Search Results (1,097)

Human activities and economic development require large amounts of water and energy. The analysis of the nexus between water and energy flows can improve the understanding of the quantitative relationship between the two resources and guide actions and policies to obtain better results with lower risks. This article aimed to analyse and evaluate the use of rainwater in urban environments and its relationship with the water–energy nexus through a literature review. The PRISMA guidelines were used to structure the research, and the RStudio programme was used for the bibliometric analysis. A total of 118 articles published between 2013 and 2023 were identified in the Scopus and Web of Science databases, of which 30 met the eligibility criteria and were included in the review. The risk of bias in the studies included was assessed by two independent reviewers, and disagreements were resolved by consensus. The results were synthesized in a narrative and descriptive way, and organized in a table containing the authors, year, country, and main findings. The studies were grouped according to the theme addressed and the results related to the use of rainwater and the water–energy nexus were compared. The results indicate that the main use of rainwater is for non-drinkable purposes, to reduce the demand for potable water, lessen the pressure on water resources and contribute to environmental sustainability. Climate change can affect rainfall regimes and, consequently, the feasibility of systems. By decentralizing water supply services, the use of rainwater can save drinking water. When assessing energy savings, the use of rainwater is not always the best option, as system configurations and pump specifications are determining factors. Regarding the environmental impacts, all stages of the urban water cycle consume energy for their operation, and the environmental impact is directly related to the energy source used. Policies and regulations focused on rational use, water conservation, demand reduction, and tax incentives for the installation of rainwater harvesting systems, together with awareness campaigns, are necessary for the widespread adoption of rainwater harvesting systems. Finally, there is consensus regarding saving drinking water, but there is still a lack of studies and specifications regarding energy savings. The findings highlight the need for future longitudinal and simulation-based studies to strengthen knowledge of water–energy nexus dynamics in buildings. Full article

Sustaining agricultural economic performance under climate and market disruptions has become a strategic priority for developing economies facing escalating climate risks and persistent rural development challenges. Using an unbalanced panel of 281 prefecture-level cities in China (2011–2023), this study examines the association between the Digital Village Pilot policy and relative agricultural economic performance (RAEP)—a city’s agricultural growth measured against the national agricultural benchmark, which captures the resistance dimension (whether a city maintains its agricultural-economic position during disruptions) rather than the recovery, adaptability, ecological, or household-livelihood dimensions of the broader resilience concept—through difference-in-differences estimation, Hansen panel threshold regression, and a two-step channel analysis. The results indicate that the Pilot is associated with a statistically significant improvement in relative agricultural economic performance, an effect that remains broadly stable across specification checks. A threshold pattern emerges: the estimated policy association is negligible in city-year observations where digital infrastructure falls below an identified cutoff but rises substantially above it. Because a large share of cities falls below this threshold, the program’s benefits remain unevenly distributed. Channel analysis reveals that the Pilot is associated with a marginally significant increase in digital financial inclusion and a significant reduction in agricultural agglomeration, with the latter reflecting a shift toward diversified rather than spatially concentrated agricultural activity, a pattern theoretically linked to greater shock resistance. These findings advance understanding of how digital rural policies affect relative agricultural economic performance and provide empirical evidence for identifying the enabling conditions under which digital transformation strengthens sustainable agriculture. Full article

Climate change is expected to significantly alter hydrological regimes in high-altitude tropical basins, where water availability strongly depends on precipitation variability and groundwater processes. The Ramis River basin, a major tributary of Lake Titicaca in the Peruvian Altiplano, is particularly vulnerable to hydroclimatic variability due to its dependence on seasonal water resources. This study evaluates the impacts of climate change on runoff, groundwater recharge, percolation, and renewable water resources using the SWAT hydrological model calibrated and validated for the period 1981–2024. Future projections were developed using the MPI-ESM-MR and ACCESS1-0 global climate models under RCP 4.5 and RCP 8.5 scenarios for the period 2025–2100, applying bias correction through CMhyd. The results indicate a strong sensitivity of basin hydrology to climate forcing. Under the MPI-ESM-MR model, runoff decreases by up to 68% under RCP 4.5, while extreme increases exceeding 130% are projected under RCP 8.5. In contrast, ACCESS1-0 shows moderate reductions in most scenarios. Renewable water resources exhibit a general declining trend (−23% to −41%), suggesting increasing water scarcity conditions. Additionally, the Standardized Precipitation Index (SPI) reveals a higher frequency and persistence of drought events toward the end of the century, particularly under high-emission scenarios. Overall, the findings indicate that the Ramis River basin may face a dual hydroclimatic risk characterized by reduced water availability and increased hydrological extremes. These results highlight the need to integrate climate projections into water resource management and to implement adaptive strategies to reduce future water vulnerability in high-Andean basins. Full article

Climate change affects all sectors, with a particularly significant impact on agricultural production. Therefore, agricultural production must adapt to these changes, and adaptive strategies for managing agricultural production should be applied. This research evaluates which adaptive strategies yield the best results in agricultural production in Bosnia and Herzegovina and Serbia through expert decision-making. In doing so, the interval type-2 fuzzy set (IF2S) is applied, using symmetric fuzzy numbers through the membership function. The results obtained by applying IF2S M-SiWeC (Modified Simple Weight Calculation) show that the criteria of the greatest importance are yield stability and climate risk reduction. The ranking of the six selected adaptive strategies is carried out using the IF2S MABAC (Multi-Attributive Border Approximation area Comparison) method, which indicates that agricultural production diversification and adaptive water management strategies provide the best results according to expert assessments. These results are confirmed by additional analyses, including comparative analysis and sensitivity analysis. The contribution of this research is reflected in proposing guidelines on the adaptive strategies that should be applied in practice in agricultural production in order to reduce the negative effects of climate change. Full article

Extreme flooding has emerged as a major climate risk for low-lying Australian macadamia (Macadamia spp.) orchards, yet the physiological mechanisms underlying tree decline remain poorly understood. We investigated whole-plant responses to complete submergence in young, grafted macadamia trees by subjecting plants to one- and two-week floods, as well as repeated flooding. Following emergence from the flood water, photosynthetic rate (A) and stomatal conductance (g_s) declined progressively with increased flood duration and repeated exposure. Grafted plants of G on H2 maintained a more resilient photosynthetic apparatus post-flood than G grafted on Beaumont, as reflected by a smaller decline in maximum assimilation rates as well as biochemical capacities for ribulose 1,5 bisphosphate (RuBP) carboxylation (V_cmax), and RuBP regeneration (J_max). Despite these differences in leaf-level function, prolonged and repeated flooding triggered a cascade of post-flood stress symptoms in both rootstocks, including progressive canopy dieback, sharp reductions in root biomass, depletion of total non-structural carbohydrates, and ultimately scion mortality. Collectively, these findings indicate that plants only partially tolerated one week of complete submergence, whereas longer or repeated flooding severely compromised carbon balance and plant survival in both rootstocks. Full article

In the highly climate- and ecology-sensitive eastern margin of the Qinghai–Tibet Plateau (QTP), understanding the adaptation behaviors of agro-pastoralists is crucial for reconfiguring human–climate–ecosystem interactions. However, existing studies often overlook the bounded rationality of micro-level decision-makers. Based on behavioral decision theory, this study constructs a “Perception–Capital–Adaptation” analytical framework. Utilizing micro-survey data from 890 agro-pastoralist households and employing Multinomial Logit (MNL) and Ordinary Least Squares (OLS) models, this paper systematically explores how environmental risk perception and livelihood capital are jointly associated with livelihood strategy choices and land-use behaviors. The findings reveal that (1) risk perception exhibits significant heterogeneity: sudden risks show a strong association with risk-avoidance transitions, whereas gradual risks often manifest as traditional livelihood lock-in due to “cognitive lag.” (2) The moderation of capital exhibits non-linear characteristics: physical and natural capital correspond to path dependence on existing production, while financial capital may be associated with expansionary behaviors, reflecting “maladaptation” in specific contexts. (3) Their interaction corresponds to a duality of adaptation pathways: a coordinated pathway (balancing ecological conservation and livestock reduction) and a conflictive pathway (maintaining production scale). Accordingly, a “risk-capital” trade-off matrix is constructed to identify four typical adaptation patterns: risk-avoidance transformation, path-dependent persistence, resilience-driven expansion, and fragile maintenance. This study demonstrates that climate adaptation essentially reflects the dynamic trade-offs made by boundedly rational actors between cognitive constraints and capital structures, providing a novel micro-behavioral perspective for avoiding maladaptation. Full article

Glacial lake outburst floods (GLOFs) are a major cryosphere-related hazard in High Mountain Asia (HMA), where glacier mass loss and changing hydroclimatic conditions are reshaping glacial-lake systems and increasing the prevalence of potentially unstable lake–dam configurations. However, current knowledge remains fragmented across HMA. Therefore, this review synthesizes historical evidence, future changes, and risk-reduction strategies of GLOFs across HMA from a remote-sensing perspective. Historical evidence derived from satellite archives, multi-temporal lake inventories, geomorphological analyses, and documented event records indicate that reported GLOFs in HMA are strongly clustered by sub-region and dam type, with moraine-dammed lakes representing the dominant source of documented events, while ice-dammed lakes remain important in several mountain belts. The compiled record also shows that GLOFs have caused severe human, economic, geomorphic, and ecological losses. Future projections based on glacier evolution, glacial-lake expansion, and climate-sensitive hazard assessments indicate continued glacial-lake growth under global warming. However, reliable prediction of future GLOF event timing, magnitude, and frequency remains constrained by uncertainties in glacier evolution, dam stability, and triggering processes. This review further shows that effective GLOF risk reduction in HMA requires integrated systems that combine hazard and risk mapping, early warning, structural interventions, and non-structural measures. It also highlights the need to better link remote sensing with monitoring, assessment, and implementation frameworks, and proposes an integrated management cycle to support practical risk reduction. It concludes that the most urgent research priorities are harmonized multi-temporal lake inventories, targeted field observations, explicit consideration of heatwaves and compound extremes, transparent uncertainty propagation, and stronger operationalization of monitoring and warning systems to support durable climate adaptation and disaster risk reduction across HMA. Full article

Due to global change and the associated increase in climate hazards, the study of ecosystem services and their potential to reduce disaster risk has gained relevance in recent years. However, access to ecosystem services is not evenly distributed, leading to environmental injustice. Currently, there is no commonly accepted approach to simultaneously integrate ecosystem services and environmental justice into the risk assessment equation (risk = hazard × exposure × vulnerability). In this study, a framework was developed that integrates ecosystem service assessment into the vulnerability component using InVEST models, which was applied to the case study of Valencia, Spain. The approach applied here not only allowed visualising risk reduction through ecosystem services but also identified a robust synergy between heatwave and flood mitigation as well as mismatches between socioeconomic vulnerability and ecosystem service provision, with foreign residents being at a disadvantage in Valencia. The practical application of this framework in urban planning was shown by comparing the results of the risk assessment of the existing land use conditions with three hypothetical future scenarios. The results support the current municipal ambitions of urban greening in Valencia, while highlighting the need to consider socioeconomic vulnerability in decision-making. Full article

Urban pluvial flood risk in industrial zones is intensifying under climate change, yet the joint influence of digital elevation model (DEM) resolution, surface roughness heterogeneity, and infiltration capacity on simulation accuracy remains insufficiently characterized. This study presents a comprehensive sensitivity analysis combining five DEM resolutions (0.5, 1, 2, 5, and 10 m), six rainfall scenarios (10- to 200-year return periods plus the observed event of 10 July 2024), and three infiltration rates (5, 10, and 20 mm h⁻¹), yielding 90 simulation cases executed with the open-source GPU solver SynxFlow on an NVIDIA A100 80GB GPU. A spatially distributed Manning’s roughness field (n_M = 0.013–0.100 s m^−1/3) was derived from the Ministry of Environment land cover product, replacing the conventional uniform-roughness assumption. Model performance was assessed against seven validation gauges (five flooded, two no-flood controls) compiled from contemporaneous news reports, using the 25 m × 25 m patch-maximum simulated depth at each gauge and probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI). The 0.5 m baseline achieved POD = 0.80, FAR = 0.20, and CSI = 0.67 at the 5 cm depth threshold. Coarsening the grid reduced peak depth by up to 37% and flooded area by 5%, with the most rapid degradation occurring between 2 m and 5 m. A 2 m grid retained area error within 2% and volume error within 1% while delivering an approximately 33-fold runtime reduction relative to the 0.5 m baseline; the 10 m grid achieved up to ~1400× speedup, spanning three orders of magnitude across the resolution range. Resolution sensitivity intensified under higher rainfall and lower infiltration, confirming that “adequate” resolution is conditional on event severity. A tiered resolution selection matrix linking application scale, target accuracy, and computational cost is proposed to support evidence-based flood adaptation planning for industrial zones. Full article

This systematic review examines the global sustainable urban planning strategies used worldwide and whether they are applicable to the United Arab Emirates. This study reviewed 150 peer-reviewed articles and identified 14 of the most significant sustainable urban planning strategies in use today, including green infrastructure, smart city technologies, compact urban development, transit-oriented development, circular economy principles, mitigation of urban heat island effects, renewable energy integration, sustainable drainage systems, biophilic design, fifteen-minute city concepts, mixed-use development, vertical farming, participatory planning, and urban resilience frameworks. The methodologies applied by the authors to identify the sustainable urban planning strategies employed in the research were thematic analysis and the classification of the strategies into five main categories: environmental sustainability, technological innovation, social equity, economic viability, and cross-cutting. Case studies from Singapore, Copenhagen, Melbourne, and Amsterdam, and examples of current sustainable urban planning initiatives underway in Dubai and Abu Dhabi show how the models can be successfully implemented. The results indicate that multi-strategy approaches produce better results than the application of single strategies. Based on the results of the research, green infrastructure, smart city technologies, and the mitigation of urban heat island effects have been identified as strategies whose characteristics are closely aligned with the UAE’s arid climate conditions, while emphasizing that all fourteen strategies contribute to comprehensive sustainability outcomes and that their relative importance depends on local relevance. The researchers also concluded that for sustainable urban planning to be successful in the UAE, it will require the best practices from around the world be adapted to the unique environmental conditions, cultural contexts, and economic structures of each country. The findings of this study will contribute to the growing body of knowledge related to sustainable urbanism and provide practitioners with useful information and practical guidance when implementing sustainable urban planning practices in the UAE and other arid regions. Full article

Climate change is emerging not only as a threat to global food production but also as a major driver of declining nutritional quality in food crops. Throughout this review, terms such as nutrient decline, imbalance, and nutritional quality changes are used to describe relative changes in the nutritional attributes of edible crop tissues, as reported in the source studies. Elevated atmospheric CO₂, altered rainfall patterns, shifts in solar radiation, and rising temperatures influence soil processes, plant metabolism, and genotype × environment interactions that determine nutrient composition and density. Evidence from controlled experiments, free-air CO₂ enrichment (FACE) studies, field trials, and meta-analyses suggests a recurrent tendency toward reduced concentrations of essential macronutrients and micronutrients, including protein, iron, zinc, and selected B-vitamins in a range of cereals, legumes, and horticultural crops, while responses remain context-dependent and are not universally observed across all nutrients, cultivars, or production systems. These reductions raise serious concerns for populations already experiencing widespread micronutrient deficiencies. This review synthesizes the current knowledge on the extent and mechanisms of climate-driven nutrient decline across major crops, highlighting variability among species, cultivars, and production environments. We also evaluate the potential health consequences, particularly heightened risks of anemia, impaired immunity, developmental challenges, and other deficiency-related disorders. Regions such as South Asia, Southeast Asia, and Sub-Saharan Africa are identified as highly vulnerable due to their strong dependence on nutrient-poor staples and existing burdens of hidden hunger. Furthermore, we assess key mitigation and adaptation pathways, including agronomic innovations, climate-smart agricultural practices, biofortification, advanced breeding strategies, and the emerging use of microbial and cyanobacterial biostimulants to enhance nutritional resilience in cropping systems. Finally, this review provides an integrated synthesis of climate-induced nutrient decline, its health implications for vulnerable populations, and priority actions needed to protect global food and nutrition security in the face of accelerating climate change. Full article

This study examines the evolution of thermal discomfort in Athens, Greece, using Thom’s Discomfort Index (TDI). The research commences from a historical reference period (1976–2005) and examines two future periods (2031–2060 and 2071–2100). TDI, which combines air temperature and relative humidity, was calculated based on three-hourly projections of five EURO-CORDEX regional climate models under the RCP4.5 and RCP8.5 emission scenarios. Model outputs were bias-corrected using observational data from the National Observatory of Athens for the reference period and subsequently applied to future projections. Results indicate a clear upward trend in high thermal discomfort days in the city center. Under RCP4.5, intense discomfort days increase by 21–39 days by mid-century and by approximately 1–2 months by the end of the century. Under the high-emission RCP8.5 scenario, the increase becomes dramatic, with intense discomfort conditions potentially extending by up to three months annually. Overall, projections reveal a clear deterioration of thermal conditions with a difference between RCP 4.5 and RCP 8.5, highlighting the critical importance of emission reduction strategies. The study of TDI shows that climate change does not merely raise temperatures, but drastically increases perceived discomfort and heat-related risk, transforming long parts of the year into thermally uncomfortable periods. Full article

Compound and consecutive extreme events are increasingly understood as key contributors to climate risk, as their interactions can intensify impacts beyond those produced by individual hazards alone threatening the long-term sustainability of regional infrastructure. Compound coincident events involve multiple climate drivers or hazards that occur simultaneously or in close temporal proximity, exhibiting overlapping spatial and temporal characteristics. For assessing multi-hazards, information on critical thresholds of the events investigated (extreme precipitation and wind gusts in the presented study) is key, as is the time frame needed to determine the probability of event B after an event A. As this data is location-specific, stakeholder integration provides a potential tool for gathering this information to enable socially robust disaster risk management. The presented study displays a potential interdisciplinary approach to how multi-hazards and their occurrence can be investigated locally. Therefore, stakeholder integration is combined with climate model output and a copula-based analysis of compound coincident and consecutive extreme daily wind and precipitation events for the Salzburg region under different climate change scenarios (SSP1-2.6, SSP5-8.5). Through stakeholder integration, relevant thresholds and potential time frames were identified. Our findings indicate that the thresholds critical to the considered assets (properties, transport, energy) are well aligned between different stakeholders; however, the time frame of increased vulnerability due to a previous event differs strongly between them. Compared to the baseline scenarios, the ranges within the climate model used for rainfall and wind speed intensity under SSP1-2.6 and SSP5-8.5 scenarios are examined, and, for rainfall, have expanded to greater values for both compound coincident and consecutive events, highlighting challenges and future research needs for sustainable adaptation and regional policy. Full article

Against the backdrop of the “dual carbon” goals, carbon emission trading prices serve as a core signal of market operational efficiency. Accurately predicting carbon prices facilitates scientific decision-making, and model optimization is key to improving prediction accuracy. This study takes five major carbon trading pilots in China—Shenzhen, Guangdong, Hubei, Beijing, and Shanghai—as the research objects. An indicator system is constructed from four dimensions: macroeconomy, energy prices, climate and environment, and international markets. The Least Absolute Shrinkage and Selection Operator (LASSO) algorithm is employed to identify the key influencing factors of carbon prices across different markets. Among them, “WTI crude oil price” and “EUA futures closing price” are consistently significant factors common to all five pilots. On this basis, four models—Autoregressive Integrated Moving Average with Exogenous Variables (ARIMAX), Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), and Transformer—are constructed for multi-method prediction comparison. The results show that ARIMAX and GRU achieve the best prediction performance among the four models. To further enhance prediction accuracy, hybrid optimization models are respectively developed: Support Vector Regression (SVR) is used to optimize the nonlinear residuals of ARIMAX (SVR-ARIMAX), and Genetic Algorithm (GA) is used to optimize the key hyperparameters of GRU (GA-GRU). The hybrid models significantly reduce prediction errors in most markets. Specifically, SVR-ARIMAX shows particularly notable improvements in Beijing and Hubei, while GA-GRU outperforms standard GRU in Guangdong, Shenzhen, Shanghai, and Hubei. Based on the optimized models, 12-month-ahead forecasts indicate that the Shenzhen market exhibits high volatility and greatest uncertainty; Guangdong remains relatively stable; Hubei, Beijing, and Shanghai are characterized by narrow-range fluctuations. The findings provide empirical support for corporate emission reduction decision-making, carbon market risk management, and price mechanism improvement. Full article

Green roofs offer significant potential for urban stormwater management, yet their capacity to improve runoff water quality is constrained by the limited pollutant retention of conventional substrates and inherent nutrient leaching risks. This critical review synthesizes recent advances in substrate engineering and phytoremediation to establish an integrated framework for transforming green roofs into active bio-filtration systems. Our analysis reveals that amending conventional substrates with waste-derived biosorbents substantially enhances heavy metal and nutrient retention through complementary mechanisms of surface complexation, ion exchange, and microprecipitation. When strategically coupled with hyperaccumulator plant species and rhizospheric microbial communities, these amended substrates significantly reduce contaminant loads in urban runoff while maintaining hydraulic functionality. We critically evaluate standard growing media versus substrates amended with targeted biosorbents: biochar, which enhances heavy metal retention and hydraulic conductivity via surface complexation; seaweed biomass, which provides superior water retention and cation exchange while reducing synthetic fertilizer dependence; and chitin-rich crab shell waste, which promotes microprecipitation of metals and phosphates while valorizing marine waste. The novelty resides not in the materials themselves, but in their synergistic combination and the systematic comparative analysis of their retention mechanisms under green roof hydrological conditions. This review further identifies critical engineering trade-offs, including biosorbent-induced hydraulic conductivity reductions and long-term adsorption site saturation, and provides actionable design thresholds for amendment dosing, substrate depth, and species selection. Ultimately, this work establishes a mechanistic and practical roadmap for next-generation green roofs that simultaneously optimize stormwater retention, runoff quality, and circular economy valorization, highlighting priority research directions for long-term field validation and climate-adaptive standardization. Full article