Optimized approach for developing soil fugitive dust emission inventory in "2+26" Chinese cities. (15th September 2021) - Li, Tingkun; Bi, Xiaohui; Dai, Qili; Wu, Jianhui; Zhang, Yufen; Feng, Yinchang
Abstract: Based on the wind erosion equation and the use of moderate resolution imaging spectroradiometer (MODIS) satellite remote sensing data combined with parameter normalization processing, an optimized high spatial-temporal resolution soil fugitive dust (SFD ) emission inventory compiling method was proposed in this study. The "2 + 26" cities in northern China, where heavy pollution frequently occurs, were used as a case study. Using the optimized method, we estimated that the PM50, PM10, and PM2.5 emissions from SFD of "2 + 26" cities in 2018 were 2, 014, 927, 1, 007, 463, and 151, 120 tons, respectively. The dust emissions and emission factors of each city presented significant differences and were generally of a greater level in high-latitude areas (such as cities in Hebei Province) than in low-latitude areas (such as cities in Henan and Shandong Province). Moreover, with an increase in latitude, vegetation cover factors generally exhibit an upward trend, while temperature and rainfall exhibit a downward trend. The dust emissions in the different months showed significant differences. The total dust emission reached the highest level in "late winter–early spring" season (February to April), and the monthly emission accounted for 15–17% of the annual emissions. While in the "summer–autumn" season (July to November), it is the lowest level of the whole year, monthly emissions accounted for 3–5% of the annual emissions. The emission inventory method proposed in this study can provide a reference for dust emission assessment and further pollution prevention and control work. Graphical abstract: Image 1 Highlights: An optimized method for compiling high spatial-temporal resolution soil fugitive dust emission inventory was proposed. The "2 + 26 cities" in northern China, where heavy pollution weather frequently occurs and attracts wide attention, were taken as case study. The spatial-temporal distribution characteristics of key factors and dust emissions were analyzed.