Response of air quality to Covid-19 lockdown policies from Sentinel-5P TROPOMI sensor

The outbreak of the coronavirus disease 19 (Covid-19) has posed a worldwide threat to human beings, economic activities, and society. Enforced lockdowns for limiting the spread of Covid-19 virus also substantially reduce air pollutant emissions from vehicle traffic, industrial plants, etc. The lockdown restrictions have brought beneficial environmental implications, such as improvement of air quality. Previous studies recorded the reduction of air pollutants during the short-term lockdown in some cities and areas in Indian, China, and the U.S. [1-5]. While some studies argue that the improvement of air quality is not due to lockdown, but season influence or temporary change by coincidence [6]. Therefore, there is not enough evidence that the improvement of air quality is mainly due to reduced human activities. It is beneficial to answer this question by investigating and comparing the air pollution changes within countries with multi waves of pandemic timelines and different lockdown measures.
Our research chose Germany and the Netherlands to investigate the air pollutant changes during their multiple lockdowns. Both of the two countries have gone through several pandemic waves while their imposed strategies are different, ranging from lockdown light, partial lockdown, full lockdown, to curfew in different stages of the pandemic. Our research investigates changes in air quality during their multiple pandemic waves and compares seasonal and monthly changes with the historical records (pre-pandemic) from ground stations to analyze the anomalies. During the pandemic period, the research will compare the disparities of air quality improvement with the several pandemic waves among mega urban agglomerations within the two countries. For the pre-pandemic period, this research analyzes the anomaly in comparison with the historical records with the air quality index.
In particular, we adopt the datasets produced by a space-borne air pollution sensor TROPOMI on the Sentinel-5P satellite, provided in Google Earth Engine data catalog. We process the data and extract information about air pollution, including CO, NO2, SO2, O3, and CH4 for analyzing the air pollutant composition changes during the several pandemic waves. First, the decline values of air pollutant composition will be calculated and analyzed between the pandemic waves to prove the different changes following every wave in main urban areas within the two countries. Second, by aggregating the air pollutant concentrations from the satellite-based air pollution data into monthly, seasonal, and annual data and comparing them with corresponding historical records from ground stations at the same periods of pre-pandemic time, the anomalies will be calculated and analyzed to illustrate the improvement of air quality because of pandemic lockdowns at the country level. The historical record data will be collected from the air quality index based on the ground station measurements. Third, the disparities of air pollutant reduction during the pandemic will be also analyzed between the Netherlands and Germany, considering their different lockdown strategies.
The result will provide strong evidence on the air quality improvement due to the reduction of human activities during lockdown periods and highlight the influence of anthropogenic activities on air pollution. The resulting information will provide information to policymakers concerning emission control and sustainable urban development.
Keywords: Air quality changes, lockdowns, pre-pandemic, Google Earth Engine
Reference:
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6.Etchie, T.O., et al., Season, not lockdown, improved air quality during COVID-19 State of Emergency in Nigeria. Science of The Total Environment, 2021. 768: p. 145187.