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

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Title: Sensitivity analysis of WRF-CMAQ model in predicting PM2.5 and O3 concentration in Peninsular Malaysia: 2019 transboundary burning smoke case study.
Authors: Mohd Napi, Nur Nazmi Liyana1 (AUTHOR), Ooi, Maggie Chel Gee1 (AUTHOR) chelgee.ooi@ukm.edu.my, Latif, Mohd Talib2 (AUTHOR), Juneng, Liew2 (AUTHOR), Mohd Nadzir, Mohd Shahrul2 (AUTHOR), Cheah, Wee3 (AUTHOR), Chan, Andy4 (AUTHOR), Li, Li5,6 (AUTHOR)
Source: Atmospheric Environment. Dec2025, Vol. 362, pN.PAG-N.PAG. 1p.
Subject Terms: *Particulate matter, *Ecological forecasting, Atmospheric ozone measurement, Sensitivity analysis, Internal combustion engine exhaust gas, Malaysians
Geographic Terms: Indian Ocean, Malaysia, Malay Peninsula
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. [Display omitted] • During the smoke event in Peninsular Malaysia, PM 2.5 exceeded local and international standards, while O 3 remained permissible. • Grid nudging improved weather prediction by 95 % during the smoke event. • In WRF-CMAQ, adjustment of fire input (FINN) enhanced PM 2.5 prediction by 87.23 % and O 3 by 44.76 %. • WRF-CMAQ outperformed CAMS and MERRA-2 in predicting PM 2.5 and O 3 in Peninsular Malaysia. [ABSTRACT FROM AUTHOR]
Copyright of Atmospheric Environment is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Sensitivity analysis of WRF-CMAQ model in predicting PM2.5 and O3 concentration in Peninsular Malaysia: 2019 transboundary burning smoke case study.
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  Data: <searchLink fieldCode="AR" term="%22Mohd+Napi%2C+Nur+Nazmi+Liyana%22">Mohd Napi, Nur Nazmi Liyana</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ooi%2C+Maggie+Chel+Gee%22">Ooi, Maggie Chel Gee</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> chelgee.ooi@ukm.edu.my</i><br /><searchLink fieldCode="AR" term="%22Latif%2C+Mohd+Talib%22">Latif, Mohd Talib</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Juneng%2C+Liew%22">Juneng, Liew</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mohd+Nadzir%2C+Mohd+Shahrul%22">Mohd Nadzir, Mohd Shahrul</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cheah%2C+Wee%22">Cheah, Wee</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Chan%2C+Andy%22">Chan, Andy</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Li%22">Li, Li</searchLink><relatesTo>5,6</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Atmospheric+Environment%22">Atmospheric Environment</searchLink>. Dec2025, Vol. 362, pN.PAG-N.PAG. 1p.
– Name: Subject
  Label: Subject Terms
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  Data: *<searchLink fieldCode="DE" term="%22Particulate+matter%22">Particulate matter</searchLink><br />*<searchLink fieldCode="DE" term="%22Ecological+forecasting%22">Ecological forecasting</searchLink><br /><searchLink fieldCode="DE" term="%22Atmospheric+ozone+measurement%22">Atmospheric ozone measurement</searchLink><br /><searchLink fieldCode="DE" term="%22Sensitivity+analysis%22">Sensitivity analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Internal+combustion+engine+exhaust+gas%22">Internal combustion engine exhaust gas</searchLink><br /><searchLink fieldCode="DE" term="%22Malaysians%22">Malaysians</searchLink>
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  Label: Geographic Terms
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  Data: <searchLink fieldCode="DE" term="%22Indian+Ocean%22">Indian Ocean</searchLink><br /><searchLink fieldCode="DE" term="%22Malaysia%22">Malaysia</searchLink><br /><searchLink fieldCode="DE" term="%22Malay+Peninsula%22">Malay Peninsula</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. [Display omitted] • During the smoke event in Peninsular Malaysia, PM 2.5 exceeded local and international standards, while O 3 remained permissible. • Grid nudging improved weather prediction by 95 % during the smoke event. • In WRF-CMAQ, adjustment of fire input (FINN) enhanced PM 2.5 prediction by 87.23 % and O 3 by 44.76 %. • WRF-CMAQ outperformed CAMS and MERRA-2 in predicting PM 2.5 and O 3 in Peninsular Malaysia. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Atmospheric Environment is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.atmosenv.2025.121496
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Particulate matter
        Type: general
      – SubjectFull: Ecological forecasting
        Type: general
      – SubjectFull: Atmospheric ozone measurement
        Type: general
      – SubjectFull: Sensitivity analysis
        Type: general
      – SubjectFull: Internal combustion engine exhaust gas
        Type: general
      – SubjectFull: Malaysians
        Type: general
      – SubjectFull: Indian Ocean
        Type: general
      – SubjectFull: Malaysia
        Type: general
      – SubjectFull: Malay Peninsula
        Type: general
    Titles:
      – TitleFull: Sensitivity analysis of WRF-CMAQ model in predicting PM2.5 and O3 concentration in Peninsular Malaysia: 2019 transboundary burning smoke case study.
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            NameFull: Mohd Napi, Nur Nazmi Liyana
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            – D: 01
              M: 12
              Text: Dec2025
              Type: published
              Y: 2025
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