Estimating and characterizing spatiotemporal distributions of elemental PM2.5 using an ensemble machine learning approach in Taiwan

Huang, Chun-ShengChun-ShengHuangLo, KangKangLoWu, Yee-LinYee-LinWuWang, Fu-ChengFu-ChengWangShiu, Yi-ShiangYi-ShiangShiuChen, Chu-ChihChu-ChihChenLin, Yuan-ChienYuan-ChienLinKuo, Cheng-PinCheng-PinKuoLiao, Ho-TangHo-TangLiaoLin, Tang-HuangTang-HuangLinCHANG-FU WU2026-01-022026-01-022025-05https://scholars.lib.ntu.edu.tw/handle/123456789/734991[SDGs]SDG3[SDGs]SDG11Estimating and characterizing spatiotemporal distributions of elemental PM2.5 using an ensemble machine learning approach in Taiwanjournal article10.1016/j.apr.2025.102463