Emission Inventory of Soil Fugitive Dust Sources with High Spatiotemporal Resolution: A Case Study of Daxing District, Beijing, China

Qianxi Liu, Yalan Liu (), Shufu Liu (), Jinghai Zhao, Bin Zhao, Feng Zhou, Dan Zhu, Dacheng Wang (), Linjun Yu, Ling Yi and Gang Chen
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Qianxi Liu: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Yalan Liu: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Shufu Liu: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Jinghai Zhao: Daxing District Ecological Environment Bureau of Beijing Municipality, Beijing 102699, China
Bin Zhao: Daxing District Ecological Environment Bureau of Beijing Municipality, Beijing 102699, China
Feng Zhou: Daxing District Ecological Environment Bureau of Beijing Municipality, Beijing 102699, China
Dan Zhu: Daxing District Ecological Environment Bureau of Beijing Municipality, Beijing 102699, China
Dacheng Wang: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Linjun Yu: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Ling Yi: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Gang Chen: Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

Land, 2024, vol. 13, issue 12, 1-18

Abstract: Soil fugitive dust (SFD) is a significant contributor to environmental particulate matter (PM), which not only pollutes and affects air quality but also poses risks to human health. The emission inventory can provide a basis for the effective prevention and control of SFD pollution. However, current emission inventories with low resolution and frequency make it difficult to assess dust emissions accurately. Obtaining monthly high-resolution bare soil information is one of the solutions for compiling SFD emission inventories. Taking Daxing District, Beijing, as a case study, this study first extracted bare soil for each month of 2020, 2021, and 2022, respectively, using high-spatial-resolution remote sensing satellite data, and then constructed a 10 m-size emission grid and monthly SFD emission inventories based on the wind erosion equation by inputting vegetation cover factor, meteorological data, and soil erosion index. The total emissions of TSP, PM 10 , and PM 2.5 in Daxing District from 2020 to 2022 were 3996.54 tons, 359.26 tons, and 25.25 tons, respectively. Temporally, the SFD emissions showed a decreasing trend over the years and were mainly concentrated in the winter and spring seasons. Spatially, the SFD emissions were predominantly concentrated in the southern and northern areas. And the emissions of PM 10 exhibit a significantly stronger correlation with wind speed and the extent of bare soil area.

Keywords: soil fugitive dust; bare soil; wind erosion equation; emission inventory; remote sensing; high spatiotemporal resolution; air quality (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2024
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