Search Results (17,696)

Improving the effluent quality of municipal wastewater treatment plants (WWTPs) is essential for sustainable water management and water quality protection in the Yellow River Basin. Many existing WWTPs in northern China were constructed under earlier discharge requirements and now face dual challenges of stricter effluent standards and poor low-temperature performance in winter. In this study, a municipal WWTP with a design capacity of 5 × 10⁴ m³/d in northern China was upgraded to improve winter treatment performance and support stable compliance with the discharge requirements of the Yellow River Basin. The original anaerobic + oxidation ditch process suffered from unstable effluent quality, excessive sludge loading, and insufficient pollutant removal under low-temperature conditions. A land-saving retrofit strategy was therefore proposed, involving oxidation ditch wall-height raising to extend the hydraulic retention time (HRT) and membrane bioreactor (MBR) integration to increase the mixed liquor suspended solids (MLSS) concentration. After the retrofit, the total HRT increased to 19.82 h, and the average MLSS concentration reached 7050 mg/L. The relative abundances of key nitrogen-removing bacteria, including Nitrospiraceae, Nitrosomonadaceae, and Rhodocyclaceae, increased markedly. Meanwhile, denitrification sludge loading and BOD₅ sludge loading decreased to 0.030 and 0.033 kg/(kg·d), respectively. Under low-temperature conditions, the theoretical removal capacities of total nitrogen (TN) and BOD₅ reached 44.32 and 286.19 mg/L, respectively, enabling stable effluent compliance. The results show that this retrofit strategy can improve WWTP effluent quality while avoiding large-scale land expansion, providing a practical and sustainable solution for upgrading cold-region WWTPs along the Yellow River Basin. Full article

The durability of building façades is critical to sustainable construction because it affects maintenance demand, safety, and long-term service performance. As building stocks age, especially in rapidly urbanizing countries such as China, reliable prediction of façade degradation becomes increasingly important for service-life planning and maintenance decision-making. However, conventional service-life prediction methods are commonly based on ordinary least squares (OLS) regression, which mainly estimates the conditional mean and may therefore fail to represent the heterogeneity of degradation processes. Using visual inspection data from 375 painted façade samples in Ningbo, China, this study applies quantile regression (QR) to model façade degradation and predict service life. Degradation was quantified using an overall degradation level (ODL) index that integrates defects related to aesthetic deterioration, loss of integrity, and loss of adhesion. The results show that façade degradation follows heterogeneous rather than uniform trajectories, and that the effects of key variables vary across degradation levels. In particular, pollution exposure and water ingress become markedly more influential at higher quantiles, while the effect of routine maintenance weakens in severely degraded façades. After 5-fold cross-validation, the median quantile model reduced MAE by approximately 5.3% relative to the OLS benchmark (0.0537 vs. 0.0567), and the fitted quantiles showed good calibration, with empirical coverage deviations not exceeding 0.007. The QR framework predicted a service-life range of 4.3–31.8 years, substantially wider than the 8.8–20.2 years obtained from the MLR model, indicating a stronger ability to represent uncertainty and high-risk degradation paths. These results show that QR provides a more informative basis for risk-based inspection planning and façade service-life assessment in existing buildings. Full article

While valorisation pathways are increasingly promoted as sustainable solutions, their ability to genuinely minimise environmental harm and contribute to long-term material circularity remains uneven. This study systematically identifies and maps existing valorisation routes across the EU and UK, with particular attention to their environmental performance and economic viability through a material value retention lens. A literature review highlights a spectrum of practices—from soil amendment and composting to bioenergy recovery and bio-based construction materials—each offering different sustainability benefits but varying significantly in their capacity to preserve material quality and function. To address the absence of robust comparative approaches, this paper introduces a novel evaluative framework centred on intrinsic material value retention, a key principle in sustainable and circular material systems. Building on established scholarship, the framework provides a structured means of comparing valorisation options based on how effectively they conserve material properties, particularly in terms of the material’s structural and functional values, and enable high-value reuse. Supported by a dedicated classification tool and a set of guiding questions refined through expert interviews, the framework complements existing environmental assessment methods by foregrounding material circularity. In doing so, it supports more integrated, holistic decision-making for the development of a resilient and sustainable circular bioeconomy. This research is intended for academic audiences and may also be of relevance to industry practitioners. Full article

In the Internet of Vehicles, vehicular crowdsensing is crucial for alleviating traffic congestion and ensuring the safety of autonomous driving. However, practical vehicular crowdsensing processes face dual challenges of skewed spatial distributions of vehicles and inadequate data quality guidance. These issues cause sensing redundancy in high-participation areas (HPAs) and coverage deficits in low-participation areas (LPAs), while also leading to unstable data quality. Given that participants’ decisions are profoundly influenced by bounded rationality and psychological preferences, this paper proposes a collaborative incentive mechanism integrating behavioral economics and psychology (BEP-IM) to drive sustained spatial coverage and proactive sensing shaping. First, to mitigate coverage deficits in LPA, a reference-dependent two-sided selection and bidding strategy (RD-TSB) is designed to guide participants toward LPA via a reference-driven utility evaluation. Concurrently, a loss-aversion-based sustained incentive strategy (LA-RPI) is introduced to enhance their sustained participation within LPAs by amplifying loss perception. Furthermore, to overcome weak data quality constraints, an operant conditioning-based proactive sensing shaping strategy (OC-SFQ) is constructed, utilizing a closed-loop mechanism of relative improvement, variable-ratio reinforcement, and association updating to drive participants to output high-quality data. Simulation results demonstrate that the proposed mechanism effectively increases participation frequency in LPAs and optimizes sensing data quality. Full article

Strategies based on the use of recycled materials have been widely discussed as alternatives to reduce environmental impacts in transport infrastructure. In pavement engineering, the use of Reclaimed Asphalt Pavement (RAP) in base layers offers environmental benefits; however, its benefits depend on processing conditions and structural performance. Chemical stabilization techniques, although mechanically effective, tend to introduce environmental hotspots associated with binder production. In this study, controlled thermal conditioning of RAP is evaluated as a warm base solution without chemical stabilizers in the context of airport pavements. A comparative life cycle assessment was conducted under a production- and construction-stage scope (A1–A3 and A5, excluding transportation under equivalent logistical assumptions), considering untreated RAP, heated RAP, and RAP stabilized with emulsion and cement, and was integrated with mechanistic–empirical structural performance analyses. The results indicate that, although heated RAP presents intermediate absolute environmental impacts due to additional energy consumption, it achieves the highest eco-efficiency, expressed as the lowest ratio between global warming potential (IPCC 2023) and estimated structural service life. In the analyzed scenarios, the warm base showed approximately 71% lower environmental impact per year of service than untreated RAP and about 90% lower than the emulsion-stabilized alternative. These findings suggest that performance-based sustainability assessment can reveal environmental advantages in solutions that exhibit moderate increases in production-stage impacts but enhanced structural longevity. It should be noted that the conclusions are conditioned by the adopted production and construction system boundaries, which do not include the use, rehabilitation, or end-of-life phases. Full article

The construction sector consumes significant amounts of natural resources and contributes substantially to global CO₂ emissions, making it necessary to develop materials with a reduced environmental impact. In this context, the valorization of reusable industrial waste as secondary raw materials represents a strategic direction for applying circular economy principles and for decarbonizing the construction materials industry. The scientific problem addressed in this review is the urgent need to develop construction materials with a reduced environmental footprint, given that the construction sector is a major consumer of natural resources and a significant contributor to global CO₂ emissions. This challenge requires the identification and critical evaluation of sustainable solutions that support decarbonization and the transition toward a circular economy. The main findings indicate that the valorization of industrial waste offers high decarbonization potential: supplementary cementitious materials (SCMs), such as ground granulated blast furnace slag and fly ash, can reduce CO₂ emissions by approximately 20–50%, while alkali-activated binders and geopolymers achieve reductions of 40–80% compared to Portland cement. These materials also enhance durability, extending service life by 10–20% in aggressive environments, although early-age strength may decrease by 10–30%; recycled aggregates derived from construction and demolition waste (CDW) can substitute up to 100% of natural aggregates, while rubber fibers can increase impact resistance by 30–50% and reduce density by 10–20%. However, key limitations relate to waste variability, heavy metal leaching risks (requiring immobilization efficiencies > 90%), and the relatively low technological maturity of many solutions (TRL < 7), leading to the TRL–CO₂ paradox and highlighting the need for standardization and performance-based regulatory frameworks. The synthesized results indicate that the appropriate integration of industrial waste enables a significant reduction in clinker content, lowers associated CO₂ emissions, and decreases primary energy consumption while maintaining physical–mechanical properties and durability characteristics comparable to or in some cases superior to those of traditional materials, if mix design is based on clear performance criteria, stratified according to the type of waste, dosage used, curing regime, binder chemistry, and the target application. Full article

Green Total Factor Productivity (GTFP) serves as a pivotal indicator for balancing high-quality economic growth with increasingly stringent environmental regulations. However, empirical evidence regarding whether and how firm-level GTFP is associated with enhanced Environmental, Social, and Governance (ESG) performance in emerging markets remains limited. This study addresses this gap by examining the GTFP–ESG nexus within the macro-context of China’s “Dual-Carbon” goals (aiming for peak carbon emissions by 2030 and carbon neutrality by 2060). Utilizing an unbalanced panel dataset of Chinese A-share listed companies strictly covering the period from 2011 to 2022 (with 2010 data exclusively used for one-period lagged variables), we construct firm-level GTFP metrics using a non-radial SBM-DDF global Malmquist–Luenberger index—incorporating both desirable economic outputs and undesirable environmental emissions—and link them with Huazheng ESG ratings. To ensure robust empirical identification, we employ two-way fixed-effects models with lagged variables, propensity score matching (PSM), and an instrumental variable two-stage least squares (IV-2SLS) approach utilizing the leave-one-out provincial average GTFP as an instrument. The results indicate a significant positive association between GTFP and overall ESG performance, as well as its three sub-pillars. Specifically, a one-standard-deviation increase in GTFP corresponds to a 0.15-standard-deviation increase in the ESG score, a marginal effect of profound economic significance, providing robust associational insights via the IV estimates. Mechanism analyses reframe traditional mediation as descriptive associational pathways, revealing that digital transformation, green innovation, and information transparency serve as significant channels, theoretically demonstrating how resource efficiency translates into social legitimacy. Heterogeneity tests show that this association is more pronounced for non-state-owned enterprises, firms in eastern China, and those with lower financing constraints. These findings unpack the “black box” between technical efficiency and sustainability, providing empirical support for policymakers to align corporate productivity with international disclosure standards (such as the EU’s CSRD). Full article

Despite the extensive literature on microalgal production, most studies focus on controlled laboratory-scale systems, resulting in a critical lack of confidence at industrial scale. This is further compounded by the frequently observed inconsistencies, with only modest increases achieved in operational scale. This work demonstrates the design, construction, and operation of a commercial-scale tubular photobioreactor and associated equipment for the production of algae using CO₂ derived from an industrial nickel refinery. The reactor was demonstrated by growing the species Nannochloropsis gaditana. Biomass concentrations of 1.0 to 1.3 g L⁻¹ were achieved with a productivity of 0.11 g L⁻¹ d⁻¹. Extrapolation to a 300-day production year showed that the reactor was capable of producing 541.2 kg algae and sequestering around 1 tonne of CO₂. A technoeconomic assessment showed that the total plant CAPEX was £583,905 and the OPEX was £98,196. Sales of algae alone showed poor economic performance. However, economic favourability is observed for species that contain phycocyanin pigment and yield a positive net present value within 4 to 7 years based on recovery yield. This work effectively provides reliable process data developed at scale that can be used to formulate business cases for further scale-up and expansion of algal production systems. This moves the technology a step closer to full-scale realisation and the potential for a net-zero, sustainable future. Full article

In the context of China’s “Dual Carbon” goals, the composite policy mechanism combining carbon trading and carbon taxation is widely considered a key pathway to achieve emission reductions. Although households are a major source of carbon emissions, their consumption behaviour has long remained outside the mainstream carbon reduction system, as existing policies focus primarily on enterprises and lack sufficient household-level participation and incentive mechanisms. Because China has not yet implemented an actual carbon tax, this study uses household high-carbon consumption dependency (HCD) as a proxy variable to capture the hypothetical administrative pressure that a carbon tax would impose on high-carbon consumption. Based on the concept of “Carbon Inclusion”, we construct an analytical framework for a composite mechanism that combines the carbon trading pilot policy (ETS) with this carbon-tax proxy. Using data from the China Family Panel Studies (CFPS) and a two-way fixed-effects panel model, we empirically test the impact of this composite mechanism on household carbon emissions (total volume) and carbon intensity. The findings show that, while the composite mechanism does not lead to a statistically significant reduction in total household carbon emissions, it effectively lowers household carbon intensity by restraining high-carbon consumption and optimizing the consumption structure. This decoupling of intensity from total volume occurs because the mechanism reduces the share of high-carbon consumption (a compositional effect) but does not suppress total consumption growth (a scale effect). This result remains robust across multiple tests, confirming the policy effectiveness of the composite mechanism at the micro-individual level. By reducing carbon intensity without suppressing total consumption, this mechanism contributes directly to sustainable development, aligning with UN Sustainable Development Goals 12 (Responsible Consumption and Production) and 13 (Climate Action). The main contributions of this paper are threefold: (1) it moves beyond traditional single-policy or single-agent studies by linking a carbon-trading-and-proxy-carbon-tax composite mechanism with household carbon consumption; (2) it explores a Carbon Inclusion pathway that connects households, enterprises and the nation; and (3) it provides empirical support and a theoretical reference for improving household-level emission reduction policies and promoting public participation in achieving the “Dual Carbon” goals. Full article

Coal gangue (CG) and iron tailings (ITs) are major industrial solid wastes, and their high-value reuse is crucial for sustainable construction materials. This study explores the feasibility of fabricating sintered porous bricks using CG and ITs as primary constituents, with shale as an auxiliary component. To evaluate durability in cold regions, laboratory freeze–thaw (F-T) cycling experiments were conducted. A degradation assessment framework based on the Wiener stochastic process was developed to predict frost-resistance service life by integrating experimental data with regional climatic conditions. Results show that the fabricated bricks exhibit satisfactory initial properties, with a compressive strength of 10.6 MPa and water absorption of 13.3%. With increasing F-T cycles, compressive strength decreases significantly, accompanied by increased mass loss and water absorption. Stress–strain analysis reveals progressive stiffness reduction and a transition from brittle to ductile failure. Microstructural observations confirm degradation of the glassy phase, pore expansion, and enhanced interconnectivity. The Wiener process-based model effectively describes the stochastic accumulation of F-T damage. By establishing equivalence between laboratory and natural F-T cycles, the long-term service life of coal gangue–iron tailing sintered porous bricks (CG-IT SPBs) in cold regions is theoretically evaluated. This work provides an integrated understanding of F-T damage behavior and establishes a scientific foundation for durability-oriented design and application of such bricks in extremely cold environments. Full article

This study proposes a data-driven evaluation framework to quantify the impact of artificial intelligence (AI) on industrial process performance and enterprise value creation. The framework integrates enterprise value assessment based on the Feltham–Ohlson model with a multi-level performance evaluation framework that incorporates a hybrid Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) for indicator weighting, together with Fuzzy Comprehensive Evaluation (FCE) for multi-dimensional aggregation. This integrated approach enables systematic analysis of AI-driven effects from the perspectives of intelligent investment input, operational governance environment, and process output performance. Using panel data from 3515 Chinese A-share listed firms (20,076 firm-year observations) during 2014–2022, a Process Performance Index (PI) is constructed to measure AI-enabled operational capability across resource allocation efficiency, coordination effectiveness, and production performance dimensions. Empirical results indicate that PI is positively associated with abnormal earnings and firm profitability, demonstrating that AI-enabled process capability contributes to sustained enterprise value growth. The findings further show increased digital technology investment intensity, knowledge-based human capital accumulation, and improved data governance conditions, accompanied by enhanced production and service performance. By explicitly integrating AHP–EWM weighting and FCE aggregation within the Feltham–Ohlson valuation structure, the proposed framework provides an interpretable quantitative mechanism linking AI adoption, operational capability development, and enterprise value creation. The results offer practical insights for evaluating intelligent transformation strategies in the context of Industry 5.0 and data-driven industrial development. Full article

Infrastructure projects of significant scale face persistent challenges in data coordination, scheduling, and cost control. Although individual digital tools are widely adopted in the construction sector, empirical evidence on their coherent systemic integration within a unified management cycle remains limited. This explanatory case study addresses that gap by examining ^{Section 3} of the Sibiu–Făgăraș Motorway (17.61 km, 27 structures) in Romania—an ongoing TEN-T project. Evidence was collected during the active construction phase (January 2022–December 2024) from Common Data Environment (CDE) logs, BIM/BrIM model outputs, drone photogrammetry datasets, schedule and payment records, and Business Intelligence (BI) dashboards. The study demonstrates how six digital applications—CDE, model-based fabrication (LOD 400), 3D coordination, 4D/5D simulation, reality capture, and BI dashboards—were operationalized as a closed-loop Plan–Do–Check–Act (PDCA) cycle, functioning as a human-in-the-loop digital twin for project Please check if this address is duplicate with aff .1 or not. If so, please merged them into one and revise the author’s associated number and ensure that each number in numerical order. delivery. Illustrative operational indicators observed during implementation include an estimated 20% reduction in coordination-related RFIs, a 15% reduction in steel fabrication material waste, a reduction in payment validation cycle time from 15 days to approximately 2 days, and a 40% improvement in cash flow stability through data-driven activity re-sequencing. These findings suggest that systemic digital integration, rather than isolated tool adoption, supports more proactive and sustainability-aligned infrastructure project control. Full article

The construction sector contributes approximately 40% of global energy-related CO₂ emissions, necessitating the development of low-carbon and high-performance sustainable building materials. The lightweight volcanic glass known as expanded perlite is an excellent candidate due to its pozzolanic reactivity, thermal insulation, and self-compacting properties. The literature review presented here is based on 100 articles (1985–2024) and examines the mechanical, thermal, durability, and sustainability aspects of this material. According to the literature, the incorporation of expanded perlite significantly reduces thermal conductivity, from 1.81 W/m·K in conventional concrete to 0.69 W/m·K and further to 0.034–0.06 W/m·K in insulation-oriented mixes. In addition, ground perlite exhibits enhanced pozzolanic reactivity, yielding up to 50% higher compressive strength at a 35% replacement rate. When added to self-consolidating concrete, perlite at 220–260 kg/m³ makes mixes more durable by reducing permeability, carbonation, and chloride-ion migration. However, higher perlite replacement levels adversely affect mechanical performance, with early-age compressive strength decreasing by more than 60% when cement replacement exceeds 30%. The appropriate percentage of perlite depends on the desired outcome. A content of 20% is ideal for balancing strength and durability, while higher levels up to 50% improve insulation and reduce density (25–400 kg/m³). Overall, expanded perlite demonstrates strong potential to enhance durability, reduce permeability, and improve sulfate resistance, positioning it as a viable material for low-carbon construction systems. Full article

Mining plays a key role in economic development but faces increasing challenges in reconciling sustainability with social expectations in the territories where extractive activities operate. In regions with a strong mining presence, incorporating community perceptions has become essential for guiding sustainable development strategies. However, systematic evidence to prioritize these dimensions at the local level remains limited. In this context, the present study identifies and ranks critical sustainability factors from the perspective of communities located near mining projects in the Coquimbo Region, Chile. To structure the decision problem, the Analytic Hierarchy Process (AHP) was applied. This multi-criteria decision-making (MCDM) method integrates qualitative and quantitative judgments through pairwise comparison matrices processed using Expert Choice software, based on a hierarchical structure of criteria, subcriteria, and decision elements associated with social, economic, and environmental dimensions. The results indicate that the criterion with the highest global priority was “Improvement in health, social cohesion, and quality of life” (36.3%), followed by “Economic development” (20.3%) and “Local development and social participation” (15.7%). Among the most prioritized actions were “Construction of health facilities” (15.5%), “Promote the hiring of local labor” (8.7%), and “Protection and continuous monitoring of aquifers” (6.3%). Sensitivity analysis confirmed the stability of the model, suggesting that the proposed framework can support the systematic incorporation of community perceptions into the planning of mining sustainability strategies. Full article

Under the strategic context of building a transportation powerhouse in China, the transportation sector faces the dual challenge of reducing emissions while improving efficiency. This study constructs a two-dimensional regional classification framework based on the “economic-carbon” dimension and systematically investigates the coordinated evolution of the development level (TD) and carbon emission intensity (TCEI) of the transportation systems in 31 provinces of China from 2014 to 2023, using methods such as entropy weight TOPSIS, the coupling coordination degree (CCD) model, kernel density estimation (KDE), spatial autocorrelation analysis, and the XGBoost-SHAP explainable machine learning framework based on transfer learning. The study finds that (1) TD shows a fluctuating upward trend, while TCEI continues to decline, with regional imbalances; (2) in terms of time, CCD shows a general upward trend with an N-shaped evolution; spatially, CCD presents a pattern of stronger coordination in the east and weaker in the west, with sustained regional heterogeneity, forming a development pattern of “Region I leading, Region II breaking through, Region III maintaining, Region IV catching up”; and (3) regarding the driving factors, freight volume, transport industry output value, and passenger turnover are the core driving factors of CCD, with significant regional heterogeneity in their mechanisms. This study provides a systematic analytical framework and differentiated policy tools for promoting coordinated regional development of green transportation. Full article