| Citation: | CHEN Z Y,HE C,LI J Q,et al.Inventory and spatiotemporal distribution characteristics of greenhouse gas emissions from vehicles on expressways in Kunming City[J].Journal of Environmental Engineering Technology，2024，14（1）：8-16 doi: 10.12153/j.issn.1674-991X.20230226
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In order to study the emission inventory of greenhouse gases (GHGs) such as CO, CO2, N2O and CH4 from motor vehicles on expressways in Kunming City, the expressway passenger traffic flow data and vehicle GPS information data in Kunming City in 2021 were used to obtain the basic data such as vehicle type composition and vehicle flow on the expressway network. The localized modified MOVES model was applied to calculate the emission factors of CO, CO2, N2O and CH4 of vehicles on the expressways. Based on the actual traffic flow data, GHG emission factors and the actual road information of expressways, the GHG emission inventory of the expressways in Kunming City was constructed, and its emission characteristics and spatial distribution characteristics were analyzed. The results showed that the emissions of CO, CO2, N2O and CH4 from expressway vehicles in Kunming City in 2021 were 20 337.1, 2 575 677.1, 33.8 and 72.9 t, respectively, with a total CO2 equivalent of 2 626 212.5 t. According to emission standards, the vehicles with national stage Ⅳ emission standards were the main contributors to the four types of GHG emissions. According to vehicle types, passenger cars were the main contribution models to CO, CO2 and N2O emissions, while large buses were the main contribution models to CH4 emissions. Divided by fuel type, gasoline vehicles were the main contribution models of CO, CO2 and N2O, while diesel vehicles were the main contribution models of CH4 emission. The temporal distribution characteristics showed that the emission intensity had a positive correlation with the traffic flow in different time periods, and the GHG emission intensity of motor vehicles on expressways in Kunming City showed a "bimodal" change within 24 h. The spatial distribution of emission intensity was closely related to road network density and regional traffic flow. The region with higher road network density and higher traffic flow had higher emission intensity.
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