Search Results (685)

The effective drainage radius is a key parameter for borehole layout and gas drainage performance evaluation, and it is determined by the spatiotemporal evolution of gas pressure around drainage boreholes. Taking the M4–5 coal seam of a Xinjiang coal mine as the study case, the residual gas-content criterion was converted into a site-specific equivalent pressure criterion using Langmuir adsorption parameters, and 0.58 MPa was adopted as the working pressure threshold for effective drainage. A transient radial gas pressure evolution model was then established based on mass conservation, Darcy seepage, and Langmuir adsorption and evaluated against field measurements. For 62 paired measured–calculated data points at radial distances of 1.0 and 1.5 m, the overall MAE, RMSE, and MAPE were 0.0204 MPa, 0.0265 MPa, and 2.86%, respectively, with an R² of 0.9756 and a maximum absolute relative error of 8.67%. Decreasing the borehole boundary pressure, increasing the coal-seam gas permeability coefficient, and increasing the borehole radius could promote gas pressure reduction, while the additional benefit of further reducing the boundary pressure gradually diminished at lower pressure levels. Increasing the coal-seam gas permeability coefficient from 0.015 to 0.090 m²·MPa⁻²·d⁻¹ reduced the gas pressure at 1.0 m by 35.63% and increased the effective drainage radius from 0.65 to 2.01 m over 15–90 d. Field measurements showed that, after 90 d, the residual gas pressure and gas content at 2.0 m were 0.39 MPa and 3.95 m³/t, respectively, providing preliminary field support for the calculated drainage range. An empirical relationship among initial gas content, drainage duration, and effective drainage radius was further established, with an overall MAPE of 7.50% and an R² of 0.9562 within the fitted range. For an initial gas content of 8.3 m³/t and a drainage duration of 300 d, long-term mathematical extrapolation yielded an effective drainage radius of 2.80 m; after conservative engineering correction, 2.30 m was adopted, corresponding to a geometrically estimated upper-limit borehole spacing of 4.60 m. The results provide a reference for effective drainage radius prediction and borehole layout optimization under gas-geological conditions similar to those of the test area. Full article

Evaluating the net energy-saving effect of a mandatory energy efficiency labeling system implemented uniformly at a national scale remains a persistent challenge in policy quantification. Household refrigerators in China have been subject to mandatory energy efficiency labeling since 2005, with the third revision enacted in 2016, tightening the Grade 1 efficiency threshold by approximately 40%. Because the policy was rolled out simultaneously nationwide, no untreated control group exists, rendering conventional difference-in-differences approaches inapplicable and impeding the causal attribution of energy savings to the labeling system. This study employs an interrupted time series (ITS) design, with the 2016 revision designated as the policy breakpoint, to estimate the net effect of the label update on refrigerator energy consumption. Using a segmented linear regression model with Newey–West HAC robust standard errors (lag = 1), the fully adjusted specification identifies a statistically significant negative immediate change of approximately 0.069 kWh in daily energy consumption at the policy implementation point (p < 0.001), although the estimated magnitude is sensitive to the model specification. The flow-based cumulative electricity saving associated with the 2016–2025 period is estimated at 4.84 billion kWh, equivalent to 1.49 million tonnes of coal equivalent and a CO₂ emission reduction of 4.31 million tonnes. The findings provide conditional evidence that the label revision was associated with lower refrigerator energy consumption and improved product-level energy performance. Full article

This study presents a context-grounded conceptual design for an environmentally sustainable hotel in Shiraz, Iran, integrating three complementary strategies: a biomimicry-inspired responsive façade, a Voronoi-based façade and landscape design, and solar energy generation. Inspired by the adaptive behavior of morning glory flowers, the responsive façade is designed to adjust dynamically to environmental conditions with the aim of improving daylight utilization and thermal performance. Voronoi patterns are incorporated into the façade and landscape with the design intent of enhancing natural light distribution, airflow, structural efficiency, and aesthetic quality. In addition, photovoltaic panels installed on the hotel and parking roofs provide renewable energy to improve building sustainability. The façade and landscape geometry are developed parametrically in Rhinoceros 3D with Grasshopper, and the rooftop photovoltaic system is simulated using site-specific climate data for the project location. The System Advisor Model (SAM) simulations indicate that the proposed solar system can generate approximately 4,281,172 kWh of electricity annually, corresponding to approximately 9,889,507 lb (4486 t) of avoided CO₂ relative to the cited U.S. coal generation benchmark. The integration of biomimicry, computational design, and renewable energy demonstrates an integrated conceptual approach to environmentally sustainable hotel architecture, with quantified solar energy generation and emissions reduction potential, and design-intent strategies for daylighting, thermal comfort, and occupant well-being that warrant further validation. This work presents an integrated design framework, not a validated or constructed building. Consistent with this scope, the term sustainability is used here in its environmental sense; the economic and social pillars are not assessed, and the study does not claim that Voronoi geometry is necessary for, or superior to, more regular and repetitive façade alternatives, a question that would require a controlled comparative study. The proposed design illustrates how nature-inspired strategies and advanced digital design methods can be combined to create innovative, resilient, and environmentally responsible buildings, providing a context-specific design proposition for future sustainable hospitality research. Full article

As a typical high-emission process industry, cement manufacturing features strong non-linearity, time-varying delays, and nonstationary dynamics, with clinker calcination dominating energy costs and carbon emissions. This paper proposes a receding-horizon MPC coordinated optimization framework for reducing coal and electricity consumption during calcination. First, ReliefF screening extracts key energy-related state variables from high-dimensional DCS data under process-mechanism constraints. VMD and sliding windows are then used to construct multiscale dynamic features describing nonstationary and delayed process responses. An HHO-ELM model predicts future energy-consumption trajectories, while a GWO-based upper-layer optimizer searches for energy-efficient reference trajectories under operating constraints. A data-identified discrete-time plant-response model serves as the internal dynamic model of the lower-layer MPC, which calculates constrained control moves for tracking these references. The framework is evaluated using archived industrial DCS data and an offline receding-horizon closed-loop simulation. VMD-HHO-ELM yields the lowest prediction errors among the compared predictors, and GWO shows favorable convergence for economic reference generation. The simulated MPC results indicate coordinated reductions in coal and electricity consumption within the observed operating region. Full article

Volatile organic compounds (VOCs) from coal-chemical enterprises pose a significant challenge to the environment and sustainability. Nevertheless, the fugitive VOC emissions from equipment and pipeline systems, and the application research of leak detection and repair (LDAR) technology within coal-chemical enterprises have received limited attention, impeding sustainable development goals. This study selected three representative coal-chemical enterprises to conduct large-scale LDAR surveys in 2022 and 2023. Based on field measurements exceeding 260,000 affected components per year, leak characteristics, emissions, and LDAR effectiveness were analyzed and evaluated from three aspects: enterprise-wide, process-specific, and component-level. The one-way analysis of variance revealed no statistically significant differences in overall leak concentrations between enterprises, whereas significant differences between component types. Non-flanged connectors had a higher leak level, followed by open-ended lines, pumps, valves, and flanges. The process-specific leak ratios (0.29~1.71%) and emission contributions (9.33~35.31%) were highest in downstream units, whereas leak ratios (0.05~0.08%) and emission contributions (0.75~10.57%) were lowest in midstream and upstream units, respectively. The component-level ratios were pronounced for open-ended lines (1.84%) and valves (0.79%), while emissions were primarily concentrated on flanges, non-flanged connectors, and valves (96.1~99.1%). The repair ratios (87.42%, 90.88%), emission reduction rates (58.56%, 60.45%) under restorations, and decreases in leak ratios (44.59%) and emissions (33.22%) over consecutive years comprehensively identified the LDAR effectiveness. Finally, the precise control and policy implications were discussed accordingly. These findings aimed to provide basic references for coal-chemical enterprises in precise control and sustainability policies. Full article

To mitigate high-pressure Ordovician limestone water inrush hazards at the 3203 working face of Hongshan Coal Mine, a synergistic water inrush mechanism is proposed involving mining-induced stress and concealed structures. Based on field measurements and theoretical analyses, this study established a mechanical model of floor failure and derived the critical conditions for water inrush. The vulnerability index method was employed to develop a risk assessment model incorporating five multisource indicators, with combined weights determined using the analytic hierarchy process (AHP) and the entropy-weight method. A whole-process prevention and control system covering the pre-mining, mining, and post-mining stages is also proposed. The results show that mining-induced fractures and concealed structures progressively propagate under cyclic mining-induced stress. Delayed water inrush is triggered when the cumulative propagation amount, ΔH, exceeds the thickness of the aquiclude. The vulnerability index method divides the study area into seven risk levels. TS1–TS4 (water bursting point 1–4) were used for model development, and TS5–TS6 were reserved for independent validation. The identification rates were 100% on both the modeling and independent validation datasets. Leave-one-out cross-validation yielded a mean identification rate of 83.3% with a standard deviation of 0.14, outperforming the conventional water inrush coefficient method. After implementation of the whole-process prevention and control system, water inflow at the working face stabilized at 0.4–0.6 m³/min, representing a 60–73% reduction compared with the untreated working face, which was shown to be statistically significant (p < 0.01) using the Mann–Whitney U test. The critical conditions established in this study provide a semi-quantitative mechanical basis for identifying floor water inrush. The proposed prevention and control system has considerable potential for application in coal seam extraction under similar geological and hydrogeological conditions. Full article

Methane contained in ventilation air from hard coal mines (VAM, ventilation air methane) represents a significant environmental and technological challenge due to very large volumetric airflow rates and low methane concentrations. The feasibility of applying VAM utilisation technologies depends not only on methane concentration but also on ventilation air quality, including dust content, humidity and gaseous contaminants. This paper presents an analysis of dust in air emitted from hard coal mine exhaust shafts in Poland and Romania, based on measurement data and studies conducted within the ProVAM project. The dataset includes 155 dust concentration measurements from 24 main fan stations, supplemented by analyses of dust composition and particle size distribution for selected shafts. The results show that, in the analysed dataset, most reported mean total dust concentrations were within the range of approximately 1–3 mg/Nm³, with considerable temporal variability. Particle size analysis performed for two selected Polish shafts showed that fine particles dominate in terms of number, whereas coarser particles contribute disproportionately to the volume weighted distribution and, approximately, to the mass contribution. The results are compared with the requirements of VAM oxidation technologies, particularly regenerative thermal oxidisers (RTOs), for which selected commercial systems specify technical reference values for dust concentration in the supplied air. In many analysed cases, particularly where dust was dominated by incombustible mineral matter, air pre-treatment should be considered before ventilation air is introduced into VAM utilisation systems. A comparative assessment of dry dust-removal methods is also conducted, including gravitational, inertial, centrifugal, filtration and electrostatic devices. Considering the operating conditions of mine ventilation air, including high airflow rates, high humidity and dust characteristics, cyclone battery systems are discussed as a technically justified candidate for the primary dust-removal stage, while their final applicability requires site specific verification. The results indicate that dust removal should be considered an integral element in the design of methane emission reduction systems based on VAM utilisation technologies. Full article

This article examines how grassroots civic mobilization can drive the transition from solid fuel combustion to low-emission urban heating systems, using the Kraków Smog Alert (KSA) as a case study. Employing the Multi-Level Perspective (MLP) framework alongside sociological theories of resource mobilization, frame analysis, and political opportunity structures, the study analyses the mechanisms through which civil society actors can shape energy policy and accelerate emission reduction at the urban scale. The empirical focus is the city of Kraków, Poland, historically one of Europe’s most severely air-polluted cities due to widespread domestic coal and wood combustion for heating. The study draws on documentary analysis, legislative records, stakeholder mapping, and expert interviews conducted within the CO-SUSTAIN research project (Horizon Europe, 2024–2026). The investigation traces KSA’s trajectory from a social media initiative founded in 2012 to the Polish Smog Alert, a national coalition encompassing nearly fifty local groups, culminating in a binding municipal ban on solid fuel combustion in 2019 and a subsequent reduction in PM2.5 concentrations exceeding 60% by 2023. Key strategic mechanisms identified include reactive scaling, health-based reframing of air quality as a public health issue, media amplification, and cooperative institutional engagement with regulatory bodies. An MLP chronological analysis spanning 1945 to 2024 maps landscape, regime, and niche dynamics that enabled the anti-smog energy transition; stakeholder mapping spans actors across NGOs, public institutions, media, and civil society. Findings demonstrate that landscape-level pressure from EU air quality and environmental protection directives alone was insufficient to drive regime change in domestic fuel use without credible, evidence-based niche actors capable of building alliances with institutional stakeholders. The findings offer transferable insights for coal-dependent cities across Central and Eastern Europe seeking to replace solid fuel heating with low-emission alternatives through integrated approaches combining environmental monitoring, energy policy reform, and civic governance. These findings matter for cities across Central and Eastern Europe still reliant on solid-fuel domestic heating, offering evidence-based guidance for civil society organizations and municipal policymakers seeking to accelerate the low-emission transition while protecting public health. Full article

Carbon-accounting studies of small, lightly industrialized provinces remain underrepresented despite their relevance to regional climate policy. This study quantifies energy-related CO₂ emissions from selected sources in Tunceli Province, Eastern Türkiye, for 2022 using the IPCC Tier 1 methodology, with an activity-based bottom-up road-transport estimate as a sensitivity analysis. Because the official grid factor is published on a CO₂-equivalent basis, we report the aggregate in Gg CO₂-eq yr⁻¹. Under the adopted activity-data assumptions, the selected sources were estimated to produce 288.47 Gg CO₂-eq yr⁻¹. The fuel-based road-transport series reaches a minimum in 2020, although observed vehicle-activity data are lacking. As an illustrative scenario conditional on the assumed coefficients, applying a literature-derived gross-uptake coefficient range of 2–5 t CO₂ ha⁻¹ yr⁻¹, whose local applicability could not be established, to 137,718 ha of productive closed-canopy forest gives an indicative gross sequestration potential of 275.44–688.59 Gg CO₂ yr⁻¹; the upper bound exceeds the compiled emissions, and the lower bound does not. So the comparison shows only that forest uptake capacity is of the same order of magnitude as emissions, not an observed net balance or an operating sink. Under ceteris paribus assumptions, a 75% reduction in residential coal use would avoid about 97.85 Gg CO₂ yr⁻¹ (33.9% of the baseline), roughly 42% of which would be reintroduced by natural-gas substitution. Residential heating decarbonization, building efficiency, and forest conservation emerge as mitigation priorities for small forest-rich provinces. Full article

Coal development produces large amounts of coal-based solid wastes (coal gangue, slag, fly ash) and substantial CO₂ emissions, posing severe ecological burdens on mining areas. This study integrated coal-based solid-waste cemented backfilling with CO₂ mineral sequestration to co-dispose of coal-based solid wastes and CO₂, experimentally investigating the CO₂ sequestration performance and uniaxial compressive strength (UCS) of coal-based solid-waste cemented backfill (CSCB) under mineralization curing with different CO₂ concentrations. TG-DTG, SEM-EDS, and XRD were adopted to investigate the CO₂ mineral sequestration process and the strength reduction of CSCB. The TG-DTG-based calculated CO₂ uptake of CSCB was positively correlated with the CO₂ concentration, rising by 86.9% from 2.52% to 4.71% as the concentration increased from 1.5% to 10%. In contrast, CSCB UCS decreased drastically by 88.1% from 6.05 MPa to 0.72 MPa when concentration increased from 0 to 10%. The combined microcharacterization results suggest that CO₂ reacted with alkaline substances and hydration products (CH, C-(A)-S-H gel, AFt) in CSCB to form carbonates. The UCS reduction is interpreted as arising mainly from a weakened alkaline environment (according to results and speculation), degradation of the C-(A)-S-H gel, and the AFt–CO₂ substitution reaction. Within the investigated conditions (a single mix proportion and a 14-day curing age), this study provides a reference for coal-based solid-waste backfilling coupled with CO₂ mineral sequestration; extrapolation to other mix proportions, longer curing ages, or field-scale applications requires further verification. Full article

The industrial sector in Liaoning Old Industrial Base exhibits energy consumption per unit of added value substantially above the national average, with carbon emissions from industrial energy consumption characterized by a large baseline and stringent reduction constraints. To address these challenges, this study applies the IPCC emission-factor method to construct a long time-series accounting of provincial carbon emissions from industrial energy consumption and develops a multi-dimensional carbon intensity evaluation system. An extended Logarithmic-Mean Divisia Index (LMDI) decomposition framework is employed to integrate five driving factors—energy structure, energy intensity, economic structure, per-capita economic output, and population scale—alongside differentiated mechanisms across four fossil-fuel categories (raw coal, crude oil, coke, and diesel). The results identify per-capita economic output as the dominant positive driver, while energy intensity and economic structure serve as primary abatement factors, with their cumulative contributions exhibiting notable phase transitions over the study period. These findings provide a quantitative foundation for designing industry- and region-specific emission-reduction policies and offer practical insights for reconciling industrial revitalization with the “dual-carbon” strategy in old industrial bases. Full article

This study presents a Life Cycle Assessment (LCA) conducted to evaluate the environmental performance of a Free-Piston Linear Generator (FPLG) compared to conventional internal combustion engines in two applications: automotive range extenders and stationary generator sets. A cradle-to-grave approach was adopted, covering production, use, and end-of-life phases, with consistent modelling of engine materials, fuel supply chains (gasoline, diesel, hydrogen), and mission profiles. The FPLG, modelled based on key components (e.g., stator, magnets, coils), was evaluated under multiple hydrogen-production pathways, including steam methane reforming, wind- and photovoltaic-powered electrolysis, nuclear-based hydrogen production, and coal gasification. Conventional engine baselines were assessed using gasoline, diesel, and hydrogen pathways. Results highlight that environmental impacts are strongly driven by the fuel supply chain, particularly the Well-to-Tank phase. When hydrogen is produced through wind-powered electrolysis, the FPLG achieves over 90% reduction in fossil fuel consumption and more than 80% reduction in greenhouse gas emissions compared to gasoline. With hydrogen produced through steam methane reforming, benefits are limited in automotive applications but remain significant for stationary systems (>20% reduction in greenhouse gas emissions). However, hydrogen produced through wind-powered electrolysis increases impacts in categories such as resource use and toxicity due to materials and infrastructure required for wind farms and electrolyzers. The extended pathway analysis further showed that nuclear-based hydrogen achieved the lowest global warming potential among the investigated hydrogen scenarios, whereas coal gasification produced the highest climate-change impacts. These results confirm that the environmental performance of hydrogen-fuelled FPLG systems depends strongly on the upstream hydrogen-production pathway. Full article

Surface deformation triggered by coal extraction activities, together with the consequent development of unstable slopes within rugged mountainous landscapes, constitutes a critical focus for geological risk assessment and mitigation strategies. Conventional SBAS-InSAR processing pipelines suffer from inadequate tropospheric phase mitigation in topographically complex environments, while existing clustering-based recognition approaches fail to incorporate sufficient geophysical constraints. To overcome these deficiencies, the present investigation introduces a refined methodology that synergizes InSAR measurements with an enhanced clustering scheme for the automated screening of potentially unstable slope units. First, a two-stage coupled atmospheric correction framework is constructed within the SBAS-InSAR processing chain, comprising spatially varying stratified atmosphere estimation based on geographically weighted robust regression (GWRR-M) and turbulent atmosphere compensation based on structure-guided deformation-preserving interpolation (SGDPI); both stages require no external meteorological data and effectively protect deformation signals from overcorrection. Second, a spatiotemporally constrained density peak clustering algorithm (STC-DPC) is developed, which constructs a multi-dimensional feature space integrating spatial location, deformation rate, temporal evolution characteristics, and topographic-geological background, and introduces a spatiotemporally constrained distance metric together with an Unstable Slope Index (USI) to achieve automatic identification and quantitative discrimination of unstable slopes. The proposed method was evaluated using 120 ascending-track Sentinel-1A SAR images acquired from 2019 to 2023 over the coal-mining mountainous areas of Mentougou and Fangshan districts in western Beijing, China. The results show that the improved atmospheric correction reduces the phase standard deviation of a representative interferogram from 1.6 rad to 0.6 rad, with an average reduction of 42.3% across all interferograms. A total of 187 unstable slopes were identified by the STC-DPC algorithm, mainly distributed in abandoned mining areas and steep terrain with gradients of 10–35°, with a mean deformation rate of −25.3 mm/a; field investigations at representative sites confirmed significant deformation evidence (e.g., tension cracks and bulging), providing qualitative support for the identification results. Compared with the identification results obtained without atmospheric correction (79 unstable slopes), the improved method improves the detectability of weak deformation signals in areas with strong topographic relief and diverse deformation patterns. This study provides a practical technical pathway for the early screening and monitoring of geological hazards in coal-mining mountainous areas and holds great significance for mine ecological restoration and regional disaster prevention and mitigation. Full article

Ukraine entered the definitive period of the EU Carbon Border Adjustment Mechanism (CBAM) in January 2026 as the largest exporter of CBAM-covered goods to the EU by physical volume, while its industrial base remains under direct wartime pressure. This study provides the first structural analysis of the open microaggregated dataset of the State Statistics Service of Ukraine (SSSU) on air pollutant and greenhouse gas emissions, covering 1990–2025 across 1284 territorial units, 128 substances, and 605 economic activities (NACE/KVED-2010). A documented harmonization procedure is proposed that resolves the 2020/2021 dimensional break and the ambiguity between oblast (region)- and hromada (municipality)-level records, yielding consistent 36-year series with independent national total validation for 2015–2025. Four phases are identified: transformational decline (1990–1999, −56.5%), stabilization (1999–2013, +4.6%), post-2014 structural decline (2013–2021, −47.9%), and the full-scale war shock (2021–2025, −55.0%). Stationary source emissions fell by 89.3% overall, but the wartime reduction reflects destruction and occupation of capacity, not decarbonization, as reflected in the collapse of metallurgy (−73.8%) and coke production (−89.6%) and the loss of the Mariupol district from statistical coverage after 2022. Mobile sources now supply 65% of the national total. Coal mine methane dominates stationary CH₄ (301 kt in 2021; ≈9.0 Mt CO₂ eq), directly relevant to Regulation (EU) 2024/1787. The regional Herfindahl–Hirschman index fell from 1847 (2021) to 1524 (2025), indicating war-driven regional deconcentration and a westward shift in the emission center of gravity. The findings are validated against independent satellite-based and conflict attribution estimates, and implications for monitoring, reporting and verification (MRV) infrastructure, CBAM default value exposure, and the phased design of Ukraine’s emissions trading system are derived. Full article

An in-depth understanding of the factors that enhance carbon footprints is a plausible pathway to enthrone environmental sustainability. Currently, the implications of energy and mineral depletion for carbon footprints in South Africa and Nigeria have received minimal empirical attention. The few available studies are non-exhaustive, often limiting broad-based policy refinements. With datasets spanning more than five decades (1971–2022), the novel Fourier Bootstrap Autoregressive Distributed Lag estimator was selected to account for structural breaks and nonlinearities. The empirical findings reveal divergent environmental pathways: South Africa’s carbon footprint (0.666% increase) is more related to energy depletion, reflecting coal-dominated electricity generation. Mineral depletion emerges as the primary culprit in Nigeria (10.856% increase), attributable to unregulated mining activities, including gas flaring and deforestation. Both countries face common challenges from urbanization (0.094% and 0.087% increases) and economic growth (0.107% and 0.046% increases). Trade openness shows insignificant effects. Short-run carbon footprint reductions from resource depletion improvements do not persist, underscoring the need for policy consistency. Policy effectiveness analysis identifies coal phase-out (0.9) and carbon pricing (0.8) as South Africa’s highest-return interventions. Mining regulation (0.9), green mining (0.9), and artisanal formalization (0.9) emerge as Nigeria’s priorities. The integration frameworks outperform siloed approaches. This implies South Africa may capture higher returns from policy coherence, while Nigeria may depend more on enforcement capacity. These findings provide evidence-based guidance for context-specific environmental policy design in resource-dependent economies. Full article