Search Results (2,812)

Increases in global temperatures, due to the climate change, are generating stress in most plant species. We hypothesize that young plants of Opuntia spp. adjust their Crassulacean acid metabolism (CAM) to the increase in nighttime temperature, allowing them to continue growing. The study was carried out in a greenhouse and laboratory of the Colegio de Postgraduados, Montecillo, Mexico. Three-month-old greenhouse-grown plants remained in a control environment with an average day/night temperature of 19.1/12.3 °C or were maintained in a chamber with increased nighttime temperatures averaging 19.1/18.9 °C day/night for 70 days. The experimental design was completely randomized with two treatments (control and high nighttime temperatures). After 70 days of high nighttime temperatures (HNT), at dawn (end of CAM phase I), plants had a 45% decrease in glucose (2.9 to 1.5 mg/100 mg dry tissue; dt) concentration and doubled and tripled fructose (0.43 to 0.95 mg/100 mg dt) and sucrose (0.47 to 0.09 mg/100 mg dt) concentrations. Glucose consumption may be related to the plant’s metabolic energy expenditure to overcome stress. The significant increase in fructose and sucrose is explainable by their function as signaling molecules among others. In contrast, photosynthetic efficiency, i.e., increased compared to the control, but the difference of acidity (end of phase I less phase III), the concentration of starch (1 mg/100 mg dt), free amino acids and soluble protein (1.2 mg/100 mg dt), wet and dry matter, stem height (60 cm) and width of the stem at dawn were not significantly affected. The adjustments in C and N metabolism and the non-significant effect on growth promoted by 70 HNT days may be related to adjustments in enzyme activities without changes in protein concentration. Young Opuntia spp. plants adjust their metabolism in response to increased nighttime temperatures, allowing them to maintain growth similar to that of the control. The results confirm the great potential of using the Opuntia genus in agriculture and genetic improvement in the face of the challenges posed by climatic change. Full article

In recent years, against the backdrop of increasingly prominent global climate change and environmental issues, high-efficiency cooling technologies and energy-saving materials have become key research focuses. Radiative cooling, which reflects sunlight and emits thermal radiation into outer space, enables passive cooling without energy consumption. The phase separation method has emerged as a promising approach for fabricating porous daytime radiative cooling materials, attracting extensive research interest due to its favorable processability, excellent cooling performance, low cost, and scalability. Based on radiative cooling principles, this review summarizes the preparation methods, structural design, and application fields of porous radiative cooling films fabricated via the phase separation method. Furthermore, it is suggested that phase-separated porous radiative cooling films hold great potential in green buildings, personal thermal management, and food preservation. Full article

Climate change significantly challenges efforts to maintain and improve crop production worldwide. Diversified crop rotations have emerged as a promising way to adapt cropping systems and bolster food security under changing climate conditions; however, robust empirical evidence remains limited. This study evaluates the long-term performance of diversified crop rotations under future climate scenarios in the North China Plain via an 80-year scenario analysis (2020–2100) spanning three shared socioeconomic pathways (SSPs:126, 370, 585). The calibrated and validated SWAP (Soil–Water–Atmosphere–Plant)–WOFOST (WOrld FOod STudies) model simulated water consumption and yield. Sustainability indices were employed to assess the cereal yield stability and compensation effect to yield loss caused by climate change. The study compares the conventional winter wheat–summer maize rotation (WM) with two legume-based rotations: soybean–WM (S–WM) and peanut–WM (P–WM). The results indicate that, under all three climate scenarios, the two legume-based rotations reduced annual water consumption by 7–9%, maintained system economic equivalent yields with one crop less, and improved water productivity by up to 10%. Future climate change decreased cereal yields by 9–26% across all rotations compared to historical baselines. However, the two legume-based rotations showed a significant residual effect, increasing subsequent cereal yields by 9–14% over the conventional WM under all scenarios. Consequently, the legume-based rotations provided a 25–51% yield compensation. Additionally, these rotations improved the sustainable yield index and system resilience and reduced cereal yield variance under future climate scenarios compared to the more vulnerable WM. This study demonstrates that diversified crop rotations are a viable strategy to mitigate negative climate impacts. The study provides critical insights for policy-makers, supporting crop-rotation diversification as a core component of risk-reduction strategies to mitigate future climate change impacts. Full article

In the fight against global climate change, the transportation sector is of critical importance because it is one of the major causes of total greenhouse gas emissions worldwide. Although urban rail transit systems offer a lower carbon footprint compared to road transportation, accurately forecasting the energy consumption of these systems is vital for sustainable urban planning, energy supply management, and the development of carbon balancing strategies. In this study, forecasting models are designed using five different machine learning (ML) algorithms, and their performances in predicting the energy consumption and carbon footprint of urban rail transit systems are comprehensively compared. For five distribution-center substations, 10 years of monthly energy consumption data and the total carbon footprint data of these substations are used. Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), Long Short-Term Memory (LSTM), Adaptive Neuro-Fuzzy Inference System (ANFIS), and Nonlinear Autoregressive Neural Network (NAR-NN) models are developed to forecast these data. Model hyperparameters are optimized using a 20-iteration Random Search algorithm, and the stochastic models are run 10 times with the optimized parameters. Results reveal that the SVR model consistently exhibits the highest forecasting performance across all datasets. For carbon footprint forecasting, the SVR model yields the best results, with an $R^2$ of 0.942 and a MAPE of 3.51%. The ensemble method XGBoost also demonstrates the second-best performance ($R^2=0.648$). Accordingly, while deterministic traditional ML models exhibit superior performance, the neural network-based stochastic models, such as LSTM, ANFIS, and NAR-NN, show insufficient generalization capability under limited data conditions. These findings indicate that, in small- and medium-scale time-series forecasting problems, traditional machine learning methods are more effective than neural network-based methods that require large datasets. Full article

Achieving Net-Zero Energy Building (NZEB) performance through retrofitting requires identifying optimal measures that effectively enhance energy efficiency. Determining these optimal retrofit strategies typically involves running thousands of building energy simulations, which imposes a substantial computational burden. To address this challenge, a novel machine learning-based framework is proposed to optimize retrofit strategies for NZEBs under future climate change scenarios. A Non-Dominated Sorting Genetic Algorithm (NSGA-III) is employed to minimize both annual energy consumption and the Predicted Percentage of Dissatisfied (PPD), while simultaneously ensuring net-zero energy balance, thereby generating a Pareto front of optimal solutions. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is then applied to rank the Pareto-front solutions and identify the most favorable retrofit scenario. The results show that the proposed framework reduces optimization time by at least a factor of two compared with simulation-only optimization. Leveraging these computational savings, the framework evaluates a suite of passive and renewable measures across multiple future timeframes to capture the influence of climate change on retrofit performance. The findings indicate that achieving NZEB under future climate conditions requires higher levels of thermal insulation and greater renewable integration than under present-day conditions. Under the Shared Socioeconomic Pathways (SSP) framework, optimal insulation levels in the fossil fuel-dependent scenario are lower than in the sustainable scenario by up to 18% in C-type (warm temperate), 12% in D-type (snow), and 13% in E-type (polar) climates. The combined retrofit measures can reduce annual energy consumption by up to 80% and lower PPD by as much as 67% compared to the base case. Full article

Purpose: A growing body of evidence has emerged on the role of diet for health outcomes in cancer survivors. Patients transitioning to post-treatment care may seek guidance on dietary changes, and summaries of the evidence for dietary patterns recommended by guidelines can support providers in effectively answering questions. Increasing evidence suggests that food choices impact planetary health. Plant-based diets are one eating pattern that may improve patient outcomes and planetary health. Methods: We performed a literature review and used narrative reporting to summarize evidence for plant-based diets and offer specific guidance for breast, colorectal, and prostate cancer patients who are post-diagnosis. Specifically, we reviewed impacts on recurrence, all-cause, and cancer-specific mortality. Results: Increased fibre intake by consuming foods like fruits, vegetables, and whole grains is associated with a decreased risk of breast cancer-specific and all-cause mortality, as well as reduced colon cancer-specific mortality. Replacing refined grains with whole grains is associated with improved disease-free survival for colon cancer survivors. Higher tree nut consumption is associated with improved disease-free survival for breast, colorectal, and prostate cancer survivors. Soy is safe to consume for breast cancer survivors and is associated with a reduced risk of recurrence. Conversely, more Western dietary patterns high in processed meat intake are associated with an increased risk of colon cancer recurrence and prostate cancer mortality. There are also environmental benefits of a shift towards plant-based diets to address the adverse health outcomes associated with climate change and its potential impact on cancer care delivery as previously outlined in a 2024 ASCO policy statement. Conclusions: Based on the best existing evidence, providers can suggest that patients consider plant-based dietary patterns in the post-treatment phase of their cancer care to support health outcomes and planetary health. Full article

Background: Climate change is a serious threat to global health. The healthcare sector contributes substantially to greenhouse gas (GHG) emissions, with anaesthetic gases being a major source of Scope 1 emissions. We aimed to evaluate the 2024 impact of the Sustainable Anesthesia Project, designed to reduce the environmental footprint of anaesthetic gases by eliminating and/or replacing the most polluting agents (nitrous oxide and desflurane) with more sustainable alternatives (sevoflurane, total intravenous anaesthesia, and regional/local anaesthesia). Methods: We conducted a descriptive analysis of anaesthetic gas consumption in 2023 and 2024, as well as a comparison of emissions in tons of CO₂, the impact on the carbon footprint, and the potential future emissions savings that full implementation of the project would entail. Results: In the first year, nitrous oxide consumption decreased by 64% and desflurane by 63%. Overall anaesthetic-gas emissions fell by 8386 tCO₂e versus 2023, a 54% relative reduction. Furthermore, the contribution of these gases to the total Scope 1 emissions markedly declined from 35.18% in 2023 to 21.22% in 2024. An additional reduction potential of around 4800 tCO₂e was identified for consolidation by 2025 with full implementation. Conclusions: The results observed in this study demonstrate the success of the Sustainable Anesthesia Project, whose strategy represents an extensible and applicable option to other centers and companies in the health sector to reduce their environmental impact. Full article

Food security and income generation remain a critical issue for small-scale farming households in Sub-Saharan Africa (SSA) due to population growth, climate change, and market instability. Indigenous leafy vegetables (ILVs) offer high nutritional value and have the capability to mitigate food insecurity but are underutilized due to social stigma. This review aims to systematically analyze the food and income contribution of cultivation and utilization of ILVs by small-scale farming households in Sub-Saharan Africa. This review analyses the literature on the role of ILV cultivation in enhancing food security and household income over the past two decades. A systematic search across five databases was conducted and identified 53 relevant studies. Findings indicate that ILVs contribute significantly to household nutrition and income through consumption and surplus sales. However, ILV cultivation faces barriers such as climate change, pest infestations, land degradation, water scarcity, insecure land tenure, limited agricultural training, poor communication networks, and restricted market access. Policy interventions are necessary to support small-scale farmers in ILV cultivation by providing agricultural extension services, promoting sustainable farming practices, and integrating ILVs into food security strategies. Further research should examine policy frameworks and supply chain mechanisms to enhance farmer participation and economic benefits from ILV production. Full article

The quest for environmental sustainability continues to gain prominence, but the environmental goods trade-environmental sustainability nexus has not received adequate research attention. Therefore, this study evaluates the impact of environmental goods trade on environmental performance. Environmental goods (EGs) are defined as products designed to support environmental protection and climate-change mitigation and are identified using the IMF environmental goods classification based on the WTO–OECD list, ensuring cross-country comparability. Using second-generation panel time series methods and the Augmented Anderson–Hsiao (AAH) estimation technique with a sample of 47 Asian countries over the period 1994–2021, this study provides interesting findings and insightful policy implications. First, the findings confirm the EKC Hypothesis in all the models. Second, the results support the pollution halo hypothesis because trade openness has a significant negative impact on the ecological footprint in all the models. This implies that trade openness reduces environmental degradation. Also, the result revealed that an increase in ecological goods reduces ecological footprint in production, consumption, and distribution, as well as imports and exports, based on ecological footprint in Asia. Therefore, we conclude that environmental goods trade enhances environmental sustainability. Full article

Enhanced silicate rock weathering (ESRW) has been proposed as a promising carbon dioxide removal strategy, yet its carbon sequestration pathways, durability, and ecosystem dependence remain incompletely understood. Here, we synthesize evidence from field experiments, observational studies, and modeling to compare ESRW-induced carbon dynamics across forest and cropland ecosystems using a unified SOC–SIC dual-pool framework. Across both systems, ESRW operates through shared geochemical processes, including proton consumption during silicate dissolution and base cation release, which promote atmospheric CO₂ uptake. However, carbon fate diverges markedly among ecosystems. Forest systems, characterized by high biomass production, deep rooting, and strong hydrological connectivity, primarily favor biologically mediated pathways, enhancing net primary productivity and mineral-associated organic carbon (MAOC) formation, while facilitating downstream export of dissolved inorganic carbon (DIC). In contrast, intensively managed croplands more readily accumulate measurable soil inorganic carbon (SIC) and soil DIC over short to medium timescales, particularly under evapotranspiration-dominated or calcium-rich conditions, although SOC responses are often moderate and variable. Importantly, only a subset of ESRW-driven pathways—such as MAOC formation and secondary carbonate precipitation—represent durable carbon storage on decadal to centennial timescales. By explicitly distinguishing carbon storage from carbon transport, this synthesis clarifies the conditions under which ESRW can contribute to climate change mitigation and highlights the need for ecosystem-specific deployment and monitoring strategies. Full article

This study is an economic evaluation of a composting facility in southeastern Spain (applying Life Cycle Costing), a key region in European horticulture with a significant availability of agricultural biomass. Composting helps reduce dependence on inorganic fertilizers, aligning with European policies that promote the transition toward organic fertilization practices. In addition, compost enhances soil health, increases soil organic carbon, and supports climate change mitigation. Despite its agronomic and environmental benefits, and the large availability of biomass in this region, there is a notable lack of literature addressing the economic costs of composting, which is the first step in assessing the sustainability of a production process. The proposed facility (production: 9000 tonnes of compost per year) utilizes pruning residues and manure to produce high-quality organic amendments. The analysis includes infrastructure, equipment, and every operational input. Likewise, the analysis also provides socio-economic indicators such as employment generation and contribution to the regional economy. Three scenarios were evaluated based on the pruning–shredding location: at the plant, at the farm with mobile equipment, and at the farm with conventional machinery. The most cost-effective option was shredding at the farm using mobile equipment, reducing the unit cost to EUR 65.19 per tonne due to the transport of a smaller volume of prunings and, therefore, lower fuel consumption. The plant also demonstrates high productivity per square metre and generates stable employment in rural areas. Overall, the findings highlight composting as a viable and competitive strategy within circular and low-carbon agricultural systems. Full article

Sustainability in the agri-food sector has become a cornerstone of global efforts to combat climate change, ensure food security through climate-smart agriculture, and strengthen economic resilience. Sustainability reporting within agri-food systems has gained increasing regulatory significance with the introduction of mandatory frameworks such as the Turkish Sustainability Reporting Standards (TSRSs). This article searches for the sustainability reports of agri-business firms listed in BIST in Turkey. Although TSRS reporting is not yet mandatory for the agribusiness sector, this study examines the first TSRS-aligned sustainability reports published by eight agri-food companies, excluding the retail sector. The analysis assesses how effectively these reports address sector-specific environmental and social challenges defined in the GRI 13 Agriculture, Aquaculture and Fishing Sector Standard and their alignment with the United Nations Sustainable Development Goals (SDGs). Using a structured content analysis approach, disclosure patterns were examined at both thematic and company levels. The findings indicate that TSRS-aligned reports place strong emphasis on environmental and climate-related disclosures, particularly emissions, climate adaptation and resilience, water management, and waste. In contrast, agro-ecological and land-based impacts—such as soil health, pesticide use, and ecosystem conversion—are weakly addressed. Economic disclosures are predominantly framed around climate-related financial risks and supply chain traceability, while social reporting focuses mainly on occupational health and safety, employment practices, and food safety, with limited attention to labor and equity issues across the broader value chain. Company-level results reveal marked heterogeneity, with internationally active firms demonstrating deeper alignment with GRI 13 requirements. From an SDG alignment perspective, high levels of coverage are observed across all companies for SDG 13 (Climate Action), SDG 12 (Responsible Consumption and Production), and SDG 6 (Clean Water and Sanitation). By contrast, SDGs critical to agro-ecological integrity and social equity—namely SDG 1 (No Poverty), SDG 2 (Zero Hunger), SDG 10 (Reduced Inequalities), and SDG 15 (Life on Land)—are weakly represented or entirely absent. Overall, the results suggest that while TSRS-aligned reporting enhances transparency in climate-related domains, it achieves only selective alignment with the SDG agenda. This underscores the need for a stronger integration of sector-specific sustainability priorities into mandatory sustainability reporting frameworks. Full article

Against the backdrop of global climate change and China’s “dual-carbon” goals, carbon emissions from the construction phase of transportation infrastructure, particularly the rapidly expanding railway network, have garnered significant attention. However, systematic research and general evaluation models targeting the factors influencing carbon emissions during the railway bridge construction phase remain insufficient. To address this gap, this study presents a novel low-carbon evaluation model that integrates the analytic network process (ANP) and the fuzzy comprehensive evaluation (FCE) method. First, a carbon accounting model covering four stages—material production, transportation, construction, and maintenance—is established based on life cycle assessment (LCA) theory, providing a data foundation. Second, an innovative low-carbon evaluation index system for railway bridges, comprising 5 criterion layers and 23 indicator layers, is constructed. The ANP method is employed to calculate weights, effectively capturing the interdependencies among indicators, while the FCE method handles assessment ambiguities, forming a comprehensive evaluation framework. A case study of the bridge demonstrates the model’s effectiveness, yielding an evaluation score of 82.38 (“excellent” grade), which is consistent with expert judgement. The ranking of indicator weights from the model is highly consistent with the actual carbon emission inventory ranking (Spearman coefficient of 0.714). Key indicators—C21 (use of high-performance materials), C22 (concrete consumption), and C25 (transportation energy consumption)—collectively account for approximately 60% of the total impact, accurately identifying the major emission sources. This research not only verifies the model’s efficacy in pinpointing critical carbon sources but also provides a scientific theoretical basis and practical tool for low-carbon decision-making and optimization in the planning and design stages of railway bridge projects. Full article

Existing office buildings in Australia contribute to 24% of the nation’s electricity consumption and 10% of greenhouse gas emissions, with energy use projected to rise by 84%. Meeting the 2050 sustainability target and United Nations (UN) 17 Sustainable Development Goals (SDGs) requires improving sustainability within existing office buildings. This systematic review examines net zero energy and climate resilience strategies in these buildings by analysing 74 studies from scholarly literature, government reports, and industry publications. The literature search was conducted across Scopus, Google Scholar, and Web of Science databases, with the final search in early 2025. Studies were selected based on keywords and research parameters. A narrative synthesis identified key technologies, evaluating the integration of net zero principles with climate resilience to enhance energy efficiency through HVAC modifications. Technologies like heat pumps, energy recovery ventilators, thermal energy storage, and phase change materials (PCMs) have been identified as crucial in reducing HVAC energy usage intensity (EUI). Lighting control and plug load management advancements are examined for reducing electricity demand. This review highlights the gap between academic research and practical applications, emphasising the need for comprehensive field studies to provide long-term performance data. Current regulatory frameworks influencing the net zero transition are discussed, with recommendations for policy actions and future research. This study links net zero performance with climate adaptation objectives for existing office buildings and provides recommendations for future research, retrofit planning, and policy development. Full article

Air conditioners are a critical adaptation measure against heat- and cold-related risks under climate change. However, their electricity use and refrigerant leakage increase greenhouse gas (GHG) emissions. This study developed a data-driven life-cycle assessment (LCA) framework for residential room air conditioners in Japan by integrating large-scale field operation data with life-cycle climate performance (LCCP) modeling. We aggregated 1 min records for approximately 4100 wall-mounted split units and evaluated the 10-year LCCP across nine climate regions. Using the annual operating hours and electricity consumption, we classified the units into four behavioral quadrants and quantified the life-cycle GHG emissions and parameter sensitivities for each. The results show that the use-phase electricity dominated the total emissions, and that even under the same climate and capacity class, the 10-year per-unit emissions differed by roughly a factor of two between the high- and low-load quadrants. The sensitivity analysis identified the heating hours and the setpoint–indoor temperature difference as the most influential drivers, whereas the grid CO₂ intensity, equipment lifetime, and refrigerant assumptions were of secondary importance. By replacing a single assumed use scenario with empirical profiles and behavior-based clusters, the proposed framework improves the representativeness of the LCA for air conditioners. This enabled the design of cluster-specific mitigation strategies. Full article