Long-Term (2005–2017) View of Atmospheric Pollutants in Central China Using Multiple Satellite Observations

Abstract

The air quality in China has experienced dramatic changes during the last few decades. To improve understanding of distribution, variations, and main influence factors of air pollution in central China, long-term multiple satellite observations from moderate resolution imaging spectroradiometer (MODIS) and ozone monitoring instrument (OMI) are used to characterize particle pollution and their primary gaseous precursors, sulfur dioxide (SO2), and nitrogen dioxide (NO2) in Hubei province during 2005–2017. Unlike other regions in eastern China, particle and gaseous pollutants exhibit distinct spatial and temporal patterns in central China due to differences in emission sources and control measures. OMI SO2 of the whole Hubei region reached the highest value of ~0.2 Dobson unit (DU) in 2007 and then declined by more than 90% to near background levels. By contrast, OMI NO2 grew from ~3.2 to 5.9 × 1015 molecules cm−2 during 2005–2011 and deceased to ~3.9 × 1015 molecules cm−2 in 2017. Unlike the steadily declining SO2, variations of OMI NO2 flattened out in 2016 and increased ~0.5 × 1015 molecules cm−2 during 2017. As result, MODIS AOD at 550 nm increased from 0.55 to the peak value of 0.7 during 2005–2011 and then decreased continuously to 0.38 by 2017. MODIS AOD and OMI SO2 has a high correlation (R > 0.8), indicating that annual variations of SO2 can explain most changes of AOD. The air pollution in central China has notable seasonal variations, which is heaviest in winter and light in summer. While air quality in eastern Hubei is dominated by gaseous pollution such as O3 and NOx, particle pollutants are mainly concentrated in central Hubei. The high consistency with ground measurements demonstrates that satellite observation can well capture variations of air pollution in regional scales. The increasing ozone (O3) and NO2 since 2016 suggests that more control measures should be made to reduce O3-related emissions. To improve the air quality in regional scale, it is necessary to monitor the dynamic emission sources with satellite observations at a finer resolution.

Unprecedented Temporary Reduction in Global Air Pollution Associated with COVID-19 Forced Confinement: A Continental and City Scale Analysis

“…In the present study, we used the daily concentration of five pollutants (NO 2 , CO, PM2.5, O 3 and SO 2 ) from 1 January-15 May for the year of 2015-2019 (defined as baseline period) and 2020, for sixteen selected cities located in South Asia, East Asia, Europe, and North America (Figure 1a). The pre-assumption behind the baseline period was that the air quality in this period mainly responded to regular conditions of anthropogenic emissions while changes in the air quality during January-May 2020 was caused primarily by effects of country-specific lockdown measures when most of the anthropogenic activities were stopped [51,55,62]. Also, using past multi-year data as baseline helps to reduce the effects of inter-annual climatic variability in air pollution [63].…”

“…Ground-based air quality observations provide accurate estimates of mass concentration of air pollutants but are short of spatial representativeness, which restricts our understanding of air pollution changes in response to COVID-19 pandemic lockdown at the continental scale. To better address this problem, satellite observations along with ground-based data during COVID-19 pandemic lockdown at continental and city scales-as indicated in other studies [54,55]-can provide a unique chance to detect real-time changes in air pollution globally. Moderate resolution imaging spectroradiometer (MODIS) and ozone monitoring instrument (OMI) have facilitated the observation of particulate matters and pollutants at high spatial and temporal resolutions [56,57].…”

Measurement report: An assessment of the impact of a nationwide lockdown on air pollution – a remote sensing perspective over India

“…Earlier studies indicate that the emissions from vehicles (Mahalakshmi et al, 2014(Mahalakshmi et al, , 2015, industry, and thermal power plants contribute significantly to atmospheric pollution, including gaseous pollutants. The ambient air quality is largely determined by the concentration of trace gases and particulate matter in the atmosphere (Nishanth et al, 2014).…”

Trends in Air Pollutant Concentrations and the Impact of Meteorology in Shandong Province, Coastal China, during 2013-2019

“…for heating resulted in the highest air pollutant concentrations in winter (Li et al, 2020b;Zhou et al, 2020). All of these factors resulted in great fluctuations in the five criteria pollutants concentrations during the four seasons.…”