Evaluation and Prediction of PM10 and PM2.5 from Road Source Emissions in Kuala Lumpur City Centre

Autor: Mohd Talib Latif, Kadaruddin Aiyub, Anis Asma Ahmad Mohtar, Matthias Ketzel, Nor Diana Abdul Halim, Azliyana Azhari
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Sustainability, Vol 13, Iss 5402, p 5402 (2021)
Azhari, A, Halim, N D A, Mohtar, A A A, Aiyub, K, Latif, M T & Ketzel, M 2021, ' Evaluation and Prediction of PM10 and PM2.5 from Road Source Emissions in Kuala Lumpur City Centre ', MDPI .
Sustainability
Volume 13
Issue 10
Aarhus University
Azhari, A, Halim, N D A, Mohtar, A A A, Aiyub, K, Latif, M T & Ketzel, M 2021, ' Evaluation and prediction of PM 10 and PM 2.5 from road source emissions in Kuala Lumpur city centre ', Sustainability (Switzerland), vol. 13, no. 10, 5402 . https://doi.org/10.3390/su13105402
ISSN: 2071-1050
DOI: 10.3390/su13105402
Popis: 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 PM10 and PM2.5 in Kuala Lumpur city centre. The OML-Highway model calculates hourly time series of PM10 and PM2.5 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 PM10 and PM2.5 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 PM10 and PM2.5 during BAU runs were in the ranges 41.4–65.9 µg/m3 and 30.4–43.7 µg/m3 respectively, compared to during the 30% traffic reduction run ranging at 40.5–59.5 µg/m3 and 29.9–40.3 µg/m3 respectively. The average concentration of PM10 and PM2.5 at the Continuous Air Quality Monitoring Station (CAQMS) was 36.4 µg/m3 and 28.2 µg/m3 respectively. Strong correlations were observed between the predicted and observed data for PM10 and PM2.5 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.
Databáze: OpenAIRE