MDPI and ACS Style
Gao, S.; Liu, Y.; Zhang, J.; Yu, J.; Chen, L.; Sun, Y.; Mao, J.; Zhang, H.; Ma, Z.; Yang, W.;
et al. Soil-Derived Dust PM10 and PM2.5 Fractions in Southern Xinjiang, China, Using an Artificial Neural Network Model. Atmosphere 2023, 14, 1644.
https://doi.org/10.3390/atmos14111644
AMA Style
Gao S, Liu Y, Zhang J, Yu J, Chen L, Sun Y, Mao J, Zhang H, Ma Z, Yang W,
et al. Soil-Derived Dust PM10 and PM2.5 Fractions in Southern Xinjiang, China, Using an Artificial Neural Network Model. Atmosphere. 2023; 14(11):1644.
https://doi.org/10.3390/atmos14111644
Chicago/Turabian Style
Gao, Shuang, Yaxin Liu, Jieqiong Zhang, Jie Yu, Li Chen, Yanling Sun, Jian Mao, Hui Zhang, Zhenxing Ma, Wen Yang,
and et al. 2023. "Soil-Derived Dust PM10 and PM2.5 Fractions in Southern Xinjiang, China, Using an Artificial Neural Network Model" Atmosphere 14, no. 11: 1644.
https://doi.org/10.3390/atmos14111644