Search Results (78)

Corporate net-zero pledges have proliferated across the Middle East, yet whether capital markets distinguish credible decarbonization strategies from symbolic ones remains unexamined in energy-exporting emerging markets, a gap this study addresses. This omission matters because the six Gulf Cooperation Council (GCC) economies in our sample face acute stranded-asset exposure amid national diversification programmes such as Saudi Arabia’s Vision 2030 and the UAE’s Operation 300bn. We test whether net-zero credibility is associated with firm valuation among 167 listed firms across seven Middle Eastern countries (2020–2025, 1002 firm-year observations), constructing a five-dimension Credibility Index (pathway specificity, capex alignment, verification, policy compliance, and track record) and applying event-study, pooled panel regression, mediation, moderation, and firm/year fixed-effects analysis. The index is internally consistent (Cronbach’s α = 0.92) and its estimated valuation association is invariant to equal, alternative and leave-one-out weighting schemes. Credibility is positively associated with all four valuation multiples (p < 0.001, firm-clustered standard errors); a one-standard-deviation increase corresponds to a 0.133 increase in Tobin’s Q (95% CI [0.116, 0.149]). High-credibility announcements earn cumulative abnormal returns 5.95 percentage points above low-credibility announcements over (−5, +5) trading days (95% CI [4.79, 7.11]), a gap robust to nonparametric tests, placebo dates and strictly pre-announcement credibility scoring. The association survives firm and year fixed effects (within-firm β = 0.119 per SD, p < 0.001). No moderator—foreign ESG fund, domestic institutional or sovereign wealth fund ownership, regulatory stringency, carbon intensity or financial health—reaches significance after correction for multiple testing, so we find no evidence of investor-type or jurisdictional heterogeneity in this sample. To the authors’ knowledge, this is the first Middle East-calibrated, capex-verified credibility index and the first evidence on the pricing of transition authenticity across GCC markets and Egypt, informing regulators, boards, and ESG investors. Full article

This study provides a stakeholder-based assessment of the drivers, barriers, and strategic priorities shaping energy efficiency (EE) adoption across Egypt’s private sector, focusing on the industry, buildings, and transport sectors. Drawing on 17 semi-structured interviews with stakeholders from government, industry, finance, academia, and development organizations, the study identifies the main factors influencing EE implementation. The findings show that sustainability objectives, particularly carbon reduction commitments and compliance with environmental regulations, alongside donor-funded grants and green finance instruments, are the primary drivers of EE uptake. However, progress remains constrained by institutional and financial barriers, including weak enforcement mechanisms, fragmented governance, limited policy coordination, high upfront costs, restricted access to finance, inflexible banking conditions, and the absence of a domestic EE finance market. Technical and awareness-related challenges further hinder implementation. While gender-related barriers were generally perceived as limited, the analysis revealed underlying disparities in women’s leadership and decision-making roles. Financial barriers represented the largest share across all sectors, while institutional barriers ranked second. The absence of enforcement mechanisms was the most significant individual constraint, cited by 13 out of 17 respondents, followed by limited access to finance (10 out of 17) and high upfront costs (9 out of 17). The study highlights the need for stronger regulatory frameworks, clearer institutional mandates, accessible financing mechanisms, and the integration of gender perspectives to accelerate EE adoption and support Egypt’s sustainable energy transition. Full article

Nickel has become a strategic mineral for the energy transition, yet its supply chain is increasingly shaped by a compound risk regime involving resource nationalism, processing concentration, geopolitical compliance rules, carbon-footprint requirements, and commodity-market volatility. This study develops NiChain-LLM-ABM, a large-language-model-empowered agent-based model for simulating nickel supply chain resilience under semantically rich policy shocks. The framework uses a policy semantic parsing module to transform official policy texts into structured shock parameters, a multi-agent strategy generation module to represent adaptive decisions by seven agent classes, a calibrated supply chain network module to simulate material, financial, and information flows, and a four-dimensional resilience assessment module. The model is anchored in observed nickel production, price, trade, and technology data from USGS, IEA, UN Comtrade, LME, and official legal sources, and its scenario outputs are generated through 100 Monte Carlo replications over 2025–2035. Results show that the baseline Comprehensive Resilience Index (CRI) declines from 0.620 in 2025 to 0.547 in 2035. Indonesian policy tightening causes the sharpest near-term deterioration, with CRI falling to 0.445 in 2028 and the simulated supply deficit reaching 24.5 kt Ni equivalent. A geopolitical compliance shock produces the lowest terminal resilience (CRI = 0.472 in 2035). A green-compliance scenario is disruptive in the short run but exceeds the baseline by 2035, while a coordinated policy portfolio raises the terminal CRI to 0.744, a 36.0% improvement over the baseline. Compared with a conventional rule-based ABM, the LLM-ABM reduces extreme-event backcasting error by 57%, improves policy-response fidelity by 53%, and more than doubles agent heterogeneity differentiation. The results support portfolio-based critical-mineral governance combining strategic reserves, overseas equity investment, recycling, technology substitution, and international cooperation. Full article

As a key market-based instrument for low-carbon transition, China’s national carbon emission trading market facilitates emission abatement and reshapes labor allocation in regulated firms. Based on the task-based framework, a task embedding hypothesis is proposed. Restricted by organizational adjustment costs, firms tend to integrate green compliance tasks into existing roles instead of massively establishing specialized green positions. Using 13 million job postings and matched financial data of Chinese A-share listed firms from 2016 to 2024, this study regards the launch of the national carbon market as a quasi-natural experiment and adopts a difference-in-differences (DID) approach. The results indicate that the carbon market raises the green job share of regulated enterprises by 4.7 percentage points. Such growth is not driven by newly built environmental departments. Management compliance posts decrease markedly, technical posts remain stable, while task-embedding positions combining traditional and green tasks dominate the growth effect. Heterogeneously, private enterprises and eastern China dominate the transformation, while state-owned enterprises lag behind and central and western regions witness a green job share decline. This study enriches task-based theory application in environmental regulation and provides empirical implications for sustainable green talent development and just transition policy design. Full article

Lithium carbonate is a cornerstone therapy for bipolar disorder, typically administered long-term, which necessitates strict control of elemental impurities beyond the quantification of the active ingredient. While previous studies focused on lithium concentration and dosing accuracy, this study characterized the unique inorganic signatures and evaluated the toxicological implications of reference, similar, and generic lithium carbonate formulations marketed in Brazil. Seven commercial brands were analyzed by inductively coupled plasma optical emission spectrometry (ICP OES). Elemental concentrations (mg/kg) ranged as follows: As (0.50–0.62), Pb (0.39–0.57), Se (0.80–1.01), Cr (detected in one similar formulation at 0.18), Fe (<LOD–0.86), Mg (8.10–14.65), K (1.18–4.2), Mn (0.072–0.40), and P (24.3–74.4), while Cd, Cu, and Zn were below detection limits. Statistical analysis (p < 0.05) demonstrated significant inter-manufacturer differences, indicating that pharmaceutical equivalence does not imply inorganic identity. Despite this variability, all formulations complied with ICH Q3D (R2), USP <232>, and Brazilian Pharmacopoeia limits. Under maintenance doses of 600–1200 mg/day, daily exposure remained well below Permitted Daily Exposure thresholds; the cumulative Hazard Index was <0.02, and Incremental Lifetime Cancer Risk (5.46 to 6.80 × 10⁻⁶) was within safe levels. These findings confirm that while distinct elemental signatures exist, the medications are toxicologically safe for chronic therapy. Full article

The inclusion of the cement industry into China’s national carbon emissions trading system in 2025 has fundamentally altered the compliance environment for high-emission enterprises, transforming carbon allowances from passive regulatory instruments into dynamic assets whose management directly affects financial performance. We develop a multi-scenario carbon asset management decision model tailored to the intensity-based benchmarking mechanism adopted by the national market. The model centres on the quota surplus-deficit variable EA4, which is computed from enterprise-level emission intensity relative to the industry benchmark, and decomposes the management problem into sequential selling and buying subproblems linked by coupled decision boundaries. A systematic parameter framework is constructed, and the model is applied to two cement enterprises—Enterprise A, a leading producer with a clear allowance surplus, and Enterprise B, a mid-tier producer operating near the benchmark boundary—through historical backtesting over the 2024–2025 period. Three principal findings emerge. First, the intensity benchmarking mechanism creates a dual-leverage effect whereby a 1.4% improvement in emission intensity (from 0.8112 to 0.8000 t/t) increases the quota surplus by 27%, a nonlinearity not captured by conventional compliance-cost models. Second, the model-driven strategy outperforms traditional experience-based approaches by 36.8% (baseline scenario, +95.20 vs. +69.58 MRMB) and 37.3% (risk scenario, −44.55 vs. −71.08 MRMB), with the improvement rate remaining consistent across both enterprises, suggesting that trading timing outweighs instrument selection in determining compliance cost outcomes. Third, dynamic CEA–CCER allocation captures an incremental 2.33 MRMB through the exploitation of a transient price inversion, a gain invisible to single-instrument strategies. Sensitivity analysis confirms that the relative advantage is robust to carbon price variations (±30%) and CCER offset caps (2–10%), while emission intensity and carry-over allowances represent the most consequential parameters for strategy direction, with EA4 crossing zero near the industry benchmark (I ≈ 0.85). The framework provides actionable decision support for cement and other high-emission enterprises navigating the unified carbon market, and contributes a quantitative methodology to the emerging field of environmental management accounting. This study contributes to Sustainable Development Goal 13 (Climate Action), Goal 7 (Affordable and Clean Energy), and Goal 9 (Industry, Innovation, and Infrastructure) by providing operational tools for decarbonisation in carbon-intensive industries. Full article

The global regulatory landscape is shifting from voluntary corporate social responsibility (CSR) reporting to mandatory Environmental, Social, and Governance (ESG) disclosure, yet whether this transition drives substantive corporate environmental change or merely symbolic compliance remains empirically contested. This study investigates the causal impact of mandatory ESG disclosure on firm value and operational carbon intensity, drawing on an unbalanced panel of 9682 firm-year observations for 1626 listed firms from the European Union (EU-27) and Japan covering the period 2018 to 2024. The EU serves as the treatment group, where mandatory disclosure requirements escalated substantially from 2021 onward through the Sustainable Finance Disclosure Regulation and the Corporate Sustainability Reporting Directive proposal. Japan serves as the control group, representing a developed economy with sophisticated capital markets and high ESG awareness that maintained a voluntary disclosure environment throughout the study period. A Difference-in-Differences framework with firm- and year-fixed effects is employed, and causal identification is validated through a dynamic event study analysis. Three principal findings emerge. First, mandatory ESG disclosure is not associated with a statistically significant improvement in firm value in the EU–Japan comparative context, a result that is interpreted as descriptive rather than causal given evidence of pre-existing valuation divergence between the two groups. Second, mandatory disclosure is associated with a significant and progressive reduction in Scope 1 and 2 carbon intensity, indicating substantive operational decarbonization rather than symbolic compliance. Third, this emissions-reducing effect is significantly amplified among firms with dedicated CSR sustainability committees, while the board independence policy indicator yields no significant moderating effect, a finding attributed to data limitations. These results carry direct implications for policymakers designing climate-related disclosure frameworks and for scholars examining the boundary conditions under which mandatory transparency translates into genuine environmental performance. Full article

Reliable prediction of carbon allowance prices plays a crucial role in emissions trading systems, particularly for market participation, regulatory compliance, and long-term cost planning. In China, regional carbon markets differ markedly in trading activity, price formation mechanisms, and responsiveness to external signals, which limits the effectiveness of conventional single-model forecasting approaches. This study develops a unified machine learning framework designed to accommodate such cross-market heterogeneity. The framework incorporates a diverse set of explanatory variables, including historical price-based indicators, trading volume information, inter-market linkage signals, and macroeconomic factors. Three ensemble-based learning algorithms-XGBoost, LightGBM, and Random Forest—are implemented, and their outputs are further integrated using a weighted aggregation scheme to improve generalization across markets. The empirical evaluation across seven pilot markets shows that, while LightGBM consistently performs well as a standalone model, the proposed ensemble framework achieves superior stability and adaptability under varying market conditions. The forecasting accuracy is high across all cases, with coefficients of determination above 0.74 and reaching values greater than 0.92 in most markets. Further investigation through feature ablation highlights the heterogeneous role of external information, indicating that predictor importance varies significantly between markets and that no universal feature combination yields optimal performance. Leveraging the forecast outputs, the study also demonstrates practical applications in decision support, including timing strategies for allowance sales and dynamic cost assessment in offshore wind engineering scenarios. By systematically evaluating the marginal contribution of different information groups to predictive uncertainty, the framework offers a flexible tool for managing information-structure uncertainty in fragmented carbon markets. The proposed framework offers an integrated solution that connects predictive modeling with operational and engineering decision on processes, providing a flexible tool for managing uncertainty in fragmented carbon markets. Full article

In green credit markets, information asymmetry and corporate greenwashing increasingly undermine the efficiency of resource allocation, while traditional assessment models relying on static, self-reported environmental data fail to impose effective constraints. To address this limitation, this paper develops a dynamic corporate carbon credit evaluation framework by integrating multiple sources of physical (hard) signals and embeds it into commercial banks’ credit management systems. Anchored in multi-source power-carbon signals (e.g., carbon intensity and compliance records), the framework integrates verifiable physical metrics with ESG disclosures via a Bayesian AHP–CRITIC weighting scheme to construct a dual-dimensional classification scheme (“Credit Rating–Green Label”). It further embeds carbon credit scores into dynamic adjustments to credit limits and differentiated interest rate pricing, forming an integrated risk management mechanism. Empirically, a stratified validation strategy is adopted. Analysis based on a sample of 3327 firms shows that the proposed framework achieves a classification consistency of 81.3%, significantly outperforming both a financial-only baseline model (46.8%) and models based on voluntary carbon disclosure (61.4%). Ablation studies further confirm that physical (hard) signal indicators contribute substantially to ranking stability. Moreover, panel regression analysis, based on 36,185 firm-year observations from 3327 firms over the period 2000–2023, demonstrates that carbon credit scores have robust predictive power for future financial distress. Overall, the proposed framework offers a sustainable, data-driven approach to green credit risk management. Full article

With decarbonization, decentralization, and digitalization, energy coordination increasingly involves many actors, heterogeneous cyber–physical data, and compliance-sensitive settlement workflows. Although blockchain has been widely discussed in this domain, existing studies are still fragmented across application-specific or platform-specific narratives. As a result, it remains difficult to compare recurring mechanisms across scenarios or to determine which blockchain functions are operationally justified in deployable energy systems. We address that fragmentation through a structured narrative review of 41 representative sources, including prior surveys, foundational technical references, and scenario-specific studies. We formulate three research questions concerning architectural positioning, cross-scenario mechanisms, and deployment barriers. On this basis, we synthesize a unified five-layer reference architecture that links off-chain physical infrastructure and trusted data acquisition to protocol-level trust anchoring, reusable business services, interface and compliance functions, and application scenarios. The framework is then used to compare five recurring scenario families, namely peer-to-peer energy trading, carbon markets and renewable energy certificates, electric vehicle charging and vehicle-to-grid services, virtual power plants, and grid flexibility coordination. The analysis shows that blockchain is most defensibly positioned as an evidence-and-settlement trust layer, rather than as a replacement for real-time physical control. It also identifies three persistent adoption bottlenecks, namely scalable ledger interaction, trustworthy cyber–physical data binding, and interoperability with regulatory and operational infrastructures. By making the trust boundary explicit and by providing a common analytical lens for cross-scenario comparison, this review clarifies the scientific contribution of blockchain to energy systems and outlines stakeholder-oriented directions for deployable hybrid designs. Full article

This study analyzes the econometric correlation between resale prices and CO₂ emissions of 832 bulk carriers sold from 2018 to 2025. It uses a cross-sectional hedonic pricing model to look at how environmental performance affects the value of sub-types of dry bulk vessels (Capesize, Panamax, Supramax, and Handysize) and age groups (0–5, 6–10, 11–15, and 16+). The findings show that emission efficiency has a statistically significant and negative effect on second-hand prices for all models. Results indicate that higher emission intensity (higher technical efficiency values) reduces vessel values. The magnitude of this effect varies by ship type and age group. Based on the Technical Efficiency Indicator (TEI), refers to Energy Efficiency Existing Ship Index (EEXI) or Energy Efficiency Design Index (EEDI) coefficients, the Supramax segment appears to be the most price-sensitive, followed by Panamax, Capesize, and Handysize. Age has a consistently negative and significant effect on prices, while vessel size positively affects asset values. Further analysis shows that TEI levels increase with vessel age, whereas they decrease with larger vessel size and more recent measurement years. These results are consistent with tightening regulatory pressures under the International Maritime Organization (IMO) frameworks. The economic implications of IMO’s environmental regulations on carbon intensity indicate that compliance with regulation standards creates a measurable price differential in the second-hand ship market. These findings have important implications for shipowners’ investment strategies, regulatory policy design, and the decarbonization path of the maritime sector. This study contributes to the growing research on environmental economics in maritime transport by providing empirical evidence on how carbon regulations translate into tangible asset value impacts. Full article

Against the background of deepening “dual carbon” goals and the continuously tightening policies of the national carbon market, the carbon asset risks faced by thermal power enterprises have shifted from short-term compliance cost fluctuations to medium- and long-term systemic risks. Managing these risks effectively is essential for ensuring the financial viability of thermal power operations during the low-carbon transition, thereby supporting the long-term sustainability of the energy sector. This study constructs a risk management framework for carbon assets in thermal power enterprises based on the LSTM model and option portfolios. First, the multi-dimensional characteristics of medium- and long-term carbon asset risks are systematically identified at the policy, market, and enterprise levels. Second, a dual-layer LSTM model with Dropout regularization is employed to simulate medium- and long-term carbon prices. The prediction results indicate a moderate upward trend in future carbon prices, with the fluctuation range gradually narrowing. On this basis, a combined hedging strategy of “core call options + auxiliary put options” is designed, capping the maximum procurement cost at 72.63 CNY/ton and covering over 90% of the risk of carbon price increases. Monte Carlo simulations and rolling window backtesting, conducted using operational data from a thermal power enterprise to validate the framework, verify the effectiveness and robustness of the strategy. The study shows that, through the integration of accurate LSTM predictions and proactive option hedging, thermal power enterprises can transform their carbon asset management from passive compliance to active value creation, thereby enhancing their operational sustainability and resilience during the energy transition. Full article

The European Union’s Carbon Border Adjustment Mechanism (CBAM), the world’s first system to impose tariffs on the carbon emissions of imported products, commenced its transition period in October 2023 and is scheduled for full implementation in January 2026. This mechanism exerts a profound impact on the global trade landscape and corporate environmental management practices. Taking the CSI All Share Index constituent companies as a research sample, this paper empirically evaluates the impact of the CBAM transition period on the environmental scores of Chinese export enterprises utilizing the Propensity Score Matching Difference-in-Differences (PSM-DID) method. The results indicate that the CBAM transition period significantly inhibits the short-term environmental performance of regulated enterprises. Mechanism analysis reveals that increased financing constraints serve as a core mediating channel, wherein escalated compliance costs and compressed cash flows crowd out resources for low-carbon investments. Furthermore, heterogeneity analysis demonstrates that the negative impact is more pronounced among state-owned enterprises, firms with lower audit quality, and firms with a higher proportion of female executives. Accordingly, the study recommends establishing targeted green transition financing mechanisms, accelerating domestic carbon market reforms, and strengthening international technical harmonization to build corporate resilience against global climate governance shocks and promote sustainable growth. Full article

The accelerated growth of e-commerce has intensified the dual challenges of weak infrastructure and carbon emission pressures in last-mile delivery for rural and mountainous regions. As the World Bank calls for integrating carbon market development into national strategies, Truck-Drone Collaborative Delivery (TDCD) has emerged as a critical sustainable solution. However, existing research often overlooks the strict airspace regulations in sensitive border areas. Therefore, this paper proposes a Vehicle Routing Problem with Drones and Mobile Base Stations (VRPDBS) model that explicitly incorporates airspace constraints and mobile hub deployment. We introduce a quantified “Regional Flyability Factor” ($f_k$) to measure the impact of airspace restrictions on routing decisions and solve the problem using a hybrid metaheuristic algorithm. A case study based on real-world data from the Yanbian Korean Autonomous Prefecture reveals that strict airspace compliance imposes an absolute delivery delay of 4–5 h and an operational cost premium of up to 15%, an impact that can be effectively mitigated through a mobile base station mediation strategy. More importantly, multi-scenario sensitivity analysis under carbon price uncertainty indicates that although truck-dominant modes are cost-effective at current low carbon prices, drone-intensive configurations demonstrate superior economic robustness and environmental performance under high carbon price scenarios. This study not only provides a technical framework for green logistics planning in complex airspace but also offers strategic decision support for logistics enterprises to navigate long-term climate policy risks. Full article

A central goal of carbon (C) management and a critical outcome of sustainable land stewardship is reducing greenhouse gas (GHG) emissions from agriculture, forestry, and other land uses. Integrating GHG considerations into management can take many forms, but C credit markets are increasingly providing sources of private capital to offset the often high costs of stewardship. In Hawaiʻi, participation in voluntary C credit markets and the establishment of jurisdictional compliance C markets are constrained by a lack of institutional capacity, successful demonstrations, and high-quality data, making private capital for C market-based approaches in Hawaiʻi difficult to access. The State of Carbon in Hawaiʻi Hui (hui translates to partnership in ʻŌlelo Hawaiʻi, the Hawaiian language) convened landowners, researchers, federal and state government professionals, and for-profit and not-for-profit organization staff to better understand limitations to implementing C management in Hawaiʻi. This paper describes why the State of Carbon in Hawaiʻi Hui was formed, how we planned for, hosted, and assessed the success of a C-focused summit, and what outcomes resulted from this process. A Pathway Forward document, a decision support tool, and this article are outcomes. These products will serve as resources for those considering Hawaiʻi-based forest C projects, as well as contributing towards the legislated goal of reducing greenhouse gas emissions in Hawaiʻi. Our knowledge exchange process is readily replicable and can support a variety of efforts in environmental conservation and beyond. Full article