Synergy Between Air Pollution and Carbon Emissions of On-Road Mobile Sources, Evidence from a Typical Southwestern Region in China

Policy Pathways for Coordinated CO2 and Air Pollutant Reductions in Urban Road Transport: A Case Study of Zhengzhou, China

Urban road transport policies must simultaneously address climate mitigation, local air quality, and the infrastructure requirements associated with vehicle electrification. However, these dimensions are rarely evaluated within a unified city-level framework. This study develops an integrated assessment framework that combines a bottom-up co-source inventory of CO2 and seven air pollutants, Long-range Energy Alternatives Planning (LEAP)-based scenario modeling, policy contribution analysis, elasticity-based co-benefit assessment, and electric vehicle charging demand estimation for Zhengzhou, China. In 2022, the road transport sector consumed 10,178 ktce of energy and emitted 27.8 Mt of CO2. Private cars contributed 66.7% of CO2 emissions, whereas heavy- and medium-duty trucks and light-duty trucks contributed 48.1% and 27.9% of NOx emissions, respectively, collectively accounting for 76.0% of the total. Under the existing policy scenario (EPS), CO2 emissions increase to 45 Mt in 2030 and 55 Mt in 2040. Under the dual carbon scenario (DCS), emissions peak at approximately 36 Mt in 2030 and decline to 32 Mt by 2040, representing reductions of 20% and 42% relative to the EPS, respectively. Electric vehicle promotion and green transport development contribute 42% and 32% of peak-year CO2 mitigation. Policy effectiveness differs across emission types. Electric vehicle promotion and green public transport are relatively more effective for CO2 mitigation, whereas old vehicle retirement, motorcycle phase-out, light-truck electrification, and tighter emission standards provide greater air pollutant reduction benefits. Supporting an electric vehicle stock of approximately 1.22 million in 2030 would require about 610,000 charging piles at a vehicle-to-charger ratio of 2:1. The principal contribution of this study is to demonstrate how complementary vehicle technology, transport structure, emission control, power sector, and infrastructure policies can be combined to support city-level carbon peaking and air pollution co-control.

The Impact of Pilot Policies for New Energy Vehicles on Pollutant Emissions in Prefecture-level Cities

Against the backdrop of the "Dual Carbon" goals, transportation electrification serves as a critical low-carbon technical pathway to optimize urban energy structures and cut mobile-source air pollution. To quantitatively assess the environmental techno-economic performance of new energy vehicle (NEV) pilot promotion policies, this paper adopts panel data of 282 prefecture-level and above cities in China from 2014 to 2024, and conducts empirical estimation via the PSM-DID model, transmission pathway test, and multi-dimensional heterogeneity grouping. The results indicate that NEV pilot policies can significantly reduce urban PM₂.₅ and NOₓ emission levels, and the net policy effect remains robust after parallel trend and placebo tests. NEV ownership acts as the core transmission carrier of emission reduction dividends, with the substitution of fuel vehicles contributing 48.91% of total emission cuts. The emission reduction performance of the policies presents prominent differentiation across spatial location, city scale and industrial structure, where megacities, eastern cities and service-dominated cities achieve better low-carbon technology penetration effects. Such disparities stem from unbalanced local supporting policies, charging infrastructure and industrial market foundations. From a techno-economic optimization perspective, differentiated promotion schemes are proposed to provide quantitative support for local governments to formulate targeted NEV support policies and advance collaborative pollution reduction in the transportation sector. Keywords: New energy vehicles, Pilot policy, Pollutant emission reduction, PSM-DID, Low-carbon techno-economy, Prefecture-level panel.

Smart Highway Pilots, Carbon Emissions, and Air Pollution: Evidence from China

The digitalization and intelligent transformation of transportation have emerged as technological solutions for enhancing traffic efficiency and reducing traffic-related pollutants. However, existing studies primarily focus on traditional traffic emission reduction measures, and there is limited empirical evidence demonstrating how the digitization and intelligence of road infrastructure can reduce carbon dioxide emissions and air pollutants. To address this research gap, this study employed a difference-in-differences methodology to investigate the causal effects of the Smart Highways Pilot (SHP) policy on carbon emission intensity (i.e., CO2 emissions per unit of GDP) and air pollution (i.e., PM2.5 concentrations), using data from 272 Chinese cities spanning 2012 to 2023. Our estimation results demonstrate that the implementation of the SHP policy led to an average reduction of about 4.7% in CO2 emissions per unit of GDP and a 5.1% decrease in PM2.5 concentrations, translating to an average annual abatement of approximately 707,008 tons of CO2 and a 2.204 μg/m3 drop in PM2.5 concentrations among the sample pilot cities. Furthermore, the carbon reduction and pollution mitigation effects of the SHP policy were more pronounced in regions emphasizing pilot themes, such as infrastructure digitalization and vehicle–road collaboration, cities promoting new-energy vehicles, and eastern regions. This study provides robust causal evidence for policymakers to assess the synergistic carbon abatement and pollution reduction benefits of SHP policies, while contributing to the literature on smart transportation and sustainable development, and offering valuable insights for other countries and regions on building green, low-carbon transportation systems through the digitalization and intelligent upgrading of road infrastructure.

Carbon Emissions and Their Impact on Ecosystem Services: A Comprehensive Study

Carbon dioxide (CO 2 ) emissions have emerged as a major driver of environmental degradation, particularly in rapidly industrializing economies such as China. This study examines the relationship between sectoral CO 2 emissions and key ecosystem services, including carbon sequestration, water yield, and biodiversity. However, existing studies have rarely integrated long‐term emission datasets with spatial ecosystem service modeling to examine sector‐specific and regional variations in ecological impacts. CO 2 emission data from the Our World in Data database (1960–2023) are integrated with ecosystem service simulations generated using the InVEST (Integrated Valuation of Ecosystem Services and Trade‐offs) model. The analysis applies statistical techniques, including Pearson correlation, regression analysis, and GIS‐based spatial analysis, to evaluate the relationship between emission sources and ecosystem service dynamics across regions in China. The study focuses on major emission sectors such as coal, cement, oil, and gas, with particular attention to high‐emission provinces including Hebei and Shandong, and ecological restoration regions such as the Three‐North Shelter Forest. The findings indicate that coal‐based emissions constitute the largest share of national CO 2 emissions and are strongly associated with declines in carbon sequestration, water yield, and biodiversity indicators. Spatial analysis further reveals substantial regional disparities in ecological impacts between industrial and afforestation regions. Scenario simulations suggest that a 50% reduction in emissions could significantly enhance ecosystem service recovery, including improvements in carbon sequestration and biodiversity levels. The study provides a spatially explicit framework for understanding emission–ecosystem interactions and offers insights to support region‐specific environmental policy and sustainable development strategies.

Marginal Abatement Costs and Pollution–Carbon Co-Governance in Sustainable Urban Transitions: Evidence from the Yangtze River Delta

Urban agglomerations concentrate activities that generate both PM2.5 pollution and carbon emissions, but the economic basis for governing them jointly remains unclear. Taking the Yangtze River Delta as a case, this study evaluates pollution–carbon co-governance from a marginal abatement cost (MAC) perspective. Using panel data for 41 cities from 2011 to 2023, we estimate shadow prices and MACs under joint and single-objective abatement scenarios with a non-radial directional distance function dual model. We then construct carbon-reduction and pollution-reduction cost-saving effects, classify synergy types, and examine their temporal, spatial, and nonlinear transition patterns. The results show that joint abatement generally lowers the MACs of both carbon mitigation and PM2.5 reduction, with stronger cost-saving on the pollution side. Under the baseline classification, the share of balanced synergy increases over time, and the balanced state shows high persistence in Markov transitions. Core cities show weaker measured cost-saving effects, which may reflect limited remaining low-cost co-abatement potential rather than weak governance. Semiparametric evidence further indicates that industrial upgrading, openness, and urbanization are nonlinearly associated with MACs and synergy balance. These findings suggest that urban pollution–carbon coordination should be guided by local cost structures and development stages.

[Assessment and Scenario Prediction of Pollution-carbon Reduction Synergies Toward Dual Carbon Goals in Shanxi Province].