Abstract
Satellite-based aerosol optical depth (AOD) is columnar light extinction by aerosol absorption and scattering and has become the most important variable for the assessment of the spatiotemporal distribution of aerosols at a regional and global level. In this paper, we have used AOD observations of multiangle imaging spectroradiometer (MISR) from September 2002 to May 2017, moderate resolution imaging spectroradiometer (MODIS) from September 2002 to December 2020, and sea-viewing wide field-of-view sensor (SeaWiFS) from September 2002 to December 2010 over South Asia. We have observed the association of AOD with enhanced vegetation index (EVI) and meteorological variables (temperature (TEMP), wind speed (WS), and relative humidity (RH)) acquired from Giovanni during the period September 2002–December 2020. The satellite observations of Terra-, MISR-, and SeaWiFS-AOD were also compared with Aqua-AOD. The findings show that AOD in eastern Pakistan is higher than in the western Pakistan due to increase in population density and biomass burning. Mean annual peak AOD (˃ 0.7) has been observed over the IGB region because of the significant increase in economical, industrial, and agricultural activities while AOD of ˃ 0.6 is observed over Bangladesh. The lowest mean annual AOD of ˂ 0.3 is observed over northeastern Afghanistan, western Nepal, and Bhutan whereas the AOD of 0.3 is seen over Sri Lanka. The highest seasonal mean AOD of 0.8 has been seen over Bihar, India, and AOD of ~ 0.7 is observed over Bangladesh while the lowest AOD is observed over Afghanistan, Sri Lanka, Nepal, and Bhutan during the winter season. However, the mean AOD over eastern Pakistan is maximum in both monsoon and post-monsoon season but relatively low in pre-monsoon and winter. The highest positive seasonal AOD anomalies were observed over South Asia in winter season followed by post-monsoon, pre-monsoon, and least being monsoon. The higher mean AOD anomaly value is found to be 0.2 over eastern Pakistan and western India. In northeastern Pakistan and central India, AOD and RH are positively correlated (r ˃ 0.54) while negatively correlated over Afghanistan, southwestern region of Pakistan, eastern India, Nepal, Bhutan, and Bangladesh. AOD is negatively correlated (r = ~ − 0.3) with EVI over eastern Pakistan and western India. The highest correlation coefficient (r) obtained among Terra and Aqua is 0.97, MISR and Aqua is 0.93, and SeaWiFS and Aqua is 0.58 over South Asia.
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Data availability
Data used in this study can be downloaded from the Giovanni website (http://giovanni.gsfc.nasa.gov).
References
Alam K, Khan R, Blaschke T, Mukhtiar A (2014) Variability of aerosol optical depth and their impact on cloud properties in Pakistan. J Atmos Solar-Terrestrial Phys 107:104–112. https://doi.org/10.1016/j.jastp.2013.11.012
Alam K, Shaheen K, Blaschke T et al (2016) Classification of aerosols in an urban environment on the basis of optical measurements. Aerosol Air Qual Res 16:2535–2549. https://doi.org/10.4209/aaqr.2016.06.0219
Ali G, Bao Y, Ullah W, et al (2020) Spatiotemporal trends of aerosols over urban regions in Pakistan and their possible links to meteorological parameters. Atmosphere (Basel) 11:. https://doi.org/10.3390/atmos11030306
Ali M, Tariq S, Mahmood K et al (2014) A study of aerosol properties over Lahore (Pakistan) by using AERONET data. Asia-Pacific J Atmos Sci 50:153–162. https://doi.org/10.1007/s13143-014-0004-y
Bilal M, Mhawish A, Nichol JE et al (2021) Air pollution scenario over Pakistan: characterization and ranking of extremely polluted cities using long-term concentrations of aerosols and trace gases. Remote Sens Environ 264:112617. https://doi.org/10.1016/j.rse.2021.112617
Bilal M, Nichol JE, Bleiweiss MP, Dubois D (2013) A simplified high resolution MODIS aerosol retrieval algorithm (SARA) for use over mixed surfaces. Remote Sens Environ 136:135–145. https://doi.org/10.1016/J.RSE.2013.04.014
Bilal M, Nichol JE, Nazeer M, et al (2019) Characteristics of fine particulate matter (PM 2.5) over urban, suburban, and rural areas of Hong Kong. 1–15
Bilal M, Nichol JE, Wang L (2017) Remote sensing of environment new customized methods for improvement of the MODIS C6 dark target and deep blue merged aerosol product. Remote Sens Environ 197:115–124. https://doi.org/10.1016/j.rse.2017.05.028
Chi Y, Zuo S, Ren Y, et al (2019) The spatiotemporal pattern of the aerosol optical depth (AOD) on the canopies of various forest types in the exurban national park: a case in Ningbo City, Eastern China. Adv Meteorol 2019:. https://doi.org/10.1155/2019/4942827
Chung CE, Ramanathan V, Kim D, Podgorny IA (2005) Global anthropogenic aerosol direct forcing derived from satellite and ground-based observations. J Geophys Res Atmos 110:1–17. https://doi.org/10.1029/2005JD006356
David LM, Ravishankara AR, Kodros JK et al (2018) Aerosol optical depth over India. J Geophys Res Atmos 123:3688–3703. https://doi.org/10.1002/2017JD027719
Deng X, Shi C, Wu B et al (2012) Analysis of aerosol characteristics and their relationships with meteorological parameters over Anhui province in China. Atmos Res 109–110:52–63. https://doi.org/10.1016/J.ATMOSRES.2012.02.011
Dey S, Tripathi SN, Singh RP, Holben BN (2004) Influence of dust storms on the aerosol optical properties over the Indo-Gangetic basin. J Geophys Res Atmos 109:20211. https://doi.org/10.1029/2004JD004924
Diner DJ, Beckert JC, Reilly TH et al (1998) Multi-angle imaging spectroradiometer (MISR) instrument description and experiment overview. IEEE Trans Geosci Remote Sens 36:1072–1087. https://doi.org/10.1109/36.700992
Guo JP, Zhang XY, Wu YR et al (2011) Spatio-temporal variation trends of satellite-based aerosol optical depth in China during 1980–2008. Atmos Environ 45:6802–6811. https://doi.org/10.1016/J.ATMOSENV.2011.03.068
Han X, Zhang M, Tao J et al (2013) Modeling aerosol impacts on atmospheric visibility in Beijing with RAMS-CMAQ. Atmos Environ 72:177–191. https://doi.org/10.1016/j.atmosenv.2013.02.030
Holben BN, Eck TF, Slutsker I et al (1998) AERONET—a federated instrument network and data archive for aerosol characterization. Remote Sens Environ 66:1–16. https://doi.org/10.1016/S0034-4257(98)00031-5
Hsu NC, Tsay SC, King MD, Herman JR (2006) Deep blue retrievals of Asian aerosol properties during ACE-Asia. IEEE Trans Geosci Remote Sens 44:3180–3195. https://doi.org/10.1109/TGRS.2006.879540
Jethva H, Satheesh SK, Srinivasan J (2005) Seasonal variability of aerosols over the Indo-Gangetic basin. J Geophys Res Atmos 110:1–15. https://doi.org/10.1029/2005JD005938
Jr. REE, Meister G, Patt FS, et al (2011) Uncertainty assessment of the SeaWiFS on-orbit calibration. 101117/12892340 8153:93–109. https://doi.org/10.1117/12.892340
Jung J, Souri AH, Wong DC et al (2019) The impact of the direct effect of aerosols on meteorology and air quality using aerosol optical depth assimilation during the KORUS-AQ campaign. J Geophys Res Atmos JGR 124:8303. https://doi.org/10.1029/2019JD030641
Kahn RA, Gaitley BJ, Garay MJ et al (2010) Multiangle imaging spectroradiometer global aerosol product assessment by comparison with the aerosol robotic network. J Geophys Res Atmos 115:23209. https://doi.org/10.1029/2010JD014601
Kaufman YJ, Tanré D, Remer LA et al (1997) Operational remote sensing of tropospheric aerosol over land from EOS moderate resolution imaging spectroradiometer. J Geophys Res Atmos 102:17051–17067. https://doi.org/10.1029/96JD03988
Kiran Kumar T, Gadhavi H, Jayaraman A et al (2013) Temporal and spatial variability of aerosol optical depth over South India as inferred from MODIS. J Atmos Solar-Terrestrial Phys 94:71–80. https://doi.org/10.1016/J.JASTP.2012.12.010
Kumar KR, Yin Y, Sivakumar V et al (2015) Aerosol climatology and discrimination of aerosol types retrieved from MODIS, MISR and OMI over Durban (29.88°S, 31.02°E). South Africa Atmos Environ 117:9–18. https://doi.org/10.1016/J.ATMOSENV.2015.06.058
Kumar M, Parmar KS, Kumar DB et al (2018) Long-term aerosol climatology over Indo-Gangetic Plain: trend, prediction and potential source fields. Atmos Environ 180:37–50. https://doi.org/10.1016/j.atmosenv.2018.02.027
Ling X, Han X (2019) Aerosol impacts on meteorological elements and surface energy budget over an urban cluster region in the Yangtze River Delta. Aerosol Air Qual Res 19:1040–1055. https://doi.org/10.4209/aaqr.2017.12.0602
Logan T, Xi B, Dong X et al (2013) Classification and investigation of Asian aerosol absorptive properties. Atmos Chem Phys 13:2253–2265. https://doi.org/10.5194/ACP-13-2253-2013
Mahapatra PS, Puppala SP, Adhikary B et al (2019) Air quality trends of the Kathmandu Valley: a satellite, observation and modeling perspective. Atmos Environ 201:334–347. https://doi.org/10.1016/J.ATMOSENV.2018.12.043
Mainul M, Mamun I, Islam MM et al (2015) Monitoring the spatio-temporal variations of aerosols over Bangladesh. IOSR J Appl Phys 7:18–29. https://doi.org/10.9790/4861-07321829
Mamun MI (2014) The seasonal variability of aerosol optical depth over Bangladesh based on satellite data and HYSPLIT model. Am J Remote Sens 2:20. https://doi.org/10.11648/j.ajrs.20140204.11
Martonchik JV, Diner DJ, Kahn RA et al (1998) Techniques for the retrieval of aerosol properties over land and ocean using multiangle imaging. IEEE Trans Geosci Remote Sens 36:1212–1227. https://doi.org/10.1109/36.701027
Mehmood U, Azhar A, Qayyum F et al (2021) Air pollution and hospitalization in megacities: empirical evidence from Pakistan. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-021-14158-0
Mhawish A, Banerjee T, Sorek-Hamer M et al (2020) Estimation of high-resolution PM2.5 over the Indo-Gangetic Plain by fusion of satellite data, meteorology, and land use variables. Environ Sci Technol 54:7891–7900. https://doi.org/10.1021/ACS.EST.0C01769
Mhawish A, Sorek-hamer M, Chatfield R et al (2021a) Remote sensing of environment aerosol characteristics from earth observation systems : a comprehensive investigation over South Asia (2000–2019). Remote Sens Environ 259:112410. https://doi.org/10.1016/j.rse.2021.112410
Mhawish A, Sorek-Hamer M, Chatfield R et al (2021b) Aerosol characteristics from earth observation systems: a comprehensive investigation over South Asia (2000–2019). Remote Sens Environ 259:112410. https://doi.org/10.1016/j.rse.2021.112410
Nichol JE, Bilal M, (2016) Validation of MODIS 3 km resolution aerosol optical depth retrievals over Asia. Remote Sens, (2016) Vol 8. Page 328(8):328. https://doi.org/10.3390/RS8040328
Nizar S, Dodamani BM (2019) Spatiotemporal distribution of aerosols over the Indian subcontinent and its dependence on prevailing meteorological conditions. Air Qual Atmos Heal 12:503–517. https://doi.org/10.1007/s11869-019-00677-w
Ojha N, Sharma A, Kumar M et al (2020) On the widespread enhancement in fine particulate matter across the Indo-Gangetic Plain towards winter. Sci Rep 10:1–9. https://doi.org/10.1038/s41598-020-62710-8
Panday AK, Prinn RG (2009) Diurnal cycle of air pollution in the Kathmandu Valley, Nepal: observations. J Geophys Res Atmos 114:. https://doi.org/10.1029/2008JD009777
Prasad AK, Singh RP (2007a) 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 112:9208. https://doi.org/10.1029/2006JD007778
Prasad AK, Singh RP (2007b) Comparison of MISR-MODIS aerosol optical depth over the Indo-Gangetic basin during the winter and summer seasons (2000–2005). Remote Sens Environ 107:109–119. https://doi.org/10.1016/J.RSE.2006.09.026
Qayyum F, Mehmood U, Tariq S, et al (2021) Particulate matter (PM2.5) and diseases: an autoregressive distributed lag (ARDL) technique. Environ Sci Pollut Res. https://doi.org/10.1007/s11356-021-15178-6
Ramachandran S, Kedia S, Srivastava R (2012) Aerosol optical depth trends over different regions of India. Atmos Environ 49:338–347. https://doi.org/10.1016/J.ATMOSENV.2011.11.017
Remer LA, Kaufman YJ, Tanré D et al (2005) The MODIS aerosol algorithm, products, and validation. J Atmos Sci 62:947–973. https://doi.org/10.1175/JAS3385.1
Ren-Jian Z, Kin-Fai H, Zhen-Xing S (2015) The role of aerosol in climate change, the environment, and human health. New Pub KeAi 5:156–161. https://doi.org/10.1080/16742834.2012.11446983
Riffler M, Popp C, Hauser A et al (2010) Validation of a modified AVHRR aerosol optical depth retrieval algorithm over Central Europe. Atmos Meas Tech 3:1255–1270. https://doi.org/10.5194/AMT-3-1255-2010
Sayer AM, Hsu NC, Bettenhausen C et al (2012) SeaWiFS ocean aerosol retrieval (SOAR): algorithm, validation, and comparison with other data sets. J Geophys Res Atmos 117:3206. https://doi.org/10.1029/2011JD016599
Sharif F, Alam K, Afsar S (2015) Spatio-temporal distribution of aerosol and cloud properties over Sindh using MODIS satellite data and a HYSPLIT model. Aerosol Air Qual Res 15:657–672. https://doi.org/10.4209/aaqr.2014.09.0200
Sijikumar S, Aneesh S, Rajeev K (2016) Multi-year model simulations of mineral dust distribution and transport over the Indian subcontinent during summer monsoon seasons. Meteorol Atmos Phys 128:453–464. https://doi.org/10.1007/s00703-015-0422-0
Singh N, Mhawish A, Deboudt K et al (2017) Organic aerosols over Indo-Gangetic Plain: sources, distributions and climatic implications. Atmos Environ 157:59–74. https://doi.org/10.1016/J.ATMOSENV.2017.03.008
Sreekanth V (2013) Satellite derived aerosol optical depth climatology over Bangalore, India. Adv Sp Res 51:2297–2308. https://doi.org/10.1016/J.ASR.2013.01.022
Tariq S (2020) Investigating the aerosol optical depth and Angstrom exponent and their relationships with meteorological parameters over Lahore in Pakistan. Proc Natl Acad Sci India Sect A Phys Sci 90:861–867. https://doi.org/10.1007/s40010-018-0575-6
Tariq S, Ali M (2015) Spatio–temporal distribution of absorbing aerosols over Pakistan retrieved from OMI onboard Aura satellite. Atmos Pollut Res 6:254–266. https://doi.org/10.5094/APR.2015.030
Tariq S, Ali M (2016) Satellite and ground-based remote sensing of aerosols during intense haze event of October 2013 over Lahore. Pakistan 52:25–33. https://doi.org/10.1007/s13143-015-0084-3
Tariq S, Nawaz H, Ul-Haq Z, Mehmood U (2021) Investigating the relationship of aerosols with enhanced vegetation index and meteorological parameters over Pakistan. Atmos Pollut Res 12:101080. https://doi.org/10.1016/j.apr.2021.101080
Tariq S, Ul-Haq Z (2018) Ground-based remote sensing of aerosol properties over a coastal megacity of Pakistan. Adv Meteorol 2018:. https://doi.org/10.1155/2018/3582191
Tiwari S, Kaskaoutis D, Soni VK et al (2018) Aerosol columnar characteristics and their heterogeneous nature over Varanasi, in the central Ganges valley. Environ Sci Pollut Res 25:24726–24745. https://doi.org/10.1007/s11356-018-2502-4
Tiwari S, Tiwari S, Hopke PK et al (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. https://doi.org/10.1007/s11356-016-6060-3
ul-Haq Z, Tariq S, Ali M (2017) Spatiotemporal patterns of correlation between atmospheric nitrogen dioxide and aerosols over South Asia. Meteorol Atmos Phys 129:507–527. https://doi.org/10.1007/s00703-016-0485-6
Acknowledgements
We acknowledged NASA for providing us MODIS, MISR, and SeaWiFS datasets and NOAA NCEP/NCAR Reanalysis group for meteorological datasets.
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Salman Tariq conceptualized the work and wrote the manuscript. Fazzal Qayyum made maps and wrote the description. Usman Mehmood conducted analysis. Zia ul-Haq wrote the manuscript.
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Tariq, S., Qayyum, F., Ul-Haq, Z. et al. Long-term spatiotemporal trends in aerosol optical depth and its relationship with enhanced vegetation index and meteorological parameters over South Asia. Environ Sci Pollut Res 29, 30638–30655 (2022). https://doi.org/10.1007/s11356-021-17887-4
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DOI: https://doi.org/10.1007/s11356-021-17887-4