Search Results (678)

Green buildings are recognised for their potential to reduce energy consumption, minimise environmental impact, and improve occupants’ well-being, benefits that are especially critical in rapidly urbanising regions. However, questions remain about whether these buildings fully meet occupant comfort expectations while delivering energy efficiency. This is particularly relevant in Africa, where climate conditions and energy infrastructure challenges make sustainable building operation essential. Although interest in sustainable construction has increased, limited research has examined the real-world performance of green buildings in Africa. This study helps address that gap by evaluating indoor thermal comfort in a green-certified office building and two conventional office buildings in Abuja, Nigeria, through post-occupancy evaluation (POE). The Predicted Mean Vote (PMV) and Thermal Sensation Vote (TSV) were used to assess comfort, revealing discrepancies between predicted and actual occupant responses. In the green building, PMV indicated near-neutral conditions (0.28), yet occupants reported a slightly cool sensation (TSV: −1.1). Neutral temperature analysis showed that the TSV-based neutral temperature (26.5 °C) was 2.2 °C higher than the operative temperature (24.3 °C), suggesting overcooling. These findings highlight the importance of incorporating occupant feedback into HVAC control. Aligning cooling setpoints with comfort preferences could improve satisfaction and reduce unnecessary cooling, promoting energy-efficient building operation. Full article

Against the backdrop of multifaceted strategies to combat climate change, understanding soil erosion’s role in carbon cycling is critical due to terrestrial carbon pool vulnerability. This study integrates bibliometric methods with visualization tools (CiteSpace, VOSviewer) to analyze 3880 Web of Science core publications (1994–2024, inclusive), constructing knowledge graphs and forecasting trends. The results show exponential publication growth, shifting from slow development (1994–2011) to rapid expansion (2012–2024), aligning with international climate policy milestones. The Chinese Academy of Sciences led productivity (519 articles), while the US demonstrated major influence (H-index 117; 52,297 citations), creating a China–US bipolar research pattern. It was also found that Dutch journals dominate this research field. A keyword analysis revealed a shift from erosion-driven carbon transport to ecosystem service assessments. Emerging hotspots include microbial community regulation, climate–erosion feedback, and model–policy integration, though developing country collaboration remains limited. Future research should prioritize isotope tracing, multiscale modeling, and studies in ecologically vulnerable regions to enhance global soil carbon management. This study provides a novel analytical framework and forward-looking perspective for the soil erosion research on soil carbon cycling, serving as an extension of climate change mitigation strategies. Full article

Urban metabolism frameworks offer insight into flows of energy, materials, and services in cities, yet tree species selection is seldom treated as a metabolic indicator. In Amman, Jordan, we integrate spatial metabolic metrics to critique monocultural greening policies and demonstrate how species choices forecast long-term urban metabolic performance. Using ENVI-met 5.61 simulations, we compare Melia azedarach, Olea europaea, and Ceratonia siliqua, mainly assessing urban flow related elements like air temperature reduction, CO₂ sequestration, and evapotranspiration alongside rooting depth, isoprene emissions, and biodiversity support. Melia delivers rapid cooling but shows other negatives like a low biodiversity value; Olea offers average cooling and sequestration but has allergenic pollen issues in people as a flow; Ceratonia provides scalable cooling, increased carbon uptake, and has a high ecological value. We propose a metabolic reframing of green infrastructure planning to choose urban species, guided by system feedback rather than aesthetics, to ensure long-term resilience in arid urban climates. Full article

The Qinghai–Tibet Plateau, a region susceptible to global change, stores substantial amounts of soil organic carbon (SOC) in its alpine grassland. However, little is known about how SOC is regulated by soil microbial communities, which vary with elevation, mean annual temperature (MAT), and mean annual precipitation (MAP). This study integrates phospholipid fatty acid (PLFA) analysis to simultaneously resolve microbial biomass, community composition, and membrane lipid adaptations along an elevational gradient (2861–5090 m) on the Qinghai–Tibet Plateau. This study found that microbial PLFAs increased significantly with rising MAP, while the relationship with MAT was nonlinear. PLFAs of different microbial groups all had a positive effect on SOC storage. At higher altitudes (characterized by lower MAP and lower MAT), Gram-positive bacteria dominated bacterial communities, and fungi dominated the overall microbial community, highlighting microbial structural adaptations as key regulators of carbon storage. Saturated fatty acids with branches of soil microbial membrane dominated across sites, but their prevalence over unsaturated fatty acids decreased at high elevations. These findings establish a mechanistic link between climate-driven microbial community restructuring and SOC vulnerability on the QTP, providing a predictive framework for carbon–climate feedbacks in alpine systems under global warming. Full article

Quantifying long-term variations in the cloud liquid water path (LWP) is crucial to obtain a better understanding of the processes relevant to cloud–climate feedback. The 12-year (2013–2024) time series of LWP values obtained from ground-based measurements by the RPG-HATPRO radiometer near the Gulf of Finland is analysed, and the linear trends of the LWP for different sampling subsets of data are assessed. These subsets include all-hour, daytime, and night-time measurements. Two different approaches have been used for trend assessment, which produced similar results. Statistically significant linear trends have been detected for most data subsets. The most pronounced general trend over the period 2013–2024 has been detected for the daytime LWP, and it constitutes −0.0011 ± 0.00015 kg m⁻² yr⁻¹. This trend is driven mainly by the daytime LWP trend for the warm season (May–July, −0.0014 ± 0.00015 kg m⁻² yr⁻¹), which is considerably larger than the trend for the cold season (November–January, −0.00064 ± 0.00026 kg m⁻² yr⁻¹). Additionally, the analysis shows that the absolute number of clear-sky measurements decreased approximately by a factor of 4 if the years 2013 and 2024 are compared. Full article

Forest drought monitoring tools are crucial for managing tree water stress and enhancing ecosystem resilience. The Forest Drought Response Index (ForDRI) was developed to monitor drought conditions in forested areas across the contiguous United States (CONUS), integrating vegetation health, climate data, groundwater, and soil moisture content. This study evaluated ForDRI using Pearson correlations with the Bowen Ratio (BR) at 24 AmeriFlux sites and Spearman correlations with the Tree-Ring Growth Index (TRSGI) at 135 sites, along with feedback from 58 stakeholders. CONUS was divided into four forest subgroups: (1) the West/Pacific Northwest, (2) Rocky Mountains/Southwest, (3) East/Northeast, and (4) South/Central/Southeast Forest regions. Strong positive ForDRI-TRSGI correlations (ρ > 0.7, p < 0.05) were observed in the western regions, where drought significantly impacts growth, while moderate alignment with BR (R = 0.35–0.65, p < 0.05) was noted. In contrast, correlations in Eastern and Southern forests were weak to moderate (ρ = 0.4–0.6 for TRSGI and R = 0.1–0.3 for BR). Stakeholders’ feedback indicated that ForDRI realistically maps historical drought years and recent trends, though suggestions for improvements, including trend maps and enhanced visualizations, were made. ForDRI is a valuable complementary tool for monitoring forest droughts and informing management decisions. Full article

Accurate, energy-efficient climate regulation is crucial for scaling smart greenhouse production. While nonlinear model predictive control (NMPC) can co-optimize yield and resource use, its efficacy hinges on short-range weather information and real-time solver feasibility. This paper investigates the performance of advanced NMPC strategies for smart greenhouse climate control, with particular emphasis on the roles of AI-driven disturbance prediction and warm-start initialization for real-time optimization. Six controller configurations, including feedback-only, LSTM-based forecast, and ideal disturbance models, each with and without warm-start, were tested in a 40-day simulation of a lettuce smart greenhouse. Performance metrics included final biomass, constraint violations, resource costs, profit, and solver time. Results show that feedback-only controllers maximize yield and profit, incurring higher CO₂ costs but lower heating costs, alongside greater constraint violations compared to the predictive strategies. Predictive and ideal disturbance-aware controllers effectively reduce resource consumption and improve constraint compliance at the expense of lower yields. Importantly, warm-start initialization significantly accelerates computation without affecting control quality. The study also demonstrates that penalty parameters, rather than economic weight settings, predominantly determine aggregate constraint violation. The findings provide actionable insights for designing and deploying NMPC-based greenhouse controllers, highlighting the importance of warm-start techniques and the trade-offs between productivity, resource efficiency, and environmental compliance. Full article

Urban vegetation shows significant spatial differences due to the combined effects of natural and human factors, yet fine-scale evolutionary patterns and their cross-scale feedback mechanisms remain limited. This study focuses on the Yangtze River Delta (YRD), the top economic area in China. By integrating data from multiple Landsat sensors, we built a high—resolution framework to track vegetation dynamics from 1990 to 2020. It generates annual 30-m Enhanced Vegetation Index (EVI) data and uses a new Vegetation Green—Brown Balance Index (VBI) to measure changes between greening and browning. We combined Mann-Kendall trend analysis with machine—learning based attribution analysis to look into vegetation changes across different city types and urban—rural gradients. Over 30 years, the YRD’s annual EVI increased by 0.015/10 a, with greening areas 3.07 times larger than browning. Spatially, urban centers show strong greening, while peri—urban areas experience remarkable browning. Vegetation changes showed a city-size effect: larger cities had higher browning proportions but stronger urban cores’ greening trends. Cluster analysis finds four main evolution types, showing imbalances in grey—green infrastructure allocation. Vegetation baseline in 1990 is the main factor driving the long-term trend of vegetation greenness, while socioeconomic and climate drivers have different impacts depending on city size and position on the urban—rural continuum. In areas with low urbanization levels, climate factors matter more than human factors. These multi-scale patterns challenge traditional urban greening ideas, highlighting the need for vegetation governance that adapts to specific spatial conditions and city—unique evolution paths. Full article

Against the backdrop of the profound restructuring in global climate governance, China’s energy management system is undergoing a comprehensive transition from dual energy consumption control to dual carbon emissions control. This policy shift fundamentally alters the underlying logic of energy-focused regulation and inevitably impacts the economy–energy–environment (3E) system. This study innovatively constructs a “Triangular Trinity” theoretical framework integrating internal, intermediate, and external triangular couplings, as well as providing a granular analysis of their transmission relationships and feedback mechanisms. Using Guangdong Province as a case study, this study takes the dual control emissions policy within the external triangle as an entry point to research the restructuring logic of dual carbon emissions control for the coupling coordination mechanisms of the 3E system. The key findings are as follows: (1) Policy efficacy evolution: During 2005–2016, dual energy consumption control significantly improved energy conservation and emissions reduction, elevating Guangdong’s 3E coupling coordination. Post 2017, however, its singular focus on total energy consumption revealed limitations, causing a decline in 3E coordination. Dual carbon emissions control demonstrably enhances 3E systemic synergy. (2) Decoupling dynamics: Dual carbon emissions control accelerates economic–carbon emission decoupling, while slowing economic–energy consumption decoupling. This created an elasticity space of 5.092 million tons of standard coal equivalent (sce) and reduced carbon emissions by 26.43 million tons, enabling high-quality economic development. (3) Mechanism reconstruction: By leveraging external triangular elements (energy-saving technologies and market mechanisms) to act on the energy subsystem, dual carbon emissions control leads to optimal solutions to the “Energy Trilemma”. This drives the systematic restructuring of the sustainability triangle, achieving high-order 3E coupling coordination. The Triangular Trinity framework constructed by us in the paper is an innovative attempt in relation to the theory of energy transition, providing a referenceable methodology for resolving the contradictions of the 3E system. The research results can provide theoretical support and practical reference for the low-carbon energy transition of provinces and cities with similar energy structures. Full article

Understanding how wetland changes affect near-surface humidity is essential for evaluating their climate-influencing functions, especially in mid- and high-latitude regions. Here, using multi-source remote sensing data, we investigated the impacts of wetland area changes and leaf area index (LAI) on 2 m specific humidity (2m SH) within the China side of the Heilongjiang River Basin (CHRB) from 2003 to 2020 across latitudinal gradients and seasonal scales. The results indicated that the wetland area initially decreased and then increased, while the LAI rose by 0.015/year. A significant positive correlation was identified between wetland coverage and 2m SH, with a threshold of 60%. A transition point at 50°N was observed in the response of humidity to wetland area changes, shifting from an increase to a decrease in humidity. The Wetland LAI Change Humidity Index increased with latitude from 2003 until 2010, significantly decreasing thereafter (R² = 0.634, p < 0.05). Seasonally, the humidifying effect strengthened with latitude in spring and autumn, with a strong negative correlation observed in autumn between 2003 and 2010 (R² = 0.789, p < 0.001). These findings deepen the understanding of wetland–humidity interactions and provide a scientific basis for wetland conservation and regional climate adaptation, supporting SDG13. Full article

Drought, an increasingly prevalent climate stressor due to global warming, profoundly impacts agricultural systems, particularly the soil microbiome. Soil microorganisms are crucial for nutrient cycling, plant health, and ecosystem stability; however, drought-induced changes disrupt microbial community structure, function, and interactions with plants. This review synthesizes current knowledge on the effects of drought on soil microbiomes, with a focus on microbial diversity, resilience, and functional shifts in agricultural contexts. It highlights key microbial mechanisms underpinning plant drought tolerance, including symbioses with plant growth-promoting bacteria and fungi. Furthermore, it addresses knowledge gaps in the long-term effects of repeated drought events, microbial adaptations, and plant–soil feedback mechanisms. By advancing our understanding of drought–microbiome dynamics, this review aims to inform sustainable agricultural practices and resilience strategies to mitigate the adverse impacts of drought on crop productivity and ecosystem health. Full article

As climate change intensifies the frequency and magnitude of extreme weather events, such as storm surges, understanding how extreme weather events alter mangrove carbon dynamics is critical for predicting the resilience of blue carbon ecosystems under climate change. Mangrove forests are generally recognized for their resilience to natural disturbances, a characteristic largely attributed to the evolutionary development of species-specific functional traits. However, limited research has explored the impacts of storm surges on carbon flux dynamics in both natural and restored mangrove ecosystems. In this study, we analyzed short-term responses of storm surges on carbon dioxide flux and methane flux in natural and restored mangroves. The results revealed that following the storm surge, CO₂ uptake decreased by 51% in natural mangrove forests and increased by 20% in restored mangroves, while CH₄ emissions increased by 14% in natural mangroves and decreased by 22% in restored mangroves. GPP is mainly driven by PPFD and negatively affected by VPD and RH, while Reco and CH₄ flux respond to a combination of temperature, humidity, and hydrological factors. NEE is primarily controlled by GPP and Reco, with environmental variables acting indirectly. These findings highlight the complex, site-specific pathways through which extreme events regulate carbon fluxes, underscoring the importance of incorporating ecological feedbacks into coastal carbon assessments under climate change. Full article

Global climate change has intensified the heterogeneity of precipitation regimes in subtropical regions, and the increasing frequency of extreme drought events poses a significant threat to biogeochemical cycling in forest ecosystems. Yet, the pathways by which reduced precipitation regulates deadwood decomposition and thereby influences soil nutrient pools remain poorly resolved. Here, we investigated a Cunninghamia lanceolata (Lamb.) Hook. plantation in subtropical China under ambient precipitation (CK) and precipitation reduction treatments of 30%, 50%, and 80%, systematically examining how reduced precipitation alters the chemical properties of deadwood substrates and, in turn, soil nutrient status. Our findings reveal that (1) as precipitation declined, soil water content decreased significantly (p < 0.01), while deadwood pH declined and total organic carbon (TOC), nonstructural carbohydrates (NSCs), and lignin content markedly accumulated (p < 0.01); (2) these shifts in deadwood chemistry affected feedback mechanisms, leading to the suppression of soil nutrient pools: extreme drought (80% reduction) significantly reduced soil TOC, dissolved organic carbon (DOC), total nitrogen (TN), and total phosphorus (TP) (p < 0.01) and inhibited N and P mineralization, whereas the 30% reduction treatment elicited a transient increase in soil microbial biomass carbon (MBC), indicative of microbial acclimation to mild water stress; and (3) principal component analysis (PCA) showed that the 80% reduction treatment drove lignin accumulation in deadwood, while the 30% reduction treatment exerted the greatest influence on soil DOC, TOC, and MBC; partial least squares path modeling (PLS-PM) further demonstrated that soil water content and deadwood substrate properties (pH, lignin, soluble sugars, TOC, C/N, and lignin/N) were strongly negatively correlated (r = −0.9051, p < 0.01), and that deadwood chemistry was, in turn, negatively correlated with soil nutrient variables (pH, TOC, DOC, MBC, TP, TN, and dissolved organic nitrogen [DON]; r = −0.8056, p < 0.01). Together, these results indicate that precipitation reduction—by drying soils—profoundly modifies deadwood chemical composition (lignin accumulation and NSC retention) and thereby, via slowed organic-matter mineralization, constrains soil nutrient release and accumulation. This work provides a mechanistic framework for understanding forest carbon–nitrogen cycling under climate change. Full article

To better understand the temperature changes in face slab concrete and address challenges such as delayed curing and outdated methods in complex and variable environments, this study investigates the use of visualization and real-time feedback control in concrete construction. The conducted study systematically develops an intelligent curing control system for face slab concrete based on multi-source measured data. A tailored multi-source data acquisition scheme was proposed, supported by an IoT-based transmission framework. Cloud-based data analysis and feedback control mechanisms were implemented, along with a decoupled front-end and back-end system platform. This platform integrates essential functions such as two-way communication with gateway devices, data processing and analysis, system visualization, and intelligent curing control. In conjunction with the ongoing Maerdang concrete face rockfill dam (CFRD) project, located in a high-altitude, cold-climate region, an intelligent curing system platform for face slab concrete was developed. The platform enables three core visualization functions: (1) monitoring the pouring progress of face slab concrete, (2) the early warning and prediction of temperature exceedance, and (3) dynamic feedback and adjustment of curing measures. The research outcomes were successfully applied to the intelligent curing of the Maerdang face slab concrete, providing both theoretical insight and practical support for achieving scientific and precise curing control. Full article

Groundwater plays an important role in areas facing water scarcity, which can cause many problems if poorly managed. In Northern Cyprus, in the Güzelyurt region, where agriculture is thriving, excessive and inappropriate groundwater use has caused a sharp decrease in water levels and electrical conductivity in many coastal areas. This study explores this problem using system dynamics tools designed to analyze feedback loops and causal links. The qualitative system dynamics approach is employed to investigate complex systems by focusing on structural and behavioral patterns through qualitative elements such as feedback loops, causal relationships, and system archetypes, rather than relying solely on numerical data. For this purpose, group model building is used, for which a basic model is built using library studies, and then the model is developed and improved through numerous interviews and meetings held with policymakers, farmers, soil and water managers, university professors, and representatives from the local community. The study examines water management practices, including transferring water from Turkey to Northern Cyprus and allocating a portion for agricultural use in Güzelyurt. It also explores agricultural strategies and the employment of advanced irrigation methods. In the tourism and urban consumption sectors, raising public awareness and educating citizens about water scarcity linked to climate change are highlighted as essential measures in promoting sustainable water usage. Full article