Chinese satellite implicates global air quality

image: ac, the recovery of NO2, SO2 and HCHO without spectral calibration, respectively. df, NO2, SO2 and HCHO recovery with spectral calibration, respectively.
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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 new coronavirus disease (COVID-19), governments around the world imposed containment measures to prevent crowd gatherings in early 2020, resulting in a sharp reduction in emissions of air pollutants and dramatic changes in air quality. Many literatures have reported the variation of 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 article published in Light sciences and applicationsScientists from University of Science and Technology of China and Hefei Institutes of Physical Sciences (Chinese Academy of Sciences) developed new methods to improve the traditional retrieval algorithm and successfully retrieved tropospheric vertical column densities ( TVCD) of several air pollutants, such as NO2SO2 and HCHO, during the COVID-19 pandemic from the Environmental Trace Gases Monitoring Instrument (EMI) aboard the GaoFen-5 satellite, as China’s first satellite instruments to measure air pollutants. Based on the data extracted from the EMI, the relationship between air quality and lockdown measures and the economy was investigated. These scientists summarize the improvements in recovery methods and their conclusions from the EMI observation:

“While the full width at half height (FWHM) of the EMI Instrumental Spectral Response Functions (ISRF) changes dramatically in spatial and temporal dimensions, we performed the in-orbit calibration to calculate daily ISRFs and length offsets waveform and reduced adjustment residuals.”

“As the signal-to-noise ratio (SNR) of EMI is only one-third of that of TROPOMI, we implemented an adaptive iterative recovery algorithm that selects the best recovery setting with minimal uncertainty among the Fit results using different recovery settings and more.Reduce fitting residual.

“Due to the insufficient mechanical structure of the optical path switching, EMI provides a solar spectrum once every six months. To obtain the daily solar spectrum required for the following recovery algorithm, we used the simulated irradiance at locus of the measured irradiance to eliminate crossbands during recovery and reduce average adjustment residuals.

“From the EMI observation, we found that the TVCDs of NO2 decreased overall in March 2020, however, no significant reduction in SO2 TVCDs were found.

“Thanks to the sharp drop in NO2we 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, in February in Seoul, and in March in Tokyo and various cities in Europe and America.

“We found significant decreases in HCHO in Wuhan, Shanghai, Guangzhou and Seoul, indicating that the majority of volatile organic compound (VOC) emissions were anthropogenic. In contrast, the lack of evident reduction in Beijing and New Delhi suggests 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 secondary industry in China, while on primary and tertiary industries in Korea and countries in Europe and ‘America.

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