Toward Understanding the Variation of Air Quality Based on a Comprehensive Analysis in Hebei Province under the Influence of COVID-19 Lockdown

Abstract

Associated with the outbreak of new coronavirus in 2019 (COVID-19), lockdown measures were taken in spring 2020 in China, providing an ideal experiment to investigate the effects of emission controls on air quality. Using the observation data at 56 stations in Hebei province from the China National Environmental Monitoring Center from January 2019 to May 2020, along with the reanalysis meteorology data from ERA5, this study investigates the spatial and temporal variations of six air pollutants, and the clean and pollution events in COVID-19 period. Compared with the same periods in day and month in 2019 (SP19), the concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2), particulate matter with an aerodynamic diameter of less than 10 μm (PM10), particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5), and carbon monoxide (CO) decreased by 39.2%, 38.2%, 42.1%, 39.8%, and 24.8% for lockdown period, respectively; and decreased by 13.7%, 8.9%, 16.8%, 13.4%, and 10.6% for post-lockdown period, respectively. In contrast, ozone (O3) increased by 8.0% and 5.5% for lockdown and post-lockdown periods, respectively. The diurnal variation analysis shows that the air pollutants other than O3 decrease more in the morning time (6:00–10:00 local time) than in the afternoon time (14:00–18:00 local time) during both lockdown and post-lockdown periods compared to SP19, implying the potential contribution from pollution-meteorology interaction. After lockdown period, SO2 and NO2 resumed quickly in most cities other than in Zhangjiakou, which is a city with few industries making it more sensitive to meteorology. The significant improvement of air quality during the lockdown period suggests that the whole air quality is highly dependent on the pollutant emissions, while the relatively weak reduction of pollution events imply that the pollution events are more dependent on adverse weather conditions.

Multi‐Source Data Based Investigation of Aerosol‐Cloud Interaction Over the North China Plain and North of the Yangtze Plain

“…A total of 96 ground-based stations evenly distributed in the NCNYP are selected from the urban air quality monitoring network in this study. The urban air quality data released by the Ministry of ecological environment of China (archived at https://quotsoft.net/air) has a high temporal resolution (hourly) and is wildly used in air quality-related research (H. Fan et al, 2020;Jiang et al, 2021;K. Li et al, 2020 The same data quality control process is also applied to PM 10 data.…”

Spatio-temporal variations of tropospheric nitrogen dioxide in South Mato Grosso based on remote sensing by satellite

“…The main sources of NO 2 are fossil fuel combustion, biomass burning, soil emissions and lightning (Hagenbjörket et al 2017 ). NO 2 is a toxic air pollutant in the high-concentration condition and plays an important role in tropospheric chemistry as a precursor of tropospheric ozone and secondary aerosols (Jiang et al 2021 ; Fan et al 2021 ; Castellanos and Boersma 2012 ; Grajales and Baquedo-Bernal 2014 ; Fantozzi et al 2015 ; Griffin et al 2018 ; Xue et al 2020 ; Nakada and Urban 2020 ). Observations of the space–time variations of NO 2 form the basis for understanding the spatial distributions and temporal trends of NO 2 .…”

Assessment of PM2.5 Chemical Composition and Air Quality Monitoring: Implications of Air Pollutants Emissions from a Night Market in Kaohsiung City, Taiwan

“…According to the World Urbanization Prospect 2018 Revision, Asia and Africa's megacities are expected to experience a population rise of over 90% by 2050. Along with the increase in population, cities economic growth activities have increased pollution levels from many industries (Jiang et al, 2021;Kumari and Toshiwal, 2020).…”