Proposal of policies based on temporal-spatial dynamic characteristics and co-benefits of CO 2 and air pollutants from vehicles in Shanghai, China.

In megacities, vehicle emissions face urgent challenges related to air pollution and CO ₂ control. To achieve the refinement of vehicle control policies for the co-control of air pollutants and CO ₂ , this study established a vehicle emission inventory with high spatial and temporal resolution based on the hourly traffic flow in Shanghai and analyzed the spatial and temporal distribution characteristics of the real-time vehicle emissions. Meanwhile, a policy evaluation framework was constructed by combining pollutant emission predictions with quantitative co-control effect assessments. The results indicated that spatio-temporal variations in different air pollutants and CO ₂ could mainly be attributed to primary contributing vehicle types. The pollutants (CO ₂ , CO and VOCs) primarily contributed by private cars exhibited a bimodal pattern in 24-h time series and their spatial distribution was concentrated in the urban city center. The spatial distribution of NOx and PM primarily contributed by heavy trucks was still obvious on non-urban center areas. Furthermore, the results of synergistic effect analysis revealed that the alternative energy replacement scenario demonstrated the most significant potential for the co-control. Based on temporal-spatial and co-benefit analysis, the precise control policy of vehicle emissions can be established through time-, region-, and model-control. This study provides references and research methods for the formulation of the vehicle refinement control policies in worldwide megacities.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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