Assessment of variations of air pollutant concentrations during the COVID-19 lockdown and impact on urban air quality in South Asia

Modeling assessment of air pollution control measures and COVID-19 pandemic on air quality improvements over Greater Bay Area of China

A remarkable progress has been made toward the air quality improvements over the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China from 2017 to 2020. In this study, for the first time, the emission reductions of regional control measures together with the COVID-19 pandemic were considered simultaneously into the development of the GBA's emission inventories for the years of 2017 and 2020. Based on these collective emission inventories, the impacts of control measures, meteorological variations together with temporary COVID-19 lockdowns on the five major air quality index pollutants (SO2, NO2, PM2.5, PM10, and O3, excluding CO) were evaluated using the WRF-CMAQ and SMAT-CE model attainment assessment tool over the GBA region. Our results revealed that control measures in the Pearl River Delta (PRD) region affected significantly the GBA, resulting in pollutant reductions ranging from 48 % to 64 %. In contrast, control measures in Hong Kong and Macao contributed to pollutant reductions up to 10 %. In PRD emission sectors, stationary combustion, on-road, industrial processes and dust sectors stand out as the primary contributors to overall air quality improvements. Moreover, the COVID-19 pandemic during period I (Jan 23-Feb 23) led to a reduction of NO2 concentration by 7.4 %, resulting in a negative contribution (disbenefit) for O3 with an increase by 2.4 %. Our findings highlight the significance of PRD control measures for the air quality improvements over the GBA, emphasizing the necessity of implementing more refined and feasible manageable joint prevention and control policies.

Impact of Covid-19 lockdown regulations on PM2.5 and trace gases (NO2, SO2, CH4, HCHO, C2H2O2 and O3) over Lahore, Pakistan

The COVID-19 pandemic altered the human mobility and economic activities immensely, as authorities enforced unprecedented lock down regulations. In order to reduce the spread of COVID-19, a complete lockdown was observed between 24 March - 31 May 2020 in Pakistan. This paper aims at investigating the PM_2.5, AOD and column amounts of six trace gases (NO₂, SO₂, CH₄, HCHO, C₂H₂O₂, and O₃) by comparing periods of reduced emissions during lockdown periods with reference periods without emission reductions over Lahore, Pakistan. HYSPLIT cluster trajectory analyses were performed, which confirmed similar meteorological flow conditions during lockdown and reference periods. This provides confidence that any change in air quality conditions would be due to changes in human activities and associated emissions. The results show about 38% reduction in ambient surface PM_2.5 levels during the lockdown period. This change also positively correlated with MODIS_DB and AERONET_AOD data with a decrease of AOD by 42% and 35%, respectively. Reductions for tropospheric columns of NO₂ and SO₂ were about 20% and 50%, respectively during a semi lockdown period, while no reduction in the CH_4, C₂H₂O₂, HCHO and O₃ levels occurred. During the lockdown period NO_2, O₃ and CH₄ were about 50%, 45% and 25% lower, respectively, but no reduction in SO₂, C₂H₂O₂ and HCHO levels were noticed compared to the reference lockdown period for Lahore. HYSPLIT cluster trajectory analysis revealed the greatest impact on Lahore air quality through local emissions and regional transport from the east (agricultural burning and industry).

Temporal characteristics and spatial heterogeneity of air quality changes due to the COVID-19 lockdown in China

Previous studies have evaluated the impact of lockdown measures on air quality during the COVID-19 pandemic in China, but few have focused on the temporal characteristics and spatial heterogeneity of the impact across all 337 prefecture cities. In this study, we estimated the impact of the lockdown measures on air quality in each of 337 cities using the Regression Discontinuity in Time method. There was a short-term influence from January 24th to March 31th in 2020. The 337 cities could be divided into six categories showing different response and resilience patterns to the epidemic. Fine particulate matter (PM2.5) in 89.5% of the cities was sensitive to the lockdown measures. The change of air pollutants showed high spatial heterogeneity. The provinces with a greater than 20% reduction in PM2.5 and PM10 and greater than 40% reduction in NO2 during the impact period were mainly concentrated southeast of the "Hu Line". Compared to the no-pandemic scenario, the national annual average concentration of PM2.5, NO2, PM10, SO2, and CO in 2020 were decreased by 6.3%, 10.6%, 7.4%, 9.0%, and 12.5%, respectively, while that of O3 increased by 1.1%.This result indicates that 2020 can still be used as a baseline for setting and allocating air improvement targets for the next five years.