Search Results (331)

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. Full article

Tourism is carbon-intensive, with transport and mobility driving much of its greenhouse-gas emissions, yet destination-level evidence on carbon hotspots and decarbonization from a supply-chain perspective remains scarce, especially in developing regions. This study examines low-carbon tourism supply chain management in seven purposively selected provinces of Northeastern Thailand (Isan) using a qualitative-dominant convergent mixed-methods design that integrates demand- and supply-side evidence. A visitor survey yielded 74 open-ended responses (60 complete questionnaires), alongside seven semi-structured key-informant interviews with tourism supply chain operators across the seven provinces. Quantitative data were analyzed with descriptive statistics, and qualitative data with thematic analysis using qualitative data analysis software, drawing on code-frequency and co-occurrence analysis; the two strands were triangulated in joint displays. Visitors reported moderate satisfaction (grand mean 3.91 on a five-point scale) but rated environmental management and safety lowest, engaging with sustainability through visible service cues rather than emissions. Key informants identified perceived carbon hotspots, carrying capacity, and seasonality as dominant concerns, attributing the destination’s footprint chiefly to transport dependence (informant-reported estimates ranging from approximately 80% to nearly 100% private-car arrivals, amid limited public transport) and accommodation energy; these hotspots reflect stakeholder perceptions rather than measured emissions, as no carbon accounting, environmentally extended input–output analysis, or life-cycle assessment was conducted. Integration revealed a demand–supply perception gap and five proposed, interdependent low-carbon pathways: coordinated mobility, accommodation energy efficiency, strengthened local procurement, carrying-capacity and waste management, and multi-stakeholder governance. The findings offer a developing-region, supply-chain-oriented basis for future tourism decarbonization research and practice. Full article

Proximity-based urban models, including the widely discussed 15 min city, aim to bring everyday destinations within a short walk, cycle, or shared-mobility trip, with promising benefits for well-being, public health, local economies, and low-carbon mobility. While the appeal of proximity is widely shared, far less is known about how to deliver and govern such neighbourhoods so that these benefits are realised, durable, and embraced by residents across the full range of their mobility needs. Implementation, public acceptance, and governance therefore remain comparatively under-examined. This article contributes an enabling governance approach for proximity-based, accessible neighbourhoods, centred on co-creation and on a rich, attractive menu of mobility options. Through a cross-disciplinary synthesis organised by the CalmMobility paradigm, a governance-posture lens that emphasises co-creation, sequencing, and readiness, it integrates evidence on proximity, accessibility, active travel, shared mobility, well-being, and low-carbon outcomes. The article argues that proximity and shared mobility widen the range of convenient and attractive options for everyday trips, and that this supports health, quality of life, and lower emissions. It also argues that these benefits are more likely to last under calm, co-created governance, which builds good options first and respects the freedom of residents to choose among all modes, including the car. To put the paradigm to work, the study introduces the Governance Compass and applies it to Paris, Barcelona, and Melbourne. The Compass was applied through a qualitative document analysis carried out by one analyst. It is offered as an exploratory tool that aims to make the reasoning open to inspection, not as a validated measuring instrument. Results are reported as ordinal bands, from Absent to Exemplary, and a 0 to 100 index is kept only as an illustration. The three cases show different patterns. In Paris and in the early Barcelona work, the documents set ambitious proximity goals but say much less about how change is paced, how residents shape it, and how choice is preserved, and these dimensions fall in the lower bands. In Melbourne, whose programme is still a pilot, the pattern is the reverse. The process dimensions are stronger there, but proximity itself is less developed. These bands describe the documents examined, not a fixed ranking of the three cities. Positioned as a constructive complement to the proximity-city agenda rather than a critique of it, the article closes with a cross-disciplinary research agenda spanning planning, transport, public health, and policy. Full article

Environmental protection has become a key priority for the Chinese government. This study examined the symmetric complementarity of spatial layouts between inter-city high-speed rail and urban subway systems. Their co-location formed a structurally symmetric low-carbon travel chain that bridged long-distance and short-distance trips. The study evaluated their joint effect on urban carbon productivity within a difference-in-differences framework. The baseline two-way fixed-effects DID estimate showed that the simultaneous operation of HSR and subway systems significantly improved urban carbon productivity, with an average increase of approximately 10.51% in treated cities relative to non-treated ones. This core finding remained qualitatively robust across a series of tests, including conditional coarsened exact matching (CEM), placebo simulations, sample exclusions, and decomposition of joint effects relative to individual rail impacts. Complementary nonparametric causal forest estimates yielded smaller but still significant effect sizes, providing supportive evidence for causal validity under weaker functional form assumptions. Heterogeneity analysis based on dynamic GDP grouping revealed that high-GDP cities experienced stronger emission reductions, while low-GDP cities benefited more from the economic growth dimension of carbon productivity. Empirical patterns aligned with the theoretical prediction of the transportation substitution mechanism. The positive effect of dual rail availability on carbon productivity was stronger in cities with higher private car stock, as shown by double machine learning interaction models. This finding only provided indirect evidence and did not constitute direct proof of actual modal shift behavior. The results exhibited magnitude asymmetry between parametric and nonparametric methods, yet all estimates consistently pointed to a positive qualitative direction. This consistency revealed directional symmetry in the causal conclusion. The study contributed by (1) examining the combined carbon productivity effect of co-located HSR and subway systems, (2) identifying the moderating role of private car stock in the transportation substitution mechanism, (3) revealing development-stage-based heterogeneity, (4) and combining machine learning methods with parametric causal inference as complementary robustness evidence. Policy implications suggested that high-GDP cities should prioritize expanding dual rail coverage and optimizing connections to amplify emission reductions, while low-GDP cities should focus on improving HSR connectivity with existing public transit systems and fostering low-carbon industrial development in line with local conditions. Full article

Urban areas, where diverse human activities take place, generate significant amounts of carbon dioxide. This study proposes a simplified method for estimating the reduction effects of carbon dioxide emissions from passenger transportation resulting from compact city measures, which are expected to contribute to reducing emissions in urban areas. In particular, this study contributes by introducing a distance-band-based estimation framework, enabling scenario-based analysis with reduced data requirements while retaining key spatial characteristics. This method enables planners to quickly assess whether the required CO₂ reduction levels can be achieved under given policy settings, thereby supporting evidence-based policy formulation. As an example of how this method could be applied in the policy formulation stage, it was applied to Toyohashi City, which faces the challenge of car dependency, a common problem in many regional cities. It was demonstrated that the scenario assuming the achievement of the targets for land use and transport measures outlined in municipal plans from 2022 to 2050 could reduce carbon dioxide emissions by over 40%. This research supports integrated consideration of urban and transportation measures at the planning and policy formulation stages, contributing to highlighting pathways toward sustainable urban development aimed at achieving carbon neutrality. Full article

Vehicles with electrified powertrains carry the promise of significant reductions in greenhouse gas (GHG) emissions from a lifecycle analysis (LCA) standpoint compared to conventional internal combustion engine (CICE) vehicles. However, trade-offs exist between different types of electrified powertrains in terms of cost, consumer acceptance, and GHG reduction efficacy for different operating conditions. The open-source tool CarGHG was developed with an aim to enable the exploration of a plethora of parametric study scenarios, including the cost of electrification technologies, different driving patterns and charging habits, and the cost and carbon intensity of electricity and fuel blends. This paper introduces the framework of CarGHG, then showcases total cost of ownership (TCO) and LCA GHG results for select models of light-duty vehicles. Another capability of CarGHG, which is the ability to estimate the performance of “virtual” vehicle models (perceived vehicle design specifications not yet on the market), is utilized to explore future scenarios of electrification and low-carbon fuel blends for Small Sports Utility Vehicles (SUVs), a popular light-duty vehicle segment in North America. With opportunities, but also uncertainties, in future scenarios, it is likely wise to continue pursuing multiple ways towards the reduction of LCA GHG. Full article

The expansion of the European Union Emissions Trading System to road transport and buildings (ETS2) raises significant concerns regarding the distributive social impacts of carbon pricing on vulnerable households, particularly in regions characterized by high car dependency, limited public transport accessibility, and pronounced territorial inequalities. This paper aims to develop an integrated conceptual framework for analyzing transport poverty in the context of ETS2 and the just climate transition. The study adopts a conceptual–analytical approach based on a structured literature review of peer-reviewed publications and EU policy documents, combined with a qualitative policy analysis focused on Bulgaria as a critical case. The paper identifies six interacting analytical dimensions of transport poverty—economic vulnerability, spatial vulnerability, mobility dependency, infrastructure vulnerability, climate-policy exposure, and social vulnerability—and maps the causal pathways through which carbon pricing mechanisms may intensify mobility deprivation, particularly among low-income, rural, and forced-car-ownership households. The analysis demonstrates that ETS2 may exacerbate existing socio-spatial inequalities unless accompanied by well-designed compensatory, accessibility-oriented, and territorially sensitive policy measures. The Bulgarian case illustrates the specific structural risk factors prevalent in Central and Eastern European countries. The paper contributes to the emerging academic literature on transport poverty by positioning it as a critical dimension of the just climate transition and by providing a conceptual foundation for future empirical research within the ACTETS2 project framework. Full article

Rapid economic development has led to a growing reliance on private car commuting, making the mitigation of carbon dioxide (CO₂) pollution along road environments critical for the health of nearby residents. Road greening serves as an ecological barrier between traffic emissions and adjacent residential areas, and its effectiveness in reducing local CO₂ pollution has been widely studied. However, the influence of different spatial morphologies of road greening on the distribution of CO₂ around buildings remains underexplored. In this study, we developed a numerical simulation model to investigate CO₂ dispersion on building surfaces under various road greening spatial configurations. Simulation results indicate that a “tree–shrub–grass” composite configuration significantly reduces CO₂ concentrations around buildings. These findings provide practical guidance for optimizing vegetation spatial layouts in high-density road networks and contribute to the global pursuit of carbon peak and carbon neutrality goals. Full article

Chang Moi Subdistrict is in Chiang Mai Province, Thailand. It is a subdistrict characterized by cultural heritage and everyday community life. The study pursued three objectives: (1) to explore the tourism context of Chang Moi together with tourist attitudes and behaviors; (2) to develop creative tourism routes and evaluate their carbon implications; and (3) to propose appropriate routes and activities for low-carbon creative tourism development. A mixed-method design was employed, comprising qualitative interviews with key stakeholders, a quantitative tourist survey (n = 408), route development, an LCA-informed greenhouse gas assessment, route testing, and synthesis of findings. Three representative route programs were developed: a one-day walking route for international tourists, a one-day private-car route for Thai tourists, and a two-day mixed route. The carbon-footprint results showed that the one-day routes generated substantially lower greenhouse gas emissions (Program 1 = 10.58 kg CO₂ eq; Program 2 = 10.82 kg CO₂ eq) than the two-day overnight route (Program 3 = 31.52 kg CO₂ eq). Waste management was the largest contributor in the one-day routes, whereas Program 3 showed a more distributed emission profile across waste management, creative activities, food and beverage services, and accommodation. Among the assessed activities, flower arranging generated the highest carbon footprint. Overall, the findings indicate that low-carbon creative tourism development in Chang Moi should emphasize compact and walkable route structures, lower-impact creative activities, sustainability-oriented interpretation, and community-based implementation. The study provides an evidence-based basis for tourism planning in Chang Moi and offers implications for other compact creative districts pursuing low-carbon tourism transition. Full article

The intensifying climate problem requires substantial decarbonisation in the energy, industry, and transportation sectors, with hydrogen recognised as a crucial energy carrier. The increase in global energy consumption, driven by population growth and industrialisation, challenges the constraints of fossil fuel resources and their detrimental impact on CO₂ levels. Hydrogen, noted for its high energy density and versatility in generating power from both fossil and renewable sources, acts as a crucial supplement to direct electrification. Currently, worldwide hydrogen production exceeds 100 million tonnes per year, predominantly in the form of “grey hydrogen,” which significantly contributes to CO₂ emissions without the use of carbon capture systems. This analysis comprehensively assesses hydrogen’s contribution to decarbonisation, encompassing the entire value chain: production methods, storage options (compressed gas, liquid hydrogen, and complex hydrides), transportation techniques (pipelines, cars, rail, and ammonia carriers), and various uses. Key performance parameters indicate trade-offs concerning energy density, storage, production expenses, and transportation alternatives. Notwithstanding advancements in hydrogen technologies, obstacles persist, encompassing energy penalties, infrastructural requirements, and safety issues. This evaluation highlights the need for coordinated policies and investment to enhance hydrogen’s adaptability, ensuring alignment with direct electrification policies to achieve net-zero emissions by 2050. Full article

The electrification of public transport, particularly Bus Rapid Transits (BRT), is a significant step toward achieving sustainable urban mobility and reducing dependency on fossil fuels. However, rapid adoption of Electric Vehicles Smart Charging (EVSC) infrastructure presents grid stability, economic and environmental concerns. The rising demand for electric cars, particularly in developing nations such as Nigeria, highlights the urgent need for a sustainable hybrid renewable energy charging infrastructure for BRT systems. This study presents a techno-economic assessment of an off-grid hybrid systems that use photovoltaic (PV), wind turbines (WTs), hydrogen (H₂), fuel cell (FC) and battery technologies to power Electric Vehicles Smart Charging within Bus Rapid Transits networks. The Lagos BRT charging system at City Mall Station (CMS) serves as a case study, with hourly renewable resources obtained from National Aeronautics and Space Administration database (NASA). Using the HOMER pro-optimization tool, a multi-criteria analysis is performed to evaluate system viability, with special focus on key metrics such as levelized cost of energy (LCOE), net present cost (NPC), renewable energy fraction (REF), and greenhouse gas (GHG) emissions. The simulation results demonstrate that the hybrid PV/wind/FC/battery configuration is exceptionally economical, with an LCOE as low as $0.222/kWh, $2.03M NPC, 51.3% REF, and 159,209 kg of carbon dioxide emissions per year compared to grid-dependent charging. The study shows that integrated renewable-hydrogen systems are not only financially feasible, but also provide significant insights for policymakers, transportation authorities, and energy planners seeking to accelerate the transition to green public transportation infrastructure through innovative hybrid energy schemes. Full article

In urban areas, where car congestion is increasing daily, improving traffic-signal control is a key area of study that directly affects people’s quality of life. It is expected that such improvement will reduce environmental traffic load and increase mobility. However, the inability to determine traffic load deterministically complicates the problem. Multi-agent reinforcement-learning approaches provide a solution thanks to their adaptive learning capabilities from instantaneous data. This study evaluates the Multi-Agent Deep Q-Network (MADQN) algorithm and the QMIX value decomposition method (QMIX) in an urban traffic network with 16 signalized intersections, comparing them with Fixed-Time and Max-Pressure. Experiments were conducted under three vehicle-density levels within the same network geometry and phase-matching rules. Performance was evaluated using waiting time, travel time, speed, efficiency, carbon dioxide (CO₂) emissions, time to collision below 1 s (TTC < 1 s), and post-encroachment time below 1 s (PET < 1 s).. In all demand scenarios, both reinforcement-learning controllers achieved successful results. MADQN consistently provided lower average waiting times, whereas QMIX consistently achieved higher efficiency and, in some settings, lower CO₂ and lower cross-seed variation. No statistical superiority between MADQN and QMIX was established. Overall, the results support the value of adaptive control in this test environment and indicate trade-offs among efficiency, emissions, and proxy safety. Full article

This study develops a comprehensive carbon footprint assessment model that integrates forward and reverse logistics to evaluate and compare greenhouse gas emissions from online and offline apparel sales channels in China, with a particular focus on high return rates. The model quantifies emissions from transportation, packaging, storage, and operations, incorporating return and exchange logistics. The system boundary is limited to enterprise-controllable sales-phase activities and excludes consumer travel. Three sales models are compared: factory-to-consumer (F2C), traditional business-to-consumer (B2C) e-commerce, and brick-and-mortar retail (BMR). Within this defined boundary, BMR exhibits the lowest carbon footprint (0.296 kg CO₂e/item), followed by F2C (0.408 kg CO₂e/item) and B2C (0.602 kg CO₂e/item). Packaging dominates online emissions (55–57%), whereas store operations are the main contributor to offline emissions (43%). Return rates are identified as a decisive factor, accounting for over 31% of e-commerce emissions and potentially increasing them by 171.3% under extreme scenarios. Sensitivity analysis reveals that trunk line distance (factory to warehouse) has a greater impact on emissions than last-mile return route optimization. Relocating the factory closer to consumers reduces B2C transport emissions by 72.3%, whereas replacing conventional packaging with recycled plastic reduces total B2C emissions by 46.0%. These findings provide channel-specific sustainability strategies: return reduction and packaging innovation for online channels, and energy efficiency improvements for physical stores. These results are conditional on the defined system boundary. If consumer travel by private car were included, the relative advantage of offline channels would diminish or could reverse. Full article

Curbside saturation in dense commercial corridors compromises the sustainability of last mile logistics. This study investigates the impact of “authorized but non functional occupancy” (Class S (Service)), referring to service and tradespeople vehicles, on the operational capacity of loading and unloading zones (LUZ). Based on direct field observations of 474 real vehicle entries in a zone in Zaragoza (Spain), an Erlang B no wait queuing model (M/M/1/1) using weighted occupancy time was applied to contrast current saturation levels with a regulated functional scenario. The results demonstrate that the infrastructure is structurally sufficient: removing inefficient uses reduces traffic intensity from 1.31 to 0.48 Erlangs, increasing service potential by 121.84%. Class S was identified as consuming 36.62% of the lost capacity, exceeding the impact of unauthorized private cars. Total Hidden Carbon Emissions (HCE) amounted to 45.34 kg CO₂, establishing an environmental impact of 0.066 kg CO₂ per misused linear meter. The study concludes that proper utilization of loading zones is sufficient to accommodate logistics demand and effectively reduce CO₂ emissions. Full article

Distributed integrated energy systems embedding biomass combined heat and power (BCHP) have the potential to enhance energy supply reliability in rural areas and to support the low-carbon transformation. However, the sources and transmission paths of car-bon emissions remain difficult to quantify due to the multi-energy coupling and diverse conversion processes. To address these issues, this study develops a carbon flow tracking and scheduling strategy for BCHP-integrated distributed energy systems. First, a bio-chemical reaction process model for BCHP is established to enable a life cycle-based carbon emission accounting. Second, the flexible heat-to-power ratio characteristics of BCHP are considered to more accurately reflect multi-energy coupling under varying operating conditions. Third, a dual-objective optimal scheduling model is constructed by combining node carbon potential with operating costs, enabling the system to simultaneously minimize operating costs and carbon emissions. A case study of an integrated energy system in Anping County, Hebei Province, demonstrates that the proposed method reduces total carbon emissions by over 9.8%, increases renewable energy utilization by 15.2%, and lowers operating costs by 7.5%. The results reveal the carbon flow characteristics and emission reduction potential of rural distributed integrated energy systems embedding BCHP, providing methodological support and empirical evidence for refined low-carbon governance. Full article