Research on the fugitive soil dust emission inventory in Western China based on wind erosion equation parameter optimization

Abstract

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.