Comparative analysis of drive-cycles, speed limit violations, and emissions in two cities: Toronto and Beijing

Traffic costs of air pollution: the effect of PM2.5 on traffic violation

Although emerging studies have investigated the effect of air pollution on traffic crashes, it is unclear to scholars whether air pollution affects another road safety problem-traffic violations. To address this gap, the current paper constructs a data set from 1,390,221 traffic violation records of 640,971 drivers from the Wuhan Traffic Management Bureau between January 2018 and December 2018. An ordered logistic regression was conducted to verify our hypotheses. The result shows that PM_2.5 has no overall impact on the severity of traffic violations, but each 1% increase in the daily concentration of PM_2.5 leads to a 1.02-fold increase in the odds of serious inexperience-related violations and a 0.99-fold decrease in the odds of serious overconfidence-related violations. This effect is the strongest in PM_2.5, followed by NO₂, and has not been observed in CO and O₃. In addition, robustness tests indicate that the relationship between air pollution and traffic violations is consistent among the different subsets (e.g., clear weather, no rain and snow, and good visibility). We also provide valuable practical advice for drivers and traffic authorities.

Optimal Speed Model of Urban Underwater Tunnel Based on CO2 Emissions Factor

This study aims to reduce air pollution caused by vehicle emissions in confined spaces and realize low-carbon travel in urban underwater tunnels. Based on the MEET (Methodologies for Estimating Air Pollutant Emissions from Transport) and COPERT (Computer Programme to Calculate Emissions from Road Transport) models, combined with real vehicle test data, an urban underwater tunnel speed–CO2 emissions factor model was constructed. Results show that: Different working conditions have a great impact on the MEET model; load and slope factors expand the actual CO2 emissions factor, which is different from the actual situation. The CO2 emissions factor in the COPERT model is negatively correlated with the speed, and there are fewer variables in the model, so the parameters are more controllable and more in line with the actual situation. According to the vehicle gasoline consumption and taking CO2, i > GC as the judgment index, the optimal limit speed of the ramp is calculated to be 40 km/h, while the main line maintains the existing state of 60 km/h. The model is simple and easy to operate, can be applied to estimate vehicle CO2 emissions factor at underwater tunnels in other cities, providing a basis for traffic management and effectively realizing low-carbon travel.