Sensitivity analysis of WRF-CMAQ model in predicting PM2.5 and O3 concentration in Peninsular Malaysia: 2019 transboundary burning smoke case study

The high PM2.5 concentrations significantly influence the air quality in the Maritime Continent region, especially in Peninsular Malaysia (PMY), which is affected by the annual burning season. However, the 2019 pollution case is unique due to the presence of a positive Indian Ocean dipole (pIOD) with a weak El Niño, which influenced the transport of pollutants toward PMY. This work aims to evaluate the ability of the numerical chemical weather prediction model (WRF-CMAQ) by performing a sensitivity analysis to reproduce the air quality during this event. Two model settings were studied: weather nudging and the burning emission amount of the fire inventory from NCAR (FINN). Three cases were established: 1) WRF-CMAQw (without nudging setting and with original fire emission), 2) WRF-CMAQn (with nudging setting and with original fire emission), and 3) WRF-CMAQa (with nudging setting and adjusted fire emission) to predict the PM2.5 concentration in PMY during the 2019 transboundary smoke event. The weather (temperature and wind profile) simulation results showed that WRF-CMAQa and WRF-CMAQn agreed up about 95 % and WRF-CMAQw agreed up to 93 % when compared with ground weather stations based on the statistical evaluation of correlation coefficient, bias, and error measures. For air quality, overall, WRF-CMAQa (87.23 %) demonstrated better performance compared to WRF-CMAQw (62.41 %) and WRF-CMAQn (78.72 %) in predicting the ground PM2.5. However, the diurnal prediction during the transboundary smoke event remains weak. For O3 concentration, the model performance agreement was quite low for all simulations. However, WRF-CMAQa could predict about 44.76 % compared to WRF-CMAQn (26.66 %) and WRF-CMAQw (41.90 %) in overall model performance, and all simulations managed to capture the diurnal trend of O3 when compared with ground observation station data. In conclusion, the sensitivity study on the weather and chemical prediction model, especially WRF-CMAQ, could help improve the air quality prediction system in PMY during the recurrence of transboundary smoke events.