Search Results (1,136)

Increasing surface albedo can reduce absorbed solar radiation and generate negative radiative forcing, but its application to landfill covers remains insufficiently investigated. This study assessed the potential climate benefit of reflective cover systems at the Malagrotta landfill in Rome, Italy, by integrating unmanned aerial vehicle (UAV) radiometry, Sentinel-2 imagery, shortwave-radiation modeling, and CO₂-equivalence methods. The existing landfill exhibited low and heterogeneous reflectance. Quality-controlled Sentinel-2 observations produced seasonal mean albedos ranging from 0.0819 in winter to 0.1236 in summer, with a radiation-weighted baseline albedo of 0.1091. UAV campaign means ranged from 0.1391 to 0.2145. Comparisons over common 20 m cells showed that Sentinel-2 underestimated UAV albedo by approximately 0.087 on average (RMSE ≈ 0.093), demonstrating that the two platforms should not be considered interchangeable without site-specific calibration. Five hypothetical reflective-cover scenarios with albedos of 0.55–0.75 were subsequently evaluated. Relative to the existing surface, annual absorbed shortwave energy decreased from 1481.1 kWh m⁻² to 748.1–415.6 kWh m⁻², equivalent to reductions of 49.5–71.9%. After accounting for modeled atmospheric transmission, avoided absorbed energy at the top of the atmosphere ranged from 487.4 to 708.9 kWh m⁻² yr⁻¹. Under a three-year material service life, the modeled compensation was 71.49–103.98 kg CO₂-eq m⁻² over a three-year assessment horizon. Alternative literature-based conversion methods yielded landfill-scale estimates of approximately 31,700–142,000 tCO₂-eq, highlighting substantial methodological uncertainty. The findings indicate that reflective landfill covers could provide a meaningful supplementary climate benefit on low-albedo, centrally managed surfaces. However, the results are scenario-based and represent radiative equivalence rather than physical CO₂ removal or avoided methane emissions. Field trials, multiyear monitoring, complete surface-energy-balance measurements, and cradle-to-grave life-cycle assessment are required before operational deployment or carbon-offset applications. Full article

A key challenge in port–road logistics is the need to align operational priorities with efficient and sustainable freight transportation decisions. This study develops an Analytic Hierarchy Process (AHP)-based decision-support system for the Multi-Objective Electric Vehicle Routing Problem (MOEVRP) in port–road logistics. Initially, the AHP method is used to determine the relative importance of cost-efficient route planning, vehicle and port management, environmental impact management, energy efficiency, and operational efficiency and well-being based on expert judgment. Next, the resulting priority weights are then used to inform the decision-making framework for the MOEVRP, which determines routing decisions by minimizing total cost, carbon emissions, and maximum vehicle working time while accounting for electric vehicle constraints and charging behavior. This issue is critical in rapidly developing industrial corridors such as Thailand’s Eastern Economic Corridor, where growing freight demand, energy constraints, and environmental pressures must be managed simultaneously. By linking port–road operational priorities with the routing model, the proposed framework provides a structured approach for evaluating trade-offs between economic, environmental, and operational considerations during the transition toward low-carbon freight transportation. A case study in Chonburi–Rayong provinces demonstrates the applicability of the integrated system in a real-world maritime–land logistics corridor. The findings contribute to the design of more sustainable supply chain systems that support renewable and decarbonized logistics. Full article

Against the backdrop of the coordinated advancement of the dual carbon goals and new-type urbanization, the traditional high-carbon development model has become a major constraint on urban green transformation. As a critical vehicle for digital technologies to empower low-carbon governance, smart cities have yet to receive a systematic evaluation of their long-term policy effects based on quasi-natural experiments. Using panel data from 280 prefecture-level cities from 2003 to 2023, this study takes the smart city pilot policy as a quasi-natural experiment. It adopts Interpretive Structural Modeling (ISM) to identify the key influencing factors and transmission paths of carbon emissions, and employs the progressive difference-in-differences (DID) model to assess the carbon emission reduction effects, dynamic evolutionary characteristics and urban heterogeneity of smart city construction. Furthermore, the mediation effect model is applied to clarify its underlying mechanisms. The empirical results show that smart city construction significantly curbs urban carbon emissions, and this finding remains valid after a series of robustness tests, including the parallel trend test, placebo test and PSM-DID. The emission reduction effect of the policy exhibits an obvious time lag: the effect is insignificant in the first and second years after policy implementation but turns significantly negative and continues to strengthen starting from the third year. Noticeable urban heterogeneity is also observed, with a more prominent emission reduction effect in eastern regions, central cities with high administrative ranks and large-sized cities. Mechanism analysis reveals that the conventional industrial pollution reduction pathway does not serve as the primary transmission channel. Instead, a suppression effect is identified, suggesting that smart cities achieve carbon abatement primarily through the digital empowerment of energy allocation efficiency—a pathway distinct from traditional end-of-pipe governance approaches. Unlike previous studies, this study combines ISM with a staggered DID framework to reveal the dynamic effects and transmission mechanisms of smart city policies. Full article

Dairy cold-chain network planning requires coordinated decisions under demand variability, product perishability, and environmental constraints. To address these interrelated challenges, this study formulates an order-driven multi-objective mixed-integer nonlinear programming (MINLP) model for the tactical planning of a three-echelon dairy cold-chain network. The model coordinates distribution-center selection, inventory, transportation allocation, vehicle configuration, and refrigeration decisions to minimize total cost, transportation-related carbon emissions, and the quantity- and importance-weighted average freshness-loss rate. Demand variability is represented through service-level-based safe demand, whereas product freshness is evaluated using Weibull-based shelf-life reliability and inventory–transportation exposure. Transportation congestion is further incorporated to capture its effects on travel time, refrigeration emissions, and freshness deterioration. NSGA-II is employed to generate Pareto solutions, with entropy-weighted TOPSIS used for compromise-solution selection and MOEA/D serving as the benchmark algorithm. Numerical results indicate that NSGA-II achieves favorable convergence performance and comparable solution diversity relative to MOEA/D, while small-scale mixed-integer approximation tests support the quality of the obtained solutions. Multi-scale experiments demonstrate stable computational performance as network size increases. Sensitivity and scenario analyses further reveal distinct effects of service levels, shelf-life characteristics, and road capacity on economic, environmental, and freshness performance. The proposed framework provides tactical decision support for coordinating demand-responsive supply, low-carbon operations, and freshness preservation in dairy cold-chain networks. Full article

As electromobility reduces tailpipe emissions, regulatory focus, including the upcoming Euro-7 standard, shifts to non-exhaust emissions (NEEs). Brake wear particulate matter (PM) significantly contributes to urban pollution and severe health risks. This Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) for Scoping Reviews (ScRs) compliantly reviews systematically mapped research on brake dust generation, measurement methodologies, and mitigation strategies. Following a literature search across Scopus, Web of Science, and EBSCOhost for English and German publications, 125 studies were extracted using the AI tool Elicit and manually verified. The synthesis indicates that coarse particles (PM₁₀ and PM_2.5) originate primarily from mechanical abrasion and tribo-oxidation, while ultrafine particles (UFPs) form via thermal decomposition of organic binders at critical temperature thresholds. For quantification, enclosed inertia dynamometers with constant volume sampling (CVS) show clear convergence as the standard. Effective mitigation includes wear-resistant hard coatings, low-emission pad formulations, active on-board filtration, and enclosed drum or encapsulated wet brakes. Furthermore, regenerative braking in electric vehicles (EVs) can reduce particulate emissions by up to 95% under standardized driving cycles or optimal operating conditions. Despite these advancements, knowledge gaps remain. Future research must prioritize standardizing real-world on-road measurement protocols, enabling wet braking concepts for automotive applications by addressing drag losses and performance limits, and developing and validating coupled predictive models as a basis for future digital twins to design zero-emission braking architectures. Full article

Last-mile delivery routing requires simultaneous control of distance, travel time, service deadlines, vehicle capacity, workload balance, operating cost, emissions, and uncertainty. This study provides a controlled low-budget comparison of ten classical metaheuristics for a LaDe-calibrated stochastic CVRPTW. The GA, DE, PSO, ACO, ABC, SA, GWO, WOA, TLBO, and JAYA used the same random-key representation, capacity-aware split decoder, repair rules, CRN scenarios, and exactly 50 objective evaluations per run. The experiment comprised 1065 fixed design conditions, 30 seeded runs per algorithm-condition cell, and 319,500 metaheuristic runs, with NNS, Clarke–Wright Savings, and OR-Tools Guided Local Search as benchmarks. PSO achieved the lowest grand-mean weighted logistics cost, whereas the WOA achieved the lowest median and best Friedman mean rank. The grand-mean difference between the WOA and PSO was only 125.2 objective units, and the context winner changed across the three cities and five customer-size levels (PSO: 4, WOA: 2, and JAYA: 2). Accordingly, corrected p-values are treated as conditional design diagnostics, while practical interpretation prioritises paired magnitude, stratified consistency, feasibility, and benchmark proximity. A design-stratified sensitivity analysis showed that the preferred method changed across cities and customer sizes. Crucially, every metaheuristic and benchmark recorded 0% full feasibility under the common evaluator; capacity- and lateness-violation profiles are therefore elevated to primary outcomes, and no algorithm is claimed to be operationally superior. The 50-evaluation protocol is interpreted as an early-budget screening regime rather than evidence of asymptotic convergence. The results show that algorithm choice is conditional on the tested data, weights, problem sizes, uncertainty settings, and evaluation budget and that feasibility-preserving decoding is more important for deployment than small differences in penalised objective value. Full article

The growing penetration of renewable energy sources introduces significant uncertainties into integrated energy systems (IESs). Conventional single-timescale management strategies, typically designed for static power balance, fail to address the symmetry of source-load uncertainties arising from both supply and demand sides. To address this challenge, this paper proposes a multi-timescale optimal scheduling framework that integrates demand response (DR) and multi-energy flow coupling. The framework adopts a hierarchical progressive strategy across day-ahead, intra-day, and real-time stages. The day-ahead stage optimizes the economic baseline with an hourly resolution. The intra-day stage conducts rolling correction at 15 min intervals to activate slow-response equipment flexibility, boosting combined heat and power (CHP) generation by 40.70% and increasing waste-heat cooling consumption by 41.12%. The real-time stage employs energy storage at 5 min resolution to suppress fluctuations, maintaining electricity, heat, and cooling load deviations, respectively, at remarkably low levels of 0.17%, 0.10%, and 0.06%. Comparative results show that with power-to-gas (P2G) integration, the system purchases off-peak electricity for synthetic natural gas production, cutting gas procurement costs by 12.70% and reducing net carbon emissions from 5.14 t to 4.91 t. DR mechanisms enable a gas–electricity substitution strategy that lowers electricity purchase costs by 9.97%, reduces evening peak electric vehicle (EV) charging load by 8.32%, and decreases charging expenses by 15%. Full article

In recent years, traditional cast-in-place concrete construction for pre-drilling engineering in unconventional natural gas fields has generated large amounts of waste concrete, consumed significant resources, and prolonged project schedules. To address these issues, this study proposes a prefabricated pavement slab system as a green and low-carbon alternative. Based on vehicle load surveys at shale-gas well sites in southwestern China, three loading conditions (design, overload, and ultimate axle loads) were defined. Theoretical calculations were then performed for reinforcement design, crack-width control, and local bearing capacity verification. A full-scale precast slab (3000 × 1495 × 150 mm) was fabricated and tested under static monotonic loading to measure deflection, crack development, steel strain, and concrete strain until failure. Separately, a three-dimensional finite element model of a four-panel pavement system (including a mortar-leveling layer and soil subgrade) was developed in ANSYS to simulate static and, preliminarily, moving loads. The experimental slab reached an ultimate load of about 365 kN (based on a single specimen, and thus not statistically representative), with ductile bending failure and crack/deflection patterns typical of reinforced concrete. The numerical model reproduced the cracking load and peak capacity with deviations below 17% from the test data, though post-cracking deflections were underestimated. Overall, the results demonstrate that the proposed prefabricated system is structurally feasible for heavy-duty drilling sites. It enables factory production, rapid on-site assembly, and reuse after dismantling, thereby reducing construction waste, shortening timelines, and supporting energy conservation and emission-reduction goals in the context of China’s green building policies. Full article

Selecting three-way catalysts (TWCs) solely from precious-metal loading or a single light-off metric may not reflect the broad operating domain encountered by plug-in hybrid electric vehicles (PHEVs). This study linked bench-scale conversion characteristics of three aged, Pt-free Pd-Rh formulations to cycle-level emissions. The formulations represented a low-loading baseline (TWC-1), a proportional increase in Pd and Rh (TWC-2), and a higher-loading Pd-rich strategy (TWC-3). Light-off, temperature–space-velocity, and λ-sweep data were incorporated into coupled vehicle, engine-out emission, catalyst thermal, and aftertreatment models for Worldwide Harmonized Light Vehicle Test Cycle (WLTC) and Real-driving Emission (RDE) evaluation. The formulation ranking varied with the test boundary. At 30,000 h⁻¹, TWC-3 exhibited the lowest CO light-off temperatures, whereas TWC-2 achieved the lowest T50 values for C₃H₆ and NO. At 50,000 h⁻¹ with its corresponding inlet composition, TWC-2 produced the lowest T50 and T90 values for all three species. Across the broader operating domain, TWC-1 deteriorated most when lower temperature coincided with higher space velocity, while the higher-loading Pd-rich strategy provided no consistent advantage for C₃H₆ or NO conversion. The WLTC emphasized light-off and intermediate-temperature activity, whereas the predominantly hot RDE profile included space velocities above 200,000 h⁻¹. Relative to TWC-3, TWC-2 reduced predicted TWC-out CO and NO_x emissions by 10.0% and 4.1% over the WLTC and by 36.4% and 18.8% over the RDE profile, respectively, while producing the lowest cycle-integrated THC emissions. These results demonstrate that the highest precious-metal loading does not necessarily provide the best cycle-level emission control. Linking formulation-specific conversion characteristics with cycle-dependent operating-domain distributions provides a more representative basis for TWC selection than a single light-off metric. Full article

Metro feeder activity is commonly summarized by trip counts, although equal counts can correspond to different occupied distances and emissions. Using occupied taxi-trip records from 19 days in June 2023 at six purposively selected peripheral stations on Lanzhou Metro Line 1, this study links directional feeder activity, occupied distance, occupied feeder vehicle-kilometers traveled (VKT), and occupied-phase CO₂. Egress dominates in the evening peak and off-peak under the three entrance-buffer specifications, whereas morning balance is buffer-sensitive; Access is more spatially concentrated than Egress. Under the 150 m reference specification, 200,493 feeder trips average 5.451 km and generate 1,092,957 km of occupied VKT. Count-proportional allocation produces station-level VKT errors from −26.7% to +22.3%; five of the six station rankings change under VKT, and top-10 count and attributed-VKT grids overlap by 6.67 of 10. At the same occupied VKT, the all-battery-electric scenario yields 82.10 t of occupied-phase CO₂, 37.6% below the proxy-fleet base of 131.57 t; contextual non-occupied-VKT assumptions raise the estimate to 177.80–197.35 t. Counts and occupied VKT capture different operational dimensions. Low-carbon sustainability assessment should combine service frequency, occupied distance, and vehicle technology to support station-area carbon monitoring. Full article

Sustainable urban freight logistics requires routing decisions that jointly account for operating cost, vehicle technology, low-emission-zone (LEZ) access, terrain-sensitive energy use, and battery feasibility. This study develops a policy–terrain-coupled mixed-fleet routing framework integrating LEZ exposure, system-level carbon settlement, terrain-sensitive energy consumption, electric-vehicle (EV) battery feasibility, and route-level EV/internal-combustion-engine vehicle reassignment within a unified daily total operational cost (DTOC) evaluator. An adaptive large-neighborhood search (ALNS) procedure reconstructs feasible routes, while vehicle type is re-evaluated through counterfactual comparison of the complete system objective. The main experiments use 60 enhanced Gehring–Homberger benchmark-derived scenarios and 20 independent seeds, supplemented by ablation, carbon-price, EV-fixed-cost, heuristic-weight, convergence, and customer-scale scalability analyses. The ALNS-based framework achieves the lowest mean DTOC among the tested procedures, albeit with higher runtime. Policy and terrain information alter modeled fleet composition, with topology-dependent cost effects. Lower EV fixed costs consistently increase EV share, whereas carbon-price effects vary across network structures. All runs in the additional 200–1000-customer tests were feasible, although runtime increased with problem size. London- and Madrid-informed cases are treated as archetypes rather than as real-world validation cases. These results provide a basis for scenario screening and comparative planning of policy–terrain interactions before city-specific calibration and deployment. Full article

The increasing integration of distributed energy resources and flexible loads has transformed university campuses into complex energy systems that require coordinated operational strategies capable of managing renewable uncertainty while maintaining economic and environmental performance. This paper proposes a two-stage stochastic mixed-integer linear programming (MILP) framework for the optimal day-ahead energy management of a smart university campus. The proposed model jointly coordinates photovoltaic generation, battery energy storage systems, electric vehicle charging, HVAC operation, and demand response under uncertainties associated with solar generation, electricity demand, energy prices, and ambient temperature. Unlike previous campus energy management approaches, the proposed framework explicitly distinguishes first-stage scheduling decisions from second-stage recourse actions, enabling adaptive operation while preserving decision consistency across uncertainty scenarios. A realistic case study based on the operational characteristics of the Universidad Politécnica Salesiana campus in Ecuador is used to evaluate the proposed methodology. The results demonstrate that the coordinated stochastic scheduling strategy reduces daily operating costs by 36.37%, decreases CO₂ emissions by 42.81%, and lowers peak grid demand by 37.99% compared with conventional operation. In addition, photovoltaic self-consumption reaches 91.7%, while renewable energy utilization increases to 93.4% without compromising occupant thermal comfort. The proposed framework provides a scalable pathway toward low-carbon, resilient, and energy-efficient smart campus operation. Full article

Urban parking search remains a major source of congestion, travel delay, and unnecessary emissions, especially in areas where free on-street parking is not instrumented by dedicated infrastructure. This article investigates an infrastructure-less cooperative parking-guidance approach in which participating vehicles contribute lightweight parking-related evidence that is aggregated into shared heatmaps. The proposed model formalises parking-event semantics, heatmap representation, evidence updates, and a score-based parking-selection strategy that balances parking opportunity against walking distance. A SUMO-based simulation campaign evaluates the model under different user-preference parameters, system-adoption rates, and levels of initially available information. The results show that shared parking evidence can reduce search time under the evaluated conditions, including scenarios with partial adoption, while also highlighting the influence of user preferences and cold-start information availability on system performance. To examine the implementation feasibility of the information-generation mechanism assumed by the model, the article additionally presents a compact proof-of-concept pipeline based on a Bluetooth Low Energy beacon, a smartphone application, and a lightweight back-end service. Functional testing demonstrates that parking-related state-change events can be generated, transmitted, stored, spatially aggregated, and visualised without dedicated roadside parking sensors. This prototype serves only as an implementation-feasibility demonstration and does not constitute field validation of the guidance strategy or establish real-world accuracy, latency, reliability, or deployment readiness. Full article

The environmental sustainability of passenger-car electrification depends not only on powertrain technology but also on vehicle size, material intensity, energy-system decarbonisation, and end-of-life management. This study applies prospective life cycle assessment to compare battery electric vehicles (BEVs) with gasoline-powered internal combustion engine vehicles (ICEVs) across A/B, C, and SUV segments for 2025 and 2050, including a Paris Agreement-aligned 2050 pathway. ReCiPe 2016, IPCC 2021, Cumulative Energy Demand, CML-IA, and Ecological Scarcity 2021 were applied to evaluate climate, energy, resource, ecosystem, and policy-weighted environmental pressures, while well-to-tank and tank-to-wheel modelling quantified operational emissions. Environmental burdens generally increased with vehicle segment, and BEVs showed higher production-stage impacts because of traction batteries and electric-powertrain components. Recycling reduced most indicators but increased eutrophication in some variants, demonstrating the risk of burden shifting. In the integrated manufacturing-to-wheel assessment, BEVs achieved approximately 49% lower greenhouse gas emissions than gasoline ICEVs in the A/B segments and 54–55% lower emissions in the C and SUV segments under 2025 conditions. The results show that electrification alone is insufficient to ensure sustainable mobility. Its environmental benefits are maximised when combined with vehicle right-sizing, appropriately sized batteries, low-carbon electricity, energy-efficient manufacturing, and high-quality closed-loop recycling. Full article

Urban elevated-road exits concentrate deceleration, merging and surface-road control within a short transition, yet their emission responses are difficult to resolve from routine vehicle records. This study analyzed six dates of 1 Hz GPS and on-board diagnostics from one China VI diesel commercial vehicle operating in Nanjing. Sequence map matching linked the trajectories to a frozen OpenStreetMap network and identified 92 stable layer 1 → 0 exit occurrences. Leave-one-date-out telemetry models estimated the downstream OBD-derived NOx indicator expected from recorded vehicle, engine and aftertreatment states without using road variables. The trip-balanced post-minus-pre residual contrast was 0.084 log units (95% confidence interval, 0.020–0.151), whereas same-trip non-exit controls balanced on recorded operating changes showed a smaller contrast. The direction persisted across alternative models, map-matching settings, timing falsification, continuity thresholds, low-speed inclusion and an analysis restricted to recurring sites. Twenty sites were observed on multiple dates. These findings identify a recurrent, map-aligned OBD-derived NOx response signature within the observed operation and provide a practical basis for prioritizing targeted field measurements of emissions, traffic and road geometry at complex urban transitions. Full article