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

The high PM 2.5 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-CMAQ w (without nudging setting and with original fire emission), 2) WRF-CMAQ n (with nudging setting and with original fire emission), and 3) WRF-CMAQ a (with nudging setting and adjusted fire emission) to predict the PM 2.5 concentration in PMY during the 2019 transboundary smoke event. The weather (temperature and wind profile) simulation results showed that WRF-CMAQ a and WRF-CMAQ n agreed up about 95% and WRF-CMAQ w 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-CMAQ a (87.23%) demonstrated better performance compared to WRF-CMAQ w (62.41%) and WRF-CMAQ n (78.72%) in predicting the ground PM 2.5 . However, the diurnal prediction during the transboundary smoke event remains weak. For O 3 concentration, the model performance agreement was quite low for all simulations. However, WRF-CMAQ a could predict about 44.76% compared to WRF-CMAQ n (26.66%) and WRF-CMAQ w (41.90%) in overall model performance, and all simulations managed to capture the diurnal trend of O 3 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. • PM 2.5 levels has exceeded NMAAQS and WHO limits, while O 3 remained within permissible levels during transboundary smoke event in PMY. • Grid nudging improved weather prediction by 95% during the smoke event. • In WRF-CMAQ a , adjusted FINN enhanced PM 2.5 prediction by 87.23% and O 3 by 44.76%. • WRF-CMAQ a outperformed CAMS and MERRA-2 in predicting PM 2.5 and O 3 concentrations during transboundary smoke events in Peninsular Malaysia.

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Journal
Atmospheric Environment
Published
2025-08-18
DOI
https://doi.org/10.1016/j.atmosenv.2025.121496
Primary Topic
Atmospheric chemistry and aerosols
Type
article
Field-Weighted Citation Impact
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article

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

Mohd Shahrul Mohd Nadzir, Nur Nazmi Liyana Mohd Napi, Wee Cheah, Maggie Chel Gee Ooi et al.
Atmospheric Environment
Atmospheric chemistry and aerosols
article

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

Mohd Shahrul Mohd Nadzir, Nur Nazmi Liyana Mohd Napi, Wee Cheah, Maggie Chel Gee Ooi, Mohd Talib Latif, Andy Chan, Liew Juneng, Li Li
article en

Abstract

The high PM 2.5 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-CMAQ w (without nudging setting and with original fire emission), 2) WRF-CMAQ n (with nudging setting and with original fire emission), and 3) WRF-CMAQ a (with nudging setting and adjusted fire emission) to predict the PM 2.5 concentration in PMY during the 2019 transboundary smoke event. The weather (temperature and wind profile) simulation results showed that WRF-CMAQ a and WRF-CMAQ n agreed up about 95% and WRF-CMAQ w 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-CMAQ a (87.23%) demonstrated better performance compared to WRF-CMAQ w (62.41%) and WRF-CMAQ n (78.72%) in predicting the ground PM 2.5 . However, the diurnal prediction during the transboundary smoke event remains weak. For O 3 concentration, the model performance agreement was quite low for all simulations. However, WRF-CMAQ a could predict about 44.76% compared to WRF-CMAQ n (26.66%) and WRF-CMAQ w (41.90%) in overall model performance, and all simulations managed to capture the diurnal trend of O 3 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. • PM 2.5 levels has exceeded NMAAQS and WHO limits, while O 3 remained within permissible levels during transboundary smoke event in PMY. • Grid nudging improved weather prediction by 95% during the smoke event. • In WRF-CMAQ a , adjusted FINN enhanced PM 2.5 prediction by 87.23% and O 3 by 44.76%. • WRF-CMAQ a outperformed CAMS and MERRA-2 in predicting PM 2.5 and O 3 concentrations during transboundary smoke events in Peninsular Malaysia.

Atmospheric EnvironmentVol. 362
Shanghai University (CN), University of Nottingham Malaysia Campus (MY), University of Malaya (MY), National University of Malaysia (MY)
Ministry of Higher Education, Malaysia, Kementerian Pendidikan Malaysia
Zero hunger
Openalex Percentile: Top 74%
Atmospheric chemistry and aerosols
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