Abstract

With the rapid development of the social economy, nitrogen dioxide (NO2), a trace gas that is an air pollutant, has dual impacts on human health and climate change. In this study, the Google Earth Engine platform is used to retrieve the vertical column concentration inverted by the Tropospheric Monitoring Instrument (TROPOMI) sensor onboard the Sentinel-5 Precursor satellite, and the characteristics of the spatial–temporal distribution of the tropospheric NO2 column concentration in Shandong Province from 2019 to 2023 are analyzed. The results show that there is a high correlation between the NO2 column concentration retrieved from the TROPOMI and the NO2 concentration observed at ground-level monitoring points in Shandong Province (R = 0.8289). The distribution of the NO2 column concentration in Shandong Province exhibits a progressive structure of “high in the west and low in the east” with significant spatial heterogeneity. In addition, the fluctuation in the NO2 column concentration in Shandong Province has obvious cyclical and seasonal characteristics, and the change rate is “summerflat in spring and autumn, high in winter and low in summer.” The results of the geographical detectors indicate that temperature has the greatest influence on the NO2 column concentration in Shandong Province (q = 0.5). The geographically weighted regression model indicated that the NO2 column concentration was negatively correlated with the topography, temperature, and precipitation, and the correlation coefficients are −0.010, −0.952, and −0.330, respectively. It is positively correlated with the intensity of human activities, the degree of urbanization of the land, and the population density, and the correlation coefficients are 0.1610, 0.982, and 0.001, respectively.

Details

Title
Spatial–temporal variations of NO2 pollution in Shandong Province based on Sentinel-5P satellite data and influencing factors
Author
Zeng, Siting 1 ; Zhou, Shijian 2 ; Wang, Fengwei 3 ; Zhou, Yunqi 4 ; Zhang, Yuan 1 

 School of Surveying and Geoinformation Engineering, East China University of Technology, Nanchang, 330013, China; Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake of Ministry of Natural Resources, East China University of Technology, Nanchang, 330013, China 
 School of Software, Nanchang Hangkong University, Nanchang, 330063, China 
 College of Surveying and Geo-informatics, Tongji University, Shanghai, 200092, China 
 School of Geographical Sciences, University of Bristol, Bristol, BS8 1SS, United Kingdom 
Publication year
2025
Publication date
2025
Publisher
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
e-ISSN
23915447
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3268078620
Copyright
© 2025. This work is published under http://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.