Aug 2026· Sustainability· Vol 18, pp. 8076· 0 citations· 67 references
Abstract
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.
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.
Yun-Yan-Ze-Yu-Li Chen· Advances in Management and A...· 0 citations
The transport sector has emerged as a significant source of greenhouse gases and airborne pollutants. However, few studies have carried out a comprehensive assessment of the synergistic benefits between air pollutant and carbon emission reductions that account for the unique regional characteristics of individual provinces. In this study, we establish nonlinear prediction models for future activity levels of on-road mobile sources by integrating economic and demographic drivers. We then dynamically quantify the co-benefits of simultaneous air pollutant and CO2 abatement under diverse mitigation scenarios. Environmental tax rates and carbon trading prices are combined with conventional elasticity coefficients and coordinate-based methodologies to convert emission cuts into economic advantages. The results show that under the most optimistic scenario, 47.86% of the CO2 emissions could be mitigated, while emissions of NOX may increase by 60.49% in the absence of mitigation strategies (BAU scenario). Marginal CO2 emissions under the ELC scenario indicates a peak around 2027. Elasticity coefficients for all pollutants gradually converge toward 1, indicating that more stringent mitigation efforts enhance co-benefits. Findings in this study could provide essential insights for the co-management of CO2 and air pollutants from road mobile sources in Guangxi and other key regions along the Belt and Road Initiative.
Yucai Bai, Bei-Bei Yao, Xia-Hong Shi et al.· Sustainability· 0 citations
The coordinated reduction of pollutant and carbon emissions (CRPC) has become a central objective of urban environmental governance. Although smart city construction is primarily intended to advance digital urban transformation, its role in CRPC remains insufficiently understood. Using panel data for 259 prefecture-level cities in China from 2006 to 2022, this study examines whether smart city construction promotes CRPC. Exploiting the staggered rollout of the national smart city pilot policy, we estimate a multi-period difference-in-differences (DID) model to identify the policy effect. The results show that smart city construction significantly reduces both sulfur dioxide emission intensity and carbon emission intensity, indicating a clear CRPC effect. The findings remain robust to parallel-trend tests, placebo tests, propensity score matching, alternative variable specifications, and the inclusion of additional policy controls. Mechanism analyses based on the technology-organization-environment (TOE) framework show that smart city construction promotes CRPC by stimulating green innovation and digital infrastructure development, advancing industrial upgrading and human capital accumulation, and strengthening ecological investment and pollution control capacity. Further analyses indicate that the effect is stronger in cities with more stringent environmental regulation, in growing cities, and in non-resource-based cities. Smart city construction also generates positive spillover effects across geographically proximate and economically connected cities. Overall, the findings show that smart city construction can serve as an important pathway toward integrated pollution and carbon governance.
Yan Bu, Xun Zhang, Yi Wu et al.· Carbon Footprints· 0 citations
Objective: Over the past decades, US policies intended to reduce air pollution emissions from electric generating units (EGUs), mobile sources (e.g., cars and trucks), and port activities have been implemented to improve air quality. This study aimed to estimate and compare counterfactual air pollution concentrations (i.e., concentrations that would have occurred without these policies) to observed concentrations, and then evaluate the health impacts of such policies in New York City, Los Angeles, and Atlanta from 2005 to 2019. Materials and Methods: We obtained data on respiratory emergency department (ED) visits and cardiovascular disease ED visits that result in hospitalizations for the three cities from 2005-2019. Daily concentrations of fine particulate matter (PM2.5), criteria gases [carbon monoxide (CO), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3)], and 1-in-3-day measured concentrations of PM2.5 components and PM sources estimated using positive matrix factorization were acquired from six monitoring sites in the three cities. To estimate health impacts of selected EGU, mobile, and port policies we estimated: 1) counterfactual daily pollutant concentrations at each of the 6 city-sites; 2) associations between daily pollutant concentrations and rates of cardiorespiratory visits using city-site specific multi-pollutant Poisson models; and 3) the percent of cardiorespiratory visits prevented by the implementation of the selected policies, through applying observed and counterfactual concentrations to the fitted health models. Results: Air quality policies were estimated to reduce ambient pollutant concentrations across the three cities, with median PM2.5 reductions of 27%-62% due to all policies combined during 2005-2019. Changes in criteria-pollutant concentrations associated with the selected policies were estimated to avert 7.1% (95% UI: 5.4%, 8.9%) of respiratory visits in New York City, 2.4% (95% UI: 1.4%, 3.4%) in Los Angeles, and 4.5% (95% UI: 0.8%, 8.2%) in Atlanta. In addition, 2.6% (95% UI: 0.9%, 4.2%) and 1.2% (95% UI: 0.3%, 2.1%) of cardiovascular visits were averted in New York City and Los Angeles, while the estimate in Atlanta did not indicate cardiovascular visits averted. Conclusion: The selected EGU, mobile-source, and port policies evaluated during 2005-2019 were estimated to reduce ambient pollutant concentrations and avert respiratory visits in all three cities and cardiovascular visits in New York City and Los Angeles.
H. Zhang, H. Chang, Z. Gao et al.· medRxiv· 0 citations
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 economic and social development of coal resource-exhausted cities (CRECs) depends heavily on coal resources. Measures to improve the carbon emission efficiency (CEE) of CRECs are urgently needed because this development path, characterized by high resource dependence, inevitably generates substantial carbon emissions. However, there has not been much focus on the spatial spillover effects and regional heterogeneity of CEE in these cities. To address this gap, this study selects 37 Chinese CRECs as research subjects. It comprehensively evaluates the static characteristics and dynamic changes in these cities’ CEE from 2011 to 2023 using the SBM-DDF model and the GML index. It then employs the spatial Durbin model to identify key influencing factors of CEE. According to the empirical results, the average CEE of the sample cities did not reach the production frontier, generally remaining at a moderate level and fluctuating. The main factor driving CEE growth for CRECs in all regions is technological progress. CRECs in the western region had the greatest growth in CEE (0.71%), followed by the northeastern (0.36%) and central (0.05%) regions, while the growth in CEE remained unchanged in the eastern region. The local CEE grew by 0.286 units for every unit increase in CEE in neighboring cities, demonstrating the spillover effects essential for regional sustainability. There is significant regional heterogeneity in the influencing factors of CEE in China’s CRECs, necessitating tailored sustainable development strategies.
L. Yu· Sustainability· 0 citations
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