Utilisation of local emission inventory data for forecasting PM10 using the WRF-Chem model in the Bandung Basin

The 2015 local emission data from the Ministry of Environment and Forestry of the Republic of Indonesia is used as the anthropogenic emission input for the WRF-Chem model to forecast particulate matter with a size of 10 μm or less (PM10). The research examines the model’s performance when the anthropogenic emission data were replaced from global to local. The study focuses on the Bandung Basin, running the model for both dry and wet seasons. Two scenarios are conducted for each season: the first (control scenario) uses global emissions, whereas the second (updated scenario) utilises local emissions. The results indicate that the WRF-Chem model’s performance improved slightly when regional emissions replaced global emissions in either season. When the model’s output was compared with ground station data, the PM10 pattern of the second scenario followed the pattern of the observation data. Regarding the Pearson correlation and root mean square error (RMSE), the wet season result exhibits a better score than the dry season result. Though the RMSE for both seasons shows an unsatisfactory score, the Pearson Correlation shows a good score. Both scenarios produce a poor RMSE score, and these results reveal that anthropogenic emissions updated with local emissions still cannot produce a high accuracy of PM10 prediction in the Bandung Basin.