Search Results (7,349)

Climate change has intensified heat stress in poultry production systems, raising concerns about productivity, animal welfare, and system sustainability. This study aimed to analyze the evolution, structure, and emerging trends of scientific research on climate change and heat stress in industrial poultry production using a bibliometric approach. Records were retrieved from the Scopus and Web of Science Core Collection databases. After deduplication and eligibility screening, 342 documents published between 1974 and 2025 were retained. Bibliometric analyses were performed using Bibliometrix/Biblioshiny in RStudio, including publication dynamics, international collaboration, author co-citation, conceptual structure, thematic evolution, trend topics, and keyword co-occurrence. Scientific production increased markedly in recent years, with an annual growth rate of 8.36% and international co-authorship in 22.51% of the publications. China and the United States were the leading contributors. At the same time, the international research structure showed interconnected collaboration networks and complementary intellectual communities focused on physiological and neuroimmune responses, cellular and oxidative mechanisms, and nutritional and management-based mitigation. Heat stress was the main conceptual hub, connecting thermoregulation, oxidative stress, immunity, welfare, productive performance, and product quality. Heat tolerance, thermotolerance, chronic heat stress, and genetic adaptation showed recent or developing bibliometric visibility, although their structural and temporal patterns differed across analyses. However, heat waves, long-term resilience, validation under commercial conditions, climate-vulnerable regions, environmental engineering, and digital monitoring exhibited lower bibliometric representation and network centrality within the analyzed corpus. Future research should combine nutritional, physiological, genetic, environmental, and precision-monitoring approaches to support economically viable and climate-resilient poultry production. Full article

Nitrogen (N) sources affect forage production, soil N dynamics, and greenhouse gas (GHG) emissions. This study evaluated short-term effects of contrasting N sources on forage responses, soil health indicators, and GHG emissions in a cool-season oat (Avena sativa L.) and annual ryegrass (Lolium multiflorum L.) system. Treatments were T1 (grass only), T2 (grass + N), T3 (grass + legume), T4 (grass + poultry litter), and T5 (grass + cattle dung). Crude protein was greater in T3 than in T4 (18% versus 13%; p = 0.02). In May, T3 had the greatest microbial C:N ratio (60.6) and soil inorganic N (45.5 mg N kg⁻¹; p < 0.01). Potentially mineralizable N was greater in T3 than in T1, T2 and T4 (3.96 versus ≤ 2.71 mg NH₄-N kg⁻¹ day⁻¹; p < 0.01). Mean daily CH₄ fluxes were greater (p < 0.01) under T5 (1106 g CH₄-C ha⁻¹ day⁻¹) than under T1 and T3 (≤−3.59 g CH₄-C ha⁻¹ day⁻¹). Mean daily CO₂ fluxes were lower in T3 and T4 than in T1, T2, and T5. There were no effects on N₂O emissions. Legume integration enhanced short-term N cycling and forage nutritive value, without N₂O emissions, over a 60-day experiment. Full article

Ornamental aquaculture represents a high-value segment of global aquaculture and plays an important role in income diversification for small-scale producers. Despite its economic relevance, investment decisions in ornamental fish farming are often supported by limited economic information and rarely incorporate risk and uncertainty into economic assessments. This study developed and applied a stochastic framework to evaluate the economic performance and investment risk of intensive ornamental aquaculture using Betta splendens production as a representative case study. A representative production system was developed from technical and economic surveys conducted on 20 commercial family operated farms located in one of Brazil’s major ornamental fish production clusters. The production system comprised three greenhouse units with an estimated annual output of 162,288 marketable fish. Production costs were estimated using conventional cost-accounting procedures, whereas economic risk was assessed through Monte Carlo simulation incorporating uncertainty in biological, productive, and market variables. The estimated total production cost was US$0.14 fish⁻¹, while the weighted average selling price reached US$0.18 fish⁻¹, resulting in a benefit–cost ratio of 1.33, a profitability of 25.09%, and an annual return on invested capital (ROIC) of 23.90% under the deterministic baseline scenario. Monte Carlo simulation estimated a mean annual ROIC of 22.46%, with a 98.53% probability of positive economic returns. Sensitivity analysis identified labor demand, the selling price of premium males, and reproductive productivity as the principal drivers of economic risk. The results indicate that economic returns in B. splendens farming are primarily influenced by managerial efficiency, labor requirements, and market conditions rather than production volume alone. The proposed framework provides a robust tool for evaluating economic viability and investment risk in ornamental fish farming under uncertainty and may support decision-making in small-scale aquaculture systems. Full article

The Hwange Mining Area, located in the Mid-Zambezi Karoo Basin in northwestern Zimbabwe, is a major centre for coal mining, processing, and thermal power generation. This study evaluates the ecological and public health risks associated with these activities by characterising radionuclide (²²⁶Ra, ²³²Th, ⁴⁰K) activity concentrations in coal and surrounding soils using Hyper-Pure Germanium (HPGe) gamma spectrometry. Samples were collected from four locations, as follows: Hwange Colliery Company (underground and open-cast mines), Zambezi Gas open-cast operations, residential areas, and the Zimbabwe Power Company (ZPC) thermal power station. Radionuclide concentrations were measured using Hyper-Pure Germanium (HPGe) gamma spectrometry. Mean activity concentrations in coal were low at both mining sites (Hwange Colliery: ²²⁶Ra 16 ± 5.3 Bq/kg), ²³²Th 14 ± 5.7 Bq/kg), (⁴⁰K 51 ± 8.8 Bq/kg) and Zambezi Gas (²²⁶Ra 9.80 ± 2.3 Bq/kg), ²³²Th (11 ± 3.3 Bq/kg), ⁴⁰K (43 ± 26 Bq/kg), well below UNSCEAR world coal averages. In contrast, soils from residential areas): ²²⁶Ra (36 ± 15 Bq/kg), ²³²Th (36 ± 12 Bq/kg) and ⁴⁰K (220 ± 80 Bq/kg), and the ZPC power station (²²⁶Ra 47 ± 8.6 Bq/kg, ²³²Th (42 ± 10 Bq/kg), and ⁴⁰K 230 ± 92 Bq/kg, showed markedly elevated concentrations, consistent with the accumulation of coal-combustion by-products such as fly ash. Radiological hazard indices remained within internationally accepted limits at all sites, as follows: radium equivalent (Raeq) ranged from 29 ± 6.7 Bq/kg (Zambezi Gas) to 120 ± 18 Bq/kg (ZPC), well below the 370 Bq/kg safety ceiling, while external and internal hazard indices (H_ex, H_in) remained below unity throughout, peaking at 0.32 and 0.46, respectively, at ZPC. Annual effective dose equivalents (AEDE) ranged from 16 ± 3.8 to 69 ± 10 μSv/year, the latter (ZPC) representing approximately 7% of the ICRP public dose limit of 1 mSv/year. Excess lifetime cancer risk (ELCR) values ranged from 5.56 × 10⁻⁵ (Zambezi Gas) to 2.42 × 10⁻⁴ (ZPC), remaining below the global average outdoor reference of 0.29 × 10⁻³ but reaching approximately 83% of this reference at ZPC and 71% in residential areas. These findings indicate that, while coal mining activities in Hwange contribute minimally to environmental radioactivity, coal combustion at the ZPC thermal power station is the dominant driver of elevated radionuclide concentrations and radiological indices in the surrounding environment, with residential soils reflecting the same enrichment pathway. Although no immediate radiological hazard was identified at any location, the comparatively higher indices at ZPC and in nearby residential areas underscore the need for continuous environmental monitoring, strengthened regulatory control, and targeted radiation protection strategies to safeguard workers and nearby communities. Full article

Satellite precipitation products like GPM IMERG are crucial for hydrological modeling and disaster prevention; yet, their reliability in complex mountainous monsoon regions remains challenging. While the latest IMERG V07 introduces key upgrades, including a Climatological Calibration Algorithm (CCA), its cross-scale error propagation mechanisms and performance heterogeneity in complex underlying surfaces are poorly understood. This study evaluates the daily and monthly performance of IMERG V07 and V06 (Early, Late, and Final Runs) from 2014 to 2020 against 91 rain gauges in Guangxi, China—a typical mountainous monsoon region. The evaluation employs multiple statistical metrics and a multi-dimensional stratification approach based on elevation, precipitation intensity, and seasonality to quantify error propagation and climate-topography coupling effects. The results reveal that V07, particularly the Late Run, enhances daily precipitation detection capabilities, it significantly increases the proportion of systematic positive bias from 62.3 to 64.8% (V06) to 67.2–68.9% (V07). Consequently, upon temporal aggregation to the monthly scale, this systematic overestimation is severely amplified, leading to degraded performance, with the Final Run suffering the most substantial accuracy loss. Furthermore, retrieval accuracy is heavily constrained by surface heterogeneity, with systematic overestimation surging in areas where relatively dry (mean annual precipitation < 1300 mm) and complex terrain (elevation 100–500 m) coincide. The introduced CCA effectively improved dry season estimations but failed during wet season by introducing substantial positive biases. Ultimately, while V07 better captures short-term precipitation dynamics, its structural systematic biases compromise long-term cumulative reliability, highlighting the necessity for physics-based bias correction in hydrological applications and dynamic calibration in future algorithm upgrades. Full article

Plant diseases destroy 20–40% of global food production annually, posing a critical threat to food security for a projected population of 9.7 billion by 2050. Conventional diagnostic approaches relying on expert visual assessment are slow, costly, and unsuitable for modern agricultural scales. While deep convolutional neural networks demonstrated early promise, single-modality, image-centric systems consistently fail under real-world field conditions characterized by variable lighting, co-occurring infections, and cultivar diversity. This review synthesizes a decade of progress across four interconnected frontiers: the evolution of deep learning architectures for plant disease detection; the adaptation of foundation models including CLIP, SAM, and DINOv2 to agricultural contexts; the development of multimodal fusion frameworks integrating imagery, environmental, genomic, and hyperspectral data; and the transition from static disease diagnosis to descriptive comparison of reported metrics, which suggested that multimodal approaches frequently reported improved diagnostic performance relative to corresponding single-modality baselines, although direct cross-study comparison was limited by methodological heterogeneity. A systematic review following PRISMA guidelines identifies eligible comparative studies. Descriptive comparison of reported performance metrics across these studies indicated that multimodal approaches generally achieved higher accuracy and sensitivity than single-modality models, particularly for pre-symptomatic disease detection. Eight critical research gaps are identified, including the absence of a unified agricultural foundation model and limited climate-aware forecasting under non-stationary climate projections. A structured research agenda is proposed to accelerate translation from laboratory performance to globally equitable, field-deployable crop protection systems. Full article

This article presents a technical and economic analysis of a photovoltaic system operating in conjunction with a heat pump in a single-family home. The aim of this study was to compare the cost-effectiveness of two prosumer billing systems currently in use in Poland, net metering and net billing, implemented in accordance with the provisions of the Renewable Energy Sources (RES) Act and the Energy Law and to assess the effectiveness of a proprietary algorithm for managing surplus electricity produced by the photovoltaic system. The energy performance of the facility was determined using ArCADia Termo 11.1 software, while energy and economic calculations were performed using Microsoft Excel 365 and a developed heat pump control algorithm. The algorithm is based on an analysis of the building’s energy balance with a 15 min resolution and utilizes data on outdoor temperature, energy production from the PV system, building heat loss, heat pump operating parameters, and energy self-consumption. Its goal was to maximize the use of energy produced for the building’s own needs by appropriately controlling the heat pump and storing surplus energy as heat stored in domestic hot-water tanks. The annual electricity consumption of the analyzed building was 6902.18 kWh, of which 3724.13 kWh was for heating and domestic hot water provided by the heat pump. The algorithm reduced grid energy consumption by approximately 900 kWh per year and achieved a self-consumption level of 12.73 (%). Full article

Accurate precipitation data are critical for hydrological and climatic studies in Guangdong Province, where complex terrain and frequent extreme rainfall pose substantial challenges. However, the performance of gridded precipitation products is still not well understood. This study evaluates nine products, including gauge-based (CHM_PRE, CN05.1, GMCP, NOAA CPC), satellite-based (IMERG-E, IMERG-F, TMPA RT, TMPA 3B42), and ERA5 reanalysis against NCDC observations from 2001 to 2019 using metrics including trend significance, correlation (R), root mean square error (RMSE), categorical statistics (POD, FAR, ETS), and relative bias across rainfall intensities. The results indicate that, based on validation against NCDC observations, CHM_PRE performs the best across all temporal scales, capturing significant increasing trends (p < 0.05) and achieving the highest consistency with observations at the annual (R = 0.99), monthly (R = 0.99), and daily (R = 0.89) scales. Using CHM_PRE as the reference, CN05.1 shows the highest spatial consistency with it, especially for extreme events. NOAA CPC exhibits the best performance in monthly event detection (ETS = 0.42; BIAS ≈ 1). Satellite products show acceptable performance at the monthly scale but exhibit intensity-dependent biases and high daily variability, with pronounced “light rain overestimation and heavy rain underestimation.” ERA5 shows limitations, particularly in its severe underestimation of extreme precipitation. CHM_PRE is thus identified as the most suitable dataset for Guangdong based on its agreement with NCDC observations. With CHM_PRE as the reference, CN05.1 provides a reliable alternative for spatial analyses; NOAA CPC performs the best in monthly event detection. Satellite products suit monthly use but require daily-scale caution; ERA5 shows a relatively poor performance. Full article

Static wake steering can increase wind-farm power production, but its application to floating offshore wind farms requires assessment of the coupled wake, platform, structural, and station-keeping response. This study evaluates whether power-maximizing static yaw setpoints identified using the steady, control-oriented FLORIS model retain their benefit when transferred without re-optimization to a coupled FAST.Farm floating wind-farm model. The reference farm comprises four IEA Wind 15 MW turbines mounted on VolturnUS-S semi-submersible platforms. Greedy and static wake-steering operations are compared at three below-rated wind speeds, three sea states, and five matched turbulent-inflow realizations, resulting in 90 farm-level FAST.Farm simulations. Wake behavior is characterized through wake-center deflection, meandering, and velocity-deficit profiles, while turbine and mooring fatigue responses are evaluated using paired damage-equivalent-load statistics. Static wake steering increases mean farm power under all nine investigated wind–wave conditions. The gains are approximately 5.1–$5.2\%$ at $7\mathrm{m}{\mathrm{s}}^{-1}$, $5.0$–$5.1\%$ at $8\mathrm{m}{\mathrm{s}}^{-1}$, and $4.0$–$4.2\%$ at $9\mathrm{m}{\mathrm{s}}^{-1}$, with all paired $95\%$ confidence intervals remaining above zero. The gain results from a power redistribution in which the intentionally yawed upstream turbine incurs a local loss that is exceeded by the combined recovery of the downstream turbines. The fatigue response is strongly component- and turbine-dependent. The paired farm-mean blade-root DEL decreases by $0.82$–$2.24\%$, whereas the tower-base DEL increases by $0.76$–$2.78\%$, and the FairTen1 response generally increases by $0.88$–$2.92\%$. The farm-mean yaw-bearing response is mixed, ranging from a $1.15\%$ reduction to a $4.32\%$ increase. Turbine-level analysis reveals larger localized penalties, reaching approximately $10.4\%$ for the yaw-bearing DEL and $12.8\%$ for FairTen1. Spectral analysis associates the yaw-bearing response with yaw-induced aerodynamic and structural excitation, while the tower-base response is strongly influenced by low-frequency wave–platform dynamics. A complementary FLORIS sensitivity analysis demonstrates that the optimized aerodynamic benefit depends strongly on wind direction, spacing, wind speed, and turbulence intensity. For a Tampen-derived 11-turbine layout, resource weighting over the modeled 4–$13\mathrm{m}{\mathrm{s}}^{-1}$ interval produces an annual energy-contribution increase of $3.653\mathrm{GWh}{\mathrm{year}}^{-1}$, or $0.921\%$. These results provide numerical evidence that static wake steering can retain a positive power benefit in a coupled floating wind-farm environment, but controller assessment must include turbine- and component-specific dynamic loads rather than farm power alone. Full article

Coal fires are a significant source of greenhouse gas emissions and ecological pollutants, yet their emission characteristics and carbon accounting remain poorly constrained. To reveal the pollutant generation characteristics and carbon emission levels of the typical underground coal fire area in Sulabulak, Xinjiang, this study integrated laboratory simulation, multi-source remote sensing inversion, and in situ field monitoring. Thermogravimetric analysis, a high-temperature tube furnace, HSC thermodynamic simulation, and multi-source remote sensing data from Landsat-8/9 and Sentinel-1A were employed to investigate the gaseous products and heavy metal migration mechanisms at different combustion stages, and to delineate the spatial extent of different combustion states in the fire area. A coal loss model was then constructed by coupling experimentally determined carbon emission factors with remote sensing-derived areas and was compared with an emission flux model based on field measurements. The results show that the coal oxidation process proceeds through three distinct stages, with indicator gas ratios (CO₂/CO and C₂H₄/C₂H₆) serving as effective indicators for combustion state identification. Heavy metal partitioning is governed by elemental volatility and redox conditions: As and Se partition predominantly into the gas phase, while Zn becomes enriched in fly ash. Remote sensing time series analysis documents continuous fire expansion accompanied by progressive surface subsidence. By cross-validating the indirect coal loss model (constrained by remote sensing area) against the direct emission flux model (constrained by field measurements), we estimate the current annual GHG emission of the Sulabulak fire area at approximately 0.65 × 10⁴ t CO₂ equivalent. This study proposes a coupled “micro-experiment–macro-remote sensing–field measurement” approach for carbon emission accounting, providing reliable data support for environmental pollution control and the development of carbon inventories for coal fires in arid regions. Full article

Freshwater scarcity can weaken water governance when hydrological pressure interacts with intensive agricultural demand, regulatory weakness, and political conflict. This research evaluates whether Irrigation District 005 (IR 005) in Chihuahua, northern Mexico, demonstrates local water-governance fragility across three domains: public security, the rule of law, and the ability to sustain water access and food production. A mixed-methods approach integrates legal and human rights documentation, institutional records, published studies, and a structured media review with hydrological, agricultural, climatic, and reservoir data. Water balances were analysed for 1998–2023, precipitation trends for 1980–2020, and crop water requirements were estimated using the Food and Agriculture Organization’s Irrigation and Drainage Paper No. 56 (FAO-56) Penman–Monteith framework, the crop coefficient (Kc), the water-stress coefficient (Ks), the United States Soil Conservation Service (SCS) Curve Number method, and application-efficiency assumptions. The 2020 water conflict resulted in fatalities, injuries, arrests, and documented human rights violations. Rule-of-law capacity was further diminished by unauthorised withdrawals, cultivation beyond authorised irrigation plans, and limited enforcement. The annual water balance shifted to persistent deficits after 2016, reaching an estimated deficit of 2268 cubic hectometres (hm³) in 2020. Annual precipitation did not exhibit a statistically significant monotonic decline during 1980–2020 (Mann–Kendall Z = −0.79, τ = −0.0878, p = 0.4251; Sen’s slope = −1.1628 mm yr⁻¹; Mann–Whitney p = 0.5313), indicating that recent stress is more closely linked to production scale, crop mix, governance conditions, and irrigation efficiency than to a long-term reduction in rainfall. Sensitivity analysis revealed that ±15% changes in Kc and Ks altered gross water requirements by approximately ±16–17%, while equivalent changes in effective precipitation produced changes of only 1–3%. These results demonstrate heightened water-governance fragility resulting from mutually reinforcing hydrological, institutional, and conflict-related pressures. Future research should refine locally calibrated water-demand parameters and develop reproducible monitoring systems that combine hydrological, institutional, satellite, and participatory data to support anticipatory, transparent, and rights-based water governance. 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

Photorespiration and drought-induced stomatal closure are two important physiological constraints that reduce carbon assimilation and productivity in C₃ forest trees under Mediterranean climatic conditions. Türkiye’s two dominant commercial pine species, Pinus brutia Ten. (Calabrian pine) and Pinus nigra J.F. Arnold subsp. pallasiana (Anatolian black pine), together cover approximately 8.15 million hectares. This study integrated published gas-exchange measurements, radiation-use efficiency estimates from MODIS, official forest inventory data, and dendrochronological growth records into a counterfactual accounting framework and propagated parameter uncertainty by Monte Carlo simulation (N = 40,000 draws). The two constraints jointly reduced weighted-mean net primary productivity (NPP) from a radiation-limited potential of 5.61 to an actual 3.46 Mg C ha⁻¹ yr⁻¹, a reduction of 37.9% (95% CI 32.2–43.4%). Decomposition shows that 47.7% of this loss is the obligate metabolic cost of C₃ carboxylation, which no silvicultural intervention can address, while 52.3%—20.1 of the 37.9 percentage points—is drought-attributable. Nationally, the deficit corresponds to 64.3 Mt CO₂ yr⁻¹ of forgone sequestration (47.8–81.2) and 34.4 Mm³ yr⁻¹ of forgone stemwood-volume equivalent (24.9–44.5), of which approximately 20.6 Mm³ would be merchantable, giving an annual economic deficit of USD 3.37 billion (2.40–6.48). Filtering the drought-attributable component for eligible area, recovery efficiency, additionality, leakage, and permanence yields approximately 1.0 Mt CO₂ yr⁻¹ of potentially issuable credits, fewer than two per cent of the headline figure. Eco-physiological suppression of this magnitude is currently invisible in national forest carbon accounting, and its recognition bears directly on dynamic baseline design and on the credibility of offsets generated from Mediterranean conifer forests. Full article

Rapid urban expansion reshapes urban morphology and the spatial organization of regional city systems. However, provincial-scale studies rarely integrate expansion dynamics, morphological change, and the evolution of morphological polycentricity, while stage-specific shifts in associated factors remain insufficiently understood. This study examines 16 prefecture-level cities in Shandong, China, from 2000 to 2020 to quantify urban expansion and morphological change, assess morphological polycentricity and the city-size hierarchy, and evaluate stage-specific factors associated with newly added built-up land. Built-up land was extracted from the Prolonged Artificial nighttime-light Dataset of China (PANDA-China) using a statistics-constrained bisection threshold method and evaluated against independent land-cover products, followed by complementary spatial, morphological, rank–size, and GeoDetector analyses. The results show that the built-up area increased from 1912.10 to 5646.04 km² in Shandong, while the annualized expansion rate declined from 7.09%/yr to 4.14%/yr despite persistently high absolute expansion after 2010. The dominant northeast–southwest axis remained stable, while urban forms became less compact and more complex. Secondary built-up nodes strengthened, whereas Jinan and Qingdao retained their dominant positions, indicating strengthening morphological polycentricity within a persistent dual-core structure. GeoDetector revealed a temporal shift from greater GDP prominence in 2000–2010 toward stronger population and road associations in 2010–2020. Initial built-up density remained the strongest explanatory factor, and factor interactions consistently exceeded individual explanatory power. These findings clarify the stage-dependent evolution of urban expansion and support differentiated land management and coordinated regional development. Full article

Existing industrial buildings represent a critical but under-addressed field for operational carbon emission reduction, as retrofit decisions are constrained by production continuity, limited investment capacity, and heterogeneous technical options. This study developed a decision support framework integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods to evaluate and prioritize operational phase decarbonization retrofit schemes for existing industrial buildings. The framework was applied to the Thyssenkrupp S Plant in eastern China, where ten candidate schemes were identified through an energy audit, on-site investigation, and expert consultation. The results show that heating, ventilation, and air conditioning (HVAC) operational control and temperature set-point optimization ranked first, followed by lighting operational management and automatic control. These management-based measures offer strong near-term applicability because of their low investment, short payback periods, limited implementation disturbance, and immediate emission reduction benefits. Their sustained effectiveness, however, requires standardized procedures, staff education, energy monitoring, and appropriate automation. Rooftop photovoltaics provide the largest annual carbon reduction but have a lower short-term priority because of their high upfront investment. Expert-consistency testing and sensitivity analyses, including criterion weight perturbation, preference scenarios, and Monte Carlo simulation, support the robustness of the leading ranking pattern. The findings support staged retrofit planning that prioritizes durable management measures in the short term, equipment-level efficiency improvements in the medium term, and renewable energy deployment in the long term. Full article