Development and application of a multi-task oriented deep learning model for quantifying drivers of air pollutant variations: A case study in Taiyuan, China
Description
Quantitative assessment of the drivers behind the variation of six criteria pollutants, namely fine particulate matter (PM(2.5)), ozone (O(3)), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), particulate matter (PM(10)), and carbon monoxide (CO)
