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Analysis of the Spatial and Temporal Patterns of Ground-Level Ozone Concentrations in the Guangdong–Hong Kong–Macao Greater Bay Area and the Contribution of Influencing Factors.
- Source :
- Remote Sensing; Nov2022, Vol. 14 Issue 22, p5796, 21p
- Publication Year :
- 2022
-
Abstract
- Ozone (O<subscript>3</subscript>) pollution has negative impacts on human health and property. The Guangdong–Hong Kong–Macao Greater Bay Area (GBA) is facing severe O<subscript>3</subscript> pollution problems due to rapid economic development. In this paper, we used sensitivity experiments and GeoDetector to analyze the effects of meteorological factors, anthropogenic emissions, and landscape patterns on O<subscript>3</subscript> concentrations as well as the contributions of NO<subscript>x</subscript> and NMVOC (non-methane volatile organic compounds) to the variation of O<subscript>3</subscript> concentrations and the causes of sectoral emissions in the GBA in 2017. The results revealed that, in GBA, the contribution of meteorology to the variation of O<subscript>3</subscript> concentration was dominant both in terms of region and extent, and the contribution of emissions was relatively weak. The contribution of meteorology and emissions to O<subscript>3</subscript> production was mainly contributory. Meteorology contributed significantly to O<subscript>3</subscript>, and its non-linear interaction with anthropogenic emissions and surface landscape affected O<subscript>3</subscript> concentration changes. The degree of contribution of NO<subscript>x</subscript> and NMVOC varied widely among seasons, and the variation of their relative contribution areas was related to residential sector emissions and agricultural sector emissions. This article enriches the exploration of the O<subscript>3</subscript> formation mechanism in the GBA and provides theoretical support for the implementation of differentiated regional and seasonal mitigation strategies for O<subscript>3</subscript> concentration. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20724292
- Volume :
- 14
- Issue :
- 22
- Database :
- Complementary Index
- Journal :
- Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 160465465
- Full Text :
- https://doi.org/10.3390/rs14225796