Affiliation:
1. Institute of Science and Environment, University of Saint Joseph, Macau, China
Abstract
Road transportation is a common mode of transport in Macao and is also known to be a significant source of the emission of PM10 and PM2.5 on a local and regional scale. There are six air quality monitoring stations (AQMS) evenly distributed throughout Macao, but some densely populated areas are currently not covered by the monitoring network. Therefore, a monitoring campaign was conducted at four roadside locations in Macao’s most densely populated areas. This work aims to study the concentrations of PM10 and PM2.5 in several roadside locations in Macao. The monitoring campaign was conducted for 24 non-consecutive periods, with a total of 192 monitoring hours. The sampling sites were chosen based on Macao’s most densely populated areas and the most traffic-congested locations. In addition, traffic characterization was performed alongside the monitoring campaign to provide a clearer perspective on the pollution sources. Based on the collected data, a correlation analysis was performed between the number of vehicles and the levels of PM10 and PM2.5 concentration. The results showed a weak relationship between the hourly traffic flow and the level of PM10 and PM2.5 concentrations, with a correlation of determination (R2) of 0.001 to 0.122. In addition, the results showed a weak relationship between the vehicle types and the level of PM10 and PM2.5 concentrations, with an R2 of 0.000 to 0.043. As shown, there is little to no relationship between local traffic volume and roadside PM concentration in the monitored locations of Macao, leading us to conclude that PM concentration is more likely tied to regional sources and meteorological conditions. Nevertheless, the complex geographical setting of Macao is also likely an influential factor in this study.
Subject
Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction
Reference43 articles.
1. Lei, T.M.T., Siu, S.W.I., Monjardino, J., Mendes, L., and Ferreira, F. (2022). Using Machine Learning Methods to Forecast Air Quality: A Case Study in Macao. Atmosphere, 13.
2. WHO (2021). World Health Statistics 2021: Monitoring Health for the SDGs, Sustainable Development Goals, WHO.
3. Effect of Particulate Matter on Human Health, Prevention, and Imaging Using PET or SPECT;Zaheer;Prog. Med. Phys.,2018
4. Lei, M.T., Monjardino, J., Mendes, L., Gonçalves, D., and Ferreira, F. (2020). Statistical Forecast of Pollution Episodes in Macao during National Holiday and COVID-19. Int. J. Environ. Res. Public Health, 17.
5. Chemical Characterization of Roadside PM2.5 and Black Carbon in Macao during a Summer Campaign;Song;Atmos. Pollut. Res.,2014