Pollution source emission inventories are the basis for analyzing the causes of pollution, identifying the contribution of pollution sources, and scientifically formulating air pollution prevention strategies. The current inventory construction methods mainly focus on improving the accuracy and spatial and temporal resolution of the inventory, and there is an urgent need to look into dynamic updating methods to address the problem of lagging source emission inventories. In order to develop an effective and versatile method for the dynamic updating of source emission inventories, a meteorological normalization method based on random forests was chosen to capture the response relationship between pollutants and anthropogenic emissions.
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