Model development and integrated analysis of the impact of traffic emissions on air quality in urban areas in Jakarta, Indonesia

• Main Author: Suhadi, Dollaris Riauaty
• Format: Thesis
• Language: English; English
• Published: 2007
• Online Access: http://psasir.upm.edu.my/id/eprint/4768/1/FPAS_2007_9A.pdf; http://psasir.upm.edu.my/id/eprint/4768/
• Institution: Universiti Putra Malaysia

This research aims to assess air quality status in the urban area of Jakarta and evaluate the effect of traffic emissions control of selected air pollutants by employing a Gaussian-plume dispersion model developed in Delphi. Sources of air pollutants were divided into point, line, and area sources representing three contributing sectors, i.e. industry, transport, and household. Input data for the model was obtained from the government statistics and industrial and traffic surveys conducted in other previous studies. Improvement of the model run-time was done by developing a parallel implementation coded in a data-parallel approach. The dispersion model performed reasonably in estimating the concentrations of SO2 and NOx. Testing of the model resulted in the relative standard errors of estimates of below 50% indicating the model could be reproducible. However, the simulation of PM10 concentration resulted in underestimation. The cause for this was the exclusion of other significant sources of PM10 beside three contributing source categories under study. Prediction of future emissions using the 2002 emission data and socio-economic factors which affect air quality revealed that the emissions of SO2, NOx, and PM10 would increase by a factor of 1.64, 1.48, and 1.64, respectively in 2010 if control of the pollutants emissions was not taken. Similarly, simulation of future air quality under business-as-usual scenario resulted in increased pollutant concentrations. The number of grids exceeding the annual NOx ambient standard in 2010 was twice the number of grids exceeding the standard in 2002. Under the scenario with control measures, the concentrations of pollutants, particularly the transport-contributed PM10 were reduced by 44%. The reduction of PM10 concentration was a result of simulated implementation of vehicle inspection and maintenance. Updating the emissions inventory to include other pollutant contributing sources, and continued improvement of the dispersion model to fit the best conditions of the urban area are suggested.