Dispersion of PM₁₀ from industrial and road transportation network emissions in the Klang Valley, Malaysia

• Main Author: Jamalani, Mohd Asrul
• Format: Thesis
• Language: English
• Published: 2019
• Subjects: Neural networks; Colloids - Analysis
• Online Access: http://psasir.upm.edu.my/id/eprint/84448/1/FPAS%202019%208%20-%20ir.pdf; http://psasir.upm.edu.my/id/eprint/84448/

Particulate matter (PM₁₀) has been the major concern due to their negative impact to the environment, human health and spatial planning for greener environment. In order to have better understanding on the issues, three main objectives were stated in this study. Firstly, was to determine the airborne PM₁₀ emission inventory from the local sources. Secondly, was to correlate the meteorological conditions resulted from meteorological modelling towards the study area. Lastly, to validate the obtained concentration thematic map from the integration modelling approach. The Department of Environment (DOE) reported that almost half of the total PM₁₀ emission load in Malaysia were contributed by the vehicular and industrial activities. Therefore, the initiative was taken decades ago to monitor the ambient air quality with proper recording. However, Malaysia still lack of pollutant emission inventory due to limitation on expertise. Therefore, this study initiatively collects the information to execute the PM₁₀ emission inventory from the best available resources. In general, the air pollutants dispersed freely without knowing the direction and magnitude of the pollutants. Therefore, the Regional Air Quality Model (RAQM) was used to correlate the calculated emission with the meteorological conditions forming the PM₁₀ concentration thematic map. Thus, this modelling approach could address the unmonitored area between the DOE monitoring stations with providing the PM₁₀ concentration information. The preliminary study on the localised air quality status was conducted by the descriptive statistical and ANOVA analysis. Then, the modelling part were initiated with the calculation of the PM₁₀ emission from two main sources consist of the industrial and road transportation network emission. In the end producing the emission inventory file to fulfil the first objective. This emission inventory was processed and converted into gridded emission profile by the application of the Sparse Matrix Operator Kernal Emission (SMOKE) model. To achieve the second objective, the gridded meteorological profile was produced from the Fifth Generation Mesoscale (MM5) model. Community Multiscale Air Quality (CMAQ) model as the chemical transport modelling system was able to simulate the PM₁₀ concentration thematic map. Thus, the integration process between the models create an integrated SMOKE-MM5-CMAQ model under similar gridding system namely known as the RAQM for achieving the third objective. The emission inventory showed higher contribution of PM₁₀ emissions in industrial source rather than road transportation network. Whilst, the MM5 model showed positive result in correlating the meteorological conditions. Thus, the integrated modelling system was able to interpolate the PM₁₀ concentration thematic map for every location in the domain. However, the obtained concentration was extremely low due to the limitation on the primary input of the emission. This study only considered the generalised industrial area basis and the average on-road vehicles’ travel distance emissions from land use map and vehicles statistic, respectively as the input. Besides, the presence of the fugitive elements was being underestimated which contributed to the huge uncertainties in the study. A comprehensive study on determining the fugitive elements in the future is necessary for the emission input improvement in gaining a convincing PM₁₀ concentration information.