Environmental taxes are used as policy measures to address pollution and encourage sustainable development. However, there are also concerns about their potential side effects. This study investigates the relationship between environmental taxes and energy poverty in 47 developing countries from 2002 to 2020 using panel estimation methods, including the two-step system generalized method of moments and three-stage least squares. The findings demonstrate that environmental taxes are associated with higher energy poverty as household access to clean fuels and technologies for cooking is decreased, particularly in rural areas facing greater infrastructure and affordability constraints. The negative relationship is more pronounced for resource and pollution taxes. Interestingly, better institutional quality can reduce the adverse effects of environmental taxes on energy poverty. Environmental taxes may increase inflation, but renewable energy production may alleviate energy poverty. This paper sheds light on the trade-off between green fiscal instruments and social objectives especially in developing countries.
This paper constructs a theoretical model and examines the effects of meteorological disasters on the efficiency of energy supply chains. The findings reveal that: (1) Meteorological disasters increase the inventory of WIP in the energy sector, thereby reducing the efficiency of energy supply chains, with a noted spillover effect of these disasters on supply chain efficiency. (2) Meteorological disasters significantly extend the lead time for procurement and increase the uncertainty of lead times, which in turn raises the inventory of WIP and reduces the efficiency of energy supply chains. (3) In heterogeneity tests, flooding, severe convective storms, and typhoons significantly decrease the efficiency of energy supply chains in the affected provinces. The impact of meteorological disasters on energy supply is more significant in the energy extraction, energy processing, and conversion industries. Based on these findings, the paper puts forward some policy recommendations accordingly.
Emerging economies are confronted with the challenge of balancing rising economic complexity with environmental efficiency while restraining anthropogenic emissions. To support the resolution of this challenge, this study explores whether economic complexity limits environmental intensity via the channel of biological capacity between 1995 and 2021 in Emerging 7 (E7) countries, including Brazil, China, India, Indonesia, Mexico, Russia, and T & uuml;rkiye. These findings support the legitimacy of the EKC hypothesis, confirming an inverted U-shaped relationship between economic growth and environmental intensity. Notably, economic growth escalates environmental intensity in the early growth stages, while in later stages, it gives rise to mitigating environmental intensity in favor of stronger environmental efficiency. Furthermore, economic complexity, financial development, and trade openness have contributed to rising energy and carbon intensity, thereby compromising environmental efficiency. Conversely, globalization and biological capacity improved environmental efficiency by limiting energy and carbon intensity. Regarding moderation effects, biological capacity turns the adverse impact of economic complexity on environmental intensity into a beneficial one. In line with these findings, E7 countries are advised to align rising economic complexity with biological capacity restoration strategies through large-scale forest restoration, sustainable use of land resources, and soil rehabilitation initiatives.
Digital finance has emerged as a key driver of China's green transition, yet existing research largely neglects how its effects depend on the development level of traditional finance. Motivated by this gap, this study examines whether and how digital finance improves regional energy efficiency under different financial conditions. Building on theoretical arguments that digital finance directly enhances energy efficiency and indirectly operates through green innovation and green assetization-and that these effects may vary non-linearly with traditional financial development-we articulate a set of corresponding hypotheses and test them using panel data for 282 prefecture-level cities from 2011 to 2023. We measure energy efficiency through the Super-Efficiency Slacks-Based Measure (SE-SBM) and capture digital finance by the Peking University Digital Financial Inclusion Index. Using dual fixed-effects models and a panel threshold framework, we find that digital finance significantly enhances energy efficiency, with stronger effects in cities characterized by higher levels of new urbanization, informatization and market openness. Mechanism analyses indicate that digital finance promotes energy efficiency indirectly through green innovation and the assetization of green resources. Threshold estimations further reveal a dual-threshold pattern in which moderate levels of traditional finance maximize the marginal contribution of digital finance, whereas underdeveloped or excessively developed financial systems weaken it. These findings enrich the understanding of the digital-traditional finance nexus and provide empirical support for coordinating the two financial systems to promote sustainable and energy-efficient development.
This study investigates the wind energy potential of Karabuk Kahyalar village, Turkiye, using comprehensive statistical characterizations and techno-economic evaluations based on measured wind data collected between August 2013 and June 2014. Representing the inaugural academic investigation of wind energy investment feasibility in this rural inland region, the study characterizes the wind regime using the Weibull distribution, with parameters optimized via the Method of Moments (MM), Least Squares Method (LSM), and the Generalized Reduced Gradient Method (GRG). Statistical error metrics indicate that the GRG and MM methods provide superior alignment with the observed frequency data. To mitigate the inherent limitations of the 11-month sampling period and capture regional annual cycles, non-parametric Classical and temporal-dependent Block Bootstrap resampling analyses were conducted, establishing narrow confidence intervals and validating the data against long-term NASA POWER climatological trends (R<^>2 > 0.75). Based on these robust statistical frameworks, five commercial horizontal-axis wind turbines were evaluated across utility and micro-scales. Techno-economic metrics reveal that while the Nordex N100/2500 model delivers the lowest Cost of Energy (0.08195 $/kWh) due to economies of scale, the Proven 15 kW micro-turbine stands out as the most technically viable decentralized option, achieving the highest capacity factor (14.2%). Ultimately, this analysis demonstrates that despite a low regional average wind speed (3.47 m/s), strategically selected small-scale or optimized hybrid renewable configurations can achieve cost-effective electricity generation, offering a repeatable planning framework for rural decarbonization.
This study investigates the effects of energy source diversification on countries' ESG environmental performance scores. To this aim, we use panel data from 36 developed economies covering the period from 2000 to 2018. As a novelty, in contrast with the point estimators based on OLS, we employ the recently introduced robust estimators, i.e., Method of moments quantile regression (MMQR) and instrumental variable quantile regression (IVQREG), to account for the variation in the energy diversification and environmental performance relationship across the different levels of the ESG score. The empirical results from both robust estimators support the positive effects of energy diversification on ESG environmental performance across most quantiles. However, this relationship is less significant for countries with higher environmental scores. The positive effect of diversification is more pronounced in countries with lower environmental performance. As the country reaches higher environmental performance quantiles, the impact of diversification diminishes. The results show that economic growth increases environmental performance across all quantiles. The results also suggest that although government effectiveness is an essential prerequisite for achieving environmental objectives, globalization has a negative effect on environmental quality, especially in lower ESG-score countries, as it leads to higher energy consumption. Hence, policymakers should not rely on fossil fuels but rather focus on energy sources that emit zero or negligible carbon. The transition to renewable energy requires establishing economic expertise and stability to foster the breakthroughs needed.
As major economies, the Group of Seven (G7) countries confront the dual challenges of escalating environmental degradation and the transition towards the low-carbon economy. While scholars have studied the factors influencing carbon emissions (CE), the synergistic effects of various factors on CE in the G7 countries remains unclear. Through cross-sectional augmented autoregressive distributed lag (CS-ARDL) method, we test the driving effects of CE, including renewable energy consumption (REC), green technology innovation (GTI), and financial development (FD). The cointegration among the variables are confirmed. Both REC and GTI are key determinants of CE in the short and long run. These two factors help cut carbon emissions and curb environmental deterioration. By contrast, FD and economic growth (EG) drive up fossil fuel use, thereby increasing carbon emissions. Additionally, a two-way causal relationship is identified between REC and CE. Overall, this research offers empirical support for designing low-carbon development policies in developed economies.
Against the background of China's dual-carbon transition and the strategic rise of new-type energy storage, this study develops a composite indicator framework to evaluate the development of new-type energy storage across Chinese provinces. Based on provincial-level data covering industrial capacity, policy and planning conditions, technological innovation, environmental responsibility, and international influence, the framework integrates entropy-based objective weighting with expert-informed subjective weighting to support transparent and comparable assessment. The results reveal differentiated regional development patterns, characterized by strong performance in eastern provinces. Guangdong, Fujian, Jiangsu, Zhejiang, and Beijing form a leading cluster, while many provinces outside the eastern region remain primarily deployment-oriented and show relatively greater room for improvement in innovation capacity, market conditions, and external engagement. Among the assessed dimensions, technological innovation and external orientation display the most evident spatial differentiation. A sensitivity analysis further confirms that the main ranking pattern remains stable under alternative weighting assumptions. These findings suggest that China's rapid expansion of new-type energy storage capacity is increasingly moving from scale-oriented growth toward quality-oriented upgrading, while differentiated provincial conditions continue to shape regional development pathways. From a planning and policy perspective, the results highlight the importance of improving coordination across regions, strengthening market-related institutional conditions, and addressing environmental management challenges associated with large-scale deployment. The proposed framework offers a practical tool for comparative analysis of energy storage development at the regional level.
This study presents an experimental and economic assessment of a 50-kW downdraft fixed-bed coal gasification system, bridging the gap between laboratory-scale investigations and industrially relevant producer gas applications. Unlike most prior studies focused on modelling or small-scale units, the present work provides experimentally validated performance and economic data for high-ash Indian coal under continuous operation. The gasifier was operated under air-blown conditions to evaluate syngas composition, thermal behaviour, gas yield, and CGE. The system produced a stable combustible producer gas with an average hydrogen concentration of approximately 14.02 +/- 0.76 vol% and an LHV of 4.39 +/- 0.14 MJ/Nm & sup3;. A cold gas efficiency of 61.5 +/- 1.94% was achieved, demonstrating the effective conversion of coal's chemical energy despite the challenges associated with its high ash content. An economic evaluation based on the direct utilization and sale of producer gas was performed to assess long-term feasibility. The system generated an annual revenue of approximately USD 8112, resulting in a net present value (NPV) of about USD 19,889 over a 20-year project life at an 8% discount rate. The payback period was approximately 4 years, and the profitability index exceeded unity, indicating strong economic attractiveness. Sensitivity analysis further revealed that economic performance is more sensitive to syngas selling price than coal cost. Temperature measurements confirmed the establishment of stable gasification zones, and uncertainty analysis indicated that syngas composition and temperature measurements were reliable, with uncertainties within +/- 2% and +/- 2 degrees C, respectively.
Ultra-high-voltage (UHV) transmission, a key new infrastructure project, addresses China's spatial mismatch between energy supply and demand, supporting energy reform and the "dual carbon" goals. This paper leverages the phased rollout of UHV projects as a quasi-natural experiment and employs a staggered difference-in-differences model to analyze prefecture-level carbon emissions (2004-2021). Results show UHV operation significantly reduces adjacent areas' emissions, with sustained and robust policy impacts. The effect is stronger in eastern/western regions and growing/mature cities, where energy allocation efficiency improves. Mechanism analysis reveals energy substitution and economies of scale as key drivers. The findings strengthen the empirical link between cross-regional energy allocation and environmental outcomes, offering policy insights for building a modern energy system and achieving synergistic pollution-carbon reduction.
This paper investigates whether geopolitical risk increases Vietnam's vulnerability in crude oil imports in both the short and the long run. Using monthly data for 2016M7-2023M12, the study employs an ARDL framework in which crude oil import value is explained by the geopolitical risk index, Brent crude oil prices, the VND/USD exchange rate, and a dummy variable capturing the Russia-Ukraine war shock. The empirical results indicate that the variables are integrated of mixed orders, I(0) and I(1), which supports the use of the ARDL framework. Bounds testing confirms the existence of a long-run relationship among the variables. The error-correction term is negative and highly significant, implying a rapid adjustment back to equilibrium after short-run shocks. Among the explanatory variables, the exchange rate emerges as the most robust driver of Vietnam's crude oil import vulnerability, while the Russia-Ukraine war dummy captures an additional adverse geopolitical shock. By contrast, the direct effect of the aggregate geopolitical risk index is weaker. The findings suggest that Vietnam's energy vulnerability is transmitted primarily through exchange-rate pressure and major geopolitical disruptions. Additional robustness checks, including an alternative model using crude oil import quantity, confirm the qualitative stability of the main findings.
This study investigates the impact of corporate social responsibility (CSR) on energy security (ENSEC) for 34 developed countries. It offers a new institutional perspective by linking CSR to ENSEC within the framework of sustainable development. MMQR, PLFC, and DID methods are used for this analysis. The MMQR results indicate that CSR enhances ENSEC across all percentiles (10%-90%) in both aggregate and disaggregated analyses, across the social, environmental, and governance dimensions. Moreover, the PLFC model's findings reveal that CSR promotes ENSEC in aggregate, regardless of income level. However, in the disaggregated estimates from the PLFC model, the social dimension of CSR has no effect on ENSEC, whereas the environmental and governance dimensions continue to have a positive effect on ENSEC. As for the impact of China's energy investment, only China's fossil energy investment ensures ENSEC. These findings provide important policy insights by empirically validating the role of CSR in addressing long-term energy risks.
India's commitment to achieving net-zero emissions by 2070 requires state-level strategies for low-carbon economic transitions. This study develops a state-specific macroeconomic framework linked to an energy system model to assess the investment needs and employment impacts of decarbonization. Focusing on Odisha, an eastern coastal state producing 23% of India's coal and 44% of mineral output, with a high industrial GDP share, we construct a 49-sector computable general equilibrium (CGE) model and soft-link it with a bottom-up MESSAGEix model. Studies utilizing integrated CGE-MESSAGEix models at the subnational or regional level in India remain limited. The integrated approach evaluates the economic and employment impacts of alternative low-carbon pathways, capturing inter-sectoral and national-global linkages. The findings indicate that fossil-fuel taxation with revenue recycling and renewable energy investment, if applied in isolation, may dampen growth. However, combining renewable energy development policies with energy efficiency and productivity gains mitigates adverse effects, supporting a sustainable transition. In the policy scenario, while coal sector jobs decline, overall employment rises, highlighting opportunities for a just transition in resource-dependent states.
Levelized Cost of Energy (LCOE) is widely used to assess the competitiveness of electricity generation technologies and is often applied as a standard socioeconomic metric. However, in financial assessments where taxes affect cash flows, as recently observed in the Brazilian Photovoltaic Distributed Generation (DG-PV) market, LCOE may yield results that differ from those of Net Present Value (NPV). This study evaluates this divergence by comparing financial LCOE and NPV across 26 cities in Minas Gerais state under two scenarios: with and without the tax on the use of the distribution system (TUSD-B Wire). The results show significant quantitative differences in rankings, with substantial position changes among cities when switching from LCOE to NPV, particularly after the inclusion of the tax (e.g., Po & ccedil;os de Caldas shifts from 21 st to 1 st in LCOE ranking). Financial LCOE values increase from approximately 0.044-0.059 US$/kWh (without tax) to 0.066-0.102 US$/kWh (with tax), while NPV decreases but remains positive in all cases, ranging from about US$ 3,138 to US$ 12,021 under the tax scenario. Cities with higher electricity tariffs, such as Manhua & ccedil;u and Cataguases, achieve the highest NPV values (above US$ 11,600), whereas cost factors primarily drive LCOE rankings and may indicate different investment priorities. These findings confirm that financial LCOE may not adequately capture the economic attractiveness of DG-PV projects in tax-inclusive environments, leading to a systematic divergence from NPV-based rankings. The key implication is that relying solely on LCOE can result in suboptimal investment decisions. Therefore, NPV is a more appropriate metric for investors. At the same time, policymakers should consider the limitations of LCOE when designing and evaluating regulatory policies in markets with heterogeneous tariffs, taxes, and incentives.
This study proposes a novel electricity resilience index to capture the temporal stability, recovery capacity, and redundancy of electricity consumption across Taiwan's 22 regions from 2016 to 2024. By integrating the coefficient of variation, post-shock recovery time, and an entropy-based diversity index, we assess the dynamic adaptability of local energy systems amid climate risks and urban transformation. Using the Spatial Durbin Model (SDM), the analysis reveals both direct and spillover effects of socioeconomic, geographic, and environmental factors on electricity resilience. Principal findings highlight the negative impact of rapid aging, island geography, and high disaster frequency, while industrial electricity share and average temperature show positive associations. The results offer spatially grounded insights into the design of adaptive energy strategies and localized resilience policies, especially for island economies facing compound shocks. This study contributes to the growing discourse on urban sustainability by framing electricity resilience not only as an infrastructural attribute but also as a spatial and social construct.
