image: a-c, the retrieval of NO2, SO2 and HCHO without spectral calibration, respectively. d-f, the retrieval of NO2, SO2 and HCHO with spectral calibration, respectively. view more
Credit: Cheng Liu, Qihou Hu, Chengxin Zhang, Congzi Xia, Hao Yin, Wenjing Su, Xiaohan Wang, Yizhou Xu, Zhiguo Zhang
In order to prevent the spread of the novel coronavirus disease (COVID-19), governments worldwide imposed lockdown measures to prevent crowd gathering in early 2020, resulting in sharp reduction in the emissions of air pollutants and dramatic changes in air quality. Numerous literatures have reported the variation in air pollution due to the COVID-19 pandemic through satellite remote sensing based on American and European satellite instruments, such as OMI and TROPOMI.
In a new paper published in Light Science & Application, scientists from the University of Science and Technology of China and the Hefei Institutes of Physical Science (Chinese Academy of Sciences) developed new methods to improve the traditional retrieval algorithm and successfully retrieved the tropospheric vertical column densities (TVCDs) of several air pollutants, such as NO2, SO2 and HCHO, during the COVID-19 pandemic from the Environmental Trace Gases Monitoring Instrument (EMI) onboard the GaoFen-5 satellite, as the first Chinese satellite instruments aimed at measuring air pollutants. Based on the data retrieved from EMI, the relationship between air quality and lockdown measures and economy were investigated. These scientists summarize the improvements in retrieval methods and their finding from EMI observation:
“As the full width at half maximum (FWHM) of the EMI instrumental spectral response functions (ISRFs) changes drastically in spatial and temporal dimensions, we performed the on-orbit calibration to calculate daily ISRFs and wavelength shifts and decreased the fitting residuals.”
“As the signal-to-noise ratio (SNR) of EMI is only one-third of that of TROPOMI, we set up an adaptive iterative retrieval algorithm that selects the retrieval setting best with minimum uncertainty among fitting results using different retrieval settings and further reduce the fitting residual.”
“Due to the insufficiency mechanical structure of optical path switching, EMI provides solar spectrum once every six months. To obtain the requisite daily solar spectrum for the following retrieval algorithm, we used simulated irradiance instead of measured irradiance to eliminate the cross-track stripes in the retrieval and reduce the average fitting residuals.”
“From EMI observation, we found that the TVCDs of NO2 decreased globally in March 2020, however, no significant reductions in SO2 TVCD were found.”
“Through the abrupt drop in NO2, we captured the time for each city when effective measures were implemented to prevent the spread of the pandemic, for example, in January 2020 in Chinese cities, February in Seoul, and March in Tokyo and various cities across Europe and America.”
“We found significant decreases in HCHO in Wuhan, Shanghai, Guangzhou and Seoul, indicating that the majority of volatile organic compounds (VOCs) emissions were anthropogenic. Contrastingly, the lack of evident reduction in Beijing and New Delhi suggested dominant natural sources of VOCs.”
“By comparing the relative variation of NO2 to gross domestic product (GDP), we found that the COVID-19 pandemic had more influence on the secondary industry in China, while on the primary and tertiary industries in Korea and the countries across Europe and America.”
Journal
Light Science & Applications