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

Organic matter enrichment in marine–continental transitional shales is influenced by volcanism, continental weathering, and paleoceanographic evolution, but their interactions during the Late Paleozoic Ice Age (LPIA) remain unclear. Mineralogical, elemental, and organic geochemical data from the Upper Carboniferous Yanghugou Formation, western Ordos Basin, were used to reconstruct volcanic input, weathering intensity, productivity, redox conditions, and organic carbon accumulation. High Hg/TOC, Zr/Al₂O₃, and Zr/Cr ratios indicate strong volcanic input during early deposition, followed by an upward decline. Chemical Index of Alteration values of 76.5–91.5 increase upward, indicating intensified chemical weathering under warmer and more humid conditions. Increasing C_org/P, Mo_EF, and U_EF values record a shift from oxic–suboxic to predominantly anoxic bottom waters. The weak relationship between productivity proxies and TOC suggests that volcanic fertilization was not the main control on organic matter enrichment. Instead, negative δ¹³C_org values, high Al₂O₃ contents, organic matter–clay associations, and reducing conditions indicate that enhanced terrestrial organic matter input and improved preservation jointly promoted organic carbon accumulation. Volcanism likely intensified climatic warming and weathering, whereas subsequent organic carbon burial contributed to atmospheric CO₂ drawdown and climatic feedbacks during the LPIA. Full article

The rapid transition toward electrified mobility and climate neutrality has prioritized the structural and environmental optimization of battery electric vehicle (BEV) subsystems. While vehicle lightweighting enhances operational efficiency, the production phase of structural enclosures and battery cells frequently introduces severe environmental and economic impacts and supply chain vulnerabilities. This study presents a comprehensive cradle-to-gate environmental life cycle assessment (LCA), life cycle costing (LCC), and semi-quantitative social assessment of alternative battery housing materials and battery cell architectures. To achieve a functionally accurate comparison, alternative materials, including a novel recyclable thermoplastic acrylic sheet molding compound (SMC), commercial thermoset SMCs, aluminum (AlMg₃), and stainless steel, are evaluated using an analytical stiffness- and strength-equivalent methodology across three real-world geometric demonstrators. Simultaneously, lithium iron phosphate (LFP) liquid electrolyte prismatic cells and solid-state polymer pouch cells are assessed. Material-level results indicate that, while aluminum minimizes the structural mass, primary aluminum manufacturing exhibits the highest global warming potential and processing costs. Conversely, Polytec SMC and Elium SMC achieve the lowest environmental impacts alongside competitive total production costs. At the cell level, prismatic LFP architectures display superior environmental performance compared to solid-state pouch cells, which suffer from energy-intensive processing and lower volumetric capacity normalization. Demonstrator-level aggregation reveals that the electrochemical cells heavily dominate the environmental and economic footprint of the complete assembly, with the housing accounting for less than 5% of the total global warming potential (GWP) and 1% of the total costs. The social assessment reveals moderate and comparable performance across all systems, with slight advantages for thermoplastic composite-based configurations in terms of circularity potential and innovation perception. Overall, the study highlights the critical importance of the cell architecture and manufacturing processes in determining battery system sustainability, while demonstrating the relevance of lightweight composite housings in reducing the structural mass with a minimal environmental penalty. Full article

Large mineral flotation workshops in severe cold regions represent special industrial indoor environments characterized by the coexistence of limited ventilation and intense heat release. Such conditions generate pronounced spatial thermal stratification and localized heat accumulation within the workshop, leading to uneven worker thermal exposure and increased thermal discomfort and heat stress risk. However, conventional thermal comfort models were primarily developed for ordinary buildings with relatively stable thermal environments. Their applicability to large industrial workshops remains insufficiently validated. Nine representative monitoring points were arranged in the summer operating areas of the workshop, and thermal comfort surveys were conducted among 35 workers who had adapted to the local climate and working environment. The predicted mean vote (PMV) model was used as the baseline assessment framework, while an adaptive predicted mean vote (aPMV) model was further calibrated using field-based thermal sensation information. Monte Carlo simulation was employed to evaluate uncertainty propagation under field-data constraints, and Sobol sensitivity analysis was conducted to identify the dominant factors affecting thermal comfort predictions. The results demonstrated that the conventional PMV model exhibited a clear warm prediction bias under the investigated industrial conditions. After adaptive correction, the deviation from the field-based TSV was reduced by 82.93%, indicating improved agreement with workers’ actual thermal perception. Sensitivity analysis identified metabolic rate as the dominant contributor to aPMV output variance, with first-order and total-effect Sobol indices of 0.530 and 0.535. The proposed framework provides a scenario-specific approach for thermal comfort assessment in the investigated flotation workshop and offers preliminary methodological references for similar large-scale flotation workshops. Full article

Soil organic carbon (SOC) stocks are strongly influenced by land use, vegetation condition and climate, particularly in heterogeneous mountain catchments. This study quantified SOC stocks and simulated long-term SOC dynamics in the Çapakçur micro-catchment, eastern Türkiye, by integrating field assessment, geostatistical prediction, uncertainty analysis, inverse RothC calibration and scenario modelling. A total of 428 soil samples were collected from the 0–30 cm layer across forest, degraded forest, and pasture areas. SOC stocks were calculated from SOC concentration, bulk density and soil depth, and spatially predicted using ordinary kriging of log-transformed SOC stocks. RothC was calibrated for each land-use class to estimate the annual carbon inputs required to maintain observed SOC stocks, followed by 50-year restoration and climate-sensitivity simulations. SOC stocks ranged from 7.69 to 247.68 Mg C ha⁻¹, averaging 55.52 Mg C ha⁻¹. Forest had the highest mean SOC stock (78.5 Mg C ha⁻¹), followed by pasture (55.9) and degraded forest (50.2 Mg C ha⁻¹). Required annual carbon inputs were 5.17, 4.58 and 3.29 Mg C ha⁻¹ yr⁻¹, respectively. Increasing degraded forest carbon inputs to forest-equivalent levels increased SOC by 14.76 Mg C ha⁻¹ over 50 years, equivalent to 37.77 Gg C or 138.49 Gg CO₂eq at the catchment scale. A stronger restoration scenario increased this potential to 63.77 Gg C. Warming caused SOC losses, with +2 °C reducing catchment SOC by 56.78 Gg C. These findings demonstrate the potential of degraded forest restoration for SOC sequestration while highlighting the vulnerability of long-term SOC gains to climate warming. Full article

The growing environmental impact of the construction sector is driving a shift toward sustainable design practices, in which digital technologies are integrated to enable designers to make informed decisions from the early design stages. In this study, a DSS is developed that combines BIM, VPL and TPL to identify the optimal wall stratigraphy for the building envelope. The process is structured into sequential phases, in which Autodesk Revit v2026.06.24.01, Dynamo v.3.6.1 and Python v3.9 are integrated within an end-to-end workflow. In the first phase, wall stratigraphies are modelled in BIM, and parametric variations in layers are allowed alongside customisation of the material database. In the second phase, an automated workflow calculates a set of indicators covering thermal performance, environmental assessments (LCA, MRc2 LEED and mandatory national requirements), and economic evaluations (LCC). In the third phase, indicators are imported into an automated Dynamo-based MCDM, where a hybrid AHP/PROMETHEE analysis is applied and results are directly integrated into BIM, thereby supporting sustainability-focused decisions. The tool is validated on different sustainable wall stratigraphies in warm-climate contexts. The hybrid solution is ranked first, followed by rammed earth, while platform frame and X-LAM are ranked lower. Full article

Although climate warming affects photosynthetic carbon sequestration in coastal wetland plants, the seasonality of this effect has not been assessed. We investigated the growth traits and photosynthetic properties of Phragmites australis by using open-top chambers (OTCs) to conduct a warming experiment in the coastal wetlands of the Yellow River Delta during a single growing season. The OTCs significantly elevated temperatures by ~1 °C across the growing season, and the effects of warming on stem diameter, net photosynthetic rate (P_n), and water use efficiency (WUE) were characterized by a significant month × warming interaction. Early-season carboxylation efficiency (φ) increased by 71%, but a significant late-season decline of P_n by 49% accompanied by a rise of intercellular CO₂ concentrations (C_i) and decline of stomatal limitation (L_s) led to a seasonal shift from stomatal to non-stomatal (biochemical) limitation of growth. A consistent increase in plant height and C_i across all months and concomitant decrease in L_s indicated that the additive effects of warming were independent of phenological stage. The results revealed that the phenological mediation of warming responses is trait specific. Carbon cycle models should therefore adopt trait-specific parameterizations to accurately project the impact of the wetland carbon sink under future warming. Full article

As a globally climate-sensitive region and ecological security barrier, the spatiotemporal dynamics of net ecosystem productivity (NEP) on the Qinghai–Tibetan Plateau are of great significance for understanding carbon cycling in alpine ecosystems. However, due to insufficient representation of parameter heterogeneity in models and unclear nonlinear attribution of complex environmental factors, substantial uncertainties remain in the spatiotemporal patterns and driving mechanisms of NEP in this region. Therefore, this study first employed an improved Carnegie–Ames–Stanford Approach (CASA) model to assess NEP on the Qinghai–Tibetan Plateau from 2000 to 2022 and characterize its spatiotemporal evolution, and subsequently applied the optimal multivariate-stratification geographical detector (OMGD) to quantify the independent and synergistic driving effects of hydrothermal conditions, extreme climate events, and human activities on NEP variations. The results indicate that: (1) from 2000 to 2022, vegetation NEP on the Qinghai–Tibetan Plateau exhibited a southeast-to-northwest decreasing spatial heterogeneity pattern, with a multi-year mean value of 219.61 g C·m⁻²; (2) during the study period, NEP showed an overall increasing trend (at a rate of 1.596 g C·m⁻²·yr⁻¹), with 52.5% of the region experiencing significant increases, primarily concentrated in the central–eastern humid regions and alpine meadow areas; and (3) among individual factors, the growing season length was the primary driver of NEP, in addition to temperature and precipitation, while human activities exerted negligible influence; under interaction effects, the hydrothermal synergistic enhancement (0.79 < q < 0.89) exhibited the highest explanatory power. These results show that carbon sequestration in alpine ecosystems is governed by nonlinear hydrothermal interactions and provide a scientific basis for assessing carbon sink resilience in the “Asian Water Tower” under global warming. Full article

Stored-product insects threaten global food security, yet the environmental mechanisms governing their responses to climate change remain poorly understood. Existing pest distribution projections rarely integrate diurnal thermal variability with agricultural land use. Here, we show that diurnal thermal variability, together with agricultural land use, is a major determinant of habitat suitability for three globally important Callosobruchus pests across the Middle East. Using optimized species distribution models integrating climate, topography, and cropland under contrasting CMIP6 climate scenarios, we demonstrate that mean diurnal temperature range and cropland consistently emerge as the strongest predictors across all species, revealing the importance of daily thermal fluctuations beyond mean warming alone. Under the low-emission scenario (SSP1-2.6), suitable habitat by mid-century expands substantially for C. chinensis and C. phaseoli, while remaining little changed overall for C. maculatus, for which comparable local expansion and contraction largely offset one another; under the high-emission scenario (SSP5-8.5), gains are reduced, and localized contractions occur, particularly for C. chinensis and C. maculatus, the latter shifting to a slight net loss in total suitable area. Persistent climatic refugia remain along Mediterranean and Red Sea coastal regions, whereas habitat losses are concentrated in the northern Gulf lowlands and Zagros foothills. Our findings identify diurnal thermal variability as an overlooked dimension of stored-product pest ecology and show that integrating agricultural landscapes with climate projections can improve forecasts of future pest risk, providing a framework for climate-informed surveillance, biosecurity, and adaptation. Full article

Climate change drives shifts in forest vegetation zones, and the major tree species of warm–temperate evergreen broad-leaved forests in South Korea are also expected to undergo changes in their potential distributions under future climate conditions. This study applied a Committee Averaging (CA) ensemble species distribution model to Quercus acuta, Machilus thunbergii, Quercus glauca, and Castanopsis sieboldii to project changes in their potential distributions under four Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) across two future periods (2050s and 2090s). To compare interspecific differences in response more clearly, we applied a two-tier threshold scheme that distinguished potential habitat (agreement ≥0.6) from highly suitable habitat (>0.8), and we concurrently conducted a Multivariate Environmental Similarity Surface (MESS) analysis to assess predictive uncertainty arising from extrapolation into future climates. The CA ensemble models showed excellent predictive performance (AUC 0.947–0.989; TSS 0.837–0.943). For Q. acuta, M. thunbergii, and Q. glauca, potential habitat expanded consistently across all SSP scenarios, and highly suitable habitat shifted northward into parts of the central and Gangwon regions. In contrast, both the potential habitat and the highly suitable habitat of C. sieboldii contracted under most future scenarios. These results demonstrate that even species belonging to the same warm–temperate evergreen broad-leaved forest community can respond differently to future climate. The two-tier threshold scheme applied in this study was effective not only for assessing whether distributions expand but also for delineating and evaluating climatically stable core habitats. Although our findings need to be interpreted in light of the uncertainty associated with extrapolation into future climates, they can serve as useful baseline data for establishing climate-change-adaptive forest conservation and species-specific management strategies. Full article

East Asia is both the densest subsystem of the global liner shipping network and the home basin of its signature hazard, the typhoon. This study quantifies the relationship in both directions, as a stress test of the sustainability of maritime connectivity, across Alphaliner-based reconstructions of the 2017 and 2021 networks that cover every port with at least one scheduled liner service. A Typhoon Vulnerability Index built from validated IBTrACS exposure, betweenness sensitivity, and national adaptive capacity scores 330 and 272 affected ports. The risk geography anchors in East Asia in both years and more strongly in the second, as the regional share of affected ports is 29 percent in 2017 and 44 percent in 2021, the 2017 top five are all East Asian, and the 2021 top four are all Chinese, led by Shanghai. Removing every indexed typhoon port in descending risk order destroys 47.5 and 41.3 percent of baseline efficiency. Equal-sized random removals destroy a similar share at the end, so the information of the hazard ordering lies earlier and elsewhere, in early losses that run about forty percent above the random expectation, in seven of the ten earliest failures being invisible to degree screening, and in the identity of the removed ports, while equal-depth-degree targeting destroys far more at every stage. An East Asia-only attack reproduces a third of the full attack’s damage in 2017 and half in 2021. Under one fixed baseline, East Asia carries 23.8 and 24.6 percent of global efficiency before the attack and its survivors retain 7.1 and 3.6 percent after it. On the evidence of these two years, the typhoon corridor is a jointly held systemic asset, its protection is a problem shared by the three economies, and the bidirectional accounting gives sustainable maritime transport a measurable resilience baseline under a warming climate. Full article

Chikungunya is undergoing global expansion, but how El Niño–Southern Oscillation (ENSO) influences its transmission remains unclear. We aim to assess the impact of ENSO phases on chikungunya incidence via temperature and precipitation teleconnections and to project future risk burden under climate change. We compiled annual national and subnational chikungunya case data (2008–2024), quantified ENSO–climate teleconnections using the E-index (eastern Pacific El Niño) and C-index (central Pacific La Niña), and applied distributed-lag time-series models to assess the teleconnection-mediated impact of ENSO on chikungunya incidence. We further projected future risk burden under climate change scenarios. Modelling shows that El Niño increased chikungunya risk after a 2-year lag (cumulative relative risk [CRR] = 1.40, 95% confidence interval [CI]: 1.02–1.85), while La Niña suppressed it (CRR = 0.09, 95% CI: 0.07–0.13). Temperature teleconnections were the dominant modifier of spatial heterogeneity in effects. Under all scenarios, El Niño-driven warming led to positive median excess cases, the highest under SSP2-4.5, whereas La Niña-driven changes projected smaller, highly uncertain reductions. ENSO influences chikungunya transmission through asymmetric and spatially heterogeneous teleconnection pathways. Integrating ENSO forecasts into surveillance efforts has the potential to enhance preparedness in climate-sensitive regions. Full article

High-solar-reflectivity cladding materials are widely promoted to reduce cooling demand and mitigate urban heat island effects. However, in cold and mixed climates, their overall energy and carbon performance remains uncertain due to potential winter heating penalties and embodied carbon trade-offs. This study presents a comparative evaluation of energy use, annual operational carbon emissions, and material-level embodied carbon for high-reflectivity cladding applied to commercial buildings across representative Canadian climate zones. Dynamic simulations were conducted in EnergyPlus using a standardized warehouse archetype in Montreal, Toronto, and Vancouver, representing cold continental, mixed continental, and marine climates. Roof and wall solar reflectivity (albedo) was varied from 0.2 (baseline) to 0.8 (high reflectivity), while other envelope properties remained constant. Increasing reflectivity reduced annual cooling demand by approximately 15% in Montreal and Toronto and 20% in Vancouver, with the largest reductions during peak summer periods. However, reduced winter solar heat gains produced heating penalties, increasing total annual energy use by 1% in Montreal, 0.5% in Toronto, and less than 0.5% in Vancouver. Operational greenhouse gas emissions were calculated by converting simulated annual electricity and natural gas use into CO₂-equivalent emissions using provincial grid emission factors and combustion factors consistent with Environment and Climate Change Canada reporting. The results demonstrate the strong influence of regional energy supply on operational carbon outcomes. A cradle-to-gate (A1–A3) life cycle assessment quantified embodied carbon of representative cladding materials using Environmental Product Declarations and North American databases. Embodied carbon varied considerably: product-specific steel cladding manufactured in low-carbon electricity regions showed global warming potential as low as 1.76 kg CO₂e/kg, compared with industry averages exceeding 2.4 kg CO₂e/kg. Rather than performing a complete whole-life carbon assessment, this study comparatively evaluates annual operational carbon emissions and material-level embodied carbon to improve understanding of the energy and carbon implications of high-solar-reflectivity cladding materials in representative Canadian climates. The results demonstrate that climate conditions, envelope thermal performance, regional energy supply, and manufacturing pathways influence the environmental performance of cool envelope strategies. Full article

Climate change is driving hydroclimatic changes that are not fully captured by conventional trend analyses. This study presents a multidimensional assessment of hydroclimatic changes in Northern Cyprus using observational records from 27 precipitation stations and 12 temperature stations, with precipitation records spanning 35–46 years and temperature records spanning 21–30 years. Modified Mann–Kendall (MMK), Pettitt (PT), Innovative Trend Analysis (ITA), and Structural Trend and Variability Identification (STVI) methods were integrated to examine monotonic trends, abrupt shifts, distribution-dependent changes, and mean–variability interactions at annual and seasonal scales. Results revealed pronounced spatial heterogeneity and seasonal asymmetry in precipitation totals and their temporal evolution. Increasing tendencies were mainly concentrated in the Kyrenia mountainous region and parts of the western coast, whereas several eastern coastal stations showed drying tendencies, particularly in spring. Winter exhibited the most coherent wetting signal, while spring was more fragmented and drying-dominated. Monthly mean of daily maximum temperature (Tmax) and monthly mean of daily minimum temperature (Tmin) generally showed widespread warming, although Tmin responses were more localized and season-dependent. ITA indicated asymmetric precipitation behavior, with medium and high precipitation values generally increasing, while low values often decreased or showed mixed responses. STVI further revealed that precipitation changes involved substantial restructuring of both mean and variability components, whereas temperature changes were mainly mean-driven. The findings provide a more comprehensive understanding of evolving hydroclimatic conditions, which can support climate adaptation and water resources management in semi-arid Mediterranean regions. Full article

With the ongoing intensification of climate warming and human activities, the permafrost on the Qinghai–Tibet Plateau has exhibited a degradation trend characterized by rising ground temperatures and thickening active layers over the years. Particularly in ice-rich permafrost regions, thermal melting disasters, such as ground subsidence caused by thermal melting, pose a significant threat to infrastructure in permafrost areas. Based on monitoring data from the source region of the Datong River, this article developed a calculation model for active layer thickness (ALT) based on underlying surface types. Utilizing an underground ice distribution model established through geomorphic classification and lithological characteristics, in conjunction with the Nelson model, a risk evaluation of thermal melting disasters in the source region of Datong River was conducted. Based on the current warming trend, the future variation trend of ALT was predicted, and thermal stability was evaluated. The results indicated that ALT in the source region ranged from 1.0 to 3.5 m, with a close correlation between ALT and underlying surface types. The overall thermal stability of the source region is relatively satisfactory, yet it is inadequate in high-altitude areas and on bare ground. Compared to bare ground, swamp meadows and alpine meadows offer superior protective effects on the thermal stability of permafrost in the source region. Full article