investigations [1]. The typical spectrum is shown in Figure 6.10, relative to a specific case of low CO concentrations. In similar

6.7 General Applications

Figure 6.9 Hydrogen CARS spectra. The horizontal axis is the same for all the plots. The vertical axis is normalized to the maximum peak of each plot.

fashion to nitrogen spectra, CO demonstrates the characteristic structure of vibrational bands (two are shown in the figure) composed of finer rotational lines. In order to complete the picture, it is important to note that CARS may also be applied to more complex molecules, although the spectral shapes may become highly intricate such that any spectral interpretation is made much more difficult. Examples of this type are limited to triatomics, namely water vapor and carbon dioxide [1], and are very rarely considered for combustion diagnostics.

6.7 General Applications

Today, the applications of CARS are numerous such that, at the time of writing this chapter, on entering the keywords “coherent anti-Stokes Raman” into a scientific

Figure 6.10 Carbon monoxide CARS spectrum.

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search engine, the outcome will invariably list up to 1800 entries. Perhaps more importantly, the number of CARS-related studies – whether in terms of applications or improvements – continues to rise. Much of this success has been due to the considerable versatility of CARS, not only in relation to the combination of various types of laser sources but also to the varying experimental arrangements. Hence, it will come as no surprise that today the technique is employed in several scientific disciplines beyond combustion. With regards to the field of combustion, a summary of practical applications is available in Table 6.1 of Ref. [1], which includes the studies of jet engines, internal combustion engines, coal gasifiers, furnaces, exhausts in a magnetohydrodynamic (MHD) environment, propellant burning, and scramjets. Although an analysis of these highly interesting applications cannot be pursued in this chapter, for the sake of conciseness a brief note is included here on the paradigmatic use of nitrogen CARS in the case of practical combustion systems. Specifically, thermometric measurements were undertaken to map the internal volume of a Dry Low-NOx combustor (General Electric, model DLE for gas turbines LM 1600, 2500, and 6000). This was equipped with a series of primary methane/air nozzles in the centerbody, surrounded by a group of secondary nozzles operated to stabilize the flame in the presence of a high air flux. In order to guarantee an optical access, the body of the combustor was modified to house quartz widows (see Figure 6.11; the focusing and collecting lenses

Figure 6.11 Pictures and thermometric results along horizontal (top, right-hand plot) and vertical (lower, left-hand plots) lines scanned inside the combustion chamber. The picture at the top is a side view of the gas inlet. The vertical crosscuts (red) were taken at 2, 20, 40, and

50 mm from the burner head. The horizontal crosscut (blue) was scanned along the burner axis. The image at lower right shows the combustor with some parts of the optical (focusing and collecting lenses) and mechanical (movable turret) set-up.

6.7 General Applications

are also visible). The final structure was mounted on top of a turret with motorized translators that allowed for spatial scanning inside the combustion chamber. The signal of broadband N2 CARS in a planar BOXCARS configuration was collected by a lens of 30 cm focal length, and directed to a Jobin-Yvon spectrograph (model HR 640, Czerny–Turner type) operating with an holographic diffraction grating of 3000 grooves per mm. Following burner ignition, a series of single shot measurements was acquired for each position inside the combustion chamber. This series was controlled with a histogram (bar size 25 K), and the temperature determination provided after statistical elaboration. The experimental strategy was limited to mapping temperatures that lay in the vertical plane and crossed the central axis of the burner. In particular, thermometry close to the fuel nozzles provided the opportunity of verifying the temperatures in close proximity to the gas entrance. The data shown in Figure 6.11 contain the general results, with detailed views of the combustor provided in the images. The red marks that appear on the detail of the burner head (upper left image) roughly indicate the traces of the vertical crosscuts, the corresponding measurements of which are reported in the four lower left-hand graphs of Figure 6.11. Here, it is shown that the maximum temperatures were close to 2000 K in the proximity of the fuel nozzles. The blue mark in the upper left image of Figure 6.11 highlights the central axis, called the y-axis (z is then the vertical axis) of the burner. Measurements along this axis are reported in the upper righthand graph of Figure 6.11. The plot identifies the horizontal dependence of the temperature along the central section of the combustor. As described in the inset, the spatial origin of the y-axis has been taken on the vertical plane, passing tangentially to the inner surface of the burner head. With this reference, the measurements demonstrated a linearly increasing temperature with distance from the burner head. In particular, when the gas was injected at room temperature, from an initial value the temperature in the gas flow inside the combustor rose at about 4 K mm 1. This increase was derived from a combined effect between the presence of the cold gas stream and the progressive expansion of the combustion process, driven by the pilot flames. At this point, no further discussions will be included with regards to practical applications, although relevant details are available in Ref. [1]. Rather, attention is now turned to other general aspects encountered in combustion research. Attention is focused first on uses that differ from the classical view of CARS as a thermometric resource since, although CARS is acknowledged for its accurate temperature predictions, it can also be used to measure concentrations. This may be carried out in either of two ways [1]: (i) via methods based on spectrally integrated resonant CARS signals; and (ii) via methods centered on the spectral interference between a resonant signal and a nonresonant background. The latter method is especially applicable when the nonresonant and resonant susceptibility are comparable (within a certain range of species concentrations) and the CARS spectrum acquires features that provide information on the quantitative value of the concentration. For typical CARS diatomics (N2, O2, CO), the concentration range is between 0.5% and 30% at flame temperatures, and the method relies

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heavily on the correct curve fitting of the experimental data. An excellent example of this is seen in Stufflebeam and Eckbreth [61], where the temperatures and concentrations of three species (H2, N2, CO) were obtained after analysis based on Equation 6.4 and collisional narrowing. When employing the second method, which is based on spectrally integrated CARS signals, the background contribution must be suppressed. This critical premise is met by polarization-sensitive experimental set-ups, which are arranged in such a manner that it becomes possible to make a distinction between the different polarization states of resonant and nonresonant signals. As the nonresonant background stems from two-photon absorption of the exciting radiation, it does not alter the molecular motion (i.e., oscillations and rotations), which is instead responsible for the resonant contribution. For this reason, nonresonant CARS exhibits polarization properties that differ from the polarization properties of resonant CARS such that, with the correct choice of polarization orientation of the pump and Stokes fields, a very efficient suppression of background is achievable. When the background has been suppressed, the second main problem when measuring concentrations is the calibration to a standard. Rather than use a reference cell containing a gas with the target CARS molecule at known pressure and temperature, it may be preferable to generate a reference signal at the same location as the measurement. This procedure is referred to as in situ referencing, and requires that a background is collected by splitting off a fraction of the whole signal from the main beam path. This method was first demonstrated long ago [57, 62], and an excellent example of its application can be found in the experimental analysis of an internal combustion engine [63]. More sophisticated applications of CARS in relation to concentration measurements imply the planning of multicolor approaches [1]. These methods have been developed to realize the simultaneous measurement of more than one chemical species, and are assembled following the ingenious combination of laser systems. As an example, two nondegenerate pump wavelengths and a broadband Stokes laser give rise to the so-called “dual-pump CARS,” while “dual-broadband CARS” is represented by two broadband Stokes laser and a single pump wavelength. The choice is rather large, and more details are available in Ref. [1]. In principle, multicolor approaches have the potential to detect a number of molecular species close to what is possible with Raman spectroscopy (see Chapter 5), but with the advantage of the highly reliable temperature measurements that CARS guarantees. An example is in studies conducted by Weikl et al. [64], three species (N2 H2 and CO) were detectable simultaneously (with N2 CARS used for thermometric reasons). Among other general applications of CARS can also be included a variant of the technique, termed “pure rotational CARS” [1]. If vibrational CARS (see Section 6.6) is characterized by optical transitions with unitary changes of the molecular vibrational state, rotational CARS involves transitions between different rotational levels when the vibrational state remains untouched. This difference in the physical origins of rotational and vibrational CARS is reflected in remarkable spectral

6.8 Outlook

differences. First, the Raman cross-sections in rotational CARS are about one order of magnitude higher. Second, the spectral transitions are widely spaced, such that problems with line overlaps are significantly reduced. Third, since the purely rotational spectra of different molecules reside in close proximity to one another, the technique permits multiple species concentrations measurements. Unfortunately, rotational CARS is prone to various difficulties (small molecular population differences, CARS and pump frequencies nearly degenerate, and so on), and for these reasons vibrational CARS is often the preferred technique. Improvements have been made to circumvent the troubles of rotational CARS. For example, a strategy with a dual-broadband approach can produce excellent results, and an example of thermometry based on N2 spectra has been reported by Alden et al. [65]. Since these early developments, the applications for practical combustion devices have been much improved over the past few years, and extensively reviewed by Brackmann et al. [66] In this brief and somewhat incomplete overview of possible applications for CARS, one question that should not be overlooked relates to its possible use for the diagnosis of turbulence. It was noted earlier that a typical laser system has modest repetition rates, of generally less than 50 Hz (the typical value is 10 Hz). Since turbulence occurs on faster time scales, CARS clearly cannot be used to detect turbulent phenomena, although the creation of an average value over many single-shot measurements can provide valuable and reliable information with regards to mean values and variances. In general, such measurements are meaningful only under certain severe conditions; an example is when the dimensions of the probe volume are smaller than the typical turbulent spatial scale. Likewise, other experimental details may become crucial in order to avoid the bias of measurements that may render CARS thermometry devoid of any practical interest [67].

6.8 Outlook

Today, the practical possibilities of CARS are far from being completely explored. Despite much of the basic research being carried out during the 1980s and 1990s, there remain many aspects that continue to reveal new perspectives for CARS and its applications. The details of some recently developed procedures, as well as some future lines of development, will be outlined very briefly at this point. The increasing demand for two-dimensional (2-D) imaging has set an important goal for CARS spectroscopy. It is well known that, for combustion applications, the CARS technique is best suited to provide point-like (or zero-dimensional) information; in other words, the interrogation volume is considerably smaller than the spatial scales that are typical of combustion imaging. As a consequence, the research groups began to prefer other techniques that were capable of mapping 2-D temperature variations, including fluorescence [1, 68, 69] and Rayleigh imaging [1, 70]. Although the possible use of a 2-D visualization of CARS measurements was investigated from the very outset [71], one major drawback was the large reduction in

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signal caused by the laser beams dispersing over the large spatial areas captured by the image. As seen in Equation 6.1, CARS intensities are nonlinear with respect to the laser intensities; this means that as soon as the beams are arranged in light sheets, the relative intensities fall and, in turn, the CARS signal decreases disproportionately. A compromise to this would be to use one-dimensional (1-D) (or linear) imaging, such that sufficient spectral intensity could be concentrated along the lines of interaction. On the other hand, the accommodation was not completely reassuring, having been demonstrated for gas flows [72, 73] and having shown promise for combustion at high pressures that ensured an enhanced CARS response [74]. At moderate pressures, the anti-Stokes signal was found to be amenable for diagnostic purposes, as long as the temperatures were not too high [75, 76]. Understandably, the restraint on thermometric measurements prevented the use of CARS from being used in those temperature ranges particularly relevant to combustion. In an attempt to circumvent the limitations inherent in linear imaging, recent experimental developments have inclined towards multipoint reconstructions [77, 78]. Following this strategy, the 1-D information can be extrapolated from aligned points of CARS interaction in place of data acquisition along continuous lines. This solution seems to safeguard the integrity of the diagnostic potential of CARS, without altogether denying access to the rich information stored in linear imaging. The search for composite knowledge, of which 2-D or 1-D spatial resolution is only one obvious example, has responded to a common trend in recent research on laser diagnostics. This refers to the integration of multiple information sources, which is deemed to be extremely important when facing the complexity of combustion processes. This is also why there is today a growing interest in combining different spectroscopic techniques, the measurements of which are complementary to the multifaceted and interdisciplinary theoretical understanding of reacting gas flows. Within this scenario, CARS is usually adopted by virtue of its thermometric capability, whereas other well-established laser techniques are used for concentration and velocity measurements. In particular, CARS is being used increasingly in concert with laser-induced fluorescence (LIF) measurements [79–83]. The same objective can also be reached with CARS measurements supplemented by Raman data [84, 85], while coupling with velocity-based techniques has also been demonstrated [86]. Yet, the compatibility of CARS thermometry with other spectroscopic tools can undoubtedly be further extended. In fact, combustion diagnostics have recently shown an unprecedented level of versatility when three different laser techniques can be joined together [87]. And in this respect CARS is no exception, since quite recently it has been combined with LIF and degenerate four-wave mixing (DFWM) [88, 89]. The coupling of fluid-dynamic, chemical and thermometric information has also been investigated by means of a combination of particle image velocimetry (PIV), LIF, and CARS measurements [90, 91]. It is expected that this line of research will be strengthened in the near future. Another promising aspect of CARS spectroscopy is related to the advent of commercial lasers that have triggered experimental investigations of very fast coherent phenomena [92]. Today, picosecond and femtosecond lasers are available commercially; moreover, if laser systems with pulses on the nanosecond scale can be

6.8 Outlook

regarded as a traditional light source in CARS applications to combustion, the new frontier resides in much shorter time domains of the pump and Stokes beams. Lately, the numbers of studies with time-resolved CARS have flourished, and there is no doubt that the use of ultra-short pulses will set a direction that will be explored in detail. One important reason for the rapid popularity of such systems lies in the extremely high repetition rates that contrast with the poor repetition achievable with nanosecond lasers (the latter is typically on the order of 10 Hz). Additional characteristics – namely the low influence of nonresonant background and the elimination of the troubles with the collision environment – also deserve attention for the importance that these problems have in traditional CARS. For example, time-delayed experiments with picosecond lasers have demonstrated that the nonresonant background can be enormously reduced while, in contrast, the resonant signal is only minimally affected [93, 94]. Although, according to these findings measurements with picosecond lasers would seem auspicious, present-day research is oriented more towards femtosecond lasers. In this regard, CARS thermometry has been studied for both hydrogen [95–97] and nitrogen [96, 98–100]. Furthermore, the sensitivity towards pressure-dependent effects in femtosecond CARS represents an up-to-date subject [101–105] for which theoretical analyses explaining the intricacy of femtosecond CARS have only just been reported [106–108]. Returning to traditional CARS, one question that often troubles the experimentalist’s mind is whether to have a negative or positive attitude towards the nonresonant background (see discussions in previous sections). On the one hand, a background suppression is evoked with the aim of purifying as much as possible the resonant contribution to the total CARS signal (ways to achieve this in combustion diagnostics are restricted to polarization-sensitive approaches). On the other hand, the background could be perceived as a means suggestive of meaningful information, because it alters the spectral shape in a manner that could be directly related to the species concentration. Although, unfortunately, this is not always applicable, it does raise an important question. Usually, CARS diagnostics relies on a priori knowledge of the molecular parameters (see Section 6.4), but whether there is a method that makes the spectral shape completely informative of the physics behind it, without any a priori determination of the parameters, is unclear. Recently, however, a positive answer to this question has emerged which consists of a strategy that revolves around concepts elaborated in the context of information theory and summarized in the so-called maximum entropy method (MEM) [109]. Based on the idea that the true values of a measured quantity (when subjected to noise) maximize the information entropy, the method is able to identify a specific treatment of the spectral CARS shapes, so that real and imaginary parts of the susceptibility are revealed [110]. Currently, although the method has been proven to work for CARS spectra of samples of biochemical interest (see Ref. [111] and references therein), there are hopes that measurements in the gas phase could soon benefit from the advantages that MEM analysis carries. The mention of biochemical applications of CARS introduces another possible line of development for the technique as a diagnostic tool in combustion. The use of CARS to study biological matter is well known [112–115] and, according to this

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newly established field of study, light has now been shed on the problem of a CARS process taking place at the focus of a microscope. This may have a dramatic effect on the field of microcombustion that is currently receiving great attention because of increasing demands for small-scale devices [116–118]. The compatibility of CARS with the extremely reduced sizes of the optical interaction region might ultimately promote applications in combustion environments confined to the submillimeter scale.

6.9 Summary

In this chapter, an attempt has been made to contextualize CARS spectroscopy in relation to the specific needs of combustion science, in which the technique is used primarily as a tool for thermometric purposes. This task is not easy, because CARS spectroscopy, despite its acknowledged value, does not lend itself well to the understanding built on elementary concepts. In effect, a full comprehension of the details about the generation and interpretation of coherent anti-Stokes radiation requires a deep knowledge of optical and molecular physics that is not immediately available to the non-expert. Although any description of the intimate mechanisms behind CARS has been avoided in this chapter as much as possible, some more compulsory introductory elements were introduced initially. This served the purpose of facilitating the presentation of CARS spectroscopy in its theoretical and applicative aspects, and included the well-known role of CARS as an accurate means of thermometric diagnostics. The physical explanation of this feature was followed by a deeper analysis of the CARS signal and its spectral dependences on laser and molecular parameters. One of the most difficult parts of CARS diagnostics, namely the physical characterization of the CARS molecule, was then described. Another difficulty was shown to reside in the experimental set-up since, unlike other more simple spectroscopic techniques such as spontaneous Raman scattering (see Chapter 5), CARS spectroscopy is grounded on a third-order optical process such that three laser fields must be combined. The use of more than one laser leads to certain complications, including the phase-matching conditions and experimental geometry required for the CARS amplitude and spatial resolution. Despite these difficulties, vibrational N2 CARS is today commonplace in combustion science, and the characteristics of high-temperature spectra have been outlined, along with details of other general applications, with particular reference to concentration measurements and purely rotational CARS. In conclusion, it is reasonable to suggest that CARS will continue to undergo further examination with regards to its more advanced use. These will surely embrace a limited imaging capacity, the combination with other spectroscopic techniques, ultra-fast excitations, conceptual strategies of data handling that avoid the need for a priori knowledge, and applications in microcombustion.

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7 Laser Doppler Anemometry Damien Blondel 7.1 Introduction

Laser Doppler anemometry (LDA) (also known as laser Doppler velocimetry; LDV) is a widely accepted technique for fluid dynamic investigations in gases and liquids, and has been used as such for more than four decades. It is a well-established technique that provides information about flow velocity and turbulence. The nonintrusive principle and directional sensitivity of LDA make it very suitable for applications with reversing flow, chemically reacting or high-temperature media and rotating machinery, where physical sensors are difficult or impossible to use. LDA requires tracer particles to be present in the flow. Laser anemometers offer unique advantages in comparison with other fluid flow instrumentation: .

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Noncontact optical measurement: Laser anemometers probe the flow with focused laser beams, and can sense the velocity without disturbing the flow in the measuring volume. The only necessary conditions are a transparent medium with a suitable concentration of tracer particles (or seeding). No calibration – no drift: The laser anemometer has a unique intrinsic response to fluid velocity, namely absolute linearity. The measurement is based on the stability and linearity of optical electromagnetic waves which, for most practical purposes, can be considered unaffected by other physical parameters such as temperature and pressure. Well-defined directional response: The quantity measured by the laser Doppler method is the projection of the velocity vector on the measuring direction defined by the optical system (a true cosine response). The angular response is thus unambiguously defined. High spatial and temporal resolution: The optics of the laser anemometer is able to define a very small measuring volume and thus provide good spatial resolution and allow local measurement of the Eulerian velocity (the fluid velocity at a fixed position and given time). The small measuring volume, in combination with fast signal-processing electronics, also permits a high-velocity span (also called

Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright
2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

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bandwidth), time-resolved measurements of fluctuating velocities, providing excellent temporal resolution. Usually, the temporal resolution is limited by the concentration of seeding rather than by the measuring equipment itself. Multicomponent bidirectional measurements: Combinations of laser anemometer systems with component separation based on color, polarization, or frequency shift allow one-, two-, or three-component LDA systems to be put together based on common optical modules. Acousto-optical frequency shift allows the measurement of reversing flow velocities.

Taken together, these properties of laser anemometers certainly constitute a very attractive description of a measuring instrument. As is often the case, however, optimization of the performance of a system with respect to certain parameters may influence other performance characteristics in a negative fashion. As a matter of fact, some of the compromise decisions which must be made when selecting and setting up a laser anemometer system can be traced back to the famous “uncertainty principle of wave theory,” which describes the impossibility of attaining complete information of both spatial and temporal location of a wave train simultaneously.

7.2 Measurement Principles 7.2.1 Laser Beam

The special properties of continuous-wave (CW) lasers (gas and solid state), which makes them so well suited for the measurement, are the spatial and temporal coherence. At all cross-sections along the laser beam, the intensity has a Gaussian distribution, and the width of the beam is usually defined by the edge-intensity being 1/e2 ¼ 13% of the core-intensity. At one point, the cross-section attains its smallest value, and the laser beam is uniquely described by the size and position of this socalled “beam waist.” With a known wavelength l of the laser light, the laser beam is uniquely described by the size d0 and position of the beam waist, as shown in Figure 7.1.

Figure 7.1 Laser beam with Gaussian intensity distribution.

7.2 Measurement Principles

With z describing the distance from the beam waist, the following formulas apply: 4l pd0 vffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 0 12ffi u u u 4lz Beam diameter dðzÞ ¼ d0 t1 þ @ 2 A ! az for z ! 1 pd0 0 12 3 2  2 pd ! 1 for z ! 0 Wave front radius RðzÞ ¼ z41 þ @ 0 A 5 ! z for z ! 1 4lz Beam divergence

a¼

The beam divergence a is much smaller than indicated in Figure 7.1, and visually the laser beam appears to be straight and of constant thickness. It is important, however, to understand that this is not the case, as measurements should take place in the beam waist so as to obtain an optimal performance of any LDA equipment. This is due to the wave fronts being straight in the beam waist, and curved elsewhere (this will be explained in more detail later). For now, it should just be noted that the wave front radius approaches infinity for z approaching zero, which means that the wave fronts are approximately straight in the immediate vicinity of the beam waist. This in turn means that the theory of plane waves can be used here, greatly simplifying the calculations. 7.2.2 Doppler Effect

As indicated by its name, the LDA technique is based on Doppler shift of the light reflected (and/or refracted) from a moving seeding particle. The principle is illustrated in Figure 7.2, where the vector U represents the particle velocity, and the unit vectors ei and es describe the direction of incoming and scattered light respectively. According to the Lorenz–Mie scattering theory, the light is scattered in all directions at once, but here only the light reflected in the direction of the receiver is considered. The incoming light has the velocity c and the frequency fi, but due to the particle movement the seeding particle “sees” a different frequency fp, which is scattered towards the receiver. From the receiver point of view, the seeding particle acts as a moving transmitter, and the movement introduces an additional Doppler-shift in the frequency of the light reaching the receiver.

Figure 7.2 Light scattering from a moving seeding particle.

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Using Doppler-theory, the frequency of the light reaching the receiver can be calculated as: fs ¼ fi

1
ei  ðU=cÞ 1
es  ðU=cÞ

Even for supersonic flows, the seeding particle velocity |U| is much lower than the speed of light, which means that |U/c|  1. Taking advantage of this, the above expression can be linearized to:   U fi fs ffi fi 1 þ  ðes
ei Þ ¼ fi þ U  ðes
ei Þ ¼ fi þ Df c c

With the particle velocity U being the only unknown parameter, in principle the particle velocity can be determined from measurements of the Doppler shift Df . In practice, this frequency change can only be measured directly for very high particle velocities (Fabry–Perot interferometer). More commonly, the light scattered from two intersecting laser beams is mixed, as illustrated in Figure 7.3. In this way, both incoming laser beams are scattered towards the receiver, but with slightly different frequencies due to the different angles of the two laser beams: 2

3 U fs;1 ¼ f1 41 þ  ðes
e1 Þ5 c 2

3 U fs;2 ¼ f2 41 þ  ðes
e2 Þ5 c

When two wave trains of slightly different frequency are superimposed, the wellknown phenomenon of a beat frequency due to the two waves intermittently interfering with each other constructively and destructively emerges. The beat frequency corresponds to the difference between the two wave-frequencies, and since the two incoming waves originate from the same laser, they also have the same frequency, f1 ¼ f2 ¼ fI, where the subscript I refer to incident light:

Figure 7.3 Scattering of two incoming laser beams.

7.2 Measurement Principles

fD ¼ fs;2
fs;1 2

3 2 3 U U ¼ f2 41 þ  ðes
e2 Þ5
f1 41 þ  ðes
e1 Þ5 c c 2 3 U ¼ fI 4  ðe1
e2 Þ5 c

ð7:1Þ

fI ¼ ½je1
e2 j  jUj  cosðjÞ c ¼

1 2sinðq=2Þ  2sin ðq=2Þ  ux ¼ ux l l

where q is the angle between the incoming laser beams and j is the angle between the velocity vector U and the direction of measurement. Note that the unit vector es has dropped out of the calculation, meaning that the position of the receiver has no direct influence on the frequency measured. (According to the Lorenz–Mie light-scattering theory, the position of the receiver will however have considerable influence on signal strength.) The beat frequency, which is also called the Doppler frequency, fD, is much lower than the frequency of the light itself, and can be measured as fluctuations in the intensity of the light reflected from the seeding particle. As shown in Equation 7.1, the Doppler frequency is directly proportional to the x component of the particle velocity, and the velocity can thus be calculated directly from fD: ux ¼

l fD 2sin ðq=2Þ

ð7:2Þ

7.2.3 The Fringe Model

Although the above description of LDA is accurate, it may be intuitively difficult to quantify. To handle this, the fringe model is commonly used in LDA as a reasonably simple visualization producing the correct results. When two coherent laser beams intersect, they will interfere in the volume of intersection. If the beams intersect in their respective beam waists, the wave fronts are approximately plane, and consequently the interference produce parallel planes of light and darkness, as shown in Figure 7.4. The interference planes are known as fringes, and the distance df between them depends on the wavelength and the angle between the incident beams: df ¼

l 2sin ðq=2Þ

ð7:3Þ

The fringes are oriented normal to the x-axis, so the intensity of light reflected from a particle moving through the measuring volume will vary with a frequency proportional to the x-component ux of the particle velocity:

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Figure 7.4 Fringes form where two coherent laser beams cross.

fD ¼

ux 2 sin ðq=2Þ ux ¼ l df

ð7:4Þ

which is identical to the result in Equation 7.1. If the two laser beams do not intersect in the beam waists but elsewhere in the beams, then the wave fronts will be curved rather than plane, and as a result the fringe spacing will not be constant but will depend on the position within the intersection volume. As a consequence, the measured Doppler frequency will also depend on the particle position, and as such it will no longer be directly proportional to particle velocity. If the beams are badly misaligned, it will probably not be possible to obtain any results at all; however, if the beams are just slightly misaligned the errors will be small and may not be noticed. 7.2.4 Measurement Volume

Measurements take place in the intersection between the two incident laser beams, and the measuring volume is defined as the volume within which the modulation depth is higher than e
2 times the peak core value. Due to the Gaussian intensity distribution in the beams, the measuring volume is an ellipsoid, as indicated in Figure 7.5.

Figure 7.5 Measurement volume.

7.2 Measurement Principles

The size of the measuring volume can be calculated from the beam waist diameter df of the focused laser beams and the angle q between them: dx ¼

df ; cos ðq=2Þ

dy ¼ df ;

dz ¼

df sin ðq=2Þ

ð7:5Þ

where dx is the height, dy the width, and dz the length of the measuring volume. Since beam intersection angles are usually small, dx and dy are often almost equal, and are sometimes referred to as the diameter of the measuring volume. The measuring volume dimensions in Equation 7.5 are guidelines only. A very small seeding particle in the outskirts of the measuring volume may not reflect sufficient light to be detected. On the other hand, a very large seeding particle may reflect so much light that it is detected even if technically it is slightly outside the measuring volume as defined above. Other parameters such as system gain and threshold level influence the measurements similarly. From the height dx of the measuring volume and the fringe spacing df, the total number of fringes can be calculated: Nf ¼

dx df =cos ðq=2Þ 2df ¼ tan ðq=2Þ ¼ l=2sin ðq=2Þ l df

ð7:6Þ

This number of fringes applies for a seeding particle moving straight through the center of the measuring volume along the x-axis. If the particle passes through the outskirts of the measuring volume, it will pass fewer fringes, and consequently there will be fewer periods in the recorded signal from which to estimate the Doppler frequency. In order to obtain good results from LDA equipment, a sufficiently high number of fringes in the measuring volume is necessary. Typical LDA set-ups produce between 10 and 100 fringes, but in some cases reasonable results can be obtained with fewer fringes. The key issue here is the number of periods produced in the oscillating intensity of reflected light. The older LDA processors often require a minimum of eight periods to validate the burst, whereas modern processors based on fast Fourier transform (FFT) algorithms can estimate particle velocity from as little as one period. The accuracy will, however, be improved with more periods. Frequency shift (as described in Section 7.3.4) will cause the fringe pattern to “roll” through the measuring volume, increasing or decreasing the number of fringes passed by a seeding particle. If the fringes move towards the movement of the seeding particle, then the effective number of fringe-passing will increase; however, if the fringes move away from the particle, the number will decrease, corresponding to an increase or decrease in the number of periods in the recorded signal. 7.2.5 Backscatter versus Forward-Scatter LDA

With the particle sizes used, the majority of light is scattered in a direction away from the transmitting laser. Hence, in the early days of LDA forward scattering was

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Figure 7.6 Mie scatter diagram for different sized seeding particles (dp is the particle size and l the wavelength). The light intensity is shown on a logarithmic scale.

frequently used, which meant that the receiving optics was positioned opposite the transmitting aperture. Although a much smaller amount of light is scattered back towards the transmitter (see Figure 7.6), advances in technology have made it possible to perform reliable measurements even on these faint signals, such that today backward scatter is the usual choice in LDA. This so-called “backscatter LDA” allows for the integration of transmitting and receiving optics in a common housing, thus avoiding the need for much tedious and time-consuming work aligning the separate units. Forward-scattering LDA is not completely obsolete, however, since in some cases its improved signal-to-noise ratio (SNR) makes it the only way to obtain any measurements at all. Experiments requiring forward scatter might include: .

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High-speed flows, requiring very small seeding particles that stay in the measuring volume for a very short time, and thus receive and scatter a very limited number of photons. Transient phenomena, such as acoustic shock waves, which require high datarates in order to collect a reasonable amount of data over a very short period of time. Very low turbulence intensities, where the turbulent fluctuations might drown in noise, if measured with backscatter LDA.

Forward- and back-scattering is identified by the position of the receiving aperture relative to the transmitting optics. However, another option is off-axis scattering, where the receiver visualizes the measuring volume at an angle. Like forward scattering, this approach require a separate receiver, and this in turn involves the careful alignment of the different units. However, it does help to mitigate an intrinsic problem which is present in both forward-scatter and backscatter LDA. As indicated in Figure 7.5, the measuring volume is an ellipsoid, where usually the major axis dz is much bigger than the two minor axes dx and dy, which renders the measuring volume more or less “cigar-shaped.” As a consequence, both forward and backscattering LDA become very sensitive to velocity gradients within the measuring volume, and in

7.3 System Description

Figure 7.7 Effective probe volume section in backscatter and off-axis configuration.

many cases measurements made near surfaces are also disturbed due to reflection of the laser beams. Figure 7.7 illustrates how off-axis scattering can reduce the effective size of the measuring volume. Seeding particles which pass either end of the measuring volume will be ignored as they are out of focus, and as such will contribute to the background noise rather than to the actual signal. This reduces the sensitivity to velocity gradients within the measuring volume, while the off-axis position of the receiver automatically reduces problems with reflection. These properties make off-axis scattering LDA very efficient, for example in boundary layer measurements.

7.3 System Description

A complete LDA system consists of a laser light source, one or two optics probes to create the probe volume and collect the LDA signals, a signal detection device to transform the light signals into electrical signals, a signal processor for the signal processing, and acquisition software for the data analysis and display. A traverse system can be added to move the measurement point in the three directions. In most cases the backscatter configuration (Figure 7.8) using a single probe is preferred. In modern LDA equipment the light from the Bragg cell is transmitted through optical

Figure 7.8 Principles of an LDA probe for a one-velocity component (along the x-axis).

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fibers, as is the light scattered back from seeding particles. This not only reduces the size and weight of the probe itself, but also makes the equipment flexible and easier to use for practical measurements. The laser, beam splitter, color separator, Bragg cell and photodetector (receiver) can be installed in a stationary fashion and out of the way, while the LDA probe can traverse between different measuring positions. This construction is especially helpful for combustion applications when there is a need to limit the number of active components (e.g., the electronics) that are close to a hot environment. Otherwise, with new laser technology it is possible to integrate all of the components (laser, Bragg cells, detector) into the optics head so as to produce an even more compact system. 7.3.1 Optics

Figure 7.8 shows, schematically, the construction of the backscatter LDA equipment. First, the beam from the laser is split into two identical beams, with (most importantly) the beam splitter having been adjusted to produce very similar intensities in the two laser beams. An acousto-optical component, known as a Bragg cell, is then inserted into one of the beams; this introduces a fixed frequency shift in the particular beam (Section 7.3.4), which in turn allows the sign of the measured velocity to be determined. The front lens deflects the two beams so that they intersect, such that in the intersecting volume the seeding particles will scatter the incoming laser light. Part of this light will be scattered backwards toward the front lens (backscatter), and registered in the receiver (normally a photomultiplier). Those seeding particles that pass the laser beams outside of the measuring volume will of course also reflect light but, as the receiving optics is focused on the measuring volume, this will be out of focus and so cause only a slight increase in the background noise. The beam waist diameter df, as used in Equation 7.6 and 7.7, is calculated from: df ¼

4f l pEdI

ð7:7Þ

where f is the focal length of the front lens (as shown in Figure 7.9), l is the laser wavelength, dI is the beam waist diameter of the laser beam before passing the front

Figure 7.9 The principle of the beam expander.

7.3 System Description

Figure 7.10 Example of LDA probe without a beam expander. The units length is 275 mm, and the diameter 60 mm.

lens, and E is the beam expansion factor, as explained below. It should be noted that df and dI are inversely proportional, which means that a large dI is desirable to produce a small df. It is normally desired to make the measuring volume as small as possible which, according to Equation 7.6, means that df should be small. The laser wavelength l is a fixed parameter, and the focal length f is normally limited by the geometry of the model being investigated. Although some lasers allow for adjustment of the beam waist position, the beam waist diameter dI is normally fixed. When E ¼ 1 in Equation 7.7, this corresponds to no beam expander; however, if the measuring volume is too large, then increasing E is the only other way to reduce the size of the measuring volume. This corresponds to installing a beam expander, which is a combination of lenses which locates in front of or replaces the front lens of a conventional LDA system (Figures 7.10 and 7.11). This converts the beams exiting the optical system to beams of greater width. At the same time, the spacing between the two laser beams is increased, as the beam expander also increases the aperture. Provided that the focal length f remains unchanged, the larger beam spacing will thus increase the angle q between the two beams; according to Equation 7.5, this will further reduce the size of the measuring volume.

Figure 7.11 Example of LDA probe with a beam expander. The total length of the unit is 475 mm, and the diameter 112 mm.

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In agreement with the fundamental principles of wave theory, a larger aperture is able to focus a beam to a smaller spot size, and hence create a greater light intensity on the scattering particles. At the same time, the greater receiver aperture is able to accept more of the reflected light. As a result, the benefits of the beam expander are threefold: . . .

To reduce the size of the measuring volume at a given measuring distance. To improve the SNR at a given measuring distance To reach greater measuring distances without sacrificing the SNR.

7.3.2 Two- and Three-Dimensional LDA for Two- and Three-Velocity Components

By adding a second and a third laser with a different wavelength (color), the LDA technique can be applied to measure, simultaneously, up to three velocity components. A typical three-dimensional (3-D) LDA set-up is depicted in Figure 7.12, where 3-D velocity measurements are performed with a 2-D probe positioned at off-axis angle a1, and a 1-D probe positioned at off-axis angle a2. The velocities actually measured in Figure 7.12 are u1, u2, and u3, but the velocities desired are in the directions u, v, and w. While u1 corresponds to u directly, v and w must be calculated from u2 and u3, knowing the angles a? and a2. The non-Cartesian velocity components (u1, u2, u3) are transformed to Cartesian coordinates (u, v, w) using the transformation matrix C: 8 9 8 9 8 9 < u = < C11 C12 C13 = < u1 = C22 C23  u2 v ¼ C ð7:8Þ : ; : 21 ; : ; u3 C31 C32 C33 w

Figure 7.12 Three-dimensional LDA configuration.

7.3 System Description

In this particular example we get: 8 9 1 0 0 > > > > 8 9 > 8 9 > > > > > sina sina u 2 1 > > > > u1 > > > > > > < = = = > sinða1
a2 Þ sinða1
a2 Þ v ¼  u2 > > > > > > > > : > > ; > : > ; > cosa2 cosa1 > > > w u3 > > 0 > > > > : ; sinða1
a2 Þ sinða1
a2 Þ

ð7:9Þ

The use of two probes requires the three measurement volumes to overlap accurately, which may not be an easy task, especially through windows. The use of two probes might even not be possible if only one optical access is available. In these configurations the solution might be to use a five-beam LDA probe which has five exiting beams arranged as shown in Figure 7.13. The center beam, when combined with the blue and green beams, forms two fringe patterns at an angle to each other. Two velocity components in the horizontal plane, u1 and u2, are measured in this way, and the angle between u1 and u (and between –u2 and u) is termed j. The violet beam pair measures the vertical component. The transformation from the measured velocity components to orthogonal components can be expressed as:     1 1   8 9
0 8 9   2cosj=2 2cosj=2 u> u1 >   > > > >  > < > = < =    v ¼ 0 0 1   u2  > > > >  >  > : > ; : > ;  1 1 u3 w   0  2sinj=2  2sinj=2  

Figure 7.13 The five-beam LDA configuration, showing the position of the beams at the front lens and a definition of the coordinates.

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Short-focal length front lenses are recommended in order to obtain a good resolution of the w component.

7.3.3 Laser

When LDA was first developed, only He–Ne (632 nm) and Ar-Ion lasers (488, 514, and 476 nm) were available. Initially, the He–Ne system was attractive based on its low cost and good optical beam quality, but it has now largely been replaced by superior technologies which have emerged. The main advantage of Ar-Ion lasers is that they offer three different wavelengths for measuring up to three velocity components; however, they require much more laser power, are bulky, and need to be water-cooled while in use. Over the past few years, solid-state lasers have been introduced that are easier to use because they are more compact and do not require any water-cooling. Moreover, these lasers are also being developed in increasingly powerful forms. 7.3.4 Frequency Shift

One drawback of the LDA technique described here is that negative velocities (ux < 0 according to Equation 7.4) will produce negative frequencies fD < 0. However, as the receiver cannot distinguish between positive and negative frequencies, there will be a directional ambiguity in the measured velocities (Figure 7.14). In order to overcome this problem, a Bragg cell is introduced into the path of one of the laser beams. The Bragg cell (see Figure 7.15) is a slab of glass on one side of which is an electromechanical transducer that is driven by an oscillator. This produces an acoustic wave that propagates through the slab, generating a periodic moving pattern of high and low density. The opposite side of the slab is shaped so as to minimize any reflection of the acoustic wave, and is attached to a material that absorbs the acoustic energy. The incident light beam hits a series of traveling wave fronts, which act as a thick diffraction grating. Interference of the light scattered by each acoustic wave front causes maximal intensity to be emitted in a series of directions. By adjusting the acoustic signal intensity and the tilt angle qB of the Bragg cell, the intensity balance between the direct beam and the first order of diffraction can be adjusted. In modern LDA equipment this is exploited by using the Bragg cell itself as beam splitter; this not

Figure 7.14 Directional ambiguity without frequency shift.

7.3 System Description

Figure 7.15 The Bragg cell; operating scheme.

only eliminates the need for a separate beam splitter, but also improves the overall efficiency of the light-transmitting optics, as over 90% of the lasing energy can be made to reach the measuring volume, effectively increasing the signal strength. The Bragg cell adds a fixed frequency shift f0 to the diffracted beam, and including this in the Equation 7.1 yields: 2 3

U U fs;2 ¼ ðfI þ f0 Þ41 þ  ð
es

e2 Þ5 ¼ fI þ f0 þ ðfI þ f0 Þ  ð
es

e2 Þ c c 2 3

U U fs;1 ¼ fI 41 þ  ð
es

e1 Þ5 ¼ fI þ fI  ð
es

e1 Þ c c

U U fD ¼ fs;2
fs;1 ¼ f0 þ ðfI þ f0 Þ  ð
es

e2 Þ
fI  ð
es

e1 Þ c c

U U ¼ f0 þ fI  ð
es

e2

es þ
e1 Þ þ f0  ð
es

e2 Þ c c

U U ¼ f0 þ fI  ð
e1

e2 Þ þ f0  ð
es

e2 Þ c c    
 U 2 sin ðq=2Þ ux þ f0   jð
es

e2 Þj cosj ¼ f0 þ l  c  |fflfflfflfflffl{zfflfflfflfflffl} |ffl{zffl} 1 |{z} 2 10
5 |fflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl} Negligible

to give:

fD ffi f0 þ

2sin ðq=2Þ ux l

ð7:10Þ

As long as the particle velocity does not introduce a negative frequency shift numerically larger than f0, the Bragg cell will thus ensure a measurable positive Doppler frequency, fD (Figure 7.16).

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Figure 7.16 Resolving directional ambiguity using frequency shift.

In other words, the frequency shift f0 allows measurement of velocities down to ux >


lf0 2 sin ðq=2Þ

ð7:11Þ

without directional ambiguity. Typical values might be l ¼ 514 nm, f0 ¼ 40 MHz, and q ¼ 20 , allowing for measurement of negative velocity components down to
55.9 m s
1. Upwards, the maximum measurable velocity is limited only by the response time of the photomultiplier and the following signal-conditioning electronics. In modern equipment this allows measurement well into supersonic velocities. In order to acquire an intuitive understanding of the frequency shift, the fringe model can be used once more. The introduction of a fixed frequency shift f0 into one of the beams will cause the fringe pattern itself to roll along the x-axis with constant velocity. This means that even a stationary particle will scatter light with an intensity pulsating at a frequency equal to f0. A seeding particle moving towards the fringes will produce a Doppler burst of higher frequency, while particles moving in the same direction as the fringes will produce a lower frequency. The lower velocity limit in Equation 7.11 corresponds to a seeding particle moving with exactly the same speed as the fringes. The key issue here is the number of fringes crossed by the seeding particle while it is in the measuring volume. If Dt is the particle’s residence time within the measuring volume, and fD is the measurable Doppler frequency according to Equation 7.10, then the fringe count Nf is simply calculated as: Nf ¼ fD  Dt

ð7:12Þ

This will usually differ from the fringe count calculated from Equation 7.6, which applies only when a seeding particle moves straight through the center of a set of stationary fringes. (i.e., no frequency shift). If, for example, the diameter of the focused laser beam is df ¼ 100 mm, the laser wavelength is l ¼ 500nm, and the beam intersection angle is q ¼ 20 , then Equation 7.6 will predict that a seeding particle passing the measuring volume along the xaxis will cross 70 fringes, irrespective of its velocity. Whilst this is sufficient to determine the absolute velocity of the particle, the direction will be unknown. To resolve the directional ambiguity, a frequency

7.4 Seeding

shift of f0 ¼ 40 MHz can be applied, allowing for detection of velocities ux > ux,min ¼
55.9 m s
1, according to the previous example. Since the frequency shift causes the fringes to move, the number of fringes crossed by the particle will also change. In the limit ux ¼
55.9 m s
1, the particle moves with the same speed as the fringes, and consequently there are no fringe crossings, and the particle will not be detected at all. It can be shown that for ux ¼ 12ux,min ¼
28.0 m s
1, the number of fringe crossings will be identical to the case of no frequency shift; Nf ¼ 70. For lower velocities, the fringe count will be smaller, and for higher velocities it will be bigger. In the special case ux ¼ 0, the fringe count will, in principle, approach infinity, as the seeding particle remains in the measuring volume. In practice, no particle is ever completely immobile, however, and even if ux equals 0, then uy or uz will most likely not, and as such ensure that the seeding particle leaves the measuring volume “sideways,” thereby limiting the number of fringe crossings. The nonzero velocity components uy and/or uz will generally reduce the fringe count, as they mean that the seeding particle does not pass the measuring volume along the x-axis. If it is certain that all velocities are bigger than 12ux,min, the frequency shift may also help to increase the effective fringe count in cases where the number of fringes according to Equation 7.6 might otherwise be too small. In principle, the frequency shift will also tilt the fringes slightly, so they are no longer exactly normal to the x-axis. However, in practice this can be ignored, as the typical frequency shift of 40 MHz is several orders of magnitude smaller than the frequency of light. This means that the difference in wavelength between the shifted and the unshifted beam will also be several orders of magnitude smaller than the laser wavelength itself, and consequently the tilt angle of the fringes will become negligible. In the example above (fI ¼ c/l ¼ 3  108/5  10
7 ¼ 6  1014 Hz, f0 ¼ 40 MHz and q ¼ 20 ), the tilt angle would be approximately 10
5 degrees. 7.4 Seeding

In LDA, it is not actually the velocity of the flow that is measured, but rather the velocity of particles suspended in the flow. In this respect, these seeding particles can be considered to be the actual velocity probes, and seeding considerations are thus important in LDA. The particles must be small enough to track the flow accurately, yet large enough to scatter sufficient light for the photodetector to be able to detect the Doppler frequency. Ideally, the particles should also be neutrally buoyant in the fluid; that is, they should have approximately the same density as the fluid itself, but in many experiments this is a secondary consideration. In outlining the desired properties of seeding particles, Durst et al. [1] have suggested that particles of which the motion is used to represent that of a fluid should be: . .

able to follow the flow good light scatterers

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. . . . . .

conveniently generated cheap nontoxic, noncorrosive, and non-abrasive nonvolatile, or slow to evaporate chemically inactive clean.

7.4.1 Seeding as Flow Field Tracers

In general, the motion of particles suspended in a fluid is affected by: (i) the particle shape; (ii) the particle size; (iii) the relative density of the particle and fluid; (iv) the concentration of particles in the fluid; and (v) those forces exerted only on the surface of the particle (body forces). The shape of the seeding particles affects the drag exerted on them by the surrounding fluid, while the size of the particles along with their relative density influences their response to velocity changes of the surrounding fluid. The concentration of the particles affects their motion through interaction between different particles; however, in practice the concentrations used are normally so low that such particle interaction can be neglected. Body forces, such as gravity, can also normally be ignored, except in very slow flows, where the buoyancy of the seeding particles may be an issue. In experiments that include the use of electrostatic fields the body forces may be important, although in such cases they will most likely form part of the experiment and so cannot really be considered a disturbance. Since the analysis of particle motion is rather complicated even for spherical particles, and “real” particles cannot easily be modeled, only spherical particles in an infinite fluid have been analyzed. It is assumed, that these results would also apply qualitatively for particles of more irregular shape. Such an assumption is good for liquid particles and fair for monodisperse solid particles, but poor for other solid particles, such as agglomerates. Basset derived the equation of motion for a sphere relative to an infinite, stagnant fluid in 1888 [2], and this was later expanded by Hinze [3] to a moving fluid, considering the instantaneous velocity V Up
Uf, of the particle relative to the fluid [1]: t

ð p 3 dUp p 3 dUf p 3 dV 3 2 pffiffiffiffiffiffiffiffiffiffiffi dV dj dp rp 6 dt ¼
3 p m dp V þ 6 dp rf dt
12 dp rf dt
2 dp pmrf dj pffiffiffiffiffiffiffiffi t
j t0

|fflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflffl} Accelerating force

|fflfflfflffl{zfflfflfflffl} Stokes viscous drag

|fflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflffl} Pressure gradient force on fluid

|fflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflffl} |fflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl{zfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflfflffl} Fluid Drag force resistance to associated with accelerating unsteady motion sphere ð7:13Þ

where the subscript p refers to the seeding particle, and the subscript f to the fluid.

7.4 Seeding

The first term in this equation represents the force required to accelerate the particle, while the second term describes the viscous drag, as given by Stokes law. Acceleration of the fluid produces a pressure gradient in the vicinity of the particle, and hence an additional force on the particle, as described by the third term. The fourth term is the resistance of an inviscid fluid to acceleration of the sphere, and is predicted by potential flow theory. The final term is the “Basset history integral,” which represents the drag force arising from derivation of the flow pattern from that occurring in steady flow. Note that when the first, third, and fourth terms are combined, the accelerating force is equivalent to that of a sphere whose mass is increased by an additional “virtual mass” equal to half the mass of the displaced fluid. The above equation is valid within the following assumptions: . . . . .

The turbulence is homogeneous and time-invariant. Particles are smaller than the turbulence microscale. Stokes drag law applies (the particles are spherical). Particles are always surrounded by the same fluid molecules. There is no interaction between particles.

Furthermore external forces, such as gravitational, centrifugal, and electrostatic forces have been ignored. 7.4.2 Light Scattering by Small Particles

Depending on the nature of the flow, seeding particles used for LDA measurements usually have particle diameters ranging from 0.1 to 50 mm. This is comparable to the wavelength of the light used, which for a green Nd: YAG is 532 nm or a Ar-Ion laser is 514.5 nm, 488 nm, and 476 nm for green, blue, and violet, respectively. With particle sizes comparable to the wavelength of light, the Lorenz–Mie light scattering theory applies [33]. This theory considers spherical particles, and thus describes only the dependency on particle size, although in practice the shape and orientation of seeding particles also play a major role in the scattering of light. Although, in general, large particles scatter more light than their smaller counterparts, particle size also affects the spatial distribution of the scattered light, as shown in Figure 7.6. The radial scale is logarithmic to allow for the large difference between forward and backscattering intensities. For large particles, the ratio of forward to backward scattered light can be in the order of 100, while smaller particles scatter more evenly. For large seeding particles, direct surface reflection generally dominates the scattered light, and the intensity is thus roughly proportional to the square of the particle diameter. For smaller particles, diffraction plays a major role in the light scattering, and polarization of the incident light has a significant influence. This is particularly important when using sub-micron seeding particles, which may be required for measurements in supersonic flows and/or shocks.

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7.4.3 Type and Size of Seeding Particles

The choice of seeding depends on a number of parameters. Primarily, the seeding material should be chosen considering the flow that is to be measured. In general, seeding particles should be chosen as large as possible in order to scatter the most light; however, the particle size will be limited because too-large particles will not track the flow properly. In general, the maximum allowable particle size decreases with increasing flow velocity, turbulence, and velocity gradients. Finally, consideration should be made as to how the flow might be seeded. In some applications, such as engines, the use of solid and very abrasive particles is simply not possible, whereas in others the natural concentration of very small particles (e.g., ash and coal powder) can also be used as tracers. Typical seeding materials for use in air flows, and in particular in flame and hot environments, are detailed in Table 7.1 [5–8]. 7.4.4 Seeding Particles Generator

LDA measurements in combustion, where the temperature is high, very often require the use of solid particles such as Al2O3, SiO2, or TiO2. The generation and Table 7.1 Typical seeding particles for LDA measurements.

Material

Particle diameter (mm)

Melting point (K)

Al2O3 (aluminum oxide powder)

Between 0.05 and a few mm

SiO2 (silicon oxide particles)

1–5

TiO2 (titanium dioxide powder)

From sub-micron to tens of microns

2100

Poorer light scatterer at high temperature. Very wide size distribution and lumped particle shapes. Can be used in engines [9]

MgO (magnesium oxide)

> 1

ð8:8Þ

8.3 LIF Applications

is true, then Equation 8.6 will simplify to Sf /

nf nfuel / nquench noxygen

ð8:9Þ

if the fluorescing molecules are seeded to the fuel and the dominant quencher available is oxygen. In this case, this strategy is called fuel/air-ratio LIF (FAR-LIF). This usually is applied to mixture analysis in internal combustion engines, where a nonfluorescing model fuel is seeded with a special LIF tracer. Commonly used FARLIF tracers include toluene, benzene, xylol, and triethylamine [22–27]. Other excited tracer molecules, which generally are ketone tracers such as acetone or 3-pentanone [28–30], are known not to be quenched by collisions with oxygen. Consequently, the denominator in Equation 8.6 is close to 1 and the fluorescence signal Sf is proportional to the tracer molecular number density. Then, the LIF signal represents the fuel molecular number density. Sf / nf / nfuel

ð8:10Þ

Whenever kStern-Volmer
nquench is neither much bigger than 1, nor close to zero, the quantitative interpretation of LIF signals is possible only under saturated conditions, when the laser excitation intensity is high enough to make the LIF signal insensitive towards excitation energy. Details concerning saturation LIF can be found elsewhere [11–14]. Often, a quantitative interpretation of LIF signals is not required, since in many applications qualitative LIF data have already provided the desired insight into combustion systems. An example of this is the visualization of the flame front or of the heat release zone, mixture formation analysis, and flow tagging or optical flow investigations [9, 31–34]. For these applications a variety of LIF tracers for gas-phase systems and liquid fuels has been identified.

8.3 LIF Applications 8.3.1 LIF of Combustion Species

Whenever possible, from an experimental point of view it is advantageous to execute LIF measurements utilizing atoms or molecules already present in the process under examination. In the case of flames, combustion intermediate species are commonly probed and, when appropriately selected, these species can indicate characteristic regions of the flame so as to provide information about the combustion process. Some of these are generated as intermediate species during the reaction, and therefore indicate high heat release rates and reaction zones [35–41], whereas others are reactants or combustion products. A summary of typical combustion species probed by LIF is provided in Table 8.1.

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Table 8.1 Commonly used combustion species for LIF applications.

Species

Application

CH, C2, HCO, CN, OH, O, H CO, C2H2, CH, CH2O, O2, NO2 OH, CO NO, OH

Flame front (reaction zone) Fuel decomposition and pre-reaction zone Burned gas and post-reaction zone Temperature

The first applications visualizing OH were reported during the 1980s [16, 42, 43], and overviews are available in several reviews (e.g., Refs. [6, 16, 40, 44, 45]). Since turbulent flames are rather complex, the visualization of a single species may not deliver sufficient information for an unambiguous interpretation. For this reason, in many of the studies conducted throughout the past decade, different combinations of planar diagnostics have been developed involving PLIF of at least one species. The most common combination in this respect has been the simultaneous imaging of CH and OH radical distributions, as illustrated in Figure 8.2. A second pair of molecules which continues to attract interest is that of OH and formaldehyde, because the pixelby-pixel product of the images correlates very well in space and time with the flame heat release [46, 47]. An overview of the different approaches in relation to combined 2-D diagnostics is available in Ref. [48]. When LIF is used, for example to track the progress of an elementary reaction or to visualize flame structures, quantitative information is usually not required. Another

Figure 8.2 Simultaneous CH/OH PLIF images [49].

8.3 LIF Applications

possible application, where semi-quantitative data are sufficient, is that of thermometry, when the intensity ratios of different spectral lines provide information concerning the Boltzmann distribution and allow the derivation of temperature (see Figure 8.1). This point is discussed in more detail elsewhere [7], with recent studies also having been carried out (e.g., Ref. [50]). In contrast, when studies of chemical kinetics are performed, it is necessary to include quantitative concentration measurements of the species of interest. In this case, the concentration must be deduced from the intensity of the fluorescence signal, which means that in principle all of the processes occurring must be considered, and the photophysics of the species of interest must be understood in detail. Today, this is the case for atoms and diatomic molecules only. The major challenge in a flame environment is that the gas composition is barely known with the required accuracy for signal quantification. Moreover, thermodynamic equilibrium cannot always be assumed in a reacting flow. A detailed description of quantitative LIF in flames, including a discussion of influences such as quenching and internal energy decay mechanisms, has been provided by Kohse-H€ oinghaus [7]. Under certain circumstances, a number of different naturally fluorescing species may also be present in the combustion systems. These might include aromatics in commercial fuels [51–53], odor markers [54] in natural gas or fluorescing molecules, which are generated during combustion [55] (e.g., formaldehyde as a combustion intermediate in cool flame zones before any reaction takes place [56, 57]; see also Vol. 1 Ch. 12), or polycyclic aromatic hydrocarbons (PAHs) during fuel-rich combustion [58]. 8.3.2 Tracer LIF

When the species that are naturally present in a combustion system do not fluoresce, or are not suitable to provide the desired information, then tracer atoms or molecules must be added artificially. The choice of potential tracers is driven by the trade-off between a minimal perturbation of the system under investigation, and maximal LIF signal intensity. Perturbing tracers should feature high absorption cross-sections and high FQYs, allowing low seeding concentrations. Whereas, tracers with modest absorption cross-sections and/or modest FQYs, should be nonperturbing, allowing high seeding concentrations. Whichever situation applies, the seeding should be adjusted to levels which avoid attenuation of the incident laser beam or fluorescence trapping, and different classes of tracers have been used to achieve this (see Table 8.2). A comprehensive overview of this subject is provided elsewhere [9]. 8.3.2.1 Metal Salts Some metal salts, when seeded into the combustion system, may be atomized in the flame front due to the high temperature present [59]. When these atoms have been generated, they can be excited by both ultraviolet (UV) and visible light sources, and so qualify especially for burned gas temperature measurements [50]. However, great care must be taken not to saturate the strong transitions [60, 61].

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Applicability of different artificially seeded tracer species for flame thermometry (FT), mixture composition analysis (MC), and mixture temperature analysis (MT).

Tl (TlCl)

Inorganic molecules

NO2

CO2

.

NO

.

Aromatic compounds

Xylene Benzene Naphtalene Triethylamine

Aliphatic compounds with chromophores

Organic molecules

. .

SO2

Toluene

Trimethylamine

Biacetyl

Acetone

3-Pentanone

MT

. .

. . . . . . . . . . . . .

Seeded to the combustion system as metal salts dissolved in a liquid; especially suitable for burned gas temperature analysis Excitable @ 532 nm Strongly quenched and highly corrosive; generated from sulphur precursors during combustion Excitable only at very high temperatures; broadband absorption, therefore its LIF signal interference with signals from other species and hot CO2 may absorb LIF signals of other species Toxic, but excellently characterized; applicable even in multi-phase flows Simultaneous temperature & composition analysis possible; excellently characterized Toxic; not comprehensively characterized Very toxic; used in combination with other tracers (exciplex LIF) Diesel fuel tracer, as it is a double ring aromat High FQY; unpleasant smell, used in combination with other tracers (exciplex LIF) Gaseous at ambient conditions, therefore suitable for seeding gaseous fuels like H2; unpleasant smell Excitable @ 355 nm; therefore suitable for high-speed applications Simultaneous temperature & composition analysis possible; excellently characterized Simultaneous temperature & composition analysis possible; excellently characterized Indicating the fuel/air-ratio; FAR-LIF tracer

In (InCl)

Comments

Indicating the tracer number density

Atoms (metal salts)

FT

Tracer class

MC

Table 8.2

8.3 LIF Applications

8.3.2.2 Inorganic Molecules The class of small inorganic molecules comprises unstable species, which are generated naturally during combustion (see Section 8.3.1) and stable molecules that must be added artificially to the flow. Among these, NO2 is the only molecule that can be excited to fluorescence in the visible with a frequency-doubled Nd : YAGlaser. SO2 is highly corrosive and can be excited to fluorescence in the UV [62–64]; however, the SO2 fluorescence is strongly quenched by different molecules, including N2 [63, 65–68]. At high temperatures, the CO2 broadband absorption spectrum shifts from the vacuum UV to the UV, and therefore its fluorescence can be excited with UV laser sources [36, 69, 70]. Despite its toxicity, NO was used as a temperature-indicating LIF tracer [35, 37, 71–73] (see also Figure 8.1). Even under highly challenging spray conditions, evaporative cooling effects could still be analyzed [74, 75]. 8.3.2.3 Organic Molecules Among organic molecules, only aromatic molecules and aliphatic molecules with chromophores can be excited to fluorescence. Aromatic molecules are excellent tracers, as they are naturally present in standard fuels. Aromatics are normally used as FAR-LIF tracers (see Equation 8.8) [23–25, 27, 76, 77], although other applications of aromatic tracers are known to be used in excited complex (exciplex)-LIF strategies [22, 78–80] in order to spectrally separate the liquid and evaporated gaseous phases. 8.3.2.4 Aliphatic Molecules Fluorescing aliphatic molecules with chromophores are represented by amines, aldehydes, and ketones. Amine LIF tracers such as ethylamine [81], N,N-dimethyl aniline [82] and triethylamine [22] may be used as FAR-LIF tracers; trimethylamine, which is gaseous under ambient conditions, is a promising FAR-LIF tracer candidate for gaseous fuel combustions systems, notably in the hydrogen internal combustion engine [26, 83]. Ketones are most frequently used for mixture analysis investigations [9]. Biacetyl, the attractive spectroscopic properties of which have been extensively studied [84–86], is less popular than simple ketones, as its boiling point of 88  C is too high to assure sufficient seeding levels to gaseous combustion systems, but significantly below that of typical liquid fuels. As biacetyl can be excited to fluorescence with solid-state high-repetition-rate lasers at 355 nm, highspeed LIF strategies have motivated its upcoming application [88]. Acetone and 3-pentanone are the most frequently used LIF tracers [28, 29, 58, 88–96]. Due to the low boiling point of acetone, the high vapor pressure allows high seeding levels in gaseous combustion systems. 3-Pentanone is normally used as a LIF tracer in liquid gasoline fuels [29, 97, 98]. As ketone tracers are assumed not to be quenched by oxygen collisions, a quantitative interpretation of LIF signals is possible, according to Equation 8.10. Due to the frequent applications of ketone tracers, the absorption crosssections and FQYs of acetone and 3-pentanone LIF tracers are photophysically well understood, and have already been described by semi-physical models [30, 99–102].

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Figure 8.3 Simultaneous number density and temperature acetone LIF measurements in an internal combustion engine [100]. The fuel, but not the intake air, was seeded with acetone (inverse tracing).

Hence concentration and temperature analyses [103], as illustrated in Figure 8.3, may be carried out simultaneously [99, 101, 104–107]. When considering aromatic LIF tracers, only toluene LIF is sufficiently understood to carry out fuel/air-ratio and temperature analyses simultaneously [23, 24, 108]. 8.3.3 High-Speed LIF

Planar LIF, at high repetition rates, is an emerging procedure that complements both single- and two-point techniques [109–111]. Although the details of very few

8.3 LIF Applications

high-speed PLIF approaches have been reported to date, they are reviewed briefly here without providing details of the combustion system to which they were applied. Basically, high-speed PLIF represents a particular form of tracer LIF that is capable of detecting combustion-generated OH radicals in most cases, or just the biacetyl tracer when applied to engines. The pioneering studies of Kaminski et al. [112] have provided fascinating insights into the dynamics of turbulence–chemistry interaction in combustion processes. Kaminski’s group used a Nd : YAG laser cluster that generated a pulse burst of up to eight pulses, pumping a dye laser. The PLIF signal was detected by using eight image-intensified charge-coupled devices (ICCDs) integrated into one camera system. Based on this technology, the early phases of spark ignition in homogeneous turbulence were investigated [113]. The temporal evolution of flame front wrinkling, which was seen to depend on the turbulence level, fuel composition and equivalence ratio, was followed and qualitatively compared to direct numerical simulations (DNS). In a follow-up study, high-speed OH PLIF at 33 kHz was combined with stereoscopic particle image velocimetry (PIV) and double-pulsed Rayleigh imaging. The individual extinction events within a turbulent diffusion jet flame were correlated to local strain fields and vortical structures [114]. The study results showed clearly the value of full three-dimensional (3-D) velocity vectors obtained from stereoscopic PIV in avoiding ambiguities due to out-of-plane motion. The eight-pulse burst laser was also applied to study cycle-to-cycle variations in internal combustion engines [115], whereby the sequences of fuel tracer or OH radical distribution were monitored during single engine cycles. The local flame front propagation could be deduced simply by tracking the fuel tracer distribution. By scanning the laser beam perpendicularly to the light sheet plane, 3-D fuel concentrations could be reconstructed from the multiple, quasiinstantaneous, 2-D measurements. The ongoing activities on high-repetition-rate burst mode operation are aimed at achieving pulse trains that contain up to 100 single pulses at high energies [116]. Several groups have demonstrated continuous pulse sequences in PLIF applications, the first appearing in 2006 [87, 117, 118], in which PLIF was combined with high-speed PIV. In one of these investigations [117], the relative OH distribution at 1 kHz was temporally tracked in a swirled lean premixed flame during flashback, while in another [88] simultaneous fuel tracer biacetyl PLIF and two-component PIV was demonstrated, at a repetition rate of 12 kHz, in an atmospheric pressure jet that showed similar instabilities to vortex shedding. This approach was also used to track, temporally, the fuel distribution in a direct-injection internal combustion engine close to the spark plug [119]. Following a correction and calibration procedure, the time history of fuel concentration was quantified, describing the ignition and early flame development. The use of an all-solid-state Yb : YAG disk laser system with 1 kHz repetition rate to excite an OH hot band transition with single-pulse energies of 3.7 mJ and a reasonable signal-to-noise ratio (SNR), was achieved despite low fluorescence quantum yields [120]. Repetition rates of frequency-doubled dye lasers were increased to 5 kHz [121], exciting OH and a remarkable improving the SNR, despite the pulse energies being

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Figure 8.4 Individual extinction events measured by simultaneous OH PLIF/PIV. The black lines denote instantaneous flame front locations deduced from relative OH

distributions. The arrows indicate two components of the flow field from which vorticity (columns 1 and 3) and strain fields (columns 2 and 4) were calculated [125].

as low as 22 mJ. In combination with two-component PIV, the same instrument was used to study extinction and spark ignition [122] in turbulent opposed jet flames. For this, the OH PLIF was combined with stereoscopic PIV, such that the out-of-plane motion could be involved in the interpretation of the flame dynamics at the flame base [123, 124]. In order to demonstrate the new perspective enabled by planar imaging at high repetition rates, Figure 8.4 shows the temporal development of the flow field interacting with the flame prior to extinction in a turbulent opposed jet flame. In this sequence, the instantaneous location of the flame front (shown as a black line) was deduced from the relative OH radical distribution. The out-of-plane vorticity and 2-D strain were each calculated from the in-plane velocity components, as measured with PIV. The instant at which the flame breached was set to zero. Therefore times before the onset of extinction were defined as negative. 8.3.4 Combined LIF Techniques

When LIF tracers are used for which the signal intensity is unaffected by intermolecular interactions (as for ketones, for example), the resultant signals must not always be interpreted on a molecular-scale mixing level. A combination of LIF with

8.4 Instrumentation

phosphorescence measurements of the same molecule [126], or the simultaneous use of two tracer molecules that transfer energy towards each other (sensitized phosphorescence), can be used to provide mixing information on a molecular scale [127]. When an internal combustion engine is operated under a high exhaust gas recirculation rate, it is not only the fuel–air ratio but also the fuel and oxygen concentrations that govern the combustion. A two-tracer strategy, as proposed by Koban et al. [77] and using a FAR-LIF tracer and a ketone tracer, is effective under these conditions. Quite complex experimental set-ups were created for the simultaneous measurement of the fuel–air ratio, the liquid fuel temperature, and the liquid phase distribution [128]. The combination of LIF measurements with other diagnostic techniques, so as to simultaneously probe scalar properties and or velocity fields, may provide information regarding the modeling strategies of the Navier–Stokes equation approximations [39, 129–131]. A more comprehensive overview of miscellaneous techniques is provided in Chapter 1. 8.4 Instrumentation

The different aspects in the choice of appropriate equipment or particular applications have been discussed previously, in combination with the application of LIF. Consequently, some details will be provided here that focus mainly on high-speed LIF, since this is not only the most recently introduced LIF technique but also has major prospects for future development and applications. As no comprehensive information on suitable light sources and detector systems has yet been reported on this subject, some basic information is included in the following sections. 8.4.1 Excitation Sources

As PLIF is based on resonant excitation, tunable lasers are mandatory for the electronic excitation of small molecules (see Figure 8.5). In contrast, for larger

Figure 8.5 Experimental set-up for PLIF measurements in a flame. SHG ¼ second harmonic generation crystal.

j231

OH

CH

CO

Excitation with tunable dye lasers or OPOs pumped with frequency doubled or tripled Nd : YAG lasers @ 532 or 355 nm, respectively.

NO

Ketones

Amines

Formaldehyde

Lasers with fixed emission wavelengths are used for excitation. Typical laser sources are excimer lasers filled with KrF or XeCl gas with emission wavelengths of 248 or 308 nm, respectively, and Nd : YAG lasers, operated in their fourth and third harmonic frequency at 266 and 355 nm, respectively.

Aromatics

Excitation with a Nd : YAG laser @ 532 nm

SO2

CO2

Broadband absorption

Large molecules

NO2

Small molecules

LIF accessibility of different species with different laser sources.

Defined absorption lines

Table 8.3

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8.4 Instrumentation Table 8.4 Excitation sources for high-speed applications.

Single-pulse energy Repetition rate

Pulse bursts high single pulse energy [116]

Continuous operation (all-solid state lasers) low single pulse energy

100s of mJ Up to MHz within one burst; the burst repetition rate is typically 10 Hz

Up to 10 mJ 1–30 kHz

molecules with broad excitation bands, such as formaldehyde [132] or commonly used fuel-tracers such as ketones, amines or aromatics [9], lasers with fixed-emission wavelengths can be employed (see Table 8.3 for an overview). Laser repetition rates exceeding 1 kHz are required for the acquisition of statistically correlated data. A high pulse repetition rate can be achieved by using either pulse bursts with high single-pulse energies, or with a continuously pulsed operation that has much lower single-pulse energies (see Table 8.4). Among the all-solid-state lasers for continuous operation, two types are currently available on a commercial basis, which exhibit pulse durations above 90 ns or below 15 ns, respectively. As long-pulse lasers produce lower intensities, an intracavity frequency conversion will be required to generate either visible or UV light. Shorter pulse durations allow extracavity frequency conversion [133]. Other specifications, such as the M2-factor, may differ significantly. The frequency-doubled or -tripled radiation from all-solid-state lasers can be used either directly for LIF [86, 118], or to pump dye lasers so as to produce tunable radiation that can be frequency-doubled into the UV region [115, 119–122]. In contrast to the burst-mode operation, the challenge here is to pump dye lasers with single-pulse energies below 10 mJ but quasi-continuous power levels up to 50–100 W. Obviously, higher pulse intensities of short-pulsed pump lasers are beneficial, especially for subsequent frequency conversion into UV. In order to avoid any bleaching of the dye and significant triplet-state population, the flow rate of the dye solution must be increased. Flow rates of these devices are typically up to 12 l min 1. In addition lowest possible oscillator laser thresholds are needed. Based on the most recent laser designs, at 10 kHz 2.4 W was achieved at about 282 nm, using 50 W of pump power. 8.4.2 Detection Strategies

The planar detection of LIF requires not only suitable optics but also a sensitive array detector. In the case of fluorescence within the UV range, the collection lens must be UV-transparent, and the array detector UV-sensitive. Similar to common chargecoupled devices (CCDs), complementary metal-oxide semiconductor (CMOS) cameras are not UV-sensitive, and for this reason (and also for shorter gating times) the

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Figure 8.6 Snapshots of raw OH distributions recorded by PLIF. For otherwise identical conditions, the SNR improved remarkably by increased collection efficiency of the UV lens.

array detectors must be combined with image intensifiers (either lens or fiber-coupled) in order to temporally discriminate the flame luminosity from the desired LIF signal. Due to the lower LIF signal intensities at high laser repetition rates, two-stage intensifiers are frequently used. Present-day technology, which involves combining a multichannel plate (MCP) with a booster, will allow frame rates exceeding 20 kHz without electron depletion, which in turn reduces the effective dynamic range. As high repetition rates go hand-in-hand with low LIF-signal intensities, high collection efficiencies are mandatory. Raw OH PLIF data, recorded in the flame brush of an unconfined lean premixed methane–air flame, are presented in Figure 8.6. In this case, the laser system was tuned to the Q1(6) line within the A2S þ X2P (1-0) band, and the single-pulse energy was 22 mJ. For otherwise identical conditions, the UV-lens was changed from 105/f#4.5 to 100/f#2.0 (camera lens focal length in mm/ camera lens f-number). This simple measure improved the SNR by an order of magnitude. A variety of different array detectors suitable for PLIF applications can be operated at high framing rates. Typically, CCD cameras can be operated at repetition rates into the MHz regime [113, 134], the main disadvantage being that only a relatively small number of frames is contained in a sequence, as the memory buffer integrated to each pixel will limit the in situ storage capacity. Depending on the type of the chip-design, up to 100 frames can be recorded during one sequence, with the image sizes being independent of the repetition rates and typically comprising less than 100 000 pixels within a rectangular array. High frame rates can also be achieved with CMOS cameras [115–122]. The key difference between a CMOS array detector and a CCD, is that the charge-to-voltage

8.5 Outlook and Summary

conversion occurs at each individual pixel. In line with a multitude of analogue/ digital converters, the information read-out is parallel rather than serial, as in a CCD. The digitized images are transferred to an on-board memory, which for a given image size and dynamic range will limit the number of frames that can be recorded during one sequence. However, as the largest on-board memories are currently up to 16 GB, thousands of frames can be recorded during a single run. In comparison to CCDs, this feature allows the temporal tracking of transients in combustion for much longer periods of time. This is clearly beneficial, as the time-intervals of interest may often spread over tens of milliseconds. Although high frame rates exceeding 500 kHz are possible with CMOS cameras, the number of active pixels is greatly reduced under these conditions. At lower frame rates (i.e., 5 kHz), a mega pixel resolution is available commercially and, similar to CCDs, the dynamic range of CMOS cameras can be as high as 14 bit. However, whereas CCDs are available in scientific-grade quality, CMOS cameras are much less optimized in terms of their homogeneity or linearity, mainly because they are used for very different purposes in industry, such as automotive crash tests. These current problems with CMOS cameras undoubtedly hamper their use in quantitative scalar imaging, particularly as a calibration per pixel must be performed in order to account for varying intensity offsets, sensitivities, and possible nonlinearities.

8.5 Outlook and Summary

LIF represents an excellent means of analyzing combustion-related phenomena, whether to assist in combustion chemistry processes, in flame structures and heat release, prior to combustion to analyze mixing phenomena, or after combustion to analyze the pollutants formed. As complex combustion processes are governed by a sophisticated interaction of flow and chemistry, in combination with heat and mass transfer, modern LIF approaches are aimed at probing multiparameters both twodimensionally and simultaneously. This can be realized not only by combining LIF with PIV, so as to combine scalar and vector distributions, but also by the simultaneous application of LIF and Rayleigh scattering for concentration and temperature determinations, or by applying more complex LIF techniques that are capable of capturing – simultaneously – more than one scalar distribution, such as concentration, mole fraction or fuel–air ratio, and temperature. Moreover, high-speed LIF applications, when combined with PIV, can provide temporally correlated information about turbulent combustion, and also allow new insights into singular phenomena such as local extinction and reignition. Oxygen quenching, which is intrinsically tied to combustion systems, can be overcome by using picosecond technology in excitation and detection. Another promising approach is the use of slightly broadband laser sources, which can cover a certain spectral range and allow the simultaneous excitation of multiple transitions, resulting in a significantly improved SNR. Clearly, the potential of modern LIF techniques in combustion research and development can only be described as vast.

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Measurements of picosecond laser induced fluorescence from gas phase 3pentanone and acetone: Implications to combustion diagnostics. Appl. Phys. B, 64, 493–502. Berckm€ uller, M., Tait, N.P., Lockett, R.D., Greenhalgh, D.A., Ishii, K., Urata, Y., Umiyama, H., and Yoshida, K. (1994) Incylinder crank-angle-resolved imaging of fuel concentration in a firing sparkignition engine using planar laserinduced fluorescence. Proc. Combust. Inst., 25, 151–156. Wolff, D., Schlueter, H., Beushausen, V., and Andresen, P. (1993) Quantitative determination of fuel air mixture distributions in an internal combustion engine using PLIF of acetone. Phys. Chem. Chem. Phys., 97, 1738–1741. Green, R.M. and Cloutman, L.D. (1997) Planar LIF observations of unburned fuel escaping the upper ring-land crevice in an SI engine. SAE Technical Paper Series 970823. Bryant, R.A., Donbar, J.M., and Driscoll, J.F. (2000) Acetone laser induced fluorescence for low pressure/low temperature flow visualization. Exp. Fluids, 28, 471–476. Arnold, A., Buschmann, A., Cousyn, B., Decker, M., Vannobel, F., Sick, V., and Wolfrum, J. (1993) Simultaneous imaging of fuel and hydroxyl radicals in an in-line four cylinder SI-engine. SAE Technical Paper Series 932696. Neij, H., Johansson, B., and Alden, M. (1994) Development and demonstration of 2D-LIF for studies of mixture preparation in SI engines. Combust. Flame, 99, 449–457. Einecke, S., Schulz, C., Sick, V., Dreizler, A., Schiessl, R., and Maas, U. (1998) Two-dimensional temperature measurements in a SI engine using twoline tracer LIF. SAE Technical Paper Series 982468, pp. 1060–1068. L€offler, M., Kr€ockel, K., Koch, P., Beyrau, F., Leipertz, A., Grasreiner, S., and Heinisch, A. (2009) Simultaneous quantitative measurements of temperature and residual gas fields inside a fired SI-engine using acetone laser-

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induced fluorescence. SAE Technical Paper Series 2009-01-0656. L€ offler, M., Pfadler, S., Beyrau, F., Leipertz, A., Dinkelacker, F., Huai, Y., and Sadiki, A. (2008) Experimental determination of the sub-grid scale scalar flux in a non-reacting jet-flow. Flow Turb. Combust., 81, 205–219. Thurber, M.C., Grisch, F., and Hanson, R.K. (1997) Temperature imaging with single- and dual-wavelength acetone planar laser-induced fluorescence. Opt. Lett., 22, 251–253. Kearney, S.P. and Reyes, F.V. (2003) Quantitative temperature imaging in gasphase turbulent thermal convection by laser-induced fluorescence of acetone. Exp. Fluids, 34, 87–97. Einecke, S., Schulz, C., and Sick, V. (2000) Measurement of temperature, fuel concentration and equivalence ratio fields using tracer LIF in IC engine combustion. Appl. Phys. B, 71, 717–723. Thurber, M.C., Grisch, F., Kirby, B.J., Votsmeier, M., and Hanson, R.K. (1998) Measurements and modeling of acetone laser-induced fluorescence with implications for temperature-imaging diagnostics. Appl. Opt., 37, 4963–4978. Thurber, M.C. and Hanson, R.K. (1999) Pressure and composition dependences of acetone laser-induced fluorescence with excitation at 248, 266, and 308 nm. Appl. Phys. B, 69, 229–240. Thurber, M.C., Kirby, B.J., and Hanson, R.K. (1998) Instantaneous imaging of temperature and mixture fraction with dual-wavelength acetone PLIF. AIAA 980379. Koban, W., Koch, J.D., Hanson, R.K., and Schulz, C. (2004) Absorption and fluorescence of toluene vapor at elevated temperatures. Phys. Chem. Chem. Phys., 6, 2940–2945. Meyer, T.R., King, G.B., Gluesenkamp, M., and Gord, J.R. (2007) Simultaneous high-speed measurement of temperature and life-time corrected OH laser-induced fluorescence in unsteady flames. Opt. Lett., 32, 2221–2223. Renfro, M.W., Guttenfelder, W.A., King, G.B., and Laurendeau, N.M. (2000)

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Scalar time-series measurements in turbulent CH4/H2/N2 nonpremixed flames: OH. Combust. Flame, 123, 389–401. Zhang, J., Venkatesan, K.K., King, G.B., Laurendeau, N.M., and Renfro, M.W. (2005) Two-point time-series measurements of minor-species concentrations in a turbulent nonpremixed flame. Opt. Lett., 30, 3144–3146. Kaminski, C.F., Hult, J., and Alden, M. (1999) High repetition rate planar laser induced fluorescence of OH in a nonpremixed flame. Appl. Phys. B, 68, 757–760. Kaminski, C., Hult, J., Alden, M., Lindenmaier, S., Dreizler, A., Maas, U., and Baum, M. (2000) Spark ignition of turbulent methane/air mixtures revealed by time resolved laser induced fluorescence and direct numerical simulations. Proc. Combust. Inst., 28, 399–405. Hult, J., Meier, U., Meier, W., Harvey, A., and Kaminski, C.F. (2005) Experimental analysis of flame extinction in a turbulent jet diffusion flame by high repetition 2-D laser techniques and multi-scalar measurements. Proc. Combust. Inst., 30, 701–709. Hult, J., Richter, M., Nygren, J., Alden, M., Hultqvist, A., Christensen, M., and Joansson, B. (2002) Application of a highrepetition-rate laser diagnostic system for single-cycle-resolved imaging in internal combustion engines. Appl. Opt., 41, 5002–5014. Jiang, N., Webster, M.C., and Lempert, W.R. (2009) Advances in generation of high repetition rate burst mode laser output. Appl. Opt., 48, B23–B31. Konle, M., Kiesewetter, F., and Sattelmayer, T. (2008) Simultaneous high repetition rate PIV-LIF-measurements of CIVB driven flashback. Exp. Fluids, 44, 529–538. Konle, M., Winkler, A., Kiesewetter, F., W€asle, J., and Sattelmayer, T. (2006) CIVB flashback analysis with simultaneous and time resolved PIV-LIF measurements. 13th International Symposium on the Application of

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j 8 Laser-Induced Fluorescence

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Laser Techniques to Fluid Mechanics, Lisbon, Portugal. Smith, J.D. and Sick, V. (2007) Quantitative, dynamic fuel distribution measurements in combustion-related devices using laser-induced fluorescence imaging of biacetyl in iso-octane. Proc. Combust. Inst., 31, 747–755. Paa, W., M€ uller, D., Stafast, H., and Triebel, W. (2007) Flame turbulence recorded at 1 kHz using planar laser induced fluorescence upon hot band excitation of OH radicals. Appl. Phys. B, 86, 1–5. Kittler, C. and Dreizler, A. (2007) Cinematographic imaging of hydroxyl radicals in turbulent flames by planar laser-induced fluorescence up to 5 kHz repetition rate. Appl. Phys. B, 89, 163–166. Heeger, C., B€ohm, B., Ahmed, S.F., Gordon, R., Boxx, I., Meier, W., Dreizler, A., and Mastorakos, E. (2009) Statistics of relative and absolute velocities of turbulent non-premixed edge flames following spark ignition. Proc. Combust. Inst., 32, 2957–2964. Boxx, I., Heeger, C., Gordon, R., B€ohm, B., Dreizler, A., and Meier, W. (2009) On the importance of temporal context in interpretation of flame discontinuities. Combust. Flame, 156, 269–271. Boxx, I., Kittler, C., Gordon, R., B€ohm, B., Aigner, M., Dreizler, A., and Meier, W. (2009) Simultaneous three component PIV/OH PLIF measurements of a lifted, C3H8-argon diffusion flame at 1.5 kHz repetition rate. Proc. Combust. Inst., 32, 905–912. B€ ohm, B., Heeger, C., Boxx, I., Meier, W., and Dreizler, A. (2009) Time-resolved conditional flow field statistics in extinguishing turbulent opposed jet flames using high-speed PIV/OH PLIF. Proc. Combust. Inst., 32, 1647–1654. Hu, H. and Koochesfahani, M. (2002) A novel method for instantaneous,

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quantitative measurement of molecular mixing in gaseous flows. Exp. Fluids, 33, 202–209. Yip, B., Lozano, A., and Hanson, R. (1994) Sensitized phosphorescence: a gas phase molecular mixing diagnostic. Exp. Fluids, 17, 16–23. Wieske, P., Wissel, S., Gr€ unefeld, G., and Pischinger, S. (2006) Improvement of LIEF by wavelength-resolved acquisition of multiple images using a single CCD detector- Simultaneous 2D measurement of air/fuel ratio, temperature distribution of the liquid phase and qualitative distribution of the liquid phase with the multi-2D technique. Appl. Phys. B, 83, 323–329. Hiller, B. and Hanson, R.K. (1988) Simultaneous planar measurements of velocity and pressure fields in gas flows using laser-induced fluorescence. Appl. Opt., 27, 33–48. Pfadler, S., Beyrau, F., L€offler, M., and Leipertz, A. (2006) Application of a beam homogenizer to planar laser diagnostics. Opt. Express, 14, 10171–10180. Sadanandan, R., St€ohr, M., and Meier, W. (2008) Simultaneous OH-PLIF and PIV measurements in a gas turbine model combustor. Appl. Phys. B, 90, 609–618. B€auerle, B., Warnatz, J., and Behrendt, F. (1996) Time-resolved investigation of hot spots in the end gas of an S.I. engine by means of 2D-double-pulse LIF of formaldehyde. Proc. Combust. Inst., 26, 2619–2626. Li, D., Ma, Z., Haas, R., Schell, A., Simon, J., Diart, R., Shi, P., Hu, P., Loosen, P., and Du, K. (2007) Diode-pumped efficient slab laser with two Nd: YLF crystals and second-harmonic generation by slab LBO. Opt. Lett., 32, 1272–1274. Etoh, T.G., Poggemann, D., Kreider, G., Mutoh, H., and Theuwissen, A.J.P. (2003) An image sensor which captures 100 consecutive frames at 1000000 frames/s. IEEE T. Electron. Dev., 50, 144–151.

j243

9 Measurement of Particle Properties: Concentration, Size Distribution, and Density Matthias Gaderer, Robert Kunde, and Christian Brandt 9.1 Introduction

A suspension of particles and droplets in the size range of 0.001 to 100 mm in a surrounding gas phase is referred to as an aerosol, while the total mass of particles and droplets is termed particulate matter (PM). The total of all particles in ambient air is known as the total suspended particulate (TSP) matter, and is divisible into coarse and fine modes. A coarse mode refers to particles with a diameter greater than 1 mm, while a fine mode refers to a particle size less than 1 mm. Coarse mode particles typically originate from abrasion (wheels, brakes, etc.) and road dust resuspension, from the handling of bulk cargo, agricultural activities, and other industrial processes. In contrast, fine mode particles typically originate from the particle emissions of industrial processes, vehicle emissions, energy production, and home heating. Notably, they originate from all types of combustion processes that involve solid or liquid fuels. If inhaled, the majority of particles less than 10 mm in size will not be precipitated in the nose; moreover, those less than 1 mm in size (termed PM1) are able to trespass deep into the lungs such that they reach the alveoli. As a consequence, they may place stress on the lungs and eventually cause respiratory disease [1], because they are in fact breathable (see Vol. 1 Ch. 19). In contrast, the term PM10 refers to particles with an aerodynamic diameter less 10 mm, according to a separation efficiency of 50% in the sampling system. The term PM2.5 (for particles emission reduction), and also for plant operators (rapid identification of unburnt carbon ¼> intervention to the technology of combustion ¼> enhancement of efficiency ¼> saving of financial expenses). Clearly, the recording of measurements at large energetic units has generated many “challenges,” all of which must be solved if a more effective operation is to be achieved and methods of environmental protection improved.

References 1 Munsell Soil Color Charts (2000) 2

3

4

5

6

7

8

GretagMacbeth, New Windsor, New York. Metzger, M. (1987) Determination of carbon in fly ashes incineration processes. Fresen. J. Anal. Chem., 327 (7), 726–727. Fox, J.M. (2005) Changes in fly ash with thermal treatment. Available at: www.flyashinfo/2005/132fox.pdf,200511-25. Vassilev, S.V. and Vassileva, Ch.G. (2007) A new approach for the classification of coal fly ashes based on their origin, composition, properties and behaviour. Fuel, 86, 1490–1512. Godarzi, F. (2006) Characteristics and composition of fly ash from Canadian coal-fired power plants. Fuel, 85, 1418–1427 Beck, J., M€ uller, R., Brandenstein, J., Matscheko, B., Matschke, J., Unterberger, S., and Klau, H.R.G. (2005) The behaviour of phosphorus in flue gases from coal and secondary fuel combustion. Fuel, 84, 1911–1919. Juchelkov
a, D., Raclavsk
a, H., and Raclavsk
y, K. (2008) Application of color measurements for estimation of composition of ash formed by fluidizedbed combustion. (eds J. Werther, W. Nowak, K.E. Wirth, and E.U. Hartge), 9th International Conference on Circulating Fluidized Beds, Hamburg, pp. 518–524. Demmich, J. (2008) Gypsum case study. Recycling gypsum construction and demolition waste – Part II. The German model. Proceedings of the 27th

9

10

11

12

13

14

Eurogypsum Congress, 12–14 June, Brussels. Munsell, A.H. (1969) A Grammar of Color, Van Nostrand Reinhold, New York. Miller, B.G., Weber, G.F., and Gass, D.J. (1987) Pilot-scale evaluation of furnace sorbent injection for SO2 control firing Canadian low-rank coals. Fourteenth Biennial Lignite Symposium, Dallas, Texas, May 18–21. Morrison, J.L., Romans, D.E., Liu, Y., Hu, N., Pisupati, S.V., Miller, B.G., Miller, S.F., and Scaroni, A.W. (1994) Evaluation of limestones and dolostones for use as sorbents in atmospheric pressure Circulating Fluidized-Bed Combustors, Pennsylvania Energy Development Authority Final Report, PEDAFR-8934016, June 24, pp. 1–124. Harasek, M., Schausberger, P., Jordan, C., and Winter, F. (2001) Exit geometry effects on the fluidization on fine particles in CFB reactor: analysis by semi-theoretical and CFD modeling. Chem.-Ing.-Tech. (ECCE), 6, 628. Bis, Z. (1999) Circulating Fluidization of Poly-Dispersion Mixtures, Treatise No. 63, F Wydawnictwo Politechniki Czestochowskiej, Czestochowa. Bis, Z., Gajewski, W., Leszczy
nski, J., Nowak, W., Slomian, C., Werther, J., and Reppenhagen, J. (2000) Utilization of ultra-fine sorbents for immediate desulphurization in circulating boilers. Conference: VIII Konferencja Kotłowa, Gliwice.

12.3 References 15 Lahovsk
y, J. (1993) Limestone products for

desulphurization of flue gases. Report Vapenick
y seminar, Loštice 13.10.1993. 16 Miller, B.G., Romans, D.E., and Scaroni, A.W. (1990) Characterization of limestones for FBC systems. SO2 Emission Control Conference, National Stone Association, Pittsburgh, Pennsylvania.  a, M. 17 Szeliga, Z., Blejchar, T., and St
an (2007) Residence time of fine grained particles in fluidised bed – Numerical vs. real model. Proceedings, Power Engineering and Environment, Modern Energy Technologies and Renewable Energy Resources, Ostrava, pp. 215–223. 18 Szeliga, Z., Juchelkov
a, D., Cech, B., Kolat, P., Winter, F., Campen, A.J., and Wiltowski, T.S. (2008) Potential of alternative sorbents for desulphurization: From laboratory tests to the full-scale combustion unit. Energy Fuel, 22 (5), 3080–3088.

19 Barret, P. (1978) Kinetics of the Gas-Solid

Reactions, Academia, Prague. 20 Vejvoda, J. and Hrn c
ır, J. (1978) The use of

limestone for reduction of exhalations of sulphur oxides from combustion processes. Treatise of the Institute for Study and Utilization of Fuels, Prague, No. 50, pp. 1–278. 21 Koppe, K. and Juchelkov
a, D. (2002) Deutsch-Tschechische wissenschaftlichtechnische Zusammenarbeit auf dem Gebiet der energetisch sinnvollen und emissionsarmen thermischen Verwertung von Biomassen und Abfallstoffen. Vortrag XXXIV. Kraftwerkstechnisches Kolloquium und 7. Dresdner Fernw€arme-Kolloquium Dresden In: Tagungsband Teil II, pp. 133–136. 22 Cech, B., Kadlec, Z., and Matousek, J. (2006) Diagnostic methods of waste gases channels of fluid chambers. Acta Geodynam. Geomater., 3 (1), 13–41.

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j357

13 Carbon Monoxide David Belcher 13.1 Introduction and Key Physical Properties [1–4]

Carbon monoxide is a colorless, odorless gas with the formula CO and a relative molecular mass of 28 atomic mass units (amu). It is more volatile than the related molecule carbon dioxide (CO2), having a melting point of
205  C, a boiling point of
191  C, and an autoignition temperature of 620  C; its explosion limits in air are concentrations between 12.5% and 74% by volume. It is present in the atmosphere at levels of between 0.5 and 0.2 parts per million (ppm), almost all of which is due to human activity. It usually occurs as a product of the incomplete combustion of fuels containing carbon and carbon-based compounds, such as petrol, coal, or wood, which can be generalized as: Cþ

1 O2 ! CO 2

ð13:1Þ

These combustion processes take place at temperatures in the region of 900–1000  C (although CO can also be formed by the routes shown in Equations 13.7–13.10 in Section 13.4). A general overview of these combustion processes is provided in Vol. 1 Ch. 1–3. Carbon monoxide (CO) itself will also burn in the presence of sufficient oxygen to form CO2; consequently, CO has in the past found use as a fuel, although it is now a much less popular choice because of its extreme toxicity. Today, safer, more efficient alternatives are widely available (the mechanism and consequences of CO poisoning will be discussed in due course). Within the context of acidity and alkalinity, CO is a neutral molecule (unlike CO2, which is weakly acidic). It can react explosively with oxygen, and burns with a pale blue flame, as evidenced by the blue “cone” of a natural gas flame, which arises from the final combustion of any gas not already completely oxidized to CO2.

Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright Ó 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

j 13 Carbon Monoxide

358

13.2 Bonding and Structure [2, 5–8]

Carbon monoxide is a covalently bound diatomic molecule with a triple bond between carbon and oxygen atoms (see structure below), the nature of the bond being dative and leaving a lone electron pair on the carbon atom which makes it an important ligand in coordination chemistry (as will be seen later). One rather simplistic way of viewing the pattern of bonding is that a lone pair on oxygen is donated to an empty orbital on the carbon atom, which offers a rudimentary explanation of the presence of a triple bond between divalent oxygen and tetravalent carbon, as well as the peculiar nature of CO’s weak dipole moment (see below). The stronger nature of the triple bond is evident in the fact that the carbon–oxygen bond dissociation energy is 1070.3 kJ mol
1 in CO, around twice that of CO2, which has a pair of double carbon–oxygen bonds each having a dissociation energy of 531.4 kJ mol
1.

The bonding in CO is shown in Figure 13.1 in terms of molecular orbital (MO) energy levels; both atoms have 2s and 2p orbitals, the former holding up to two electrons and the latter up to six electrons, capable of participating in the formation of s and p orbitals, and so a certain degree of orbital hybridization occurs (as in Figure 13.1b), namely the mixing of 2s and 2p atomic orbitals (AOs), and this is highly important in defining the bonding and characteristics of the molecule. In fact, if this were not the case the 3s highest occupied molecular orbital (HOMO) would exhibit a strongly antibonding character (Figure 13.1a) and thus, of course, the important transition metal chemistry of CO – which is so heavily dependent on the bond formed between the positively charged metal center and the lone-pair 3s orbital – would not exist. Experimental evidence reinforces this, also showing a strong s–character in the carbon–oxygen bond. The electron density in the 3s orbital is directed away from the carbon atom (a typical lone pair trait, similar to that found in ammonia or phosphine), and its electrons are also the easiest to remove. The ground state configuration of CO is 1s22p21p23s2, the HOMO being the largely nonbonding 3s lone pair on the carbon atom, whilst the lowest unoccupied molecular orbital (LUMO) consists of a pair of anti-bonding p orbitals possessing largely carbon 2p character. The HOMO participates in the formation of s bonds in transition metal carbonyls, whereas the LUMO participates in the formation of p bonds in such compounds. The s-electron density distribution (see Figure 13.2) also shows the preferential role of the carbon lone pair in CO–metal bonding, since it has some 2p character and so projects further from the molecule than the mostly 2s-character oxygen lone pair. Carbon and oxygen have a sizeable difference in electronegativity, though the CO molecule possesses only a small (0.12 Debye) dipole moment. Due to the

13.2 Bonding and Structure

Figure 13.1 Energy-level diagram of the bonding in carbon monoxide. (a) Without orbital hybridization; (b) With orbital hybridization.

Figure 13.2 Electron density distribution in carbon monoxide.

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j 13 Carbon Monoxide

360

somewhat complex distribution of lone and bonding electron pairs which results from the hybridization described above, the negative end of this dipole actually lies towards carbon, in spite of it being the less electronegative of the two constituent atoms.

13.3 Carbon Monoxide in the Research Laboratory and in Coordination Chemistry [2, 8]

Pure CO for laboratory use may be produced by the dehydration of methanoic (formic) acid with concentrated sulfuric acid at 140  C. CO can be qualitatively detected due to its ability to reduce aqueous palladium chloride solutions; bubbling the gas through such a solution precipitates a “mirror” of palladium: CO þ PdCl2 ! Pd þ CO2 þ 2HCl

ð13:2Þ

This reduction chemistry is simple yet extremely important, as will be seen later. The classical quantitative analysis of CO may be performed by measuring the amount of iodine liberated from the reduction of a solution of the iodate (V) anion by CO [9]. The strongly reducing nature of CO also makes it a vital component in the production of some pure metals from their ores at high temperature, in particular nickel (see Section 13.4.3). CO is an important ligand in the coordination chemistry of transition elements; its complexes are often described as organometallic due to the presence of carbon atoms, but they are not organometallic in the truest sense. As noted in Section 13.1, the vast majority of such compounds have CO ligands bound to the transition metal through the carbon atom – that is, via the nonbonding p orbital (HOMO) which can be regarded as a lobe projecting away from the carbon atom (as illustrated in Figure 13.2) and acting as a very weak electron donor to form a s bond with the metal atom. However, CO plays a dual role in coordination chemistry, functioning not only as a donor of s-electron density but also as an acceptor of p-electrons donated by the orbitals of the transition metal. In its role as a ligand in coordination chemistry, CO is usually referred to as a carbonyl ligand; it unusually has the coordination number 1 and a þ 2 oxidation state. CO is usually found as an orthodox terminal ligand, but sometimes acts as a bridging ligand (m2-CO) or even a triply-bridging ligand (m3-CO); being a monodentate ligand, its connectivity to metal atoms may increase, but its hapticity (g) – that is, the number of binding sites it occupies on a single transition metal center – is always 1, and it does not form chelated complexes in the way that, for instance, the ethanedioate anion or its derivatives would. Generally, the carbon end of the molecule, with its associated lone pair, is the one which binds to the transition metal. Since, as noted above, CO both accepts and donates electron density, the coordinate bonds formed with transition metal centers are said to be synergic or “mutually

13.3 Carbon Monoxide in the Research Laboratory and in Coordination Chemistry

reinforced,” resulting in relatively strong bonds due to p-electron density drifting from the metal to the carbon atom. In turn, the carbonyl ligand becomes more electronegative and its s-donor ability is enhanced, thus reinforcing the bond. It is this strong coordinate bond which results in such detrimental effects when excessive amounts of CO are present in the bloodstream. CO may also act as a weak donor of selectron density to Lewis acids (i.e., electron-deficient species) such as boron trifluoride. However, the synergic bond, which results from the p-electron density acceptor role of CO, actually weakens the bond within CO due to this charge density being back-donated into the ligand’s antibonding orbitals. The carbonyl ligand thus has a greater interatomic distance than that found in “free” CO. As such, the reduced force constant makes it easier to distinguish between the two forms of CO in terms of their infrared (IR) spectra; free CO exhibits a strong carbon–oxygen stretching frequency at 2143 wavenumbers (cm
1), whereas in a terminal neutral carbonyl complex this can be lowered to between 2125 and 1850 cm
1. Neutral binary carbonyl compounds of the general form M(CO)2 are limited to the central area of the d-block of the Periodic Table (as shown by those elements on a white background in Table 13.1), due to the need not only for low-lying vacant transition metal orbitals to successfully accept s-electron density but also for filled d-orbitals to be present on the metal center, thereby achieving the back-donation of charge to the carbonyl ligand. Such complexes are otherwise unstable, requiring other ligands to be present to produce a stable complex. Carbon monoxide is also important in transition metal chemistry for stabilizing clusters and inserting into metal–carbon bonds. There are essentially three different routes for accomplishing this: (i) direct reaction (Equation 13.3); (ii) reductive carbonylation processes (Equation 13.4); and (iii) photolytic (Equation 13.5) or thermolytic (Equation 13.6) routes: Ni þ 4CO ! NiðCOÞ4

ð13:3Þ

100  C

WCl6 þ 3FeðCOÞ5


! WðCOÞ6 þ 3FeCl2 þ 9CO

ð13:4Þ

Table 13.1 Transition (“d-block”) elements and their ability to form stable neutral carbonyl compounds of the form M(CO)2.

3

4

5

6

7

8

9

10

11

12

Sc No Y No La No

Ti No Zr No Hf No

V Yes Nb No Ta No

Cr Yes Mo Yes W Yes

Mn Yes Tc Yes Re Yes

Fe Yes Ru Yes Os Yes

Co Yes Rh Yes Ir Yes

Ni Yes Pd No Pt No

Cu No Ag No Au No

Zn No Cd No Hg No

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j 13 Carbon Monoxide

362

hn

2FeðCOÞ5
! Fe2 ðCOÞ9 þ CO 70  C

2CoðCOÞ8


! Co4 ðCOÞ12 þ 4CO

ð13:5Þ ð13:6Þ

13.4 Commercial Uses of Carbon Monoxide [2, 10] 13.4.1 Gas Production

A common use of CO in years gone by was as a constituent of water gas (often known as “town gas” in the United Kingdom, because the plants which manufactured it tended be located in, and supplied, larger urban centers). This was used as a domestic fuel, and formed by passing steam over incandescent coke in a process known as steam reforming (chemicals such as coal tar were also produced as byproducts of coke and gas manufacture). Even up to the late 1960s, by which time the UK had begun to convert to methane supplied from North Sea natural gas fields, gas synthesized from coke still constituted 90% of all British domestic gas. Water gas has a typical composition as follows: 40% CO, 50% hydrogen, 5% CO2, and 5% as a mixture of nitrogen and methane. The formation of water gas is a highly endothermic process; its standard enthalpy (DH ) is þ 131.3 kJ mol
1, while the standard entropy (DS ) is 133.7 JK
1 mol
1. The key part of the reaction is: C þ H2 O ! CO þ H2

ð13:7Þ

Similar reactions between methane and steam in the presence of a nickel oxide catalyst at high temperature (ca. 700  C) and pressure (2.5 MPa) are chiefly used as commercial routes to hydrogen production, but these also yield some CO: CH4 þ H2 O>CO þ 3H2

ð13:8Þ

CH4 þ 2H2 O>CO2 þ 4H2

ð13:9Þ

The CO produced may either be extracted or removed by “shift conversion” in the presence of a copper- or zinc-based catalyst to give more hydrogen, plus some CO2. A process in which air rather than steam is blown through the coke provides a fuel known as producer gas, the composition of which is approximately 25% CO, 4% CO2 and 70% nitrogen; from this breakdown its inefficiency as a fuel when compared to natural gas is clearly evident. The mechanism for the formation of producer gas is shown below: 2C þ O2 ! 2CO

ð13:10Þ

13.4 Commercial Uses of Carbon Monoxide

Water gas has now been largely superseded as a fuel by natural gas, which is cleaner, effectively nontoxic, and offers a much higher calorific content per volume burned, being supplied as virtually 100% pure methane with no nonflammable contaminants present. Even water gas, despite being a comparatively richer fuel than producer gas, offers a calorific content of only 18 MJ m
3, compared to 38 MJ m
3 for natural gas [9]. Producer gas (also known as synthesis gas or “syngas”), however, still finds use in the Fischer–Tropsch process (see below) and other important petrochemical reactions. During the heyday of “town gas” being used for domestic supplies in Britain, it was not uncommon for coke and gas to be produced by the same concern, and even on the same site. Indeed, there are certain similarities in the manufacturing processes (coke is the purified end product of the carbonization of incandescent coal), while the coking process is mutually beneficial to gas manufacture in terms of readily available raw materials. Coke and gas production also both yield useful chemical byproducts; in fact, the initial investigations of the chemistry of coal tar extracts led to William Perkin’s pioneering studies in the field of synthetic dyestuffs. Synthesis gas for industrial consumption can also be produced by using another variation of the steam reforming process, in which natural gas (methane) is reacted with steam using a nickel catalyst at extremely high temperature [11] (typically 800–1000  C), although the pressures employed are moderate (20–30 atm): CH4 þ H2 O>CO þ 3H2

ð13:11Þ

As with the production of water gas, this process is again highly endothermic, with a standard enthalpy (DH ) of þ 49.5 kJ mol
1. Alternatively, syngas containing CO and hydrogen in a 1 : 1 ratio, in which the more balanced composition is preferable for applications such as metals refining or the Fischer–Tropsch process (see below) can be manufactured from CO2 and natural gas using a technique known as “dry reforming,” because no steam is required [11]: CH4 þ CO2 >2CO þ 2H2

ð13:12Þ

Such reforming reactions are not without their problems in practice, however. Methane decomposition and the disproportionation of CO can lead to a layer of carbon building up on the surface of any catalyst employed, thereby impairing its efficiency and lowering the yield of the process: CH4 >2H2 þ C

ð13:13Þ

2CO>CO2 þ C

ð13:14Þ

13.4.2 Petrochemical/Polymer Production

Carbon monoxide has several important uses in the petrochemical industry; notably, it can be reduced catalytically to methanol using hydrogen under high-temperature

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and high-pressure conditions (230–400  C; 50–100 atm): CO þ 2H2 ! CH3 OH

ð13:15Þ

Another process involving methanol is its homogeneous carboxylation using CO and a mix of iodine and rhodium catalysts to yield ethanoic (acetic) acid: I2 ;Rh

MeOH þ CO


! MeCOOH

ð13:16Þ

It has already been noted that CO can be derived from formic acid; conversely, formic acid can be produced by passing CO through sodium hydroxide or, at high pressure, through methanol: Hþ

ð13:17Þ

CO þ NaOH ! HCOONa
! HCOOH H þ ;H2 O

NH3

CO þ CH3 OH ! HCOOCH3


! HCONH2




! HCOOH

ð13:18Þ

Higher alcohols can be obtained by the use of CO and hydrogen (effectively syngas as described above) in the hydroformylation of olefins (the “oxo process”) in the presence of chromium-, copper-, or zinc-based catalysts: H2 O

RCHCH2 þ CO þ H2 ! RCH2 CH2 CHO


! RðCH2 Þ3 OH

ð13:19Þ

Carbon monoxide may also be used, in conjunction with hydrogen chloride, in the synthesis of aldehydes using the Gatterman–Koch synthesis (this is related to the more widely known Friedel–Crafts acylation reaction scheme) in the presence of a Lewis acid such as aluminum chloride. Methyl acrylate and acrylic acid are important raw materials in the polymer industry, and can be produced from acetylene (ethyne) and methanol by using CO in tandem with a nickel or tetracarbonyl nickel catalyst. This process, which is known as the Reppe synthesis, takes place at 100–190  C and 30 atm of pressure if using a metallic nickel catalyst, or at 40  C and 1 atm if employing its tetracarbonyl derivative: H2 O

HCCH þ MeOH þ CO ! CH2 CHCOOMe
! CH2 CHCOOH

ð13:20Þ

The Koch process, meanwhile, generates tertiary carboxylic acids from the reaction between CO, water, and olefin hydrocarbons at high pressure under acidic conditions: Hþ

ðCH3 Þ2 CCH2 þ CO ! H2 O
! ðCH3 Þ3 CCOOH

ð13:21Þ

Methane may be obtained by the Sabatier reduction of CO, using hydrogen and a nickel catalyst, under similar conditions to the production of methanol from CO (typically 230–450  C/1–100 atm): Ni

CO þ 3H2
! CH4 þ H2 O

ð13:22Þ

13.4 Commercial Uses of Carbon Monoxide

The final petrochemical process using CO to be included is the Fischer–Tropsch hydrogenation of mixed straight-chain aliphatic, olefin and oxygenated hydrocarbons, yielding synthetic oil and petrol substitutes. The process was first developed during the mid-1920s, when it was found that high-molecular-weight hydrocarbons could be obtained by reacting CO and hydrogen at around 250–300  C in the presence of iron-cobalt catalysts at pressures of between 0.1 and 1 MPa. Later in the same decade, the process was further developed using cobalt-based catalysts. Although, as a rule, the Fischer–Tropsch process is not economically viable, it has been used in the past when political climates have either restricted or halted oil exports to certain nations. For example, in Germany during the 1930s and 1940s the process was used to enrich the low-grade crude oils obtained from oilfields in occupied Romania. During the post-war era, however, a combination of extremely plentiful coal deposits and a lack of native oil reserves led to a widespread adoption of the Fischer–Tropsch process in South Africa. In this case, a combination of techniques developed in the USA by Kellogg, and in Germany by Lurgi-Ruhrchemie, was used to manufacture a range of products normally obtained from oil refineries. The Kellogg approach used an iron-based catalyst which actually circulated in the syngas stream to give a mixture that consisted largely of low-boilingpoint alkanes for use as petrol substitutes, as well as some water-soluble organics (chiefly ethanol). In contrast, the Lurgi-Ruhrchemie method used a fixed-bed iron catalyst in the reactor vessel to produce mostly liquid and solid paraffins; these were used as coating waxes for food packaging, in household polishes, and as heavy oils for use as lubricants. In both cases, the processes use syngas in which the proportions of CO and hydrogen could be catalytically adjusted according to the equilibrium process: H2 O þ CO>H2 þ CO2

ð13:23Þ

This process is known as the “water gas shift reaction”; CO has a further role to play as the catalysts are often carbonyl complexes of ruthenium such as [HRu3 (CO)11]
and [H3Ru4 (CO)13]
. The reactions in the Fisher–Tropsch process itself may be represented by the general equations shown below: nCO þ 2nH2 ! ðCH2 Þn þ nH2 O

ð13:24Þ

2nCO þ nH2 ! ðCH2 Þn þ nCO2

ð13:25Þ

A research group at Sandia National Laboratories in New Mexico [12, 13] is currently engaged in a near-sustainable version of this process, utilizing highly concentrated solar energy to produce the high temperatures needed to cleave water and atmospheric CO2 and in turn generate the necessary “building blocks” (hydrogen and CO, respectively) of Fischer–Tropsch chemistry. These then undergo reforming in the same manner to provide a variety of synthetic petroleum products, primarily automotive fuels. Although the process was initially developed for the thermolysis of water

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to produce hydrogen for fuel cells, it was soon realized that a similar treatment – utilizing cobalt ferrite as an oxygen capture/release medium in order to generate CO – could be applied to CO2 to produce CO. Despite the scheme being at an embryonic stage, the hope is to use a solar collector in tandem with a specialized reactor vessel known as the Counter-Rotating Ring Receiver Reactor Recuperator (CR5, to use its shortened name), so as to produce a unit that can be arranged in arrays of an appropriate number. It has been calculated that each CR5 unit, if given sufficient sunlight, should yield 2–2.5 US gallons (7.57–9.46 l) of synthetic petroleum spirit per day. The CR5 is also likely to lend itself to “carbon capture” systems, in which emitted CO2 from combustion processes and the like is recovered for use elsewhere, rather than simply be dispersed into the atmosphere. This would allow the CO2 emissions from industrial installations to be utilized for CO production rather than the CO2 present at normal atmospheric levels, which in turn should reduce the problem of “greenhouse gases.” In the past, CO has also found use in a military context. For example, its reaction with chlorine gas in the presence of light or a catalyst (typically charcoal) yields phosgene gas [9, 14] (COCl2): hn or charcoal catalyst

CO þ Cl2












! COCl2

ð13:26Þ

Although phosgene was used infamously as a chemical weapon during the First World War, it does have some valuable civilian uses, including the formation of polycarbonate resins from dihydroxy compounds for the plastics industry. Alternatively, it can be reacted with ammonia gas to yield important chemicals such as urea and ammonium chloride. 13.4.3 The Refinement of Nickel

Not all commercial applications of CO involve organic chemistry, fuels or petrochemicals; rather, CO has a long-established role in the refining of nickel using the Mond process (as developed by Ludwig Mond in 1899; the Brunner Mond chemical company he co-founded in the UK was later to be one of the early partners in the series of mergers which brought into being the ICI conglomerate). In the Mond process, nickel oxide is combined with water gas, the hydrogen component of which reduces the nickel oxide to (impure) metallic nickel. At atmospheric pressure and a temperature of about 50  C, the impure nickel is then reacted with the CO component of the water gas to form tetracarbonyl nickel (NiCO4); the latter material is then passed over pure nickel pellets at an even higher temperature (230  C), which causes it to decompose and yield high-purity (ca. 99.95%) metallic nickel, while the CO produced is recycled for further use in the refining process: 50  C

Ni þ 4CO
! NiðCO4 Þ

ð13:27Þ

13.5 Carbon Monoxide in Everyday Life 230  C

NiðCO4 Þ
! Ni þ 4CO

ð13:28Þ

Although modern nickel refining installations (such as the Canadian plants in Sudbury, Ontario) that employ the Mond principle use a higher pressure (20 atm) and temperature (150  C) in the initial stage, the process is essentially the same as that developed during the late nineteenth century.

13.5 Carbon Monoxide in Everyday Life: Its Consequences and Side Effects, Detection, and Elimination [1, 2] 13.5.1 Biological Effects of CO

The use of CO as a ligand in inorganic chemistry has already been discussed, and it is its property of being able to form strong coordinate bonds with transition metal centers which renders it highly toxic. CO binds to the iron atom at the center of the porphyrin ring in the hemoglobin molecule, in preference to oxygen (the hemoglobin–CO complex is 300-fold more stable than the equivalent complex with oxygen). This leads to a gradual lowering of blood oxygen levels as CO is increasingly taken up by the body. In addition, whereas the reversible nature of the oxygen complex is the key to effective transport as the O2 molecules are easily attached to and detached from hemoglobin, the CO–hemoglobin complexation is effectively irreversible. Incidentally, as it progress though the bloodstream, a single red blood cell contains about 280 million hemoglobin molecules [15]. If 30% or more of the body’s hemoglobin is converted to the CO complex, the consequences are extremely serious. At a level of 30–40%, the reduced oxygen supply to the brain will result in impaired cognitive and motor functions; people suffering from the initial stages of CO poisoning often complain of chest pains, headaches, feeling tired, or light-headedness. At a level of 60–70% coma is likely to occur, whilst a level over 70% is inevitably fatal [16]. Victims also often exhibit distinctive signs of CO poisoning, in the form of a cherry-red tinge to the skin; this indicates the presence of a high concentration of the carbonyl–hemoglobin complex, which differs in color from its oxygenated counterpart. The amount of CO required is very small as a proportion of the air breathed; in an atmosphere with only a 1% CO content, 50% of the hemoglobin will be unavailable for oxygen transport and death will occur in about 1 hour. The value of 50% is significant, since at or above this level the blood will cease to carry oxygen altogether. Fortunately, CO is not a cumulative poison (unlike heavy metals such as cadmium or mercury), and in nonfatal cases of CO poisoning an exposure to fresh air – and hence a fairly rapid reoxygenation of the bloodstream – will ensure that the victim recovers relatively quickly, though in serious cases the survivor may suffer irreversible cardiac or brain damage. Surprisingly, CO is naturally present within the human body as a byproduct of the metabolism of hemoglobin, constituting a daily dose of around 10 mg. However, in

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spite of about 0.5% of the hemoglobin in the blood being bound to this CO, it has no detrimental effect on the body’s oxygen transport system. Extensive details of combustion products such as CO, and their effects on health, are provided in Vol. 1 Ch. 19 of this Handbook. 13.5.2 Vehicular Production of CO

During the time of its use in domestic gas supplies, CO poisoning (both accidental and deliberate) was relatively common. Even today, it remains a major hazard associated with motor vehicle exhaust gases due to inefficient combustion processes within petrol and diesel engines, where a shortfall in oxygen intake results in the production of CO rather than CO2. The normal CO output of a petrol-engined car is about 4% of the total exhaust gases, but when the engine is idling as the vehicle is at a standstill this figure may double. The impact of road traffic is especially evident in urban areas, where background CO levels can rise to between 2 and 20 ppm. In areas with restricted air movement, such as tunnels and underpasses, the levels may rise to 100 ppm, and have been linked to increased numbers of traffic accidents in such areas due to the increased possibility of the drivers’ judgment being impaired [17]. For comparison, the absolute safe upper limit for exposure to CO in exhaust gases is 120 ppm within the space of 1 hour, although only 75 ppm will result in a bloodstream CO level of about 30% and significant side effects. In the United States, the air quality standards stipulate maximum airborne CO levels of 35 ppm over a 1 hour sampling period, or 9 ppm over an 8 hour period. Deliberate CO poisoning from the exhaust emissions of a stationary vehicle in a confined space is still a commonplace cause of death in suicide cases. Approximately 89% of all CO emissions result from road traffic [18], as confirmed by a breakdown of the contributions to American CO pollution [19] (see Table 13.2); this again shows that transport – and petrol-engined road transport in particular – is by far the largest contributing factor. Surprisingly, the contributions from industry and from other fuel-burning processes (e.g., electricity generation) are, by comparison, small. This may be due to the fact that such processes are optimized for maximum fuel efficiency, providing a more complete combustion so CO2 rather than CO is produced. 13.5.3 Catalytic Converters

In many modern motor vehicles, the presence of CO in exhaust emissions has been greatly reduced by the use of a catalytic converter in the exhaust system. Although the primary role of such a converter (based on platinum and rhodium catalysts, supported on a ceramic “honeycomb”; see Figure 13.3) is to eliminate the oxides of sulfur and nitrogen (which contribute to acid rain), while CO is oxidized to CO2. (Details of catalytic systems for pollution control are provided in Chapter 11.) It is also possible to produce petrol with reduced CO2 emissions by initially blending it with CO. Unfortunately, like CO2, CO has an impact as a

13.5 Carbon Monoxide in Everyday Life Table 13.2 Breakdown of contributions to CO pollution in the United States [19].

Source

Millions of tonnes per year

Motor vehicles (petrol engine) Motor vehicles (diesel engine) Aircraft Railways and others Total transportation Coal Fuel oil Natural gas Wood Total fuel combustion Industrial processes Solid waste disposal Forest fires Agricultural burning Coal refuse burning Structural fires Total miscellaneous Total overall

53.5 0.2 2.4 2.0 58.1 0.7 0.1 0.0 0.9 1.7 8.8 7.1 6.5 7.5 1.1 0.2 15.3 91.0

greenhouse gas, by accelerating the breakdown of NO2 in the presence of sunlight and increasing ozone production, which is an undesirable consequence at atmospheric level [18]. Tropospheric CO may also be absorbed by various “sinks,” namely absorption by soil and plants, oxidation by hydroxyl radicals, or transfer

Figure 13.3 A selection of automotive catalytic converter materials.Illustration courtesy of Johnson Matthey plc.

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into the stratosphere where oxidation subsequently takes place. The reaction with hydroxyl radicals is particularly significant, and accounts for around 70% of tropospheric CO loss [17]. 13.5.4 Industrial Applications of CO

The refining of metals represents another major cause of atmospheric CO pollution, mainly because the smelting methods incorporate the combustion of a carbon source (e.g., the production of pig-iron in a blast furnace). This can be summarized by the following general equations [5], in which reduction occurs if the equilibrium shifts to the right: MO þ

1 1 C>M þ CO2 2 2

MO þ C>M þ CO

ð13:29Þ ð13:30Þ

Other industries where CO represents a problem include coal mining, as the gas may be present in deep mines (i.e., underground operations) along with CO2 (also known as “choke damp” by miners) and methane (known as “firedamp”). Although, today sophisticated detection and alarm systems (see below) warn of the presence of these gases, many years ago a caged canary was often taken underground as the bird would die when gas concentrations were below those fatal to humans, and so provide a prior warning of gas hazards [20]. 13.5.5 Smoking and CO

The absorption of CO into the bloodstream is, inevitably, one of the many detrimental effects of smoking on health. In fact, it can result in up to 10% of the hemoglobin in the bloodstream being rendered unavailable for oxygen transport (the usual maximum figure for nonsmokers is about 5%). Although this level of CO is relatively low, the long-term consequences are highly significant. They may be even more severe when smoking in the presence of certain halogenated organic compounds (e.g., chloroform), as the CO may react with chloroform vapor before inhalation to produce highly toxic phosgene (see above) in small, yet significant, amounts. 13.5.6 Domestic Appliances and CO Detection

CO poisoning from gas appliances may still cause problems, even in these times of alternative fuel gases such as methane and propane, if the ventilation of equipment, (e.g., heating boilers) is insufficient. Poor drafting of the appliances (e.g., a blocked

13.5 Carbon Monoxide in Everyday Life

Figure 13.4 A simple non-electronic CO detector based on palladium reduction chemistry.

flues) will result in the inefficient combustion of gas and the presence of CO; typical early warning symptoms include sooty marks and a tendency for the flame to be yellow rather than blue. Following a spate of fatalities due to faulty gas installations (particularly in rented properties), legislation has been introduced recently in the UK requiring the regular inspection of appliances in such accommodation, with large fines imposed on, and even the imprisonment of, noncompliant landlords and property rental companies. Older appliances are regarded as being particularly suspect, although simple, effective, and potentially life-saving CO detectors are now widely available (Figure 13.4). These employ a solid-state variation of the palladium reduction chemistry (as described above), and provide advance warnings of any dangers posed by the possible presence of CO in the home. More advanced, expensive electronic CO detectors for use in the home (Figure 13.5) are also available which employ either the above-described chemistry in conjunction with colorimetric optical detection, or a purely electrochemical system [21]. In the latter system the CO molecules diffuse into a cell via a semipermeable membrane which acts as a filter (Figure 13.6). The cell contains an

Figure 13.5 An electronic CO detector. Illustration courtesy of Tunstall Group Limited.

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j 13 Carbon Monoxide

372

Figure 13.6 The detection system in a typical electronic CO alarm.

acid electrolyte, a sensing electrode, and a counter-electrode. When the CO molecules arrive at the sensor electrode they react at the surface (see Equation 13.31), such that byproducts are formed during the generation of CO2, namely electrons and hydrogen ions. The former travel to the counter-electrode through an ammeter (for detection purposes), whilst the latter migrate through the electrolytic medium to the counter-electrode where recombination occurs (Equation 13.32). As this reaction occurs without any of the cell components being consumed overall, it makes for a simple, low-maintenance device with a long lifespan. 2CO þ 2H2 O ! 2CO2 þ 4H þ þ 4e


ð13:31Þ

4H þ þ 4e
þ 2O2 ! 2H2 O

ð13:32Þ

As the amount of electrons produced at the sensor electrode is directly proportional to the amount of CO, the circuit can easily be arranged to set off an audible and/or visual alarm if the measured current – and hence gas concentration – exceeds a safe threshold. The effective elimination of the gas itself is achieved simply by the provision of adequate ventilation for appliances, thereby ensuring both efficient combustion by a constant intake of fresh air and hence oxygen, and an unrestricted flow of combustion products to the outside air. The detection of atmospheric CO for pollution monitoring, and in flames and emissions for the real-time monitoring of combustion processes, has been

References

studied using a variety of optical techniques [22], including the Raman scattering of laser light, laser-induced fluorescence spectroscopy, multiphoton ionization spectroscopy, and IR vibrational spectroscopy [23]. In the latter method, both the CO and the species containing CO in the form of the carbonyl group exhibit strong, easily identifiable peaks in their absorption spectra (see Section 13.3). (This subject is described in greater detail in Chapters 1, 4, 5, 6 and 7, and the cited references therein.)

13.6 Outlook

A combination of more stringent environmental and domestic legislation, improvements in detection technology and emission control methods such as automotive catalytic converters, and a decline in the popularity of smoking in many parts of the globe, will all mean that – hopefully – the profile of CO as a pollutant will diminish in years to come. However, this does not mean that the fatal side effects of CO should be taken lightly by future generations. Nonetheless, the gas continues to be an invaluable material in many areas of the petrochemical and metals industries, and with the decline in reserves of naturally occurring crude oil, synthetic alternatives to refined petroleum products using CO in Fischer–Tropsch pattern treatment of the planet’s remaining coal deposits, of sustainable biomass fuels (such as wood and charcoal), or even by the as-yet unproven CR5 process using water and CO2 as raw materials, may yet gain much greater importance.

13.7 Summary

This chapter has demonstrated that, whilst CO is to a large extent a very simple molecule, it has rather unusual bonding characteristics for a diatomic substance. CO also shows some markedly different characteristics from the related molecule CO2, and is chiefly well known due to its toxicity, being rightly regarded as a major health hazard. However, it is a very useful chemical in the commercial world and seems set to remain so for some time. Improvements in detection and pollution control technology have gathered pace considerably in recent years, and this hopefully will mean that in years to come the positive benefits that industry gains from the CO molecule will far outweigh its negative aspects in other spheres.

References 1 Emsley, J. (1998) Molecules at an

Exhibition, Oxford University Press, Oxford.

2 Greenwood, N.N. and Earnshaw, A. (1997)

Chemistry of the Elements, 2nd edn, Butterworth-Heinemann, Oxford.

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374

3 Uvarov, E.B. and Isaacs, A. (1986) The

4

5 6

7 8

9

10

11

12

Penguin Dictionary of Science, 6th edn, Penguin Books, London. University of Oxford (2003) Physical and Theoretical Chemistry Laboratory Safety Data, Oxford. Available at: http://msds. chem.ox.ac.uk/CA/carbon_monoxide. html. Atkins, P.W. (1994) Physical Chemistry, 5th edn, Oxford University Press, Oxford. Brown, M.G. (1965) Carbon Chemistry: Some Aspects of Covalent Chemistry, The English Universities Press, London. McWeeny, R. (1979) Coulson’s Valence, 3rd edn, Oxford University Press, Oxford. Shriver, D.F., Atkins, P.W., and Langford, C.H. (1994) Inorganic Chemistry, 2nd edn, Oxford University Press, Oxford. Sharp, D.W.A. (1990) Penguin Dictionary of Chemistry, 2nd edn, Penguin Books, London. Tedder, J.M., Nechvatal, A., and Jubb, A.H. (1975) Basic Organic Chemistry Part 5 – Industrial Products, John Wiley & Sons, Ltd, London. Olau, G.A., Goeppert, A., and Surya Prakash, G.K. (2006) Beyond Oil and Gas – The Methanol Economy, Wiley-VCH, Weinheim. Sandia National Laboratories (2007) Alberquerque. Available at: http://www. sandia.gov/new/resources/releases/ 2007.sunshine.html.

13 Squatriglia, C. (2008) New York. Available

14

15

16 17

18 19

20

21

22 23

at: http://www.wired.com/science/ discoveries/news/2008/01/S2P. Streitweiser, A., Heathcock, C.H., and Kosower, E.M. (1992) Introduction to Organic Chemistry, 4th edn, Macmillan, New York. Tedder, J.M., Nechvatal, A., and Carnduff, J. (1972) Basic Organic Chemistry Part 4, John Wiley & Sons, Ltd, London. Alma, P.J. (1993) Environmental Concerns, Cambridge University Press, Cambridge. Jackson, A.P.W. and Jackson, J.M. (2000) Environmental Science, 2nd edn, Pearson Education, Harlow. Byrne, K. (2001) Environmental Science, 2nd edn, Nelson Thornes, Cheltenham. Kraushaar, J.J. and Ristinen, R.A. (1993) Energy and Problems of a Technical Society, 2nd edn, John Wiley & Sons, Inc., New York. Thompson, M.A. (2001) Molecule of the Month, University of Bristol, Bristol. Available at: http://www.chm.bris.ac.uk/ motm/co/coh.htm. Apollo Fire Detectors Limited (2006) Havant. Available at: http://www.apollofire.co.uk/editpics/278-1.pdf. Hollas, J.M. (1996) Modern Spectroscopy, 3rd edn, John Wiley & Sons, Ltd, Chichester. Lester, M.I., Pond, B.V., Marshall, M.D., Anderson, D.T., Harding, L.B., and Wagner, A.F. (2001) Faraday Discuss., 118 (Part 19), 373–385.

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14 CO2 Greenhouse Gas Formation and Capture Hsunling Bai and Mani Karthik 14.1 Introduction

Carbon dioxide (CO2), as a product of the complete combustion of any fossil fuel, has been identified as an important greenhouse gas (GHG). Today, global CO2 emissions continue to show an upward trend. It has been projected that, by the year 2030, the annual emission of CO2 will be 59.6 Gt, which is almost double that emitted in 2005, of 27.8 Gt (see Table 14.1) [1]. In order to mitigate the global warming effect of CO2, large reductions in its emission will be required in developed countries, and significant deviations from baselines will be required in developing countries by the year 2020. It is known that CO2 has been entering the atmosphere from a variety of anthropogenic sources for millions of years. The emission sources of CO2 can be classified as two broad classes, namely power plants burning fossil fuels, and industrial sources. The stationary emission sources are considered to be power plants, while the major industries include oil and gas refineries, ammonia, cement, ethylene and ethylene oxides, gas processing, hydrogen, and iron and steel plants [2– 4]. The major point sources of CO2 emissions are listed in Table 14.2 [5], with emissions from power plants dominating all other stationary sources [6, 7] Ever since the Kyoto Protocol was adopted on 11 December 1997, and entered into force on 16 February 2005, the emissions of CO2 due to the combustion of fossil fuels has attracted increasing concerns. Currently, fossil fuels represent the dominant form of energy utilized worldwide (86%), and account for approximately 75% of today’s’ current anthropogenic CO2 emissions [8]. There are several possible means for the reduction of CO2 emission. In this chapter, the formation and emission of CO2 from combustion processes are reviewed, and details are introduced of the Intergovernmental Panel on Climate Change (IPCC) method for estimating CO2 emission quantities from various combustion fuels. Methods on reducing CO2 emissions, such as renewable energies and the carbon dioxide capture and storage (CCS) technologies are also discussed. The emerging and promising CO2 capture technologies, the chemical looping

Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright
2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

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2

Greenhouse Gas Formation and Capture

Emissions of CO2 in 2005 and projected. Growth, shares in global total, and per capita emissions [1].

Table 14.1

Annual average growth (%)

OECD OECD North America OECR Europe OECD Pacific Transition Developing countries Developing Asia China India Indonesia Other Latin America Middle East Africa Developing countries excluding China Marine bunkers World total excluding cement Cement World total including cement

Share of total excluding cement (%)

Per capita emissions (t)

2005–15

2015–30

2005–30

2005

2030

2005

2030

0.8 1.1

0.5 0.7

0.6 0.8

48.3 25.3

26.8 14.7

11.0 15.6

11.6 15.6

0.3 1.0 2.1 5.8 6.7 7.5 4.9 4.6 4.7 3.0 4.1 2.3 4.0

0.5 0.0 1.8 4.4 4.8 4.7 5.8 6.4 2.9 2.8 3.0 3.0 3.9

0.4 0.4 1.9 5.0 5.5 5.8 5.4 5.7 3.6 2.9 3.4 2.7 4.0

15.3 7.8 9.8 39.8 28.6 19.1 4.3 1.3 3.9 3.5 4.6 3.1 20.8

8.0 4.1 7.4 63.3 51.9 37.4 7.6 2.4 4.5 3.4 5.1 2.9 25.9

7.6 10.3 7.7 2.2 2.3 3.9 1.0 1.5 1.4 2.1 6.6 0.9 1.5

7.9 11.7 13.2 5.4 6.9 14.5 3.0 4.9 2.4 3.3 10.1 1.1 2.8

7.8

1.3

3.9

2.0

2.5

3.3

2.8

3.0

Gt CO2 26.7 56.4

4.2

6.9

4.8 3.4

4.4 2.9

4.5 3.1

1.0 27.8

0.2 4.3

0.4 7.2

3.1 59.6

combustion for reducing CO2 emission, and possible methods of CO2 utilization are also briefly reviewed.

14.2 The Formation of CO2 14.2.1 Formation During Complete Combustion

In stoichiometric combustion, the fuel can react with the exact amount of oxygen required to oxidize all of the carbon, hydrogen, and sulfur in the fuels into CO2, H2O, and SO2, respectively. Therefore, the exhaust gas from a stoichiometric combustion will, in theory, contain no CO. During the stoichiometric and complete combustion

14.2 The Formation of CO2 Table 14.2 The large point sources of CO2 emissions [5].

No. of sources

CO2 emissions (Mt CO2 yr 1)

Fossil fuels burning Power plants Cement production Refineries Iron and steel industry Petrochemical industry Oil and gas processing Other sources

4942 1175 638 269 470 N/A 90

10 539 932 798 646 379 50 33

Biomass production Bioethanol and bioenergy Total

303 7887

91 13 466

Industrial process

of a fuel with chemical formula of HmCn, the reaction can be expressed by the following simple scheme: Hm Cn þ ðn þ 0:25 mÞO2 ! nCO2 þ 0:5 mH2 O

ð14:1Þ

in which the final reaction products are seen to be CO2 and H2O. For most combustion processes, air is used as the O2 source; this is composed of an approximately 1/3.76 molar ratio of O2/N2, so that if N2 is added into the reaction scheme it becomes: Hm Cn þ ðn þ 0:25 mÞðO2 þ 3:76N2 Þ ! nCO2 þ 0:5mH2 O þ 3:76ðn þ 0:25mÞN2 ð14:2Þ

For every mole of fuel combusted, [4.76n þ 1.19m] moles of air will have been consumed, and [4.76n þ 1.44m] moles of gaseous products (CO2 þ H2O þ N2) will have been formed. The mole fraction of CO2 (yCO2) under complete combustion is thus estimated as: yCO2 ¼

n 4:76n þ 1:44m

ð14:3Þ

For example, the largest component of natural gas is methane (CH4), and the complete combustion of CH4 in air can be written as: CH4 þ 2O2 þ 2ð3:76ÞN2 YCO2 þ 2H2 O þ 2ð3:76ÞN2

ð14:4Þ

The CO2 mole fraction for the stoichiometric and complete combustion of methane is thus calculated as 9.51%. Based on this calculation, it is possible to estimate the mole fraction of any fuel during complete combustion processes by using Equations 14.2 and 14.3. Table 14.3 shows the mole fractions of CO2 for various

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2

Greenhouse Gas Formation and Capture

The maximal mole fraction of CO2 for selected fuels as combusted under stoichiometric complete combustion in air.

Table 14.3

Fuel type

CH4 CH3OH C2H2 C2H4 C2H6 C2H5OH C3H6 C3H8 C4H10 C5H12 C6H6 C6H14 C7H8 C7H16 C8H18 C9H20 C10H22 CH0.808N0.013S0.013 O0.057 (Seam coal) Natural gas Coal Wood (dry) Bagasse Coke Oil

Max. mole fraction of CO2 (%) 9.51 9.51 16.13 13.09 11.01 11.01 13.09 11.63 11.96 12.17 16.13 12.32 15.61 12.42 12.5 12.56 12.61 16.9 11.8 17.0 19.1 20.6 20.1 16.5

Estimation method/reference Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3 Equations 14.2–14.3; Ref. [11] Ref. [9] Ref. [9] Ref. [9] Ref. [9] Ref. [9] Ref. [9]

fuels based on stoichiometric complete combustion. Since excess air is usually added for an actual combustion process, the estimated mole fractions are the maximal CO2 concentrations achieved during combustion. That is, the percentage of CO2 contained in the products of stoichiometric combustion is the maximum attainable, and this is referred to as the “stoichiometric CO2” or “maximum theoretical percentage of CO2.” Also shown in Table 14.3 is the maximal CO2 mole fraction of typical fuels used as estimated by TCS Incorporated [9]. The amount of carbon in fuels per unit of energy content varies significantly by fuel type; for example, coal contains the highest amount of carbon per unit of energy, while petroleum has about 25% less carbon than coal, and natural gas about 45% less. Thus, coal emits around 87% more CO2 than natural gas, and 34% more than oil [10]. For economy and safety, most combustion equipment should operate with some excess air. This not only ensures that the fuel is not wasted but also that the combustion is complete. When O2 appears in the flue exhaust, it usually indicates that excess air was supplied than was usually required for a complete combustion to occur. The amount of excess air ranges from 5% to 60%, and the CO2 mole fraction is less than predicted by stoichiometric requirement shown in Table 14.3.

14.2 The Formation of CO2

14.2.2 Formation During Incomplete Combustion

Incomplete combustion occurs when a hydrocarbon fuel is not completely oxidized during combustion process. In such a case, a hydrocarbon fuel is not completely oxidized to CO2 and H2O, but may form partially oxidized compounds such as CO, aldehydes, ketones, or other intermediate products of hydrocarbons as undesirable products. Moreover, if the combustion fuel is either coal or heavy oil (diesel oil), then the products of incomplete combustion may also be unburned carbon (i.e., particulate matter). There are two possible means of estimating the carbon distribution during incomplete combustion, namely chemical equilibrium and chemical kinetics. If the combustion temperature is much higher than 1250 K, then the products of complete combustion tend to dissociate [11]: CO2 ()CO þ

1 O2 2

ð14:5Þ

The simplest theory for estimating the concentrations of products of incomplete combustion is the chemical equilibrium, whereby the equilibrium constant (Kp) can be used to estimate the final concentrations of each product:

X  moj DG ð14:6Þ Kp ðTÞ ¼ exp uj ¼ exp RT RT where: uj ¼ stoichiometric coefficient of species j moj ¼ chemical potential of species j at P ¼ 1 atm

The equation for chemical potential, moj , is   ðT ðT Cp;j 0 dT Cp;j dT 0 þ Dhfjo ðTo Þ T Soj ðTo Þ þ moj ðTÞ ¼ 0 To T To

ð14:7Þ

where: Soj ¼ standard entropy of species j ðat 298 KÞ Cp;j ¼ aj þ bj T moj ðTÞ




¼ aj T T0

T Tln T0



bj ðT T0 Þ2 þ Dhfj  ðT0 Þ TSj  ðT0 Þ 2

ð14:8Þ

The thermodynamic data for the dissociation of carbon species are listed in Table 14.4. Although the chemical equilibrium is a simple method for estimating the CO, CO2 and trace carbon concentrations (e.g., see Ref. [11]), the actual process is not always predictable via the thermodynamic approach. When using the kinetic approach to evaluate the formation of CO and CO2 during incomplete combustion, the details of

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Table 14.4 Thermodynamic data for the dissociation of carbon species [11].

Species

C(S) CO CO2 N2 O2

Dhoj (To) (J mol 1)

0 110 700 394 088 0 0

So(To) (J mol

1

5.694 197.810 213.984 191.777 205.310

K 1)

Cp ¼ a þ bT (J mol 1 K 1) a

b

14.926 29.613 44.319 29.231 30.504

0.00 437 0.00 301 0.00 730 0.00 307 0.00 349

several experimental studies and kinetic models have been reported. However, because of the complexity of the incomplete fuel combustion process, a steady state or partial-equilibrium assumption is usually made to estimate the CO and CO2 fraction in the gaseous products. These simplified models are termed either the “twostep model” or the “global mechanism” [11]. The two-step model was developed by considering the formation and consumption of CO to form the final product of CO2: n m  m RA O2 ! nCO þ H2 O þ ð14:9Þ Cn Hm þ 2 4 2 RB

CO þ 1=2O2 ! CO2

ð14:10Þ

where:


 EA ½Cn Hm Ša ½O2 Šb RT

ð14:11Þ




 EB ½H2 OŠc ½O2 Šd ½COŠ RT

ð14:12Þ

RA ¼ AA T nA exp

RB ¼ AB T nB exp

It should be noted that Equation 14.12 contains [H2O], despite H2O not appearing in the reaction scheme of Equation 14.10; this is because the consumption of CO is from its reaction with OH. radical. The OH. radical is also formed from the reaction of O2 with the H. radical, and consumed to form H2O. Thus, it can be assumed that the OH. radical is in equilibrium with H2O [11]. Consequently, when the parameter values of the rate Equations 14.11 and 14.12 have been obtained, it is possible to estimate the CO concentration. The parameter values of Equation 14.11 can be obtained from Table 14.5, while those of Equation 14.12 are available from Refs [12] and [13], in which the forward and backward reaction rate constants were derived:   20130 10 ½COŠ½H2 OŠ0:5 ½O2 Š0:25 mol m 3 s 1 rf ¼ 1:3  10 exp ð14:13Þ T

14.2 The Formation of CO2 Table 14.5

Summary of rate parameters for the various approximate combustion models [11, 13]a). Two-step mechanism CnHm þ (n/2 þ m/4)O2 ! nCO þ m/2 H2O

Fuel

A  10 CH4 C2H6 C3H8 C4H10 C5H12 C6H14 C7H16 C8H18 C9H20 C10H22 CH3OH C2H5OH C6H6 C7H8 C2H4 C3H6 C2H2 a)

6

(Ea/R)  10

2800 41 31 27 24 22 19 18 16 14 117 56 7 6 75 15 246

24.4 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0

3

A 0.3 0.1 0.1 0.15 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.15 0.1 0.1 0.1 0.1 0.5

b 1.3 1.65 1.65 1.6 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.6 1.85 1.85 1.65 1.85 1.25

Quasi-global mechanism CnHm þ n/2 O2 ! nCO þ m/2 H2 A  10

6

4000 63 47 41 37 34 31 29 27 25 230 113 13 10 136 25 379

(Ea/R)  10

3

24.4 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0 15.0

a

b

0.3 0.3 0.1 0.15 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.15 0.1 0.1 0.1 0.1 0.5

1.3 1.3 1.65 1.6 1.5 1.5 1.5 1.5 1.5 1.5 1.5 1.6 1.85 1.85 1.65 1.85 1.25

Units: m, s, mol, K.

7

rr ¼ 1:6  10 exp



 20130 ½CO2 Š½H2 OŠ0:5 ½O2 Š T

0:25

mol m

3

s

1

ð14:14Þ

Note that the above two rate equations were obtained based on observations in the flame combustion area, and so are not suitable for estimating the CO concentration in the post-flame combustion area. Likewise, the two-step model is not suitable for predicting CO concentrations at the initial stage of combustion, mainly because it is based on the equilibrium assumption of H2O concentration, which requires some time to reach the equilibrium status. The two-step model can be further modified to the “quasi-global reaction mechanism,” which contains more chemical reactions and is more realistic. Here, the initial reaction is that:  n m O2 ! nCO þ H2 ð14:15Þ Cn Hm þ 2 2 where the CO and H2 react with other chemicals to form CO2. The quasi-global reaction model can more precisely predict the CO concentration in the flame and post-flame areas. However, even for the simplified assumption of quasi-global reaction model, the combustion mechanism is so complicated that mixtures with well-defined and reproducible compositions are often required for such studies. These fuels are referred to as “surrogates” or “model-fuels” [14]. For the sake of

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simplicity, the model fuel should include a limited number of hydrocarbons with a well-defined composition, and show a behavior similar to that of a commercial fuel. One of the simplest fuels, CH4, has attracted much more interest than the other fuels, and a number of detailed reaction mechanisms that can be used for methane flames have been reported. Both, Li and Williams [15] and Rightley and Williams [16] have provided a good compilation of the kinetic reactions for the combustion of CH4, based on the kinetic rate constant:
 Ea k ¼ BT m exp ð14:16Þ RT In the kinetic model the CO is oxidized to CO2 in absence of H2 via the following two major reactions [16]: CO þ O2 ()CO2 þ O

ð14:17Þ

O þ CO þ M()CO2 þ M

ð14:18Þ

However, as H2 is also produced via the dissociation of H2O, H2 O()H2 þ 1=2O2

ð14:19Þ

Hence, in the presence of a small amount of H2, the following reactions occur: CO þ OH ! CO2 þ H

ð14:20Þ

CO þ HO2 ! CO2 þ OH

ð14:21Þ

The reactions, and their associated rate parameters, for the combustion of a simple methane fuel are listed in Table 14.6 [16]. Rightley and Williams [16] and Li and Williams [15] have each shown that CO is formed as a result of formyl reactions, where CHO. radicals are either broken down in the presence of an external agent or react with H. , O. , or OH. radicals. In addition, methylene reactions, where CH2. radicals react with H. , O. , OH. , or CH2. radicals, can give CO as the product. Then, in the presence of OH. and HO2. radicals, CO is oxidized to CO2. Also, CHO. and O. radicals combine to form CO2, while some oxygen available in the combustion reacts with CH2 to generate CO2. The same situation occurs in the presence of HC2O, where CHO. radicals are formed in addition to CO2 [27]. 14.2.3 Estimation of CO2 Concentrations Based on the IPCC Method

Even the most complicated quasi-global reaction model has its limitations for the estimation of actual flame combustion. This is because it only considers the chemical reaction effect, such that the heat, mass, and momentum transfer effects on the pollutant concentration cannot be evaluated. Since the changes in flow systems, reactors and flame will result in different pollution emission, the model becomes

14.2 The Formation of CO2 Table 14.6 The elementary reactions and their rate parameters, with the specific reaction rate constants of Equation 14.16, except where otherwise indicated.

No.a) 1 2 3 4

Reactions H þ O2 , OH þ O H2 þ O , OH þ H H2 þ OH , H2O þ O OH þ OH , H2O þ O

Recombination reactions 5b) H þ H þ M , H2 þ M H þ OH þ M , H2O þ M 6c) 7b) O þ O þ M , O2 þ M Hydroperoxyl formation and consumption 8c) H þ O2 þ M , HO2 þ M

Ba)

ma)

Ea)

3.52  1016 5.06  104 1.17  1O9 K ¼ 5.46  1011 exp (0.00 149 T)

0.7 2.67 1.30

17 070 6290 3626

[17, 18] [17, 19] [17, 20] [17, 21]

7.20  1017 2.20  1022 1.14  1017

1.0 2.0 1.00

0 0 0

[17, 20] [17, 19] [20, 22]

6.76  1019 4.52  1013 1.70  1014 9 HO2 þ H , OH þ OH 10 HO2 þ H , H2 þ O2 4.28  1013 3.10  1013 11 HO2 þ H , H2O þ O 2.00  1013 12 HO2 þ O , OH þ O2 13 HO2 þ OH , H2O þ O2 2.89  1013 Conversion of carbon monoxide to carbon dioxide 1.33  101 14b),d) CO þ O þ M , CO2 þ M 3.0  1012 15 CO þ O2 , CO2 þ O 2.50  1012 4.40  106 16 CO þ OH , CO2 þ H 17 CO þ HO2 , CO2 þ OH 6.03  1013 Formyl formation and consumption H þ CO þ M , HCO þ M 4.56  1014 18b) 4.52  1013 19d) HCO þ H , CO þ H2 1.00  1014 20 HCO þ O , CO þ OH 3.00  1013 21 HCO þ O , CO2 þ H 3.00  1013 5.00  1013 22 HCO þ OH , CO þ H2O 23 HCO þ O2 , CO þ HO2 3.00  1012 Formaldehyde formation and consumption 24b),e) HCO þ H þ M , H2CO þ M 1.35  1024 1.10  1016 25 H2CO þ H , HCO þ H2 1.26  108 3.50  1013 26 H2CO þ O , HCO þ OH d) 27 H2CO þ OH , HCO þ H2O 3.90  1010 28 H2CO þ HO2 , HCO þ H2O2 1.00  1012 a) b) c) d) e) f)

Reference(s)

1.4 0.0 0.0 0.0 0.0 0.0 0.0

0 0 874 1411 1720 0 497

0.0 0.0 0.0 1.5 0.0

0 0 47 801 741 22 950

0.0 0.0 0.0 0.0 0.0 0.0 0.0

2385 0 0 0 0 0 0

Ko [17, 24] K¥f Þ [16] [17] [21] [21] [26] [24]

77 900 77 900 2175 3511 396 8000

Ko [22, 26] k¥ [22, 26] [22] [22] [16] [22]

2.570 0.0 1.62 0.0 0.89 0.0

Ko [17, 21] k¥ [21, 23] [17, 19] [17, 19] [17, 19] [17, 20] [17, 19] Ko [16] K¥ e) [16] [22] [17, 24] [25]

Units: mol cm 3, s 1, K, cal mol 1. Chaperon efficiencies: N2, O2:1.0, CO: 1.9, CO2: 3.8, H2: 2.5, H2O: 16.3. Chaperon efficiencies: same as b, except H2O: 12.0. An average of several rates in the literature. Estimated to be the average of the reported [19]; ka values for O þ O2 þ M ! O3 þ M and O þ NO þ M ! NO2 þ M. Estimated to be the same as ka for reaction 8.

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Greenhouse Gas Formation and Capture

unviable for the rapid evaluation of the CO2 emitted from industrial plants or utility boilers with combustion processes. The IPCC provides such estimations of CO2 emissions quantities. The methods described here that have been used to estimate CO2 emissions from the combustion of fossil fuels were derived from the IPCC report and used in the Inventory of US Greenhouse Gas Emissions and Sinks: 1990–2005 [28, 29]. Consequently, the estimation of CO2 emissions from fuel combustion presented here are calculated using the IEA energy data and the default methods and emission factors from the Revised 1996 IPCC Guidelines for National GHG Inventories [5, 29]. Since 2000, the IEA has presented CO2 emissions calculated using both the IPCC Reference Approach and the IPCC Tier 1 Sectoral Approach. National emissions estimates are made based on amounts of fuels used and the carbon content of fuels. The CO2 emissions from the combustion of fossil fuels, in terms of mass of CO2 per unit of energy in units of kg C (as CO2) GJ 1 and lb CO2 MMBtu 1, are listed in Table 14.7. In order to calculate CO2 emissions from the combustion of fossil fuels by using the IPCC methodology [29], the following steps (data) are required: . . . . . . . .

Obtain the required energy data. Estimate the total carbon content of the fuels. Estimate the total carbon stored in products. Estimate the carbon potentially emitted from bunker fuel consumption. Estimate the carbon emissions associated with net imports of electricity. Calculate the net potential carbon emissions. Estimate the carbon actually oxidized from energy uses. Convert the net carbon emissions from energy consumption to total CO2 emissions.

Based on the above steps, it is possible to estimate CO2 emissions from the combustion of fossil fuels, and total CO2 emissions. In the final step, estimating CO2 emissions from fossil fuel consumption included converting from units of carbon to units of CO2. Actual carbon emissions were multiplied by the molecular-to-atomic weight ratio of CO2 to carbon (44/12) to obtain the total CO2 emitted from fossil fuel combustion in teragrams (Tg). The CO2 emissions in 2005 from the combustion of fossil fuel, assessed by using the IPCC reference approach, are listed in Table 14.8. Table 14.7 CO2 emissions from major sources of fossil fuels per unit of energy produced [10]. 1a)

Fossil fuel

Kg(C) GJ

Coal (bituminous-CH0.8O0.1) Crude oil (CH1.8) Natural gas (CH4)

24.0–25.3 19.0–20.3 13.6–14.0

a) GJ ¼ gigajoules ¼ 109 joules, energy based on Higher Heating Value (HHV). b) MMBtu ¼ 106 Btu, energy based on HHV. c) MMBtu ¼ 1.05 GJ. Kg CO2 kg 1 C ¼ lb C ¼ 3.67.GT(C)/EJ ¼ 10 6 kg(C) GJ 1. EJ ¼ exajoule ¼ 1018 joules.

lb CO2 MMBtu 203–215 160–172 115–119

1b)

14.3 Reduction of CO2 Emissions from Combustion Sources Table 14.8

CO2 emissions in 2005 from combustion of fossil fuel by using a reference approach

[28, 29]. Fuel category

Coal Petroleum Natural gas Total a)

Potential emissions

Carbon sequestered

Net emissions

Fraction oxidized (%)

Total emissionsa)

2094.0 2872.7 1190.2 6156.9

1.6 229.6 11.9 243.1

2092.5 2643.0 1178.3 5913.9

100 100 100

2.092.5 2643.0 1178.3 5913.9

Unit: Tg carbon dioxide equivalent (CDE).

14.3 Reduction of CO2 Emissions from Combustion Sources

In order to reduce GHG emissions from fossil fuel-fired power generation, several possibilities exist [30]: . .

. . .

To improve the efficiency of the power plants. To introduce combined cycles with the generation by gas and steam turbines, as these can achieve high thermal efficiencies. To substitute coal with gas. To replace hydrocarbon fuels with renewable energies. To develop CCS strategies.

The first three options are based on the combustion theories that are described in more details in Vol. 1 Ch. 1, 2, 8 and 21. Here, the discussions will center on the last two options, namely renewable energy and CCS technology. 14.3.1 Replacement of Hydrocarbon Fuels with Renewable Energies

Sustainable energy is energy that, in its production or consumption, has minimal negative impacts on human health and the healthy functioning of vital ecological systems, including the global environment. It is an accepted fact that renewable energy is a sustainable form of energy [31]. The renewable energies include solar energy, bioenergy use, combined heat and power (CHP), fuel cells, hydrogen production, hydropower, and wind energy. In an excellent review, Omer [31] discusses the energy sources and their relationship with the environment and sustainable development. This includes all the renewable energy technologies, energy efficiency systems, energy conservation scenarios, energy savings and other mitigation measures necessary to reduce climate change. The direct use of renewable energy such as biofuels is considered to produce no net CO2 emissions in its life cycle. When co-fired with coal, a biofuel can reduce the effective CO2 emissions of a coal-fired power generation system, but may also reduce the system’s efficiency [32]. Coal co-firing with an up to a 20% biomass mix has been

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Greenhouse Gas Formation and Capture

shown to be successful [33], having accomplished the benefits of: (i) an increased boiler efficiency; (ii) reduced fuel costs; and (iii) reduced emissions of NOx and fossil CO2. With an energy offset of 1 kg of C in biomass per 0.6 kg of C in fossil fuel, there exists a vast potential for offsetting fossil fuel emission. Bioenergy crops have the potential to sequester approximately 318 Tg C yr 1 in the United States, and 1631 Tg C yr 1 worldwide [34]. Figure 14.1 compares the biomass fuel chain with that for 500 kg of coal [35]. As coal is a carbonized biomass, it is not surprising that 500 kg of coal also contains about 18.5 GJ. Furthermore, the energy required to mine coal and deliver it to a power station is similar to that required to produce biomass, per unit of carbon or energy content (in Figure 14.1, this is given as 0.5–2.0 GJ, emitting 10–50 kg C, to produce 500 kg coal). Moreover, the conversion efficiency of coal to electricity is also around 40%. Consequently, in terms of electricity generation, biomass and coal are approximate energy equivalents. The only substantial difference is that coal emits 500 kg of carbon to the atmosphere, whereas energy crops recycle it (see Figure 14.1). Consequently, to a reasonable approximation, 1.0 tonne of dry biomass will displaces 0.5 t of carbon from coal, and both will serve as primary fuels when used to generate electricity [35].

Figure 14.1 Simplified schemes of the flows of energy and carbon when generating electricity from biomass, coal, or natural gas. CHP ¼ “combined heat and power” [35].

14.3 Reduction of CO2 Emissions from Combustion Sources

There are, however, a number of drawbacks related to the application of biofuels. For example, when using biofuel blends for diesel engine applications, the emission of NOx tends to be higher. Besides, the intervals between the replacement motor parts (such as fuel filters) are reduced, and degradation by chronic exposure of varnish deposits in fuel tanks and fuel lines, paint, concrete, and paving may occur as some materials are incompatible [36]. Nonetheless, fuel additives can be used to minimize these drawbacks and produce specified products that meet international and regional standards. 14.3.2 The CCS Technologies

Among the techniques used to mitigate global warming, CCS is probably the most attractive, as it captures CO2 emitted from large point sources such power plants and stores it, rather than allowing it to be released into the atmosphere. The CCS technologies have been identified as cost-effective routes for stationary sources to mitigate the GHG effect [5], and could indeed be used to achieve the necessary major reductions in GHG emissions. In general, CCS is a three-stage processes that includes: (i) the capture of a CO2 stream from industrial and energy-related sources; (ii) the compression and transportation of CO2 to a suitable storage location; and (iii) the deep underground injection of CO2. A schematic representation of the major processes of the CCS technologies is shown in Figure 14.2. The purpose of CO2 capture is to produce a concentrated stream of CO2 that can be transported and stored. Generally, capture of CO2 can be applied to large point sources of emissions, such as fossil fuels burning from power plants and chemical industries, biomass energy production, petrochemical and oil refineries, and so on. The capture of CO2 from small and mobile sources such as transportation, residential and commercial sectors is expected to be more difficult and expensive as compared with CO2 capture from large point sources. Therefore, the technology may be applicable only to large point sources. As can be seen in Figure 14.2, the CCS technologies currently being developed from combustion and gasification technologies include [5]: .

.

.

Pre-combustion capture: This usually employs the integrated gasification combined cycle (IGCC) with a shift reactor to convert CO to CO2, followed by CO2 capture; hence, it is often referred to as IGCC-CCS [30]. Post-combustion capture: This is to capture CO2 from plants of conventional pulverized fuel technology with scrubbing of the flue gas for CO2 removal. The oxyfuel (Oxyf) combustion: This, together with the combustion, occurs in O2 rather than in air. The O2 is diluted with an external recycle flue gas so as to reduce its combustion temperature.

A schematic representation of different advanced methodologies of CO2 capture is illustrated in Figure 14.3. It is clear that few steps are involved to separate CO2, H2, and O2 from a bulk gas stream such as flue gas, synthesis gas, or an air stream. These separation steps can be achieved by using physical or chemical solvents, membranes,

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Greenhouse Gas Formation and Capture

Figure 14.2 Schematic of the major processes in the carbon dioxide capture and storage (CCS) technology [5].

solid sorbents and cryogenic separation technique. The different advanced techniques of CO2 capture will be discussed in Section 14.4. The typical CO2 concentrations prior to the post-combustion capture, pre-combustion capture and oxyfuel combustion, respectively, are 5–20%, 15–60%, and 80–96% (v/v) [30]. The main characteristics of the CCS options for these processes are compared in Table 14.9 [30]. 14.3.2.1 Post-Combustion Capture Post-combustion capture (PCC) is a downstream process, in which CO2 in flue gas stream at near atmospheric pressure is removed typically by a chemical absorption

14.3 Reduction of CO2 Emissions from Combustion Sources

Figure 14.3 Schematic of advanced CO2 capture technologies [5].

technique [37, 38]. Because of the relatively low CO2 concentration in power plant flue gas streams, chemical absorption systems have been the dominant technology of interest for PCC so far. These systems normally use an organic solvent to capture a small quantity of CO2 from flue gas stream; monoethanolamine (MEA) is frequently employed in this role in PCC systems for modern pulverized coal power plants or natural gas-combined cycle power plants. Unfortunately, due to the high energy penalty and running costs of the MEA process, newer capture technologies are under development (these will be discussed in the next section).

Table 14.9 Comparison of main characteristics of CCS options, with desirable characteristics indicated by x [30].

Technology

Suitable for retrofit of existing pf plants

PCC IGCC-CCS Oxyfuel

x x

Can be applied on slip-stream, i.e., for partial CO2 capture

x x, but unlikely

Does not require O2 supply

Does not require CO2 capture prior to compression

Generates H2 as alternative fuel

x x x

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Greenhouse Gas Formation and Capture

14.3.2.2 Pre-Combustion Capture (IPCC-CCS) The low concentration of CO2 in PCC results in large capture equipment sizes, high capital costs, and high energy consumption. However, if the CO2 concentration and pressure could be increased, the CO2 capture equipment could be much smaller and different solvents used, with smaller energy penalties for regeneration. This can be achieved by using the IPCC-CCS [37, 38], in which the fuel is reacted with O2 or air steam to give mainly CO and H2 (commonly known as “synthesis gas”). The CO is reacted with steam in a catalytic reactor, called a shift converter, to produce CO2 and more H2, after which the CO2 is separated and the H2 used as a fuel in a gas turbine combined cycle plant. The same process can be used for coal, oil, or natural gas, although when coal or oil are used additional stages of gas purification must be included to remove any ash particles, sulfur compounds, and other minor impurities. The CO2, which is emitted at a high pressure, can be captured using physical solvents at low volumes, with subsequent lower costs. High percentages of CO2 capture are generally achieved when using these systems. 14.3.2.3 Oxyfuel Combustion Capture The major component of any flue gas stream is nitrogen from the air feed. In fact, if there were no nitrogen present, the capture of CO2 from a flue gas would be greatly simplified. For the oxyfuel approach, the power plant is fed with O2 produced from an air-separation plant (these are already used on a large scale in the steel industry), rather than air [37, 38]. By using O2 rather than air for combustion, either in a boiler or a gas turbine, the concentration of CO2 in the flue gas is greatly increased. However, when using pure O2 the flame temperature will be much higher and the CO2-rich flue gas will need to be recycled to the combustor in order to reduce the flame temperature to a similar level as encountered in a normal air-blown combustor. Oxyfuel combustion and CO2 capture from flue gases represents a near-zero emission technology that can be adapted to both new and existing pulverized coalfired power stations. In oxyfuel technology, the concentration of CO2 in the flue gas is greatly increased, with laboratory-based studies having indicated that the CO2 concentration in the flue gas of a pulverized coal fired boiler might exceed 95% during oxyfuel combustion [39]. Unfortunately, however, the CO2 concentrations attained during pilot-scale experiments have been lower, due to air leakage into the furnace [40]. The CO2 produced can be captured by cooling and then compressed for subsequent transportation and storage. The main disadvantage of oxyfuel is that the production of O2 is expensive, both in terms of capital cost and energy consumption, although recent advances in this area, such as new and improved membranes that can operate at high temperatures, may lead to improved overall plant efficiencies and economics. Oxyfuel combustion may represent an attractive option for the retrofit of existing steam cycle power stations, as the modifications required would be relatively minor. Although oxyfuel combustion can also be applied to gas turbines, those that utilize CO2 as the working fluid would differ substantially from conventional gas turbines, and a simple retrofit would not be feasible. Furthermore, this technology is not yet mature and its operating and maintenance and capital costs of Oxyfuel might be comparable to those of PCC

14.4 Emerging Technologies for CO2 Reduction

technology [41]. Specifically, the O2 separation plants would consume about 23–37% of the total plant output, with costs similar to those associated with a chemical absorber. 14.3.2.4 Transportation and Storage of CO2 Following the capture of CO2 from various anthropogenic sources, its transportation to an identified reservoir forms the next two stages of the sequestration process. Currently, pipelines are the most commonly used technology for transporting CO2; however, before transport the CO2 must be compressed (typically above 8 MPa), not only to avoid two-phase flow regimes but also to increase the CO2 density so that its transport is less costly and easier. CO2 may also be transported as a liquid (in insulated tanks) in ships, or by road and/or rail tankers. In ships, the CO2 can be transported in similar fashion to liquefied petroleum gases (LPG), although at present this technique is used on only a small scale due to limited demand [5]. In addition to the technological concerns, the injection and storage of CO2 into reservoirs requires further studies to be conducted on the legislation, regulations, and permitting issues [42, 43]. At present, there are two potential storage options – the oceans, or in geological reservoirs. The total sequestration potential of these two options is considered to be sufficiently large for the total recoverable fossil fuels (4000 Gt-C) [44]. In comparison to the legal issues and environmental concerns of ocean storage, the geological storage of CO2 represents a more promising option, and is capable of achieving major reductions within the foreseeable future [45]. Currently, three types of geological formation have been identified, namely oil and gas reservoirs, deep saline formations, and unminable coal beds. These are considered more technically feasible than ocean sequestration, notably because the underground injection of CO2 has long been used on a commercial basis, an example being that of enhanced oil recovery (EOR). The techniques used for the sequestration of CO2 are described in greater detail in Vol. 5 Ch. 19.

14.4 Emerging Technologies for CO2 Reduction

The CCS technologies being used in the pre-combustion or post-combustion processes may employ a different approach from that used in the MEA absorption process. The IPCC special report [5] concluded that the design of a full-scale industrial adsorption process might be feasible and, of the emerging CO2 capture technologies available, Aaron and Tsouris [46] suggested that membrane separation, absorption and adsorption might be the most promising. The recently developed chemical looping combustion (CLC) also appears to be an efficient and low-cost process whereby the captured CO2 can be either further stored or utilized. The details of these emerging technologies of CO2 capture – CLC and CO2 utilization – are outlined in the following sections.

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14.4.1 Emerging CO2 Capture Technologies 14.4.1.1 Absorption of CO2 Absorption is a process by which one or more compound(s) of a gas mixture are transferred into a liquid in which it/they is/are soluble. The absorption can be categorized into two types – physical and chemical – on the basis of the nature of the interaction between absorbent and absorbate. In physical absorption, the component being absorbed is more soluble in the liquid absorbent than are the other gas components with which it is mixed, but it does not react chemically with the absorbent. On the other hand, chemical absorption is characterized by the occurrence of a chemical reaction between the gas component being absorbed and a component in the liquid, such that a compound is formed. Absorption processes use a suitable solvent to separate CO2 from the flue gas stream. Alkanolamines (e.g., MEA and diethanolamine) are typically used in chemical absorption, whereas methanol, dimethylether, polyethylene glycol, and sulfolane are employed in physical absorption [10]. The major issues with MEA and other solvents include equipment corrosion in the presence of O2 and the energyintensive solvent regeneration. The presence of common flue gas contaminants, such as SOx, and NOx, also has a negative impact on solvent-based process performance. Compared to the conventional MEA process for the capture of CO2 from flue gas, the ammonia scrubbing technique [47–49] provides advantages of lower material costs, a higher absorption efficiency, a greater absorption capacity and less corrosion to absorber, as well as the potential to save energy (which ultimately makes the process cheaper to operate). Ammonia absorption has attracted much attention recently, and studies are currently under way to further improve the ammonia-CO2 absorption/regeneration process [50–57]. In addition, ionic liquids may also provide breakthrough concepts to CO2 capture [58–60]. 14.4.1.2 Adsorption of CO2 An equally well-known method for separating gases from a gas stream is that of adsorption, which occurs when a gas (or) liquid solute accumulates on the surface of a solid adsorbent. Adsorption processes are based on the selective adsorption of CO2 on a solid adsorbent, such as zeolites, alumina molecular sieves and activated carbon. Recently, high-efficiency adsorbents that function at either high or low temperatures have been developed. One very promising high-temperature chemical sorbent is that of CaO, which be used either directly or in modified form [61–63], and is freely obtained from limestone, which is in abundantly available. The sorption/desorption (carbonation/calcination) temperatures of modified CaO are normally in the range of 650–850  C. In contrast, the most promising low-temperature adsorbents include carbon nanotubes (CNTs) [64, 65], mesoporous silica (MPS) materials [66–68], and metal organic frameworks [58, 69], all of which would be expected to function at temperatures below 80  C. A state-of-the-art review of calcium-based sorbent looping processes for carbon capture is provided in Vol. 5 Ch. 21.

14.4 Emerging Technologies for CO2 Reduction

14.4.1.3 Membrane Separation Porous membranes, which are capable of separating gas molecules of different molecular sizes, are available in a variety of forms, including polymers, metals, and rubber composites. Likewise, a hollow-fiber membrane with polypropylene (PP) and polytetrafluoroethylene (PTFE) has been shown to perform better than a packed column containing a Sulzer DX structured packing (Sulzer Chemtech Ltd, Switzerland) [70]. The main disadvantage of a membrane separation is its low gas throughput, and the need for multistage operation or stream recycling [71]. The development of a membrane separator for the selective removal of CO2 in the presence of CO, H2, H2O, and H2S (fuel gas) or N2, O2, H2O, SO2, NOx, and HCl (flue gas) would be of tremendous economic value [72]. A membrane separation process requires less maintenance and energy than a comparable absorption system, and a membrane material that would allow either the selective transport (diffusion) or selective exclusion of CO2 would clearly be highly desirable. Recently, extensive investigations have been conducted on the properties of CO2-selective membranes based on inorganic materials such as zeolites, alumina, carbon, and silica [72, 73]. 14.4.2 Chemical Looping Combustion

Although the process of CLC offers a great opportunity not only to eliminate the energy-intensive CO2 separation but also to reduce CO2 sequestration costs, it is not at present a fully established technology. A recent review [71] provided an excellent background of the CLC process which, initially, was intended to increase the thermal efficiency of power-generation stations but was later identified as having inherent advantages for CO2 separation, with minimum energy losses [71]. CLC involves using a metal oxide as an oxygen carrier, with the process configured in two interconnected fluidized-bed reactors, namely an air reactor and a fuel reactor (see Figure 14.4). In the CLC process, the loss of energy in the conversion reactions and in the heat exchange is reduced, while power generation efficiency is improved. For the metal/metal oxide systems considered, most (or all) of the exothermicity occurs in the air reactor, and therefore the heat of combustion will be recovered mainly from the air reactor. The overall reaction stoichiometry in the fuel reactor can be written as follows [71]: ð2n þ mÞMy Ox þ Cn H2m ! ð2n þ mÞMy Ox

1

þ mH2 O þ nCO2

ð14:22Þ

When the fuel oxidation has been completed, the reduced metal oxide MyOx 1 (or metal) is transported to the air reactor where it is reoxidized according to the following reaction: M y Ox

1

þ

1 O2 ðairÞ ! My Ox þ ðN2 þ unreacted O2 Þ 2

ð14:23Þ

The further processes and applications of the CLC system are described in Vol. 5 Ch. 20.

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Figure 14.4 Two interconnected fluidized-bed reactors of the chemical looping combustion (CLC) [71, 74].

14.4.3 Utilization of CO2

The separation of CO2 from combustion sources, followed by utilization of the separated CO2 as a useful carbon source, might represent one of the most effective routes for recycling carbon sources and reducing global warming [75]. The catalytic conversion and utilization of CO2 into industrially useful compounds has long been a major challenge for synthetic chemists, and consequently has attracted much research interest [76–79]. As CO2 can be used as an important source of carbon (raw material) for producing organic chemicals, synthetic fuels and other useful products [80], it would appear that the chemical industry can make a major contribution towards reducing the CO2 emission, by both direct and indirect routes. Currently existing and emerging industrial applications of solid, liquid and gaseous states of CO2 conversion and utilization are listed in Table 14.10. It should be noted that the amounts of CO2 emitted as the concentrated CO2-rich flue gases from electric power plants and industrial manufacturing plants have become much higher than the amounts of carbon used to produce most organic chemicals, valuable materials, and synthetic fuels [78, 81]. Nonetheless, the production of chemicals from CO2 may still have a small, but significant, positive impact on the global carbon balance. Furthermore, CO2 is generally considered to be a cheap, nontoxic feedstock that can frequently replace toxic chemicals such as phosgene or isocyanates. CO2 is a totally renewable feedstock compared to oil or coal, and the production of chemicals from CO2 can lead to new routes and new products. Consequently, CO2 has been suggested as a sustainable replacement for organic solvents in a wide variety of

14.4 Emerging Technologies for CO2 Reduction Table 14.10

Current research status of CO2 utilization in several industrial applications [79, 85–87].

S. no.

Various sectors

Industrial applications of CO2

1.

Chemicals and pharmaceuticals

2.

Food stuffs and beverages

3.

Healthcare

4.

Environment safety and other sectors

CO2 is used in chemical synthesis and for controlling reactor temperatures . CO2 is employed to neutralize alkaline effluents . CO2 is used as a blowing agent for polyurethane and polystyrene foam production and for blow-molding manufacture of plastic bottles, and containers . CO2 is used for making chemicals such as salicylic acid (aspirin); for use as an inert gas, and for supercritical fluid extraction . CO2 is used for product transportation at low temperature ( 78  C or 108  F) and also for the acidification (pH) of wastewater . Liquid CO2 can be used as cryogenic fluid in chilling or freezing operations, or as dry ice for temperature control during the storage and distribution of foodstuffs . Packaging of foodstuffs to increase the shelf life of many food products due to its inert properties and its growth-inhibiting effect of CO2 on microorganisms . Stunning of pigs and poultry in slaughterhouses instead of using electrical stunning . Carbonation of beverages such as soft drinks, mineral water or beer . Supercritical CO2 is used to remove caffeine from coffee beans by extraction . CO2 is used as shielding gas for preserving drink quality, and propellant gas for emptying tanks of drinks . CO2 is used in drinking water treatment in modern water works, together with lime or chalk . CO2 produces close-to-physiologic atmospheres for the operation of artificial organs . CO2 is used as a component in a mixture of oxygen or air as respiratory stimulant to promote deep breathing . CO2 is used for the surgical dilation by intra-abdominal insufflations . Liquid CO2 can be used in recycling of waters from acid mine drainage . Waste water treatment and waste liquid treatment by injection of CO2 for the pH of liquid effluents. CO2 is an excellent alternative to sulfuric acid for pH balance control . CO2 is used as fire extinguishers . pH control and regulation of waste waters, swimming pools, etc. .

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chemical transformations [77, 79] that includes its use as an important industrial chemical feedstocks in the following processes [77, 79]: .

CO2 reforming of methane CO2 þ CH4 ! 2CO þ 2H2

.

ðH2 =CO  1 2Þ

ð14:24Þ

CO2 hydrogenation to methanol CO2 þ 3H2 ! CH3 OH þ H2 O

ð14:25Þ

The methanol can also be dehydrated to form gasoline-like fuels mCH3 OH ! mC2 H2n þ 2 þ mH2 O .

CO2 as a soft oxidant Selective dehydrogenation of ethylbenzene into styrene using CO2 as a soft oxidant [81]: C6 H5 CH2 CH3 þ CO2 ! C6 H5 CH ¼ CH2 þ H2

H2 þ CO2 ! CO þ H2 O .

ð14:26Þ

ðdehydrogenationÞ ð14:27aÞ ð14:27bÞ

Chemical fixation of CO2 in carbonates: the synthesis of dimethyl carbonate (DMC) Conventional synthesis of DMC using toxic phosgene: COCl2 þ 2CH3 OH ! CH3 OCOOCH3 þ 2HCl

ð14:28Þ

On the other hand, environmental friendly synthesis of DMC using CO2: CO2 þ 2CH3 OH ! CH3 OCOOCH3 þ H2 O

ð14:29Þ

Although, unfortunately, the use of CO2 as a feedstock to create chemicals will not have any major impact on the mitigation of GHG emissions in the near future, it is essential that research into CO2 conversion and utilization is continued. Without doubt, these investigations will become an integral part of carbon management and its sustainable development. It seems likely that the option to utilize CO2 will contribute to a reduction in the total emissions of CO2 into the atmosphere of some 5–7%, with CO2 utilization by the chemical industry accounting for approximately 100 Mt per year [80, 82]. Among the major products that can be produced from CO2 as feedstock are included urea, salicylic acid, cyclic carbonates and polycarbonates, with urea production (ca. 90 million tonnes per year) probably representing the major use [83, 84]. In addition to the commercial processes using CO2, several reactions currently under investigation, both in industry and in the laboratory, hold promise [77]. Consequently, it is essential that research in this area is continued, the aim being to optimize the effective conversion of CO2 and its utilization for valuable chemical syntheses.

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14.5 Outlook

The capture, storage and/or reutilization of CO2 represents a promising action for industrial and utility sources that involve combustion processes to mitigate the global warming effects of the GHGs. Although in one way this could increase the costs and energy consumption of these plants, in another way it might result in new industries that demand both renewable energies and CCS technologies. With the enforcement of the Kyoto Protocol, it is expected that carbon taxes and emission trading prices will continue to increase in many countries. This will, eventually, increase the costeffectiveness of renewable energies and CCS technologies, despite many of them already having been considered as “too expensive.”. It is worthwhile, therefore, continue researching into these two areas, so that a sustainable environment might, in time, be reached. In the case of the CCS technologies, in 2007 the US Department of Energy established the initial technology goal of “. . .to develop, by 2012, fossil fuel conversion systems that offer 90% CO2 capture with 99% storage permanence at less than a 10% increase in the cost of energy services”. This may provide a guideline for the development of novel CCS technologies. However, by considering the costeffectiveness, whether 90% CO2 capture efficiency is an effective goal, or not, would require further debate. A detailed discussion of CO2 capture and sequestration techniques is also provided in Vol. 5 Ch. 19–23.

14.6 Summary

By the year 2030, the projected global annual emission of CO2 will be approximately 60 Gt – about double the 2005 level of 27.8 Gt. As fossil fuels remain the dominant source of energy worldwide, it will become necessary to effect major cuts in CO2 emissions from combustion sources in order to mitigate global warming effects. Since CO2 is a product of the complete combustion of fossil fuels, it will inevitably take on the role of a GHG. Yet, the quantities of CO2 emitted can be reduced in terms of the energy produced, by improving thermal efficiencies, by using alternative fuels, by replacing fossil fuels with renewable energies, and by employing CCS technologies.

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gas for ammonia scrubbing technology. Korean J. Chem. Eng., 24 (3), 495–498. Kim, Y.J., You, J.K., Hong, W.H., Yi, K.B., Ko, C.H., and Kim, J.-N. (2008) Characteristics of CO2 absorption into aqueous ammonia. Sep. Sci. Technol, 43, 766–777. US Department of Energy, Office of Fossil Energy, National Energy Technology Laboratory (2007) Carbon Sequestration Technology Roadmap, Program Plan. Available at: http://www.blm.gov/pgdata/ etc/medialib/blm/nv/field_offices/ ely_field_office/energy_projects/ white_pine_energy1/feis_wpes_pieces. Par.92179.File.dat/18%20-% 20WPEnergyStation%20Appendix%20E %2009252008.pdf (accessed on 23 January 2009). Camper, D., Bara, J.E., Gin, D.L., and Noble, R.D. (2008) Room-temperature ionic liquid-amine solutions: tunable solvents for efficient and reversible capture of CO2. Ind. Eng. Chem. Res., 47, 8496–8498. Pennline, H.W., Luebke, D.R., Jones, K.L., Myers, C.R., Morsi, B.I., Heintz, Y.J., and Ilconich, J.B. (2008) Progress in carbon dioxide capture and separation research for gasification-based power generation point sources. Fuel Process. Technol., 89 (9), 897–907. Li, Z.-S., Cai, N.-S., and Huang, Y.-Y. (2006) Effect of preparation temperature on cyclic CO2 capture and multiple carbonation-calcination cycles for a new Ca-based CO2 sorbent. Ind. Eng. Chem. Res., 45, 1911–1917. Iyer, M.V., Gupta, H., Sakadjian, B.B., and Fan, L.-S. (2004) Multicyclic study on the simultaneous carbonation and sulfation of high reactivity CaO. Ind. Eng. Chem. Res., 43, 3939–3947. Chen, Y.-T., Karthik, M., and Bai, H. (2009) Modification of CaO by organic alumina precursor for enhancing cyclic capture of CO2 greenhouse gas. J. Environ. Eng. ASCE, 135, 459–464. Su, F., Lu, C., Cnen, W., Bai, H., and Hwang, J.F. (2009) Capture of CO2 from flue gas via multiwalled carbon nanotubes. Sci. Total Environ., 407 (8), 3017–3023.

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www.entek.chalmers.se/anly/sy mp/ 01mattisson.pdf. Choi, M.-J. and Cho, D.-H. (2008) Research activities on the utilization of carbon dioxide in Korea. Clean-Soil, Air, Water, 36 (5–6), 426–432. Anastas, P.T. and Williamson, T.C. (1996) Green Chemistry: Designing Chemistry for the Environment, ACS Symposium Series No. 626, American Chemical Society, Washington, DC, ISBN 0-8412-3399-3. Arakawa, H., Aresta, M., Armor, J.N., Barteau, M.A., and Beckman, E.J. et al. (2001) Catalysis research of relevance to carbon management: Progress, challenges, and opportunities. Chem. Rev., 101, 953–996. Song, C.S. (2002) CO2 conversion and utilization: an overview, in CO2 Conversion and Utilization, vol. 809, ACS Symposium Series (eds C.S. Song A.M. Gaffney, and K. Fujimoto), American Chemical Society, Washington DC, pp. 2–30. Song, C.S. (2006) Global challenges and strategies for control, conversion and utilization of CO2 for sustainable development involving energy, catalysis, adsorption and chemical processing. Catal. Today, 115, 2–32. Aresta, M. and Tommasi, A. (1997) Carbon dioxide utilization in the chemical industry. Energy Convers. Manage., 38, S373–S378 Aresta, M. and Dibenedetto, A. (2004) The contribution of the utilization option to reducing the CO2 atmospheric loading: research needed to overcome existing barriers for a full exploitation of the potential of the CO2 use. Catal. Today, 98 (4), 455–462. Aresta, M. (1999) RUCADI, Recovery and Utilization of Carbon Dioxide; EU-Report. Creutz, C. and Fujita, E. (2000) Carbon dioxide as a feedstock, in Carbon Management: Implications for R&D in the Chemical Sciences and Technology: A Workshop Report to the Chemical Sciences Roundtable, The National Academies Press, Washington. Xu, A., Indala, S., Hertwig, T.A., Pike, R.W., Knopf, F.C., Yaws, C.L., and Hopper, J.R. (2005) Development and integration

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15 Soot and Soot Diagnostics by Laser-Induced Incandescence Alfred Leipertz and Johannes Kiefer 15.1 Introduction

In general, soot is composed of spherical elemental carbon (EC) nanoparticles (primary particles) with diameters in the range of 5 to 100 nm. Such nanoparticles are generated by the coagulation, surface growth, oxidation and coalescence of particle precursors which are smaller than 3–5 nm in size. These primary particles act as building blocks for the formation of soot aggregates, which contain several primary particles that form a three-dimensional (3-D) structure of up to several hundred nanometers size, with a fractal dimension of 1.5 to 3. An example of such a soot aggregate is shown in Figure 15.1. Depending on the particular soot formation process – for example, flame, electrical discharge, or engine combustion – the soot structure may differ in several aspects. Combustion-generated soot is of particular importance in many areas in combustion research and technology. There are some applications where soot formation is desirable, such as in the production of carbon black, or when heat must be carried away from the combustion process by thermal radiation. However, in other applications the formation of soot should be avoided, as it is a pollutant; a typical example is in automotive and industrial exhaust gases, where the soot may be harmful to both health and the environment. (The toxicological aspects of soot are discussed in Vol. 1 Ch. 15 of this Handbook.) The optimization of both types of process demands a detailed understanding of soot formation in combustion environments, however, and for this purpose many attempts have been made in the past. These have included modeling approaches, based on physical and chemical fundamentals, or diagnostic approaches that allow experimental investigations into fundamental and real processes to be performed. The simultaneous use of both strategies represents a powerful tool for obtaining new insights into soot formation and oxidation processes. Laser-induced incandescence (LII) has proven to be a powerful measurement technique for soot characterization in different combustion environments for many years, and has been applied to the investigation of soot in technically relevant combustion devices. In principle, time-resolved LII signals contain information

Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright Ó 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

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Figure 15.1 Transmission electron microscopy image of a typical combustion-generated soot aggregate.

about a variety of characteristic parameters, such as the primary particle size and soot volume fraction. Moreover, when combined with light scattering it is also possible to acquire information on the size of aggregates and the numbers of primary particles per aggregate. In this chapter, a brief introduction into the formation of soot and its characterization is provided, with attention focused mainly on the technique of LII, with some recent LII studies being reviewed. Specific details on the basics of LII and different applications may be found elsewhere [1–5], and in combination with the diagnostics of soot precursors [6]. Detailed information on the different aspects of combustiongenerated carbonaceous particles has been provided by Bockhorn et al. [7, 8].

15.2 Soot Formation

In general, soot is formed during an incomplete chemical conversion of the reactants – that is, when the hydrocarbon fuel and the oxidizer are converted to carbon dioxide and water. This is the normal case in non-premixed or rich premixed flames, where an oversupply of carbon atoms in terms of fuel, compared to the stoichiometric conditions, is present [9]. In real combustion systems soot is typically formed when the ratio between the carbon and oxygen atoms (C/O) is greater than 0.5–0.8 [10].

15.2 Soot Formation

Figure 15.2 Soot formation model.

Soot is commonly understood to be an ensemble of carbon fragments which are predominantly generated in fuel-rich flame regions at high temperatures. A common soot formation model is illustrated in Figure 15.2, where the typical particles thought to participate in the formation process are shown. The particle formation progress can be seen as an equivalent either for the particle size, or for the reaction time. The process starts at the molecular level, where initially the fuel and oxidizer molecules are present and form various intermediate species during their chemical decomposition. The formation of polycyclic aromatic hydrocarbons (PAHs) in fuel-rich regions is often mentioned as being the first step towards soot particles. Starting from simple ring structures, such as benzene and naphthalene, the molecules grow by adding smaller building blocks, such as acetylene. (A comprehensive overview

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concerning different formation mechanisms of PAHs as soot precursors has been provided by McEnally et al. [11]; the process is also discussed in Chapter 16.) The PAHs are basically two-dimensional (2-D) planar structures that act as precursors and which, in the next step, add together to form 3-D objects termed nuclei. The particle size is assumed to be about 2 nm [12]; this is based on X-ray studies that have revealed the crystalline structures to consist of five to ten carbon atom layers, each of which consists of some 100 carbon atoms. Interestingly, in this scenario the soot particles contain a comparatively large fraction of hydrogen, but this is rapidly decreased in line with the reaction time. After forming small nuclei, the different growth mechanisms compete with each other, and this leads to the formation of larger particles. As the soot particles (or rather, the soot nuclei) are further exposed to a hydrocarbon-rich environment at high temperature, the hydrocarbon molecules can react with the nuclei surface to form larger particles; this mechanism is termed “surface growth.” For the sake of completeness it should be noted here that, if oxidizing molecules such as OH radicals or molecular oxygen are present in the surrounding gas, then the carbon atoms at the surface may also be oxidized, such that the particle size is reduced. Coagulation is another mechanism in this context which describes the situation where two particles collide inelastically with each other and stick together, so as to form a single larger particle. As mentioned above, although both mechanisms occur at the same time they exert influences on the soot formation process in different ways. Clearly, the surface growth does not affect the particle number density, but it most certainly manipulates the particle size distribution as well as the soot volume fraction and mass concentration. In contrast, coagulation greatly influences the particle number density and the particle size distribution, without affecting the soot volume fraction and mass concentration. In general, the surface growth of nuclei and small particles leads to spherical particles, as the direction of the growth process is statistical. Coagulation on the other hand results in nonspherical particles, but this nonsphericity can be reduced again by surface growth. Ultimately, this growth mechanism will lead to the creation of so-called “primary particles” with typical sizes of between 5 nm and several tens of nanometers. The primary particles, which are the result of nucleation, surface growth, coagulation and oxidation, may again collide with each other so as to form larger structures, in an aggregation process. These aggregates, in which the primary particles act as building units, may reach a size of several hundreds of nanometers; they are also highly nonspherical, as shown in Figure 15.1. The characterization of aggregate size is difficult, as the aggregates exhibit a complex fractal structure (see Figure 15.1) that does not allow the aggregate size to be expressed by sphere-equivalent geometries. Therefore, the fractal dimension is introduced by [13]: Df ¼

log ðNp =kf Þ log ð2Rg =dp Þ

ð15:1Þ

which contains the number Np and the size dp of the primary particles and the so-called radius of gyration Rg of the aggregate:

15.3 Conventional Soot Diagnostics

sffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi n 1 X Rg ¼
ri2 Np 1

ð15:2Þ

Here, ri is the distance between the center of the single primary particle and the center of the according aggregate [14], and kf is a pre-factor that is influenced by the aggregate-forming process. For aerosols, the fractal dimension is typically around 1.8 [15]. It should be noted that the presence of soot formation in a combustion process does not necessarily mean that particulate matter (PM) is emitted to the environment, as the carbonaceous particles may ultimately be oxidized to carbon monoxide and carbon dioxide.

15.3 Conventional Soot Diagnostics

In order to characterize soot in terms of the characteristic parameters mentioned above, several different methods can be employed, although in general only two approaches are employed, namely probe techniques and optical techniques. A further distinction can be made between those methods that only provide information on the soot volume or mass fraction, and those which can be used to acquire information regarding particle size. A brief overview of some of these techniques is provided in the following sections; details of LII will be provided in Sections 15.4 and 15.5. 15.3.1 Probe Techniques

As probe techniques are usually based on a sample preparation, they do not allow in situ measurements to be made. However, they are still used widely for the characterization of soot and other aerosol particles (for a comprehensive review, see Ref. [16]). Here, the probe techniques will be discussed separately with regards to soot mass concentration and particle size determination. 15.3.1.1 Size-Probing Techniques Transmission electron microscopy (TEM) is today the most common and most accurate method for particle characterization in the field of nanotechnology. For soot diagnostics, TEM is frequently used to investigate primary particle and aggregate size distribution, as well as particle morphology, for example in the structure of soot aggregates [17, 18] (see Figure 15.1). TEM is the broadly accepted reference measurement technique for size and structure determination, in comparison to other techniques. In this procedure, the soot is first deposited on a grid and then imaged using TEM; the resulting images are then analyzed computationally to obtain statistical information. In order to deposit the particles of interest onto the grid, the

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process of thermophoretic sampling is normally used. For this, the grid is moved into the region of interest (e.g., the flame) for a short period of time, usually less than 0.1 s. The extreme temperature gradient that exists between the hot gas in the flame and the cold grid results in a force being applied to the particles such that eventually they are deposited onto the grid. Certain problems may arise from the sampling and probe preparation techniques used, and this may make it necessary to interpret each image individually and to collect information on the basis of a collective of particles which form a statistically closed sample (see, e.g., Ref. [19]). The scanning mobility particle sizer (SMPS) can be used to count particles after classification. Basically, these devices consist of a selection and detection unit. In the first step, particles are selected according to their size using a differential mobility analyzer (DMA) [20]. Then, after sampling, the particles from the probe volume are electrically charged, and the charge per particle is correlated with the particle size. The charged particles then pass a static electric field which causes them to be accelerated in a direction perpendicular to their initial motion, while the position of a slit at the end of the electric field allows the separation of a certain particle size class. In the second step, the selected particles are counted, for example, by a condensation particle counter. This method can be extended to a scanning mobility particle spectrometer [21], in which case the electric field strength is varied systematically as a function of time, such that the particle size distribution can be determined. In general, it should be noted that these methods deliver a mobility diameter – that is, an equivalent diameter to a sphere with the same mobility. Consequently, the comparison of results which mainly reflect the properties of aggregates with data obtained by LII, which provides the primary particle sizes, may lead to erroneous conclusions. This effect has been studied in greater detail for diesel engine exhaust gases [22] and in a laminar premixed flame [23]. Other size measurement techniques, such as impactors [24] and diffusion batteries [25] are not included at this point; however, further details of the different measurement concepts for soot characterization are provided in Chapter 9.

15.3.1.2 Mass Concentration Probing Techniques Gravimetry is frequently used to determine particle mass concentration. In this process, a defined gas volume with an unknown particle load is passed across a filter, onto which the PM is deposited. By weighing the filter before and after sampling, the mass fraction of the aerosol can be calculated from the increase in filter mass and the gas volume. In order to obtain accurate results, conditions of humidity and temperature must be taken into account. To assure comparable and well-defined conditions in the measurement, this technique is employed only in combination with a conditioned constant volume sampling (CVS) or a dilution micro tunnel system [26]. Gravimetric sampling is often used as a type of reference or calibration technique for other methods, which in several countries is fixed by law [27]. Problems may arise when taking into account the highly volatile components of the particulates, which may alternate independently of the particular conditions adjusted [28]. The application of gravimetry is also time-consuming, and offers no possibility for online measurements.

15.3 Conventional Soot Diagnostics

Coulometry is an analytical technique that determines only the EC part of the particulate sampled, in similar fashion to gravimetry. The EC is that part of the carbonaceous particle that can be detected on the filter probe after using extraction and thermal desorption [21]. The measurement parameter is the amount of CO2 which can be collected after oxidation of the carbon material sampled. Coulometry can be considered as an extension of gravimetry. Aethalometry, a standard measurement technique used in engine development, measures the optical absorption of the particles collected onto a filter probe that has been exposed to the engine exhaust gas. This results in a so-called filter smoke number (FSN) [29]. Problems arise at very low particle concentrations, due mainly to the absorbance of other particles present in the exhaust gas as well as soot [30]. One alternative technique that is used (but not described here in detail) is the tapered element oscillating microbalance (TEOM) [31]; this is used to control emissions, often as a standard to determine the respirable dust content in the environment. 15.3.2 Optical Techniques

Optical techniques are based on the interaction between the soot particles and electromagnetic radiation. In this context, both absorption/emission as well as the scattering of light can be used to obtain information regarding the properties of soot. The fundamentals of the procedure are provided in Ref. [32]. In principle, when describing absorption and emission phenomena, soot is usually considered as a black-body according to Planck’s radiation law. With regards to light scattering at particles, the Mie or Rayleigh theory is normally employed, depending on the particle size, although the latter is valid only if the particle diameter is much smaller than the wavelength of the incident light. This assumption is usually fulfilled when, for example, visible or infrared (IR) light interacts with nanoparticles such as soot. In order to account for aggregates, the Rayleigh theory for spherical and isotropic particles can be extended to the Rayleigh–Debye–Gans (RDG) theory, where an arbitrarily shaped particle (e.g., a soot aggregate) is considered as a collective of small subunits, each fulfilling the conditions for Rayleigh scattering. However, influences between the subunits, such as multiple scattering, are commonly neglected [33]. An overview of light-scattering techniques for soot diagnostics has been provided by Charalampopoulos [34]. The thermal radiation from soot particles in flames is frequently used for thermometry purposes, as the emitted spectrum is a strong function of temperature (according to Planck’s law). This approach, termed pyrometry, has been utilized and further developed since the 1930s (e.g., Refs [35, 36]). Although, in general, the method is straightforward and easy to apply, it does have certain drawbacks as a result of it being a line-of-sight technique. Notably, this limits the spatial resolution that can be achieved, whilst other problems involve a lack of knowledge of parameters such as the refractive index and optical properties of the soot particles [37]. The particle size and soot volume fraction can be determined by combining light extinction and light scattering (e.g., see Refs. [38, 39]). Upon irradiating a laser beam

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in the region of interest inside a flame, a part of the laser photons is absorbed or scattered by the soot particles; determination of the initial as well as the transmitted laser intensity then yields the total extinction. In addition, the scattered light is usually detected in a direction perpendicular to the laser beam. The combination of both signals eventually allows the determination of particle size and volume fraction, based on theoretical considerations for absorption and scattering. However, as extinction is a line-of-sight method, the limited spatial resolution may reappear as an issue. An alternative approach for determining the particle size is that of dynamic light scattering (DLS), where the temporal fluctuations of the scattered light from a continuous-wave laser are detected by a photomultiplier tube. Assuming a stable and constant laser intensity, the fluctuations are caused by the Brownian motion of the particles, which in turn is dependent on their size. Further details of this technique are available in Ref. [40].

15.4 Laser-Induced Incandescence

Soot characterization by laser heating was first proposed in 1984 by Melton [41] and by Dasch [42, 43]. The basic measurements of soot concentrations were carried out during the early and mid-1990s [44–48], while the primary particle size was determined in 1995 [49, 50]; this led ultimately to the introduction of time-resolved laser-induced incandescence (TIRE-LII). In recent years, the technique has been further developed for particle characterization in technically important systems (see, e.g., Refs. [2, 5]). The directly accessible parameters are the volume concentration and the primary particle diameter. Meanwhile, TIRE-LII has been extended to evaluate also the size distribution of particles [51, 52]. In combination with light-scattering measurements, the volume equivalent aggregate particle size and number of primary particles per aggregate can also be determined [53]. Details on the application of this technique are available in Refs. [1, 2, 5, 6], while the state of the art in modeling the LII process is described in some detail in Refs. [3, 4, 54]. A compilation of several LII related reports was published 2006 in a special feature issue of Applied Physics B (Vol. 83, Issue 3). 15.4.1 Fundamental Aspects of LII

The basic principle of LII is the rapid heating of nanoparticles up to their sublimation temperature, within a few nanoseconds, by irradiation with a short, intense laser pulse; the enhanced thermal radiation is then detected and evaluated. A scheme of the different processes occurring during a LII measurement is illustrated in Figure 15.3. Initially, the particles are heated by their absorbing the laser radiation, which results in an increase in the internal energy. In the case of carbonaceous particles, the maximum particle temperatures reached are in excess of 4000 K for

15.4 Laser-Induced Incandescence

Figure 15.3 Schematic of the laser-induced incandescence (LII) process.

a short time period of several nanoseconds. The subsequent heat loss is dominated by different mechanisms, mainly sublimation and heat conduction. The contribution of the thermal radiation to the energy loss is small for all times. By setting up the energy balance for one single particle, including the mass change with time, the resulting differential equation yields: Cabs
Ei LðT T0 Þpdp2 þ

DHS dm pdp2

dt M

ð

eðdp ; lÞ
Mlb ðT; lÞdl

pdp3 6

rcp

dT ¼0 dt ð15:3Þ

The differential equation includes the laser absorption in the Rayleigh-Regime (absorption efficiency Cabs, laser energy Ei), heat conduction (Knudsen numberdependent heat transfer coefficient L, particle temperature T, temperature T0 of the surrounding gas), sublimation (sublimation enthalpy DHV, molar mass M) and radiation (emission coefficient e, spectral energy density Mlb, wavelength l), as well as the change in the internal energy (mass density r, specific heat cP). Thereby, the equation assumes only spherical primary particles (diameter dp), which have only point contact to other particles inside the aggregates, and therefore any heat conduction between particles can be neglected. By solving Equation 15.3, the temporally resolved particle temperature can be determined. Then, by applying Planck’s radiation law, the detectable signal can be found as function of time (see Ref. [1]). Accurate modeling is only possible when the wavelength-dependent optical and temperature-dependent thermodynamic parameters are considered, and the correct thermal accommodation coefficient is applied (this quantity is dependent on the ambient particle conditions, and is described in detail in Refs. [3, 55, 56]). A more general form of the energy equation, including more-detailed mass transfer processes, has been derived by Hiers [57]. Nevertheless, for practical use in most cases Equation 15.3 will provide sufficient physical detail.

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One important attribute of LII is the nonlinear behavior of the maximum peak signal with the excitation laser energy. An initial increase in laser fluence leads to a rapid rise in the peak LII signal, whereby it levels off to a so-called “plateau” region at a laser fluence of about 0.2 J cm 2 for a laser wavelength of 532 nm, from which no significant signal change is evident [58, 59]. For technical applications, this “plateau” region is of advantage, as changes in the laser fluence do not affect the signal behavior. The application of higher laser fluences may induce morphological changes that might cause the particle properties to be modified [60]. Under the assumption of sufficiently high laser excitation energies, the heat loss at peak particle temperature is dominated by sublimation. Hence, the maximal signal is proportional to the particle volume: SLII / dp3 þ ð154nm=lÞ

ð15:4Þ

by using long detection wavelengths l [41, 49, 61]. If quantitative data for the mass concentration are required, then it is necessary to perform an appropriate calibration, although this can be easily achieved by a single line-of-sight extinction measurement [53, 62, 63]. Even more flexibility of LII can optionally be achieved if it is combined with elastic light scattering [53], and in this way the aggregate size is also accessible. This is, more precisely, an optically equivalent diameter of the aggregates (radius of gyration, see Equation 15.2), which correlates with the widely determined diffusion diameter of the particles. In this context it should be pointed out that elastic light scattering, in contrast to LII, is not selective towards the desired fraction of the particles. Since other particle components (e.g., volatiles) may also contribute to the scattered signal, an appropriate sample conditioning is required for performing combined scattering/ LII experiments. 15.4.2 Primary Particle Size and Size Distribution

When the LII signal is considered at a later stage, after the laser pulse, then heat conduction becomes the dominant heat loss mechanism [49]. For this reason, particles of different sizes cool at different rates, according to their specific surface areas. This is shown schematically in Figure 15.4 for three different monodispersed spherical particle diameters. The local gas temperature adjacent to the particles turns out to be the most critical parameter for the accuracy of size determination [58], which however, can be derived from the temperatures of the soot particles themselves [64]. For the evaluation of the LII signal and the derivation of the decay time, two strategies exist. First, the entire temporal LII signal decay can be detected by using a fast photomultiplier tube; however, this procedure only allows the acquisition of pointwise information, although this is not a drawback in systems where the spatially distributed particles owe the same attributes. Second, two-dimensionally resolved measurements can be performed that will provide information over an extended part of the combustion field simultaneously. For this purpose, intensified CCD cameras

15.4 Laser-Induced Incandescence

Figure 15.4 Calculated laser-induced incandescence (LII) signals for monodisperse soot particles of three different diameters.

with short gating times are used. Since there exists a minimum temporal interval between two recordings of a CCD camera, it is only possible to detect the LII signal at certain times after the laser pulse. From the ratio of the signals at different times, the signal decay time can be calculated and processed for each pixel as for the pointwise case. As a combination or compromise between both strategies, LII signals along a one-dimensional line can be detected temporally resolved by using a streak-camera. In most applications reported in the literature the time-resolved LII (TIRE-LII) signals were detected with a fast photomultiplier tube, which guarantees a good signal-to-noise ratio (SNR). For times after the laser pulse when heat conduction is the dominant process for energy release from the particles, the LII signal decay of a monodisperse class of particles is almost a single exponential. As a first approach, it is reasonable to evaluate the mean primary particle size of this monodisperse particle collective. For this, from the experimental LII signal curve a signal decay time t is determined by an exponential fit in a time interval in which heat conduction dominates particle cooling. This time is then compared to a numerically calculated signal decay time (based on the modeling of the power balance), taking into account the surrounding gas temperature T0 and assuming a monodisperse particle size distribution with diameter dP,mon. This means that the simultaneous determination of the ambient gas temperature is necessary and, moreover, that dP,mono is shifted slightly towards larger particles, compared to the medium size dP,med of the real particle size distribution which is more polydisperse in nature, because the LII signal scales nearly with dP3. Thus, TIRE-LII yields this mean primary particle diameter dp,mono without further calibration by comparison of the experimental signal behavior with theoretical predictions, as the signal decay can be evaluated independently of the total signal strength.

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Figure 15.5 Comparison of the LII-measured primary carbon black particle sizes with transmission electron microscopy results [65].

The accuracy of the technique has been tested with carbon black particles of known size (see Figure 15.5), and good agreement was observed for the studied size range between 10 and 95 nm [65]. Two of the carbon blacks with the same primary particle size of 25 nm, but with a different aggregate size formed by a different number of primary particles, were studied in this investigation. As the LII measured primary particle size was the same for both aggregates, an influence of the aggregate size on the LII results could be excluded, which was true for aggregates with fractal dimensions between 1.5 and 1.9 normally given for combustion-generated soot. A slightly different approach has been introduced which is based on the simultaneous detection of the TIRE-LII signal at two different wavelengths (two-colorLII) [66, 67]. By applying Planck’s law, the particle ensemble temperature can be calculated from the measured ratio of the TIRE-LII signals at the two wavelengths selected. The major advantage of this technique is that the particle temperatures are experimentally determined independent of the laser absorption process during the laser pulse which enters most of the models used for simulating the LII signals. The approach to evaluate the mean primary particle size of a monodisperse particle collective is sufficient if the size distribution is narrow, which is typically not always the case in technical systems. An optional extension of the mean primary particle size determination yields its distribution function. In principle, the time-resolved LII signal contains the information of the particle size distribution as the superposition of several monodisperse signal curves gives, in contrast to monodispersal decay functions, a total signal with a non-single-exponential shape. Any arbitrary distribution function can be recovered by employing an inverted Laplace algorithm. As this is a very time-consuming issue, and is also very sensitive to statistical errors and noise on the signal course, a more robust method must be chosen. One favorable way assumes the presence of any fixed distribution function, which is given by its median diameter and its distribution width. In this case, the shape of the distribution function is assumed to be well characterized by these two parameters. A broadly

15.5 LII Applications

used and well-justified assumption for this distribution is given by a logarithmic normal function, 1 Pðdp Þ ¼ pffiffiffiffiffi
exp 2p
dp
s

ðlnðdp Þ lnðdp;med ÞÞ2 2s2

!

ð15:5Þ

which is typical for combustion processes [52, 68]. Here, dp,med denotes the count median diameter and s ¼ ln(sg) is the width, sg being the geometric standard deviation. Based on this assumption, higher moments of the particle size distributions can be determined. Different approaches exist to solve this problem, for example, by fitting a calculated signal course to the whole experimental signal decay under variation of different distribution parameters, such as the width or the mean primary particle diameter [69] or by using an inversion algorithm [50]. One major drawback of both methods is the relatively high computing effort for the evaluation, which makes the application for online measurements questionable. Alternatively, a simple online approach has been developed that relies on the fact that the ratio of the contribution to the LII signal of different size classes changes with time after the induced laser pulse, as shown in Figure 15.4. Smaller particles cool down faster, and therefore a broad size distribution leads to a deceleration of the signal decay as the longlasting signal of bigger particles become more important at later times. Smaller particles show a faster signal decay, and have therefore a constantly decreasing influence on the total signal of the particle collective. This results in a deviation from an exponential decay; that is, the signal decay time increases with time. For the reconstruction of the size distribution the theoretical signal course of a particle collective is calculated directly by a weighted summation of LII signals from monodisperse size classes, which are computed from the numerical solution of the power balance [52]. The count median particle diameter dp,med, the distribution width s and the ambient temperature T0 are the input parameters for this calculation. The fitting of this theoretical signal of a size-distributed particle ensemble in two different time intervals after the laser pulse provides two characteristic signal decay times which, in comparison with precalculated decay times, can provide information on the count median diameter and the geometric standard deviation of the particle collective when the ambient temperature is known (for details see Refs. [5, 52]). One possible problem here may be the influence of aggregate size on the signal decay, when primary particles are packed together to dense structures, as this greatly affects the particle cooling [68]. This is typically not the case for aggregates with a fractal dimension between 1.5 and 1.9; therefore, in general no shielding effects are considered inside the aggregates.

15.5 LII Applications

Recently, LII has been employed in studies of the fundamental aspects of soot growth and oxidation, in both premixed and non-premixed flames, and also for the

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characterization and control of soot formation in several practical combustion systems. Whilst a comprehensive summary of this would be beyond the scope of this chapter, several overviews have been provided detailing flame studies and also technical applications [1–6]. Hence, in the following sections only a brief overview is provided of the different applications of the LII technique. 15.5.1 Flame Measurements

Fundamental investigations of soot growth and oxidation have been conducted by many research groups in both diffusion and premixed flames, with ethene and methane as fuels (see, e.g., Refs. [1, 3] and the references therein). When using TIRE-LII in flame measurements (see for example, Figure 6 in Ref. [53]) for particle size evaluation, the flame temperatures were determined using emission spectroscopy or coherent anti-stokes Raman scattering (CARS) thermometry, depending on the maximum soot concentration. Typical temperatures are in the range of 1800 K in the middle of the flames, and up to 2100 K in the outer regions, where the reactions take place. In the different flames investigated, the measured concentrations covered a range from 1  10 7 to 6  10 6 m 3, while the primary particle sizes ranged from 2 to 60 nm. Higher soot concentrations and larger particles were measured in the ethene diffusion flame; the resulting maximum number concentration of primary particles, however, was about one magnitude larger in the premixed methane flame. Examples of the distributions of the different soot quantities are shown for the ethene flame in Figure 15.6. An annular structure in the soot volume concentration was observed, with maximum values in the outer regions. The concentration decreased in the upper part of the flame, where the mean primary particle sizes also decreased due to the increasing oxidation of the soot. For the detailed investigation of soot formation, besides information on soot (primary particle size and concentration) accessible by LII additional information on local gas temperature and the local concentrations of major flame species as fuel components, air and combustion products and of radicals and intermediate species must be provided. This has been carried out in a non-premixed, bluff-body-stabilized methane flame using LII along with polarization-resolved linear Raman scattering (major species), pure rotational CARS (gas temperature) and laser-induced fluorescence (minor species) [69]. Besides traditional TIRE-LII, two-color-LII has become very popular in recent years, and applications have been reported also for fundamental flame diagnostics [70–73]. 15.5.2 Technical Applications

Besides a few more exotic applications, for example, the investigation of carbon nanotubes [74], soot particles suspended in liquids [75] or ambient air studies [5],

15.5 LII Applications

Figure 15.6 Characteristic properties of soot in a laminar non-premixed methane flame [53].

LII has mainly been applied to two different groups of technical processes, namely carbon black production and engine research. Compared to flame measurements, TIRE-LII is applied only seldom to practical combustion systems, due mainly to the special process conditions that must be met for a reliable execution of the measurements, and of the technical process under consideration. Due to the early stage of development of TIRE-LII for such technical realizations, in order to achieve a successful implementation of this technique into the process, a well-defined collaboration project with the tentative user must be executed, but this may not only be time-consuming but also require additional financial resources. One such project was the production of carbon blacks in

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a furnace black reactor, where a non-premixed fuel-rich flame is quenched by a water jet at an appropriately selected time and downstream location. TIRE-LII has been used successfully to control this process, and to provide immediate information on the quality of the carbon blacks produced [5, 76]. Another application during the early stages of LII (see Refs. [44, 77]) was to investigate soot formation and oxidation under engine-like conditions, or directly inside the combustion bowl of internal combustion (IC) engines, followed by the characterization of emitted soot in the exhaust line of IC engines. The early in-cylinder measurements in diesel engines by Dec et al. [44, 77] andPinson et al. [78, 79] relied on considerable modifications of the engine. However, some years later, investigations were conducted inside the research engines, although these were close to series production engines and were driven by standard diesel fuels [80]. Although, inside the combustion bowl of the engine, only qualitative information on the soot mass concentration or particle sizing is provided (see, e.g., Refs. [81–84]), different approaches for a quantification have more recently been developed [84, 85]. LII measurements within the engine exhaust line were initially reported by Hofeld [86, 87], since then tremendous progress has been made. Today, quantitative measurements on the soot mass concentration may be conducted, while primary particle sizes in the size range of 3 to 100 nm are monitored (see, Refs [88–95]), providing extreme sensitivity down to 3 mg m 3 and with a time resolution up to 20 Hz [5, 94]. The current commercially available LII sensors represent the results of these developments. Today, LII exhaust gas measurements are used to optimize engine operation by adjusting the injection parameters [96], as well as to characterize the performance of exhaust gas after-treatment devices, such as catalysts or particulate trap filters [94].

15.6 Summary and Outlook

The investigation of soot formation has been the subject of intense research in recent years, and has provided much new information, including details of “gas-to-particle” reactions in hydrocarbon combustion, or the reaction paths of precursors. Whilst many details of these processes remain only partly understood, the treatment of this newly acquired knowledge, and of the open questions, remains – unfortunately – beyond the scope of this chapter. However, the state of the art is described in some detail in Ref. [8]. The same is, in principle, true for LII and its current potential as a reliable measurement tool. Today’s LII community is very active and, in pooling their knowledge, has introduced the International Discussion Meeting and Workshop on LII (www.liiscience.org); this was established in 2005 and now takes the form of a biannual meeting which includes, along with oral presentations, a series of open discussions on modeling approaches, experimental best practice and standards, LII applications and comparisons of experimental and modeled data. These activities contribute to the general understanding of LII from a fundamental viewpoint, and

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Leipertz, A., and Hemm, A. (2000) Application of a new soot sensor for exhaust emission control based on timeresolved laser-induced incandescence (TIRE-LII). SAE Technical Paper No. 2000-01-2864. Smallwood, G.J., Snelling, D.R., G€ ulder, Ö.L., Clavel, D., Gareau, D., Sawchuk, R.A., and Graham, L. (2001) Transient particulate matter measurements from the exhaust of a Diesel injection spark-ignition automobile. SAE Technical Paper No. 2001-01-3581. Axelsson, B. and Witze, P.O. (2001) Qualitative laser-induced incandescence measurements of particulate emissions during transient operation of a TDI Diesel engine. SAE Technical Paper No. 2001-01-3574. Schraml, S., Kremer, H., Sommer, R., and Leipertz, A. (2004) LI2SA: Instrumentation for soot characterization and optimization of ultra-low emission vehicles. Proceedings of the 8th International Symposium on Diagnostics and Modelling of Combustion in Internal Combustion Engines, Yokohama, Japan, pp. 335–342. Witze, P.O., Shimpi, S., Durrett, R., and Farrell, L. (2005) Time-resolved laserinduced incandescence measurements for the EPA heavy-duty federal test procedure. J. Soc. Mech. Eng. Int. J. Ser. B, 48, 632–638. Schmid, M. and Leipertz, A. (2006) An approach for the control of combustion and pollutant formation in diesel engines by combined in-cylinder and exhaust gas measurements. Int. J. Vehicle Des., 41, 188–205. Eremin, A., Gurentsov, E., and Schulz, C. (2008) Influence of the bath gas on the condensation of supersaturated iron atom vapour at room temperature. J. Phys. D, 41, 055203. Maffi, S., Cignioli, F., Bellomunno, C., De Iuliis, S., and Zizak, G. (2008) Spectral effects in laser induced incandescence application to flame-made titania nanoparticles. Spectrochim. Acta B, 63, 202–209.

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16 Polycyclic Aromatic Hydrocarbons and Combustion John Fetzer 16.1 Introduction

The polycyclic aromatic hydrocarbons (PAHs) are a class of organic compounds defined as those that consist only of carbon and hydrogen atoms in fused aromatic rings [1]. There are several subclasses within this broad category of PAHs. The first and most commonly utilized class is the number of rings; however, this is not a simple arrangement because other factors create confusion in numbering. Although other ring sizes may be made in the laboratory, only those with six carbons or five carbons are found commonly in combustion products. The PAHs of only six-carbon rings are known as “alternant” PAHs, while those with some fivecarbon rings are known as “nonalternant” PAHs. The simple PAH isomer pair of pyrene and fluoranthene illustrate this difference; pyrene is alternant, while fluoranthene is nonalternant. (Some of these structures are shown in Figure 16.1, which shows the 16 PAHs targeted as priority pollutants.) The PAHs are aromatic – that is, their p electrons are not located in only one carbon–carbon bond (as in an alkene, or colloquially also called an olefin); rather, the p electrons move throughout the carbon skeleton, and are shared among the bonds. This situation, which is known as “resonance,” gives PAHs an increased stability. Alternant PAHs are fully resonant. The five-carbon ring in a nonalternant PAH is not as effective in electron resonance, so nonalternant PAHs are less stable than alternant PAHs of similar formula (PAHs with the same number of carbon and hydrogen atoms are known as isomers). Within both classes there are the subdivisions or ortho-fused and peri-fused. Ortho-fused PAHs have rings attached to each other only through one face, sharing only a single carbon–carbon bond, whereas peri-fused PAHs have ring connections to two or more faces. By convention, if a PAH structure has a peri-fused part, it is classified as peri-fused even though it may also have rings that are ortho-fused.

Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright Ó 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

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Napthalene

Acenaphthene Acenaphthylene

Phenanthene

Anthracene

Blenz[a]anthracene

Benzo[b]fluoranthene

Benzo[ghl]perylene

Fluence

Fluoranthene

Chrysene

Benzo[a]pyrene

Pyrene

Benzo[b]fluoranthene

Diebenz[ab]anthracene

Indeno[1,2,3,ed]pyrene

Figure 16.1 The 16 polycyclic aromatic hydrocarbons on the US EPA priority-pollutant list.

This degree of condensation leads to the most confusing aspect of counting rings as a classification of PAHs. Pyrene, C16H10, obviously has four rings, but so do the isomers of C18H12, naphthacene, benzo[c]phenanthrene, chrysene, and benz[a] anthracene. The confusion grows even greater for higher numbers of rings where the structures are ortho-fused, peri-fused, and some are mixtures of the two. Isomerism is a key principle in the study of PAHs. The arrangement of rings influences the arrangement of the p electrons and this, in turn, defines a diverse range of individual PAH properties, from coloration to impact on health. Why this is so will be described in the next section. PAHs have literally been found throughout every part of the planet Earth, from the depths of the oceans to the high reaches of the atmosphere. They even have been found in meteorites, comets, extraterrestrial atmospheres, and in interstellar space.

16.3 Analytical Approaches for PAHs in Combustion Processes and Products

16.2 Properties of PAHs

The arrangement of p electrons in a PAH structure determines its UV and fluorescence spectra. PAH spectra are characteristic in containing many spectral features; this is in contrast to most other types of molecules, which often have only one broad, featureless UV spectrum and do not fluoresce. PAH spectra are also very intense, so that small amounts can be readily seen. By having differing arrangements of p electrons, isomers have very different UV and fluorescence spectra; these spectra can, therefore, be easily used to identify specific PAHs.

16.3 Analytical Approaches for PAHs in Combustion Processes and Products

The complexity of most combustion-related samples and the diversity of PAHs limits which types of instrumentation and methodologies can be used for PAH analyses. Without some separation, few approaches can provide any details of composition, except on rare occasions for a few specific PAHs [2]. The separations used for PAHs can be divided into two categories: (i) fractionations and cleanups used for sample preparation; and (ii) chromatographic methods used for the analysis of individual compounds. Sample preparation involves dividing the original sample into parts. Each part either is an enriched fraction with the PAHs in higher concentrations, or the fractions are depleted of PAHs and enriched in other types of compound that would make the PAH analysis difficult. Fractionations include adsorption chromatography on silica gel, alumina, and activated carbon. In addition to a PAH-containing fraction, there often is a less-polar fraction that contains the aliphatic hydrocarbons and nonaromatic sulfur compounds and a more-polar fraction (or fractions) of the many nitrogen- and oxygen-containing molecules. Normal-phase liquid chromatography is a more precise approach than adsorption chromatography, and can be used to fractionate PAHs by the ring number. It relies on the interaction between the p electrons of the PAHs and the bonded phase. Common bonded phases for this include nitro-, amino-, phenyl-, and cyano- (nitrile) phases. The retention is increased according to the number of p bonds, so that even among four-ring PAHs, pyrene will elute before chrysene or benz[a]anthracene. For smaller PAHs, gas chromatography (GC) can be used because the compounds are volatile. However, for PAHs greater than five rings the volatility is decreased and so liquid chromatography becomes the preferred option. Gas chromatography is most often used with mass spectrometry (MS) detection. However, the combination of GC-MS is adequate for smaller PAHs for another reason. The separating power of GC is sufficient generally to separate the isomers of lower molecular weight; however, as the molecular weight increases the GC separating power becomes a limitation, because commercial GC columns have little selectivity for PAH isomers. Yet, the MS cannot differentiate between them, and will

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provide only the molecular weight of each peak. Historically, GC-MS has been the most widely used technique, mainly because of the attention focused on smaller PAHs with regards to environmental regulations. For PAHs of six or more rings, MS detection is not useful other than to provide the molecular weight of each individual GC peak. The molecular weight can easily be translated in a chemical formula; for example 276 means a PAH of C22H10. However, this is not useful in itself because a set of isomers will all have the same molecular weight, and this is a dramatic limitation as the ring number increases. For example, in the case of PAHs of molecular weight 302, C24H14, there are 34 possible PAH isomers; clearly, MS identification would not be of much help in this situation! In one PAH class (known as the ace, pronounced “ay-sa” or cyclopenta class), the molecules have a peripheral five-member ring containing a double bond, and are often formed through the addition of C2H2 to the PAH structure. This additional ring is not involved in p-electron resonance, and often these PAHs do not show fluorescence, unlike most other classes of PAHs. One commonly regulated PAH, which appears as an example on the US Environmental Protection Agency list of priority pollutants, is acenaphthylene; other lists include cyclopenta[cd]pyrene. In order to overcome this limitation, alternative approaches are used that rely on high-performance liquid chromatography (HPLC) with UV detection. For the larger PAHs, the fact that each individual isomer has a distinct UV (and fluorescence) spectrum represents the solution to the problem. HPLC, in combination with a fullspectrum UV detector, can be used to identify individual isomers [3]. These spectra have even been used to identify PAH isomers that were previously unknown, because the patterns in the PAH UV spectra follow trends based on the arrangements of the rings [4, 5]. One such example is shown in Figure 16.2, where the top and bottom spectra belonged to known compounds. The UV spectra of a pair of very similarly structured PAHs are shown in Figure 16.3. UV spectral detection is especially powerful when the eluent is then passed to a mass spectrometer to provide the empirical formula for each UV spectrum. The specifically prepared HPLC columns used for PAH analyses are invariably based on the common octadecyl (C18) bonded phase, and their special preparation makes them dissimilar to most C18 commercial columns. These PAH columns have a great ability to separate molecules by their shapes, and this results in the separation of PAHs simultaneously by both carbon number and isomer shape. An isomer set results in a cluster of separated peaks in a time range which is different from that for other isomer sets. With HPLC, the method of detection has one major advantage over that used in GC, in that UV methods are possible. Each PAH has, by definition, a specific arrangement of its rings: the number of rings; which are five-carbon and which sixcarbon rings; and how the rings are joined. But this also means that the arrangement of p electrons is discrete and individual, which in turn determines the UVabsorbance spectrum of a PAH. HPLC can be used for PAHs of 12 or more rings, whereas GC is usually limited to approximately seven rings; however, this range can be further extended and

16.4 Formation, Variation, and Occurrence of PAHs

Figure 16.2 UV spectra comparison of two known PAHs (top and bottom spectra) with a newly synthesized PAH (middle spectrum). The vertical axes have been normalized for this comparison.

improved by the choice of HPLC mobile phase. GC is also limited by the operating temperature and the thermal stability of the columns used. For smaller PAHs, mobiles phases using water and acetonitrile or methanol are commonly used, but for larger PAHs (more than six rings) solvents such as ethyl acetate, dichloromethane, chlorobenzene, and toluene have been used.

16.4 Formation, Variation, and Occurrence of PAHs 16.4.1 Formation

PAH formation is dominated by two factors – the thermodynamic stabilities and the kinetic mechanisms. Both of these are important, however, and the final distribution

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Figure 16.3 The UV absorbance spectra of two dinaphthocoronene isomers. The units of the y-axis are milliabsorbance units (mAU).

of PAHs in a combustion product usually is produced by pathways that involve both mechanisms. By sharing its p electrons throughout the carbon skeleton, a PAH gains thermodynamic stability; moreover, the more widespread and uniform the sharing, the greater the gain in stability. Such stability gain through p electron sharing is known as resonance. These resonance stabilities can be determined theoretically by computations, and the appropriate values may be obtained in tabular form in a variety of literature sources. In brief, isomers with more compact structures are generally more stable. Likewise, structures with fewer hydrogen atoms for the same number of carbon atoms are also more stable, and therefore triphenylene is much more stable than its isomer naphthacene. A PAH of formula C28H14, such as benzo[a]coronene, would be

16.4 Formation, Variation, and Occurrence of PAHs

more stable than one of formula C28H16, such as benzo[a,n]perylene, which is in turn more stable than one of formula C28H18, such as dibenzo[a,l]pentacene. Kinetic pathways are those series of reactions that produce PAHs. The specific mechanisms may depend both on the starting reactants and the favorability of specific reactions due to thermodynamics or steric effects. Although PAHs are generally produced in a series of reactions that build up larger PAHs, one ring at a time, some reactions occur in a more “leapfrog” fashion. The simplest example of this is the condensation of two naphthalene molecules to form perylene or benzo[ j] fluoranthene or benzo[k]fluoranthene. On occasion, a starting reactant will have two or more possible routes with different product PAHs, and generally when this is the case the product isomer with the more thermodynamic stability will be preferred and be seen in greater amounts. However, this does not mean that it is the sole product – only that its proportion compared to the other isomer is greater. The proportion of each isomer often is similar to the proportion of the stabilities as measured by the heats of formation. The PAHformation pathway of greatest stability is shown in Figure 16.4 [1]. 16.4.2 Variation in PAHs Due to Combustion Source

PAHs are produced at some level in every type of combustion, except for those where only water, carbon dioxide, and other small permanent gases are the products. PAHs are the precursors to soot and similar carbonaceous deposits, and their production depends on both thermodynamic stability and on the kinetics of the reaction pathways to a particular structure. These, in turn, depend on the heat in the combustion zone and the residence time. 16.4.3 Conventional Combustion of Plant Matter

Wood and peat are still commonly used fuels for home heating. The burning of plant matter in grassland or forest fires also produces similar PAHs. In some parts of the world, slash-and-burn agriculture is common, whereby fire is used either to clear the land for planting or to remove the remnants of certain crops, such as grass, wheat, or rice stubble, or the leaves and other remains from sugar cane, sorghum, and corn. As the combustion temperature is lower and the residence time shorter than with most other fuel types, the PAHs produced are smaller, with usually five rings or fewer [2]. 16.4.4 Motor Vehicles

Gasoline- (petrol) and diesel-fueled engines have a much higher combustion temperature than is encountered in the conventional burning of plant material, and this results in a greater production of nonalternant PAHs, such as fluoranthene. Although there are differences in the relative proportions of individual PAHs found

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Figure 16.4 The pathway leading to the most thermodynamically favored peri-fused PAHs.

in gasoline and diesel emissions, the variety of PAHs is similar. Almost every possible condensed alternant and nonalternant structure is found [6, 7]; for example, of the 33 possible C24H14 isomers, all are found in diesel exhaust particulate mater [8]. Diesel engines do produce nitro-substituted PAHs, a class of compounds which is not seen in many other combustion products, and which may be indicative of motor vehicle sources [9]. 16.4.5 Fuel Oil and Coal Burning

Fuel oil and coal burn less efficiently than natural gas when used to heat homes or power industrial plants. In this situation, the soot is usually required to be scrubbed

16.5 Controlled Pyrolysis as a Means to Study Combustion

or trapped in order to reduce its emission, though some nations have less strict regulations than others. Coal tar, which is the product of pyrolysis of bituminous coal, contains a very complex mixture of PAHs [10–14]. The combustion of anthracite coal produces more PAHs, and these have more rings than bituminous coal burned under similar conditions [15]. In contrast, brown (lignite) coal additionally had numerous “ace” (fused cyclopenta) PAHs structures [16]. 16.5 Controlled Pyrolysis as a Means to Study Combustion

The mechanisms of PAH formation are impossible to study in the true-world situation, and therefore carefully conducted studies using simpler, controlled

Figure 16.5 HPLC chromatogram of products of catechol pyrolysis (1000
C and 0.3 s) eluting from 40 to 75 min in the solvent program of the HPLC/UV. The rise in the baseline at 63 min corresponds to a change in HPLC mobile phase composition to UV-absorbing dichloromethane. Shown in light grey, the identified C24H14 PAH product components, in order of elution from left to right, are: naphtho [1,2-e]pyrene, naphtho[1,2-b]fluoranthene, naphtho[2,3-e]pyrene, naphtho[1,2-a]pyrene eluting with dibenzo[a,e]pyrene, naphtho[1,2-k] fluoranthene, benzo[b]perylene, dibenzo[e,l] pyrene, dibenzo[b,k]fluoranthene, naphtho[2,3b]fluoranthene, naphtho[2,1-a]pyrene, dibenzo [a,i]pyrene, naphtho[2,3-a]pyrene, naphtho[2,3k]fluoranthene, and dibenzo[a,h]pyrene. Three of these C24H14 PAHs – naphtho[2,1-a]pyrene, dibenzo[a,i]pyrene, and naphtho[2,3-a]pyrene –

have been identified in a previous catechol pyrolysis study in this series. Shown in black, the PAH product components whose identifications are demonstrated elsewhere, in order of elution from left to right, are: benzo[a] pyrene, naphthacene, dibenz[a,j]anthracene, pentaphene, dibenz[a,h]anthracene, 4H-benzo [def ]cyclopenta[mno]chrysene, benzo[ghi] perylene, indeno[1,2,3-cd]pyrene, dibenzo[a,h] fluorene, indeno[1,2,3-cd]fluoranthene, benzo [b]chrysene, 1H-benzo[ghi]cyclopenta[pqr] perylene eluting with benzo[b]perylene, anthanthrene, picene, benzo[ghi]cyclopenta[cd] perylene, 8H-dibenzo[a,jk]pyrene, coronene, dibenzo[b,ghi]perylene, 1-methylcoronene, phenanthro[2,3-a]pyrene, dibenzo[e,ghi] perylene, cyclopenta[bc]coronene, and naphtho [8,1,2-bcd]perylene.

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conditions are useful. An example of this is provided by the combined research efforts of Prof. M. J. Wornat and colleagues, formerly of Princeton University and of Louisiana State University [17–22]. Since combustion fuels are usually complex mixtures, the first step in simplification is to combust individual compounds and to observe the resultant PAHs, such that a comparison can be obtained of the different conditions required for each fuel. When a variety of fuels is compared, the thermodynamic and kinetic factors emerge.

Figure 16.6 Reversed-phase HPLC chromatogram of products of 1-methylnaphthalene pyrolyzed at 585
C, 110 atm, and 140 s. The rise in baseline at 63 min corresponds to a change in mobile phase composition to UV-absorbing dichloromethane. Identified products are listed by class, in order of elution. Classes 1 and 2 (in black): naphthalene; 1-methylnaphthalene; 2-methylnaphthalene; 1,8dimethylnaphthalene; 1-ethylnaphthalene; 1,2-dimethylnaphthalene; 1,4- and 1,5-dimethylnaphthalene; 1,3- and 1,7-dimethylnaphthalene; 2,3-dimethylnaphthalene; 1,6-dimethylnaphthalene; 2,6dimethylnaphthalene; 2,7dimethylnaphthalene; trimethylnaphthalene;

1,10 -bi-naphthyls; 1,20 -bi-naphthyls; 2,20 -binaphthyls. Class 3 (blue): benzo[j]fluoranthene; perylene; benzo[k]fluoranthene; methylbenzo[k] fluoranthene; methylbenzo[j]fluoranthene. Class 4 (green): dibenzo[a,i]fluorene; dibenzo [a,g]fluorene; methyldibenzo[a,i]fluorene; methyl-dibenzo[a,i]fluorene; methyldibenzo [a,h]fluorene; methyldibenzo[a,g]fluorene; methyldibenzo-[a,i]fluorene; dibenzo[a,h] fluorene; methyldibenzo[a,h]fluorene. Class 5 (red): benzo[c]-chrysene; dibenz[a,j] anthracene; dibenz[a,h]anthracene; picene. Class 6 (black): naphtho[2,1-a]pyrene; methylnaphtho[2,1-a]pyrene; naphtho[2,3-a] pyrene; methylnaphtho[2,1-a]pyrene; methylnaphtho[2,1-a]pyrene; and dibenzo [cd,lm]perylene. Data are taken from Ref. [18] and Ref. [17].

16.5 Controlled Pyrolysis as a Means to Study Combustion

Figure 16.7 UV absorbance spectra of the reference standard of naphtho[2,3-a]pyrene (dashed line) and of a catechol pyrolysis product component (solid line) eluting at 72.1 min in Figure 16.5.

Such as approach is far from straightforward, not only in terms of the final comparisons but also in the initial data gathering. As noted above, PAH mixtures can be complex, with many similar isomers occurring; hence the differentiation of each structure must be carried out in order to assess the reaction pathways and preferences. Yet, modern chemical analytical methods can be used to achieve this relatively

Figure 16.8 UV absorbance spectra of the reference standard of dibenzo[a,h]pyrene (dashed line) and of a catechol pyrolysis product component (solid line) eluting at 74.5 min in Figure 16.5.

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Figure 16.9 UV absorbance spectra of the reference standard of naphtho[2,1-a]pyrene (dashed line) and of a catechol pyrolysis product component (solid line) eluting at 64.2 min in Figure 16.5.

easily, with Prof. Wornat’s group employing one of the more powerful combinations, namely HPLC-UV-MS. This, as described above, allows for numerous specific PAHs to be identified quantitatively. Two example chromatograms from these studies are shown in Figures 16.5 and 16.6, while Figures 16.7–16.10 show examples of the comparisons of UV spectra used for identification [22].

Figure 16.10 UV absorbance spectra of the reference standard of dibenzo[a,i]pyrene (dashed line) and of a catechol pyrolysis product component (solid line) eluting at 70.5 min in Figure 16.5.

References

References 1 Fetzer, J.C. (2000) The Chemistry and

2

3

4

5

6

7

8

9

10

11

Analysis of the Large Polycyclic Aromatic Hydrocarbons, John Wiley & Sons, New York, ISBN 0-471-36354-5. Fetzer, J.C. (1989) Gas and liquid chromatographic techniques, in Chemical Analysis of Polycyclic Aromatic Compounds (ed. T. Vo-Dinh), John Wiley & Sons, pp. 59–109. Fetzer, J.C. and Biggs, W.R. (1996) The analysis of large polycyclic aromatic hydrocarbons. Trends Anal. Chem., 15, 196–206. Fetzer, J.C. and Biggs, W.R. (1994) Identification of a new eight-ring condensed polycyclic aromatic hydrocarbon. Polycyclic Aromat. Compd., 5, 193–199. Fetzer, J.C. and Biggs, W.R. (1988) The synthesis of peropyrene-type polycyclic aromatic hydrocarbons. Org. Prep. Proced. Int., 20, 223–230. Schmidt, W., Grimmer, G., Jacob, J., and Dettbarn, G. (1986) Relevance of polycyclic aromatic hydrocarbons as environmental carcinogens. Toxicol. Environ. Chem., 13, 1–16. Schmidt, W., Grimmer, G., Jacob, J., Dettbarn, G., and Naujack, K.W. (1987) Polycyclic aromatic hydrocarbons with mass number 300 and 302 in hard-coal flue gas condensate. Fresenius Z. Anal. Chem., 326, 401–413. Bergvall, C. and Westerholm, R. (2006) Determination of dibenzopyrenes in standard reference materials (SRM) 1649a, 1650, and 2975 using ultrasonically assisted extraction and LC–GC–MS. Anal. Bioanal. Chem., 384, 438–447. Lindner, W., Pusch, W., Wolfbeis, O.S., and Tritthart, P. (1985) Analysis of nitroPAHs in diesel exhaust particulate extracts with multicolumn HPLC. Chromatographia, 20, 213–218. Fetzer, J.C. and Kershaw, J.R. (1995) The identification of large PAHs in a coal tar pitch. Fuels, 74, 1533–1536. Suzuki, S., Kaneko, T., and Tsuchiya, M. (1996) Hyphenated techniques for chromatographic detection. Kankyo Kagaku, 6, 511–520.

12 Senthilnathan, V.P. and Stein, S.E. (1986)

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14

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19

Hydrogen transfer in the formation and destruction of retrograde products in coal conversion. J. Org. Chem., 53, 3000–3007. Colmsjo, A. and Ostman, C. (1982) Polynuclear Aromatic Hydrocarbons: Physical and Biological Chemistry (eds M. Cooke, A.J. Dennis, and G.L. Fisher), Batelle Press, Columbus OH, USA, pp. 201–210. Wise, S.A., Benner, B.A., Liu, H., Byrd, G.D., and Colmsjo, A. (1988) Separation and identification of polycyclic aromatic hydrocarbon isomers of molecular weight 302 in complex mixtures. Anal. Chem., 60, 630–637. Wornat, M.J., Vriesendorp, F.J.J., LaFleur, A.L., Plummer, E.F., Necula, A., and Scott, L.T. (1999) The identification of new ethynyl-substituted and cyclopenta-fused polycyclic aromatic hydrocarbons in the products of anthracene pyrolysis. Polycyclic Aromat. Compd., 13, 1563–0000. LaFleur, A.L., Taghizadeh, K., Howard, J.B., Anacleto, J.E., and Quilliam, M.A. (1996) Characterization of flamegenerated C10 to C160 polycyclic aromatic hydrocarbons by atmospheric-pressure chemical ionization mass spectrometry with liquid introduction via nebulizer interface. J. Am. Soc. Mass Spectrom., 7, 276–286. Somers, M.L., McClaine, J.W., and Wornat, M.J. (2007) The formation of polycyclic aromatic hydrocarbons from the supercritical pyrolysis of 1methylnaphthalene. Proc. Combust. Inst., 31 (I), 501–509. Somers, M.L. and Wornat, M.J. (2007) UV spectral identification of polycyclic aromatic hydrocarbon products of supercritical 1-methylnaphthalene pyrolysis. Polycyclic Aromat. Compd., 27 (4), 261–280. Oña, J.O. and Wornat, M.J. (2007) Identification of the C30H16 polycyclic aromatic hydrocarbon benzo[cd]naphtho [1,2,3-lm]perylene as a product of the supercritical pyrolysis of a synthetic jet fuel. Polycyclic Aromat. Compd., 27 (3), 165–183.

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20 McClaine, J.W., Oña, J.O., and Wornat,

M.J. (2007) Identification of a new C28H14 polycyclic aromatic hydrocarbon as a product of supercritical fuel pyrolysis: Tribenzo[cd,ghi,lm]perylene. J. Chromatogr. A, 1138 (1–2), 175–183. 21 Marsh, N.D., Wornat, M.J., Scott, L.T., Necula, A., La Fleur, A.L., and Plummer, E.F. (2000) The identification

of cyclopenta-fused and ethynylsubstituted polycyclic aromatic hydrocarbons in benzene droplet combustion products. Polycyclic Aromat. Compd., 13 (4), 379–402. 22 Thomas, S. and Wornat, M.J. (2008) C24H14 polycyclic aromatic hydrocarbons from the pyrolysis of catechol. Int. J. Environ. Anal. Chem., 88, 825–840.

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17 NOx Formation, Control and Reduction Techniques Alexander A. Konnov, M. Tayyeb Javed, Håkan Kassman, and Naseem Irfan 17.1 Introduction

The clean and safe oxidation of organic fuels is of major importance in human activity. Progress has been made during the past few decades in establishing a basic understanding of combustion phenomena, leading to, for example, substantial reductions of polluting emissions of NOx, CO, and unburned hydrocarbons. Yet, the present knowledge on this subject remains insufficient. The incomplete and (sometimes) erroneous modeling of the numerous and complex conversion reactions, which often rely on either equilibrium assumptions, dedicated correlations or empiricism, render many combustion phenomena difficult to predict. It is clear that all aspects of combustion chemistry of NOx cannot be described in this relatively short chapter. As the chemistry of the combustion of organic fuels and of NOx formation is currently being investigated extensively on a worldwide basis, an exhaustive review of such vast research activities would be impossible. Fortunately, the seminal review of Miller and Bowman [1] has served – and continues to serve – as a milestone for these studies; consequently, only recent studies and new developments will be discussed in the following sections. Recent laboratory studies on NOx control have been motivated by the continuous interest in improving existing technologies, such as low-NOx burners, flue gas recirculation, and over-fire air, and so on. Of special practical interest are the selective noncatalytic reduction (SNCR) techniques, which allow most efficient NOx reduction. These include ammonia-based, urea-based and ammonium carbonate-based SNCRs, as well as additive-enhanced SNCR. Examples of SNCR application in industry, including an approach for the simultaneous reduction of NOx and minimization of corrosion, have shown much promise. The potential future developments and areas of use of these reduction techniques will be discussed.

Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright Ó 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

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x

17.2 Theory: Nitrogen Chemistry in Flames 17.2.1 Classification of the NOx Formation Routes

Different routes leading to NOx from organic fuels can be divided into two major pathways: (i) NOx formation from atmospheric N2; and (ii) NOx formation from nitrogen compounds present in fuel (“fuel-nitrogen”; the oxidation of fuel-nitrogen is discussed in Section 17.2.6). The oxidation of atmospheric nitrogen can proceed via the routes that are briefly summarized at this point, and detailed in the following sections. 17.2.1.1 Direct Reactions of N2 with Radicals These reactions directly convert N2 into NO or into intermediate species that are easily oxidized to form NO. The first key reaction was originally proposed by Zeldovich [2]: N2 þ O ¼ NO þ N

ð17:1Þ

Together with the reaction O2 þ N ¼ NO þ O

ð17:2Þ

which together form the thermal-NO mechanism [2]. Usually, the reaction N þ OH ¼ NO þ H

ð17:3Þ

is also considered in the thermal-NO formation (the so-called “extended Zeldovich mechanism”). Other possible direct reactions include: N2 þ H ¼ NH þ N

ð17:4Þ

N2 þ OH ¼ NH þ NO:

ð17:5Þ

The reactions in Equations 17.1 to 17.5 are not fuel-specific, and can occur in any combustion system. The so-called “prompt-NO mechanism” was first proposed by Fenimore [3]: N2 þ CH ¼ HCN þ N

ð17:6Þ

N2 þ CH2 ¼ HCN þ NH

ð17:7Þ

with the reaction of N2 with CH proving to be the major prompt-NO route [4]. Recently, Moskaleva and Lin [5] showed that the major products of the reaction between N2 and CH are NCN and H atom. Additional recent progress in the understanding of the prompt-NO mechanism is discussed in Section 17.2.3.

17.2 Theory: Nitrogen Chemistry in Flames

17.2.1.2 Adduct Formation, and Reaction of the Adduct with Radicals These reactions are thought to proceed via intermediate compounds, for example N2O, as was first proposed by Wolfrum [6]: N2 þ O ¼ N2 O:

ð17:8Þ

The formation of N2O is followed by: N2 O þ O ¼ NO þ NO

ð17:9Þ

N2 O þ H ¼ NO þ NH

ð17:10Þ

Bozzelli and Dean [7] proposed a new route of NO formation through the oxidation of NNH radicals. Only two key reactions control this route, namely formation of the NNH radicals in recombination: N2 þ H ¼ NNH

ð17:11Þ

and oxidizing steps leading to the NO formation: NNH þ O ¼ NO þ NH

ð17:12Þ

NNH þ O2 ¼ N2 O þ OH:

ð17:13Þ

Similar reactions of adduct formation, such as: N2 þ OH ¼ NNOH and N2 þ CH3 ¼ CH3 NN

were analyzed by Bozzelli and Dean [7] and have been found to be negligible. The NNH mechanism of NO formation is further discussed in Section 17.2.2.l 17.2.2 The NNH Route

Following massive research efforts conducted during the late twentieth century, important reaction routes that led to NO formation in flames were thought to be well understood. However, any agreement between the measurements of emitting NOx and model predictions was often only qualitative. For instance, the measurements and modeling of nitric oxide formation in atmospheric and high-pressure laminar flames of methane and ethane [8–10] suggested problems in the NO prediction. It was argued that discrepancies between the NO concentrations measured by laserinduced fluorescence (LIF) and those calculated might be explained by uncertainties in the new route by which NO was formed via NNH radicals [9–12]. The oxidation of NNH radicals via the reaction in Equation 17.12 represents a key step in this route, as proposed by Bozzelli and Dean [7]. Miller and Melius [13] apparently were the first to suggest a high value of k12 ¼ 5  1013 cm3 mol 1 s 1 for T > 2000 K. This appears to be reasonably consistent with

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subsequent quantum Rice Ramsperger Kassel (QRRK) analysis [7, 14]. Experiments, aimed at corroborating the formation of NO from the NNH route, have been performed by Harrington et al. [15]. Although the agreement between measurements in low-pressure hydrogen–air flames and modeling employing GRI (Gas Research Institute) -mech. 2.11 [16] was imperfect, it was concluded that the NNH route is a viable explanation for the presence of ppm levels of NO in these flames. Assuming that the NH radicals formed in the reaction of Equation 17.12 are totally converted into NO, and that the reaction of Equation 17.11 is equilibrated, then the rate of NO formation will be proportional to the concentration of N2, O atoms, H atoms, and (k12Kp11), where Kp11 is the equilibrium constant of the reaction in Equation 17.11. Effective values of (k12Kp11) have been obtained by Hayhurst and Hutchinson [17] at 1800–2500 K in rich flames of H2 þ O2 þ N2 and CH4 þ O2 þ N2 burning at 1 atm. Konnov et al. [18] extended the temperature range for measuring (k12Kp11) down to 1400 K by modeling experiments on the lean combustion of hydrogen and air in a stirred reactor [19]. A subsequent evaluation of the NNH route forming NO in hydrogen combustion in stirred reactors showed that this pathway is important at short residence times from 1000 to 2200 K in rich, stoichiometric, and lean mixtures [20, 21]. Subsequently, the rate constant of the reaction of Equation 17.12 has been derived by comparing experiments in hydrogen–air flames at approximately 1200 K [15] with modeling, employing an updated detailed H/N/O kinetic scheme [22]. To match calculations with experimental profiles of [NO] in these flames, the rate constant of this reaction is found to be reduced significantly (by ca. 50%) below values adopted earlier [7, 13, 14]. Combination of the adjusted rate constant with measurements in the range 1800–2500 K [17] strongly suggested a nonzero activation energy of the reaction of Equation 17.12. The accurate determination of the rate constant k12 was hampered by unavoidable uncertainties in temperature measurements, and by the presence of other sources of NO. For instance, in the lean combustion of hydrogen and air in a stirred reactor [19], a significant part of the NO is formed via the nitrous oxide route [21]. In rich flames of H2 þ O2 þ N2, the nitric oxide formed via the thermal Zeldovich mechanism had to be taken into account, whilst in rich flames of CH4 þ O2 þ N2, potential prompt-NO might also interfere [17]. Finally, in low-pressure hydrogen–air flames [15] both the NNH route and reactions of N2Hx species were shown to contribute to the formation of NO [22]. Therefore, dedicated measurements of NO in flames of H2 þ CO þ CO2 and air have been performed by Konnov et al. [23]. It was shown that, in rich mixtures, where the NNH route forming NO is dominant, the heat losses have no significant effect on the calculated [NO]. The comparison of experimental data with the detailed flame structure modeling strongly suggested a reduced value of the rate constant k12 for the reaction NNH þ O ¼ NH þ NO. The calculations with k12 ¼ (1  0.5)  1014 exp( 16.75  4.2 kJ mol 1 RT 1) cm3 mol 1 s 1 brings the modeling close to the measurements not only in rich flames but also in stoichiometric and lean flames. Haworth et al. [24] performed an ab initio analysis of the reaction in Equation 17.12, and obtained a rate constant between 1000 and 2600 K, which is approximately a factor of 4 less than the previous estimate of Bozzelli and Dean [7]. Surprisingly, at

17.2 Theory: Nitrogen Chemistry in Flames

1000 K the rates of Konnov et al. [23] and of Haworth et al. [24] coincide. These authors also performed kinetic modeling of NO formation in lean mixtures burned in a stirred reactor, and concluded that in most combustion systems, the NNH þ O pathway represents a very minor route to NO [24]. Recently, the potential energy profile of the reaction in Equation 17.12 was studied by Lue et al. [25]. Although the thermal rate constant was not derived, the authors concluded that Equation 17.12 could be expected to be an important channel in NO production. The relative importance of the NNH route and other mechanisms of NO formation in premixed flames are discussed in Section 17.2.5. 17.2.3 New Developments in the Prompt-NO Mechanism

It is now well accepted [26] that most of the Fenimore’s prompt NO is due to a reaction between CH and N2, as suggested previously [3]. The reaction in Equation 17.6: CH þ N2 ¼ HCN þ N

ð17:6Þ

was therefore included in all detailed kinetic mechanisms developed for the prediction of NO formation in combustion. Cui et al. [27] were apparently the first to show that the calculated thermal constant of the HCN þ N product channel was about two orders of magnitude lower than experimental measurements of the reactants consumption. This prompted Moskaleva et al. [28] to perform a detailed transition state search of the CH þ N2 reaction. Moskaleva and Lin [5] demonstrated that the reaction CH þ N2 ¼ NCN þ H

ð17:14Þ

is a major pathway to prompt NO, and derived a rate constant for it. An implementation of this reaction in detailed reaction mechanisms was for a long time hampered by the unknown chemistry of NCN radicals. El Bakali et al. [29] attempted to implement the rate constant of Moskaleva and Lin [5], and found that it led to a large underestimation of prompt-NO in flames. These authors then derived the rate constants of the reactions in Equations 17.6 and 17.14, based on the measurements of Lindackers et al. [30]. NCN reactions with O, H, OH, and O2 in the GDFKin3.0_NCN mechanism [29] were simple upper-limit estimates taken from the work of Glarborg et al. [31]. El Bakali et al. [29] concluded that switching from the reaction of Equation 17.6 to that of Equation 17.14, the choice of products for this reaction, and subsequent reactions of the NCN oxidation, did not affect the overall [NO]. Williams and Fleming [32] proposed several modifications to the Konnov detailed reaction mechanism for small hydrocarbons combustion [33] related to the promptNO route. These authors argued that a proper prediction of the NO formation could not be achieved if it was assumed that CH was the only prompt-NO precursor. Thus, they suggested the formation of NCN and related species for the reaction of CH2 þ N2, analogous to the NCN þ H channel for the reaction of CH þ N2, and concluded that their modeling supported inclusion of the reactions of CH2 and C2O with N2 into the NO-formation schemes [32].

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Naik and Laurendeau [34] attempted to reconcile their LIF measurements of CH and NO in methane counterflow flames at different pressures considering, among other options, an implementation of the NCN prompt-NO route in the GRI-mech. 3.0 [35]. These authors [34] also confirmed the conclusion of El Bakali et al. [29], that the production of NO was dominated by the oxidation sequence. Thus, the actual initiation step, namely the reaction in Equation 17.6 or 17.14, does not influence the predicted NO concentration. Taking into account this observation, the role of C2O radicals in the prompt-NO mechanism was re-evaluated [36]. The measurements of NO concentrations in the post-flame zone of different hydrocarbon þ O2 þ N2 flames at standard temperature and atmospheric pressure available in the literature were compared with predictions of the original Konnov reaction mechanism [33], and with the same mechanism extended by the reaction of C2O with N2. The goal was to investigate a possible role for this reaction as proposed by Williams and Fleming [32]. This new reaction of C2O with N2 seems to be a reasonable explanation of the deficiencies in the prompt-NO route. A direct comparison of the experimental measurements performed in different flames with the modeling strongly suggested that the upper limit of this reaction rate constant was smaller than the originally proposed expression [32] by more than an order of magnitude. Sutton et al. [37] performed LIF measurements of NCN in low-pressure CH4 þ O2 þ N2 flames, and compared their results with the GDF-Kin3.0_NCN mechanism [29] and with the modified GRI-mech. 3.0 [35]. It was concluded that the rate coefficients of El Bakali et al. [29] for the reaction in Equation 17.14 led to a better agreement with experimental results than the rate coefficients of Moskaleva and Lin [5] for the low-pressure flame conditions, if CH was considered as the only prompt-NO precursor. Sutton and Fleming [38] further simplified the NCN submodel implemented in the GRI-mech. 3.0 [35], and included only the reaction of Equation 17.14 with the rate constant measured by Vasudevan et al. [39] and four pathways of NCN consumption in reactions with H, O, OH, and O2. The rate constants of these four reactions were taken either from Glarborg et al. [31], or from the calculations of Lin et al. [5, 40–42]. It was concluded that the rate constants estimated in Ref. [31] were too high for a correct prediction of [NCN]. Sutton and Fleming [38] performed extended modeling of NO formation in low-pressure (10–40 Torr) flames, under the conditions of experimental studies reported elsewhere [32, 43–46]. Although the NO predictions were generally better when the NCN pathway was used, the comparison with all 36 flames showed a systematic trend: a significant underprediction in lean mixtures and an overprediction in rich mixtures [38]. Williams et al. [47] attempted to resolve this discrepancy by introducing an additional prompt-NO precursor, diazomethane, which could be formed in the recombination of singlet 1CH2 with molecular nitrogen. These authors showed that this assumption could significantly improve prompt-NO modeling under lean conditions in low-pressure methane flames. It can be summarized that different modifications of the existing detailed reaction mechanisms [29, 33, 35] were proposed at low [32, 37, 38, 47], atmospheric [36] and high [34] pressures. Not all of these areconsistent with recent measurements [39] and an

17.2 Theory: Nitrogen Chemistry in Flames

ab initio modeling [48] of the rate constant of the reaction in Equation 17.14. As the productionofNOisdominatedby the oxidationsequence(i.e.,the actualinitiationstep), neither of the reactions in Equations 17.6 and 17.14 can influence the predicted NO concentration [29, 34]. An analysis of the relative importance of the prompt-NO route could be performed using existing mechanisms [33, 35], as described in Section 17.2.5 17.2.4 Relative Importance of Different NO-Formation Routes in Flames

The relative importance of the different NO-formation routes varies with flame temperature, stoichiometry, pressure, heat losses in the burner, and so on. Extended discussions of this topic are available in the reviews of Bowman [49–51], Correa [52], and Carvalho [53]. 17.2.4.1 Hydrogen Flames The objective of the analysis performed by Konnov [54] was to evaluate the relative importance of the different routes forming NO in premixed hydrogen flames, by comparing experiments on the combustion of lean mixtures of H2 þ O2 þ N2 [55] with modeling, employing sensitivity analysis. This comparison strongly supports the new rate constant [23] of the reaction: NNH þ O ¼ NH þ NO. The sensitivity analysis has shown that the relative importance of thermal NO and that from NNH varies with the temperature, with the latter route being dominant below 2000 K. Similar to the analysis of the combustion of hydrogen in stirred reactors [20], NO formation via NNH is of major importance not only in rich flames [15, 17] but also in lean mixtures up to moderately high (1900 K) temperatures. This route therefore must be explicitly taken into account as a source of NO in hydrogen-fueled industrial installations and turbulent flames. 17.2.4.2 Flames of Hydrocarbons The NO formation rates as functions of local gas composition and temperature have been derived for the thermal-NO, the prompt-NO, the nitrous-oxide mechanism, and the NNH mechanism [56]. Independent of the chemical mechanism implemented in computational fluid dynamics (CFD) modeling, they can be used for NOx predictions in high-temperature industrial flames. When used with reduced or skeletal mechanisms, the steady-state approximations for the NO precursors are valid while [O], [H], and [OH] are estimated correctly. For the prompt-NO formation, two sources of the CH radicals have been considered, namely CH3 radicals, and C2H2 formed from higher hydrocarbons. This enables an analysis to be made of the influence of natural gas composition on the NOx exhaust. Calculated contributions of the different NO formation mechanisms are in general agreement with previous analyses. The NNH mechanism is of minor importance in most cases of natural gas combustion. Calculations of the NO concentration employing full chemistry and explicit expressions for the instantaneous NO formation rates derived in this studies are in good qualitative and acceptable quantitative agreement. The difference observed is not higher than 50% at high temperatures.

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17.2.5 Fuel-NO

Numerous experimental and modeling studies of flames doped with ammonia (as reviewed recently by Glarborg et al. [57]) were motivated by concerns relating to NOx emissions from the combustion of biomass and other solid fuels. During the initial stages of biomass combustion, fuel-nitrogen is released as volatile components, mostly in the form of ammonia. The biomass itself is converted into a combustible mixture of low- to medium-heating value, as compared to typical natural gas, due to the presence of water vapor and carbon dioxide. The formation of NO in ammonia-doped flames of hydrocarbons has been studied for many years, with extensive data having been reported [57]. At low pressures, either neat methane þ oxygen þ ammonia flames [58–61], or flames diluted by Ar [62, 63], were studied. Air as an oxidizer was used in a subatmospheric study [64], and also in many investigations of methane flames at atmospheric pressure (e.g., Refs [65–67]). The replacement of nitrogen by argon and helium, or variations of the dilution ratios of oxygen, O2/(O2 þ N2), in flames of methane and other hydrocarbons, was employed to control the flame temperature and to arrange “comparable” flames having close temperatures at different equivalence ratios [68–73]. These flame studies and other studies of ammonia oxidation were summarized by Miller and Bowman [1]. Subsequent developments of the detailed reaction mechanisms for ammonia oxidation (e.g., Refs [74–77]) were largely based on the review of Miller and Bowman [1]. Glarborg et al. [57] concluded that “. . .the oxidation chemistry of hydrogen cyanide and ammonia is quite well established. . .” and attributed remaining uncertainties to very fuel-rich conditions. Ammonia chemistry under fuel-rich conditions was addressed recently by Skreiberg et al. [77], with the mechanism developed in these studies being tested together with the Konnov mechanism [33] in a dedicated study of methane þ oxygen þ nitrogen flames doped with ammonia (0.5% of the fuel) [78]. In (CH4 þ NH3) þ O2 þ CO2 mixtures [79], the modeling overpredicted the measured concentrations of NOx, although the experimental trends were well reproduced. In (CH4 þ NH3) þ O2 þ N2 mixtures [78], the plots of the concentrations of NOx in the post-flame zone as a function of the stoichiometric ratio, differed qualitatively from that in (CH4 þ NH3) þ O2 þ CO2 mixtures. Whilst this modeling was in satisfactory agreement with the experiments in lean flames, in rich flames it did not confirm the conclusions of Glarborg et al. [57]. 17.2.6 NOx Reburning

Flue gas recirculation (FGR) is considered to be a basic method for controlling combustion. The application of FGR has a number of effects on the combustion process and emissions: . .

Preheating effect: the inlet temperature increases due to hot FGR gases. Dilution effect: the introduction of the FGR gases leads to a reduction of the oxygen concentration.

17.2 Theory: Nitrogen Chemistry in Flames .

.

Heat capacity effect: the total heat capacity of the mixture of the FGR gases, air, and fuel will be higher owing to the higher heat capacity of carbon dioxide and water vapor. Chemical effect: unburned hydrocarbons, CO, CO2, NO, H2O, and so on in the FGR gases are chemically active and could moderately affect reaction rates.

In an effort to address these effects, and also the NO reburning processes in flames, a number of studies have been conducted in methane flames with admixture of NO at subatmospheric pressures [45, 60–62, 80–90], and also at atmospheric and higher pressures [67, 72, 91–94]. A summary of the experimental results obtained in premixed CH4 þ O2 þ N2 þ NO flames under various conditions is shown in Figure 17.1, where the conversion ratio of NO versus the initial concentration of NO in the flames is plotted. Here, the conversion ratio was determined as the ratio of destroyed [NO] to [NO] added initially to the fresh mixture. It can be seen that all the experimental data were obtained in the flames with initial [NO] additive higher than 1000 ppm. Lean (w ¼ 0.86) premixed CH4/O2/N2 and H2/O2/N2 flames stabilized on a McKenna burner at atmospheric pressure with the addition of 0.11–0.33% of NH3, NO, and N2O were studied by Martin and Brown [67]. By using microprobe gas sampling, relationships between NO and N2O formation in the post-flame zone and the addition of NH3, NO, and N2O to the combustion mixture were determined. The effect of addition of 1000 ppm of NO on the structure of premixed CH4–air flames in a range of equivalence ratios from 0.8 to 1.7 was studied by Jansohn et al. [92]. Here, a nozzle burner was used for flame stabilization, and concentrations of stable species were determined. A comparison of the measurements and modeling using the mechanism of Miller and Bowman [1] in the rich (w ¼ 1.25) undoped flame showed an underprediction of NO concentration in the post-flame zone by a factor of 2. On the other hand, in the flame seeded with 1000 ppm NO, the modeling overpredicted the NO concentration by a factor of 1.2, under the same experimental conditions. Feng et al. [94] studied the structure of burner-stabilized CH4/O2/Ar flames doped with NO (960–1070 ppm) using a quartz microprobe sampling and subsequent chemiluminescence analysis. These authors found that the modeling using the mechanism of Lindstedt et al. [75] underpredicted the NO concentrations in the post-flame zone at rich conditions (w ¼ 1.3–1.4) by a factor of 1.5–2. In both very rich flames (w ¼ 1.4–1.7) and in lean flames (w ¼ 0.8–1.0), however, the modeling satisfactorily predicted the NO concentrations. Measurements of NO conversion in the flames doped with lower concentrations of NO were not reported. Numerical simulations (e.g., Refs [45, 91, 93, 95, 96]) based on the GRI-Mech. 2.11 [16], 3.0 [35], and Miller–Bowman kinetic mechanism [1] showed that, in the lean flames doped with low concentrations of NO (on average, 450  C), however, the ammonia reacts with oxygen in an undesirable parallel reaction to produce N2, N2O, or NO. In contrast, at temperatures below 200  C, ammonia and NOx may form solid deposits of ammonium nitrate and nitrite. NOx can be reduced continuously by NH3 on a SCR catalyst, resulting in the selective formation of nitrogen and water. At this point, it should be mentioned that the SCR procedure is the only technique converting NOx selectively into N2, even under strongly oxidizing conditions. Hence, SCR was considered the technology of choice when deNOx became an issue for lean-burn engines. In fact, the SCR process covers the relevant temperature range of diesel engines, providing effective NOx abatement, to a point where during the past few years it has advanced to become state-of-the-art deNOx technology for heavy-duty vehicles. Whilst the operational range of the SCR procedure is limited at low temperatures ( 0.5 can lead to NH4NO3 deposits, thus deactivating the SCR catalyst. As the hydrolysis of urea may not be fully completed at the entrance of the SCR catalyst, the front section of the SCR structure is composed of a urea hydrolysis catalyst, such as alumina or titania. The subsequent part, which forms the “real” SCR catalyst, is commonly extended by an NH3 oxidation catalyst to avoid any slip of NH3.

18.3 Catalytic Technology for Gaseous Pollution Control

Figure 18.34 Mechanism of the SCR reaction on V2O5/TiO2 catalysts [98].

The most common SCR catalyst used today is a TiO2-supported WO3/V2O5; this is normally used in the form of an homogeneous monolith, although in a few applications charcoal catalysts may also be used. The mechanism of the SCR reaction on a V2O5 catalyst was elucidated both experimentally [94–97] and by using quantum-mechanical calculations [98]. The reaction follows an Eley–Ridealtype mechanism, where two different active sites are involved (Figure 18.34) that are in such close proximity that they represent a Brønsted acid site (V5 þ OH) and a (V5 þ ¼O) redox site. In the first step, NH3 is adsorbed onto the Brønsted site to produce NH4 þ ; this subsequently interacts with the neighboring redox site, leading to a reduction of the latter. The gaseous or weakly adsorbed NO then reacts with the activated N species to form N2 and H2O. In the final stage, the (V4 þ OH) group is reoxidized into (V5 þ ¼O), again resulting in the production of H2O. 18.3.1.2.4 Alternate Catalysts [99] Currently, a major trend in automotive SCR is the substitution of V2O5 catalysts by harmless materials. In the meantime, catalytic converters based on V2O5 have been prohibited in Japan and California, on the basis of the toxicity of the active component; similar discussions regarding this point are currently ongoing in the European Union. An additional problem is that V2O5 demonstrates a limited high-temperature stability, which may cause difficulties when coupling SCR with particulate filter systems in passenger cars. At present, Fe-ZSM5 zeolite is considered to be the most-favored type of catalyst as an efficient substitute for the classical V2O5 patterns [80, 100–102]. 18.3.1.2.5 Alternative Reducing Agents Alternative reducing agents have been investigated extensively over the past two decades, mainly hydrocarbons (HC-SCR) and hydrogen (H2-SCR). In the case of HCs, additional fuel may be injected in the raw exhaust or the exhaust line upstream of the SCR catalyst. Unfortunately, difficulties in achieving a high conversion and selectivity over the catalysts [103], the catalyst stability at high temperature, and problems in meeting HC limits have so far prevented HC-SCR from becoming widespread in terms of its applications.

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H2-SCR, which is currently still undergoing fundamental development, is of particular interest for low-temperature exhaust gases [104]. The conversion of NOx by H2 already operates at stoichiometric (TWC) and rich (NSC in regeneration phase) conditions. However, low-temperature H2-SCR has also been reported for strongly oxidizing conditions using Pt catalysts. Although a very good performance is obtained below 100  C, the narrow range in activity and the high selectivity towards N2O remain challenging issues. The mechanism of the NO reaction by H2 on Pt/ Al2O3, under lean conditions, implies the dissociative adsorption of NO on reduced Pt sites [105]. The recombination of two N atoms leads to the evolution of N2, while the oxygen is retained on the Pt surface. The production of N2O is explained by the combination of a surface N atom with NO adsorbed onto neighboring Pt sites. Finally, the effect of the hydrogen is to regenerate the active Pt sites. A potential source for the onboard production of H2 is the processing of fuel by catalytic partial oxidation or steam reforming [106–108]. Additionally, the temporary generation of H2 might also occur by engine management; that is, after the injection of fuel. 18.3.1.3 NOx Storage Catalysts NOx storage reduction catalysts were originally developed for lean SI engines, and are currently being transferred for use in diesel-powered passenger cars. The NSC procedure is based upon the periodic adsorption and reduction of NOx [4, 109], the principle of which is illustrated in Figure 18.35. The catalysts consist of Pt, Pd, and Rh in the mass ratio of approximately 10 : 5 : 1, with a total precious metal load of approximately 4 g l 1. The NSC contains basic adsorbents such as Al2O3 (160 g l 1), CeO2 (98 g l 1) and BaCO3 (29 g l 1, denoted as

Figure 18.35 Reduction of NOx emissions of lean operated engines. Principles of a NOx storage/ reduction catalyst (NSC).

18.3 Catalytic Technology for Gaseous Pollution Control

BaO equivalent) [110]. In the lean phase of the engine (general operation mode), the NOx of the exhaust is adsorbed onto the basic components of the NSC, mainly on the barium carbonate, to form a nitrate. When the storage capacity is reached, the engine is operated at rich conditions (l  0.9) for a few seconds, and this leads to an exhaust containing CO, HCs, and H2 as reducing agents for catalyst regeneration (backtransformation of the nitrate to the carbonate): Storage (lean) phase: .

NO oxidation over noble metal: NO þ

.

1 O2 ! NO2 j 2

NOx storage on Ba sites: BaCO3 þ 2NO2 þ

.

1 O2 >BaðNO3 Þ2 þ CO2 2

Regeneration (rich) phase: BaðNO3 Þ2 þ CO=H2 =HC>BaCO3 þ 2NO þ CO2 =H2 O

Obviously, this global scheme is an oversimplification, and many research investigations have been devoted to elucidating the intrinsic kinetics [111–116]. The effect of the Ba component is to adsorb NOx at temperatures above 250  C, whereas substantial storage is also provided by Al2O3 and CeO2 at lower temperatures [117]. However, below 250  C the effectiveness of NSC catalysts is limited by the kinetics of the NO2 production on the Pt component, while above 400  C the thermal stability of the NOx surface species represents the limiting factor. For the NO2 adsorption on the Ba sites, two parallel pathways of nitrate formation are suggested [118]. The first route involves the adsorption of NO on Ba to form nitrites, which are subsequently oxidized by gas phase O2 into nitrates. The second route includes the catalytic NO oxidation on Pt into NO2, followed by its immediate adsorption in the form of nitrates. It has also been suggested that barium peroxide species might serve as the crucial sites for nitrate formation [119]. As compared to SCR, the most important advantage of the NSC technique is the fact that no additional liquid tank (Urea-SCR), additional injection management/ system (HC-SCR), or chemical reactor (H2-SCR) is needed. However, a substantial constraint is the susceptibility to sulfur poisoning. In parallel to NO, SO2 is also oxidized on Pt, followed by the adsorption of SO3 onto the basic substrate. The sulfate species produced lead to a drastic deactivation of the NOx storage sites. Although, the poisoned sites of ceria and alumina can be regenerated thermally above 300  C, the released SOx is readsorbed selectively onto the Ba species. The regeneration of poisoned Ba sites is inadequate, even under rich conditions and high temperatures, as the sulfate groups are partially converted into highly stable BaS [110]. In recent years, several groups have coupled detailed kinetic models and CFD to provide a numerical simulation of NOx storage catalysts under varying conditions and using different modeling approaches [116, 120–124]. These approaches have

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differed especially in the applied reaction mechanisms, and the treatment of mass transfer in the single channels and the washcoat. Furthermore, most studies have considered NO oxidation only in the lean phase, and its reduction in the rich phase. The applied gas matrix is sometimes far from a realistic exhaust gas, because it contains neither water nor CO2, both of which have a major influence on the catalytic activity of the noble metal and the morphology of barium. As the storage of nitrogen oxides is a slow process compared to the subsequent reduction, the observed behavior was explained by the different molar volumes of BaCO3 and Ba(NO3)2, the so-called “shrinking core” model [116, 120]. State-of-the art simulations have included detailed reaction mechanisms, radial mass transfer limitations in the catalytic channels and the washcoat, and have been capable of describing the transient behavior of the NSC at varying inlet conditions. As an example, Figure 18.36 shows the numerical predicted and experimentally measured NO and NO2 profiles in a laboratory flat-bed reactor, using a commercially manufactured Pt/Ba/Al2O3 model NSC as function of axial position and storage time. The effect of NO2 formation in the first section of the catalyst, and its subsequent storage, is clearly captured. The model applied a detailed reaction scheme for the processes on the noble metal Pt [125], and a lumped scheme coupled with the shrinking core model for the storage component Ba. 18.3.2 Reduction of Gaseous Emissions from Stationary Sources 18.3.2.1 Catalytic Technologies for NOx Removal [1] Nitrogen oxides arise from the oxidation of nitrogen-containing compounds of the fuel (fuel NOx), the oxidation of atmospheric nitrogen from combustion with air (thermal NOx), and by the oxidation of intermediate combustion species (prompt NOx). Often, a combination of combustion modifications and catalytic gas cleaning is used, for example, low-NOx burners, and SCR. In addition, a selective noncatalytic reduction (SNCR) step can be applied by injecting ammonia into the furnace. Primary NOx formation can substantially improved by oxy-fuel combustion – that is, combustion with pure oxygen or enriched air. Interestingly, the potent greenhouse gas nitrous oxide (N2O) cannot be removed by the normal SCR process. This emerges as a particular in nitric acid production plants, where the threat of environmental harm is inevitable, unless innovative end-of-pipe N2O removal technologies can be developed to effect the reduction of the N2O produced as waste. The current approach to this problem has focused on the use of transition-metal, ion-exchanged zeolites for the decomposition of N2O. SCR with ammonia is by far the most relevant technology for the catalytic removal of NOx from stationary sources, and has been implemented since the 1980, notably to deal with NOx produced not only by power plants but also by industrial boilers and gas turbines. It should be noted that SCR with ammonia would utilize a similar approach for both mobile and stationary applications, except that the size of the structured catalyst would be much larger in the latter case.

18.3 Catalytic Technology for Gaseous Pollution Control

Figure 18.36 Axial profile of NO (a) and NO2 (b) concentration at varying storage time in the lean phase of Pt/Ba/Al2O3 catalyst at 350  C [124, 127].

The selective catalytic reduction of NOx was first carried out using Pt catalysts although, due to the high N2O selectivity of this catalyst, base metal catalysts have subsequently been developed for NOx reduction. Vanadia supported on titania (in the anatase form) and promoted with tungsten or molybdenum oxide exhibits the best catalytic properties. Although BASF were the first to describe vanadia as an active component for SCR, a TiO2-supported vanadia for the treatment of exhaust gases was

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also developed in Japan. Anatase is the preferred support for SCR catalysts for two main reasons. First, it is only moderately sulfated under real exhaust gas conditions; in fact, its catalytic activity even increases after sulfation [128]. Second, vanadia can be spread in thin layers on the anatase support, which in turn leads to highly active structures with large surface areas. Unfortunately, the amount of vanadia in a technical catalyst is limited to only a few weight%, because it is also catalytically active for SO2 oxidation. The mechanism of the standard SCR reaction over vanadia-based catalysts is generally assumed to proceed via an Eley–Rideal mechanism that involves adsorbed ammonia and gas-phase NO (as described above). As the rate of the SCR reaction under industrially relevant conditions is quite high, external and intraparticle diffusion resistances play an important role, especially for the frequently used honeycomb monolith or plate-type catalyst geometry operating in a laminar flow regime. These geometries must be used to minimize the pressure drop over the catalyst bed. Monolithic elements usually have channel sized of 3–7 mm, a crosssection of 15  15 cm, and lengths of 70–100 cm. Monoliths or packages of plate catalysts are assembled into standard modules which are then placed in the SCR reactors as layers. Notably, these modules can be easily replaced to introduce fresh or regenerated catalysts. SCR reactors can be used in different configurations, depending on the fuel type, the flue gas composition, the NOx threshold, and other factors. The first possibility is a location directly after the boiler (a “high-dust” arrangement), where the flue gas usually has the optimal temperature for the catalytic reaction. However, dust deposition and erosion, as well as catalyst deactivation, will be more pronounced than in other configurations. A second option, which is common in Japan, is to place the SCR reactor after a high-temperature electrostatic precipitator for dust removal (“low-dust” arrangement). In this case, although damage of the catalyst by dust can be prevented, the deposition of ammonium sulfate (which in the high-dust configuration mainly occurs on the PM in the gas stream) may become more critical. It is for this reason that especially low limits for ammonia slip must to be met. Finally, the SCR reactor may be located in the cold part after the flue gas desulfurization unit, in the so-called “tail-end” arrangement. In this case, in order to achieve the required reaction temperature the exhaust gases must be reheated by means of a regenerative heat exchanger and an additional burner. A major benefit here, however, is that catalysts with very high activities can be used, as no poisons will be present and SO2 oxidation need not be considered. New promising catalysts for the removal of NOx include iron-exchanged zeolites, such as MFI and BEA. Although field tests in the flue gases of power plants have shown a quite strong deactivation, notably by mercury [129], these catalysts appear to be especially suited for “clean” exhaust gases, such as in nitric acid plants. The main advantages of iron zeolite catalysts include a broader temperature window for operation, and the ability also to reduce N2O emissions. Uhde GmbH has recently developed the EnviNOxÒ process for the simultaneous udreduction of NOx and N2O, which uses iron zeolite catalysts provided by S€ Chemie AG.

18.4 Outlook

18.3.2.2 Technologies for Removal of Other Emissions Catalytic technologies may play a minor role in the removal of other gaseous emissions from stationary sources; however, for the sake of brevity, the reader should consult comprehensive reviews produced by Gabrielsson and Pedersen [1] and by Spivey [2]. Catalytic combustion may be applied to remove VOCs [1], and also to reduce the formation of gaseous pollutants, in particular NOx [130, 131]. Further details on these topics are available in the reviews of Forzatti et al. [130] and Hayes and Kolaczkowski [131].

18.4 Outlook

The currents trends in the implementation of exhaust-gas after-treatment systems for cars and trucks are determined by an increasing complexity. The system often includes several of the components described above. As an example, Figure 18.37 illustrates the recently developed system that includes DOC, NSC, DPF, and SCR technology. Whilst the management of this “chemical plant” underneath a car represents a major challenge, the even lower legislative emission limits planned for the future may require even greater complexity of designs and operation strategies. Yet, on the other hand, integrated systems are becoming increasingly attractive, with Kolios et al. having recently proposed a heat-integrated reactor concept for catalytic reforming and automotive exhaust purification [132].

Figure 18.37 Exhaust-gas treatment of the E320 BLUETEC. Illustration courtesy of Daimler AG.

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Clearly, increasing efforts will have to be made to substitute the expensive noble metal catalysts, or at least reduce the amount needed. These include: .

. .

An optimization of the technical device (geometry, flow conditions, washcoat structure, zone coating) to reduce any mass transfer limitation of the overall reaction rate. A maximization of the dispersion of the catalyst particles. Finding alternative noble metal-free catalysts; in particular, some promising results have recently been reported with the use of nanostructured catalysts.

Acknowledgments

The studies of A.G. Konstandopoulos (A.G.K.) in the Diesel Emissions area have been supported in part by the European Commission framework programs through the industrial collaborative projects DIDTREAT, CERFIL, MULTISENS, ART-DEXA, PSICO-DEXA, SYLOC-DEXA, STYFF-DEXA, FLOWGRID, IMITEC, COMET, MAAPHRI, IPSY, PAGODE, TOP-EXPERT, ATLANTIS, the Hellenic General Secretariat for Research and Technology through collaborative projects EPET-II, PAVE, EPAN, and from a number of automotive industries and their suppliers, including Honda, Centro Ricerche Fiat, Ibiden, The Dow Chemical Company, AMR, and Johnson Matthey. A.G.K. is very grateful to these sponsors, and also to colleagues at the APT Laboratory for their hard work and support. Particular thanks go to Ms Souzana Lorentzou, for her valuable assistance in putting together the present chapter. O. Deutschmann would like to thank W. Boll, F. Birkhold, D. Chatterjee, G. Eigenberger, R.J. Kee, J. Koop, S. Kureti, L. Maier, N. Mladenov, S. Tischer, V. Schmeisser, and M. Votsmeier for many fruitful discussions and collaborations. Thanks also to Y. Dedecek for her help with editing the manuscript. O.D. gratefully acknowledges the financial support of the German Research Foundation (DFG), Forschungsvereinigung Verbrennungskraftmaschinen e.V. (FVV) and of many automotive industries and suppliers.

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19 Corrosion Renata Włodarczyk, Rafał Kobyłecki, and Zbigniew Bis 19.1 Introduction

The industrial operation of any hard coal- and lignite-fired boiler – of either the stoker, pulverized coal (PC)- or fluidized-bed combustion (FBC) -type – is more or less associated with the need for periodic cleaning of the heat-transfer surfaces and removal of any deposits. In recent years – most likely as a consequence of fuel change or implementation of large-scale combustion of coal and various waste or biomass – the formation of deposits on boiler heat-transfer surfaces and the corrosion of several boiler elements have become an increasingly serious issues for boiler operators [1, 2]. Despite the fact that operational experiences have been collected for many years, and significant research data have been acquired, the results and achievements obtained to date to reduce deposit formation rates and to minimize fouling and hardening of the deposits remain inadequate and far from acceptable. Until now, it has been generally agreed that the main factors affecting the formation rate and structure of the deposits that form on the heat-transfer surfaces of the industrial boilers include: the fuel particle size distribution; fuel ash composition; flue gas temperature and velocity; the design of soot-blowing systems; and the application of chemical agents during boiler shut-downs. The corrosion and erosion of heating elements usually occur in parallel with persistent fouling of the heat-transfer surfaces [3]. Corrosion is often caused by “aggressive” components of the flue gases, particularly products of the combustion of chlorine- and sulfur-containing feedstocks, as well as by certain other “corrosion intensifiers” that might either be fed with the air (e.g., moisture) or included in the ashes and subsequently evolved and deposited inside the boiler system. Thus, correct ventilation of the boiler during shut-downs and stoppages is particularly important in order to minimize corrosion. Taking into consideration boiler operational safety, as well as the economics of steam or hot water production, the deposits should be regularly removed from the heat-transfer surfaces in order to guarantee not only the required boiler efficiency but also the outlet temperature of the flue gases, and to minimize expenditure for repairs.

Handbook of Combustion Vol.2: Combustion Diagnostics and Pollutants Edited by Maximilian Lackner, Franz Winter, and Avinash K. Agarwal Copyright Ó 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim ISBN: 978-3-527-32449-1

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In this chapter, the processes of deposit formation on boiler heat-transfer surfaces, and the factors affecting the process intensity, are first described. The deposits are classified according to their origin, chemical composition, and the effects of boiler operation. The chemical properties of the flue gas components are also classified depending on their corrosive action and material damage. Finally, the possibilities of controlling wastage processes, as well as the countermeasures taken to minimize corrosion, are described. Apart from the type of fuel being burned, the combustion products and a hightemperature environment represent the main factors that initiate corrosion processes on the surfaces of steel boiler elements. The wide variety of corrosion microprocesses that occur simultaneously during fuel combustion in a particular system means that it is more appropriate to describe the overall process with several corrosion mechanisms, among which one mechanism is dominant. Such an assumption is supported by the operational data from several industrial systems which indicate, for example, that the formation of an oxide layer occurs simultaneously with the formation of low-eutectic salts, while the formation of scales occurs in parallel with the process of leaching, or the erosion and/or perforation of steel/ metal elements. Although, in terms of their mechanisms, those processes may appear completely different, they are in fact quite closely related to each other, since they are all associated with a decrease in the mechanical properties of the corresponding boiler elements. In this chapter, however, only those processes and phenomena associated with the damage and destruction of steel elements that have corroded due to being exposed to the “chemical activity” of fuel combustion products are described and discussed. 19.1.1 Corrosion

The term “corrosion” is used to describe a material’s destruction due to its interactions with the surrounding environment. Corrosion is usually an unwanted phenomenon, as the material will be damaged or destroyed by the chemical or physico-chemical activity of the environment, and the material will be changed from a “metallic” into an “ionic” state. Corrosion occurs spontaneously, as the oxidized form of metal is more stable at ambient conditions [4]. As the process of corrosion is heterogeneous, it will occur on the boundary between two phases: solid (metal) and gas; or solid and liquid. Corrosion is a common process; examples include: the rusting of pipelines in an air environment; the destruction of metals in sea or river water; the interaction of chemicals and equipment surface in the chemical industry; the rusting of underground pipelines; or the oxidation of metals at high temperatures. During the operation of industrial devices and machinery, the processes of corrosion and erosion usually occur simultaneously. Corrosion is usually started by the destruction of a metal surface, and this then extends into the metal’s interior. This action is always accompanied by a change in the composition and properties of the material, such that the metal can be either partly dissolved (i.e., transferred into the ionic state, as occurs during the dissolution of zinc in hydrochloric acid), or the

19.1 Introduction

corrosion products may form a deposit on the metal’s surface, as occurs during rusting (e.g., the corrosion of iron in a wet environment). Corrosion processes may be associated with disintegration of the elemental structure, or a change in the physicochemical properties of metals or alloys (e.g., a reduction in strength due to changes in the distribution of intermolecular bonds). Taking the above points into consideration, it becomes evident that corrosion may proceed according to a variety of mechanisms that are driven by: . . .

chemical action electrochemical action mechanical action (erosion, cavitation) [5].

The corrosion of metals proceeds without any division into individual stages, and the corrosion products are formed directly on that part of material where the deterioration occurs. In the case of electrochemical corrosion, two processes may occur simultaneously – that is, the oxidation (dissolution of metal) and reduction (liberation of hydrogen or metal, reduction of oxygen, etc.). Electrochemical corrosion is also accompanied by an electric current (i.e., a directional movement of the electrons in the metal and/or ions in the electrolyte). The rather wide range and scope of material corrosion processes permits these phenomena to be classified with respect to: (i) the type of environment in which the element is working; and (ii) the type of material that is being exposed to corrosion. With regards to the type of environment, distinctions can be made among corrosion in a wet environment (sea water, humid air, or soil), in molten salts, or at a low or high temperature. However, with regards to the structure and type of material, corrosion may be associated with the deterioration of metals and alloys, the corrosion of selfpassivating metals (crevice, penetrating, pitting, intergranular), of ceramic materials, glass, polymers, or the destruction of concrete materials [6–11]. Various selected types of corrosion are shown schematically in Figure 19.1. 19.1.2 Corrosion Processes

Generally, corrosion may proceed as either a uniform or a selective process. In uniform corrosion, the destruction affects the overall metal surface (Figure 19.1a), whereas in selective corrosion some components or parts are more seriously damaged than others (see Figure 19.1b–f). The term “selective corrosion” is commonly used to describe various damage processes that occur locally and result in only some parts of the material surfaces being attacked. Pitting corrosion (Figure 19.1c) is characterized by deep pits located on a relatively small external area. The presence of chlorine ions in the surrounding environment favors this process, as the ions can quickly penetrate the passive metal layer and begin the formation and rapid growth of pits. Electrochemical pitting corrosion may often result from the shut-down and stoppage of a power production device, particularly if the equipment is left for over two weeks without any preventive measures being taken (standstill corrosion). One direct reason for standstill corrosion is the presence of moisture, dew, condensate and oxygen

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Figure 19.1 The main selected types of corrosion. (a) Uniform; (b) Selective; (c) Pitting; (d) Subsurface; (e) Intergranular; (f) Tension-related.

since, under such conditions, a large quantity of water is saturated with oxygen and remains inside the device (e.g., the boiler). It is also possible for moisture to enter the device with the air, and then to condense after contacting the cold metal surfaces. In such a case, deep perforations of thin-walled (0.05% of carbon (the steel types are described according to AISI 304SS) [12]. Intergranular corrosion occurs during the heating of steels at temperatures of 400 to 800  C since, under these conditions, the inclusions containing chromium carbide will be generated between the granules. This results in the chromium content of the austenite falling below

19.1 Introduction

Figure 19.2 (a) The evidence of corrosion of heat-transfer surfaces of an industrial boiler; (b) The effects of standstill corrosion.

12%; that is, below the lower limit required for the self-passivation of steel. In the final stage, the intergranular corrosion may result in pulverization of the steel – that is, a loss of material coherence and a significant decrease in its strength and ductility. A certain “supplement” of intergranular corrosion, referred to as cranny corrosion, is caused mainly by previous thermal or mechanical processing of metals, both of which have been conducted to produce specially required shapes or properties of the material. Corrosion proceeds more intensively in closely contacted areas (tight cracks, rivets, sheet metal overlaps, flanges, welds and under scratched protective coatings) than on the open surfaces of the same element. Such a phenomenon can be explained by the different concentration of liquid solutions inside the cracks, rivets, metal overlaps, flanges, and so on, as well as by limited penetration of air to those areas. The simultaneous action of aggressive agents and constant or periodically changed loads are also factors required in order for stress corrosion to occur (see Figure 19.1f). Since austenite steel is not especially resistant to any stress cracks, this type of corrosion is extremely dangerous in the case of chromium-nickel steels, with such destruction occurring in turbines and crucial boiler elements, including the steam

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drums, combustion chambers, pipelines, and the tubes and bodies of the condensers and coolers. 19.1.4 Corrosion in the Power Industry

Within the power industry, many types of corrosion have been identified, including low-temperature (below 100–300  C), high-temperature (>800  C), low-oxygen, subsurface, hydrogen, or selective (local) corrosion. This situation has in turn forced power engineers and boiler operators to develop continuous diagnostic systems, and also to control and optimize the boiler parameters so that they can predict the chemical regimes inside the system and maintain a safe and efficient operation of the combustor. Low-temperature corrosion is usually caused by the reaction between SO2 and H2O and subsequent condensation of the sulfuric acid from the flue gases. In the majority of cases, such corrosion results in pits on the boiler waterwalls and convective heattransfer surfaces. In order to minimize damages caused by this type of corrosion, it is recommended to: (i) adopt combustion techniques that require a low of excess air and high temperatures; and (ii) dry and ventilate the combustion chamber and heattransfer surfaces immediately after any cleaning activities have been completed. The application of a protective layer on the steel surface is also possible, but is usually quite expensive and thus not popular among boiler operators. Regardless of the counteraction performed to minimize corrosion damage, an important issue is also to measure the flue gas dew point temperature, in order to avoid sulfuric acid condensing in the flue gas duct during boiler operation. The rate of high-temperature corrosion is affected mainly by the composition of the fuel, the fly ash, and the flue gas. In order to minimize the negative effects of such corrosion, low-volatility fuels are normally chosen for the combustion, or special “fuel modifiers” and chemical agents may be added to modify the fuel’s properties. A positive benefit may also be achieved by modifying the combustion hydrodynamics, perhaps by replacing a few large burners by numerous small ones. A crucial point here is to control the process, so as to avoid any overheating of the boiler tubes. For safety reasons, metallographic analyses and visual inspections are conducted systematically, usually once or twice yearly for large-scale boilers. A satisfactory delay of high-temperature corrosion may also be achieved by the application of suitably coating those surfaces that are mostly exposed to corrosive and/or erosive environments.

19.2 Theory

In this section, attention will be focused on the details of metal damages, as well as on the corrosion-related effects of flue gas activities, particularly at high temperatures. In general, the corrosion of metal heat-transfer surfaces in modern boilers proceeds in

19.2 Theory

a variety of forms, as these devices have been designed to operate in different environments with respect to pressure, temperature, and mechanical and thermal stresses, as well as in the presence of aggressive chemical components. The lack of any effective surface protection chemicals is not the only reason that corrosion may proceed in a particular device; rather, the problems of corrosion of the heat-transfer surfaces are also associated with overall boiler structure and design. The type of fuel and the corresponding composition of the flue gases and ashes, as well as the materials used, the furnace height, the cross-section of the combustion chamber, and/or the design and location of the burners, also represent corrosion-generating factors that must be considered during the design and commercial operation of a boiler. For example, those boilers in which the concentration of the fly ash particles in the flue gases is high are usually “exposed” to much more serious erosion-, deposition-, fouling-, and corrosion-related problems, particularly with regards to the heat-transfer surfaces located in the convective section. A schematic of the interactions between flue gas flow and a heat-transfer surface tube is shown in Figure 19.3a. The typical deposits formed on the superheater tube bundle of a commercial circulating fluidized-bed combustor (CFBC) are shown in Figure 19.3b. The average composition of the various fuels is listed in Table 19.1. Most often, it is assumed that this information, as well as some additional data concerning the ash properties (e.g., softening temperature), are sufficient to predict fuel behavior during the combustion and, accordingly, to undertake counteractive measures to avoid or minimize the eventual corrosion. Unfortunately, as indicated by numerous data from large-scale industrial units (e.g., Refs [13–21]), these factors are not the only and dominant ones in large-scale industrial boilers, and often the laboratory procedures cannot provide any progress and correlations to the industrial data [14–16, 20]. The contradiction becomes obvious since in large-scale industrial boilers the corrosion is an extremely complicated phenomenon that is affected by numerous parameters, including the fuel type (gas, solid or liquid), the combustion rate, fuel particle residence time, the attrition rate and the formation of fines, the combustion conditions (temperature, pressure, air ratio), fuel mixing, air distribution, the heat-transfer rate, interactions between the particles, homogeneous and heterogeneous reactions, ash properties (softening, agglomeration, attrition, etc.), and – last but not least – the fuel composition (the latter parameter is particularly important when the cofiring process is implemented). These parameters are mainly dependent on the combustion conditions, and much less on the fuel characteristics. Unfortunately, due to the simplicity of the investigations the effect of all of the above factors is seldom considered during laboratory investigations and, accordingly, contradictions between the large-scale and laboratory-scale results are often reported [14–16, 21]. The above conclusion may reasonably explain many data from large-scale combustors, where the reported results of industrial tests were rather surprising and significantly different from the expectations and information provided by laboratory analyses [13–22]. In those reports, for example, the authors pointed out that the data collected from large-scale industrial combustion facilities could not be reasonably correlated. Moreover, and no satisfactory results with regards to “deposition control” could be obtained simply by taking into consideration the composition of fuel and

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Figure 19.3 (a) Factors affecting boiler heat-transfer surfaces, and their mutual interactions; (b) Example deposits in large-scale industrial combustor. This picture was taken by the authors during a boiler inspection.

flue gas and implementing some commonly used parameters, such as the base/acid ratio. The same type of coal, when burned in two facilities, may behave in completely different ways; this may mean that one facility could be operated almost perfectly, while the other would suffer difficulties and need to be redesigned [22]. As both facilities were operated at the same temperature range, the observed contradictions were most likely due to differences in the process hydrodynamics and the combustion conditions and, accordingly, the differences in residence time, mixing, heat transfer rate, local oxygen concentration, the time required for combustion of the volatile matter, and so on. In order to minimize the probability of eventual contradictions, and to eliminate these “small-scale-effects,” all of the above factors should be considered in the design phase of laboratory facilities and laboratory-scale investigations, so that the experimental conditions of the laboratory would closely match those

19.2 Theory Table 19.1 Average composition of some chosen fuels burned in industrial boilers.

Moisture (%) Ash (%) Volatiles (%) Sulfur (%) Chlorine (%) High heating value, HHV (MJ kg 1) a)

Hard coal

Straw

Woody biomass

RDF

TDF

3–15 8–20 25–35 1–3 0.01–1.5 20–28

10–20 3–8 65–80 0.02–0.05 0.1–1.5 14–17

10–30 1–5 60–75 140 mm were also observed. These different thicknesses caused by nonuniform corrosion and the formation of pits. The deposits could be easily peeled off to expose the inner base surface (see Figure 19.16), and longitudinal cracks and inclusions of copper were also visible. The presence of copper in the inner deposits (>5%, as indicated by the red areas in Figure 19.16) may provide evidence of significant erosion and corrosion of the brass tubes used to manufacture other boiler elements. It is possible to estimate the progress of corrosion on the basis of quantitative investigations (e.g., by microstructure analyses). In this case, analyses of the chemical and phase composition of the scales, as well as information relating to any changes of the material core, can provide important information to help understand the

Figure 19.15 Scanning electron microscopy images showing cross-section of a steel sample with corrosive deposits on its external surface.

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Figure 19.16 Scanning electron microscopy images showing cross-section of corrosive deposits on external surface of a superheater tube.

processes that occur on a material’s surface when exposed to a corrosive environment. For example, a microanalysis of the deposit’s chemistry and its phase composition provided important information relating to the deposit-forming components of a 13CrMoV44 steel which is generally used to construct steam superheaters (Figure 19.17). The analysis results indicated the presence of Al-, Ca-, and Scontaining ash deposits on the sample surface, with the dominant components being various oxides, whilst sulfur was detected between the iron oxides. An analysis of the chemical composition of samples is especially useful when investigating the effects of gaseous environment components on the kinetics of the corrosion process. In cases where the biomass is co-fired with coal, such an analysis would allow the effects of biomass-origin components on the corrosion process to be determined. As biomass usually contains much more alkali (mainly potassium), calcium, phosphorus and chlorine than coal, the “byproducts” of the co-combustion processes would normally increase not only corrosion of the heat-transfer surfaces but also the deposit formation rate and ash-fouling tendencies [46]. During the combustion process, alkali-, sulfur- and chlorine-containing compounds are evolved to the gas phase, where they would cause high-temperature corrosion. However, biomass cofiring should not increase the danger of erosion as the biomass ash is composed of rather fine, “soft” particles. As noted above, sulfur has been recognized as a major promoter of almost all corrosion processes; indeed, corrosion caused by sulfur and its compounds is acknowledged as being much more dangerous than oxygen-based corrosion as the growth of the scales and, accordingly, oxidation of the metal, occurs much more rapidly. The melting temperature of sulfur-containing compounds is usually low, and, accordingly, the liquid phase is easily formed in the scales. The high pressure caused by the presence of such liquids initiates intergranular corrosion. Chlorine, as another dangerous component, is usually present in most fuels as sodium chloride (e.g., biomass), and in this form it can react with SO3 to form salty

19.3 Applications in Research and Industry

Figure 19.17 (a) Microstructure and (b) composition of a 13CrMoV44 alloy steel sample. The sample was exposed to CFBC flue gases; the boiler was fired with coal only.

deposits with low-temperature eutectic mixtures. As shown in Figure 19.18, a microanalysis of steel samples indicated the presence of chlorine and sulfur compounds, as well as potassium, sodium, zinc, and lead in the scales layers. The presence of these elements favors the formation of low-temperature salty eutectics.

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Figure 19.18 (a) Microstructure and (b) composition of a 13CrMoV44 alloy steel sample. The sample was exposed to CFBC flue gases; the boiler was co-fired with a coal/biomass mixture.

The samples in Figure 19.18 were exposed to the CFBC flue gases during tests when the boiler was fired with a coal/biomass mixture. Taking the above into consideration, it is vital that a continuous monitoring be conducted for an industrial boiler, with information relating to the structure of the heat-transfer element surfaces (superheater, evaporator, etc.) being provided in order to determine the long-term effects of biomass/coal cofiring on boiler operation and corrosion, and to avoid any unexpected emergency shut-down. Whilst numerous analytical methods are recommended to estimate the kinetics and progress of corrosion processes, a gravimetric approach remains the most commonly applied. For a uniform corrosion, and also for the case when the corrosion products are transferred from the sample surface (e.g., to the gas phase), the process rate is determined by dividing the sample mass loss by the corresponding time. The same approach may, of course, be applied to the uniform corrosion processes when

19.3 Applications in Research and Industry Table 19.2 The average kinetics of oxides corrosion for various steel samples.

Sample outer surface (g m 2)

Steel sample

St37 SA192 15Mo 13CrMoV44 7CrMoVTi (P24) 10CrMo910 X20CrMoV121 TP347 HFG SA213 TP347HFG

Biomass/coal co-firing

No biomass co-fired

708 515 472 464 412 367 296 77 31

2009 1545 1000 670 373; the scales fall off 485 438 96 105

the products are deposited on a sample surface (e.g., as oxides), but in those cases the increase in sample mass is detected. The corrosion rate is estimated as the ratio of wall thickness loss versus time, and is expressed as mm per year. Some example results of the present authors’ investigations into the corrosion kinetics of various steel samples in different environments are listed in Table 19.2. The highest corrosion resistance was estimated for samples SA 213 and TP347 HFG, while the properties of X20CrMoV121 and 10CrMo910 steel samples were significantly inferior. The worst situation was detected for 7CrMoVTi, 13CrMo44, 15Mo3, SA192, and St37. Information as to whether environmental conditions favor corrosion, or not, may be obtained by determining the flue gas dew point temperature, tr. The dew point is the temperature at which a given parcel of gas (e.g., air) must be cooled, at constant barometric pressure, in order for water vapor to condense. In cases where the flue gas temperature is below that of the corresponding dew point, some of the flue gas water will condensed and be present as a liquid phase. Likewise, if acidic components are present in such environments (e.g., as NOx or SO2), then nitric, nitrous, sulfuric, and sulfurous acid solutions are formed, and the rate of corrosion of the heat-transfer surfaces is significantly increased. Today, two methods are mainly used to estimate the dew point temperature: .

.

Indirect method: This is based on the determination of tr from measurements of the concentrations of H2O and H2SO4, assuming that the dew point temperature is characterized by partial pressures of water and the sulfuric(VI) acids only, and that the effects of other flue gas components are negligible. In order to simplify the calculations, an equilibrium between the gas and H2O/H2SO4 liquid phase is also assumed. Direct method: Various methods are known, but the conductivity-based approach is normally used in industrial plants [24]. It is based on the immediate increase in the conductivity of the gas between two electrodes when the dew is formed. The temperature of the surface on which the dew is formed is also measured.

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Figure 19.19 The temperature of the dew point versus sulfur content in the fuel for various boiler types. Modified from Ref. [24].

Figure 19.20 The dew point temperature versus the air ratio for various fuels. Modified from Ref. [24].

The relationships relating the dew point temperature to the fuel sulfur content and air ratio are shown graphically in Figures 19.19 and 19.20.

19.4 Outlook

Today, the permanent goals of improving boiler operating conditions, coupled with the economics of the combustion of solid fuels of continuously downgraded qualities, is forcing the operators of industrial boilers to strive for increasingly efficient means to: (i) maintain the required and profitable power production standards; and (ii) meet the increasingly tight environmental regulations associated with the emission of flue

19.4 Outlook

gases and solid combustion byproducts (e.g., ash, slag, particulate matter). These difficulties and problems are currently undergoing extensive investigations in large, modern power production facilities, to ensure the correct design and construction of the combustor, and/or to apply proper devices and auxiliary systems. Yet, despite much progress having been made, problems relating to the efficient removal of deposits and successful corrosion management (notably of high-temperature corrosion) are yet to be brought under control. Moreover, the boiler construction in many of today’s plants is rather old, and – mainly for reasons of economy – cannot justify the incorporation of systems such as sootblowers, electrostatic precipitators (ESPs), or desulfurization and denitrification plants. In fact, such facilities are normally equipped with stoker boilers where, particularly for those burning hard coal as the basic fuel, methods for the easy and efficient control of combustion conditions have long been sought. The determination of material properties represents one of the main approaches to estimating the properties and actual structure of an element (e.g., the heat-transfer surface). For those materials used to manufacture the elements exposed to boiler flue gases, procedures to determine the material properties are based on the following factors: . .

.

.

.

Analysis of the operational history. Estimation of the basic mechanical properties at some temperatures (usually ambient and one or two higher values). Attribution of individual material coefficients to the corresponding structures, based on the data possessed. Estimation of a real operation temperature of a particular element, based on determination of the scales thickness at the tube surface. Analysis of chemical and phase composition of the deposits.

The above research tasks will allow a detailed analysis to be conducted of the current material properties, and to estimate the conditions for their further safe use in real operational conditions of the industrial boiler. A suggested procedure to control and manage corrosion problems is shown in Figure 19.21. The methods used to protect equipment in power or heat/power stations against corrosion are, in principle, no different from those used in other industrial sectors. As the oxygen dissolved in water represents one of the fundamental factors affecting the corrosion processes in combined heat and power (CHP) plants, its removal from the feed water offers a fundamental method of protecting equipment against corrosion. Removal of the oxygen is normally achieved by: (a) thermal release of the gas; (b) sulfation; (c) binding the oxygen with hydrazine; or (d) displacing it by another gas. Sulfation is based on the reaction between water and sodium sulfate (IV); the latter reacts with oxygen dissolved in water to form sodium sulfate (VI), according to the reaction: 2Na2 SO3 þ O2 ! 2Na2 SO4

ð19:10Þ

For solution deoxidation, the gaseous SO2, or sodium hydrosulfate (IV) may also be used. Other applicable methods include those employing various metal oxidation inhibitors are used. Carbonic acid represents the main factor affecting in particular the

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Figure 19.21 The procedure to control and manage the corrosion problems of the heat-transfer surfaces of industrial boilers.

elements of the feeding facilities, such as degassers, preheaters, or pumps. At higher temperatures and higher concentrations of hydrogen ions (i.e., for pH  7), and conditioned by the presence of dissolved carbonic acid, hydrogen may be generated. In that case, protection will be focused on increasing the pH above 7 (i.e., an alkaline environment). Quite often, ammonia is introduced into the feed water to protect the boiler elements against corrosion. In this case, the amount of ammonia will be that required by the stoichiometric formation conditions of acidic ammonium carbonate. The increase in pH brought about by introducing the ammonia, however, does not affect the pH rise of the water, as the ammonia can be removed with steam. In order to select the material for boiler heat-transfer surfaces – and particularly for devices that will be exposed to steam (e.g., superheaters, steam pipelines, etc.) – the estimated heat flux must also be calculated and taken into consideration. Carbon steels, for example, are not suitable if the wall temperature is to be >500  C, whereas low-alloyed chromium and molybdenum steels are recommended as superheated steam corrosion-resistant materials if the wall temperatures are to be