Validation and Spatiotemporal Analysis of the Modis 1 Km Aerosol Product over China during the Covid-19 Pandemic

The Moderate Resolution Imaging Spectroradiometer (MODIS) 1 km aerosol product based on the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm has great potential in understanding the interaction between human activities and the atmospheric environment. In this paper, the MODIS 1 km aerosol product over China during the Coronavirus Disease 2019 (COVID-19) pandemic was validated against with the ground measured data collected from the Aerosol Robotic Network (AERONET). The result shows a good agreement between the two datasets. The spatiotemporal analyses of three selected regions, which are Beijing-Tianjin-Hebei, Hubei and Guangdong-Hong Kong-Macao, indicate that the COVID-19 pandemic has a significant impact on human activities and aerosol loadings.

Comparison of Atmospheric Environment in China during Sars and Covid-19 Pandemics

Satellite remote sensing has advantages in monitoring environmental changes during the global pandemics such as the Severe Acute Respiratory Syndrome Coronavirus (SARS) and the Corona Virus Disease 2019 (COVID-19). In this paper, the variations of atmospheric environment during SARS and COVID-19 pandemics were calculated and analyzed based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Atmosphere Monthly Global Product. Preliminary results show that: (1) aerosol optical depth is most affected by the pandemics, especially the duration and prevention and control measures;(2) the correlations between the variables of aerosol optical depth, cloud fraction, total column ozone and precipitable water vapor were not very strong during the two pandemics.

Season, not lockdown, improved air quality during COVID-19 State of Emergency in Nigeria.

Globally, ambient air pollution claims ~9 million lives yearly, prompting researchers to investigate changes in air quality. Of special interest is the impact of COVID-19 lockdown. Many studies reported substantial improvements in air quality during lockdowns compared with pre-lockdown or as compared with baseline values. Since the lockdown period coincided with the onset of the rainy season in some tropical countries such as Nigeria, it is unclear if such improvements can be fully attributed to the lockdown. We investigate whether significant changes in air quality in Nigeria occurred primarily due to statewide COVID-19 lockdown. We applied a neural network approach to derive monthly average ground-level fine aerosol optical depth (AODf) across Nigeria from year 2001-2020, using the Multi-angle Implementation of Atmospheric Correction (MAIAC) AODs from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) satellites, AERONET aerosol optical properties, meteorological and spatial parameters. During the year 2020, we found a 21% or 26% decline in average AODf level across Nigeria during lockdown (April) as compared to pre-lockdown (March), or during the easing phase-1 (May) as compared to lockdown, respectively. Throughout the 20-year period, AODf levels were highest in January and lowest in May or June, but not April. Comparison of AODf levels between 2020 and 2019 shows a small decline (1%) in pollution level in April of 2020 compare to 2019. Using a linear time-lag model to compare changes in AODf levels for similar months from 2002 to 2020, we found no significant difference (Levene's test and ANCOVA; α = 0.05) in the pollution levels by year, which indicates that the lockdown did not significantly improve air quality in Nigeria. Impact analysis using multiple linear regression revealed that favorable meteorological conditions due to seasonal change in temperature, relative humidity, planetary boundary layer height, wind speed and rainfall improved air quality during the lockdown.