Publications

Etchie, TO; Etchie, AT; Jauro, A; Pinker, RT; Swaminathan, N (2021). Season, not lockdown, improved air quality during COVID-19 State of Emergency in Nigeria. SCIENCE OF THE TOTAL ENVIRONMENT, 768, 145187.

Abstract
Globally, ambient air pollution claims similar to 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 (AOD(f)) 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 AOD(f) 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, AOD(f) levels were highest in January and lowest in May or June, but not April. Comparison of AOD(f) 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 ACID (levels for similar months from 2002 to 2020, we found no significant difference (Levene's test and ANCOVA; alpha = 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. (C) 2021 Elsevier B.V. All rights reserved.

DOI:
10.1016/j.scitotenv.2021.145187

ISSN:
0048-9697