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Open AccessArticle

Spatial Variation of NO2 and Its Impact Factors in China: An Application of Sentinel-5P Products

1
School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China
2
Department of Land, Environment, Agriculture and Forestry, University of Padova, 35020 Padova, Italy
3
Guangdong Province Engineering Technology Research Center for Geographical Conditions Monitoring and Comprehensive Analysis, Guangzhou 510006, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(16), 1939; https://doi.org/10.3390/rs11161939
Received: 30 June 2019 / Revised: 8 August 2019 / Accepted: 9 August 2019 / Published: 19 August 2019
As an important tropospheric trace gas and precursor of photochemical smog, the accumulation of NO2 will cause serious air pollution. China, as the largest developing country in the world, has experienced a large amount of NO2 emissions in recent decades due to the rapid economic growth. Compared with the traditional air pollution monitoring technology, the rapid development of the remote sensing monitoring method of atmospheric satellite has gradually become the critical technical means of global atmospheric environmental monitoring. To reveal the NO2 pollution situation in China, based on the latest NO2 products from Sentinel-5P TROPOMI, the spatial–temporal characteristics and impact factors of troposphere NO2 column concentration of mainland China in the past year (February 2018 to January 2019) were analyzed on two administrative levels for the first time. Results show that the monthly fluctuation of tropospheric NO2 column concentration has obvious characteristics of “high in winter and low in summer”, while the spatial distribution forms a “high in East and low in west” pattern, bounded by Hu Line. The comparison of Coefficient of Variation (CV) and spatial autocorrelation models at two kinds of administrative scales indicates that although the spatial heterogeneity of NO2 column concentration is less affected by the observed scale, there is a “delayed effect” of about one month in the process of NO2 column concentration fluctuation. Besides, the impact factors analysis based on Spatial Lag Model (SLM) and Geographic Weighted Regression (GWR) reveals that there is a positive correlation between nighttime light intensity, the secondary and tertiary industries proportion and NO2 column concentration. Furthermore, for regions with serious NO2 pollution in North China Plain, the whole society electricity consumption and vehicle ownership also play a positive role in increasing the NO2 column concentration. This study will enlighten the government and policy makers to formulate policies tailored to local conditions, to more effectively implement NO2 emission reduction and air pollution prevention. View Full-Text
Keywords: NO2; Sentinel-5P; air pollution; spatial autocorrelation; impact factor; China NO2; Sentinel-5P; air pollution; spatial autocorrelation; impact factor; China
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Zheng, Z.; Yang, Z.; Wu, Z.; Marinello, F. Spatial Variation of NO2 and Its Impact Factors in China: An Application of Sentinel-5P Products. Remote Sens. 2019, 11, 1939.

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