The Relationship between Roadside PM Concentration and Traffic Characterization: A Case Study in Macao

Thomas M. T. Lei () and Martin F. C. Ma
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Thomas M. T. Lei: Institute of Science and Environment, University of Saint Joseph, Macau, China
Martin F. C. Ma: Institute of Science and Environment, University of Saint Joseph, Macau, China

Sustainability, 2023, vol. 15, issue 14, 1-14

Abstract: Road transportation is a common mode of transport in Macao and is also known to be a significant source of the emission of PM 10 and PM 2.5 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 PM 10 and PM 2.5 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 PM 10 and PM 2.5 concentration. The results showed a weak relationship between the hourly traffic flow and the level of PM 10 and PM 2.5 concentrations, with a correlation of determination (R 2 ) of 0.001 to 0.122. In addition, the results showed a weak relationship between the vehicle types and the level of PM 10 and PM 2.5 concentrations, with an R 2 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.

Keywords: air quality; air pollution; particulate matter; monitoring campaign; traffic characterization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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