Search Results (2,231)

Global warming poses a serious environmental challenge worldwide. Agriculture, as a significant source of greenhouse gas (GHG) emissions, exerts considerable influence on the atmospheric environment. Chengdu, renowned for its thriving agricultural sector, serves as a key grain production center in China. Reducing agricultural greenhouse gas (AGHG) emissions is essential for mitigating the impact of climate change on Chengdu. Firstly, this paper employed the IPCC (Intergovernmental Panel on Climate Change) coefficient method and the Super-SBM-Undesired model to calculate the AGHG emissions and emission efficiency in Chengdu, respectively. Then, center of gravity shift analysis, kernel density estimation and spatial autocorrelation theory were used to analyze the spatial–temporal evolution characteristics of AGHG emissions. Finally, this paper conducted an in-depth analysis based on the STIRPAT model to identify key factors affecting AGHG emissions. The results show that: (1) From 2007 to 2021, Chengdu experienced an overall decline in both AGHG emissions and emission intensity, with reductions of 22.32% and 66.20%, respectively. And the AGHG emission efficiency was largely low. (2) AGHG emissions display regional variations and spatial clustering phenomena, characterized by a pattern of “high in the east, low in the west, high outside and low inside”. (3) AGHG emissions are highly increased by the sown area (S) and pesticide and fertilizer utilization (F) and may be reduced by the agricultural industrial structure (V) and the urbanization rate (U). These findings provide valuable scientific insights into the spatial–temporal dynamics of regional agricultural emissions. Furthermore, this study offers practical references for local governments to optimize agricultural resource allocation, formulate tailored low-carbon agricultural policies, and promote sustainable rural development. Full article

The use of manufactured sand (MS) as a substitute for natural sand or quartz sand in the production of ultra-high-performance manufactured sand concrete (UHPMC) represents a critical approach to alleviating the shortage of high-quality aggregates and promoting low-carbon development. However, after steel fibers and steel rebars are introduced into this material system, the synergistic working mechanism and damage evolution characteristics of the resulting ultra-high-performance manufactured sand-reinforced concrete (UHPMRC) beams under flexural loading remain largely unexplored. Acoustic emission (AE) technology, owing to its high sensitivity to the initiation and propagation of microcracks, enables real-time dynamic monitoring of UHPMRC beams throughout the entire process from the elastic stage to fracture failure, thereby providing an effective means to reveal the internal performance degradation law. Accordingly, this study conducted simultaneous AE monitoring on small-scale reinforced beams under four-point bending and investigated the effects of MS replacement ratios (0%, 50%, 100%) and steel fiber contents (1.0%, 1.5%, 2.0%). Results show that UHPMRC beams with 100% MS replacement and 1.5% steel fiber content achieve optimal performance. Compared to 0% MS specimens, those with 100% MS exhibit superior early stiffness, ductility, and flexural capacity due to the combined effects of steel fibers and MS. Beams with 2% steel fiber content experienced fiber clustering, reducing bridging capability and promoting earlier cracking relative to those with 1.5% fibers. AE energy parameters accurately identified cracking and characterized crack propagation in UHPMRC beams. Increasing MS content raised the proportion of shear cracks while reducing tensile cracks. The highest shear signal proportion occurred at 1.0% steel fiber content. These findings provide a valuable reference for the design of sustainable high-performance reinforced-concrete structures using manufactured sand. 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

Process mineralogy provides valuable information for understanding the mineralogical and textural characteristics of volcanogenic massive sulfide (VMS) deposits and their influence on mineral liberation. This study investigates the relationship between ore texture and chalcopyrite liberation in massive and stockwork/disseminated copper ore samples from a Kuroko-type VMS deposit in the Eastern Black Sea Region of Türkiye. Whole-rock mineralogy, textures, and mineral intergrowth relationships were characterized using X-ray diffraction (XRD), reflected-light ore microscopy, and field-emission scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (FE-SEM/EDS) mapping. Both ore types contain chalcopyrite, pyrite, sphalerite, and galena as the main valuable minerals, with quartz as the predominant gangue mineral. However, they show distinct textural characteristics. In the massive ore, chalcopyrite occurs as fine-grained aggregates filling fractures in cataclastic pyrite and commonly forms complex intergrowths with adjacent sulfides. In contrast, the stockwork/disseminated ore exhibits a more dispersed sulfide distribution within a quartz-rich matrix. Liberation analyses conducted across six particle size fractions, ranging from −600 + 500 to −38 µm, demonstrate that chalcopyrite liberation increases as particle size decreases. The stockwork/disseminated ore consistently exhibits higher liberation than the massive ore across all size fractions. The highest liberation values were achieved in the −38 µm fraction, reaching 98% for the stockwork/disseminated ore and 90% for the massive ore. FE-SEM/EDS mapping confirms that micron-scale sulfide intergrowths in the massive ore limit complete liberation and contribute to its lower liberation efficiency. These findings highlight the influence of ore texture on chalcopyrite liberation and provide useful geometallurgical information for optimizing the grinding and beneficiation of Kuroko-type VMS ores. Full article

This study investigates the influence of near-surface air temperature on the performance of internal combustion engines during mobile transects conducted in Mexicali, Baja California, Mexico, one of the hottest cities in North America. Field measurements were carried out along a 15 km urban transect on representative days in April, August, and February. Air temperature and relative humidity were recorded simultaneously at two engine air intake heights (0.66 m and 2.5 m), complemented by surface temperature data obtained from both in situ measurements and Landsat 8 thermal imagery. The results indicate that near-surface air temperature exhibits considerable spatial and temporal variability and is closely associated with land surface temperature (LST) patterns derived from satellite observations. The correction factor (Cf), used to quantify the combined effects of air temperature and atmospheric pressure on engine performance, showed that extremely high temperatures (approaching 50 °C) may reduce engine performance by up to 3.35% relative to standard test conditions. Conversely, cooler winter conditions may improve engine performance by approximately 4.6%. These results suggest that vehicle operation under extremely hot climatic conditions may deviate from the standardized assumptions adopted by the Intergovernmental Panel on Climate Change (IPCC) for emission factor estimation. This study contributes to a better understanding of the effects of extreme urban heat on vehicle performance and demonstrates that localized thermal conditions may influence the assumptions commonly used in vehicle emission assessments. The findings provide valuable information for improving greenhouse gas emission inventories and support evidence-based climate adaptation and urban planning strategies in arid cities. Full article

Carbon dioxide water-alternating-gas (CO₂-WAG) flooding simultaneously enables carbon emission mitigation, improved oil displacement efficiency, and expanded gas sweep coverage. Nevertheless, the field performance of this technology remains significantly constrained by gravity override effects, especially in ultra-thick oil reservoirs. In this work, a synthetic heterogeneous dipping mechanistic reservoir model is constructed. Using a quantitative metric for gravity override index in WAG processes, the variation patterns of gravity override under various operational factors are systematically analyzed. Furthermore, the eXtreme Gradient Boosting (XGBoost) machine learning algorithm is employed to conduct feature importance analysis of the controlling factors, identifying parameters with the most substantial impacts. The results indicate that well spacing, oil production rate, WAG injection strategy, and WAG slug duration all exert pronounced effects on both gravity override index and oil recovery factor. Gravity override is confirmed as the dominant factor governing the production performance of WAG flooding in ultra-thick reservoirs. In addition, an optimal combination of operational parameters exists that counterbalances the adverse effects of gravitational and viscous forces, thereby maximizing gas sweep efficiency, delaying gas breakthrough, and enhancing oil recovery. This study provides valuable insights and technical guidance for gas channeling mitigation, vertical gas sweep improvement, and efficient development of analogous ultra-thick reservoirs. Full article

During forest exploitation, large amounts of wood biomass are left as residues after harvesting, even though this material could be valuable in reducing greenhouse gas emissions by replacing fossil fuels and serving as a source of bioactive compounds. Within the context of the European Union’s circular bioeconomy strategy, enhancing the efficacy and rational application of forest logging residues constitutes a critical future objective. To evaluate the possible use of the stumps as forest residue-derived woody biomass for the first time, the chemical composition and presence of bioactive compounds in the xylem and bark of F. angustifolia Vahl. ssp. pannonica Soó & Simon stumps were analyzed, including the content of cellulose, acid-insoluble lignin, acid-soluble lignin, ash, and extractives soluble in toluene–ethanol and hot water. In hot water extracts, total phenolic content, the antioxidant activity determined by scavenging capacity toward DPPH and HPTLC, the content of elements by ICP-OES, and the identification of bioactive compounds by UHPLC-DAD-ESI MS/MS were assessed. Considering the chemical composition, the quality of the xylem of the F. angustifolia (cellulose: 42.46 ± 0.45%; lignin: 25.05 ± 0.02%; hemicelluloses: 19.74 ± 0.46%) was similar to that of the stem. Hot water extracts of the bark of F. angustifolia stumps showed high total phenolic content (33.94 ± 1.43 mg GAE/g DW) and strong antioxidant potential (198.48 ± 3.33 μmol TE/g DW), while toxic metals were not detected. UHPLC-DAD-ESI-MS/MS analysis indicated phenylethanoid glycosides as the dominant compounds in the extracts. The analyzed stumps of Fraxinus angustifolia Vahl. in the “Morović” Forest Administration represent a valuable biomass with potential for further valorization. Full article

Jarosite-type residues generated during zinc hydrometallurgical processing represent a significant environmental liability and a latent source of valuable metals (Zn, Pb, Ag). In this study, the thermal decomposition and mineralogical evolution of an industrial ammonium jarosite residue were investigated to 600–1400 °C. The behavior of the as-received residue was compared against a designed flux-assisted formulation comprising 45 wt% jarosite, 40 wt% Na₂CO₃, and 15 wt% SiC. The conventional roasting of pure jarosite forms refractory zinc ferrite (ZnFe₂O₄) and releases SO₂ above 800 °C, while the flux-assisted route stabilized the sulfur as Na₂SO₄ and CaSO₄, decreasing toxic gas emissions. Concurrently, the reducing effect of the SiC significantly inhibited bulk zinc ferrite formation up to 1200 °C and favored the partial reduction of iron to magnetite (Fe₃O₄). Thermodynamic assessment using FactSage reasonably matches experimental results by X-ray diffraction and SEM-EDS measurements. The thermodynamic evaluation predicts the formation of elemental silver available for subsequent pickup by a collector metal and a liquid slag phase at approximately 1000 °C for the flux-assisted jarosite samples. The ammonium jarosite flux-assisted roasting strategy enhances the potential for metal recovery while increasing environmental sulfur fixation in the slag, aligning with sustainable circular economy principles in non-ferrous metallurgy. Full article

Methane (CH₄) emissions from dairy cattle contribute substantially to agricultural greenhouse gas production and are influenced by genetic, physiological, environmental and management-related factors. The present study investigated CH₄-related traits and genotype–system interactions in Holstein Friesian (HF) dairy cows using repeated laser methane detector (LMD)-based measurements. A total of 134 cows from one research herd reflecting a commercial production system were repeatedly recorded for CH₄ traits (739 observations per trait) between 2020 and 2024 and linked with milk performance test-day data, behavioral observations, environmental measurements and genomic breeding values. CH₄ traits were derived separately for respiration- and eructation-related emissions. Generalized linear mixed models revealed significant effects of wind speed, rumination behavior, interaction behavior and days in milk on several CH₄ traits. Across lactation, respiration-related CH₄ traits slightly decreased, whereas eructation-related traits increased toward later lactation stages. Correlations between CH₄-related breeding values and production traits were generally low to moderately negative, ranging from −0.24 to 0.08, indicating that selection for reduced CH₄ emissions may be achievable without major unfavorable effects on milk production traits. To evaluate the complex relationships among CH₄ emissions, production, behavior, environment, diet and genetic background, a structural equation model (SEM) was applied. Environmental conditions, particularly temperature and humidity, showed the strongest positive association with CH₄ emissions, while eructation-related CH₄ traits contributed more strongly to the latent CH₄ construct than respiration-related traits. Behavioral activity, especially rumination, indicated relevant associations with CH₄ expressions. The SEM further suggested that CH₄ emissions are shaped by interconnected environmental, physiological and genetic pathways rather than by a single dominant factor. Overall, the results highlight the importance of environmental sensitivity and longitudinal biological variation in CH₄ phenotypes under commercial dairy production conditions. Repeated on-farm CH₄ measurements, particularly eructation-associated traits, may provide valuable indicator traits for future genomic breeding and management strategies to reduce the environmental footprint of dairy cattle production. 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

Energy planning should focus on actions to save energy and reduce consumption while also implementing renewable energy sources to support sustainable urban development. In addition to global regulations, individual countries also have documents that facilitate energy management at the local level. This is a particularly valuable source of information about resources that influence energy efficiency at the national level. This article analyzes the Low-Emission Economy Plans (LEEPs) developed for selected cities in Poland. Based on selected provisions, fuzzy modeling solutions are proposed to support energy decisions in municipalities. The research thesis assumes that the appropriate selection of criteria for emission reduction, as well as their objectification and hierarchization, when supported by fuzzy logic modeling and multi-criteria analysis, enables local governments to identify key variables and structures and compare decision scenarios relevant to local energy policies. To verify this thesis, an analysis of the LEEP provisions of four city municipalities located in the Kuyavian–Pomeranian Voivodeship was conducted. Based on these criteria, a set was identified, and diagrams were developed to identify variables and concepts that occupy key positions in the modeled pathways leading to emission reductions. Fuzzy logic modeling and multi-criteria analysis were used as decision-support tools in the research process. A comparison of the applied approaches enables the identification and prioritization of variables of greatest importance within the adopted set of criteria. The obtained results allow us to determine how the adopted energy strategies are linked to the implementation of local policy objectives and which relationships play a key role in the modeled decision-making structure. The analysis indicates that the decision-making variants differ in their impact on the paths leading to reduced final energy consumption and greenhouse gas emissions. Variant W1, which is based on investments in renewable energy sources, is strongly associated with the path leading to reduced greenhouse gas emissions, while increased public awareness and acceptance also play a significant role in the model’s structure. The strongest relationships were identified between increased energy efficiency and building energy standards, between building energy standards and reduced final energy consumption, and between reduced final energy consumption and reduced greenhouse gas emissions. The reasoning map thus highlighted the particular importance of the sequence of relationships linking energy efficiency, building energy standards, and reduced final energy consumption. The proposed approach can also provide a basis for further comparisons with solutions used in other countries, thus expanding the possibilities of analyzing low-emission policies at the local and national levels. Full article

Methane emissions from coal mines pose significant environmental and operational challenges. Methane can be released from coal seams and surrounding rock layers as a result of mining operations. These emissions pose environmental risks and can lead to fire and explosion hazards. Therefore, reducing coal mine methane emissions is essential for both protecting miners’ safety and cutting greenhouse gas emissions. Additionally, capturing methane before it escapes into the atmosphere can be economically beneficial and used as a valuable energy source. This study proposes an integrated approach that combines advanced methane capture and hydrogen production technologies to enhance both environmental performance and energy recovery in coal mining operations. By combining methane capture with hydrogen production, the study presents a practical solution for lowering greenhouse gas emissions in the coal sector. This strategy promotes the adoption of low-carbon energy sources and offers a sustainable path forward for coal-dependent regions facing decarbonization challenges. A scenario-based techno-economic analysis is presented, including investment and operating costs, hydrogen yield, energy generation potential, and greenhouse gas mitigation. Further research should focus on process optimization, the integration of carbon capture technologies, and the valorization of by-products to further reduce the environmental footprint. Full article

This study analyzes wastewater treatment plants (WWTPs) in Querétaro, Mexico, over a decade (2013–2022), highlighting the interdependencies between pollutant removal, energy consumption, and greenhouse gas (GHG) emissions. Despite being conventional systems, the WWTPs achieved high pollutant removal efficiencies (92–97% BOD₅, 50–60% TN), preventing 146.1 MtCO₂e over ten years. However, this efficiency came with some drawbacks: a 10% reduction in pollutants increased electricity consumption by 7%. CO₂ emissions from grid-fed operations increased by 130% between 2021 and 2022, emphasizing the carbon intensity of improving water quality. In 2022, the system emitted 0.002 tCO₂e/m³ of treated water, due to indirect N₂O and CH₄ emissions from untreated flows and electricity consumption. With only 70% of wastewater treated and minimal energy recovery, the existing infrastructure offers environmental benefits but operates near its efficiency limits in the face of increasing demand. The transition to energy-neutral models, through biogas cogeneration, solar integration, and advanced nutrient removal, is crucial for achieving urban water systems resilient to climate change. This case study provides valuable insights for cities seeking to balance water security, sustainability, and decarbonization in rapidly developing regions. Full article

Food waste has emerged as one of the most pressing global sustainability challenges because of its environmental, economic, and social implications. Nearly one-third of the food produced worldwide is lost or wasted each year, contributing to greenhouse gas emissions, depletion of natural resources, and increasing food insecurity. Advances in circular bioeconomy concepts and sustainable processing technologies have transformed food waste from an environmental liability into a valuable feedstock for producing biofuels, bioplastics, bioactive compounds, functional ingredients, prebiotics, and other high-value products. This review critically examines current strategies for converting food waste into value-added products, including green extraction technologies and biochemical, thermochemical, enzymatic, and microbial approaches. Attention is given to major agri-food by-products, such as fruit pomace, vegetable residues, oilseed meals, dairy by-products, and agro-industrial wastes. Emerging developments involving biorefinery concepts, artificial intelligence, digital biorefineries, synthetic biology, and carbon-neutral production systems are also discussed. Furthermore, the review highlights recent applications of waste-derived fibers, antioxidants, and polyphenols in functional foods, especially bakery products. Finally, key challenges related to feedstock heterogeneity, process scalability, regulatory frameworks, economic feasibility, and sustainability assessment are critically analyzed together with future research directions supporting the transition toward resilient circular bioeconomy systems. Full article

Global growth in electric mobility, portable electronics, and renewable energy storage has increased concerns about the environmental and economic impacts of managing end-of-life lithium-ion and lead-acid batteries. Although these batteries support the transition to renewable energy, their disposal presents significant challenges. Recycling has emerged as a key strategy to reduce resource depletion, limit pollution, and recover valuable materials. This study systematically reviewed and quantitatively synthesised the literature published between 2000 and 2025, assessing the environmental impacts of battery recycling programs. The review followed PRISMA guidelines to ensure a transparent and rigorous study selection process. Data from peer-reviewed articles, industry reports, and policy documents were analysed, focusing on indicators such as greenhouse gas emissions, energy use, material recovery efficiency, and economic returns. Statistical methods, including Hedges’ g, heterogeneity testing, and sensitivity analysis within a random-effects model, were applied to account for variability across technologies and battery types. The results show that recycling generally lowers emissions and improves resource recovery compared to virgin material extraction, though performance varies. Lead-acid recycling demonstrates stronger environmental benefits due to mature technologies and established systems, while lithium-ion recycling shows positive but lower gains, limited by higher energy demands and less-developed processes. Overall, recycling is essential for reducing environmental impacts and supporting a circular economy, though lithium-ion systems require further technological and policy advancements. These findings can be used by governments to strengthen regulatory frameworks to support recycling industries and invest in advanced lithium-ion recycling technologies to improve efficiency. Despite the existing limitations, the benefits of recycling outweigh the drawbacks, making it a necessary strategy for sustainable battery waste management. Full article