Modeling the effects of speed limit cameras (SLCs) on air quality and traffic flow on access-controlled highways

Abstract

The impact of speed limit cameras (SLCs) on speed limit enforcement and traffic safety has long been studied. However, the effects of SLCs on air quality have not been thoroughly investigated due to the lack of data at sites where both air quality and traffic flow measurements (such as speed and volume) are monitored in close proximity to SLCs. This study aims to quantify the effect of SLCs on air quality and traffic flow parameters on access-controlled highways using linear regression models (LRM) and generalized additive models (GAM). The latter allows the modeling of nonlinear functional relationships between the predictor and outcome variables. We collected experimental data, including traffic flow parameters, weather conditions, and air pollutants (CO, CO2, NO2, SO2, and VOC), on high-volume, high-speed access-controlled highways in the wider metropolitan area of Dammam, Saudi Arabia. Key parameters related to traffic, such as volume, speed, percentage of heavy-duty vehicles (HDV), and percentage of traffic exceeding the speed limit, were used to estimate air pollutant generation from vehicular exhaust emissions near highway locations. Our analysis of the collected data revealed that locations with SLCs showed higher adherence to the speed limit of 120 km/h. The 85th percentile speed at these sites was approximately 114 km/h, which was 11 percent lower than that at the no-camera sites. Additionally, field data demonstrated a significant reduction in CO and SO2 emissions at the camera locations by approximately 23.7 and 20.3 percent, respectively. However, at these locations, the CO2, NO2, and VOC gas concentrations increased slightly, ranging from 1.5 to 4.9 percent. The predictive capabilities of the GAMs for gas emissions were higher than those of the LRMs, except for CO2 emissions. The GAM results identified optimal speed values between 110 km/h and 130 km/h to minimize vehicle emissions. Furthermore, the GAM results indicated that SLC locations had significantly lower concentrations of exhaust gas emissions for CO, SO2, and VOC, but higher levels of CO2 and NO2 gases. Thus, the field data and GAM results were in agreement for all gases except VOC. These findings have implications for shaping environmental transportation policies and guidelines, highlighting the multifaceted impact of SLCs on both traffic behavior and air quality.