气候变化领域集成服务门户(CCPortal): Establishment of PM10 and PM2.5 emission inventories from wind erosion source and simulation of its environmental impact based on WEPS-Models3 in southern Xinjiang, China

CCPortal

DOI	10.1016/j.atmosenv.2021.118222
	Establishment of PM10 and PM2.5 emission inventories from wind erosion source and simulation of its environmental impact based on WEPS-Models3 in southern Xinjiang, China
	Liu Y.; Teng Y.; Liang S.; Li X.; Zhao J.; Shan M.; Chen L.; Yu H.; Mao J.; Zhang H.; Gao S.; Sun Y.; Ma Z.; Bai Z.; Yang W.; Azzi M.
发表日期	2021
ISSN	1352-2310
卷号	248
英文摘要	Southern Xinjiang located in the far northwest of China is experiencing serious particulate matter (PM) pollution. The wind erosion has been recognized as a great contributor of PM10 and PM2.5 concentrations in southern Xinjiang. In this study we developed a method that used the Wind Erosion Prediction System (WEPS) to establish the PM10 and PM2.5 emission inventories from the wind erosion source in southern Xinjiang with a 10 km × 10 km spatial resolution and a temporal resolution of one month. The PM10 and PM2.5 emission inventories from wind erosion sources were provided as input to the Models3/SMOKE (Sparse Matrix Operator Kernel Emission). The Community Multi-scale Air Quality (CMAQ) model was employed to simulate PM10 and PM2.5 concentrations from wind erosion source and the results were compared with the monitoring data to verify the emission inventories. The total PM10 and PM2.5 emissions were 12 × 106 t and 4 × 106 t, respectively, and the emission per unit area were 14.6 t/km2 and 4.9 t/km2, respectively, in southern Xinjiang in 2016. The PM10 and PM2.5 emissions per unit area were highest in Kashi being 19.1 t/km2 and 9.1 t/km2, respectively. The total emissions peaked at 5.4 × 106 t/km2 in PM10 and 1.4 × 106 t/km2 in PM2.5 in Bazhou. The PM10 and PM2.5 emissions were highest in spring, followed by summer, winter and autumn. The Normalized Mean Error (NME) between the predicted monthly average PM10 and PM2.5 concentrations from wind erosion source and the results from multiplying the monitoring data by the source apportionment results of PM10 and PM2.5 were 25.3% and 26.1%, respectively, which indicated that the accuracies of the PM10 and PM2.5 emission inventories from wind erosion source in southern Xinjiang were satisfactory. © 2021 Elsevier Ltd
关键词	Emission inventory Models3 Particulate matter WEPS Wind erosion
语种	英语
scopus关键词	Air quality; Monitoring; Community multi-scale air qualities; Emission inventories; Particulate Matter; Source apportionment; Sparse matrix operator kernel emissions; Spatial resolution; Temporal resolution; Wind erosion prediction systems (WEPS); Erosion; air quality; atmospheric modeling; atmospheric pollution; emission inventory; environmental impact assessment; particle size; particulate matter; spatial resolution; wind erosion; air quality; article; autumn; human; particulate matter 10; particulate matter 2.5; prediction; simulation; smoke; spring; summer; wind erosion; winter; Xinjiang; China; Xinjiang Uygur
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/248579
作者单位	School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin, 300387, China; CSIRO Energy, 10 Murray Dwyer Circuit, Mayfield WestNSW 2304, Australia; Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
推荐引用方式 GB/T 7714	Liu Y.,Teng Y.,Liang S.,et al. Establishment of PM10 and PM2.5 emission inventories from wind erosion source and simulation of its environmental impact based on WEPS-Models3 in southern Xinjiang, China[J],2021,248.
APA	Liu Y..,Teng Y..,Liang S..,Li X..,Zhao J..,...&Azzi M..(2021).Establishment of PM10 and PM2.5 emission inventories from wind erosion source and simulation of its environmental impact based on WEPS-Models3 in southern Xinjiang, China.ATMOSPHERIC ENVIRONMENT,248.
MLA	Liu Y.,et al."Establishment of PM10 and PM2.5 emission inventories from wind erosion source and simulation of its environmental impact based on WEPS-Models3 in southern Xinjiang, China".ATMOSPHERIC ENVIRONMENT 248(2021).