Search Results (2,802)

Digital technologies such as big data are reshaping resource allocation, raising interest in whether and how heterogeneous science and technology innovation (STI) policies can help unlock urban carbon lock-in. Using panel data for 286 prefecture-level cities in China from 2009 to 2023, this paper examines the relationship between heterogeneous STI policy intensity—classified as supply-side, demand-side, complementary-factor, and institutional-reform policies—and urban carbon unlocking efficiency. We develop a mechanism-based framework and empirically assess (i) the moderating roles of digital infrastructure, science and technology finance, and government green attention, and (ii) spatial spillover effects using spatial econometric models. The results show that all four policy types show a significant positive association with local carbon unlocking efficiency, with institutional-reform policies exhibiting the strongest association. When the four types are included jointly, only supply-side and demand-side policies retain statistically significant direct associations. Heterogeneity analyses indicate that demand-side, complementary-factor, and institutional-reform policies are more strongly associated with efficiency gains in low-pollution cities, whereas supply-side and demand-side policies have a stronger association in high energy-consuming cities. Mechanism analysis reveals that regional digital infrastructure exerts a selective moderating effect on the relationship between heterogeneous sci-tech innovation policies and urban carbon emission reduction efficiency. It positively reinforces the effectiveness of supply-side, demand-side, and institutional reform-oriented policies, while its interaction with complementary policies is statistically insignificant. Technology finance and government green policies function as a “resource catalyst” and an “institutional guarantee” respectively, significantly enhancing the correlation between heterogeneous sci-tech innovation policies and urban carbon emission reduction efficiency. Finally, carbon unlocking efficiency displays significant spatial dependence: the intensity of supply-side and institutional-reform policies is positively associated with carbon unlocking efficiency in neighboring cities, while complementary-factor policies exhibit a negative spatial association. Overall, the findings provide empirical evidence to inform the design and coordination of heterogeneous STI policy portfolios aimed at improving urban carbon unlocking efficiency. Full article

Background/Objectives: Contemporary food systems face dual imperatives of ensuring nutritional adequacy while minimizing environmental resource consumption, yet conventional dietary assessment methodologies inadequately integrate these competing objectives. This simulation-based proof-of-concept study developed an artificial intelligence-driven computational framework synthesizing nutritional evaluation, environmental footprint quantification, and economic accessibility assessment. Methods: The analytical architecture integrated random forest classification, dimensionality reduction, and scenario-based optimization across a simulated population cohort of 1500 individuals. Food composition data encompassed 55 representative foods across eight categories linked with greenhouse gas emissions, water use, and price parameters. Four dietary patterns (Mediterranean, Western, Plant-based, Mixed) were characterized across nutrient adequacy, greenhouse gas emissions, water consumption, and economic cost. Results: Random forest classification achieved 39.1% accuracy, with cost, greenhouse gas emissions, and water consumption emerging as the most discriminating features. Dietary patterns exhibited convergent macronutrient profiles (protein 108.8–112.8 g per day, 4% variation) despite categorical distinctions, while calcium inadequacy pervaded all patterns (867–927.5 mg per day, 7–13% below requirements). Environmental footprints demonstrated limited differentiation (greenhouse gas 3.73–3.96 kg CO₂e per day, 6% range). Bootstrap resampling (n = 1000) confirmed narrow confidence intervals, with NHANES validation revealing substantial energy intake deviations (38–58% above observed means) attributable to adequacy-prioritized design rather than observed consumption patterns. Scenario modeling identified seasonally flexible dietary configurations maintaining micronutrient and protein adequacy while reducing water use to 87% of baseline at modest cost increases. Conclusions: This framework establishes a validated computational infrastructure for integrated dietary assessment benchmarked against sustainability thresholds and epidemiological reference data, demonstrating the feasibility of AI-driven evaluation of dietary patterns across nutritional, environmental, and economic dimensions. Full article

This study investigates how Vision Language Models (VLMs) can be used and methodically configured to extract Environmental, Social, and Governance (ESG) metrics from corporate sustainability reports, addressing the limitations of existing text-only and manual ESG data-extraction approaches. Using the Design Science Research Methodology, we developed an extraction artifact comprising a curated page-level dataset containing greenhouse gas (GHG) emission-reduction targets, an automated evaluation pipeline, model and text-preprocessing comparisons, and iterative prompt and few-shot refinement. Pages from oil and gas sustainability reports were processed directly by VLMs to preserve visual–textual structure, enabling a controlled comparison of text, image, and combined input modalities, with extraction quality assessed at page and attribute level using F1-scores. Among tested models, Mistral Small 3.2 demonstrated the most stable performance and was used to evaluate image, text, and combined modalities. Combined text + image modality performed best (F1 = 0.82), particularly on complex page layouts. The findings demonstrate how to effectively integrate visual and textual cues for ESG metric extraction with VLMs, though challenges remain for visually dense layouts and avoiding inference-based hallucinations. Full article

Chile’s livestock industry faces growing demands for emissions reduction, animal welfare, and value creation, while continuing to play a key role in rural food security and pasture-based production systems. In light of Chile’s varied agroclimatic conditions, a diminishing national herd, and shifting market signals, such as alternative proteins and distinctive meat products, this narrative review explores four complementary transition pathways: sustainable intensification, organic and agroecological systems, heritage livestock, and regenerative practices. We map the structural challenges, including grazing dairy and beef herds, fragmented producer organization, and the absence of unified, farm-scale greenhouse-gas measurements. We assess the management strategies that have the strongest support; viz., efficiency gains at the animal/herd level, adaptive grazing and silvopastoral designs, nutrient cycling via manure management and local by-products, and welfare frameworks that are aligned with national law and World Organisation for Animal Health guidance. Heritage systems (e.g., Chilota sheep breed in the Chiloé archipelago) provide resilience, cultural identity, and low-input baselines for stepwise transitions. Regenerative procedures can improve soil function and drought buffering but require context-specific designs and credible outcome-based verification to avoid greenwashing. Key enabling policies include coordinated certification and labeling covering animal welfare and origin. Additional elements are cooperative and territorial governance, targeted R&D and extension services for smallholders, and a transparent, standardized greenhouse-gas measurement framework linking farm-level actions to national inventories. Chile’s pathway is not a single model but a practical combination shaped by regional conditions that can deliver long-term economic sustainability, ecosystem services, and nutrition. Full article

RCCI is a promising combustion strategy that can improve the controllability of combustion phasing. This study evaluates fusel oil (an inexpensive industrial by-product) as a low-reactivity supplementary fuel in an RCCI diesel engine. Fusel oil was injected into the intake air at 4, 6, 10, 12, and 16 g/min (DF4-DF16), and experiments were conducted on a four-cylinder, four-stroke diesel engine at 1750 rpm under 40, 60, 80, and 100 Nm. In-cylinder temperature/pressure-based combustion behaviour, air excess ratio (λ), NO and smoke emissions were assessed. The influence of fusel oil on combustion was strongest at low load. At 40 Nm, the highest fusel-oil energy share increased peak cylinder pressure by 14% and peak in-cylinder temperature by 4% compared to diesel fuel tests, while at 100 Nm the corresponding increases were 4% and less than 1%. NO increased at 40 Nm, with a maximum rise of 17.9% at the highest fusel-oil energy share, but decreased at medium and high loads, falling by 7.13 to 13.54% between 60 and 100 Nm. Smoke increased consistently with fusel oil, reaching about 42% at 40 Nm and remaining below 22% at 100 Nm. A techno-economic assessment showed that although capital costs increased slightly, the low price of fusel oil decreased operating costs by up to 33% and reduced life-cycle costs by up to 42%. Overall, fusel oil-assisted RCCI operation can provide notable cost benefits and conditional NO reductions, though with a smoke penalty that should be considered in application and after-treatment strategies. Full article

Feed stress is a very critical factor impacting livestock health and productivity. One of the major contributors to quantitative feed deficiency is the continued adherence to conventional diets and feeding practices, which renders livestock populations vulnerable to environment-induced scarcity events as well as shortages arising from supply-chain bottlenecks. These challenges occur in the face of the ever-expanding demand from a continuously growing livestock population. In a world increasingly experiencing qualitative and quantitative resource constraints due to rising demand and increasing pollutant concentrations in the environment, conventional dietary compositions require timely modification and supplementation with alternative feed ingredients. These may include the hitherto unutilized by-products of agricultural production, which are often discarded as agricultural waste, in order to mitigate the stress induced by feed availability shortfalls. Cauliflower leaf meal is one such by-product whose suitability as a feed supplement was evaluated in the present study, with results that can be reliably described as promising. The present study assessed the impact of dried cauliflower leaf meal (CLM) on growth performance, nutrient utilization, rumen fermentation, and methane emission in goats. Fifteen non-descript male goats, aged 6–8 months, were randomly allocated into three groups of five animals each and housed separately in identical pens within the same shed for the duration of the experiment. Three dietary treatments were administered: T0 (control; concentrate, hybrid Napier, and wheat straw); T20 (20% replacement of wheat bran with CLM in the concentrate, along with hybrid Napier and wheat straw); and T30 (30% replacement of wheat bran with CLM in the concentrate, along with hybrid Napier and wheat straw). The results indicated that the goats in all groups achieved a similar body-weight gain with a comparable dry-matter intake (DMI). The feed conversion ratio (FCR), nutrient digestibility, and mineral balance were also comparable across treatments. However, the methane emission rate was significantly lower (p < 0.05) in the T30 group compared with the other groups. CLM supplementation did not cause deviations in rumen pH, NH₃-N concentration, volatile fatty acid production, or bacterial and protozoal populations. The hematological parameters remained unaffected by the increased dietary inclusion of CLM, while both cell-mediated and humoral immune responses showed an improvement in the CLM-fed groups. Notable reductions in methane emission were observed in goats fed diets containing 20–30% dried CLM, highlighting the positive environmental implications of such a dietary inclusion. Full article

Hospitals are major consumers of natural resources, and their continuous 24/7 demands exert significant environmental repercussions. Notably, energy utilization and waste generation constitute primary determinants of the ecological footprint associated with healthcare facilities. This study aims to provide a replicable framework for estimating operational carbon account of orthopedic hospital operations using readily available data, without requiring expert-level life cycle assessment tools. A three-level analysis was applied to a case study in a large Italian public hospital, focusing on CO₂e emissions from energy consumption and hazardous waste generation. Operational data from the hospital and detailed audits of orthopedic procedures were used to estimate energy consumption, ventilation loads, and waste volumes. Results showed that HVAC systems dominated energy-related emissions, while surgical waste was a major contributor at the meso- and micro-levels. Several mitigation strategies were proposed, including reducing off-hours air exchange rates and improving waste segregation, leading to potential emission reductions. The study highlights that even a simplified carbon accounting approach can generate valuable insights for healthcare managers, supporting internal benchmarking and sustainability action. Full article

Laboratory test results for vehicle emissions, fuel economy, and driving range often fail to reflect real-world performance, undermining the effectiveness of sustainability policies and consumer guidance. This study provides the first integrated national assessment of real-world emissions and range outcomes for passenger vehicles in Australia. Using Portable Emissions Measurement Systems (PEMS) data from 114 petrol, diesel, hybrid, and battery-electric vehicles (BEVs) tested by the Australian Automobile Association (AAA), the analysis compares laboratory-certified values against on-road results and benchmarks them with international datasets from Europe and China. Real-world CO₂ emissions were, on average, 6.9% higher than laboratory ratings for petrol vehicles and 3.2% higher for diesel vehicles. Many diesel models exceeded Euro 6 NO_x limits by several multiples, while hybrids exhibited inconsistent CO₂ reductions under urban conditions. BEVs also displayed measurable divergence: real-world energy consumption was 1–20% higher than laboratory ratings, resulting in an average 16% reduction in effective driving range relative to WLTP values. These outcomes reveal a consistent tendency toward overstated laboratory performance across powertrains, highlighting systemic shortcomings in certification test cycles. The findings have direct implications for greenhouse gas mitigation, urban air quality, and consumer energy efficiency and support Australia’s active transition to WLTP and Euro 6 standards, institutionalisation of real-world testing, and inclusion of verified real-world energy use and range data in consumer labelling to enhance transparency and policy effectiveness. Full article

Sewage sludge management is a major challenge in modern wastewater treatment, as sludge contains organic matter, nutrients, pathogens, heavy metals, and emerging contaminants. Increasing wastewater volumes from urbanization and population growth have led to steadily rising global sludge production, emphasizing the need for sustainable and resource-efficient treatment strategies. Conventional methods—such as landfilling, land application, and biological treatment—face limitations due to contaminant risks, regulatory restrictions, and incomplete pollutant removal. Thermal and thermochemical processes offer substantial volume reduction, energy recovery, and resource valorization. Incineration is widely implemented and ensures complete oxidation but requires high energy input and emission control. Gasification and pyrolysis produce syngas, bio-oil, and biochar, supporting circular economy applications, while hydrothermal carbonization (HTC) efficiently converts wet sludge into hydrochar without intensive drying. This study presents a comparative life cycle assessment (LCA) and mass–energy assessment of these four thermal treatment methods, highlighting their environmental impacts, energy efficiencies, and resources’ recovery potential to support more sustainable sludge management. Full article

The evaluation of China’s Low-Carbon City Pilot Policy (LCCP) is critical to understanding its role in mitigating climate challenges associated with carbon emissions. While most existing research has concentrated narrowly on emission reductions within pilot cities, broader improvements in emission performance have often been overlooked. To address this gap, our study employs an integrated methodological framework combining Difference-in-Differences (DID) with Data Envelopment Analysis (DEA), enabling a dual-perspective assessment of policy effectiveness. Baseline regression results confirm that the LCCP has led to a statistically significant decrease in total urban carbon emissions. Pilot cities achieved an average reduction in emission levels that was 4.8 percentage points greater than that of non-pilot cities, underscoring the policy’s tangible impact. Further analysis using DEA reveals a consistent year-on-year enhancement in the dynamic carbon emission performance of these cities. Regionally disaggregated results highlight distinct drivers of low-carbon performance: in low-emission cities such as Huangshan, gains were primarily efficiency-led; in medium-emission cities like Beijing, technological advancement served as the main catalyst; and in high-emission cities including Shanghai, both efficiency gains and technological innovation jointly propelled progress. These findings offer valuable empirical insights for customizing low-carbon transition pathways across cities with varying emission profiles. Full article

Filter cake (or cachaza), a residue generated in the artisanal production of panela, represents an under-explored source of renewable energy in the Ecuadorian Amazon. Valorizing filter cake could reduce the use of solid biomass and emissions associated with traditional combustion. Our objective was to determine the energy potential of the biogas obtained and its contribution to the sustainability of the panela (unrefined cane sugar) production system. A sequential procedure was applied that included the physicochemical characterization of filter cake, feed flow modeling, and stoichiometric simulation under mesophilic conditions. The anaerobic digestion of filter cake with the optimal Composition 6 generated up to 1736.40 m³·day⁻¹ of biogas with 40.7% methane and a calorific value of 14,350 kJ·m⁻³. This was enough to replace 1.24 t·day⁻¹ of wood or 2.38 t·day⁻¹ of bagasse in the production system. This represents an annual saving of 631.08 t of solid biomass, equivalent to conserving 3.63 ha·year⁻¹ of the Amazon rainforest. The Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts (TRACI) analysis showed impacts on climate change (17.40 kg CO₂ eq/m³) and acidification (0.00516 kg SO₂ eq/m³), attributable to unburned methane and residual H₂S. Meanwhile, the social assessment using the Occupational Health and Safety Potential (OHSP) indicator showed high risks in terms of handling filter cake and cleaning the digestate. Full article

Building upon the methodological synthesis presented in Part I, this second part of our two-part survey examines how operations research (OR) models have been applied to capture the broader dynamics of intermodal transport (IMT) in pursuit of decarbonization. The analysis integrates chronological, modal, and sustainability-oriented perspectives to reveal how IMT strategies evolve across transportation modes, policy environments, and temporal contexts. We identify how efficiency gains, modal shifts, and low-carbon technologies interact within OR frameworks, and assess their implications for emissions reduction, energy use, and network resilience. By bridging technical modeling approaches with system-level sustainability objectives, this study offers a holistic understanding of the pathways through which OR supports the transition toward low-carbon freight systems and highlights research gaps for future interdisciplinary work. Full article

Many companies in the mining industry include decarbonization of production among their key strategic goals as part of their internal sustainability strategy. This need is driven by a number of factors: stricter regulation in the area of carbon footprint (introduction of carbon taxes, emissions quotas, reporting requirements); sustained growth in demand for electricity and rising market prices; economic feasibility—the need to optimize operating costs and improve energy efficiency. This study provides a comprehensive technical and economic justification for implementing a hybrid power supply system—combining a solar power plant (SPP) and a gas engine power plant (GPP)—at Solidcore Resources’ Varvarinsky hub in Kazakhstan. The methodology includes modeling the energy balance of the real asset (156.9 GWh of annual energy consumption), calculating the output of a 22.6 MW SPP based on local GHI/PR/η parameters, forming and determining the adaptability coefficient Kₐ (proportion of PV in total monthly electricity generation), conducting an economic assessment (NPV, payback period, sensitivity), and inventorying CO₂ emissions under Scope 1–2. The SPP provides approximately 41.3 GWh of electricity generation per year, with an average annual K_a = 0.263; the 40 MW installed capacity of the gas piston power plant covers the residual demand, forming a stable daily and seasonal balance. The project demonstrates a positive NPV (After Tax) = USD 23.65 million with an estimated payback period of 10 years, while the cost of energy in extraction and processing is reduced by almost three times, and the total reduction in CO₂ emissions will be 51%. Thus, hybridization of energy supply systems is a practical compromise between reliability and decarbonization. Determining the adaptability coefficient K_a allows the flexibility of the system to be taken into account, shows how effectively the new energy system uses renewable energy sources, and can be used to optimize the operation of the energy system to achieve the company’s internal sustainable development goals. Full article

In the context of the ongoing green transformation in the construction industry, this research presents a comprehensive economic assessment of emission reduction in residential buildings from the perspective of carbon trading. The assessment accounts for energy saving revenue, emission trading revenue, economic cost, and environmental cost. By adopting two dynamic economic indicators—Net Present Value (NPV) and Dynamic Payback Period (DPP)—a dedicated economic evaluation model for residential building emission reduction is developed. A case study of a residential building shows that roof retrofits deliver the highest NPV, owing to their lower costs and significant emission reduction benefits. Although external walls achieve the highest carbon reduction per unit area, their high costs mean they are ranked second in terms of NPV. Moreover, the introduction of a carbon trading mechanism can generate additional value of approximately 87,377.08 CNY and shorten the payback period by 0.83 years, highlighting its crucial role in advancing the low-carbon transition of the construction industry. However, current emission reduction efforts still face challenges such as a relatively low NPV and an extended payback period. To enhance the investment value and market competitiveness of such projects, it is essential to reduce emission reduction costs and increase emission reduction benefits. Full article

One of the key aspects of a smart city is to reduce CO₂ emissions by adopting different strategies that can also improve the quality of life of citizens. Current metropolises present additional issues compared to traditional cities, such as extremely heavy traffic and abandoned spaces. This paper, therefore, proposes two interventions aimed at improving the smartness of the municipality of Rome: the implementation of a photovoltaic field in an abandoned space used to charge electric buses and the implementation of smart traffic lights that optimise the traffic flow. To measure the impact and effectiveness of those interventions, key performance indicators (KPI) were defined to point out the benefits of the analysed strategies, and a quantitative matrix approach was applied. The aim was to establish a correlation between the different scenarios proposed, assigning numerical indices to each of them that can comprehensively express their impact on the identified smart axes. The results obtained showed the importance of selecting appropriate performance indicators to assess the impact of interventions. Furthermore, the findings revealed that the scenarios with the greatest number of indicators are not necessarily the most advantageous. Overall, the simulations indicated that the proposed interventions could produce a significant reduction in emissions due to the implementation of renewable energy production. Full article