Modelling ambient vehicle emissions in Zamdela using AERMOD

Abstract

Road transport has become a part of our daily lives in a highly urbanised and globalised world. With the increase in vehicle ownership over the years, on-road emissions are expected to increase. With the growing informal public transportation in poor, disadvantaged areas, it is difficult to keep track of these ever-growing numbers. This is a substantial environmental concern considering that vehicle emissions are synonymous with air pollution. Part of the challenges is the research gap identified in studies focusing solely on the contribution of vehicle emissions to ambient air quality. This results from incompetent emissions laws, lack of vehicle emissions control, and limited monitoring stations to monitor emissions consistently. The gap in knowledge and findings can be solved by incorporating ambient measuring and modelling methods. Developing a representative emissions inventory is one of the most efficient methods to assess and manage vehicle emissions. Estimated emission rates provide information on the activity rate to identify potential sources of concern within a geographic area. Henceforth data from the monitoring station, traffic fleet data and emissions factor are needed to calculate the estimations. The data is an essential input in Gaussian dispersion models. This study makes use of AERMOD to assess the contribution of PM emissions. AERMOD is an atmospheric regulatory model approved by the EPA and DEA as an essential tool in air quality assessment. The model is used to determine the dispersion of atmospheric pollutants under the influence of meteorology. Assessing the concentration and dispersion of linear pollution, such as road paths, is recommended. This study aims to characterise the contribution of vehicle emissions in Zamdela using AERMOD. This study will characterise ambient PM concentrations from 2019- 2021, quantify emissions by developing and emissions inventory and finally use the input data to model the ambient concentrations using AERMOD. The results depict that PM is a pollutant of concern in Zamdela, with regular NAAQS exceedances recorded. Temporal variability concentrations show that two peaks in the morning from 06h00-09h00 and evening from 16h00-20h00 were recorded. Both peaks coincide with domestic solid fuel combustion and vehicular emissions. The source apportionment analysis and traffic count data correlate with the monitored PM concentrations to prove that vehicle emissions are one of the sources of the poor ambient air quality in Zamdela. Emissions from vehicles are often ignored, with a considerable research gap identified on this ground-level source within low-income settlements. Henceforth an emissions inventory per vehicle classification was developed. Sedans are assessed as having a significantly higher contribution to ambient PM than the other vehicle classes. This is a consequence of the increasing ownership of private transport driven by poor public transport in low-income settlements. LDVs also showed a significant contribution, followed by mini-buses. Thereof, AERMOD was run from 2019-2021 to assess PM concentrations per vehicle classification for both PM10 and PM2.5. The predicted annual and daily PM10 concentrations are below the NAAQS annual (40 μg/m3) and daily (75 μg/m3) standard across the township. The modelled isopleths show a range between of 0.07 μg/m3 - 6.78 μg/m3 for the annual average and 0.99 μg/m3 - 38.3 μg/m3 daily average. The modelled annual PM2.5 attributed to vehicle emissions are between 0.1 μg/m3 - 12.1 μg/m3 which complies with the annual 20 μg/m3 NAAQS standards. The daily average range from 23 μg/m3 – 237 μg/m3 and exceeds the 40 μg/m3 standards over most of the township. On extreme days, daily averages can range from 40 μg/m3 – 237 μg/m3. The modelled results compared to the monitored results prove that vehicle emissions are one of the sources contributing to the recorded PM exceedances in Zamdela. It is essential to highlight that domestic fuel combustion morning and evening PM peak hours coincide with traffic emission peaks. Both sources can be identified as pollutants of concern in Zamdela.