干旱区生态环境知识资源中心(Arid): Research on the fugitive soil dust emission inventory in Western China based on wind erosion equation parameter optimization

Arid

DOI	10.3389/fenvs.2023.1301934
	Research on the fugitive soil dust emission inventory in Western China based on wind erosion equation parameter optimization
	Wang, Pengbo; Chen, Min; An, Weiming; Liu, Yongle; Pan, Feng
通讯作者	Pan, F
来源期刊	FRONTIERS IN ENVIRONMENTAL SCIENCE
EISSN	2296-665X
出版年	2023
卷号	11
英文摘要	The Wind Erosion Equation, currently one of the primary methods for estimating fugitive soil dust emission inventory, is influenced by several factors. Taking the convergent areas of the Tibet Plateau, Loess Plateau, and Qinba Mountains in Western China, we have optimized the climate factor using the WRF model driven by ERA5 reanalysis data. Additionally, we have modified the vegetation cover The Wind Erosion Equation, currently one of the primary methods for estimating fugitive soil dust emission inventory, is influenced by several factors. Taking the convergent areas of the Tibet Plateau, Loess Plateau, and Qinba Mountains in Western China, we have optimized the climate factor using the WRF model driven by ERA5 reanalysis data. Additionally, we have modified the vegetation cover factors via normalized difference vegetation index and considered the impacts of the land use and cover change. Subsequently, other factors were allocated utilizing geographic information system, and the grid-based fugitive soil dust emission inventory for the study area for 2019 was derived through calculation. Based on the climate factor and vegetation cover factor, we have come up with the monthly allocation coefficients. The study has revealed the following findings: (1) Climate factors are unevenly distributed throughout the focused region, with the Loess Plateau showing the highest value, followed by the Tibet Plateau and the Qinba Mountains. There are also significant variations in the distribution of these factors among municipalities and counties; (2) The order of vegetation cover factor, primarily influenced by regional background as well as agricultural and pastoral activities, in the Loess Plateau, Tibetan Plateau and Qinba Mountains, is consistent with that of the wind erosion index; (3) In 2019, fugitive dust emissions from total suspended particles, PM10, and PM2.5 reached 9835.9, 2950.8, and 491.8 kt/a, respectively. The Loess Plateau exhibited the highest emission intensity due to factors such as low vegetation coverage, precipitation, high wind speed and wind erosion index; (4) Climate factor and vegetation cover factor are the primary factors influencing the monthly allocation coefficients. In 2019, the highest monthly fugitive dust emissions were estimated in April, accounting for approximately 36.21% of the total. The second and third-highest were found in August and June, respectively. This phenomenon can be explained climatically, as the Loess Plateau, semi-arid and arid regions, did not experience a significant increase in rainfall corresponding to rising temperatures. via normalized difference vegetation index and considered the impacts of the land use and cover change. Subsequently, other factors were allocated utilizing geographic information system, and the grid-based fugitive soil dust emission inventory for the study area for 2019 was derived through calculation. Based on the climate factor and vegetation cover factor, we have come up with the monthly allocation coefficients. The study has revealed the following findings: (1) Climate factors are unevenly distributed throughout the focused region, with the Loess Plateau showing the highest value, followed by the Tibet Plateau and the Qinba Mountains. There are also significant variations in the distribution of these factors among municipalities and counties; (2) The order of vegetation cover factor, primarily influenced by regional background as well as agricultural and pastoral activities, in the Loess Plateau, Tibetan Plateau and Qinba Mountains, is consistent with that of the wind erosion index; (3) In 2019, fugitive dust emissions from total suspended particles, PM10, and PM2.5 reached 9835.9, 2950.8, and 491.8 kt/a, respectively. The Loess Plateau exhibited the highest emission intensity due to factors such as low vegetation coverage, precipitation, high wind speed and wind erosion index; (4) Climate factor and vegetation cover factor are the primary factors influencing the monthly allocation coefficients. In 2019, the highest monthly fugitive dust emissions were estimated in April, accounting for approximately 36.21% of the total. The second and third-highest were found in August and June, respectively. This phenomenon can be explained climatically, as the Loess Plateau, semi-arid and arid regions, did not experience a significant increase in rainfall corresponding to rising temperatures.
英文关键词	WRF wind erosion equation climate factor vegetation cover factor fugitive soil dust emission inventory monthly allocation coefficient
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:001124913300001
WOS关键词	RIVER DELTA REGION ; SOURCE APPORTIONMENT ; AIR-POLLUTANTS ; WEQ ; MORTALITY ; MODEL ; RWEQ
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/396518
推荐引用方式 GB/T 7714	Wang, Pengbo,Chen, Min,An, Weiming,et al. Research on the fugitive soil dust emission inventory in Western China based on wind erosion equation parameter optimization[J],2023,11.
APA	Wang, Pengbo,Chen, Min,An, Weiming,Liu, Yongle,&Pan, Feng.(2023).Research on the fugitive soil dust emission inventory in Western China based on wind erosion equation parameter optimization.FRONTIERS IN ENVIRONMENTAL SCIENCE,11.
MLA	Wang, Pengbo,et al."Research on the fugitive soil dust emission inventory in Western China based on wind erosion equation parameter optimization".FRONTIERS IN ENVIRONMENTAL SCIENCE 11(2023).