Spatial and temporal changes analysis of air quality before and after the COVID-19 in Shandong Province, China

被引:0
|
作者
Huaqiao Xing
Linye Zhu
Bingyao Chen
Jingge Niu
Xuehan Li
Yongyu Feng
Wenbo Fang
机构
[1] Shandong Jianzhu University,School of Surveying and Geo
[2] The Key Laboratory of Digital Simulation in Spatial Design of Architecture and Urban-Rural,informatics
[3] Shandong Provincial Education Department,undefined
[4] University of Sydney,undefined
[5] Shandong Geographical Institute of Land Spatial Data and Remote Sensing Technology Center,undefined
来源
Earth Science Informatics | 2022年 / 15卷
关键词
Air quality; COVID-19; Google Earth Engine; Shandong Province;
D O I
暂无
中图分类号
学科分类号
摘要
Due to the COVID-19 pandemic outbreak, the home quarantine policy was implemented to control the spread of the pandemic, which may have a positive impact on the improvement of air quality in China. In this study, Google Earth Engine (GEE) cloud computing platform was used to obtain CO, NO2, SO2 and aerosol optical depth (AOD) data from December 2018-March 2019, December 2019-March 2020, and December 2020-March 2021 in Shandong Province. These data were used to study the spatial and temporal distribution of air quality changes in Shandong Province before and after the pandemic and to analyze the reasons for the changes. The results show that: (1) Compared with the same period, CO and NO2 showed a decreasing trend from December 2019 to March 2020, with an average total change of 4082.36 mol/m2 and 167.25 mol/m2, and an average total change rate of 4.80% and 38.11%, respectively. SO2 did not have a significant decrease. This is inextricably linked to the reduction of human travel production activities with the implementation of the home quarantine policy. (2) The spatial and temporal variation of AOD was similar to that of pollutants, but showed a significant increase in January 2020, with an average total amount increase of 1.69 × 107 up about 2.54% from December 2019 to March 2020. This is attributed to urban heating and the reduction of pollutants such as NOx. (3) Pollutants and AOD were significantly correlated with meteorological data (e.g., average temperature, average humidity, average wind speed, average precipitation, etc.). This study provides data support for atmospheric protection and air quality monitoring in Shandong Province, as well as theoretical basis and technical guidance for policy formulation and urban planning.
引用
收藏
页码:863 / 876
页数:13
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