Search Results (2,678)

The sustainable transformation of idle built environments represents a critical pathway for advancing low-carbon development and achieving carbon neutrality targets. This study examines how idle rural building stocks may contribute to sustainable built environment systems through rural building repurposing and regeneration strategies. It introduces the concept of Green Rural Centers (GRCs), multifunctional facilities formed through the adaptive reuse of idle buildings that integrate low-carbon design, community services, and local economic functions. Within the proposed framework, GRCs are conceptually characterized as facilities that may: (1) achieve 50–70% reductions in operational energy demand through passive and renewable measures, (2) incorporate two or more community-oriented functions (e.g., education, governance, cultural services), and (3) demonstrate embodied carbon savings of ≥40% compared to demolition-and-rebuild scenarios. Grounded in fieldwork from Fujian Province, China, and aligned with national policies, the study evaluates spatial transformation, carbon mitigation, and institutional integration. Using a mixed-methods approach that combines scenario-based carbon-reduction estimation and appraisal, spatial analysis, comparative case studies, and policy evaluation, the findings indicate that retrofitting 30% of approximately 68,000 idle rural schools could achieve approximately 734,400 metric tons of cumulative CO₂ reduction by 2060 under the baseline scenario. Under conservative and ambitious implementation conditions, the estimated cumulative reductions are approximately 408,000 and 1,224,000 metric tons of CO₂, respectively. Sensitivity analysis shows that moderate improvements in retrofit quality or implementation rates significantly amplify emissions reduction outcomes. Beyond environmental performance, the proposed framework may also support community resilience, decentralized service provision, and socio-economic revitalization. This research reframes idle building stock as a strategic asset within sustainable built environment systems, policy-relevant exploratory framework potentially adaptable to comparable rural contexts. This study contributes to the sustainable built environment discourse by demonstrating how underutilized rural building stocks can function as broader low-carbon rural regeneration systems. Full article

Forest carbon assessment requires methods that capture the combined effects of stand structure, site conditions, carbon pools, operational emissions, and circular-economy processes. This study aimed to develop and optimize hybrid machine learning models for predicting the gross CO₂e (carbon dioxide equivalent) balance of Polish forest stands using measurable stand- and site-related variables. The research was based on a primary dataset describing forest management in major Polish macroregions in 2020–2024. After data cleaning and preprocessing, multiple machine learning algorithms, including ensemble, boosting, neural, and hybrid models, were trained, validated, and tested. Model performance was assessed using standard regression metrics, overfitting diagnostics, learning curves, and SHAP (Shapley Additive Explanations). Most models achieved high predictive accuracy, with six of ten algorithms reaching R² values above 0.90 on the test set. The reduction in strongly correlated variables helped limit multicollinearity and excessive overlap between predictors and the target variable, supporting a more reliable interpretation of model performance. The CatBoost algorithm achieved the highest predictive performance on the test set (R² = 0.948), while also recording the lowest root mean squared error (RMSE = 152.242). However, the Decision Tree demonstrated the weakest generalization performance (R² = 0.806) on the test set. SHAP analysis identified tree height as the most influential predictor, followed by tree age, number of trees, species composition, and selected habitat features. The novelty of the study lies in integrating hybrid machine learning, interpretable modelling, and circular-economy-related carbon balance components into a single framework for rapid and operational forest carbon assessment in Polish forest stands. Full article

Background/Objectives: Recurrent acute otitis media (AOM) in children is known to cause cumulative cochlear and vestibular injury. Whether a single fulminant episode severe enough to require surgical intervention produces an analogous long-term audiovestibular signature, and whether infection severity contributes to outcome independently of cumulative episode count, is unclear. The present study addressed this gap. Methods: In this single-centre retrospective cohort study, 65 paediatric patients who had undergone surgical treatment for acute mastoiditis—the fulminant form of AOM—between July 2001 and March 2021 were assessed a median of 11.5 years after surgery. Of these, 35 had undergone mastoidectomy with tympanostomy and 30 had undergone tympanostomy alone because their episode had not been severe enough to require mastoidectomy. Thirty-two age-matched healthy volunteers (one ear each) formed the control group, yielding 97 ears in three groups (Group TM, 35 ears; Group T, 30 ears; Group C, 32 ears). Extended high-frequency pure-tone audiometry (125–20 kHz), distortion-product otoacoustic emissions (DPOAEs), single-frequency and wideband tympanometry, ipsilateral acoustic reflex thresholds, and lateral-canal vestibulo-ocular reflex gain were measured. Results: Both operated groups showed significantly elevated audiometric thresholds in the high- and extended high-frequency ranges compared with controls (HTA: χ² = 24.25, p < 0.001), with corresponding reductions in DPOAE amplitudes (HTA: χ² = 25.04, p < 0.001). Group TM did not differ significantly from Group T at any frequency band, indicating a negligible additional contribution of mastoidectomy itself. Acoustic reflex thresholds were elevated in Group TM. Vestibulo-ocular reflex gain was within reference ranges in all groups. Conclusions: A single fulminant episode of acute middle-ear infection in childhood—whether severe enough to require mastoidectomy or treated by tympanostomy alone—was associated, more than a decade later, with significantly elevated audiometric thresholds closely resembling those reported after multiple recurrent infections, supporting an effect of infection severity independent of cumulative episode count. Long-term audiological follow-up with extended high-frequency audiometry and otoacoustic emission testing is warranted, irrespective of whether mastoidectomy was required. Full article

This study examines how digitalization discourse is mobilized in public carbon reporting under institutional complexity and how it varies across different carbon-accountability structures in an emerging-market context within the Global South. A longitudinal comparative discourse analysis was conducted on 70 annual and sustainability reports (2015–2024) from seven Vietnamese listed firms, contrasting firms with internal carbon accountability against those with supply-chain-mediated accountability. The 2015–2024 timeframe was deliberately selected to capture a critical decade of regulatory evolution, marked by the aftermath of the Paris Agreement and the escalating enforcement of net-zero and environmental, social, and governance (ESG) disclosure mandates. Findings reveal that digitalization functions as an ambivalent rhetorical resource rather than a uniformly substantive sustainability enabler. Firms with operationally visible emissions utilize digitalization for “temporal buffering,” deferring immediate physical abatement by framing technology as a future transition pathway. Conversely, firms with supply-chain-mediated emissions employ “boundary displacement,” framing accountability as contingent on fragmented supplier data. These patterned responses constitute “digital institutional camouflage”. We conclude that digital reporting sophistication should not be conflated with substantive decarbonization; effective oversight requires cross-validating digital infrastructures with concrete emission-reduction measures. Ultimately, this study empirically specifies institutional decoupling theory by demonstrating how emissions visibility and organizational control shape distinct pathways of discursive decoupling. Full article

As climate change intensifies, transitioning the construction sector away from fossil fuels is vital to reducing global greenhouse gas emissions and localized urban pollution. This paper assesses the economic feasibility of electrifying construction machinery by developing an Annualized Cost of Ownership framework that incorporates mobile charging solutions, internalizes environmental and public health operational externalities (CO₂, PM_2.5, NO_x, and SO₂), and relies on Monte Carlo simulation with Cholesky decomposition to capture the interdependencies among cost drivers. We analyze twenty distinct models of excavators and wheel loaders—the two largest contributors to construction-machinery emissions—comprising functionally equivalent diesel and battery-electric variants. Our results show that several compact electric models are already cost-competitive even without internalizing environmental and public health operational externalities. When these are accounted for, the economic advantage of electric machinery increases, particularly in denser urban areas where local air pollution damages are severe. While projected battery cost reductions further lower electric ownership costs, the magnitude of this effect is modest. However, the weak penetration of electric construction equipment in the US underscores that targeted policy interventions—such as point-of-sale rebates, green procurement mandates, tax credits, charging infrastructure subsidies, or the creation of low-emission zones and noise ordinances that advantage electric construction machinery—are needed to accelerate market adoption. These measures are particularly critical in densely populated urban areas, where internalizing local air pollution and public health externalities significantly amplifies the economic value of zero-emission machinery. Full article

The particle emissions from diesel engines are a major environmental problem due to their harmful effects on air quality and human health. This article investigates the underlying acoustic parameters that determine the efficiency of reducing the fine particles through agglomeration. The impact of a change in frequency and voltage on the acoustic waves through the excitation source is researched and analyzed. Three blends of rapeseed methyl ester and isopropanol (RME95I5, RME90I10, and RME80I20) are used for experiments to study the combined benefit of oxygen-rich blends. The exhaust particles are measured before and after the exposure to acoustic waves operated at a varying voltage and frequency ranges. The fine particle reduction with a simultaneous increase in 5–10 µm particles is found to be better at the lower frequency due to the severe acoustic attenuation at the higher frequency. With the increase in voltage to 200 V, the reduction in fine particles and the simultaneous increase in coarse particles are comparatively less. The change in voltage induces an increase in sound intensity, which slows down the growth of agglomerates. The study presents the critical information necessary to use acoustic waves to reduce particle pollution using conventional filters, including the mechanisms by which sound intensity affects particle size distribution and the effectiveness of this method in various environmental conditions. Full article

In processes related to the treatment of mineral materials, the crushing stage determines the ability to obtain the required particle-size fraction. At the same time, it is an exceptionally energy-intensive step (accounting for about 5% of global electricity consumption) and one that generates significant environmental impacts, particularly in the form of high noise levels and considerable dust emissions. This study focuses on acoustic issues associated with the operation of crushers equipped with materials of varying hardness. Noise level measurements were carried out and then compared with the machines’ operational parameters, such as reduction ratio, throughput, energy consumption, and grain-size distribution. The results indicate that the properties of the processed material have a significant influence on noise emission during the crushing process. The study included various types of materials, such as pebble, basalt, and granite (feed size 16–22 mm), as well as lower-strength materials, including aerated concrete, recycled concrete, and ceramic materials (average particle size of approximately 50 mm), enabling a comparative analysis under controlled operating conditions. The measured noise levels ranged from front position 105.3 dB and side position 105.2 dB, depending on the material type, with the highest values observed for [hard material, e.g., recycled concrete and basalt] and the lowest for [weak material, e.g., aerated concrete]. The differences between extreme cases reached up to the top position 107.6 dB, indicating a strong relationship between material properties and acoustic emission. These findings highlight the importance of material selection in crushing processes and provide a useful reference for reducing noise impact and improving the environmental performance of industrial aggregate production. Full article

This study proposes and validates a structured methodology based on Design for Six Sigma (DFSS) for sustainable product design, addressing the lack of standardization in the integration of design tools and the need to simultaneously consider qualitative, quantitative, and sustainability-related variables. The methodology integrates Voice of the Customer (VOC), Quality Function Deployment (QFD), Theory of Inventive Problem Solving (TRIZ), computer-aided design and engineering (CAD/CAE), and Design of Experiments (DOE) within a ten-stage framework combining the stages from DMADV (Define, Measure, Analyze, Design, Verify) and IDOV (Identify, Design, Optimize, Validate) approaches. The proposed method was applied to the design of a structural concrete block, considering performance variables such as weight, factor of safety, displacement, energy consumption, and carbon emissions. The results show that the integration of QFD enabled prioritization of customer requirements, while DOE and regression models identified significant factors and interactions. Multi-response optimization using desirability functions achieved a balanced solution, improving structural performance and sustainability indicators. In particular, a significant reduction in carbon emissions was achieved. Validation through simulation confirmed the consistency between predicted and observed results. The findings demonstrate that the proposed methodology provides a systematic and replicable approach for product design, improving decision-making and supporting the development of more sustainable products. Full article

Rural sustainability planning requires spatially explicit methods that integrate agricultural resource bases, ecological condition, low-carbon feasibility, community implementation support, and cultural landscape values. Although the Circular and Ecological Sphere (CES) concept offers an integrative framework for rural transition, empirical CES studies remain largely qualitative or policy-oriented. This study develops a FarmMap-integrated Python-GIS workflow for proxy-based CES-oriented spatial prioritization in Yangpyeong-gun, a peri-rural county on the eastern fringe of the Seoul metropolitan region in Korea. Public spatial and administrative datasets were integrated into thirteen indicators grouped under five CES-relevant axes. The model does not measure realized circular material flows, governance quality, resident participation, or carbon emission reduction directly; instead, it identifies where CES-relevant spatial potentials co-occur. An axis-balanced entropy model assigned equal total weight to each axis while applying entropy weighting within axes. Robustness was tested through equal-weight, axis-emphasis, raw entropy diagnostic, Monte Carlo perturbation, and spatial-scale sensitivity analyses using 100 m diagnostic, 500 m, and eup/myeon supports. The final 250 m priority surface identified the top fifth of analyzed Yangpyeong-gun area as very-high relative priority and remained stable across weighting and spatial-support diagnostics. Rural-experience villages and village enterprises had significantly higher CES scores than random background locations. The results demonstrate a reproducible first-stage spatial screening workflow for CES-oriented rural planning while clarifying the limits of proxy-based circularity, governance, and low-carbon indicators. Full article

Environmental supply-chain governance increasingly requires firms to trace climate accountability across buyer–supplier relationships. This study examines whether downstream customer climate pressure is associated with suppliers’ green supply-chain management and value-chain carbon accountability among Chinese listed firms. We construct an exposure-weighted customer pressure measure by combining disclosed top-customer relationships with customer climate-accountability signals, and we decompose this measure into disclosure-based and non-disclosure-based components so that symbolic and substantive accountability can be separated. We then link this measure to supplier green supply-chain indicators, value-chain carbon-disclosure components, Scope 3 disclosure, environmental investment, and reported environmental performance indicators, including air emissions, water pollutant discharge, resource consumption, and environmental tax. Using firm-year panel regressions with fixed effects, alternative pressure measures, selection corrections, and extended outcome tests, we find an association between customer climate pressure and supplier value-chain disclosure. The depth of the association is concentrated where customer carbon-disclosure visibility is observed and is not separately identified in the smaller climate-only subsample, while the value-chain interaction association is positive but imprecisely estimated there. The value-chain disclosure associations are robust to a year-stratified randomization-inference placebo test. We do not find evidence that customer pressure is associated with supplier emissions, resource use, environmental investment, or environmental tax in the available matched samples. The pattern is consistent with symbolic compliance in supply-chain carbon accountability: customer disclosure visibility maps into supplier disclosure visibility, while we do not observe parallel movement in substantive environmental outcomes. The central finding is therefore that downstream customer climate pressure is associated with what suppliers disclose rather than with what they emit, shaping supplier disclosure behavior rather than substantive emission reduction. The estimates apply to supplier-year observations with disclosed and mappable listed-customer links, which we treat as the scope condition of the study rather than as an incidental data limitation. Full article

Early-age strength development and carbon emissions represent specific operational constraints in underground cemented tailings backfill (CTB) operations. A pH and ionic pre-conditioning-assisted CO₂ mineralization process was evaluated for carbonate-rich cemented tailings backfill designed to improve early UCS while retaining measurable CO₂ uptake through systematic process control and optimization. Skarn-type tailings (CaO 16.74 wt%, total carbonates 34.7 wt%) were subjected to screening under nominal pH and ionic pre-conditioning treatments (4.0–11.5), CO₂ pressure (0–0.5 MPa), cement-to-tailings ratio (1:3–1:12), and slurry concentration (66–78%). Strength evolution (1–28 d), mineralization products were characterized using TGA as the primary CO₂-uptake method, with XRD used for semi-quantitative phase-trend assessment, scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), transmission electron microscopy (TEM) with selected-area electron diffraction (SAED), X-ray computed tomography (CT), and nuclear magnetic resonance (NMR). Under optimal conditions (pH 8.5, 0.3 MPa CO₂ pressure, 48 h mineralization, 72–74% solids), mineralized specimens achieved 2-day uniaxial compressive strength equivalent to 1.47-times the 3-day control strength (p < 0.01), with peak net CO₂ sequestration of 37.1 g/kg. EBSD analysis of 347 grain boundaries and TEM-SAED examination of multiple foil sections supported the occurrence of syntaxial calcite overgrowth on primary carbonate debris as a major interfacial transition zone strengthening mechanism. Interconnected pore cluster volume decreased by 70.6%; Zn²⁺ and Pb²⁺ leaching decreased by 67.2% and 71.8%, respectively. A shrinking-core kinetics-Ryshkewitch model with pH-dependent correction functions predicted 3-day strength with acceptable accuracy for TW-A and TW-B, whereas TW-C showed a −27.3% deviation, identifying acidic and sulfate-rich wastewater as a boundary condition outside the reliable model domain. Field coring at −500 m depth provided pilot-scale evidence that a 23 mm mineralized shell was consistent with localized reduction of shallow exposed-face instability risk during the early free-standing period. Overall, the pH and ionic pre-conditioning-assisted CO₂ mineralization process is proposed as a laboratory-supported and field-informed screening framework for simultaneous early-strength enhancement and partial carbon sequestration in carbonate-rich cemented tailings systems. The resulting models and parameter guidance should be interpreted as preliminary design tools requiring further factorial optimization and long-term field validation before full site-specific deployment. Full article

Recently there has been notable interest in the reduction in emissions of the shipping industry via the substitution of the currently used fossil fuels with alternative green fuels. One such alternative studied presently could be the use of pure vegetable oils, which are cheaper and easier to produce than other proposed fuels. In this study, pure vegetable oils were tested in a constant volume combustion chamber to assess their ignition quality via the measurement of their Estimated Cetane Number (ECN) and to compare it with that of heavy fuel oils (HFOs). Moreover, the effect of vegetable oil composition on ignition quality was investigated. It was found that all the vegetable oils tested possessed significantly higher ignition quality than standard heavy fuel oils. Vegetable oil ignition quality was found to be most impacted by their degree of unsaturation. The results of the present study indicate that from the point of view of ignition quality, vegetable oils are a viable alternative to fossil fuels, being expected to lead to an increase in the ignition quality of standard heavy fuel oils. Full article

This study reframes street-level sustainable urban renewal as a coordination problem between street vitality and relative low-carbon performance, rather than treating vibrant activity and carbon-pressure reduction as separate planning objectives. Its main contribution is an integrated street-level diagnostic framework that combines multidimensional vitality measurement, township-constrained carbon-emission reference estimation, vitality–carbon mismatch identification, and interpretable nonlinear mechanism analysis within unified street analytical units. Although previous studies have substantially advanced the measurement of street vitality and urban carbon emissions, these two strands of research have often developed separately. As a result, limited evidence is available on whether high-vitality streets also perform well in low-carbon terms, where vitality–carbon mismatches emerge, and which built-environment conditions are associated with more coordinated outcomes. Taking the five central districts of Chengdu, China, as a case, this study integrates multi-source activity, mobility, built-environment, and emission-related data. Street vitality is measured through activity agglomeration, temporal continuity, functional support, and external connectivity, while relative low-carbon performance is derived from the reverse normalization of length-normalized carbon-emission intensity based on a township-constrained street-level emission reference estimate. The results show that street vitality and low-carbon performance are spatially uneven and frequently mismatched, as high activity does not automatically translate into stronger low-carbon performance, and lower-carbon pressure does not necessarily indicate a vibrant urban environment. More coordinated streets are associated with context-specific combinations of functional organization, transport operation, built form, street-interface quality, and ecological background. Nonlinear diagnostic results further suggest that coordination is favored by moderate, balanced, and locally adapted built-environment conditions rather than by the simple maximization of individual indicators. These findings shift the discussion from whether vitality and low-carbon performance are desirable in isolation to how they can be jointly diagnosed and improved in street-level urban renewal. Full article

To address the limitations in the accuracy of existing methods for calculating greenhouse gas emission intensity from underground coal mining, this study develops a more precise model for estimating methane emissions. The model is grounded in the methane release mechanism of coal, and incorporates field-measured original gas content, residual gas content after extraction, and retained gas content following ventilation. The model defines the computational scope based on different mining methods (with and without coal pillars) and incorporates potential direct emission reduction measures applicable at various stages of the mining process. Case studies of both a high-gas mine and a low-gas mine reveal that, while the pillarless mining method increases total methane emissions, emission intensity is reduced. Furthermore, the study demonstrates that preventing the direct release of low-concentration methane from ventilation systems is critical for further emission reductions. Compared to existing methods, the proposed framework adopts a computational approach that reduces operational complexity while maintaining accuracy through the use of readily available field-measured data. These findings offer a scientific basis for formulating tailored emission reduction strategies in the coal mining sector. Full article

This review paper presents a comprehensive synthesis of current scientific knowledge on the integration of low-emission technologies into airport operational models. Attention is also given to the role of artificial intelligence techniques in predicting environmental risks, optimizing energy system design, and enhancing operational safety. The primary objective of the study is to evaluate the synergy between renewable energy sources (solar and wind energy) and emerging propulsion technologies in aviation (hydrogen and electrification) from the perspective of safety and operational stability. The methodology is based on a systematic review of 78 scientific studies identified in the Scopus and Web of Science databases. The analysis identifies critical technical and operational barriers, including electromagnetic interference caused by wind turbines, optical hazards associated with photovoltaic systems, and stability challenges in airport microgrids under peak loads resulting from the charging of electric aircraft. Particular attention is given to the safety of hydrogen infrastructure, where findings from the literature indicate the need to revise separation distances and highlight the potential reduction of airport stand capacity by 5% to 16%. The study synthesizes these findings into a strategic framework for “Smart Green Airports”, proposing solutions such as adaptive infrastructure design, the deployment of predictive models based on artificial intelligence, and the implementation of inherently safe energy storage systems. The paper concludes that achieving airport energy self-sufficiency while maintaining the integrity of flight operations is feasible only through the holistic integration of technical measures, simulation-based planning, and strict compliance with updated safety regulations. Full article