Characterizations of air pollutants at roadside monitoring stations and traffic emission effects: A case study in Tianjin, China.

To investigate the response of Roadside Monitoring Stations (RSs) to traffic-related air pollution, traffic and pollutant characteristics, influencing factors, and potential source characterization in Tianjin, China were determined based on roadside monitoring of real-world data conducted at RSs in 2022. The diurnal variation trend of pollutants at RSs was consistent with that at the National Monitoring Station (NM), with notably higher pollutant fluctuations during the morning and evening peak traffic times at RSs, where the average diurnal concentration was 41.46 % higher than that at the NM. The generalized additive model (GAM) for nitrogen oxides (NO) and carbon monoxide (CO), responding to the multiple influencing factors, performed well at RSs, with deviance explained by 86.6 % and 61.4 %, respectively. The synergistic effects of wind direction and speed contributed to most of the variations in NO and CO, which were 14.74 % and 12.87 %, respectively. Pollutant concentrations were highest under windless conditions, with pollutants originating primarily from local vehicle emissions. The model results indicated that medium-duty truck (MDT) traffic flow predominantly contributed to the variability in NO emissions, whereas passenger car (PC) traffic flow was the primary source of CO emissions from traffic variables. MDTs should be the focus of urban NO traffic emissions control. Potential-source analysis validated the results obtained from the GAM, and both analyses showed that RSs can better characterize traffic-related air pollutants. Furthermore, more stringent emission standards have effectively mitigated the release of pollutants from motor vehicles and contributed to the modernization of vehicle fleet composition, effectively decreasing CO concentrations.