Search Results (348)

This study evaluates the influence of different crushed gneiss contents on the mechanical, durability, environmental, and economic performance of sand–gravel/gneiss mixtures for sustainable road construction. Natural sand–gravel aggregate was blended with crushed gneiss at three proportions (10%, 30%, and 50% by mass). The experimental program included grain size analysis, compaction characteristics, California Bearing Ratio (CBR), deformation modulus, and freeze–thaw durability tests. Environmental performance was assessed using a cradle-to-site carbon footprint approach based on Life Cycle Assessment principles according to ISO 14040, ISO 14044, and ISO 14067, with the analysis focused on Global Warming Potential (GWP100), combined with a Total Cost of Ownership analysis. Increasing gneiss content improved mechanical performance, with CBR increasing from 45% to 95% and deformation modulus from 110 to 185 MPa. The 70/30 sand–gravel/gneiss mixture provided the most balanced performance among the investigated compositions, combining high bearing capacity, satisfactory freeze–thaw resistance, and favorable environmental and economic characteristics. Its carbon footprint was 3.90 kg CO₂ eq./t, with diesel consumption during aggregate handling identified as the dominant emission source (69%), followed by gneiss transportation (20%) and electricity consumption (12%). Higher gneiss contents and longer transport distances increased environmental impacts and production costs. The results indicate that selecting an appropriate aggregate composition and reducing transport-related emissions can support lower-carbon construction materials while maintaining required engineering performance. Full article

The building and public works sector is a major source of greenhouse gas emissions in developing countries due to the high material intensity of infrastructure and the dependence on imported materials. In Burkina Faso, as in most African countries, environmental assessments remain limited by the lack of locally representative emission factors, creating uncertainty in carbon accounting. This study estimates emission factors for key construction materials in Burkina Faso using a simplified cradle-to-gate Life Cycle Assessment (LCA) adapted to national technical, energy, and logistical conditions. The materials analyzed include cement, steel, flat glass, aluminium, aggregates, sand, timber, ceramic tiles, paint, bitumen, and asphalt mixes. The results reveal significant variations in the carbon intensity of construction materials in the Burkina Faso context. Aluminium exhibits the highest emission factor (12.804 tCO₂/t), followed by paint (2.50 tCO₂/t), steel (1.970 tCO₂/t), Portland cement (1.060 tCO₂/t), ceramic tiles (0.99 tCO₂/t), flat glass (0.84 tCO₂/t), bitumen (0.628 tCO₂/t), asphalt mixes (0.130 tCO₂/t), timber (0.16 tCO₂/t), aggregates (0.008 tCO₂/t), and sand (0.0013 tCO₂/t). Portland cement exhibits a slightly higher emission factor than the values commonly reported in the literature (0.85–0.95 tCO₂/t), while steel, aluminium, flat glass, ceramic tiles, bitumen, asphalt mixes, timber, and paint remain within internationally reported ranges. In contrast, sand exhibits a slightly lower emission factor than typical literature values, reflecting its limited processing requirements. Aggregates and sand show the lowest emission factors due to minimal industrial processing and greater local availability. These differences are mainly driven by import dependence, long- distance maritime and road transportation, the characteristics of the national electricity mix, and local production conditions. The study supports the development of context-specific carbon assessments and environmental databases for Burkina Faso and other West African countries. Full article

Urban transport emissions are a major contributor to climate change and urban air pollution. Although previous studies have demonstrated that traffic demand, fleet electrification, and driving behavior individually influence vehicular emissions, their combined effects under different congestion conditions remain insufficiently understood. This study investigates the interactions among these factors using the microscopic traffic simulator SUMO (Simulation of Urban MObility). A synthetic urban corridor consisting of five signalized intersections was developed to represent arterial roads in medium-sized cities. A full factorial experimental design was implemented by considering three traffic demand levels, three electric vehicle adoption percentage levels, and three driving behavior profiles, resulting in 27 experimental scenarios with 10 stochastic replications per scenario. Traffic performance and pollutant emissions were evaluated to quantify both the individual and interaction effects of the experimental factors. The results indicate that traffic demand is the primary determinant of CO₂ and NO_x emissions, while fleet electrification substantially reduces emissions, particularly under congested conditions. Driving behavior also plays a role by influencing acceleration and deceleration patterns. Furthermore, statistically significant interaction effects among the experimental factors ($p<0.05$) reveal the benefits of fleet electrification considering the traffic demand and the driving behavior. These findings contribute to the understanding of sustainable urban mobility by providing a comprehensive assessment of how traffic demand, fleet electrification, and driving behavior jointly influence urban traffic performance and vehicle emissions, offering valuable insights for the design of integrated transportation and environmental policies. Full article

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

Maritime transport entered the EU Emissions Trading System (EU ETS) in 2024, turning a route’s carbon performance into an economic variable. Existing studies examine this on established routes; the case for a new (greenfield) short-sea corridor under the post-2024 regime remains unaddressed, particularly in the under-served south-eastern Baltic. This study proposes a transparent, transferable methodology linking multi-criteria route selection, a lane-metre demand model, a speed-dependent fuel-consumption model and a consignment-level modal-shift carbon balance, applied to a prospective Gdynia–Liepāja Ro-Pax connection (148 nautical miles). At high deck utilization, each freight unit shifted from the 850 km road alternative avoids roughly 300–380 kg of CO₂ (a 44–55% reduction), because a short-sea leg replaces a long road haul rather than because the ferry is cleaner per tonne-kilometre. The benefit is conditional: the corridor is climate-beneficial only above a break-even freight-deck occupancy of about 45% at design speed, falling to about 34% under slow steaming. Across the demand scenarios (about 17,900–35,900 units per year), it avoids on the order of 10,000–13,400 t of CO₂ annually under high demand, while under low demand the annual balance ranges from a small net increase at design speed to a modest saving under slow steaming. The corridor relieves the congested Suwałki Gap and aligns with smart-port enablers, providing a replicable decision tool for operators and port authorities. Full article

As road transport is a major contributor to anthropogenic CO₂ emissions, the importance of sustainable mobility planning and fleet management becomes very clear. Therefore, this article proposes a physics-based mathematical framework for dynamic estimation of CO₂ emissions. The proposed framework is very flexible and enables CO₂ assessment for different types of vehicles (i.e., combustion engine and electric vehicles), traffic and operating conditions. The proposed software prototype is evaluated through representative urban and peri-urban simulation scenarios. These scenarios involve conventional public transport, private vehicles, and demand-responsive ride-hailing services. The simulation results show that vehicle occupancy is one of the main factors impacting specific CO₂ emissions. In this context, in low-passenger-demand and dispersed travel conditions, demand-responsive mobility services can achieve lower emissions per passenger-kilometer than conventional public transport. In contrast, when occupancy levels are sufficiently high, public transport remains the most efficient option. These results indicate that there is no universally optimal transport mode and that emission efficiency is the result of a matching between vehicle capacity and passenger demand. Therefore, the proposed framework delivers a transparent and practical decision-support tool for transport mobility services. Full article

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., PM_2.5 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 PM_2.5 concentrations, translating to an average annual abatement of approximately 707,008 tons of CO₂ and a 2.204 μg/m³ drop in PM_2.5 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. Full article

This paper systematically reviews the applications of artificial intelligence (AI)-driven practices in road freight transport (RFT) decarbonisation. RFT scenarios are becoming increasingly complex, and the deep decarbonisation challenge is still severe. AI-driven practices are regarded as a transformative frontier and a key path to addressing them. However, related research is mainly confined to a single disciplinary background, which may hinder the field from making substantial progress in designing diverse solutions and exploring collaborative decarbonisation mechanisms in multiple transportation stages. This review conducts bibliometric analysis and science mapping on 227 articles, following the SPAR-4-SLR protocol. The performance analysis reveals exponential growth in publications over the past decade, especially in the past 3 years. Bibliographic coupling identifies eight knowledge clusters including powertrain energy management, strategic fleet electrification, intermodal corridor planning, and physics-informed co-optimisation, collectively evidencing a field-wide transition from isolated vehicle-level efficiency gains toward system-integrated decarbonisation architectures. Cross-cluster analysis exposes structural integration gaps at the boundaries of mature clusters, from which stage-specific future research opportunities are proposed across different RFT phases. The findings argue that consequential advances will arise from coupling AI-driven demand forecasting, powertrain control, and emission accounting into end-to-end collaborative optimisation frameworks, rather than from continued single-technology refinement. Full article

Low-emission zones, known in Poland as clean transport zones, grant or deny access according to a vehicle’s Euro standard, age and fuel. These administrative labels, however, are only loosely connected to what an internal combustion engine (ICE) actually emits on the road. The founding assumption of a Euro-based zone is that the Euro stage is a usable proxy for the mass a vehicle emits, so admitting newer classes lowers the fleet emission inventory, the activity-weighted sum of class emission factors defined as the product of fleet frequency, in-zone activity and emission factor. This paper tests that assumption directly. A paradox follows: a newer, compliant, large and heavy vehicle can release more carbon dioxide (CO₂), nitrogen oxides (NOx) and particulate matter (PM) than an older, smaller vehicle that the same rule turns away. We develop a reproducible emission-accounting framework that pairs real-world emission factors, resolved by Euro standard, fuel, engine displacement and mass, with a mass-dependent treatment of non-exhaust particles. Given the number of petrol, diesel, liquefied-petroleum-gas (LPG) and electric vehicles in a fleet and the areas of the city and the zone, the model returns daily emissions and their density per square kilometre before and after a rule is applied. For a fleet parameterised on Polish statistics, the Warsaw and Kraków criterion removes about 80% of zone NOx, because the oldest vehicles are also the high-NOx diesels; the same rule, however, removes only about 40% of CO₂ and 48% of PM, and it shifts the admitted fleet toward heavier vehicles that produce more non-exhaust PM. Emission-based, fuel-based and hybrid criteria deliver larger and fairer reductions at the same level of stringency. Aligning zone access with real combustion emissions is therefore both more effective and more equitable, and it supports the wider goals of sustainable, low-carbon urban mobility. Full article

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 NO_X 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. Full article

Transport decarbonization cannot rely exclusively on electrification, particularly in regions where charging infrastructure, vehicle affordability, and fleet renewal remain constrained. This review critically assesses advanced bioethanol as a complementary transition fuel for road transportation, integrating evidence on lignocellulosic and residual biomass conversion, ethanol–gasoline blend behavior in spark-ignition (SI) engines, regulated and unregulated emissions, life cycle assessment (LCA), and scalability barriers. A critical narrative and integrative approach were applied, using literature retrieved from Scopus and Web of Science and organized across production pathways, engine performance, environmental impacts, technological challenges, and Latin American deployment conditions. The evidence indicates that advanced bioethanol can valorize agricultural and agro-industrial residues, reduce fossil-carbon dependence, and lower carbon monoxide (CO) and unburned hydrocarbon (HC) emissions in suitable SI engines. However, large-scale implementation remains strongly influenced by pretreatment performance and enzymatic hydrolysis efficiency, together with feedstock logistics, fermentation robustness, ethanol recovery energy demand, and overall biorefinery economics. Life-cycle performance remains pathway-dependent, with potential trade-offs in land use, water demand, toxicity, acidification, and eutrophication. Overall, advanced bioethanol should be understood as a realistic short- to medium-term complement to electrification rather than a universal carbon-neutral solution. Full article

This study quantifies, based on real-world operational measurements, the energy intensity and greenhouse gas emissions of selected vehicle types in rail and road freight transport on the Brno–Břeclav corridor. Measurements were conducted on several generations of electric locomotives, one upgraded diesel locomotive, and two heavy road freight vehicle combinations. Energy flows were converted to a common basis, and both energy intensity and greenhouse gas emissions were assessed on a well-to-wheel (WTW) basis. Unlike many previous studies, this research focuses on a comparison of specific, currently operated vehicles rather than on an aggregated comparison of transport modes. The results reveal substantial differences not only between rail and road freight transport, but also within rail traction itself, where pronounced differences were identified among individual locomotive generations. At the same time, they confirm that, even when diesel traction is used, rail freight transport remains more energy-efficient and exhibits lower greenhouse gas emissions than heavy road freight vehicle combinations, both per gross and per net tonne-kilometre. Overall, the findings indicate that the environmental performance of freight transport is determined not only by the transport mode itself, but also by vehicle technology, traction type, and the structure of transport performance. Full article

The transport sector contributes significantly to greenhouse gases and airborne pollutants. This study focuses on the co-benefits related to decreases in air pollutants and CO₂ emissions under various mitigation scenarios. The associated mitigations in PM_2.5 concentrations are predicted by establishing a random forest (RF) model and the health benefits are evaluated with the global exposure mortality model (GEMM). Environmental tax values and carbon trading prices are integrated alongside traditional elasticity coefficients and coordinate-based approaches to transform reductions into economic advantages. The results indicate that in the most favorable scenario (ELC), CO₂ emissions are expected to peak in 2032 with a reduction of 51.71%; this is supported by the marginal CO₂ emission curve, which intersects the zero axis around that same year, while the air pollution equivalents (APeq) are projected to decline by 25.65% in 2050. The efficiency of synergistic reductions between air pollutants and CO₂ ranks as SO₂ > NO_X > CO > HC > PM_2.5 > PM₁₀, and the elasticity coefficients for all pollutants are gradually aligning toward 1, suggesting that stricter mitigation efforts will enhance co-benefits. Furthermore, the economic benefits attributable to CO₂ reduction are anticipated to be 10.81 billion CNY by 2050, and 17,297 premature deaths associated with PM_2.5 exposure could be prevented. The findings in this study could provide essential insights for the co-management of CO₂ and air pollutants from road mobile sources. Full article

Reducing carbon emissions from highway construction is vital for mitigating climate change. Based on an expressway project in central China, this study conducted a fine-grained CO₂ emission accounting and analysis. The findings reveal that bridges and culverts rank first in emissions among all subprojects, emerging as a “carbon hotspot” with an exceptionally high emission intensity, followed by subgrade and pavement. Additionally, traffic safety facilities, accounting for 6.40% of total emissions, are also not negligible. Regarding emission sources, material emissions exhibit an extreme dominance at 89.44%, whereas off-road machinery and transport vehicles demonstrate distinct patterns of input-emission asymmetry and single-vehicle-type dominance, respectively. Consequently, this study delineates decarbonization pathways, quantitatively verifies the low-carbon efficacy of four mitigation technologies, and focuses on evaluating the environmental-economic dual feasibility of substituting core equipment with pure electric alternatives. The results demonstrate that the resin-bonded gravel sound barrier achieves an emission reduction rate of 73.26%; furthermore, under a 50% penetration rate, deploying 30-ton class EV dump trucks can cut transportation emissions by 9.98%, maintaining exceptional financial resilience even under a 30% plunge in diesel prices. This study provides a replicable, scientific decision-making basis for the deep decarbonization of the transportation infrastructure sector. Full article

The role of internal combustion engines in future transport systems is expected to remain central, particularly in hard-to-abate sectors such as heavy-duty road transport and maritime applications. However, their decarbonization requires the adoption of low-carbon and renewable fuels. This review examines hydrogen, methane-based fuels, methanol, and ethanol for internal combustion engine applications using a pathway-based approach that integrates life-cycle assessment, technology readiness level, commercial readiness level, and engine-related considerations. The reviewed literature shows that the environmental performance of these fuels varies strongly depending on feedstock, production pathway, process configuration, and energy source. From a Well-to-Tank perspective, hydrogen pathways exhibit particularly large variability, ranging from around 3 gCO₂eq/MJ for wind-based electrolysis to around 230 g CO₂eq/MJ for coal gasification. Methane-based fuels range from around 16 gCO₂eq/MJ for fossil compressed and liquefied natural gas to negative values for waste- and manure-based biomethane. Methanol and ethanol also show substantial variability, with renewable, waste-derived, and bio-based pathways generally offering substantially lower life-cycle greenhouse gas (GHG) emissions than fossil-based routes. In the use phase, Tank-to-Wheel analysis shows that energy demand remains relatively similar across fuels, while differences in direct emissions are mainly related to fuel carbon content and other GHG species such as ${\mathrm{CH}}_4$ or ${\mathrm{H}}_2$ slip and combustion-related species such as ${\mathrm{N}}_2\mathrm{O}$. The Well-to-Wheel comparison for heavy-duty applications highlights that upstream fuel production pathways strongly influence overall performance, while use-phase contributions play a secondary role and mainly affect the final ranking when upstream emissions are comparable. Overall, the review shows that pathway selection is more influential than fuel identity itself, highlighting that effective decarbonization strategies should focus on pathway design and upstream fuel production rather than on fuel categories alone, and that renewable and bio-based pathways offer the greatest potential for achieving very low or near-zero life-cycle GHG emissions in internal combustion engine applications. Full article