Long-term spatiotemporal trends in aerosol optical depth and its relationship with enhanced vegetation index and meteorological parameters over South Asia.

Salman Tariq,Fazzal Qayyum,Zia Ul-Haq,Usman Mehmood

doi:10.1007/s11356-021-17887-4

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.

Highlights

Atmospheric aerosols are solid or liquid particles ranging from (0.001–100 μm), emitting from both anthropogenic and natural sources, suspended in the earth’s atmosphere and have impacts on the ecosystem, air quality, atmospheric chemistry and visibility (Streets et al, 2009; Han et al, 2013)
This study shows the spatiotemporal distribution of Aerosol optical depth (AOD) and its association with enhanced vegetation index (EVI) and meteorological variables from September 2002 to December 2020 over south Asia
The moderate resolution imaging spectroradiometer (MODIS)-Aqua AOD has been validated with datasets obtained from Terra, sea viewing wide field-of-view Sensor (SeaWiFS) and multi-angle imaging spectroradiometer (MISR) to attain accuracy in the measurement of AOD

Summary

Introduction

Atmospheric aerosols are solid or liquid particles ranging from (0.001–100 μm), emitting from both anthropogenic and natural sources, suspended in the earth’s atmosphere and have impacts on the ecosystem, air quality, atmospheric chemistry and visibility (Streets et al, 2009; Han et al, 2013). For a better understanding of aerosol distribution in the atmosphere at high spectral and temporal resolutions, an insitu observational instrument aerosol robotic network (AERONET) was used globally for continuous observations of aerosol properties (Alam et al, 2018). These in-situ observations provide accurate information on aerosols but are limited over regional and global scales (Tariq and Ali, 2015). To better address this spatial limitation problem, satellite datasets have been used to monitor the spatiotemporal distribution of aerosols at territorial and global scale (Remer et al, 2005; Tariq et al, 2018; Nichol et al, 2016)

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