Search Results (3,146)

Urban regeneration interventions extend beyond the renewal of physical building stock and the improvement of living conditions, as they also reshape local microclimatic conditions. This study examines changes in Surface Urban Heat Island (SUHI) patterns within an urban regeneration area in Istanbul, Türkiye, using multi-temporal remote sensing data. Landsat imagery from 2019, 2020, 2022, and 2023 was used to derive Land Surface Temperature (LST), the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Built-up Index (NDBI), and SUHI intensity. Pearson correlation analysis, Getis–Ord Gi* hot spot analysis, and zonal statistics were applied to evaluate statistical relationships, spatial clustering, and local thermal changes within the regeneration areas. The findings show that urban regeneration did not produce a uniform thermal response. Demolition reduced built-up intensity, whereas redevelopment of previously vegetated or open parcels increased impervious surface cover and limited vegetation recovery. Correlation results revealed strong negative associations between NDVI and both LST and SUHI, while NDBI was positively associated with these thermal variables, indicating that land-cover composition was strongly associated with local thermal conditions. Overall, the study demonstrates that renewing building stock alone may not be sufficient to ensure improvement in the urban thermal environment. Strengthening green infrastructure, expanding permeable surfaces, and embedding climate-responsive planning measures into regeneration strategies are therefore critical. The results also indicate that multi-temporal remote sensing, combined with spatial statistics and zonal assessment, provides an effective decision-support framework for monitoring SUHI dynamics and evaluating the environmental performance of urban regeneration initiatives. Full article

HVAC control trades energy against thermal comfort, complicated by two building features: thermal mass spreads a setpoint change over hours, and the input-to-outcome mapping shifts across the year. Model-free algorithms such as PPO, SAC, and TD3 carry no model of building dynamics and cannot evaluate a setpoint’s downstream effect. We apply a Latent Dynamics Learning and Planning (LDLP) framework that learns a latent model of the building’s thermal response and plans with Monte Carlo Tree Search inside it. We also gate a reward formulation common in prior work, applying its comfort penalty only while the building is occupied. On Sinergym’s 5Zone environment under hot, mixed, and cool climates, LDLP is evaluated against PPO, SAC, TD3 and Sampled EfficientZero, an independent model-based controller run at the same budget. With energy normalized for the comfort achieved, LDLP consumes 4% to 26% less than PPO and SAC under the standard reward and 1% to 19% less under the gated reward. Running the same model with one simulation per decision, which removes planning, multiplies its normalized energy fivefold. Under the gated reward the deterministic TD3 policy degenerates onto a few fixed setpoints, so we report action diversity alongside the conventional metrics. Full article

The European Union’s common climate and energy framework—the Renewable Energy Directives and the European Green Deal—seeks to align national energy systems, yet whether electricity-generation structures converge remains underexplored. Using Eurostat data (SIEC classification), we examine the generation mix of the 27 EU member states over 1990–2024, measured as unweighted country-level source shares, with generation-weighted EU aggregates reported as a complement. We assess diversification (normalized Shannon entropy, the Herfindahl–Hirschman index and the effective number of sources) and convergence (σ- and β-convergence and source-by-source Phillips–Sul log-t club tests computed on source shares, with log-ratio balances used as a robustness check). Mix diversification rises (mean normalized entropy from 0.41 to 0.62) and, as measured by entropy, its levels converge to a single club. Convergence across sources is selective: the shares of the contracting carriers—coal, oil, nuclear and hydro—display σ-convergence, whereas wind, solar and bioenergy form single all-country convergence clubs in relative terms, even as their cross-country dispersion widens. The fossil–nuclear base remains structurally divided: coal fragments into multiple clubs with a divergent group that includes Poland, and nuclear separates member states into nuclear and non-nuclear groups. These patterns emerged during the development of the common EU policy framework; identifying the causal contribution of specific instruments is left for future work. The findings carry implications for security of supply, as exposed during the 2022 energy crisis. Full article

Coastal areas are complex territorial systems where natural processes and anthropogenic pressures interact, generating vulnerable yet culturally significant landscapes. While remaining attractive for tourism and urban development, they are among the areas most exposed to the impacts of climate change, requires resilient and adaptive planning approaches. This study assesses vegetation-related environmental changes associated with the regeneration of the Portici Maritime Park, Italy, through a comparison of Sentinel-2 Normalized Difference Vegetation Index (NDVI) data acquired before and after the intervention. Mean NDVI decreased from approximately 0.245 in 2018 to 0.167 in 2026, indicating a reduction in vegetation-related conditions associated with the conversion of previously vegetated or partially vegetated surfaces into paved areas. Based on this empirical evidence and on the environmental characteristics of the site, the study proposes the integration of Nature-Based Solutions (NBS), including permeable surfaces, Sustainable Urban Drainage Systems (SuDS), multifunctional Mediterranean and halophytic green strips, and ecological nourishment. These measures are framed within the proposed Waterfront 4.0 concept, which integrates ecological regeneration, digital environmental monitoring, participatory governance, and adaptive management. By linking ex-post remote-sensing assessment with NBS-oriented planning, the study provides a conceptual and case-study-based approach for improving the climate resilience and ecological performance of highly urbanized Mediterranean waterfronts. Full article

Groundwater-dependent irrigated agriculture in semi-arid basins is increasingly threatened by climate variability and aquifer depletion. Karapınar district, located within Türkiye’s Konya Closed Basin, represents a water-stressed melon-producing area where deep-well drip irrigation and rigid calendar-based scheduling remain common. This study developed a prototype AquaCrop-based decision-support framework for adapting mature and pickled melon irrigation to climatic conditions classified by the crop-season weighted three-month Standardized Precipitation Index (SPI-3). SPI-3 was selected to represent short-term seasonal precipitation anomalies relevant to agricultural water availability, and three historical years were used as representative scenarios: Dry (2020), Normal (2018), and Wet (2017). Fourteen irrigation treatments, including farmer practice and phenologically targeted Late-Season Event (L.S.E.) deficit strategies, were simulated using FAO AquaCrop v7.1. Irrigation timing was more important than seasonal irrigation volume alone. Under Normal conditions, an L.S.E. strategy that redistributed irrigation toward four late fruit-development events (T4.2) maintained yield stability comparable to farmer practice (CV < 2%), increased mature melon yield by 12.7% relative to farmer practice, and reduced applied irrigation by 19–21%. Under Dry conditions, a lower-volume L.S.E. strategy with the same late-season targeting (T4.3) maintained baseline-level yield while reducing applied irrigation by 28–31%. The resulting SPI-based decision matrix is forecast-compatible but not operationally validated; field validation, long-term climate testing, and forecast-skill evaluation remain necessary before deployment. Full article

The Pinglu Canal, the first river-to-sea canal project since the founding of the People’s Republic of China, reshapes basin-scale ecosystem services by altering land use/land cover, landscape patterns, and soil–water processes. This study assesses spatiotemporal variations in net primary production (NPP), soil conservation, water yield, and nitrogen/phosphorus output in the Pinglu Canal Basin from 2000 to 2024. Hotspot analysis, the interannual fluctuation index, Random Forest and Shapley additive explanations, climate–NPP residual analysis, and Geodetector were integrated. The results indicate that: (1) Over the past 25 years, ecosystem services have generally improved, with NPP increasing significantly and nitrogen/phosphorus outputs declining; northern hilly and low-mountain forests formed stable service supply areas, whereas water yield was more prominent in southern plains and river valleys. Water yield showed the strongest interannual fluctuation, while soil conservation remained relatively stable. (2) Hotspot stability was mainly regulated by population density, normalized difference vegetation index (NDVI), elevation, and precipitation, with evident nonlinear threshold effects. When the NDVI reaches about 0.63, the NPP and nutrient retention capacity are significantly enhanced, indicating that vegetation coverage and community structure can exert their ecological regulation functions effectively after reaching a certain level. (3) During construction, negative NPP disturbances expanded along the canal. The Geodetector results showed that while the explanatory power of population density was enhanced during the construction stage of the Pinglu Canal, precipitation, NDVI, and topographic/hydrothermal conditions remain foundational constraints for ecosystem services spatial differentiation. Furthermore, interactions, such as population–NDVI and population–precipitation, generally manifest as bivariate enhancement. This study supports ecological monitoring, risk warning, and zoned restoration for large linear infrastructure projects. Full article

This study used 30 m Landsat imagery from 1995 to 2020 to investigate vegetation dynamics and their driving factors in Yengisar County, an arid oasis region in northwestern China. The Normalized Difference Vegetation Index (NDVI) was calculated, and the Dimidiate Pixel Model was used to estimate fractional vegetation cover (FVC). Trend analysis and a center-of-gravity migration model were employed to examine the spatiotemporal evolution of vegetation and its responses to climatic and human factors. The results showed that: (1) FVC exhibited clear spatial heterogeneity, with high vegetation coverage mainly distributed along river systems in the southwest and concentric expansion occurring around urban areas in the northeast. (2) From 1995 to 2020, the total vegetated area increased by 409.38 km², representing a 76.4% increase relative to 1995, while the average FVC increased by 15.4%. Except for the extremely low-coverage class, all vegetation classes expanded, with the medium-coverage class showing the largest increase (142.9%). (3) The vegetation center of gravity gradually shifted toward the southeast, and the period from 2015 to 2020 represented the most rapid stage of vegetation improvement. (4) Human activities, particularly agricultural reclamation and grassland expansion, exhibited a strong association with recent vegetation changes and played an important role in the expansion of the artificial oasis. The results indicate that recent oasis expansion in Yengisar County has been closely associated with land-use change and irrigation activities. These findings provide useful information for oasis management, land-use planning, and water resource allocation in arid regions. Full article

Functional trait plasticity enables invasive plant species to establish and persist across diverse environmental conditions. Following the extensive habitat disturbance caused by the 2010 floods in Khyber Pakhtunkhwa, Verbesina encelioides rapidly spread into disturbed and natural habitats. This study evaluated the phenotypic plasticity and biomass allocation traits of Verbesina encelioides across five contrasting habitats (i.e., cropland, roadside, riverside, urban, and abandoned land). Habitat differences were assessed using analysis of variance with Tukey’s HSD post hoc test, while multivariate analysis was used to examine relationships among functional traits, environmental variables, and habitats. Log-transformed data were used for linear regression analyses to satisfy normality assumptions. Plant functional traits varied significantly among habitats, demonstrating substantial phenotypic plasticity. Riverside vegetation had high functional trait plasticity followed by abandoned habitats. In contrast, riverside populations had fewer branches (14.3 ± 1.4), leaves (184.7 ± 10), lower leaf area (5360 ± 77 cm²), and reduced inflorescence biomass (8.61 ± 2.1 g) than abandoned-land populations. Cropland plants were taller (106 ± 3 cm) with heavier seeds (0.30 ± 0.04 g; p < 0.05), whereas roadside plants had smaller leaves (6.1 ± 0.3 cm) but produced more flowers (38.4 ± 6.2; p < 0.001). Biomass allocation remained relatively stable across habitats (p > 0.05), with greater investment in aboveground than belowground structures. Soil texture, organic matter, temperature, and precipitation were the principal environmental variables associated with trait variation, indicating that local environmental conditions strongly influence plant performance (p < 0.05). PCA revealed that seed traits dominated the first axis and were associated with cropland and riversides. Redundancy analysis indicated that soil properties (sand, silt, pH, EC) and climatic factors (precipitation, temperature) significantly influenced trait distribution. Hierarchical cluster analysis shows that riverside was distinct from other clusters both in functional traits and environmental variables. Inter-trait correlation revealed a significant relationship between leaf and seed traits. Overall, these findings reveal that V. encelioides adjusts its growth and reproductive traits according to habitat conditions. Greater seed weight in croplands may enhance seedling establishment under competitive conditions, whereas increased flower production in disturbed roadside habitats may promote dispersal and reproductive success of the plant. The strong functional trait plasticity of V. encelioides across different habitats highlights its potential to persist under habitat disturbance and changing environmental conditions, therefore posing risk to native plant communities and ecosystem structure. These findings support the need for habitat-based monitoring, protection of native flora and restoration of disturbed areas as part of sustainable land and biodiversity management. Full article

This study conceptualizes RE100 not merely as a voluntary corporate campaign, but as an evolving socio-technical system that intersects with South Korea’s path-dependent energy regime. Applying BERTopic to a comprehensive corpus of 21,901 raw news articles (reduced to 13,507 analytically relevant articles after noise filtering; January 2019–October 2025), we trace the systemic evolution and multi-layered governance of RE100. Grounded in social constructionism and institutional systems theory, the research reveals how the global sustainability norm becomes structurally embedded in South Korea’s industrial and economic systems through a partially sequential evolutionary process of externalization, objectivation, and internalization. BERTopic identified 39 analytically meaningful topics, subsequently organized into four interpretive clusters: (1) local government-centered construction, (2) spatial reconfiguration and industrial-policy formation, (3) corporate-led market institutionalization, and (4) ESG-driven corporate governance. Collectively, these clusters demonstrate that RE100 has evolved from a peripheral international initiative into a multilayered governance norm embedded across local governance, industrial infrastructure, corporate strategy, and ESG systems. The findings hold theoretical and policy implications for energy-transition governance and climate communication. This progression is recursive rather than strictly linear: corporate-level internalization (Cluster 4) is conceptually linked to, and may interact with, regional and industrial-policy externalization (Clusters 1–2), consistent with a non-linear reading of institutionalization in which corporate site-selection criteria shape local-government infrastructure competition. Cluster 1’s prominence reflects local governments’ discursive visibility rather than substantive policy authority. Notably, RE100’s “normalization” denotes routinized corporate compliance practices, not political consensus on its legitimacy relative to alternatives such as carbon-free 100% or nuclear power. Full article

A building façade normally keeps the weather out, lets in daylight, allows ventilation, and shapes how a building looks from outside. This study asks whether it can also help generate electricity without giving any of that up. Solar chimney power plants (SCPPs) generate clean electricity from solar heat, but they have mostly been studied for open, land-abundant rural sites. Mounting one onto a façade instead risks the very things a façade is meant to protect: thermal comfort, natural ventilation, and architectural freedom. No prior study has looked at energy output, thermal behaviour, double-skin façade (DSF) operability, and architectural freedom together for solar chimneys integrated into high-rise buildings, and this is the gap this work addresses. We coupled solar chimney power plants with double-skin façades across five configurations, evaluated using Computational Fluid Dynamics (CFD) validated against the Manzanares pilot plant to achieve 3.3% for velocity and 3.0% for temperature. Using the DSF as both collector and absorber (Model 1) pushes power to its highest point, 78.7 kW, but it drives inner-façade air to 327.1 K and shuts off ventilation entirely. Confining the collector to the roof and upper chimney instead (Model 5) settles for a more modest 31.1 kW, but it preserves DSF ventilation over most of the façade height and keeps inner air below 305.8 K through the majority of that range, with only the uppermost portion becoming thermally unsuitable for natural ventilation. Weighing power, thermal load, ventilation, and façade freedom together in a composite score, Model 5 comes out as the preferred configuration under the adopted equal-weight multi-criteria assessment. A parametric study of height, irradiance, and ambient temperature for Model 5 produced design equations that, paired with a Random Forest climate forecast, benchmarked against three alternative algorithms and evaluated on a chronological hold-out set (city-level test R² up to 0.83 for irradiance and 0.94 for temperature), power a predictive framework for hourly-to-annual energy output at any height and city, demonstrated here for seven cities across five continents. Full article

The development of temporally consistent long-term normalized difference vegetation index (NDVI)climate data records is essential for global change and ecosystem research. The Medium Resolution Spectral Imager-II (MERSI-II) sensor aboard China’s Fengyun-3D (FY-3D) satellite shares similar spectral characteristics with Moderate Resolution Imaging Spectroradiometer (MODIS), offering potential for synergistic applications. However, systematic biases arising from differences in sensor design, radiometric calibration, and atmospheric correction hinder their direct combination. This study established a full-chain framework that integrated cross-calibration of surface reflectance using quasi-synchronous FY-3D/MODIS observations and a MERSI-II-specific atmospheric correction scheme based on the 6S radiative transfer model. After correction, the FY-3D NDVI shows substantially improved consistency with MODIS, achieving a reduction in root mean square error of over 25.9%, an increase in correlation coefficient of approximately 5%, and a decrease in mean absolute error of about 40%. Spatial biases are within ±0.1 over most global land areas, with robust performance across vegetation types and climate zones. Based on this technical framework, a fused FY-3D and MODIS NDVI climate data record was established, which has been operationalized at the Beijing Climate Center for global vegetation monitoring. This work provides a transferable framework for integrating Chinese Fengyun satellite data with international datasets like MODIS/VIIRS. Full article

A cradle-to-gate life-cycle assessment (LCA) was conducted for an activated adsorbent produced from the non-metallic fraction (NMF) of waste printed circuit boards. The primary production reference was 1 kg of dry activated non-metallic fraction (ANMF) produced. Cradle-to-gate production impacts were subsequently normalized using previously reported equilibrium adsorption capacities for Pb²⁺, Cu²⁺, and Zn²⁺ to obtain performance-normalized production impacts per kilogram of theoretical metal uptake. Environmental impacts were quantified using the ReCiPe 2016 Midpoint (H) method together with cumulative energy demand (CED). Production of 1 kg of ANMF resulted in a climate change (CC) impact of 5.77 kg CO₂-eq and a CED of 140.03 MJ. After adsorption-capacity normalization, the CC impacts were 8.44, 31.35, and 43.05 kg CO₂-eq kg⁻¹ metal uptake, while the corresponding CED values were approximately 205, 761, and 1045 MJ kg⁻¹ metal uptake for Pb²⁺, Cu²⁺, and Zn²⁺, respectively. Commercial activated carbon (AC) exhibited slightly lower production impacts, but its lower representative Pb²⁺ adsorption capacity resulted in substantially higher normalized production burdens. These normalized indicators represent cradle-to-gate production impacts scaled by adsorption performance and do not include wastewater-treatment use-stage operations, regeneration, or management of spent adsorbent. The results demonstrate that adsorption performance substantially influences the interpretation of production-related environmental burdens and should therefore complement conventional mass-based assessment of adsorbents. Full article

Vegetation dynamics are highly sensitive to climate variability and constitute a key indicator of ecosystem condition, particularly in arid and semi-arid environments where field observations are often limited. This study investigated the spatiotemporal dynamics of vegetation and their relationships with climatic factors in the Quaraqum Watershed during 2001–2022 using multi-source remote sensing datasets. Vegetation dynamics were characterized using the Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery, Land Surface Temperature (LST) was obtained from MODIS products, and precipitation data were obtained from the CHIRPS dataset. Spatial and temporal patterns and trends were examined using Geographic Information System (GIS) techniques, while the relationships between NDVI and climatic variables were quantified using Pearson correlation and multiple linear regression analyses. The results revealed a pronounced west-to-east decrease in precipitation accompanied by increasing temperature across the watershed. Annual precipitation reached maximum values of 389.20 mm in 2019 and 370.79 mm in 2009, whereas the lowest values, 172.50 mm and 171.50 mm, were recorded in 2008 and 2021, respectively. Spring was the wettest season, whereas summer was the driest. Vegetation cover was highest in spring and exhibited an increasing long-term trend, while autumn and winter showed the lowest vegetation cover and declining trends. Correlation analysis revealed a strong positive relationship between NDVI and precipitation and a weaker negative relationship between NDVI and LST. These results suggest that precipitation availability was more strongly associated with vegetation variability than thermal conditions. Multiple regression analysis further indicated that precipitation was the primary climatic variable explaining annual NDVI variability, while the inclusion of LST did not substantially increase the explained variance of the model. Overall, these findings highlight the dominant role of moisture availability in shaping vegetation dynamics in the Quaraqum Watershed, with thermal conditions representing an additional environmental factor affecting vegetation responses. Full article

Climate variability can affect forage production through changes in temperature, precipitation, and the frequency of stressful weather conditions. We examined climatic variability and alfalfa (Medicago sativa L.) productivity in three Romanian development regions—South-Muntenia, South-East, and North-East—over 2006–2024. The climatic variables included mean, maximum, and minimum air temperature, annual precipitation, and maximum 24 h precipitation. Regional relationships between climatic variables and alfalfa yield were examined using descriptive statistics, Kendall’s rank-based trend analysis with Sen’s slope, Pearson correlation, and multiple linear regression with diagnostic testing. We also developed an exploratory Alfalfa Climate Resilience Index (ACRI) to compare relative climate-resilience profiles of regional alfalfa production systems. The index combines two performance-related components, normalized mean yield and yield stability, with two climatic-context components, normalized precipitation and inverse normalized mean temperature. Its sensitivity to alternative component weights was also evaluated. Mean annual temperature increased significantly in all regions, with Sen’s slopes ranging from +0.071 to +0.100 °C year⁻¹, whereas annual precipitation showed no significant monotonic trend. Yield slopes were negative in all regions, but only North-East showed a statistically significant decline (τ = −0.794, p < 0.001). Mean annual temperature was negatively correlated with yield in all three regions (r = −0.617 to −0.749), whereas the precipitation indicators showed no significant bivariate relationships with yield. The regional multiple regression models accounted for 64.3–85.1% of the observed variation in annual yield (R² = 0.643–0.851), with the relative importance and statistical significance of climatic predictors differing among regions. ACRI ranked North-East first (0.760), South-Muntenia second (0.469), and South-East third (0.295), and this ordering remained unchanged across the alternative weighting scenarios examined. These scores represent relative differences among the three regional production systems within the study dataset and should not be interpreted as absolute measures of intrinsic alfalfa resilience. The findings show that climate–yield relationships vary among regions and that temperature was more consistently associated with yield than the precipitation indicators considered here. ACRI is therefore presented as an exploratory, dataset-dependent framework for within-dataset comparison of regional alfalfa production-system climate resilience and requires validation using broader reference datasets, common normalization criteria, and additional management and environmental variables before wider application. Full article

The active development of the foothill areas of the Almaty agglomeration (Southeastern Kazakhstan) requires reliable methods for landslide susceptibility assessment. This study aims to identify the spatial association between landslide occurrence and selected environmental and anthropogenic factors using the Frequency Ratio (FR) method and geographic information systems. The analysis is based on an inventory of 157 landslides, the SRTM digital elevation model, Landsat imagery, WorldClim climate data, geological maps, and OpenStreetMap data. Ten conditioning factors were analyzed: elevation, slope, aspect, precipitation, lithology, distance to faults, rivers and roads, the Normalized Difference Vegetation Index (NDVI), and land use. FR values were calculated for each factor and integrated to produce a landslide susceptibility map. Model performance was evaluated using Receiver Operating Characteristic (ROC) analysis and the Area Under the Curve (AUC). The resulting susceptibility map identifies areas with different levels of landslide susceptibility and provides a scientific basis for sustainable land-use planning, engineering-geological investigations, safer infrastructure development, natural hazard assessment, and disaster risk reduction in rapidly developing foothill regions. By supporting risk-informed land-use decisions and targeted mitigation measures, the study contributes to the long-term environmental safety and resilience of the Almaty agglomeration. Full article