Air Pollution and Its Complications: From the Regional to the Global Scale (Springer Atmospheric Sciences) [1st ed. 2021] 3030705080, 9783030705084

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Springer Atmospheric Sciences

Shani Tiwari Pallavi Saxena   Editors

Air Pollution and Its Complications From the Regional to the Global Scale

Springer Atmospheric Sciences

The Springer Atmospheric Sciences series seeks to publish a broad portfolio of scientific books, aiming at researchers, students, and everyone interested in this interdisciplinary field. The series includes peer-reviewed monographs, edited volumes, textbooks, and conference proceedings. It covers the entire area of atmospheric sciences including, but not limited to, Meteorology, Climatology, Atmospheric Chemistry and Physics, Aeronomy, Planetary Science, and related subjects. More information about this series at http://www.springer.com/series/10176

Shani Tiwari • Pallavi Saxena Editors

Air Pollution and Its Complications From the Regional to the Global Scale

Editors Shani Tiwari Geological Oceanography Division CSIR-National Institute of Oceanography Dona Paula, Goa, India

Pallavi Saxena Department of Environmental Sciences, Hindu College University of Delhi New Delhi, Delhi, India

ISSN 2194-5217     ISSN 2194-5225 (electronic) Springer Atmospheric Sciences ISBN 978-3-030-70508-4    ISBN 978-3-030-70509-1 (eBook) https://doi.org/10.1007/978-3-030-70509-1 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

TO LOVELY PARENTS For raising me to believe that everything is possible & TO SPOUSE AND KID For their Love and Support

Acknowledgements

Dr. Shani Tiwari acknowledges the director of CSIR-National Institute of Oceanography (NIO), Goa, India. Dr. Pallavi Saxena acknowledges Dr. Anju Srivastava, Principal, Hindu College, University of Delhi, Delhi, India. Her sincere thanks to her husband, Dr. Saurabh Sonwani, for his constant help and assistance in collecting the literature available for the book. She also wants to express her deep gratitude to her loving parents, Dr. Akhilesh Saxena and Dr. Neelima Priyadarshini, for their constant support, encouragement, and love.

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Contents

1 Introduction����������������������������������������������������������������������������������������������    1 Shani Tiwari and Pallavi Saxena 2 Transport Mechanisms, Potential Sources, and Radiative Impacts of Black Carbon Aerosols on the Himalayas and Tibetan Plateau Glaciers ����������������������������������    7 Lekhendra Tripathee, Chaman Gul, Shichang Kang, Pengfei Chen, Jie Huang, and Mukesh Rai 3 Impact of Urban and Semi-urban Aerosols on the Cloud Microphysical Properties and Precipitation������������������   25 Jagabandhu Panda and Sunny Kant 4 Aerosol Characteristics and Its Impact on Regional Climate Over Northern India ����������������������������������������������������������������   37 Pradeep Kumar, Arti Choudhary, Vineet Pratap, Pawan K. Joshi, and Abhay Kumar Singh 5 Impacts of Air Pollution on Himalayan Region������������������������������������   57 Palak Balyan 6 Human-Associated Potential Risk of Metal-Bound Fine Particulate Matter ��������������������������������������������������������������������������   87 Atar Singh Pipal, Kalpana Rajouriya, and Ajay Taneja 7 Potential Impacts of Gaseous Air Pollutants on Global Crop Yields Under Climate Change Uncertainties and Urbanization��������������������������������������������������������������  109 Madhavi Jain

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8 Impacts of Air Pollutants on Forest Ecosystem and Role in Ecological Imbalance����������������������������������������������������������  129 Savita 9 Green Technologies to Combat Air Pollution����������������������������������������  143 Maryam Sarfraz 10 Urban Mobility Associated Ambient Air Quality and Policies for Environmental Implications����������������������������������������  163 Arti Choudhary, Pradeep Kumar, Anuradha Shukla, and Pawan K. Joshi Index������������������������������������������������������������������������������������������������������������������  177

Editors and Contributors

About the Editors Shani Tiwari is a scientist and working at the National Institute of Oceanography, Goa, India. He received his doctorate degree from Banaras Hindu University. After his doctorate, he served at Graduate School of Environmental Studies, Nagoya University, Japan, as a designated assistant professor. He also worked at the Physical Research Laboratory, Ahmedabad, India, and the Environmental Research Institute, Shandong University, Qingdao, China, as postdoctoral fellow. His research focuses on sedimentary black carbon, marine aerosol, environmental pollution, and climate change. He has published 34 peer-reviewed research articles and book chapters in international/national journals with h/i10 – index 13/15 and has also delivered several oral and poster presentations, along with an invited talk, in various national/ international conferences/meetings. He also serves as a reviewer for several peer-­ reviewed research journals.  

Pallavi  Saxena is an assistant professor of environmental science at the Hindu College, University of Delhi, Delhi, India. She has been awarded DST Fast Track Young Scientist position at the School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, India. She has completed her postdoc at the Space and Atmospheric Sciences Division, Physical Research Laboratory (PRL), Ahmedabad, India. She has completed her studies and obtained her Doctor of Philosophy in Environmental Science degree from the University of Delhi. Dr. Pallavi has defended her Ph.D. thesis “Effect of Photochemical Pollutants on Plant Species.” Her area of interest is air pollution and plant physiology, and she has been working in this area since 18 years. She has been elected as chair of South Asia and Middle East Region of Early Career Scientist Network of iLEAPS community, UK. She has also been awarded Jawaharlal Nehru Doctoral Scholarship; CSIR SRF, Young Scientist Award-ISPP; and DBT BioCaRe Award during her research career. Dr. Saxena has published 25 research papers in high impact factor journals and published 4 books  

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in the field of air pollution and plant health with Springer and CABI publishers. She is also a co-author and collaborator from India at TOAR International Meeting 2015 onwards. Dr. Saxena has also served as reviewer in various internationally reputed journals such as Atmospheric Environment, Environmental Pollution, Atmospheric Pollution Research, and Environmental Science and Pollution Research. She has been selected as review editor of Climate Change and Cities of the journal Frontiers of Sustainable Cities.

Contributors Palak  Balyan  Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, Delhi, India Pengfei Chen  State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, China Arti  Choudhary  Transport Planning and Environment Division, CSIR-Central Road Research Institute, New Delhi, Delhi, India Environment Climate Change & Public Health, Utkal University, Bhubaneswar, Odisha, India Chaman  Gul  Reading Academy, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China Jie  Huang  CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, China Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China Madhavi  Jain  School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, Delhi, India Pawan K. Joshi  School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, Delhi, India Shichang Kang  State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, China CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, China University of Chinese Academy of Sciences, Beijing, China Sunny  Kant  Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, Delhi, India Pradeep Kumar  School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, Delhi, India

Editors and Contributors

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Department of Physics, Institute of Science, Banaras Hindu University, Varanasi, India Jagabandhu  Panda  Department of Earth and Atmospheric Sciences, National Institute of Technology Rourkela, Rourkela, Odisha, India Atar Singh Pipal  Department of Chemistry, Dr. Bhimrao Ambedkar University, Agra, Uttar Pradesh, India Vineet  Pratap  Department of Physics, Institute of Science, Banaras Hindu University, Varanasi, India Mukesh Rai  State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, China University of Chinese Academy of Sciences, Beijing, China Kalpana Rajouriya  Department of Chemistry, Dr. Bhimrao Ambedkar University, Agra, Uttar Pradesh, India Maryam Sarfraz  Institute of Environmental Sciences and Technology, National University of Sciences and Technology, Islamabad, Pakistan Savita  Department of Botany, Hindu College, University of Delhi, New Delhi, Delhi, India Pallavi Saxena  Department of Environmental Sciences, Hindu College, University of Delhi, New Delhi, Delhi, India Anuradha Shukla  Transport Planning and Environment Division, CSIR-Central Road Research Institute, New Delhi, Delhi, India Abhay Kumar Singh  Department of Physics, Institute of Science, Banaras Hindu University, Varanasi, India Ajay Taneja  Department of Chemistry, Dr. Bhimrao Ambedkar University, Agra, Uttar Pradesh, India Shani  Tiwari  Geological Oceanography Division, CSIR-National Institute of Oceanography, Dona Paula, Goa, India Lekhendra Tripathee  State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, China Himalayan Environment Research Institute, Kathmandu, Nepal

Chapter 1

Introduction Shani Tiwari and Pallavi Saxena

Abstract  Air pollution is the most critical issue among the global scientific communities, and its continuously increasing trend due to rapid urbanization and economic development-associated energy demands causes an alarming condition for all living organisms. It has significant potential to impact air quality, human health, crop production, monsoonal circulation, and, hence, the hydrological cycle along with Earth’s climate system also. This chapter presents a brief summary of various aspects of air pollution discussed in different chapters of the book. This chapter also suggests a reconsideration of new air pollution mitigation policies and effective legislative laws along with the implementation of green technologies in terms of long-term future prospects. Keywords  Air pollution · Climate change · Human health

1.1  Background As we are all aware, air pollution is one of the major threats of the twenty-first century for all human beings and living organisms. The rapid increase in population growth and industrialization during the last few decades (mainly over south and east Asian countries) causes a large burden of atmospheric pollutants which have detrimental effects on air quality, human health, crop production, monsoonal circulation, and, hence, hydrological cycle, as well as climate change also (Mahowald 2011; Boucher et al. 2013; IPCC 2013; Raspanti et al. 2016; Seinfeld et al. 2016; Tiwari et  al. 2019; Liu et  al. 2019; Saxena and Srivastava 2020). The World Health Organization (WHO) report suggests that nearly 90% of the total world population is exposed to polluted air (annual PM2.5  ~  10  μg/m3) (WHO 2018), resulting in S. Tiwari (*) Geological Oceanography Division, CSIR-National Institute of Oceanography, Dona Paula, Goa, India P. Saxena Department of Environmental Sciences, Hindu College, University of Delhi, New Delhi, Delhi, India © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. Tiwari, P. Saxena (eds.), Air Pollution and Its Complications, Springer Atmospheric Sciences, https://doi.org/10.1007/978-3-030-70509-1_1

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millions of premature deaths (Lelieveld et al. 2015) with the global burden of the annual cost of nearly 225 billion USD (World Bank 2016). Recently, Chowdhury and Dey (2016) reported more than half a million premature deaths in India because of air pollution, while nearly seven million annual premature deaths are reported on a global scale (WHO 2018). Several studies reported that the exposure to these air pollutants causes a number of deadly diseases and illnesses, e.g., asthma, lung disease, chronic obstructive pulmonary disorder (COPD), and cardiovascular and heart disease (Deng et al. 2017; Sonwani and Kulshrestha 2019). Recently Smith et al. (2020) found that a higher risk of preterm and stillbirth in London is directly associated with air pollution. Aside from human beings, air pollution is also harmful to vegetation and plants, resulting in the reduction of crop yields (Burney and Ramanathan 2014; Saxena et al. 2020; Saxena and Sonwani 2020). Many air pollutants (like black carbon and dust) can deposit on snow and hence trap the heat resulting in a reduction of surface albedo (Zhang et al. 2018). Methane (CH4) is reported as the second most significant contributor to anthropogenic radiative forcing (RF) after CO2 (IPCC 2013). The air pollutants are broadly divided into two major types, i.e., ambient/outdoor air pollutants which include ozone, SO2, CH4, and particulate matters and indoor air pollutants which include mainly gaseous pollutants (e.g., NO2, CO) and ultrafine particles. These pollutants are mainly emitted from the primary (both natural and anthropogenic) as well as secondary emission sources (gas to particle conversion), having a large lifetime span from few minutes to several days (Sonwani and Saxena 2016). The pollutants having a relatively larger lifetime could travel over a large distance and affect the air quality and cause global climate through different atmospheric processes. Particulate matters (PM: also known as aerosols) are one of the major important pollutants present in the atmosphere and influence the Earth’s system directly/indirectly (Sonwani and Kulshrestha 2018). Recent results demonstrate significant seasonal variability of PM based on the complex combination of anthropogenic factors mixed with the contribution from the natural sources (like dust), particularly during the summer season (Tiwari et  al. 2015), resulting in considerable changes in the regional monsoonal circulation pattern and also the global climate system (Bollasina et al. 2011; Tiwari et al. 2013; Wang et al. 2019). In developing countries (like India, China, Brazil), an increasing trend in air pollutants is reported by several studies where industrial emission, transportation, and coal combustions are the major sources of air pollutants (Eduardo et al. 2019; Pant et al. 2019; Liu et al. 2019; Saxena et al. 2019). Due to the assimilation of observations through different research programs along with the climate models also, the uncertainties in quantifying the climate impact of air pollutants have been improved during the last decades but not up to the desired level, particularly at a regional scale (IPCC 2013). The Intergovernmental Panel on Climate Change (IPCC 2013) reported net global warming (positive radiative forcing +2.29 w/m2) due to various air pollutants present in the atmosphere (Fig.  1.1). The greenhouse gases cause a net positive radiative forcing, i.e., warming effect with a relatively higher level of scientific understanding, while net radiative forcing due to the atmospheric aerosol (particularly cloud adjustment due to various types of aerosol) is negative (i.e., showing

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Fig. 1.1  Global radiative forcing of various air pollutants for the period 1750–2011. (Adopted from the IPCC 2013)

cooling effect) associated with large uncertainty. This uncertainty is mainly attributed to a variety of aerosol emission sources and extreme heterogeneity in the spatial and temporal variability of their optical and microphysical characteristics.

1.2  Summary of the Chapters Based on the different issues of air pollution discussed above, the understanding of air pollution, mainly over the developing countries, is not up to a satisfactory level and is associated with large uncertainty because of the various emission sources and atmospheric mechanisms. The present book covers almost all the important topics related to air pollutions, their emission sources, impacts, cost-effective technologies, and mitigation policies. The present chapter, i.e., this chapter, provides a brief introduction about the air pollutions, types, and emission sources of air pollutants along with various detrimental effects on air quality, human health, agriculture, and climate change on a regional as well as global scale. Chapter 2 describes the long-­ range transportation and possible deposition mechanisms of black carbon (BC) over the Himalayan and Tibetan Plateau (HTP) regions. This chapter suggests that the HTP region experienced maximum and minimum BC concentration during dry

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pre-­ monsoon and monsoon seasons, respectively. In this chapter, the climatic impacts of BC in the atmosphere and cryosphere are also discussed. This chapter also includes some of the preliminary results from the research network Atmospheric Pollution and Cryospheric Change (APCC) on BC transport to the HTP regions. Chapter 3 deals with a brief review of the various effects of aerosol on cloud microphysical properties. The chapter briefly describes the formation and growth of clouds under the different thermodynamic states of the atmosphere which is directly/ indirectly perturbed by the different types of aerosols. The impacts of aerosol-cloud interaction on the Earth’s radiation budget and precipitation efficiency are also discussed in this chapter. Chapter 4 provides a comprehensive study of particulate matters over Indo-Gangetic Plain (IGP). This chapter deals with detailed information about the seasonal variability of particulate matter (PM10 and PM2.5) concentration (μg/m3), their emission, and chemical composition along with long-range transportation. This chapter also validates the satellite-observed data with in situ measurement which will help to estimate the surface aerosol concentration at remote locations where in situ measurements are not possible due to various constraints. Chapter 5 summarizes the air pollution level over the Himalayan region which has a significant increasing trend associated with a large seasonal as well as topographical variability. The emission sources of air pollutants near the Himalayan region and their transportation mechanism are also discussed. This chapter also discusses the various effects of air pollution over this region and different mitigation strategies to overcome it. Chapter 6 emphasizes a brief review of the adverse health effects (such as heart disease, lung cancer, and reduced lung capacity) of air pollution worldwide. In this chapter, the emission sources of metals associated with fine particles and related diseases are also discussed. This chapter summarizes the assessment of the potential risks to human health related to environmental exposures of metals allied with airborne particles. Chapter 7 deals with the direct consequences of gaseous air pollutants and atmospheric chemistry on crop yields. This chapter also suggests a positive correlation between crop production and crop yields which is well associated with increasing food demand. This chapter also describes the impacts of increasing population, urbanization, and climate change on global crop production. Chapter 8 provides a brief introduction about the various air pollutants (like particulate matter, O3, SOx, NOx, VOC, etc.) and their effects on vegetation as well as forest ecosystem also. The role and mechanism of these pollutants in ecological imbalance are also briefly discussed in this chapter. Chapter 9 deals with different cost-­effective technologies used for air pollution mitigation. However, Chap. 10 discusses the role of transport sectors (especially in urban cities like Delhi, Beijing, etc.) in air pollution, hence air quality and associated health risks. This chapter suggests a serious crisis of urban mobility, and long-term effective policies/legislative laws should be implemented by the policymakers. This chapter also briefly discusses the different transport policies implemented by the Government of India for better air quality and human health.

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1.3  Conclusions Based on several studies, the present book concludes that air pollution in developing countries is still increasing even after the adoption of several mitigation policies and green technologies. Thus, with the rapid increase in industrialization and economic development in the developing countries region, additional consideration should be paid, and effective environmental policies and legislative laws in the long-term future perspective are highly needed. At a time, when air pollution has become a global crisis, we realize that our current generation should have more attention to it. Therefore, the main desire of the present book is to motivate, inspire, and educate students, colleagues, and policymakers for the better amendment of air pollution and their mitigations. The different chapters in the present book explain the various emission sources of air pollutants, their impacts on several aspects like human health, environment crop production, climate change along with the different cost-­ effective technologies, and policies to combat air pollution.

References Bollasina MA, Ming Y, Ramaswamy V (2011) Anthropogenic aerosols and the weakening of the South Asian summer monsoon. Science 334(6055):502–505 Boucher O, Randall D, Artaxo P, Bretherton CS (2013) Chapter 7: clouds and aerosols. In: Biomass. Cambridge University Press, Cambridge, pp  571–658. https://doi.org/10.1017/ CBO9781107415324.016 Burney J, Ramanathan V (2014) Recent climate and air pollution impacts on Indian agriculture. PNAS 111(46):16319–16324 Chowdhury S, Dey S (2016) Cause-specific premature death from ambient PM2.5 exposure in India: estimate adjusted for baseline mortality. Environ Int 91:283–290 Deng Q, Lu C, Jiang W, Zhao J, Deng L, Xiang Y (2017) Association of outdoor air pollution and indoor renovation with early childhood ear infection in China. Chemosphere 169:288–296 Eduardo CA, Evandro SO, Elaine SL, ASG J, Nivaldo AC, Luis GN, Mônica LA (2019) Analysis and visualization of multidimensional time series: particulate matter (PM10) from São Carlos-SP (Brazil). Atmos Pollut Res 10(4):1299–1311 IPCC (2013) IPCC fifth assessment report, climatic change 2013: the physical science basis. The Intergovernmental Panel on Climate Change. https://doi.org/10.1017/CBO9781107415324 Lelieveld J, Evans JS, Fnais M, Giannadaki D, Pozzer A (2015) The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature 525:367–371 Liu K, Wang F, Li J, Tiwari S, Chen B (2019) Assessment of trends and emission sources of heavy metals from the soil sediments near the Bohai Bay. Environ Sci Pollut Res 26:29095–29109 Mahowald N (2011) Aerosol indirect effect on biogeochemical cycles and climate. Science 334(6057):794–796 Pant P, Lal RM, Guttikunda SK, Russell AG, Nagpure AS, Ramaswami A, Peltier RE (2019) Monitoring particulate matter in India: recent trends and future outlook. Air Qual Atmos Health 12(1):45–58 Raspanti GA, Hashibe M, Siwakoti B, Wei M, Thakur BK, Pun CB, Al-Temimi M, Lee YCA, Sapkota A (2016) Household air pollution and lung cancer risk among never-smokers in Nepal. Environ Res 147:141–145

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Saxena P, Sonwani S (2020) Remediation of ozone pollution by ornamental plants in indoor environment. Glob J Environ Sci Manage 6(4):497–508 Saxena P, Srivastava A (2020) Air pollution and environmental health, vol 20. Springer, Singapore Saxena P, Shukla A, Srivastava A (2019) Assessment of black carbon profiles and on-road emission factors at busy traffic intersection site in capital city of India. ATMOS 2019, Istanbul, Turkey, pp 571–579 Saxena P, Chakraborty M, Sonwani S (2020) Phytotoxic effects of surface ozone exposure on rice crop – a case study of tropical megacity of India. J Geosci Environ Protect 8(5):322–334 Seinfeld JH, Bretherton C, Carslaw KS, Coe H, DeMott PJ, Dunlea EJ, Feingold G, Ghan S, Guenther AB, Kahn R, Kraucunas I, Kreidenweis SM, Molina MJ, Nenes A, Penner JE, Prather KA, Ramanathan V, Ramaswamy V, Rasch PJ, Ravishankara AR, Rosenfeld D, Stephens G, Wood R (2016) Improving our fundamental understanding of the role of aerosol−cloud interactions in the climate system. PNAS 113(21):5781–5790 Smith RB, Beevers SD, Gulliver J, Dajnak D, Fecht D, Blangiardo M, Douglass M, Hansell AL, Anderson HR, Kelly FJ, Toledano MB (2020) Impacts of air pollution and noise on risk of preterm birth and stillbirth in London. Environ Int 134:105290 Sonwani S, Kulshrestha U (2018) Morphology, elemental composition and source identification of airborne particles in Delhi, India. J Indian Geophys Union 22(6):607–620 Sonwani S, Kulshrestha UC (2019) PM10 carbonaceous aerosols and their real-time wet scavenging during monsoon and non-monsoon seasons at Delhi, India. J Atmos Chem 76(3):171–200 Sonwani S, Saxena P (2016) Identifying the sources of primary air pollutants and their impact on environmental health: a review. IJETR 6(2):111–130 Tiwari S, Srivastava AK, Singh AK (2013) Heterogeneity in pre-monsoon aerosol characteristics over the Indo-Gangetic Basin. Atmos Environ 77:738–747 Tiwari S, Srivastava AK, Singh AK, Singh S (2015) Identification of aerosol types over Indo-­ Gangetic Basin : implications to optical properties and associated radiative forcing. Environ Sci Pollut Res 22(16):12246–12260 Tiwari S, Kumar A, Pratap V, Singh AK (2019) Assessment of two intense dust storm characteristics over Indo – Gangetic basin and their radiative impacts: a case study. Atmos Res 228:23–40 Wang H, Xie SP, Kosaka Y, Liu Q, Du Y (2019) Dynamics of Asian summer monsoon response to anthropogenic aerosol forcing. J Clim 32:843–858 World Bank (2016). http://www.worldbank.org/en/news/press-­release/2016/09/08/ air-­pollution-­deaths-­cost-­global-­economy-­225-­billion World Health Organization (2018). www.who.int/airpollution/data Zhang Y, Kang S, Sprenger M, Cong Z, Gao T, Li C, Tao S, Li X, Zhong X, Xu M, Meng W, Neupane B, Qin X, Sillanpää M (2018) Black carbon and mineral dust in snow cover on the Tibetan Plateau. Cryosphere 12:413–431

Chapter 2

Transport Mechanisms, Potential Sources, and Radiative Impacts of Black Carbon Aerosols on the Himalayas and Tibetan Plateau Glaciers Lekhendra Tripathee, Chaman Gul, Shichang Kang, Pengfei Chen, Jie Huang, and Mukesh Rai

Abstract  Black carbon (BC) is a light-absorbing particle in the atmosphere, which can heat the atmosphere by absorbing solar radiation and changing the surface snow albedo after deposition. Fossil fuel and biomass burning are contributed significantly to BC loading. This chapter presents the characteristics, potential source L. Tripathee (*) State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, China Himalayan Environment Research Institute, Kathmandu, Nepal C. Gul Reading Academy, Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China S. Kang State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, China CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, China University of Chinese Academy of Sciences, Beijing, China P. Chen State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, China J. Huang CAS Center for Excellence in Tibetan Plateau Earth Sciences, Beijing, China Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China M. Rai State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences (CAS), Lanzhou, China University of Chinese Academy of Sciences, Beijing, China © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. Tiwari, P. Saxena (eds.), Air Pollution and Its Complications, Springer Atmospheric Sciences, https://doi.org/10.1007/978-3-030-70509-1_2

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regions, and transport mechanisms of BC aerosols and their radiative impacts on cryospheric change on the Himalayas-Tibetan Plateau (HTP) (also named the Third Pole) region. We reviewed the several past studies from the region on BC mass concentration in the ambient air as well as in the glaciers (surface snow and ice) and snow cover over the fragile Third Pole region. Further, a comparison of the concentrations of BC in the surface snow and ice, potential source regions, and radiative impacts is reviewed. The preliminary results overview from the research network Atmospheric Pollution and Cryospheric Change (APCC) on BC transport to the HTP is discussed. BC particles emitted from South Asia, their transport, and deposition have a significant impact on the HTP glaciers and snow cover. The maximum and minimum mass concentration of BC was reported in dry pre-monsoon and monsoon seasons, respectively. BC deposition on glaciers could potentially reduce the surface albedo and accelerate surface snow/ice melting. Glaciers located in HTP being an essential source of fresh water for the millions of populations in the Asian region and the retreat of these glaciers will have far-reaching consequences. Keywords  Black carbon · Aerosols · Long-range transport · Himalayas · Tibetan Plateau · Cryosphere · Radiative impacts · Albedo reduction

2.1  Background Light-absorbing particles (LAPs) such as black carbon (BC), mineral dust, and water-insoluble organic carbon (WIOC) play a vital role in glacier and snow cover retreat by significantly reducing the surface albedo. Deposition of BC particles and dust on highly reflecting surfaces (snow, ice, and glacier) can significantly reduce the surface albedo and accelerate glacier/snow cover melting (Li et al. 2018a; Zhang et al. 2018). However, here we will focus on BC, which is a carbonaceous particle emitted from coal-fired power plants and incomplete combustion of biomass and fossil fuel. Carbonaceous aerosols, including BC, are the major particles in the atmosphere and are hot research areas in recent years due to its light absorption, radiative properties (Rai et al. 2019), and health impacts. It has been observed that BC particles play a vital role in climate change (IPCC 2007) and are identified as the second most significant contributor to anthropogenic radiative forcing (RF) (Jacobson 2001). It can induce significantly higher regional RF than carbon dioxide and methane (Chung et  al. 2010), mainly due to its nonuniform spatial and temporal distribution. The global mean forcing due to BC particle-induced snow darkening was estimated as +0.1 ± 0.1 W m−2, which offsets around 20% of the cooling due to aerosols at the top of the atmosphere (IPCC 2007).

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A past study has suggested that the contribution of biofuel combustions and fossil fuels was about 4.6 TgC year−1 and 3.3 TgC year−1, which was from open biomass burning (Bond et al. 2004). An increasing trend in BC mass concentration has been reported during the last 20 years (Cong et al. 2015a; Xu et al. 2009). Besides atmospheric impacts, BC particles present in the atmosphere have several other impacts such as human health effects, ecosystem damage, poor visibility, agricultural productivity, and global warming. Also, BC can affect the climate and cryosphere directly and indirectly by absorbing the solar radiation (Li et  al. 2017). Moreover, BC is capable of long-range transport and is deposited on the surface of the snow, ice, and glaciers via wet and dry deposition processes. Furthermore, modeling and simulation results have also shown an increasing trend of BC in the Tibetan Plateau (TP) mainly due to high deposition over the surface of glaciers (Qian et  al. 2011; Yang et  al. 2018). Therefore, BC in the atmosphere and cryosphere has attracted significant public interest in recent years. The HTP and its surroundings also referred to as the “Third Pole” are one of the crucial, fragile, and complex mountainous regions, which plays a dynamic role in driving the regional, Asian, or even the global climate system (Kang et al. 2010; Yao et  al. 2012). Glaciers located in the Third Pole region are a vital source of fresh water for the people living downstream of countries such as China, India, Pakistan, Afghanistan, Nepal, Bhutan, and Bangladesh. Further, the Himalayan region is often referred to as the “water towers of Asia” (Tripathee et al. 2016). More than 1.3 billion people are fed by the major rivers originating in the region; fresh water supplied to the region can be attributed to snow and glacier meltwater (Brown et al. 2014). Therefore, pollutants such as mercury, dissolved organic carbon (Dockery and Pope 1994), and BC carried from polluted areas to the pristine region can significantly impact on the freshwater resources (Li et al. 2018b; Tripathee et al. 2019) and influence the ecosystem. Hence, continuous monitoring of BC particles in the atmosphere and cryosphere is crucial for understanding its variability, radiative impacts, and climate change characteristics. This can help us to formulate a policy aiming to reduce atmospheric pollution over the HTP. Furthermore, the sources and transport mechanisms of BC aerosols are also critical to understand the pathways and source regions of such pollutants to the high-altitude pristine environment to formulate the appropriate control strategies in the region. Therefore, this chapter will provide in-depth knowledge of the BC levels, sources, and transport mechanisms over the Himalayas and TP and their impacts on glaciers in the region. Furthermore, here we also discuss the recent preliminary results from the trans-boundary research network called Atmospheric Pollution and Cryospheric Change (APCC) from the region.

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2.2  S  patial Distribution of BC Mass Concentrations in the Himalayas-TP Atmosphere The southern slope of the Himalayas is adjacent to India, where the climate is relatively humid and warm under the influence of the Indian summer monsoon. On the other side, the northern side is relatively dry and cold because the warm and humid airflow cannot reach it. The atmospheric observatories measuring BC particles in different seasons on both sides of the Himalayas were reviewed. The concentration of BC in the atmosphere (over a specific location) depends on several parameters. The meteorological parameters, i.e., air temperature, air pressure, humidity, wind speeds, and wind directions, are essential to identify the diurnal variation of BC particles over a specific site. The strength and direction of valley winds in complex topography are crucial in understanding the diurnal variation of BC particle in the atmosphere. Average ambient BC mass concentrations in the TP and surrounding regions are given in Fig. 2.1. The average BC mass concentrations in the selected sites varied between 0.048 μg m−3 and 14.5 μg m−3. The highest and lowest level of BC particle was reported in Katmandu (14.5 μg m−3) (Putero et al. 2015) and Qilian Shan Mountain (0.048 μg m−3) (Zhao et al. 2012), respectively. Katmandu is one of the largest urban cities in Nepal, and Qilian Shan is a remote mountain region in China. Data presented in Fig. 2.1 was measured by different methods such as AE-33 and sunset (total suspended particulate (TSP), particulate matter (PM10, PM2.5)). The sampling period was also different for different sites (Table 2.1). The concentration levels of BC at Yala were compared with other observation sites in the region. Comparison report showed that BC mass concentration results at Yala site were comparable to Qomolangma (Mt. Everest) (QOMS) (Chen et al. 2018) and higher than those of western China (Cao et al. 2009), Mt. Everest (QOMS) (Cong et al. 2015a), and central and northeastern TP (Ming et al. 2010) and much lower than Manora Peak (Ram et al. 2010) and Darjeeling (Sarkar et al. 2015). The BC mass concentrations from the southeastern TP Tengchong (Engling et  al. 2011) and Lulang (Zhao et al. 2013) were also higher than those at Yala, possibly due to the higher contribution of biomass burning (Zhao et al. 2013). The Manora Peak, high altitude site in western India and Kathmandu, an urban valley, is relatively closer to the populated areas of South Asia, heavily influenced by anthropogenic emissions, long-range transport, and local emission sources, respectively. BC concentrations appear to be far lower than those in rural background areas around the world, differences among methods notwithstanding. BC mass concentrations in the interiors of the continents are far higher than those in polar regions simply because BC is mainly anthropogenic in origin. The contribution from biomass burning plays a vital role in BC concentration variation. In several places, it was observed that BC concentrations were significantly higher due to biomass burning in the region (Zhao et  al. 2013). Anthropogenic emissions heavily influence the sites that are at lower altitudes and are closer to the populated areas of South Asia. Generally, the high altitude sites on both sides of the Himalayas exhibit similar BC levels, which could be

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Fig. 2.1  Distribution of black carbon mass concentrations over the Himalayas and the Tibetan Plateau atmosphere

considered as a regional background value and used in the regional climate model as input parameters.

2.3  S  patial Distribution of BC Aerosol in the Himalayas-TP Cryosphere The concentration of BC in glaciers is not constant throughout the whole TP glaciers. Depending on the season, meteorological condition, geographical location, and nearby source location, the concentrations of BC particles are changing. In dry seasons, long-range transported pollution, including BC (Yasunari et  al. 2010),

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Table 2.1  Comparison of annual average BC concentrations at Yala with those at other sites in the surrounding region Station NCO-P Yala glacier

Altitude Country (m) Period Nepal 5079 Mar 2006–Feb 2008 Nepal 4900 Oct 2016–Oct 2017

Qomolangma Nam Co Hanale Langtang Mukteshwar Darjeeling Nagarkot Katmandu Muztagh Ata Linzhi Manora Peak Ranwu Qilian Shan

Nepal China India Nepal India India Nepal Nepal China China India China China

4276 4730 4520 3920 2286 2200 2150 1380 4500 3300 1950

BC (μg m−3) References 0.16 Marinoni et al. (2010) 0.38 Gul et al. (2021) under review May 2015–May 2017 0.298 Chen et al. (2018) 0.08 Ming et al. (2010) Aug 2009–Jul 2010 0.077 Babu et al. (2011) Dec 1998–Oct 2000 0.52 Carrico et al. (2003) Sep 2005–Sep 2007 0.81 Hyvärinen et al. (2009) Jan 2010–Dec 2011 3.45 Sarkar et al. (2015) Dec 1998–Oct 2000 1.0 Carrico et al. (2003) Pre-monsoon 2013 14.5 Putero et al. (2015) Dec 2003–Feb 2005 0.055 Cao et al. (2009) Nov, Dec 2008 0.7 Cao et al. (2010) Feb 2005–Jul 2008 10–760 Ram et al. (2010) Nov 2012–Jun 2013 0.139 Wang et al. (2016) May 2009–Mar 2011 0.048 Zhao et al. (2012)

Fig. 2.2  Spatial distribution of black carbon (ng g−1) in surface snow, ice in the Himalayas-Tibetan Plateau (Gul et al. 2021, in preparation)

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moves over the glacier surface deposited on snow/ice and increases the concentration of these pollutants at surface layer snow. BC mass concentration on various glaciers of the TP is shown in Fig. 2.2. Glacier samples collected from accumulation zones had relatively low BC content as compared to samples obtained from ablation zones of a glacier. Li et al. (2017) found a strong negative relationship between the elevation of glacier’s sampling locations and the concentration of BC particles. The melting rate of surface snow and glacier is higher in the ablation zone as compared to the accumulation zone mainly due to high pollution concentration. Besides the reasons mentioned above for the spatial variation of BC particles in a glacier, one crucial aspect is an analysis and sampling method. The concentration of BC on presented glacier sites in Fig. 2.2 had a different sampling technique (thermal optical analysis and single particle soot photometer (SP2)). According to our understanding, elevation of the sampling site, distance from the emission source, and sampling season are the crucial aspects of changing BC variability. The impact of dust and analysis methods on BC mass concentration in surface snow and other related uncertainties are described in Gul et al. (2018). Besides the importance of glaciers, snow cover also plays an important role in society and sustaining ecology in mountainous regions such as the HTP and TP. BC, WIOC, and mineral dust deposited on snow can reduce the snow-covered area by surface albedo reduction and contribute to the near-worldwide melting of snow and ice. BC, WIOC, and dust concentrations in snow cover generally ranged from 202 to 17,468  ng  g−1, 491 to 13,880  ng  g−1, and 22 to 846  ng  g−1, respectively, with higher concentrations in the central to northern areas of the TP (Zhang et al. 2018). The effect of BC and dust reduced the snow cover duration by 3.1  ±  0.1 to 4.4  ±  0.2  days. Systematically higher BC mass concentrations in the snow were observed in the central to northern TP than in the southern TP (Zhang et al. 2018). The reduction in surface albedo contributed by BC and dust was estimated at approximately 38%, with an associated radiative forcing of 18–32 W m−2.

2.4  C  limatic Impacts of BC Particle in the Atmosphere and Cryosphere Aerosol RF in the atmosphere depends directly or indirectly on several intensive properties of particles such as the presence of absorbing material in their composition, including mass concentration and size distribution. Jacobson (2001) suggested that the magnitude of direct RF due to BC may exceed due to methane, thus making it one of the notable species contributing to global warming. BC particles in the atmosphere play a significant role in climate change and have been identified as the second-largest contributor to anthropogenic RF (Jacobson 2001). Making use of extensive measurements of atmospheric BC from the several HTP stations is an assessment of RF due to direct and snow-albedo darkening. BC deposition significantly affects the snow surface albedo, which may trigger the snow- and ice-albedo

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Fig. 2.3  Spectral variation in albedo for winter sampling sites and selected mass absorption cross-­ section (MAC) values: (a) average albedo of samples at each of the sites; (b) daily mean albedo reduction of fresh snow (site S6) and aged snow (site S1) (note different scales of the y-axis); (c) albedo of fresh snow site S6; (d) albedo of aged snow site S1. (Adopted from Gul et al. 2018)

feedback that amplifies surface warming (Flanner et  al. 2012). The feedback of BC-snow-albedo has been noticed in many studies, including Gul et  al. (2018). Deposition of absorbing aerosols (mainly BC and dust) on highly reflecting surfaces (like snow or ice) would reduce the surface albedo significantly and result in positive RF (warming) at the top of the atmosphere (Flanner et al. 2009). The RF due to direct, semi-direct, and snow albedo effects of BC aerosols and their implications on the hydro-climate are among the major challenges in the assessment of regional climate impact (Flanner et  al. 2007). The spectral variation in albedo for winter sampling sites and selected mass absorption cross-section (MAC) values in surface snow from north Pakistan snow-covered valleys is shown in Fig. 2.3. The Himalayas are one of the largest snowpacks (ice-covered regions) in the TP.  According to the results of the coupled climate feedback response analysis method, the snow-ice albedo feedback resulted in a warming of approximately 2.6 °C and was the primary contributor to enhanced warming over the Himalayas in recent decades. This warming was much greater than the warming induced by dynamic and other radiative factors (Ma et al. 2019).

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2.5  Seasonal Characteristics of BC in the Himalayas and TP The TP area has a relatively uniform climate. During winter, it is freezing and windy but dry, and in summer, it is mild or cool, with considerable variations between night and day due to the intense sun rays. The north face is relatively colder than the south face of the TP, but the temperature varies with differences in elevations. The TP and surrounding regions, especially southern parts, are facing four seasons of a year winter (December–February), pre-monsoon (March–May), monsoon (June– September), and retreating monsoon (October–November). Significant seasonal variability existed in the transport process of residential BC from South Asia to the TP. The South Asia monsoon during summer and the mountain-valley wind system during spring could transport South Asian residential BC across the Himalayas to the TP (Yang et al. 2019). BC particles in the atmosphere are relatively higher in pre-monsoon as compared to monsoon and the other three seasons. In the Himalayan range, the reason for higher concentration in the pre-monsoon season is mainly attributed to Indian subcontinent emission and biomass burning activities in the region. Pre-monsoon is relatively dry, and monsoon is a wet season in this region. Several pollutants have shown a marked seasonality over these regions (Tripathee et al. 2014, 2019, 2020; Chen et  al. 2016). The diurnal characteristics of BC concentration in TP depend on the diurnal variation of meteorological parameters, mainly valley winds and thermal winds regime. The mesoscale topography over the TP also plays a vital role in generating and enhancing mesoscale disturbances. The seasonal variation of BC concentration in the atmosphere can be characterized by the emission sources and seasons itself. The geological history of the TP is closely related to that of the Himalayas. During the pre-monsoon season (dry period), the westerly and southerly winds begin which play an essential role in atmospheric pollution circulation. Biomass burning activities have been reported in the IndoGangetic Plain (IGP) region mostly during the non-monsoon season (dry periods) which enhance the concentration of pollutants during this period (Tripathee et al. 2017, 2020) and BC in the atmosphere (Ram et al. 2008). Therefore, the higher concentration of BC particles over the Himalayas-TP is observed during the dry seasons. Conversely, during the monsoon season, the southwesterly winds prevail and bring much moisture from the Indian Ocean to the region, with high humidity and precipitation. The higher precipitation during monsoon washes out the aerosol particles (e.g., BC) in the atmosphere attributing to the lowest BC concentrations. One of the examples for the seasonal variation of BC particles from Darjeeling (Northeastern Himalayan site in India) is shown in Fig. 2.4. The seasonal pattern is very similar for almost all sites presented in Fig. 2.2. However, the BC concentrations could vary with changing elevation and distance from emission sources. There is a difference in among various observation sites, but the seasonal pattern was quite similar with other reported studies in the region such as reported by Sarkar et al.

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Fig. 2.4  Seasonal variation of BC concentration shown in the box-whisker plot. The lower boundary of the box, the horizontal line inside the box, and the upper boundary of the box represent 25th percentile, median, and 75th percentile, respectively. The whiskers below and above represent minimum and maximum, respectively (Sarkar et al. 2015)

(2015) in Darjeeling, India, and the northern side of the Everest region (Chen et al. 2018; Cong et al. 2015a).

2.6  P  otential Source Regions and Transport Mechanisms of BC The atmosphere plays a significant role in the transport of air pollutants to the pristine areas via transport and deposition. It may take only a few days or weeks for the pollutants to reach far away from the source region to the Himalayas and TP. Historical reconstruction of BC from past studies in ice cores has revealed that the transport mechanisms to the Himalayan-TP region have fluctuated over the last century, indicating an increasing trend in emissions and transport to the Himalayas-TP (Bond et al. 2013; Lu et al. 2012; Kaspari et al. 2011). The regional atmospheric chemistry model, weather research, and forecasting model coupled with chemistry (WRF-Chem) indicating that residential BC emissions from South Asia contributed the largest (25.8% in summer and 44.8% in winter) to BC concentrations over the TP compared to other anthropogenic emission sectors in the TP (Yang et al. 2019). Back trajectory analysis has also suggested that the northern TP was influenced mainly by air masses from Central Asia with some Eurasian influence, and air masses in the central and Himalayan regions originated mainly from South Asia (Zhang et al. 2018). Emission from Eastern China and northern India (IGP regions)

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Fig. 2.5  Conceptual model illustrating transport pathways and sources of BC in the HTP region: After transport to the Himalayas, the glacier valley wind system uplifts the air pollutants and crosses the Himalayas to the TP

plays a significant role in BC transport to the Third Pole region (Kopacz et al. 2011). In increasing populations in nearby countries like China, India, and Pakistan, the anthropogenic BC emission is very high which is easily transported and deposited to the Third Pole. South and East Asia are the two largest BC emission source regions at present (Xu et al. 2009; Menon et al. 2002, 2010; Bond and Bergstrom 2006; Ohara et al. 2007). These transported BC aerosols from the South and East Asian regions can be deposited to the Himalayan-TP glaciers. The schematic diagram shows the sources and transport of BC to the Himalayas and the TP Fig. 2.5. The APCC research network’s results have already revealed the pollutant transport mechanisms in the region (Kang et al. 2019; Chen et al. 2019). During the pre-­ monsoon season, a low-pressure system is creating a strong circulation pattern that is capable of transporting BC, accumulated in the IGP, and reached up to the TP through long-range transportation. Episodic trans-Himalayan pollution can be transported through the major south-north valleys and lifted over the Himalayas. Synoptic-scale and local meteorological processes such as the mountain peak-­valley wind systems could facilitate the trans-Himalayan transport of atmospheric pollution (Cong et al. 2015a, b; Luthi et al. 2015). The details on the APCC network and few results have been presented in the next section of this chapter. Moreover, previous studies have already provided proof of pollutants transport from South Asia to the Himalayas and TP analyzing the back trajectory analysis and model simulations over the region.

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2.7  A  tmospheric Pollution and Cryospheric Change (APCC) Research Framework The research framework APCC seeks to obtain a continuous observational dataset and regular sampling of atmosphere and cryosphere from cross-sectional regions over the HTP (Fig. 2.6). The monitoring network started in 2013 in the Nepalese Himalayas and TP and extended to Pakistan in 2015 by the State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences. This framework helps to improve the understanding of the distribution, variation, and transport of atmospheric pollutants (inorganic and organic pollutants) and assess their impacts on cryospheric changes over the HTP region. Here for this chapter, we will focus on the carbonaceous particle sources and observation results from the APCC observation network (Fig. 2.6). Carbonaceous aerosols in the atmosphere and glacier surface in the southern HTP were mainly attributed to biomass burning emissions from South Asia, particularly in pre-monsoon seasons (dry periods). This was clearly evidenced by similar aerosol composition and their clear seasonality on both the south and north sides of the Himalayas (Cong et  al. 2015a; Li et  al. 2016a). Investigation of BC isotopic signatures in glaciers and atmospheric aerosols over the HTP revealed different sources of BC regarding different geographical regions (Li et al. 2016a). The study

Fig. 2.6  Aerosol and cryospheric observational sites (APCC network) across the Himalayan-­ Tibetan Plateau. (Adopted from Kang et al. 2019)

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suggested that BC in Himalayan glaciers has equal contributions from fossil fuel and biomass combustion, which matches the BC source fingerprints from the IGP, one of the most populated and polluted regions in the world (Tripathee et al. 2017). BC in glaciers of the northern TP mainly originates from fossil fuel combustion indicating the sources from the Chinese cities. However, BC levels in glaciers of the inner TP were lower, possibly implying the local sources from the TP itself, such as few from vehicle emission and yak dung burning (Li et al. 2018b). Furthermore, the RF and mass absorption cross-section (MAC) of BC and OC revealed that the RF triggered by water-soluble organic carbon (WSOC) relative to that of BC in the atmosphere and glacier snow is up to 10% (Li et al. 2016b; Yan et al. 2016; Chen et  al. 2020), inferring significance of WSOC in carbonaceous aerosols over the Himalayan-TP region. This research framework is still continuously monitoring the aerosol and cryospheric pollution over the Himalayan-TP and surrounding regions. They have already provided the baseline information on the BC levels and transport to the HTP regions from the IGP regions. The results from this network will give the details on pollution transport and its effects on the cryosphere and the whole fragile ecosystem in the region.

2.8  Summary and Future Direction This chapter provided the scenario of BC aerosols over the HTP, their potential source regions, transport mechanism, and radiative impacts to the glaciers. Introduction to the APCC research framework and preliminary results from the network were also presented. The scenario of BC impacts on atmosphere and glaciers is shown, which could provide insights into BC levels and fate in the Himalayas and TP region. The average ambient BC mass concentrations in the selected sites varied between 0.048 μg m−3 and 14.5 μg m−3, respectively. The highest and lowest level of BC particle was reported in Katmandu (14.5 μg m−3) and Qilian Shan Mountain (0.048 μg m−3), respectively. Residential BC emissions from South Asia contributed the largest (25.8% in summer and 44.8% in winter) to BC concentrations over the TP compared to other anthropogenic emission sectors in TP. The snow-ice albedo feedback resulted in a warming of approximately 2.6 °C and was the primary contributor to enhanced warming over the Himalayas in recent decades. The effect of BC and dust reduced the snow cover duration by 3.1 ± 0.1 to 4.4 ± 0.2 days. The concentration of BC particles in the atmosphere is comparatively higher in pre-­ monsoon among the four seasons, attributed to low average rainfall than the other three seasons and enhanced biomass burning activities. Depending on the season, meteorological condition, geographical location, and nearby source location, the concentrations of BC particles in surface snow or ice are changing. The deposition of BC and dust on highly reflecting surfaces (like snow or ice) reduced the surface albedo significantly.

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The potential source region of pollutants was identified through various techniques, including air mass back trajectories and wind vector maps. However, there is still a need for more details and seasonal studies of BC transport and deposition in this complex region. Many previous studies have confirmed the long-range transport of BC from urbanized areas of South Asian countries in the remote Himalayas-TP. However, specific BC source identification, transport pathways, and deposition rate (trans-boundary pollution) are still lacking. Therefore, continuous long-term in situ measurements and spatial distribution at multiple sites are further required to confirm the pathways of short- and long-range transport of pollutants to this fragile region. Moreover, there is a need to identify the exact source contribution, which could be possible by high-resolution models and carbon isotopic fingerprints in the region. There is a need for the continuous long-term in situ measurement of cryospheric components in the region. The results obtained can be compared with the satellite data and high-resolution modeling results in the future. High-resolution updated emission inventory can further help to investigate the transport pathways of BC over the region. Acknowledgments  This study is supported by the Strategic Priority Research Program of the Chinese Academy of Sciences, Pan-Third Pole Environment Study for a Green Silk Road (Pan-­ TPE) (XDA20040501), and the State Key Laboratory of Cryospheric Science (SKLCS-ZZ-2018). Lekhendra Tripathee is supported by the Chinese Academy of Science for international Young staff under the PIFI (2020FYC0001) program.

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Tripathee L, Kang S, Huang J, Sharma CM, Sillanpää M, Guo J, Paudyal R (2014) Concentrations of trace elements in wet deposition over the central Himalayas, Nepal. Atmos Environ 95:231–238 Tripathee L et al (2016) Preliminary health risk assessment of potentially toxic metals in surface water of the Himalayan Rivers, Nepal. Bull Environ Contam Toxicol 97(6):855–862 Tripathee L et al (2017) Chemical characteristics of soluble aerosols over the central Himalayas: insights into spatiotemporal variations and sources. Environ Sci Pollut Res 24(31):24454–24472 Tripathee L et al (2019) Spatial and temporal distribution of total mercury in atmospheric wet precipitation at four sites from the Nepal-Himalayas. Sci Total Environ 655:1207–1217 Tripathee L, Guo J, Kang S, Paudyal R, Sharma CM, Huang J, Chen P, Ghimire PS, Sigdel M, Sillanpää M (2020) Measurement of mercury, other trace elements and major ions in wet deposition at Jomsom: the semi-arid mountain valley of the Central Himalaya. Atmos Res 234:104691 Wang X, Pu W, Ren Y, Zhang X, Zhang X, Shi J, Jin H, Dai M, Chen Q (2016) Snow albedo reduction in seasonal snow due to anthropogenic dust and carbonaceous aerosols across northern China. Atmos Chem Phys Discuss:1–52. https://doi.org/10.5194/acp-­2016-­667 Xu B et  al (2009) Black soot and the survival of Tibetan glaciers. Proc Natl Acad Sci U S A 106(52):22114–22118 Yan FP et  al (2016) Concentration, sources and light absorption characteristics of dissolved organic carbon on a medium-sized valley glacier, northern Tibetan Plateau. Cryosphere 10(6):2611–2621 Yang J, Kang S, Ji Z, Chen D (2018) Modeling the origin of anthropogenic black carbon and its climatic effect over the Tibetan Plateau and surrounding regions. J Geophys Res Atmos 123(2):671–692 Yang J, Kang S, Ji Z (2019) Critical contribution of south Asian residential emissions to atmospheric black carbon over the Tibetan plateau. Sci Total Environ. https://doi.org/10.1016/j. scitotenv.2019.135923 Yao T et al (2012) Third pole environment (TPE). Environ Dev 3:52–64 Yasunari T et al (2010) Estimated impact of black carbon deposition during pre-monsoon season from Nepal Climate Observatory–Pyramid data and snow albedo changes over Himalayan glaciers. Atmos Chem Phys 10(14):6603–6615 Zhang Y, Kang S, Sprenger M, Cong Z, Gao T, Li C, Tao S, Li X, Zhong X, Xu M, Meng W, Neupane B, Qin X, Sillanpää M (2018) Black carbon and mineral dust in snow cover on the Tibetan Plateau. Cryosphere 12:413–431. https://doi.org/10.5194/tc-­12-­413-­2018 Zhao S, Ming J, Xiao C, Sun W, Qin X (2012) A preliminary study on measurements of black carbon in the atmosphere of northwest Qilian Shan. J Environ Sci 24(1):152–159 Zhao ZZ et al (2013) Aerosol particles at a high-altitude site on the Southeast Tibetan Plateau, China: implications for pollution transport from South Asia. J Geophys Res-Atmos 118(19):11360–11375

Chapter 3

Impact of Urban and Semi-urban Aerosols on the Cloud Microphysical Properties and Precipitation Jagabandhu Panda and Sunny Kant

Abstract  This chapter reviews urban and semi-urban aerosol influence on cloud microphysical properties and associated precipitation through observations and numerical modeling. Over the previous decade, numerous observational and modeling studies are carried out to understand aerosol-cloud interactions. Remarkable development is made to progress the understanding of physical and chemical mechanisms associated with aerosol-cloud interaction and decrease the uncertainties related to climate forcing. The feedback of thermodynamical and dynamical processes on aerosol-cloud interaction is poorly understood on a large and local scale. Aerosols reduce incoming solar radiation and weaken the land-ocean thermal interaction, thus inhibiting the development of clouds on a large and global scale. Urban and semi-urban aerosols have significant radiative effects and influence the convective potential of the lower atmosphere leading to reduced temperatures and upsurge atmospheric stability, thereby weakening the circulation pattern. The atmospheric thermodynamic states determine the growth and formation of clouds, convection, and precipitation, which may also be influenced by the urban and semi-urban aerosols serving as ice nuclei and cloud condensation nuclei. Urban and semi-urban aerosols may alter the dynamical feedback processes leading to an influence on cloud droplet formation. The review presented in this chapter highlights the significance of urban and semi-urban aerosol-cloud-climate interaction. Keywords  Aerosol · Cloud · Precipitation · Urban

J. Panda (*) Department of Earth and Atmospheric Sciences, National Institute of Technology Rourkela, Rourkela, Odisha, India e-mail: [email protected] S. Kant Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, Delhi, India © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. Tiwari, P. Saxena (eds.), Air Pollution and Its Complications, Springer Atmospheric Sciences, https://doi.org/10.1007/978-3-030-70509-1_3

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3.1  Introduction The report by the Intergovernmental Panel on Climate Change (IPCC) recommended that human or anthropogenic activities have contributed significantly to the warming atmosphere during the past decades (IPCC 2013). IPCC (2013) gave importance to the urban-induced surface warming or urban heat island (UHI) effect, aerosol-cloud-climate interaction, warming due to greenhouse gases, and urban air pollution effect on the energy budget, hydrological cycle, and cloud microphysical properties (Jin 2006; Han et al. 2012; Stachlewska et al. 2018). Urban regions experience land use and land cover (LULC) changes due to human activities (Jin 2006; Stachlewska et al. 2018). In the urban and semi-urban locations, the natural land surface is changed by synthetic surfaces with different terminal properties (like heat capacity and terminal inertia). The difference in the surface albedo and anthropogenic heat discharge over the urban and semi-urban regions may be associated with the onset of UHI (Shepherd 2005). It may cause an increase in near-surface air temperature or land-surface temperature by 2–6  °C over the urban regions than neighboring nonurban areas since sensible heat is being transferred to the air (Kim and Baik 2002). It may lead to dry surfaces and encourage the transportation of aerosols to the urban atmosphere. The prevailing meteorological conditions, aerosols, and clouds have a significant effect on the land surface temperature (Jin 2006; Li et al. 2016) too. Urban and semi-urban aerosols are among the major concerns in the climate change point of view due to rapid urbanization. The previous observational studies reported that aerosols influence cloud microphysical properties and precipitation over urban and semi-urban regions (Han et  al. 2012; Liu et  al. 2017; Kant et  al. 2017, 2019a, b, 2021; Stachlewska et al. 2018). The absorbing types of aerosols, i.e., black carbon (BC), are produced through the fossil fuel and biomass burning over urban and semi-urban areas that influence cloud microphysical properties as well as cloud lifetime also (Cherian et al. 2014). The accumulation of absorbing aerosols on the snow surface may decrease the surface albedo, and absorbing solar radiation encourages the warming of snow surface (Kulkarni et al. 2007). Under the favorable meteorological conditions, urban and semi-urban aerosols are accumulated over the Indo-Gangetic Plain (IGP) region during the winter season; those are primarily produced through local emissions (vehicles and industrial pollution) and biomass burning (Tripathi et  al. 2005). There is strong feedback and coupling between the available atmospheric aerosols and cloud thermodynamical and dynamical processes in a suitable meteorological condition while forming fog and dense haze (Mohan and Payra 2014). It decreases visibility and worsens the local and regional air quality too. Aerosols serve as cloud condensation nuclei (CCN) and ice nuclei (IN), which help in the formation of cloud droplets (Kang et al. 2015; Kant et al. 2017, 2019a, b, c, 2021). Some of the studies suggested that precipitation is enhanced (Kant et al. 2019a, c) or suppressed (Rosenfeld 2000; Ramanathan et al. 2001; Dave et al. 2017) due to the presence of aerosols over the urban and semi-­ urban region. Paramonov et al. (2015) and Schmale et al. (2018) have studied the

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spatial and temporal distribution of the CCN characteristics and their impact on precipitating and non-precipitating clouds. Few studies, including that of Jayachandran et al. (2019), indicate that CCN concentration is significant over the central IGP and reduces from west to east above the planetary boundary layer (PBL). The supersaturation of CCN activation efficiency at 0.4% is highest over the eastern IGP. The highest activation efficiency is observed above the PBL than below it. The activation of CCN efficiency is low at all the heights, indicating the presence of a higher mass concentration of BC, whereas higher activation of CCN efficiency infers the existence of hygroscopic dust aerosols.

3.2  Aerosol-Cloud Interaction Aerosol-cloud interaction (ACI) is defined according to the IPCC (2013) report in terms of the changes in cloud microphysical properties through CCN or IN. However, aerosol influence on warm clouds is slightly less complex as compared to the deep convective and mixed-phase clouds due to the liquid phase involvement (Twomey 1977; Koren et al. 2014; Liu et al. 2017; Kant et al. 2017, 2019a, c, 2021). The first indirect effect of aerosols suggests a decrease in cloud effective radius (CER) with an increased aerosol at fixed liquid water path (LWP) (Feingold et al. 2003; Kim et al. 2008; Koren et al. 2014). It indicates an upsurge in cloud albedo which results in enhancement in reflection (Fig. 3.1) and the consequent cooling effect (Twomey

Fig. 3.1  Schematic diagram representing aerosol-cloud-radiation (ACR) interaction

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1977). Smaller cloud droplets take much more time to grow enough to precipitate, and it is known as the cloud lifetime effect (Albrecht 1989). Although aerosol effects on cloud droplet size are considered primarily to be due to microphysical factors, changes in the dynamics and thermodynamic process may still play an additional role in governing the ACI (Fig. 3.2). Feingold et al. (2001, 2013) and Kant et al. (2019a) suggested that the indirect effect of aerosols over the urban and semi-urban region is mostly dependent upon the hygroscopicity and vertical velocity (VV). The interaction between urban/semi-­ urban aerosols and cloud microphysical properties can, therefore, be influenced by the meteorological conditions and dynamical/thermodynamical processes (Quaas et al. 2010; Gryspeerdt et al. 2014, 2017; Christensen et al. 2017; Andersen et al. 2017; Kant et al. 2019a, b, c). Relative humidity (RH) is one of the meteorological parameters influencing cloud droplet growth and aerosol particle size (Small et al. 2011; Liu et al. 2017; Kant et al. 2019a). A large amount of RH presence near the cloud base may influence the interaction of aerosol and cloud properties (Fig. 3.2). The hygroscopic growth of aerosols depends upon the condensation of water vapor (Feingold et al. 2013). The higher amount of RH presence in the atmosphere may encourage the growth of larger cloud droplets due to the availability of sufficient water vapor (Jones et al. 2009; Liu et al. 2017) and, subsequently, increases cloud lifetime (Fig. 3.2). The horizontal and vertical increase in cloud cover, in the presence of urban and semi-urban aerosols, may indicate an alteration in the cloud properties. It is possibly due to the low atmospheric pressure zone and water vapor

Fig. 3.2  Schematic diagram depicting the influence of atmospheric dynamic and thermodynamic state on aerosol-cloud-precipitation (ACP) interaction

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availability over the urban and semi-urban areas, which is an essential condition for the growth and formation of cloud droplets (Fig. 3.2; Wright et al. 2010; Kang et al. 2015; Kant et al. 2019a, c). Lower tropospheric stability (LTS) is one of the important meteorological parameters, which influences aerosol and cloud relationship over the urban and semi-­ urban regions. It is used to measure the thermodynamic states of the atmosphere and also for determining the atmospheric tendency relating to the disturbance of atmospheric vertical motion (Klein and Hartmann 1993; Medeiros and Stevens 2011). The low and high LTS indicate unstable and stable conditions of the atmosphere, respectively. Cloud droplets grow bigger during the unstable condition (low LTS, anti-Twomey effect) due to the large vertical mixing of the water vapor (Small et al. 2011; Liu et al. 2017) while suppression of cloud droplets is supported by stable condition (high LTS, Twomey effect). High LTS indicates the stronger vertical inversion resulting from the suppression of vertical cloud growth and vertical mixing (Fig. 3.2). Due to this well-mixed layer and boundary layer, the favorable moist condition may be created for the growth and formation of low-level cloud droplets (Wang et al. 2014; Kant et al. 2019a, c). Another meteorological parameter, i.e., pressure vertical velocity (VV), influences ACI too. It is used to determine the strength of dynamic convection of the atmosphere. Positive (negative) pressure VV indicates an upward (downward) motion of the atmosphere (Jones et al. 2009). Negative pressure VV suggests that the upward movement of air parcel may encourage the development and growth of large droplets and, consequently, influence ACI (Fig. 3.2). The suppression of cloud droplet growth occurs in the presence of the downward motion of air parcel (Liu et al. 2017; Kant et al. 2019a, b, c). The absorbing types of aerosols present in the urban/semi-urban areas encourage the evaporation of the droplets (Fig.  3.1), and consequently, the cloud becomes too thin (Alam et al. 2014; Kant et al. 2019a, b, c). Thus, the ACI depends upon the type of aerosols, geographical location, meteorological condition, and dynamic/thermodynamic properties of the atmosphere over urban/semi-urban regions. However, it is the concentration and types of aerosols that are more significant in determining the ACI.

3.3  Aerosol-Cloud-Radiation Interaction According to the IPCC (2013) report, aerosol-radiation interaction (ARI) is defined as the alteration in radiation budget through scattering or absorption due to the presence of aerosols and is termed as aerosol direct and/or semi-direct effects (Fig. 3.1) depending upon clouds’ absence/presence (Ackerman et al. 2000). The influence of aerosols on the radiation budget through scattering or absorption depends upon their chemical composition, size, types, and mixing states. Earlier aerosol-climate models only considered mass mixing ratio (Penner et al. 2004), representing the “mixing state” of aerosols. Most of the aerosol particles reside below 2 km, and the majority of them (~60–80%) accumulate in the lower 1 km of the atmosphere (Li et al. 2016).

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This leads to the trapping of solar radiation in a considerable amount within the planetary boundary layer (PBL), and temperature inversion may arise due to intense heating in the upper part of the PBL (Li et al. 2016). Convective potential energy (CAPE) is strengthened through absorbing aerosols resulting in more stable PBL but more unstable in the free atmosphere. In general, ARI appreciably influences PBL in several ways. First, aerosol reduces incoming surface radiation resulting in the sensible heat fluxes that drive the growth of PBL. Second, absorbing aerosols warm the air in PBL, resulting in the influence of the atmospheric thermodynamic structure. And third, the positive feedback process induces interaction between aerosols and the PBL that intensifies the initial radiative effect (Fig. 3.1; Yu et al. 2002). The presence of the absorbing aerosols near the cloud droplets warms the atmosphere, decreasing the RH presence, resulting in burning of the cloud droplets, and, consequently, declines the planetary albedo, which is known as the aerosol semi-­ direct effect (Ackerman et al. 2000; Li et al. 2016; Kant et al. 2017, 2019b). Jacobson (2002) suggested that absorbing aerosol effect may be higher due to the low-cloud positive feedback loop. Absorbing aerosols present near the cloud droplets may decrease albedo. This will result in an upsurge of solar radiation absorption, and, eventually, evaporation of cloud droplets would take place (Fig. 3.1), thus influencing the atmospheric heating profile (Wang 2013). Numerical modeling is extensively used to study urban and semi-urban aerosol-radiation interaction. Dan et al. (2012) considered a one-dimensional boundary layer model with a radiative transfer scheme for analyzing the influence of urban aerosols on meteorological conditions in the PBL. An increase in cloud cover in the presence of urban absorbing aerosols is negative cloud feedback, and it depends upon the meteorological conditions and geographical region (Li et al. 2016). The aerosol-cloud-precipitation-climate (ACPC) feedback has been poorly understood, and its highly complex mechanism causes relatively higher uncertainty in the resulting climate forcing (Rosenfeld et al. 2014). The radiative forcing on the global scale due to aerosols is computed as −0.9 (−1.9 to −0.1 considered medium confidence) Wm−2 (IPCC 2013), and that of the first indirect effect is −0.42 Wm−2 (Lebsock et al. 2008). The direct radiative forcing calculated for the anthropogenic aerosols is −0.9 ± 0.4 Wm−2 (Quaas et al. 2008). The aerosol-cloud-radiative forcing is mentioned in the IPCC fifth assessment report to range from −0.5 to −2.5 Wm−2 (McCoy et al. 2017). The urban aerosols do have a significant contribution to these values of radiative forcing. The cloud radiative forcing (CRF) is computed from the net change in the fluxes with and without clouds at the top of the atmosphere (TOA). The cloud micro- and macro-properties along with other atmospheric variables such as surface albedo are more capable of influencing net cloud radiative forcing or NetCRF (Pyrina et al. 2015; Saud et al. 2016; Kant et al. 2019b). The higher cooling effect was seen over the tropical regions (long-wave CRF or LWCRF in the range of 50–100 Wm−2) and mid- and high-latitude ocean (short-wave CRF or SWCRF is up to −100 Wm−2) in the past (Ramanathan et  al. 1989). Rajeevan and Srinivasan (2000) reported the negative NetCRF seen over the Indian region during the monsoon season due to the

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presence of large, optically thick clouds. Looking at these CRF values being influenced by aerosols, it can be said that urban aerosols do play an appreciable role in governing the localized radiation budget.

3.4  Aerosol-Cloud-Precipitation Interaction Urban and semi-urban aerosols play a significant role in the growth and formation of cloud droplets over cities and their surroundings and, thus, play an important role in governing the rainfall over that particular region (Sanap and Pandithurai 2015; Kant et  al. 2019b). Cloud droplets generate microphysical and thermodynamic feedback, which in turn have the ability to influence cloud formation, growth, and their properties (Rosenfeld et al. 2008). The studies, including those of Fang et al. (2009), Feingold et al. (2013), and Kant et al. (2019b, c), used modeling approach and observations to conclude that the precipitation suppression in the polluted environment is due to the inhibition of collision and coalescence process. Such a scenario results in the formation of small size cloud droplets (Fig. 3.2). Increasing aerosol loading over a particular area like a city environment may encourage the cooling due to evaporation of cloud droplets (Fig. 3.1) and generate temperature contrast resulting precipitation suppression, but cloud lifetime is not increased (Lee et al. 2012). Due to this, vorticity around the cloud boundaries is increased, resulting in the encouragement of the convective process and, therefore, a decrease in the cloud lifetime (Li et al. 2016). However, the suppression of warm rain processes in the presence of aerosols may be due to the condensate to ascend (Li et al. 2016) as cloud water freezes and, consequently, release more latent heat before precipitation occurs. The postponing of precipitation with the more tenacious updraft is accompanied by the invigoration of clouds before downdrafts occur (Koren et al. 2005; Tao et al. 2012; Li et  al. 2011). Smaller cloud droplets freeze at low temperatures in high altitudes, releasing additional latent heat in the higher atmosphere condition (typical over an urban area) and thus invigorating convection (Rosenfeld et al. 2008; Li et al. 2011, 2016). However, this invigoration theory is used in numerous observational studies to describe the enhanced cloud fraction and cloud top height in the presence of aerosols (Wang et  al. 2014; Liu et  al. 2017; Kant et  al. 2019b). Convective strength invigoration in the presence of aerosols depends upon the dynamic and thermodynamic conditions of the atmosphere (Fan et al. 2009; Khain et al. 2008). During the strong wind shear, the suppression of convective strength through increasing CCN loading may occur because of the evaporative cooling (Fan et al. 2009). However, wind shear and gust front interaction in the mesoscale scale convective cloud system and increase in CCN may encourage aerosol-induced convection (Lee and Feingold 2010). This indicates ACI over urban and semi-urban regions may also depend upon the prevailing localized or mesoscale dynamics and thermodynamics (Fig. 3.2).

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The presence of a huge amount of aerosols over the urban and semi-urban regions may influence the precipitation efficiency (Kant et  al. 2019a). Rosenfeld et  al. (2001), using observational studies, suggest that warm rain collision and coalescence process is suppressed due to the presence of dust and smoke aerosols (Rosenfeld et al. 2001). The presence of biomass burning aerosols may encourage the invigoration of convective clouds (Koren et al. 2004) to generate a positive relationship between the elevated cloud top heights, large anvils, and rainfall amount with aerosols (Lin et al. 2006). Li et al. (2011) and Niu and Li (2012), using satellite observations, suggested the suppression of clouds and precipitation in the presence of aerosols. However, Koren et al. (2012) reported intensification of rainfall over tropics and mid-latitude due to the presence of aerosols depending upon the factors like cloud types, aerosol size, and types besides the prevailing meteorological conditions (Fig.  3.2) and geographical regions (Khain et  al. 2008; Gryspeerdt et  al. 2015). Thus, tropical urban and semi-urban areas may experience little different ACI compared to the others. The aerosol presence over the urban and semi-urban regions may have an enormously positive/negative impact on ACI over tropics due to the additional inherent heating mechanism.

3.5  Summary and Way Forward Several studies have concluded that aerosols have a significant influence on cloud microphysical properties and precipitation over the urban and semi-urban region through observational and numerical analysis (Vinoj et al. 2014; Koren et al. 2010; Rosenfeld et al. 2008, 2014; Padmakumari et al. 2013; Tao et al. 2012; Khain et al. 2008; Koren et al. 2012; Wang et al. 2014; Das et al. 2015; Liu et al. 2017; Kant et al. 2019a, b, c, 2021) as discussed earlier. The presence of high relative humidity may intensify the hygroscopic growth of the aerosols and cloud droplets and increase the probability of cloud formation. On the other hand, LTS based on unstable environmental conditions may encourage the formation of higher and thicker clouds; stable conditions may help enhance the horizontal cloud cover. Because of the dynamical process, an upward motion of air parcel may also help develop higher and thicker clouds (Wang et al. 2014; Liu et al. 2017), whereas downward motion may be helpful for the increase in horizontal cloud cover. On the other hand, the earlier type of condition is favored more in a city or urban environment. However, other factors, including temperature advection, may influence aerosol-cloud interaction (Fig. 3.2) too. The role of aerosols in governing cloud microphysical properties and precipitation over a region is influenced by the presence of CCN and IN. Mostly, they are emphasized while discussing cloud microphysical properties (such as cloud lifetime), dynamic and thermodynamic process, and radiative feedback (Figs. 3.1 and 3.2). It is quite challenging to estimate the aerosols’ influence on the cloud microphysical properties and precipitation in a comprehensive/robust manner through observational and modeling studies. Based on the above-discussed

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aspects, some of the critical issues on which further research is required are as follows: (i) Understanding the variability in atmospheric circulation pattern as a result of alterations in cloud thickness and cover due to the urban and semi-urban aerosol indirect effects (ii) Relating the variations in surface temperature due to the urban and semi-urban aerosols with the mesoscale circulations (iii) Understanding the influence of absorbing urban and semi-urban aerosols on radiative properties, cloud microphysical properties, and precipitation (iv) Role of urban and semi-urban aerosols during the Indian summer monsoon (v) Role of urban and semi-urban aerosols during extreme-/high-impact weather events

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Chapter 4

Aerosol Characteristics and Its Impact on Regional Climate Over Northern India Pradeep Kumar, Arti Choudhary, Vineet Pratap, Pawan K. Joshi, and Abhay Kumar Singh

Abstract  Aerosols in the atmosphere cause the continuous deterioration of global air quality day by day. The higher concentration of aerosol loading over Northern India affects the Earth’s radiation budget directly through absorption and scattering of solar radiation and/or indirectly by alteration of microphysical parameters which results in the modulation of the hydrological cycle and global food security. Northern India has several densely populated cities that have recorded a significant amount of anthropogenic aerosols in the atmosphere. This region has dynamic meteorological patterns and experienced severe aerosol episodes including dust storms, increased biomass, and agricultural burning which caused an enhancement in aerosol loading over Northern India. This region is characterized by highly mixed aerosols that can affect the climate on a regional as well as global scale. Therefore, it becomes necessary to measure the physical, optical, and chemical properties of aerosols concerning local/regional meteorology. Several past studies reported that fine aerosol concentrations were found higher over Northern India during post-monsoon and winter seasons which are mainly attributed to high anthropogenic activities during these seasons. Agricultural crop residue/biomass burning predominantly governs aerosol climatology during post-monsoon and winter seasons, while the transported P. Kumar School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, Delhi, India Department of Physics, Institute of Science, Banaras Hindu University, Varanasi, India A. Choudhary Transport Planning and Environment Division, CSIR-Central Road Research Institute, New Delhi, Delhi, India Environment Climate Change & Public Health, Utkal University, Bhubaneswar, Odisha, India V. Pratap · A. K. Singh (*) Department of Physics, Institute of Science, Banaras Hindu University, Varanasi, India e-mail: [email protected] P. K. Joshi School of Environmental Sciences, Jawaharlal Nehru University, New Delhi, Delhi, India © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. Tiwari, P. Saxena (eds.), Air Pollution and Its Complications, Springer Atmospheric Sciences, https://doi.org/10.1007/978-3-030-70509-1_4

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dusts from the Middle East and the Thar Desert are the major causes of aerosol loading during pre-monsoon seasons. This chapter describes the characteristics of ­atmospheric aerosol, their emission sources along with the significance of spaceborne measurements, and their impact on regional climate over Northern India. Keywords  Aerosol · Emission sources · Remote sensing · Hysplit

4.1  Introduction Aerosols are present in the solid and liquid form overhanging into the atmosphere (Hinds 1999). These atmospheric aerosols are originated from the natural as well as anthropogenic emission sources and play an important role in global as well as regional climate change (Pöschl 2005; Srivastava et al. 2012; Kumar et al. 2020a). The natural aerosols are categorized as dust particles, sea salt, fog, forest exudates, and geyser steam, whereas anthropogenic aerosols are typically categorized as particulate air pollutants, haze, and smokes (Hinds 1999). The rapidly increasing aerosol trend has critical environmental and climatic issues on both regional and global scale (Pöschl 2005). Aerosols are supposed to have a cooling as well as a warming effect directly to climate due to its scattering and absorbing nature. Indirectly aerosol affects cloud micro- and macrophysical properties (Schwartz et al. 1995). The properties of atmospheric aerosols depend generally on emission sources and regional meteorology (Srivastava and Ramachandran 2013). A large spatiotemporal variation and distinct emission sources of aerosols lead to significant uncertainty in the radiative forcing. Radiative forcing caused by aerosols is found to be positively increased which leads to an increase in the Earth’s temperature and results in net global warming. This increasing pollution significantly affects human health and increases the mortality rate day by day (Corbett et al. 2007; Hu 2009; WHO 2014). Increasing population, urbanization, and industrial expansions cause enhancement in fossil fuel combustions which are one of the main sources of air and land pollution (Choudhary et al. 2019b; Lawrence and Lelieveld 2010). Remote sensing was found to be able to assess spatiotemporal features of atmospheric aerosols and associated effects from local to global scales (Prasad and Singh 2007; Ramachandran and Cherian 2008). The assessment of aerosols by utilizing satellite technology is one of the foremost applications (Dey et  al. 2012; Sorek-­ Hamer et al. 2013; Kahn and Gaitley 2015). The satellite technology has also provided comparable results to the ground-based observations of aerosol’s impact on human health and mortality (Evans et  al. 2013). However, remote sensing is not capable of giving in-depth information about the aerosol properties on a local scale and shows relatively higher uncertainties as compared to the ground observations (El-Metwally et al. 2011). Furthermore, the exposure of atmospheric aerosols and air pollutants have increased  the higher premature mortality and about 50% of deaths were found of underaged 5 years children (WHO 2014). Mortality analysis

4  Aerosol Characteristics and Its Impact on Regional Climate Over Northern India

39

from shipping-related aerosol emissions was also performed using geospatial inventory by Corbett et al. (2007). Recently, the World Health Organization (WHO) has identified that about 92% of the population of the world is in areas with poor air quality (WHO 2016). The surface PM2.5 has given birth to coronary diseases, with increasing PM2.5 concentrations identified using regression analysis in the United States (Hu 2009). The Indo-Gangetic Plain (IGP) in Northern India has attracted researchers with a great interest in aerosol research due to its unique topography, high population, and industrialized region. The optical properties of aerosols illustrate seasonal characteristics and their dynamic nature over the middle IGP region (Kumar et al. 2019, 2020c; Pratap et al. 2020a); however, spatial aerosol concentrations mainly depend on meteorological variables (Kumar et al. 2020d). Aerosols are affecting not noly Indian weather but also the whole global climate system. The Middle East and the Thar Desert are leading sources of dust that cause dust storms regularly over the IGP in Northern India during pre-monsoon months (Singh et al. 2004; Tiwari et al. 2016). The transported dust mixed with anthropogenic aerosols during a dust storm event and alters the physical and optical properties over the IGP region (Srivastava et al. 2012). Thus, managing air quality is necessary because of possible implications for visibility, public health, and agricultural output. The aims of the present study are focused on understanding aerosol characteristics, emission sources, and their impacts on regional climate over Northern India which could be helpful for policymakers and regional climate modeling.

4.2  Aerosol Characteristics Anthropogenic emissions of fine aerosols in Southern Asia, together with the IGP, have been reported currently by Singh et al. (2017). The emissions from vehicles were found to be dominating sources of PM2.5 with natural sources, industrial emissions, and secondary aerosols (Choudhary et al. 2020a, b). Aerosol size, shape, and mass concentration are notable physical characteristics, and optical characteristics are incorporated as aerosol optical depth (AOD), angstrom exponent (α), single scattering albedo (SSA), and phase function (ϕ). The Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-based aerosol properties were widely applied for climatology, vegetation, and crop modeling study. The improved associations were assessed between PM2.5 and AOD by Wang and Christopher (2003) in Alabama. Ion Chromatography (IC) and Scanning Electron Microscopy including Energy-­ Dispersive X-ray Spectroscopy (SEM-EDX) investigations were performed recently for chemical and morphological analysis of the elements present in the atmosphere over Varanasi at the middle IGP (Kumar et  al. 2020d; Pratap et  al. 2020c). The detailed explanations of aerosol characteristics are described in the following sections.

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4.2.1  Physical Characteristics Aerosols are perceived as a significant hotspot for climate change as they affect the amount of radiation on the Earth directly by absorption and scattering of solar radiation (Satheesh et al. 2006; Srivastava et al. 2014). Indirectly, aerosols serve as cloud condensation nuclei during the process of cloud formation and perturb the microphysical parameters of the cloud (Altaratz et al. 2014; Sarangi et al. 2017). Aerosol properties (both physical and chemical) show a large spatial and temporal deviation because of different emission sources and chemical composition (Sarangi et  al. 2017; Zhao et al. 2017). Hu (2009) used a weighted regression derivative for PM2.5 estimation and found that increasing PM2.5 concentrations have given birth to coronary diseases in the eastern United States. Furthermore, the results of global mortality analysis from PM2.5 investigated by the MODIS satellite were analogous to results obtained by the chemical transport model for anthropogenic PM2.5 (Evans et al. 2013). The monthly mean variation of particulate mass concentration (both PM2.5 and PM10) in Delhi is presented in Fig. 4.1. The concentrations of aerosols were found decreasing during pre-monsoon months in comparison to post-monsoon and winter

Fig. 4.1  Monthly mean mass concentrations (μgm−3) of PM2.5 and PM10 in Delhi

4  Aerosol Characteristics and Its Impact on Regional Climate Over Northern India

41

months. During monsoon months particulate samples were lowest because of precipitations. However, observed aerosol concentrations during post-monsoon and winter months were very high. The PM2.5 mass concentrations during post-monsoon and winter months were observed nearly two to three times higher than the NAAQS limit, i.e., 40 μgm−3. In addition to this, PM10 mass concentrations during all the seasons were observed to be more than two to three times higher than the NAAQS limit, i.e., 60 μgm−3, in this research over Delhi. Recently, a similar pattern of PM2.5 and PM10 was found over Varanasi by Kumar et al. (2020d). On the other hand, during the pre-monsoon (Pratap et al. 2020b) months, PM concentration also reached the NAAQS limit over Varanasi. The comparative studies of PM2.5, PM10, and PM2.5/PM10 by several researchers over Northern India are tabulated in Table 4.1. Higher concentrations of PM2.5 in Varanasi, Delhi, Lucknow, and Agra were reported. However, higher concentrations of PM10 were reported in Varanasi, Delhi, Agra, Lucknow, and Jamshedpur in comparison to other reported cities described in Table 4.1. Recently, Pratap et al. (2020c) have reported very high PM2.5 (134 ± 48 μg−3) in the semi-urban area of Varanasi from November 2016 to February 2017. However, PM concentrations were reported lower in the semi-urban region of Varanasi by Murari et al. (2016, 2017). Maximum PM10 (500 μg−3) was observed over Jamshedpur on 21–26 October 2014 over the urban region (Ambade 2018). Comparable results were reported in the urban region of Delhi by Guttikunda and Calori (2013), Tiwari et al. (2015), and Sen et al. (2017). Similar results were also found over Agra by Pipal et al. (2014) and Sah et al. (2019). The lowest concentrations of PM2.5 (57 ± 20 μg−3) and PM10 (97 ± 20 μg−3) were reported in the suburban region of Patiala in August 2007 to January 2010 by Awasthi et al. (2011).

4.2.2  Optical Characteristics The retrieval of aerosol optical properties is always becoming intricate as a result of real-time variations in microphysical parameters impacted by the meteorology and source profiles (Mhawish et al. 2018). Singh et al. (2004) explained about the spectral characterization of AOD over the central part of the IGP using ground-based radiometric measurements. It is reported that generally higher AOD is observed in May and June which is mainly originated by the integration of desert dust along with anthropogenic aerosols (Dey et  al. 2005). The elevated AODs were also reported during winter owing to enhanced biofuel/biomass burning (Tiwari and Singh 2013). Year-long satellite measurements of MODIS and Multiangle Imaging Spectroradiometer (MISR) also revealed higher AOD in the winter season which depends on the regional environment, even though in May and June AOD rise is mainly altered from westward transported aerosols (Kaskaoutis et  al. 2011). The higher AOD determined in the region might be about 5–10 days, depending on local meteorology, which drastically affects the atmospheric heating rate (Kaskaoutis et al. 2013; Jaidevi et al. 2011) as well as human health (Jaidevi et al. 2009). Tiwari

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Table 4.1  Comparative study of PM2.5, PM10, and PM2.5/PM10 over Northern India region Study locations Varanasi

PM10 (μg−3) 213 ± 80

PM2.5/ PM2.5 (μg−3) PM10 134 ± 48 0.62

Delhi

208 ± 14

123 ± 87

0.59

Sampling period Site description (24 h) Semi-urban Nov 2016–Feb 2017 Urban 2008–2011

Agra

230.50

121

0.52

Semi-urban 2010–2011

Varanasi

161.3 ± 110.40 81 ± 66

0.50

Delhi

191.6 ± 58.10

125 ± 56

0.65

Lucknow

195.9 ± 90.30

130 ± 73

0.66

Agra

214.60

NA

NA

Patiala

140

NA

NA

Jamshedpur 500

NA

NA

Varanasi

157 ± 102

92 ± 49

0.58

Delhi

232 ± 131

118.3 ± 81.7 0.50

Lucknow

204 ± 26

101 ± 22

0.49

Semi-urban Jan 2014–Dec 2014 Urban Winter 2015 Urban Winter 2015 Urban Mar 2016–Mar 2017 Suburban 17–21 Oct 2017 Urban 21–26 Oct 2014 Semi-urban Mar 2013–Dec 2013 Urban Dec 2011–Jun 2013 Urban 2007–2008

Patiala

97 ± 20

57 ± 20

0.58

Suburban

Aug 2007–Jan 2010

References Pratap et al. (2020c) Guttikunda and Calori (2013) Pipal et al. (2014) Murari et al. (2017) Sen et al. (2017) Sen et al. (2017) Sah et al. (2019) Bansal et al. (2019) Ambade (2018) Murari et al. (2016) Tiwari et al. (2015) Pandey et al. (2012) Awasthi et al. (2011)

and Singh (2013) reported that SSA value  of 0.85 at Gandhi College  suggests absorbing aerosol allocation over the middle IGP. Ram et al. (2016) reported about varied SSA from pre-monsoon (0.65) to winter (0.92) season. SSA collectively influence absorption as well as scattering parameters of aerosols, which described aerosols that contribute in the direction of cooling or heating of the atmosphere. The comparative study between AOD and AE is compared by several researchers on a seasonal basis with an emphasis in Northern India, and the results are summarized in Table 4.2. The fractions for high AODs (>0.6) over New Delhi (76%) (Tiwari et al. 2016) and Greater Noida (70%) (Sharma et al. 2013) are indicating more turbid conditions

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Table 4.2  Comparative description of seasonal AOD and AE over Northern India Study locations Varanasi

Study AOD period Pre-mo Mo Post-mo Win 2016– 0.79 0.78 0.75 0.86 2018

ΑE Pre-mo Mo Post-mo Win 0.63 0.72 1.03 1.12

Varanasi

2011– 0.73 2014

0.73 0.95

0.87

0.76

0.86 1.16

Delhi

2011– 0.82 2013

0.86 1.00

0.95

0.51

0.89 1.03

G Noida

2010– 0.78 2012

0.73 0.98

0.87

0.68

1.02 1.19

Delhi

2001– 0.78 2012 2013 0.38– 0.98

0.74 0.91

0.77

0.49

0.66 0.93

0.80 0.54– 0.59

0.78– 0.57– 0.98 1.11

0.74 1.11– 1.25

Varanasi

2011

0.67

0.68 0.78

0.90

0.70

0.72 1.20

Kanpur

2011

0.60– 0.67

NA

NA

NA

0.54– 0.79

NA

NA

G College 2011

0.60– 0.85

NA

NA

NA

0.85– 1.05

NA

NA

0.60 0.76

0.63

0.66

0.77 1.27

NA

NA

0.65– 0.91

NA

Delhi

Kanpur

2005– 0.59 2010

G College 2009

0.51– 0.77

NA

NA

Delhi

2006– 0.47 2015

0.42 0.86

0.69

1.01

1.31 1.51

Varanasi

2006– 0.59 2015

0.49 0.76

0.89

0.79

1.37 1.50

Kanpur

2006– 0.55 2015

0.54 0.79

0.70

0.84

1.35 1.44

Patna

2006– 0.50 2015

0.52 0.70

0.93

0.87

1.29 1.40

Kanpur

2001– 0.54 2003

0.66 0.63

0.57

0.60

0.66 1.12

Pre-mo pre-monsoon, Mo monsoon, Post-mo post-monsoon, Win winter

References Kumar et al. (2020d) 1.09 Tiwari et al. (2018) 1.02 Tiwari et al. (2016) 1.13 Sharma et al. (2013) 0.97 Lodhi et al. (2013) 0.98– Taneja 1.06 et al. (2017) 1.11 Tiwari and Singh (2013) NA Tiwari et al. (2013) NA Tiwari et al. (2013) 1.24 Kaskaoutis et al. (2012) NA Srivastava et al. (2011) 1.43 Kumar et al. (2018) 1.53 Kumar et al. (2018) 1.45 Kumar et al. (2018) 1.50 Kumar et al. (2018) 1.26 Singh et al. (2004)

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Fig. 4.2  Variations of daily mean AOD500 and α380–870 over Varanasi in 2011–2014. The annual mean is represented by a solid red line, while the dash red lines are representing the ±1σ from the annual mean line. (Adopted from Tiwari et al. 2018)

around these regions. Higher AODs during the post-monsoon season are due to the strong influence of the crop residue burning in Punjab/Haryana and accumulating smoke plume over the IGP including Greater Noida (Sharma et  al. 2013), Delhi (Lodhi et al. 2013; Tiwari et al. 2016), and Kanpur (Kaskaoutis et al. 2013). The daily mean variations of ground-based AOD500 as a function of α380–870, collected by handheld MICROTOPS-II Sunphotometer from 2011 to 2014 over Varanasi, are presented in Fig. 4.2. The vast variations in AODs (0.23–1.89) and α (0.19–1.44) with mean values of 0.82  ±  0.31 and 0.96  ±  0.26, respectively, present over Varanasi demonstrate the distinct sources and atmospheric/meteorological conditions. The AOD values above the annual mean are found nearly for 44% days, while the α values are about 55% of the days above the annual mean line. Spatial heterogeneity in AOD was observed to be high in the Varanasi region in almost all seasons (Tiwari et  al. 2018). The higher values of AOD during the pre-monsoon months were primarily caused by the frequent occurrence of dust storms from the Thar Desert region which transported dust particles to the study site (Kaskaoutis et al. 2013; Lodhi et al. 2013). Prevailing winds over the region during the winter season are originated from the West to Northwest with comparatively low wind speed than pre-monsoon months. Very high AODs > 1.1 indicate the turbid conditions over Varanasi which are generally due to enhancement of the fine mode anthropogenic or biomass/wood burning aerosols during post-monsoon and winter. Throughout post-monsoon and winter days, AOD was relatively higher than the other days. Seasonal AODs observed over Varanasi are found relatively similar to those reported in Greater Noida (Sharma et al. 2013) and to some extent lower than New Delhi (Tiwari et al. 2016).

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The lower values of α are found in months April–June reflecting the influence of the transported dust plumes carrying higher concentrations of coarser particles from the Middle East and the Thar Desert. However, during post-monsoon and winter, the particle sizes are varying in the range from fine to very fine. The dominance of coarse particles over the IGP during pre-monsoon is due to dust storms from the west (Singh et al. 2004; Tiwari et al. 2016). The α > 1 values are more conspicuous in post-monsoon (about 91% days) and winter (about 75% days) which represents a relatively higher concentration of fine mode particles. Singh et al. (2004) and Tiwari et al. (2016) suggested the possibility of the hygroscopic growth of fine anthropogenic aerosols in Kanpur and New Delhi, respectively, during the humid monsoon season. An increase in higher concentrations of fine mode aerosols leads to an increase of haze, clouds, and fog and reduces visibility in winter. In the winter season, almost the whole IGP region is frequently wrapped by dense haze and fog (Gautam et al. 2007).

4.2.3  Morphological and Chemical Characteristics The physicochemical properties of atmospheric aerosol show a large variability on a spatiotemporal scale due to various emission sources and chemical compositions (Ram and Sarin 2010; Ram et al. 2016). The SEM-EDX analysis-based morphology of aerosols is describing soot, aluminosilicates, and tarball-like elements originating from construction source, crust, and coal-burning over the middle IGP (Pipal et al. 2011). Pratap et al. (2020c) found the prevalence of carbon-rich particles in November 2016–February 2017 in the suburban region because of biomass burning and other anthropogenic sources present in Varanasi. Some studies have also described the presence of soot, crystalline, and flaky elements commencing from crustal, vehicular, and long-range transportation (Srivastava et  al. 2009; Prabhu et  al. 2019). Carbonaceous aerosols are an abundant component of atmospheric aerosols, contributing about 20–70% of particulate matter, primarily allied with fine fractions of aerosol (Ram and Sarin 2015). It includes a major share of organic aerosols (OA), black carbon (BC), or elemental carbon (EC), which is comparatively low (≤10%) (Ram and Sarin 2010). Generally, in the middle IGP, aerosols are categorized into four types: background aerosols, pollution-dominated aerosols, dust-dominated aerosols, and mixed aerosols. The amounts of these four types of aerosols vary with meteorological conditions. Background aerosols have minimum dust and pollution which is at all times present in pre-monsoon. The higher concentration of Ca indicates dust-dominated aerosols, while pollution-dominated aerosols contain a higher amount of elemental carbon mass (BC mass). The chemical characterization of the middle IGP aerosol indicates the most common presentation of distinctive crustal elements like Ca, Mg, and Fe which are found in higher concentrations in dust-dominated days. Pollution-dominated aerosols are augmented through anthropogenic elements, viz., Se, Zn, V, and Cr (Misra

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et al. 2014). The PM10 samples were found affluent in Al, Si, and Ca. Higher vehicular traffic and anthropogenic activities lead to a higher concentration of Al-, Si-, S-, and C-rich aerosols. Ionic contents present in the following sequence: Na+ > SO42−  > Ca2+ > Cl− > Mg2+ > NO3− > K+ > HCO3+ > F. Common cationic species were Na+, H+, K+, Ca2+, and Mg2+ in samples, although Cl−, SO4−, and NO3− were common anions associated with relatively lesser amount of F− (Singh et al. 2014). The morphological representation from the collected aerosol sample is shown in Fig. 4.3. The SEM-EDX analysis in the current study described that in PM2.5 samples C, F, O, and Al elements are dominating. However other elements such as S, Si, Mo, and N were also present in the aerosol samples. In the PM10 samples, O, C, Si, K, and S were found dominating. However, some other elements like Fe, Ca, Na, Al, and Si were also present in Varanasi. In IC analysis, the anionic contents of the aerosols showed the following trend as SO42- > NO3− > Cl− > F− in both PM2.5 and PM10 samples throughout all seasons. However, cations showed the trend as Ca2+ > Na+ > K+ > Mg2+ > Li+ in PM2.5 and PM10 samples in the current investigation. A similar pattern was observed in the suburban region of Varanasi by Kumar et al. (2020d). SO42−, Cl−, K+, NO3−, Na+, Ca2+, and Mg2+ are the main ionic species

Fig. 4.3  Morphological representation of elements present in PM2.5 (left) and PM10 (right) samples collected at Varanasi by SEM-EDX study

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present in the PM samples found by IC analysis in the suburban region of Varanasi (Pratap et al. 2020c). The pattern of ionic contents was identified as Na+ > SO42− >  Ca2+ > Cl− > Mg2+ > NO3− > K+ > HCO3+ > F− over urban areas, though pattern over suburban areas was identified as Na+ > SO42− > NO3− > Ca2+ > Cl− > Mg2+ > K+ >  HCO3+ > F− for Varanasi by Singh et al. (2014). They have shown the urban areas were more polluted than the suburban areas of Varanasi in his research.

4.3  Spaceborne Observations Satellite remote sensing is widely used in practice for research purposes, for example, in emission estimation, long-range trend analysis, air quality forecasting, etc. Satellite data may also be applicable to improve air quality models that are used in the development of State Implementation Plans. Particularly, remote sensing is capable of assessing the quality of model forecast pollutants (Kondragunta et  al. 2008), biogenic emissions of VOCs. Diverse aerosol- and climate-/weather-­ associated research have been performed by remote sensing techniques (Kumar et al. 2019). Satellite remote sensing is found as a crucial technique regarding aerosol feature information for climate change assessment (King et al. 1999). MISRand MODIS-derived products are extensively used worldwide (Kalashnikova and Kahn 2008). Hsu et al. (2012) used satellite-inferred AOD information for regional as well as global blueprint using Sea-Viewing Wide Field-of-View Sensor. Torres et al. (2010) used the MODIS and Ozone Monitoring Instrument data for abnormal biomass burning assessment in the Southern Hemisphere. Mapping and analysis of different ground and satellite data depend on geophysical parameters. For instance, Giovanni is utilized for time series and area-averaged image map investigation (Prados et al. 2010). Aerosols represent an exceedingly variable atmospheric component which is characterized by several parameters such as scattering and absorption coefficient, particle size, morphology mass concentration, horizontal along with vertical distribution, etc. Precise monitoring of these variables is very complex and challenging; therefore, the effects of aerosol on climate and environment are described as a very uncertain factor for the research community. MODIS data (Kumar et al. 2020b) is still most frequently analyzed by the scientific community; however, it is not associated with polarimetric or multi-angular capabilities. Several updated data retrieval approaches (Dark Target; Hybrid Extinction Retrieval Algorithm) are proposed to tackle limitations and challenges. These approaches lead to more precise retrievals of important aerosol variables like AOD, aerosol extinction profile, etc.

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4.4  Aerosol Emission Sources The IGP region is one of the main regions with aerosol emission/accumulation and becomes a hotspot for aerosol research. It is surrounded by dense population and industries where various aerosol types like mineral dust, soot, sulfate, nitrate, and organics are formed and transported. This region has both urban and semi-urban populations and has different types of natural as well as industrial emissions. In semi-urban areas, emissions from the burning of crop waste, dung cake, and wood are primary sources of aerosol loading. Even so, fossil fuel burning emissions like petrol, coal, and diesel oil combustions dominate in urban regions (Tiwari et  al. 2009). A few sources additionally contribute pollution to the IGP, for instance, coal-­ based power plants, crop burning, and forest fire (Habib et al. 2006). The seasonal back trajectories were set up to be aware of the sources at different elevations using the Hybrid Single-Particle Lagrangian Integrated Trajectories (HYSPLIT) model (Draxler and Rolph 2010). Figure 4.4 shows the seasonal 5 days air mass backward trajectories for altitudinal variation (in meter) of air masses using the HYSPLIT model over Delhi.

Fig. 4.4  Seasonal 5 days air mass backward trajectories for (a) pre-monsoon, (b) monsoon, (c) post-monsoon, and (d) winter season for altitudinal variation (in meter) of air masses using the HYSPLIT model over Delhi. (Adopted from Tiwari et al. 2016)

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The long-range transported dust was mostly originated from the Middle East, oceanic region, and the Thar Desert of Rajasthan during the pre-monsoon season (Fig.  4.4a). Srivastava et  al. (2012) reported the transported aerosols that mostly originated from the desert region significantly dominated over the IGP during the pre-monsoon season. However, aerosols are coming from the oceanic region during the monsoon season (Fig. 4.4b). During the post-monsoon season, mostly aerosols are locally originated except in few occasions by long-range transportation (Fig. 4.4c). The biomass/crop residue burning from Pakistan, Punjab, and Haryana is the main source of fine mode aerosols during the post-monsoon season, transported up to the middle IGP region under suitable meteorological conditions. In the winter season, the aerosols at higher altitudes are coming from long-range transportation (Fig. 4.4d). However, anthropogenic/local activities are the major sources of aerosol generation at lower altitudes.

4.5  Aerosol Impacts on Regional Climate A variety of aerosols present are noticeable all around and can affect our Earth’s air directly by absorbing/scattering the incoming sun radiation (Schwartz et al. 1995). Aerosols strongly influence atmospheric visibility and total atmospheric energy budget, as well as climate dynamics. Likewise, aerosols influence indirectly the climate system by going about as cloud condensation nuclei and ice nuclei and consequently alter the cloud properties and their impacts (Panicker et al. 2010). The regional climate changes appear to be through aerosols’ either warming or cooling effects, which rely upon their microphysical and chemical parameters. The enormous warming in the atmosphere, during pre-monsoon months, presumably because of the mixing of natural dust with anthropogenic/manmade aerosols, may carry in excess energy to the atmosphere which can have a large effect on regional climate (Pilewskie 2007). The increase of haze, fog, and cloudy conditions reduces the atmospheric visibility in particular during winter season which demonstrates the direct impact on the weather (Singh et al. 2004). Kumar et al. (2011) exhibited the noteworthy effect of Northern India biomass burning on aerosols, trace gases, and radiation budget over the central Himalayas during spring season. Aerosols have adverse impacts significantly over the air quality and environment, in addition to human health from regional to global scale. Heterogeneities in aerosol loading exceptionally rely upon different components like topographical and geological features (Ramanathan and Ramana 2005) and the strength of emission sources alongside meteorological variables (Banerjee et al. 2015). The source apportionment studies of ambient aerosols have been discussed by several researchers from time to time which have shown significant impacts on the environment and human health (Singh et al. 2017; Mhawish et al. 2018; Choudhary et al. 2019a). A strong correlation was observed between aerosols and climatic factors; their interaction is very complex and dynamic, which significantly impacts on global climate change (Mhawish et al. 2018). Aerosol particles hanging in the air

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are well connected to the heating of the lower troposphere (Kumar et  al. 2017), which modify the solar insolation (Xia et al. 2007) and thermal equilibrium of the atmosphere (Satheesh et al. 2009). The combination of all these aspects is deteriorating the environment (Banerjee and Srivastava 2011; Choudhary et al. 2019b), as well as modifying circulation systems (Ramanathan and Carmichael 2008). Limited ground-based aerosol monitoring frameworks offered remote sensing to quantify the spatiotemporal variation of aerosols and study the biomass burning evidence and its impact on regional air quality. The remote sensing-based fire products and their potential to characterize the crop residue burning events and their impacts on air quality are highlighted by Vadrevu et al. (2011). Kaskaoutis et al. (2014) utilized in situ and satellite-based perceptions (MODIS and OMI), assessed the effect of rice crop residue burning over Northern India during post-monsoon, and watched a thick aerosol layer over the IGP. Sharma et al. (2010) recognized the impacts of crop residue burning on aerosol characteristics using in situ and multi-sensor satellite data with high AOD and α value. The escalating aerosol loading satellite observations (MODIS and MISR) over major cities of the IGP in 2000–2005 demonstrate the effect of natural and anthropogenic sources, especially biomass burning, bringing about various climatic implications (Prasad and Singh 2007). The impacts of aerosol emissions from a variety of natural, anthropogenic sources and the existing meteorology support us to further investigate the logical causes and impacts over the radiation budget on weather and climate.

4.6  Summary and Future Prospects The present study has presented aerosol characteristics, emission sources, and long-­ range transportation, which show a significant gradient in the magnitude of aerosol properties. This type of gradient in the magnitude of aerosol properties may be because of regular changes in the climatic variables and/or sources of emissions, which brought an impact on the atmosphere of the “Earth.” So, in-depth aerosol study is highly needed for a longer period in different regions to enhance the understanding of physicochemical characteristics along with its impacts. The aerosol characteristics from satellite-based remote sensing have been used most efficiently in several previous research works to validate ground-based observations and to investigate the aerosol association with climate change. Accordingly, the accessibility of near-real-time remote sensing data will accurately help in air quality determining and advancement of effective health advisory services shortly. Mostly during the pre-monsoon season, the IGP region is found to be affected by enhanced dust aerosols from the Thar Desert. Further, during the winter season, the fog was observed as a common feature over the IGP region in Northern India. During the winter season, the number of foggy days is increasing with increasing trends of anthropogenic aerosols over the IGP region. Fog accumulation begins in mid-­ December and continues till the middle of January. Increasing fog is significantly affecting the lives of millions of peoples in progressive days in different regions of

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the world. Intense fog decreases visibility distance (less than 100  m) and affects flights and trains. A few quantities of passing happen in numerous merciless occasions like vehicular mishaps (Hameed et al. 2000). Thus, it is needed urgently for recent and accurate modeling approaches and studies over Northern India to scrutinize the influence of increasing aerosols. Acknowledgments  The present work is supported by SERB, New Delhi, India, under a sanctioned project (PDF/2017/001898). This work is also sponsored by the UGC–New Delhi under the UGC sanctioned project No.F.4-2/2006 (BSR)/ES/18-19/0041. Aerosol mass concentration data were collected from the India Meteorological Department, New Delhi.

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Prados AI, Leptoukh G, Lynnes C, Johnson J, Rui H, Chen A, Husar RB (2010) Access, visualization, and interoperability of air quality remote sensing data sets via the Giovanni online tool. IEEE J Sel Top Appl Earth Obs Remote Sens 3:359–370 Prasad AK, Singh RP (2007) Changes in aerosol parameters during major dust storm events (2001–2005) over the Indo-Gangetic Plains using AERONET and MODIS data. J Geophys Res Atmos 112(D9):1–10 Pratap V, Kumar A, Kumar P, Singh AK (2020a) Seasonal variability of atmospheric aerosols over Varanasi Region during 2010–2016. In: 2020 URSI Regional Conference on Radio Science (URSI-RCRS). IEEE, pp 1–3 Pratap V, Kumar A, Kumar P, Singh AK (2020b) Pre-monsoon study of aerosol parameters and particulate matters over Varanasi for 2017. In: 2020 URSI Regional Conference on Radio Science (URSI-RCRS). IEEE, pp 1–2 Pratap V, Kumar A, Tiwari S, Kumar P, Tripathi AK, Singh AK (2020c) Chemical characteristics of particulate matters and their emission sources over Varanasi during winter season. J Atmos Chem 77:83–99 Ram K, Sarin MM (2010) Spatio-temporal variability in atmospheric abundances of EC, OC and WSOC over Northern India. J Aerosol Sci 41:88–98 Ram K, Sarin MM (2015) Atmospheric carbonaceous aerosols from Indo-Gangetic Plain and Central Himalaya: impact of anthropogenic sources. J Environ Manag 148:153–163 Ram K, Singh S, Sarin MM, Srivastava AK, Tripathi SN (2016) Variability in aerosol optical properties over an urban site, Kanpur, in the Indo-Gangetic Plain: a case study of haze and dust events. Atmos Res 174:52–61 Ramachandran S, Cherian R (2008) Regional and seasonal variations in aerosol optical characteristics and their frequency distributions over India during 2001–2005. J Geophys Res Atmos 113(D8). https://doi.org/10.1029/2007JD008560 Ramanathan V, Carmichael G (2008) Global and regional climate changes due to black carbon. Nat Geosci 1:221–227 Ramanathan V, Ramana MV (2005) Persistent, widespread, and strongly absorbing haze over the Himalayan foothills and the Indo-Gangetic Plains. Pure Appl Geophys 162:1609–1626 Sah D, Verma PK, Kandikonda MK, Lakhani A (2019) Pollution characteristics, human health risk through multiple exposure pathways, and source apportionment of heavy metals in PM10 at Indo-Gangetic site. Urban Clim 27:149–162 Sarangi C, Tripathi SN, Kanawade VP, Koren I, Pai DS (2017) Investigation of the aerosol-­ cloud-­ rainfall association over the Indian summer monsoon region. Atmos Chem Phys 17(8):5185–5204 Satheesh SK, Moorthy KK, Kaufman YJ, Takemura T (2006) Aerosol optical depth, physical properties and radiative forcing over the Arabian Sea. Meteorog Atmos Phys 91:45–62 Satheesh SK, Vinoj V, Babu SS, Moorthy KK, Nair VS (2009) Vertical distribution of aerosols over the east coast of India inferred from airborne LIDAR measurements. In: Annales geophysicae: atmospheres, hydrospheres and space sciences, vol 27. Springer, Heidelberg, p 4157 Schwartz SE, Arnold F, Blanchet JP, Durkee PA, Hofmann DJ, Hoppel WA, King MD, Lacis AA, Nakajima T, Ogren JA, Toon OB (1995) Group report: connections between aerosol properties and forcing of climate. In: Aerosol forcing of climate. Wiley, Chichester, pp 251–280 Sen A, Abdelmaksoud AS, Ahammed YN, Banerjee T, Bhat MA, Chatterjee A, Choudhuri AK, Das T, Dhir A, Dhyani PP, Gadi R (2017) Variations in particulate matter over Indo-Gangetic Plains and Indo-Himalayan Range during four field campaigns in winter monsoon and summer monsoon: role of pollution pathways. Atmos Environ 154:200–224 Sharma AR, Kharol SK, Badarinath KVS, Singh D (2010) Impact of agriculture crop residue burning on atmospheric aerosol loading  – a study over Punjab State, India. Ann Geophys 28:367–379 Sharma M, Kaskaoutis DG, Singh RP, Singh S (2013) Seasonal variability of atmospheric aerosol parameters over Greater Noida using ground sunphotometer observations. Aerosol Air Qual Res 14:608–622

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Singh RP, Dey S, Tripathi SN, Tare V, Holben B (2004) Variability of aerosol parameters over Kanpur, northern India. J Geophys Res Atmos 109(D23):D23206 Singh AK, Srivastava MK, Singh M, Srivastava AK, Kumar S, Tiwari S, Singh BP, Bisht DS (2014) Characterisation of atmospheric aerosol by SEM-EDX and Ion-chromatography techniques for eastern Indo-Gangetic plain location, Varanasi, India. Int J Adv Earth Sci 3:41–51 Singh N, Murari V, Kumar M, Barman SC, Banerjee T (2017) Fine particulates over South Asia: review and meta-analysis of PM2. 5 source apportionment through receptor model. Environ Pollut 223:121–136 Sorek-Hamer M, Cohen A, Levy RC, Ziv B, Broday DM (2013) Classification of dust days by satellite remotely sensed aerosol products. Int J Remote Sens 34:2672–2688 Srivastava R, Ramachandran S (2013) The mixing state of aerosols over the Indo-Gangetic Plain and its impact on radiative forcing. Q J R Meteorol Soc 139:137–151 Srivastava A, Jain VK, Srivastava A (2009) SEM-EDX analysis of various sizes aerosols in Delhi India. Environ Monit Assess 150:405 Srivastava AK, Tiwari S, Devara PCS, Bisht DS, Srivastava MK, Tripathi SN, Goloub P, Holben BN (2011) Pre-monsoon aerosol characteristics over the Indo-Gangetic Basin: implications to climatic impact. Ann Geophys 29:789–804. Copernicus GmbH Srivastava AK, Dey S, Tripathi SN (2012) Aerosol characteristics over the Indo-Gangetic Basin: implications to regional climate. Atmos Aerosols Reg Charact Chem Phys 10:47782 Srivastava AK, Yadav V, Pathak V, Singh S, Tiwari S, Bisht DS, Goloub P (2014) Variability in radiative properties of major aerosol types: a year-long study over Delhi – an urban station in Indo-Gangetic Basin. Sci Total Environ 473:659–666 Taneja K, Attri SD, Ahmad S, Ahmad K, Soni VK, Mor V, Dhankhar R (2017) Comparative assessment of aerosol optical properties over a mega city and an adjacent urban area in India. Mausam 68:673–688 Tiwari S, Singh AK (2013) Variability of aerosol parameters derived from ground and satellite measurements over Varanasi located in the Indo-Gangetic Basin. Aerosol Air Qual Res 13:627–638 Tiwari S, Srivastava AK, Bisht DS, Bano T, Singh S, Behura S, Srivastava MK, Chate DM, Padmanabhamurty B (2009) Black carbon and chemical characteristics of PM 10 and PM 2.5 at an urban site of North India. J Atmos Chem 62:193–209 Tiwari S, Srivastava AK, Singh AK (2013) Heterogeneity in pre-monsoon aerosol characteristics over the Indo-Gangetic Basin. Atmos Environ 77:738–747 Tiwari S, Hopke PK, Pipal AS, Srivastava AK, Bisht DS, Tiwari S, Singh AK, Soni VK, Attri SD (2015) Intra-urban variability of particulate matter (PM2.5 and PM10) and its relationship with optical properties of aerosols over Delhi, India. Atmos Res 166:23–232 Tiwari S, Tiwari S, Hopke PK, Attri SD, Soni VK, Singh AK (2016) Variability in optical properties of atmospheric aerosols and their frequency distribution over a mega city “New Delhi,” India. Environ Sci Pollut Res 23:8781–8793 Tiwari S, Kaskaoutis D, Soni VK, Attri SD, Singh AK (2018) Aerosol columnar characteristics and their heterogeneous nature over Varanasi, in the central Ganges valley. Environ Sci Pollut Res 25:24726–24745 Torres O, Chen Z, Jethva H, Ahn C, Freitas SR, Bhartia PK (2010) OMI and MODIS observations of the anomalous 2008-2009 Southern Hemisphere biomass burning seasons. Atmos Chem Phys 10(8):3505–3513 Vadrevu KP, Ellicott E, Badarinath KVS, Vermote E (2011) MODIS derived fire characteristics and aerosol optical depth variations during the agricultural residue burning season, north India. Environ Pollut 159:1560–1569 Wang J, Christopher SA (2003) Intercomparison between satellite-derived aerosol optical thickness and PM2. 5 mass: implications for air quality studies. Geophys Res Lett 30(21):2095 World Health Organization (2014) Burden of disease. World Health Organization, Geneva World Health Organization (2016) Ambient air pollution: a global assessment of exposure and burden of disease. World Health Organization, Geneva

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Xia X, Li Z, Holben B, Wang P, Eck T, Chen H, Cribb M, Zhao Y (2007) Aerosol optical properties and radiative effects in the Yangtze Delta region of China. J Geophys Res Atmos 112(D22). https://doi.org/10.1029/2007JD008859 Zhao H, Zhang X, Zhang S, Chen W, Tong DQ, Xiu A (2017) Effects of agricultural biomass burning on regional haze in China: a review. Atmosfera 8:88

Chapter 5

Impacts of Air Pollution on Himalayan Region Palak Balyan

Abstract  Himalaya is an ecologically fragile region. Around 1.3 billion people are dependent on Himalaya for their water, energy, and economic needs. Air quality in the Himalayan region has deteriorated significantly in past decades. Air pollution is on the rise in the Himalayan region, and pollutant levels have crossed World Health Organization (WHO) annual prescribed standards at many places. Seasonal and diurnal cycles of air pollutants are observed in the Himalayan region, with both emission sources and meteorology significantly affecting air pollutant levels. The causes of the rapid rise in air pollutant levels are population growth, rapid and unplanned urbanization, increase in the number of vehicles, diesel pump sets along with traditional sources such as cookstoves, brick kilns, forest fire, mining industries, and garbage and stubble burning. The pollution in Himalayan not only is in situ but it  also receives a significant amount of air pollution from surrounding regions. Air pollution has significant impacts on the Himalayan region, affecting its ecosystem, health of inhabitants, the cryosphere, water availability, agroforestry, precipitation patterns, seasons, income, and nutrition status. Despite recent improvements in understanding of air quality and its impact, major challenges in air quality monitoring, mitigation effort, and regional coordination networks persist. Promotion and venturing in clean energy, infrastructure, and technology is needed to mitigate air pollution and its effects. Dedicated institutional arrangements with skilled workforce actively engaging multiple stakeholders and enabling inter-agency collaboration and cooperation at both national and regional levels in the Himalayan countries are needed to tackle trans-boundary air pollution and scale and implement policies for mitigationefforts. Knowledge generation and dissemination and public awareness are required to bring behavioral change and build public support for the promulgation and implementation of eco-friendly policies. Keywords  Air pollution · Himalayan region · Environmental impacts · Human health P. Balyan (*) Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, Delhi, India © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021 S. Tiwari, P. Saxena (eds.), Air Pollution and Its Complications, Springer Atmospheric Sciences, https://doi.org/10.1007/978-3-030-70509-1_5

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5.1  Introduction The Himalaya, the world’s highest mountain, India, Nepal, Bhutan, Pakistan, and China having sovereignty over it, with an area of 5,46,00  km2, is known for its exquisite environment (Berthier et al. 2007). The Himalayan mountains are inhabited by 52.77 million (2011) people, and around 1.3 billion people depend upon it for their water and power need (Apollo 2017). Half of the Himalayan population is below poverty line (Apollo 2017) with limited resources and mechanisms for mitigation and adaptation to climate changes. Himalayan air quality is rapidly deteriorating due to the rapid increase in human population and vehicles, degrading forest cover, unplanned industrialization and urbanization, and the frequent occurrence of forest fires (Pradhan et al. 2012; Kim et al. 2015; Sonwani and Saxena 2016). Data from monitoring stations and a number of researches have revealed a rapid rise in air pollutant’s concentration in the Himalayan ranges (Giri et al. 2008; Xu et al. 2009; Putero et al. 2015). In Nepal, the annual average particulate matter below 10 μm (PM10) and PM2.5 concentrations have exceeded WHO standards by factors of 7 and 5, respectively (Putero et al. 2015; World Bank 2016). The gaseous pollutant level has reached an alarming level at many places (Ran et al. 2014). The atmospheric brown cloud (ABC) that formed in the Indo-Gangetic Plain (IGP) penetrates deep into the Himalayan region (Ramana et al. 2004). The Himalayan region is a seismically and tectonically fragile region, and even small tinkering with the environment and geo-ecological balance can trigger changes affecting the health of people, climate, monsoon patterns, forest cover, and economy to an alarming proportion (Nandy et al. 2006; Sonwani and Kulshrestha 2019). It is essential to understand the status of air pollution, enlist emission sources, and compute their contribution to address air pollution in the Himalayan region. An understanding of adverse effect of air pollution and challenges to scale and implement mitigation strategies is necessary for mitigation efforts. This chapter takes a stock on the level of air pollution in the Himalayan region, its sources impact, the need and major challenges for mitigation efforts.

5.2  Topography and Economic Significance of the Himalaya The Himalayan region extends around 2500 KM in length and is about 250–300 km in width. The Himalaya, the world’s highest and youngest folded mountain systems, is a series of four parallel or converging mountain ranges, designated, from north to south, as the Trans-Himalayas, the Great Himalayas, the Lesser Himalayas, and the Outer Himalayas (Nandy et al. 2006). A characteristic feature of Himalayan topography is a large number of bowel-shaped basins and longitudinal, flat-bottomed spindle-shaped valleys lying between the mountain ranges. Most of the Himalayan population is concentrated in these valleys owing to their favorable environmental

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conditions such as conducive climate, availability of fertile soil and water, and irrigation and infrastructural provisions, while the mountainous part and steep inclines possessing adverse conditions is sparsely populated (Sharma 1999; Sonwani and Kulshreshtha 2016). The Himalayan region has abundant natural resources. The Himalaya has enormous water potential, in the forms of glaciers, perennial rivers, springs, lakes, and groundwater. Himalayan glaciers, around 15,000  in number, account for 70% of extra-polar glaciers of the world and cover 17% of total geographical area of the Himalyan region (Negi 1991). The Himalayan rivers drain about 8634 million m3 of water every year (Negi 2003). These perineal river systems met the water need of around 1.3 billion people (Apollo 2017). The Himalayan rivers having cut down their valleys through the rising Himalayan ranges formed a number of longitudinal and transverse valleys (Oldham 1907) acting as a conduit of least resistance for trans-Himalayan wind system (Dhungel et al. 2018). The Himalayan meteorological regime is characterized by synoptic-scale regime superimposed by local meteorological processes lifting air masses over the mountain range. The Himalayan mountains receive humid air masses originating in the Indian Ocean during the monsoon and westerly’s in other seasons facilitating the movement of air masses from the Middle East and South Asia independent of seasonal changes of air circulation pattern (Cong et al. 2015). The local mountain-valley wind system comprised of an up-valley wind in daytime on the southern slope and a predominant down-valley wind known as “glacier wind,” generated by the vast snow cover, occurs on the northern slope of the Himalaya.  The local orography acts as efficient south-to-north air flow channels facilitating easy penetration of the air from IGP to the Himalayan region  (Cong et al. 2015; Saxena et al. 2020) (Fig. 5.1). The Himalaya, one of the biodiversity hotspots of the world, has a heterogeneous dispersion of biodiversity elements due to its enormous span and altitude (Sati

Fig. 5.1  Local orographic transport of air mass from the Indo-Gangetic Plain to the Himalaya

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2014). The Himalayan forests provide a large variety of timber for industries and host a wide variety of medicinal plants (Samant and Palni 2000). Agriculture is the main source of livelihood, characterized by traditionally grown cereal crops. Most of the Himalya have  rugged and sloped terrain, covered by lithosols, formed of imperfectly weathered rock fragments lacking in humus content and are not suitable for agriculture (Suri et al. 2013). The most productive alluvial soils are limited to few valleys and duns. About 34% workforce is involved in horticulture, agriculture, and agriculture-allied practices (Niti Aayog 2018).

5.3  Status of Air Pollution in the Himalayan Region Although the available data are not comprehensive, it shows the Himalayan region has a high level of air pollution at many places. The Himalayan region is surrounded by most polluted cities of the world like Delhi, Peshawar, etc. Along with the pollutant generated in situ, pollutants from these cities penetrate into the Himalayan region.

5.3.1  Air Pollutant Level in the Himalayan Region 5.3.1.1  Particulate Matter Many Himalayan habitats have higher PM10 level than the WHO prescribed standard of 20 μg/m3 averaged over a year (WHO 2006). Figure 5.2 shows the rapid rise in PM10 concentration at the Kathmandu Valley, Nepal, between 2000 and 2014. PM10 concentration at Kathmandu, Nepal 300 250 200 150 100 50 0 2000-2001

2003-2005

2013-2014

Fig. 5.2 PM10 concentration between 1998 and 2014 at Kathmandu, Nepal. (Source: Carrico et al. 2003; Giri et al. 2008; Putero et al. 2015)

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PM2.5 level in the Himalayan countries 60 50

µg/m3

40 30 20 10 0 China

India

Nepal 1993

Pakistan

2013

Fig. 5.3 PM2.5 concentrations between 1993 and 2013 at four Himalayan countries. (Source: World Bank and IHME 2016)

Carrico et al. 2003 recorded average PM10 level of 81 ± 76 μg/m3 at the Kathmandu Valley between 1998 and 2000, whereas the valley had an average PM10 concentration of 123 ± 57 μg/m3 between 2003 and 2005 (Giri et al. 2008). The concentration of PM nearly doubled in subsequent decade with an average PM10 level of 169 ± 113 μg/m3 per annum during 2013–2014 (Putero et al. 2015). PM2.5 level increased by around 50% between 1993 and 2013 in the Himalayan nation (Fig.  5.3). The averaged PM2.5 level in this country was much above the WHO prescribed standard of 10 μg/m3 for PM2.5 (WHO 2006). The highest level of PM2.5 (54.36 μg/m3) was recorded at China, while data for Bhutan was not available (World Bank 2016). The PM2.5 concentration ranged from 8 ± 7 to 57 ± 61 μg/m3 during 1998–2000, and the annual average PM2.5 concentration was 49  μg/m3 in 2013 at Kathmandu (WHO database). Concentration of PM2.5 ranged from 39 to 348 μg/m3 during 2009 to 2010 at the north-eastern Himalya (Rajput et al. 2013). A significant portion of PM2.5 is black carbon (BC). Nair et al. 2013 recorded the mean atmospheric BC concentration of 106  ±  27  ng/m3 over Hanle, western Himalaya and 190 ± 95 ng m−3 over Nepal, central Himalaya Black carbon present in the air settles at a rate of 2.89 μg/m2 per day over glacial ice and lakes at Nepal (Yasunari et  al. 2010). These glacial cores and lake deposits serve as an archive deciphering the long-term trend of air quality (Xu et al. 2009). The historical trends (from 1860 to 2000 AD) reconstructed from a Mount Everest ice core show a multifold rise in BC in recent decades, starting from the 1960s (Kaspari et al. 2011). A threefold rise in BC concentrations was observed in the ice core corresponding to 1975–2000 compared to 1860–1975. BC content has increased two times in the ice core at the southern rim of the Tibetan Plateau from the 1980s to 1990s (Xu et al. 2009).

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5.3.1.2  Gaseous Pollutants A rise in sulfur oxides (SOX) and nitrogen oxides (NOX) is seen in the Himalayan region due to rise in vehicular fleet and industrial, developmental, and recreation activities in the area (Saxena and Naik 2018). The Himalayan region is one of the most visited tourist destinations in Southeast Asia due to its pristine beauty and presence of various pilgrimage sites like Gangotri, Mount Kailash, Amarnath, etc. Ran et  al. 2014 made a comparison of sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) level between 1998 and 2012 at Lhasa. They observed 40 times rise in NO2 concentration during these 15  years. During the sampling period in 1998, measured NO2 never exceeded 2  μg/m3. In contrast, the lowest daily NO2 concentration was around 18 μg/m3, and the highest concentration was close to 54 μg/m3 in 2012. The rise in SO2 level was about three times from about 0.4 μg/m3 to 1.31 μg/m3. O3 concentration increased by around 50% (from 54 to 72  μg/m3) between 1998 and 2012. CO level remained almost constant (around 750 μg/m3) between 1998 and 2012 (Fig. 5.4). Kiros et al. 2016 compiled weekly concentration of NO2, SO2, and O3 level at urban, semi-urban, and rural sites of the Kathmandu Valley and recorded the highest levels of NO2 (25.8 ± 6.5 μg/m3) in urban sites with high traffic density, whereas the highest SO2 concentration (39.2 ± 21.6 μg/m3) was observed at an industrial site which comprises petroleum product industries and low-grade coal-fueled brick kiln factories almost two times than the WHO standard of 20 μg/m3 for SO2 (WHO 2006). Sulfate and nitrate residues for the periods 1000–1997  AD from the Dasuopu glacier reveal that sulfate concentrations in air were very low prior to 1870 but the

SO2 (µg/m3)

NO2 (µg/m3) 70 60 50 40 30 20 10 0

1998

2012

1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0

1998

O3 (µg/m3) 100 90 80 70 60 50 40 30 20 10 0

1998

2012

CO (µg/m3)

2012

1000 900 800 700 600 500 400 300 200 100 0

1998

2012

Fig. 5.4  Comparison of level of NO2, SO2, CO, and O3 between 1998 and 2012 at Lhasa. (Source: Ran et al. 2014)

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rate of increase has accelerated rapidly since 1930, having nearly doubled since 1970 (Duan et al. 2007). This is in contrast to sulfate concentration in the Greenland ice cores where sulfate concentration peaked during the 1970s and reduced by nearly one-third thereafter due to strict environmental and legal provisions in the United States and Europe (Fischer et  al. 1998). Similarly, nitrate concentrations have increased multiple times over recent years as compared to the 1000-year background level at Dasuopu (Thompson et al. 2000). O3, a secondary air pollutant, formed in the presence of sunlight and its precursors, e.g., NOx, volatile organic compounds (VOCs), etc. (Saxena et al. 2019a, b). Ali et al. 2004 recorded O3 concentration in range of 38–85 μg/m3 during 1999–2000 at the north-western Himalaya. A decade later, O3 concentration peaked up to 160 μg/m3 at the north-western Himalaya (Sharma and Kuniyal 2013). During 2003 and 2004, O3 levels exceeded the WHO standard of 100 μg/m3 for O3 for only 12% of the days monitored at the Kathmandu Valley (Pudasainee et al. 2006). Higher O3 (108.5 ± 31.4 μg/m3) was recorded in 2014 (Kiros et al. 2016). Surface O3 level in the central Himalayan region increased with altitude with concentrations that exceed 200 μg/m3 for 8-h exposure at Mount Everest (Semple et al. 2016). 5.3.1.3  Atmospheric Brown Cloud Himalayan ridge forms a sharp northern border of atmospheric brown cloud (ABC) of particles and pollutant gases formed over the Indo-Gangetic Plain (IGP) (Sonwani and Maurya 2018). These clouds extend up to 5 km above sea level penetrating in a large portion of the Himalayan region through deep trans-Himalayan valleys (Ramanathan et al. 2007). Ramana et al. 2004 observed high aerosol optical depth (AOD) signifying the presence of pollutant and particle-rich air mass in the Himalayan region.

5.3.2  Seasonal Trend of Air Pollutants Air quality shows a strong seasonal pattern in the Himalayan regions owing to the emission patterns and meteorology (Saikawa et al. 2019). Giri et al. 2008 compiled PM10 concentrations data from 2003 to 2005 at seven different sites in the Kathmandu Valley (Fig. 5.5a). The minimum PM10 concentration was noted during monsoon season because of air clearing by precipitation. A continuous rise in PM10 concentrations from post-monsoon to winter season was observed due to the accumulation of PM at the bowl-shaped Kathmandu Valley during the winter months. Similar observations were made by Aryal et al. 2008 between 2002 and 2007 at six different sites in the urban area of Kathmandu and during 2013–2014 by Putero et al. 2015 (Fig. 5.5b). BC aerosols with the capacity to perturb the radiation balance peak in pre-­ monsoon season in the Himalayan air. Sarkar et al. 2015 observed a seasonal pattern

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a) Seasonal variation of PM 10 at Kathmandu valley during 2003-2005 250

µg/m3

200 150 100 50 0 Pre-monsoon

Monsoon

Post-monsoon

Winter

b) Seasonal variation of PM10 at Kathmandu valley during 2013-2014 450 400 350

µg/m3

300 250 200 150 100 50 0 Pre-monsoon

Monsoon

Post-monsoon

Winter

Fig. 5.5  Seasonal variation of PM10 at the Kathmandu Valley during (a) 2003–2005 and (b) 2013–2014. (Source: Giri et al. 2008; Putero et al. 2015)

of black carbon with the highest concentration in pre-monsoon (5.0 ± 1.1 μg/m3) than in winter (3.9 ± 2.2 μg/m3) and post-monsoon (2.9 ± 1.0 μg/m3) and lowest in monsoon (1.7  ±  0.7  μg/m3) over Darjeeling in the eastern Himalaya (Fig.  5.6a), whereas Putero et  al. 2015 observed the highest BC concentration during winter season (18.3 ± 14.1 μg/m3) in the Kathmandu Valley (Fig. 5.6b). This difference in seasonal pattern is attributable to heterogeneity in emission sources at these places. Pre-monsoon is the best season for tourists in Darjeeling. The huge number of tourist vehicles along with the increased frequency of coal run toy train emits á considerable amount of BC during pre-monsoon tourist season. Further, transport of BC from north-west India by pre-monsoon westerly contributes to BC at Darjeeling (Sarkar et al. 2015). The high winter concentration of BC at the Kathmandu Valley can be due to increased use of power generators, rise in emissions from domestic heating,refuse burning and thermal inversion. Kumar et  al. 2010 measured O3 concentration from 2006 to 2008 at Manora Peak/Nainital and found the highest O3 concentration in late spring (May:

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a) Black carbon at Darjeeling during 2010-2011 7 6

µg/m3

5 4 3 2 1 0 Pre-monsoon

Monsoon

Post-monsoon

Winter

b) Black carbon at kathmandu during 2013 35 30

µg/m3

25 20 15 10 5 0 Pre-monsoon

Monsoon

Post-monsoon

Winter

Fig. 5.6  Seasonal pattern of black carbon at (a) Darjeeling and (b) Kathmandu. (Source: Sarkar et al. 2015; Putero et al. 2015)

67.2  ±  14.2  ppb) and lowest in the summer and monsoon season (August: 24.9 ± 8.4 ppb). Increase of O3 concentrations in late springs is due to the production of O3 precursors during agro-residue burning (Kiros et al. 2016).

5.3.3  Diurnal Trend of Air Pollutant PM and CO have been found to exhibit a diurnal pattern with morning and evening peaks in the Kathmandu Valley, Nepal. Similar diurnal pattern has also been noted in BC concentrations in Pantnagar (Joshi et  al. 2016) and in Darjeeling, India (Sarkar et al. 2015). The diurnal pattern of pollutant is mainly due to the presence of heavy traffic in the morning and evening along with the pollutant transport by mountain and valley wind pattern observed in the Himalaya (Shrestha et al. 2010). The pattern of daytime peak with fall in concentration during night is found in tropospheric ozone (formed in sunlight by catalytic reaction of NOX) in Kathmandu (Putero et al. 2015).

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5.4  Source of Air Pollution in the Himalayan Region It is a prerequisite to understand the emission sources and their intensity to address the problem of air pollution. Air pollutants are emitted from a range of both anthropogenic and natural sources in the Himalayan region (Fig. 5.7). Kim et  al. 2015 conducted a source apportionment study for PM10 in the Kathmandu Valley (Fig. 5.8a). Major emission sources of PM10 in the Himalayan region are soil dust, transport vehicles, heating and cooking fires, forest fires, combustion of garbage, agricultural stubble, and industries, while the major emitter of SO2 and NOx were industries and transport sector, respectively (Pradhan et  al. 2012) (Fig.  5.8b and c). Further, bowl and spindle spoon-like topography of the Himalayan valleys restricts the air movement and retains the air pollutants within valleys. This is especially worse during the winter when thermal inversion keeps pollutants sealed within the valleys. The Himalaya has diversified source apportionment pattern of pollutants based on heterogeneous distribution of emission sources and their emission intensity. Fossil fuel (46%) and bio-fuel (54%) burning contribute equally to BC in the southern Himalaya congruous with BC source appropriation pattern from the Indo-­ Gangetic Plain, whereas in the northern Himalaya, the predominant source of BC is fossil fuel (66%), agreeing with Chinese pattern (Li et al. 2016).

Solid fuel for cooking &heang

Transported polluon

Forest and scrub fire PM,O3,SOX, NOX,BC, VOCs, CO2 & other GHGs

Vehicles and diesel engines

Stubble and garbage burning

Industrial growth and urbanizaon

Fig. 5.7  Source of air pollution in Himalayan region

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a) Source apportionment for PM 10 at Kathmandu

27%

31%

Soil dust Industrial

15%

5%

Biomass and garbage burning Secondary

22%

Transport

b) Source apportionment for SO2 at Kathmandu 0.2%

0.5%

0.3%

16%

Power generaon

9%

Manufacturing sector Transport

74%

Crop residue Garbage burning Other (Forest fire etc.)

c) Source apportionment for NOx at Kathmandu 0.5% 1%

0.85% 6.3% 6% 6

Power generation Manufacturing sector Transport Crop residue

85.5%

Garbage burning Other (Forest fire etc.)

Fig. 5.8  Source apportionment for (a) PM, (b) SO2, and (c) NOx at Kathmandu. (Source: Pradhan et al. 2012; Kim et al. 2015)

5.4.1  Solid Fuel for Cooking and Heating The cheap and ample availability of solid biofuel in the region along with poor access to clean fuel makes it the obvious choice for domestic cooking and heating. Emission factors (EF), i.e., units of pollutant mass emitted per kilogram of fuel

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combusted, of PM2.5 calculated from field tests at Nepal were 10.7 ± 1.6 gkg − 1 for hardwood, 5.3  ±  0.8  gkg  −  1 for twigs, 14.5  ±  2.2  gkg  −  1 for dung, and 15.0 ± 2.3 gkg − 1 for a mixture of dung and hardwood. The PM2.5 mass emitted by traditional cookstove contains 49–68% OC and 3.3–18% EC (Jayarathne et  al. 2018). Rupakheti et al. 2019 observed marked diurnal variations of the pollutants with the highest concentrations during cooking times in sampled kitchens at the Kathmandu Valley. The PM and BC levels rose steeply during cooking.

5.4.2  Forest and Scrub Fires Forest and scrub fires are common in the Himalayan region especially in foothills due to the close proximity to dense populated area during the dry season (Rupakheti et al. 2017). Kimothi and Jadhav 1998 reported a loss of 22% of forest by fire burn in four districts of Himalaya in 1 year. Around 4000 per year fire incidents were reported in the Himalayan region between 2005 and 2010, burning around 1129 km2, producing black carbon emission of 431 tyear−1 (Vadrevu et al. 2012). An average 533.81 mg m−2 day−1 CO, 69.7 mg m−2 day−1 non-methane VOCs (NMVOCs), and 13.66 mg m−2 day−1 NOx were emitted due to forest fire for the month of April during 2003–2016 over the southern Himalayan region (Kumar et al. 2019).

5.4.3  Stubble and Garbage Burning The open-field burning of stubbles is done by farmers to clear fields for the next crop after mechanical harvesting. Agricultural stubble burning emits organic and black carbon aerosols and gaseous air pollutants, like CH4, NOx, CO, CO2, and NMVOCs (Sharma et al. 2010). Burning of 1 kg of wheat straw and maize stover releases 1690 ± 580 mg and 1590 ± 430 mg of NMVOCs, respectively (Li et al. 2009). In situ crop residue burning in India emitted 141.15 Mt. of CO2 (92%), 8.57 Mt. of CO (2.7%), 0.037 Mt. of SOx, 0.23 Mt. of NOx, 0.12 Mt. of NH3, 1.46 Mt. of NMVOC, and 1.21 Mt. of particulate matter for the year 2008–2009. Major emitters were from the IGP states accounting for around two-thirds of total emission from stubble burning in India (Jain et al. 2014). These emissions accentuate the formation of the ABC and to the worsening winter fog in the Himalaya. The open burning of waste is one of the accepted and routine ways to treat garbage in South Asia (Idris et al. 2004; Asian Productivity Organization 2007). The emission pattern varies substantially with garbage composition. Garbage burning emits Sb, Cu, Pb, and other trace elements along with CO, BC, PM, and OC (Jayarathne et al. 2018).

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5.4.4  Industrial Growth and Urban Housing The Kathmandu Valley housed 14,791 industrial units in 2010 (Pradhan et al. 2012). Of these, brick making and cement industries contribute to two-thirds of total suspended particles at Kathmandu (URBAIR program, world bank). The demand of bricks and, hence, number of brick kilns are on the rise with urbanization in the Himalayan and surrounding region. Three-fourths of global brick production occur in four Himalayan and neighboring countries China, India, Pakistan, and Bangladesh (Saikawa et al. 2019). Around 80% of bricks in the Himalayan countries are produced by fixed chimney Bull’s trench kiln (FCBTK), the most polluting kiln types (Greentech 2014). Nepal has around 1000 FCBTK (Weyant et al. 2014) fueled by high sulfur coal and biomass (Joshi and Dudani 2008). The brick kilns emit 2.5 Tg year−1 CO, 120  Tg year−1 CO2, 0.12  Tg year−1 EC, and 0.19  Tg year−1  PM2.5 in Southeast Asia (Weyant et al. 2014). Brick kilns contribute more than two-thirds of total SO2 (Pariyar et al. 2013) and 40% of BC concentration emissions (Kim et al. 2015) in the Kathmandu Valley. Regions within 3 km of brick kilns had higher SO2 level (22.3 ± 14.7 μgm−3) than far-flung sites (5.8 ± 1.1 μgm−3) (Kiros et al. 2016). The Himalaya is a source of rich minerals and stones. Around 150 mines were operating in the Indian Himalayan region at the start of the millennium. China has large-scale mining operations in the northern Himalayan region. Mining in the Himalayan region is mostly open-cast stripping of hill tops along with “hill mining on slopes” which emits relatively more mineral dust in the air than closed mines (Soni 2016). The use of explosives during mining, such as in mountain top removal, releases CO (Ghosh and Majee 2010).

5.4.5  Vehicles, Diesel Generators, and Pump Sets Diesel and petrol engine generators and engines are used for transport, to meet power shortage, and to uplift water for agriculture in the Himalayan region (Saxena and Sonwani 2019). Three-fourths of emission from diesel generator in high-­altitude area is composed of BC (Kurokawa et al. 2013). The transport sector is an important source of NOx and SOX emissions (Fig. 5.7). Between 2000 and 2015, the number of vehicles in the Kathmandu Valley grew at an unprecedented rate: from less than 200,000 registered vehicles to around a million between 2000 and 2015 (Bajracharya and Bhattarai 2016) (Fig. 5.9). Transport sector in the Kathmandu contributes about 86% of anthropogenic NOx emission (Pradhan et  al. 2012) (Fig.  5.7c). Further, incomplete fuel burning due to low oxygen at high altitude increases the pollution (Ran et  al. 2014). The diesel-powered vehicles emitted 570  t year−1 and 2117  t year−1 of OC and EC, respectively, in the Kathmandu Valley in 2010 (Shrestha et al. 2013).

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P. Balyan Number of registered vehicles at Kathmandu 1000 900

Number ('000)

800 700 600 500 400 300 200 100 0 2000-2001

2004-2005

2009-2010

2014-2015

Year

Fig. 5.9  Number of registered vehicles at the Kathmandu Valley between 2000 and 2015. (Source: Bajracharya and Bhattarai 2016)

5.4.6  Transported Pollution from Surrounding Regions The pollution in the Himalayan region is not only in situ but is also from the transport of the pollutants generated in the surrounding regions (Li et  al. 2016).  The Himalayan region is surrounded by densely populated IGP and China. A large number of fossil fuel-based vehicles, industries, stubble burning, etc. emit a large quantity of NOx, CO, SO2, and BC forming regional haze (Saxena et al. 2019a, b). The mountain/valley wind system enables the uplifting and advection of air pollutant mass from IGP to be transported across the Himalaya (Babu et al. 2011) and to the Tibet (Lüthi et al. 2015). Dhungel et al. 2018 produced observational evidence of the presence of strong wind systems within deep trans-Himalayan valleys which act as a pathway for the transport of pollutants from IGP to higher Himalayan ranges. Sand dust from the Thar Desert reaches the central and western Himalaya in spring season (Ram et al. 2010). Multiple synoptic westerly wind dust events bring mineral dust from southwest Asian deserts over the southern Himalaya in each year. Mixed with in situ anthropogenic emission, the dust forms a large vertically extended haze over IGP and the southern Himalaya (Gautam et al. 2013).

5.5  Effects of Air Pollution in the Himalayan Region Air pollution impacts the country’s economy in many ways like causing human morbidity, mortality, changing climate (increasing temperature, modifying precipitation), agro-forestry, and loss of urban competitiveness (World Bank 2016). Worsened air quality results in premature death, loss of labor workforce due to morbidity, and increase in health expenditure (Fig. 5.10 and Table 5.1).

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5  Impacts of Air Pollution on Himalayan Region •Rise in temerature •Rise in winter precipitation with overall precipitation •Reduced duration of winter

Climac effects

Crosphere and hydrosphere

decrease

in

monsoonal

and

annual

•Glacial retreat and formation of GLOFs •Increase in early winter flow and decrease in late winter and spring flow

agro-forestry

•Culvaon shied to higher altudes •Decreased crop and forest yields •Leaching of nutrients

Health effects

•Respiratory and cardiovasclar morbidity •Deteriorated mental health •Increased infecon & Cancer

Fig. 5.10  Effects of air pollution in the Himalayan region Table 5.1  Mean annual PM2.5, total death, total welfare losses, and total labor output forgone for Himalayan countries

Country Bhutan China

Mean annual ambient PM2.5 (μg/m3) 1993 2013 NA NA 39.3 54.36

India

30.25

46.68 1,043,182

Nepal

29.68

46.09 16,436

Pakistan 36.55

Total death from air pollution 1993 2013 NA NA 1,518,942 1,625,164

46.18 103,111

Total welfare lossesa 1993 2013 NA NA 126,592 1,589,767 (7.35%) (9.92%) 1,403,136 104,906 505,103 (6.8%) (7.69%) 22,038 1033 2833 (4.6%) (4.68%) 156,191 19,935 47,713 (6.06%) (5.88%)

Total labor output forgoneb 1993 2013 NA NA 12,558 44,567 (0.73%) (0.28%) 28,742 55,390 (1.86%) (0.84%) 195 287 (0.87%) (0.47%) 4713 6582 (1.43%) (0.81%)

Source: World Bank and IHME (2016) a Million 2011 USD, Purchasing power parity-adjusted (% GDP equivalent) b Million 2011 USD, Purchasing power parity-adjusted (% GDP equivalent)

5.5.1  Climatic Effect 5.5.1.1  Temperature Greenhouse gases (CO2, CO, CH4, NO, etc.) and particles like black carbon, sulfate aerosols, and dust raise the temperature by trapping the long-wavelength radiation reflected from surface. Black carbon and dust deposited on snow decrease albedo resulting into warm surface temperature and the atmosphere (Flanner et al. 2009).

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The air temperature in the Himalayan region increased about 0.06 °C per decade in monsoon to about 0.14 °C per decade in winter and 0.11 °C per decade in annually during 1876–2006 with warming effect being more predominant during the winter (Bhutiyani et  al. 2010). Maximum temperature data of 49 monitoring stations reveals a warming trend ranging from less than 0.03 °C year−1 in the Siwalik and Terai to 0.06° to 0.12 °C year−1 in most of the Middle Himalaya between 1971 and 1994. The rise in regional mean temperature in high-altitude areas was almost twice than that of foothills in Nepal (Shrestha et al. 1999). A significant rise in mean minimum temperature throughout the year increases the duration of warmer climate with fewer cold wave conditions in the Himalayan region (Singh et al. 2015). 5.5.1.2  Precipitation Perturbations of the radiation budget over the South Asian region caused a significant alteration in monsoon circulation and rainfall distribution in the Himalayan region. Winter precipitation has increased significantly in the Himalayan region with overall decrease in monsoonal and annual precipitation in the Himalayan region (Bhutiyani et  al. 2010). Two-thirds of rainwater sample collected during monsoon season of 2013 and 2014 at Darjeeling were acidic in nature with an average pH of 5.0 ± 0.8. Air masses arriving from the Arabian Sea precipitate into more acidic rainwater acidity over Darjeeling compared to the air masses from Bay of Bengal as continental contribution is more in Arabian mass than that of Bay of Bengal (Roy et al. 2016). 5.5.1.3  Season Cycle Variation in temperature and precipitation resulted in the alteration of onset and duration of seasons in the Himalaya. Winter onset is lagged by about 2 days per decade, and spring onset led by about 3 days per decade in the Himalayan region. This has resulted in significant reduction in the snowfall duration by 5–6 days per decade (Bhutiyani et al. 2010).

5.5.2  Cryosphere and Hydrosphere The rise in temperature is associated with glacial retreat, increases in flooding of river, and change in vegetation pattern of the Himalayan region. Chalise and Khanal 2001 observed a rise in frequency and intensity of rainfall, leading to flashfloods and consequent landslides in the Himalayan region. Glacial melting and retreat form glacial lakes behind the weak terminal moraine dams. Breach in moraine dams causes sudden flow of a huge amount of water and debris causing glacial lake outburst floods (GLOFs) resulting in catastrophic damage to human life and property, natural resources, and infrastructure. The Himalayan region has 204 potentially dangerous glacial lakes which can burst at any time (Saikawa et  al. 2019). An

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increase in early winter flow due to warmer winter and a decrease in late winter and early spring flow in the Himalayan stream are also observed (Krishnan et al. 2019).

5.5.3  Effect on Agro-forestry Acid rain due to air pollution decreased yields of many crops (Saxena et al. 2020), acidifies soils (Roy et  al. 2016), and leaches minerals such as phosphates and nitrates in the rivers leading to disastrous algal blooms creating “dead zones” (Rabalais et al. 2017) in coastal areas. Exposure to ground-level O3 increases susceptibility to infection, diseases, and senescence of forest tree, plant, and agricultural crops (Mauzerall and Wang 2001). Apple cultivation has to be shifted to higher altitudes due to fall in apple yield at lower altitude because of inadequate chilling (Vedwan and Rhoades 2001; Vishvakarma et al. 2003). A significant decline in yield of non-timber forest produce like Morchella esculenta (an edible fungi) and Kafal (Myrica esculenta) fruits, which are important means of earning for local people in the Garhwal Himalaya, has significantly declined due to climate change (Bhatt et al. 2000; Prasad et al. 2002). The rise in temperature with prolonged draught during summer has increased the vulnerability and incidences of forest fire in the Himalaya. Sharma et al. 2012 used three seasons’ satellite imageries of winter, spring, and summer of the Sikkim Himalaya to measure the incidence of forest fire. They observed 4 incidences in the winter, 201 forest fires in spring, and 82 additional forest fire incidences till mid-­ summer with the total burnt area of 0.2214 sq. km, 22.975 sq. km, and 9.995 sq. km, respectively. Himachal Pradesh lost a record 8195 hectares of forest to fire in 2005–2006 (Bhatta 2007).

5.5.4  Human Health Effects Several health problems are linked with air pollution, including acute respiratory infections (ARI), chronic lung disease, cardiovascular disease, cataracts, cancers, etc. Despite this, very few studies were conducted on the population in the Himalayan region (Gurung and Bell 2013). Researches conducted to observe the health effect of indoor air pollution concluded that biomass smoke exposure increases prevalence of cough, phlegm, wheezing, breathlessness, asthma, and chronic obstructive pulmonary disease and increased the exacerbation of pre-existing respiratory illness. Indoor smoke was associated with around half of pneumonia and acute respiratory illness cases in children