Using panel data on Chinese A-share listed private enterprises from 2009 to 2023, this study examines the relationships among listing-time private equity (PE) backing, ESG communication, externally rated ESG practices, and subsequent total factor productivity (TFP). TFP is interpreted as the economic-efficiency and productive-capacity dimension of sustainable corporate development rather than a comprehensive sustainability measure. ESG Talk captures annual-report textual attention or disclosure salience, whereas ESG Do is a third-party rating-based proxy for observable ESG practices or outcomes. In the baseline specification, which contains 12,327 firm-year observations, listing-time PE backing is positively associated with TFP (β=0.0185, p<0.01), although the estimate is sensitive to balancing and richer adjustment for persistent firm heterogeneity. Within the post-listing age 0–6 sample, Social Talk is positively associated with Social Do across all four industry groups examined, while overlap-weighted Talk–Do configuration contrasts do not show that High Talk–High Do firms have higher TFP. Environmental evidence is weaker and more conditional. The results provide bounded conditional associations and exploratory pathway evidence, not identified causal or mediation effects.
Timely computation of vegetation indices from remote sensing imagery would assist in sustainable agriculture monitoring through quick analysis of vegetation state and surface water. However, high-resolution multispectral imagery can be computationally expensive to process, especially on embedded systems. In this research work, we evaluate heterogeneous approaches that aim to enhance the computation of the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI) through sequential C++, OpenMP, CUDA and OpenCL on desktop and embedded CPU–GPU platforms. We compare multicore and GPU-based computations while also exploring optimizations of the OpenCL kernels with respect to memory management, loop unrolling and work-group settings. OpenMP increased the image-processing throughput from 211.24 to 500.85 images/s on the desktop platform and from 55.30 to 145.11 images/s on the Odroid XU4. These results correspond to speedups of 2.37× and 2.62×, respectively. These results demonstrate that heterogeneous processing can accelerate vegetation index calculation and provide a computational basis for timely, locally available agricultural monitoring. This capability may support precision agriculture applications, including vegetation stress assessment and water management decisions. Nevertheless, the experiments used offline multispectral images; energy consumption, energy per image, water savings, and onboard UAV performance were not measured.
Carbon dioxide is the number one choice for use as a natural refrigerant for environmentally friendly and sustainable solutions in refrigeration technologies today. It is used for new installations required for all types of applications, from small cold rooms in restaurants or supermarkets to large industrial applications. Practically, it is used to cool down solid products or liquids. Due to its significant inefficiencies, especially related to high operating pressures and throttling processes, the basic CO2 transcritical refrigeration system requires improvement for superior overall efficiency. For this reason, this review paper provides insight into four types of improved CO2 transcritical refrigeration systems: first, a CO2 transcritical refrigeration system with one EJ or dual EJs, parallel compression, and mechanical subcooling; second, a CO2 transcritical refrigeration system with two-stage heat recovery and a GS/CC heat exchanger; third, a CO2 transcritical refrigeration system with two-stage compression and intermediary gas supplementation; and fourth, a solar-assisted ejector subcooling CO2 transcritical refrigeration system. These systems provide COP increases of 21.6%, 26.3%, 25%, up to 30.1%, and 3.4%, as calculated for certain conditions. This review paper explains the mathematical modulation assumptions, energy model construction, heat recovery thermodynamic principle, and conventional and advanced exergy evaluation. As a result, all four improved CO2 transcritical systems have superior efficiency when compared with standard CO2 transcritical systems, consuming less energy and being suitable for use in real applications.
We examine whether digital industry cluster policy is associated with corporate environmental, social, and governance (ESG) performance. We study digital industry clusters within China’s Innovative Industrial Cluster program, a spatial industrial policy combining cluster designation, fiscal support, digital infrastructure, and innovation platforms. Using Chinese A-share listed firms from 2009 to 2023, we exploit staggered cluster designation across cities and estimate difference-in-differences models with firm and year fixed effects. Cluster designation is associated with higher ESG scores, mainly through the governance dimension and, to a lesser extent, the environmental dimension. Additional analyses show that treated firms receive more government innovation subsidies, face lower financing constraints, and increase R&D intensity, consistent with resource provision channels. The results are robust to industry-by-year and province-by-year fixed effects and to wild cluster bootstrap inference. Effects are stronger for firms with greater market attention and in high-technology industries, and larger in regions with weaker digital infrastructure. The findings provide firm-level evidence on how spatially targeted digital industrial policy may support corporate sustainability practices.
State Council Document No. 43 and the revised Budget Law legally disclaimed Chinese local governments’ responsibility for the debts of the enterprises they own. Across 22,233 firm-year observations on 1686 listed firms from 2009 to 2023, the effective cost of debt of local state-owned firms fell by 0.33 percentage points relative to private firms, 5.5 percent of its mean. The direction was not obvious in advance: withdrawing a guarantee that lenders had been pricing should have made credit dearer, while the debt swap enacted alongside the disclaimer replaced high-cost vehicle liabilities with low-cost provincial bonds and eased the balance sheets standing behind those firms. Central state-owned enterprises, whose support the reform left untouched, serve as a falsification group and show no statistically distinguishable change. The estimate passes the joint pre-trend test, survives matching, entropy balancing and twenty specification changes, and operates through the interest paid rather than the quantity of debt, which identifies a price effect. Investment rose by 0.76 percentage points of assets, but no improvement in investment efficiency was detected, and an equivalence test cannot exclude a small one. A cross-sectional pattern consistent with fiscal relief does not survive correction for multiple testing, so that channel is reported as suggestive rather than identified. Hardening the budget constraint of local governments lowered the debt servicing burden of the firms they own without directing the freed resources toward more productive use, so the sustainability gain is fiscal rather than allocative.
Public participation plays a crucial role in modernizing urban renewal and advancing social sustainability; however, micro-renewal practices often navigate complex institutional coordination and varying levels of community engagement. To better understand these operational dynamics, this study adopts an institutional–behavioral analytical framework to examine how institutional mechanisms shape public participation, grounded in an empirical investigation of pocket parks in Shenyang, China. Integrating policy text analysis with 20 in-depth interviews framed within a citywide baseline of 3198 pocket parks, qualitative content analysis reveals that coercive, mimetic, and normative institutional pressures foster three distinct implementation pathways: Mandate-Driven, Exemplar-Driven, and Collaborative Co-governance. These pathways generate differentiated behavioral responses across four key stakeholder cohorts, while highlighting specific alignment opportunities regarding governance timing, feedback channels, and inter-departmental roles. To resolve these operational friction points and secure long-term social and institutional sustainability, we propose a full-lifecycle governance strategy offering group-tailored policy recommendations. This research bridges neoinstitutional theory with participatory spatial governance, providing actionable insights for advancing sustainable urban micro-renewal and stock space management.
Rural cultural revitalization is the soul and endogenous driving force of comprehensive rural revitalization. The continuous optimization and effective implementation of the policy system serve as the core guarantee for promoting the sustainable development of rural cultural construction. Existing studies mostly conceptualize policy operation as a linear process, overlooking the dynamic closed-loop relationship among attention allocation, policy change, and effect evaluation, which results in fragmented policy implementation and insufficient sustainability. Accordingly, this study constructs an integrated analytical framework of “Attention–Change–Evaluation” for policy, incorporating policy attention (A), policy change (B), policy implementation (C), policy evaluation (D), and policy feedback (E) into a unified closed-loop system. It proposes H1–H14 hypothetical paths to reveal the multiple mechanisms through which attention influences effect evaluation via policy change, policy implementation, and their chained combinations. The findings indicate that the operation of rural cultural construction policies is not a unidirectional causal chain, but rather a periodic closed loop formed by the end-to-end connection of the main transmission chain (A→B→C→D) and the reverse feedback path (D→E→A). Policy attention jointly affects policy evaluation through both direct effects and indirect chained effects, driving the policy shift from one-off task fulfillment to continuous dynamic adjustment. The study suggests that establishing an effective linkage mechanism between policy feedback and attention reconfiguration is the key pathway to achieving sustainable development of rural cultural construction policies.
In this study, we examine whether digitalization, measured by internet, fixed telephone, and mobile phone usage, has helped to lower carbon dioxide (CO2) emissions. The correlation between ICT and CO2 emissions is assessed via panel data analysis using a sample of 33 years of G20 countries’ data. We use mediation analysis to express the association between digitalization and CO2 via a set of channels, and we implement a panel econometrics model to measure the influence of digitalization and CO2 through both direct and indirect relationships. The association between digitalization and CO2 is divided into two channels: these channels have direct and indirect relationships, with the latter operating through different paths, encompassing industry, trading, and energy consumption from different sources, such as renewable and fossil fuels. Mediation analysis is used to distinguish between direct and indirect relationships, with our findings suggesting a nonlinear relationship between ICT and CO2 emissions that resembles an environmental Kuznets curve.
Agricultural burning remains a persistent environmental challenge in many rural production systems. This study examines how and under what conditions rural transformation reshapes material dependence on and perceived social defensibility of agricultural burning. Using a qualitative multiple-case design, 30 semi-structured interviews were conducted in three rural communities in northern Thailand with farmers, village heads, residents and government officials. Data were analysed through within-case analysis and cross-case comparison. The findings identify three pathways through which rural transformation can weaken dependence on fire: functional replacement, functional removal and residue revaluation. Dependence nevertheless persists where labour scarcity, steep terrain and other production constraints limit workable alternatives. Practical substitutability therefore conditions whether production-system change reduces dependence on fire. Material dependence also becomes normatively consequential through perceived necessity. Where burning remains difficult to avoid, its harmful effects may be recognised while continued use remains perceived as socially defensible. Where necessity weakens, continued burning becomes harder to justify. These evaluations are interpreted as perceived social defensibility rather than community-wide normative consensus. The study contributes by identifying practical substitutability and perceived necessity as mechanisms linking rural production restructuring to material dependence and perceived social defensibility, explaining why material, behavioural and normative trajectories may align or diverge.
Augmented reality head-up display (AR-HUD) navigation is becoming a practical road–vehicle interface in intelligent transportation systems. However, it remains unclear how AR-HUD navigation symbols reshape lateral fixation transitions and attention distribution across maneuver phases. This eye-tracking study divided fixation sequences into nine maneuver scenarios and analyzed them using first-order Markov transition probabilities, the time-normalized area under the curve (AUC) of horizontal fixation position, and fixation-to-arrow-tip distance. Exploratory maneuver-level analyses suggested that AR-HUD cues attenuated, but did not eliminate, center bias, and redirected fixation toward the target direction. A participant-mean sensitivity analysis (n = 20) retained AUC differences after false discovery rate (FDR) correction in the pre-lane-change-left, pre-lane-change-right, and pre-turn-left scenarios, whereas several maneuver-phase effects were less robust after aggregation. The converging proximity and lateral-distribution patterns suggest guided spatial occupancy as a provisional description of attentional influence extending from the rendered arrow toward the maneuver-relevant region it implies. The findings concern driver attention and interface behavior; traffic-flow and environmental outcomes were outside the scope of the present measurements. These findings provide empirical guidance for optimizing the timing and spatial placement of in-vehicle AR cues during maneuver preparation, while their safety benefits require confirmation in interactive and naturalistic driving. Because the retained sample comprised young licensed drivers aged 19–25 years and the task involved passive video viewing, these implications should not be generalized to older drivers, the wider licensed-driver population, or closed-loop vehicle control without age-diverse interactive validation.
The transition toward Industry 5.0 requires safety management systems that are not only intelligent and data-driven but also human-centric, resilient, and aligned with sustainable operations. However, conventional safety risk assessment in steel manufacturing remains heavily dependent on expert judgment and often lacks the adaptability required to address complex and dynamic production environments. This study proposes a text-driven intelligent framework for sustainable safety risk governance by integrating natural language processing, topic modeling, objective indicator weighting, and Bayesian decision fusion. The framework establishes a closed-loop process encompassing risk identification, quantitative assessment, risk classification, and hierarchical control. It automatically extracts risk-related information from unstructured safety records, maps the identified hazards onto a human–machine–environment–management structure, quantifies multidimensional risk indicators, and translates assessment outcomes into differentiated control measures. The framework was evaluated using field safety records collected from Tianjin Iron and Steel Group. The topic modeling results identified four major dimensions of operational risk, while the CRITIC–Bayesian weighting mechanism combined data-driven indicator differentiation with context-sensitive probabilistic reasoning. Following its integration into the company’s intelligent safety management platform and one year of operational use, the framework reduced the time required to formulate safety inspection plans by 70%, supported dynamic four-level risk classification, and achieved a 97% task completion rate. The number of recorded safety accidents also decreased by 35% compared with the pre-deployment baseline. These findings demonstrate that unstructured safety text can be transformed into actionable risk intelligence, enhancing the proactive, systematic, and adaptive governance of safety risks. The proposed framework provides a practical pathway for advancing human-centric safety management, operational resilience, and sustainable production in the steel industry.
Commercial format diversity serves as a key indicator indicative of the health and resilience of the commercial structure in rail transit station areas. This study focuses on the rail transit station areas in Shanghai, integrates multi-source geospatial data with Partial Least Squares Structural Equation Modeling (PLS-SEM), and systematically examines the differential influence paths of six categories of factors—urban form, location, facility configuration, passenger flow, land rent, and commercial spatial form—on commercial format diversity between urban core and suburban areas. Multi-group analysis (MGA) is further used to test whether path coefficients differ across concentric zones around stations. The findings are as follows: (1) Passenger flow characteristics are the primary contributing factors to commercial format diversity and serve as a key mediator through which most other factors influence diversity. Location characteristics, particularly the distance to the rail transit station, primarily play a moderating role to commercial format richness. Urban form characteristics function as the “spatial framework” providing a fundamental regulatory influence, with significant interaction effects with station distance. (2) In urban core areas, the temporal rhythm of passenger flow dominates: weekday passenger flow is positively associated with commercial format richness, whereas weekend passenger flow shows a more complex pattern—associated with an increase in format count but declines in both diversity and dominance concentration, indicating a structural reorganization rather than a simple directional effect. In suburban areas, an initial increase followed by a decrease is observed, with an “optimal synergistic zone” existing approximately 600–1000 m from stations where rail transit and other public service facilities jointly promote commercial format diversity. (3) Land rent is mainly associated with the number of format categories rather than their evenness or dominance. These findings reveal systematic differences in the influence paths of commercial format diversity between urban core and suburban rail transit station areas, as well as the distance-dependent zonal variation patterns of these effects, providing empirical evidence for differentiated spatial design in the context of station-city integration.
Constructed wetlands (CWs) are increasingly used for decentralized wastewater treatment and reuse where conventional infrastructure is difficult to sustain. This review integrates evidence on hydraulic reliability, biogeochemical performance, reuse safety, sustainability trade-offs, and process-based modeling, and derives design implications for Neotropical settings. Organic-matter and suspended-solids removal is generally more robust than nitrogen, phosphorus, and pathogen control. More reliable performance is associated with controlled hydraulic loading, solids-limiting pretreatment, stable flow distribution and water levels, and protection against stormwater-driven short-circuiting and clogging. Reuse should therefore be evaluated against fit-for-purpose microbial, nutrient, salinity, and chemical endpoints rather than removal efficiency alone. We propose seasonal monitoring, tracer or residence-time-distribution assessment where decisions depend on hydraulic efficiency, locally calibrated design envelopes, and a minimum reporting set covering climate/season, flow and loading, HRT/HLR, configuration, pretreatment, media, monitoring duration, influent/effluent concentrations, and hydraulic indicators. This study is a structured narrative review with thematic synthesis; literature identification and corpus reporting were informed by applicable PRISMA 2020 principles. Three Scopus searches yielded 593 records; after removal of 37 duplicates, 556 unique records remained. The final thematic corpus comprises 80 reports, of which 30 are present in the Scopus exports and 50 were identified through complementary routes.
In recent years, the concept of “connectivity” between financial and sustainability reporting has emerged as a central construct in both regulatory frameworks and academic discourse, being recognised as a qualifying attribute of high quality corporate reporting by major standard setters, including the IIRC, the EFRAG and the IFRS/ISSB. Despite its growing normative prominence, the concept remains theoretically fragmented, empirically underexplored and methodologically contested—with interpretations varying significantly across regulatory frameworks, theoretical traditions and empirical research designs. A preliminary critical narrative review was conducted, combining structured searches of major academic databases (WOS, Scopus, Google Scholar)—which identified a total corpus of 115 publications—with a purposive examination of key regulatory documents produced by the IIRC, the EFRAG and the IFRS/ISSB. This review was structured around three research questions addressing, respectively, the conceptualisation of connectivity across theoretical and regulatory frameworks, its principal typologies and theoretical foundations, and the approaches developed for its empirical measurement. The analysis reveals that connectivity is an intrinsically multidimensional concept—aptly described as a “portemanteau” term—whose meanings, typologies and measurement approaches remain fragmented and only partially convergent. Five families of typologies are identified (direct/indirect; specific/general; technical–accounting/informational–managerial; investor-focused/stakeholder-oriented; textual/intertextual/relational), operating at different analytical levels and not mutually exclusive. Regulatory frameworks conceptualise connectivity as an attribute of holistic, coherent corporate reporting but diverge significantly in their underlying conception of materiality—single financial materiality in the IFRS/ISSB framework versus double materiality in the ESRS—with direct implications for the scope and direction of connectivity. Empirical measurement remains a genuine “work in progress”: disclosure indices, textual measures and hybrid indicators each capture different facets of the construct and do not yet converge towards a shared and widely validated framework. The available evidence—while broadly consistent in reporting low to medium-low levels of connectivity, with qualitative linkages predominating over quantitative ones—should be interpreted as associative rather than causal, given unresolved endogeneity concerns. This paper provides the first structured critical mapping of all principal dimensions of connectivity in corporate reporting, at a stage when the literature is still in formation. It identifies the distinction between formal and substantive connectivity as a central open question and outlines a specific future research agenda addressing construct validity, causal identification, longitudinal analysis and the role of assurance.
Post-disaster reconstruction of educational facilities is frequently driven by heuristic decision-making that prioritises speed over long-term sustainability, resilience or climate compatibility. To address this gap, this study proposes a BIM-LCA decision-support framework for the evaluation and prioritisation of school retrofit strategies in post-disaster contexts. The framework integrates a BIM-derived building energy model with life cycle assessment based on EN 15978-compliant material take-offs and explicitly accounts for future climate projections. A two-storey school building in Damascus, Syria, classified under the Köppen-Geiger hot semi-arid climate zone, serves as the case study. Three retrofit scenarios are systematically evaluated against the status quo, namely shallow retrofit (external painting and shading), advanced retrofit (compliant with Passivhaus EnerPHit hot-climate standards) and deep retrofit (EnerPHit with photovoltaic integration). Simulations conducted in DesignBuilder v7 (DesignBuilder Software Ltd., Stroud, UK) assess three performance dimensions including operational and embodied energy, operational and embodied carbon footprint, and financial metrics including Net Present Value (NPV) and Marginal Abatement Cost (MAC). Future climate conditions for horizons 2030, 2050, and 2080 are generated using Meteonorm v8 (Meteotest AG, Bern, Switzerland) software under Representative Concentration Pathways RCP 2.6, RCP 4.5, and RCP 8.5. Results under the deep retrofit, on-site photovoltaic generation delivers net-positive energy performance, with an annual surplus of 27.15 MWh and net-negative operational carbon of −14,428 kgCO2e. The advanced retrofit realises a 32% decline in operational energy consumption at a MAC of £0.89/kgCO2e, rendering it the most favourable financial strategy under stable inflation-adjusted energy prices. Sensitivity analysis shows this ranking inverts towards the deep retrofit under sustained energy-price growth, and towards the shallow retrofit under a high cost of capital. Under RCP8.5 by 2080, cooling demand rises by up to 82% in the advanced and deep retrofits relative to their respective present-day values. The shallow retrofit records the lowest cooling demand among the retrofit options but remains approximately 9% above the contemporaneous status quo. These findings underscore the necessity of climate-adaptive, scenario-aware decision frameworks for post-disaster reconstruction, moving beyond static energy optimisation toward long-term resilience planning.
This study examines how environmental, social and governance (ESG) pressures are translated into verifiable governance practices in European banking and asks why this translation remains uneven in the Western Balkans. Drawing on institutional theory, Europeanisation and the evolving architecture of the Corporate Sustainability Reporting Directive (CSRD), European Sustainability Reporting Standards (ESRS), prudential ESG risk governance and sustainability assurance, the article distinguishes between ESG pressure and ESG measure. The empirical analysis uses an original, manually coded dataset of 55 banks across eleven European countries. A governance-oriented maturity framework captures the progression from CSR-dominant disclosure to formal reporting standards, board-level integration and external assurance. Descriptive statistics and group comparison tests reveal a pronounced institutional divide: EU-core and Croatian banks occupy the highest maturity category, while banks in selected Western Balkan systems remain concentrated around partial integration and lack local assurance. A robustness comparison using ESG_core, which excludes reporting standards and assurance, confirms that the regional divide persists beyond those mechanically related components. A double-coded subsample of 17 banks further demonstrates substantial-to-perfect inter-coder reliability across the principal coded dimensions. The article then develops a complementary policy architecture for a permissioned, blockchain-enabled ESG data platform based on standardized application programming interfaces, off-chain data storage, on-chain hashes and shared attestations. The proposed design links triple-entry accounting principles with regulatory supervision and independent assurance while explicitly addressing data protection, interoperability and the oracle problem. The article contributes by integrating comparative evidence on ESG governance maturity with a technologically realistic pathway for reducing data and assurance gaps in transition economies.
Critical raw material (CRM) lists are published almost exclusively by import-dependent economies, most notably the European Union (EU) and the United States, while many of the countries holding the world’s largest mineral reserves lack official CRM frameworks of their own. This asymmetry shapes global supply chain governance from the perspective of consuming economies rather than producing ones, with direct consequences for the sustainability and equity of the raw material flows underpinning the energy transition. This paper develops a semi-quantitative screening application, informed by EU criticality concepts—the most comprehensive publicly documented framework—applied to Chile, Brazil, and Peru, using 2025 production and reserve data from the USGS Mineral Commodity Summaries 2026 and building on a previously published national-scale application of the methodology to Turkey. For each country, the materials expected to lose critical status owing to leading global positions in reserves and/or production are identified, and the expected change is justified material by material. Results identify Chile as a high-confidence de-listing candidate for copper and lithium; Brazil as a de-listing candidate for several materials (most robustly niobium) and a reduced-criticality candidate for others; and Peru as a de-listing candidate for copper and arsenic. The confidence attached to each case is reported explicitly. Criticality is thus shown to be both perspective-dependent and time-dependent, as evidenced by ranking shifts between the 2023 and 2025 data. The findings support the development of national CRM frameworks that integrate environmental criticality indicators and circular economy strategies, aligning raw material governance with the UN Sustainable Development Goals.
Climate change poses increasing risks not only to natural ecosystems but also to cultural heritage sites and the communities that depend on them. Climate literacy, encompassing knowledge, awareness, and decision-making capacity, is essential for strengthening local resilience and supporting effective climate adaptation. This study investigates climate literacy and perceptions of climate change across historic settlements with different conservation statuses and socio-cultural characteristics. Amasra, Mudurnu, and Taraklı were selected as case studies because of their distinctive historic urban identities and heritage values. A quantitative research design was adopted, and face-to-face surveys were conducted with 300 participants between 15 May and 15 June 2026 using a structured questionnaire consisting of a climate literacy scale and questions on climate change perceptions. The data were analyzed using descriptive statistics, one-way analysis of variance (ANOVA), and K-Means cluster analysis. The analysis revealed meaningful differences in climate literacy across the three historic settlements, while the cluster analysis further showed that participants could be grouped into low, moderate, and high levels of climate awareness. These patterns suggest that climate literacy is not shaped solely by individual knowledge, but is also closely related to the geographical, conservation, and socio-cultural contexts in which people live. The findings therefore point to the importance of place-based climate education and heritage-sensitive approaches to climate adaptation in historic settlements.
The rapid growth in artificial intelligence (AI) demand has significantly increased the electricity consumption and carbon emissions of computing centers. How to schedule AI requests across computing centers to reduce carbon emissions and electricity costs while maintaining low latency is an essential research problem. Existing schedulers reduce emissions by shifting workloads or balancing resources but usually simplify power system modeling, ignore transmission-side costs and carbon emissions, or make local decisions without batch-level coordination. To better address these problems, we first develop an ILP-based scheduler to get optimized results, but it faces scalability limitations. Then, we propose RAPID, a region-aware and power-informed scheduling framework that integrates static and online heuristic schedulers for large-scale AI request scheduling. Experiments based on real-world GenAI traces and Chinese regional power profiles show that RAPID significantly reduces carbon emissions, electricity costs, and total energy consumption compared to methods from previous works while maintaining zero Service Level Agreement (SLA) violations.
Sustainability transitions depend on public willingness to carry the costs they impose, yet recognition of climate risk does not necessarily extend to support for measures that place those costs directly on households. This exploratory cross-sectional study examines that distinction among urban respondents in Adana, Mersin, and Osmaniye in Türkiye’s Mediterranean Region. The analytic dataset comprised 214 adult urban respondents. Because no sampling frame or respondent-level inclusion probabilities are available, the achieved sample is treated as an unweighted non-probability sample and no claim of population representativeness is made. Principal-axis exploratory factor analysis with oblimin rotation and parallel analysis identified three dimensions: personal climate–environmental risk, support for cost-bearing environmental action, and an exploratory environmental concern. An in-sample three-factor confirmatory sensitivity model showed acceptable fit (comparative fit index (CFI) = 0.970, Tucker–Lewis index (TLI) = 0.958, root-mean-square error of approximation (RMSEA) = 0.057, standardized root-mean-square residual (SRMR) = 0.057). Personal risk (mean (M) = 8.70) and environmental concern (M = 8.62) were much higher than cost-bearing support (M = 4.27). The within-person risk–cost support gap was 4.43 points (95% confidence interval (CI) 3.99–4.87; d_z = 1.36). Risk and concern were not significantly correlated with cost-bearing support, and their addition to a heteroskedasticity-robust (HC3) adjusted model increased explained variance by only 1.2% (p = 0.210). Provincial differences were substantial: Mersin had the widest gap, whereas Osmaniye had the highest cost-bearing support. The results do not estimate public opinion for the provinces; rather, they show that climate-policy legitimacy cannot be inferred from high risk perception alone. Policy-specific research should test fairness, effectiveness, trust, revenue use, and distributive safeguards in representative samples. For sustainability governance the implication is direct: the social pillar of sustainability—perceived fairness, affordability, and distributive protection—has to be designed into climate and environmental measures rather than assumed to follow from environmental awareness.
