scholarly journals Trends of Aerosol Optical Thickness Using VIIRS S-NPP during Fog Episodes in Pakistan and India

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 242
Author(s):  
Muhammad Umar ◽  
Salman Atif ◽  
Mark L. Hildebrandt ◽  
Ali Tahir ◽  
Muhammad Azmat ◽  
...  

Aerosol Optical Thickness (AOT) is one of the important parameters for assessing regional and global level of climate change. Fog episodes have considerably increased in south Asia because of environmental factors, and the burning of agricultural residue leads to major social and economic problems. In present study, Mann-Kendall trend analysis of AOT and active fire events was done, and their significance were assessed using long-term (October 2012–February 2020) remote sensing data derived smog maps. Visible Infrared Imaging Radiometer Suite National Polar Partnership (VIIRS N-PP) was used to map AOT episodes over the northern region of Pakistan and India. Results reveal that AOT displays a significantly decreasing trend over the northern and eastern region of Pakistan and a similar decreasing trend from the Western to Eastern region of India. Furthermore, active fire events have a significantly increasing trend at the Northern region of Pakistan. However, fire events have a significantly decreasing trend over the southern and southeastern region of India. Additionally, statistically significant decreasing trends were observed for AOT over Chakwal (p-value = 0.2, Z_MK = −2.3) and Patiala (p-value = 0.15, Z_MK = −3.2). Fire events have a significantly increasing trend for Dera Ismail Khan (p-value = 0.01, Z_MK = 1.9), Jhang (p-value = 0.01, Z_MK = 1.9), and Chakwal (p-value = 0.01, Z_MK = 1.8), while they are significantly decreasing trend near New Delhi (p-value = 0.2, Z_MK = −0.9), Aligarh (p-value = 0.15, Z_MK = −0.9) and Patiala (p-value = 0.2, Z_MK = −0.8).

2021 ◽  
Author(s):  
Mahesh Pathakoti ◽  
Aarathi Muppalla ◽  
Sayan Hazra ◽  
Mahalakshmi D. Venkata ◽  
Kanchana A. Lakshmi ◽  
...  

Abstract. The nationwide lockdown was imposed over India from 25th March to 31st May 2020 with varied relaxations from phase-I to phase-IV to contain the spread of COVID-19. Thus emissions from industrial and transport sectors were halted during lockdown (LD) which resulted in a significant reduction of anthropogenic pollutants. The first two lockdown phases were strictly followed (phase-I and phase-II) and hence are considered as total lockdown (TLD) in this study. Satellite-based tropospheric columnar nitrogen dioxide (TCN) from the years 2015 to 2020, tropospheric columnar carbon monoxide (TCC) during 2019–2020 and aerosol optical depth (AOD550) from the years 2014 to 2020 during phase-I and phase-II LD and pre-LD periods were investigated with observations from Aura/OMI, Sentinel-5P/TROPOMI, and Aqua-Terra/ MODIS satellite sensors. To quantify lockdown induced changes in TCN, TCC, and AOD550, detailed statistical analysis was performed on de-trended data using student’s paired statistical t-test. Results indicate that mean TCN levels over India showed a dip of 18 % compared to the previous year and also against the 5-year mean TCN levels during the phase-I lockdown, which was found statistically significant (p-value <0.05) against the respective period. Furthermore, drastic changes in TCN levels were observed over hotspots namely the eastern region and urban cities. For example, there was a sharp decrease of 62 % and 54 % in TCN levels as compared to 2019 and against 5-years mean TCN levels over New Delhi with a p-value of 0.0002 (which is statistically significant) during total LD. The TCC levels were high in the North East (NE) region during the phase-I LD period, which is mainly attributed to the active fire counts in this region. However, lower TCC levels are observed in the same region due to the diminished fire counts during phase-II. Further, AOD550 is reduced over the country by ~16 % (Aqua and Terra) from the 6-years (2014–2019) mean AOD550 levels, with a significant reduction (Aqua/MODIS 28 %) observed over the Indo-Gangetic plains (IGP) region with a p-value of


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