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Evaluation and Prediction of PM 10 and PM 2.5 from Road Source Emissions in Kuala Lumpur City Centre

Author

Listed:
  • Azliyana Azhari

    (Center for Research in Development, Social and Environment, Faculty of Social Science and Humanities, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Selangor, Malaysia)

  • Nor Diana Abdul Halim

    (Institute for Environment and Development (LESTARI), Universiti Kebangsaan Malaysia, UKM Bangi 43600, Selangor, Malaysia)

  • Anis Asma Ahmad Mohtar

    (Department of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Selangor, Malaysia)

  • Kadaruddin Aiyub

    (Center for Research in Development, Social and Environment, Faculty of Social Science and Humanities, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Selangor, Malaysia)

  • Mohd Talib Latif

    (Department of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Selangor, Malaysia)

  • Matthias Ketzel

    (Department of Environmental Science, Aarhus University, Frederiksborgvej 399, DK-4000 Roskilde, Denmark
    Global Centre for Clean Air Research (GCARE), Department of Civil and Environmental Engineering, University of Surrey, Guildford GU2 7XH, UK)

Abstract

Particulate matter (PM) is one of the major pollutants emitted by vehicles that adversely affect human health and the environment. This study evaluates and predicts concentrations and dispersion patterns of PM 10 and PM 2.5 in Kuala Lumpur city centre. The OML-Highway model calculates hourly time series of PM 10 and PM 2.5 concentrations and distribution caused by traffic emissions under different scenarios; business as usual (BAU) and 30% traffic reduction to see the impact of traffic reduction for sustainable traffic management. Continuous PM 10 and PM 2.5 data from a nearby monitoring station were analysed for the year 2019 and compared with modelled concentrations. Annual average concentration at various locations of interest for PM 10 and PM 2.5 during BAU runs were in the ranges 41.4–65.9 µg/m 3 and 30.4–43.7 µg/m 3 respectively, compared to during the 30% traffic reduction run ranging at 40.5–59.5 µg/m 3 and 29.9–40.3 µg/m 3 respectively. The average concentration of PM 10 and PM 2.5 at the Continuous Air Quality Monitoring Station (CAQMS) was 36.4 µg/m 3 and 28.2 µg/m 3 respectively. Strong correlations were observed between the predicted and observed data for PM 10 and PM 2.5 in both scenarios ( p < 0.05). This research demonstrated that the reduction of traffic volume in the city contributes to reducing the concentration of particulate matter pollution.

Suggested Citation

  • Azliyana Azhari & Nor Diana Abdul Halim & Anis Asma Ahmad Mohtar & Kadaruddin Aiyub & Mohd Talib Latif & Matthias Ketzel, 2021. "Evaluation and Prediction of PM 10 and PM 2.5 from Road Source Emissions in Kuala Lumpur City Centre," Sustainability, MDPI, vol. 13(10), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:10:p:5402-:d:552921
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    References listed on IDEAS

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    1. Francesco Russo & Antonio Comi, 2016. "Urban Freight Transport Planning towards Green Goals: Synthetic Environmental Evidence from Tested Results," Sustainability, MDPI, vol. 8(4), pages 1-18, April.
    2. Badland, Hannah & Whitzman, Carolyn & Lowe, Melanie & Davern, Melanie & Aye, Lu & Butterworth, Iain & Hes, Dominique & Giles-Corti, Billie, 2014. "Urban liveability: Emerging lessons from Australia for exploring the potential for indicators to measure the social determinants of health," Social Science & Medicine, Elsevier, vol. 111(C), pages 64-73.
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    1. Jozef Salva & Miroslav Vanek & Marián Schwarz & Milada Gajtanska & Peter Tonhauzer & Anna Ďuricová, 2021. "An Assessment of the On-Road Mobile Sources Contribution to Particulate Matter Air Pollution by AERMOD Dispersion Model," Sustainability, MDPI, vol. 13(22), pages 1-23, November.

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