Urban air pollution constrains progress toward sustainable urban development, particularly where rapid growth intensifies the tension between economic activity and environmental health. Yet decision tools that compare mitigation options across environmental, social, technical, institutional, and economic dimensions remain limited. This study develops a sustainability-oriented multi-criteria decision-making (MCDM) framework that combines Fermatean Fuzzy Stepwise Weight Assessment Ratio Analysis (FF-SWARA) for criterion weighting and Fermatean Fuzzy Combined Compromise Solution (FF-CoCoSo) for strategy ranking. The assessment uses the UTOPIA structure and judgments from a seven-member interdisciplinary expert panel. Transformation Impact receives the largest main criterion weight, while Health Improvement is the most influential sub-criterion. Among five strategies, Renewable Energy and Energy Efficiency (S3) ranks first, followed by Strengthening Pollution Emission Standards (S5); S3 also retains first place throughout the λ sensitivity tests. These findings indicate that clean-energy transition, efficiency improvements, and credible emission regulation should be considered together in urban air-quality policy. Methodologically, the study contributes a Fermatean fuzzy decision framework that converts multidimensional expert evidence into transparent and policy-relevant priorities for sustainable air pollution management.
New-type urbanization (NTU), as a crucial pathway for China’s sustainable development, enhances residents’ well-being while simultaneously intensifying ecological pressures. Existing research still suffers from incomplete evaluation systems, insufficient application of remote sensing monitoring, biases in coupling coordination models, and inadequate identification of nonlinear mechanisms. To address these gaps, this study examines 108 prefecture-level cities in the Yangtze River Economic Belt from 2010 to 2022, constructing a multi-method integrated framework to comprehensively evaluate the coupling coordination relationship between NTU and ecological quality (EQ). The research employs combined entropy-AHP-game theory weighting with TOPSIS to assess NTU, builds an Adjusted Remote Sensing Ecological Index (ARSEI) on the GEE platform to measure EQ, introduces an improved Coupling Coordination Degree (CCD) model with Exploratory Spatiotemporal Data Analysis (ESTDA) to characterize spatiotemporal dynamics, and adopts XGBoost-SHAP to identify driving mechanisms. Results show: (1) NTU increased from 0.22 to 0.29, whereas EQ exhibited an M-shaped fluctuation and reached its lowest value in 2016 under the combined influence of cumulative urbanization-induced pressures and acute climatic extremes. (2) CCD improved from 0.4315 to 0.50, with 72.2
Climate change has emerged as a paramount global challenge over the past decade. With COP30 explicitly calling for the integration of “water security and climate adaptation” into Nationally Determined Contributions (NDCs), water is increasingly recognized as a critical medium linking climate mitigation, adaptation, and human-natural systems. Recognizing the multifaceted roles of water, this study develops a novel climate resilience evaluation index system and an integrated assessment model to provide robust decision support for climate action. First, to address the insufficient consideration of water in traditional frameworks, this study incorporates the triple identity of water—as a disaster-inducing medium, a regulatory tool, and a recovery resource—into the climate resilience index, specifically aligning them with the dimensions of robustness, recovery, and adaptation. Second, to overcome the inconsistency inherent in single-method evaluations, a hybrid Multi-Criteria Decision-Making (MCDM) model is constructed. This model enhances scientific rigor by eliminating marginal evaluation outliers through a combination of weighting and a consensus approach. Finally, an empirical analysis is conducted on the Shandong Peninsula in eastern China, followed by an investigation into the driving factors of climate resilience. The results demonstrate that the proposed index system and model exhibit high applicability for resilience assessment, offering a comprehensive framework for policymakers to design holistic climate change mitigation and adaptation strategies.
Recovering automotive components requires a reverse network that reconciles financial returns with sustainability and resilience. Decisions about facility suitability and future demand must therefore be connected within a circular planning framework that accommodates uncertainty. Here, fuzzy best–worst weighting and Gradient Boosting support location assessment, while SARIMA supplies demand estimates to a robust fuzzy, multi-objective network formulation. Goal programming with multiple choices and utility functions is used to select a compromise configuration. For three components examined in Tehran–Karaj, the solution established three collection facilities, two repair facilities, and two recycling facilities. Weights assigned to the twelve siting criteria lay between 0.08209 and 0.08482; the consistency ratio was 0.0683. Location classification attained 91.4
Climate-transition policies can reshape firms’ financing conditions, yet individual financing indicators may not capture the overall adjustment. We examine China’s Peaking-Carbon-Dioxide-Emissions Policy (PCDEP) using 2,013 listed firms over 2008–2021. We adapt an established two-stage network data envelopment analysis framework to measure network financing efficiency (NFE) and employ a difference-in-differences design. The PCDEP is associated with a 2.65-percentage-point decline in NFE among climate-policy-related firms. Long-term debt and dividend payouts decline, cash holdings rise, and observed financing costs fall, while the short-term debt estimate is insignificant. The negative NFE estimate persists after controlling for regional and industry shocks and concurrent environmental policies, and is corroborated by synthetic difference-in-differences. Channel analyses document greater reliance on supplier financing, increased capital expenditure and green invention activity, and higher ESG-oriented fund participation and government subsidies. Environmental investment and bank-loan composition show no detectable average response. The financing-efficiency response is more favorable among firms with higher ESG ratings and state ownership, but less favorable in regions facing greater carbon-reduction pressure. The decline is more pronounced in the later post-policy period, indicating that the financing adjustment extends beyond the policy’s introduction within the observed sample. These findings highlight the importance of coordinating climate-transition objectives with access to long-horizon finance, credible climate-related disclosure, and support tailored to firms’ adjustment needs.
