Search Results (419)

Carbon pricing can change manufacturers’ material choices, while the costs of managing the residual waste remain geographically uneven. We formulate a manufacturer–regulator bilevel model for a household plastic-waste closed-loop supply chain with quantity-dependent recycled-bale prices, activity-specific carbon accounts, physical interregional waste routing, and a proportional regional cost-burden standard. The lower level is explicitly a single coordinating-regulator linear program rather than a game among independent regions. Its primal constraints, dual constraints, and strong-duality equality are embedded in the manufacturer problem; binary-continuous products are exactly linearized using the manufacturer’s SOS1 price-grid variables. Thus, every reported policy point is obtained from the same 12-region mixed-integer equilibrium formulation. Across 36 central policy combinations, HiGHS reports a zero mixed-integer programming gap, and the largest feasibility and optimality residual is $5.24\times {10}^{-8}$. Raising the carbon tax from 0 to 10 USD/tCO₂ increases the real recycling rate (RRR) from 15.33% to the bale-capacity limit of 29.85% and reduces physical emissions by 11.64%. Tightening the allowed regional burden deviation from 25% to 5% reduces the standard deviation of normalized residual-waste cost burden by 77.89% and interregional residual-waste transfers by 77.05%, but does not change the RRR. This zero-recycling effect overturns the earlier assumption-driven result: a pure routing-based cost-balancing rule cannot mechanically stimulate the manufacturer’s recycled-input demand. A global analysis of 300 parameter sets and five independent regional samples re-solves 1800 equilibrium models; all have a zero solver gap and pass the residual audit. Carbon-induced RRR increases have a median of 17.03 percentage points, while strict-versus-loose burden-threshold changes in RRR are zero in every set. The results distinguish carbon efficiency, regional cost incidence, and fiscal incidence and show that policy complementarity must be demonstrated through endogenous decision links rather than imposed response functions. Full article

Energy efficiency (EE) is integral to a sustainable energy system and can play a significant role in climate mitigation by reducing energy consumption and the adverse effects of climate change. This paper examines the association between CO₂ emissions, EE, environmentally related taxes (ERTs), renewable energy (RE), and non-renewable energy consumption (EC) in Australia from 1990 to 2020. Using a dynamic ARDL model, the empirical findings show that adopting EE (β = −0.14, p = 0.000), ERT (β = −0.08, p = 0.071), and RE (β = −0.008, p = 0.007) is associated with lower carbon emissions, particularly in the short run. Conversely, EC impedes climate mitigation, as revealed by the substantial positive and significant coefficient of 1.4%. Notably, EE has the largest short-run coefficient among the mitigating variables, indicating that energy efficiency is the most significant mitigator of carbon emissions in Australia in the short run. The ARDL bounds test confirms the existence of a long-run equilibrium relationship among the variables. However, in the long run, EE, ERT, and RE do not mitigate carbon emissions, given their statistically insignificant coefficients, whereas EC remains strongly positively related to CO₂ emissions. Results from the FMOLS and DOLS estimates largely support the ARDL findings, though some sensitivity is observed for ERT. Consequently, this paper proposes a comprehensive policy direction for governments and international organizations, emphasizing the importance of reducing energy intensity and promoting EE as core climate mitigation instruments to foster a green, sustainable environment. Full article

International oil price volatility poses severe risks to macroeconomic stability and energy security, presenting complex policy challenges for China as it simultaneously pursues economic growth and a low-carbon transition. To bridge the gap between general equilibrium reallocation and transition quality, this study couples an 18-sector recursive dynamic computable general equilibrium (CGE) model with a super-efficiency slacks-based measure (SBM) model to evaluate China’s macroeconomic path and green total factor productivity (GTFP) from 2023 to 2045. We simulate a permanent 200% international oil price shock starting from 2026—conceived as a tail-risk stress test—together with alternative shock scenarios of varying magnitude and persistence (P50, P100, and a five-year temporary variant of P200_5Y), and evaluate four counterfactual policies under the P200 stress-test condition: household transfers (Tran_HG), price regulation (P_REG), structural tax reduction (T_RED), and energy-transition acceleration (Delta_ENE). The shock triggers imported cost-push inflation and a regressive shift toward coal, with the long-run damage governed jointly by shock magnitude and persistence; since GTFP deteriorates monotonically with shock size, the apparent emission reductions under extreme shocks suggest a contraction-driven “efficiency illusion” rather than genuine green improvements. Individually, P_REG and T_RED are effective only as temporary shields, Tran_HG provides the strongest welfare protection but amplifies the high-carbon rebound, and Delta_ENE uniquely improves resilience and green efficiency simultaneously. Building on these results, a combined policy package (COM) is further designed and simulated, which exhibits positive complementarities; it cuts the 2026 GDP loss by about 70%, turns GDP and welfare losses into net gains by 2043 and 2040, respectively, and delivers favorable green-transition outcomes. These findings call for coordinated, phased policy packages in which fiscal space rotates from emergency shields to demand-side repair and, ultimately, to electrification-led structural transformation. Full article

Deep saline aquifers are among the most promising formations for large-scale carbon capture and storage (CCS); however, reservoir pressure buildup, limited CO₂ dissolution, plume migration, and salt precipitation can reduce storage efficiency and injectivity. This study evaluates the technical and economic performance of engineered CO₂ injection strategies, including intermittent CO₂ injection (ICI), water-alternating-CO₂ (WA–CO₂), carbonated water injection (CWI), and carbonated water-alternating-CO₂ (CWA–CO₂), under low- (180 mD) and high-permeability (1000 mD) saline aquifers and injection rates ranging from 0.01 to 0.5 MTPA. Laboratory-derived relative permeability and CO₂ diffusivity data were incorporated into three-dimensional compositional reservoir simulations, while the most promising strategy was validated using the Sleipner benchmark model. Techno-economic performance was assessed through Monte Carlo uncertainty and sensitivity analyses. The results show that injection strategy, rate, and reservoir permeability strongly influence trapping efficiency and pressure evolution. ICI increased dissolution trapping by up to 20%, enhanced residual trapping by approximately 40%, and reduced average reservoir pressure by up to 10%, although its extended operating period reduced its economic attractiveness. Among the evaluated alternatives, WA–CO₂ provided the best balance between technical and economic performance by enhancing dissolution trapping, improving pressure management and plume control, and maintaining storage costs within 3.6–3.7% of the continuous injection base case. Field-scale validation using the Sleipner model demonstrated improved long-term trapping efficiency and reduced mobile CO₂ and plume extent. Monte Carlo analysis (20,000 realizations) confirmed the economic robustness of the evaluated strategies under the assumed policy framework, identifying Section 45Q tax credit and discount rate as the dominant economic drivers. These findings demonstrate that properly designed WA–CO₂ schemes can significantly improve the technical and economic performance of geological CO₂ storage. Full article

Within a coordinated fiscal financial policy framework, this study combines complex network analysis with cellular automata to construct a contagion model of debt risk across industrial enterprises. It then uses numerical simulations to examine the dynamic evolution and mitigation strategies of debt risk contagion. The results show that the following: (1) As the contagion probability, immunity failure probability, and contagion probability of immune enterprises increase, debt risk contagion among industrial enterprises is strengthened, whereas higher immunity probability and recovery probability improve network stability. (2) Market noise, carbon tax rate, credit interest rate, and risk preference increase the basic reproduction number relative to the critical boundary of one, whereas fiscal subsidy intensity, green credit ratio, and risk assessment capability reduce it. Within the normalized simulation framework, a carbon tax rate around 0.3, fiscal subsidy intensity around 0.15, and green credit ratio around 0.5 serve as illustrative model-based reference values for interpreting changes in debt risk contagion pressure and risk-mitigation effects. (3) Coordinated fiscal–financial intervention can more effectively reduce $R_0$ and narrow the contagion scope than a single policy tool, suggesting that debt risk prevention should combine fiscal support, green credit allocation, risk assessment improvement, and carbon-policy rhythm management. Full article

This study analyzes carbon-pricing mechanisms in Taiwan and Republic of Korea—two high-carbon manufacturing economies embedded in global supply chains—to examine how developmental-state institutions shape the design and effectiveness of carbon-pricing policies and whether these mechanisms effectively contribute to emissions reduction. Using a comparative case study design, policy document analysis, and quantitative emission and survey data, this study compares the evolution and outcomes of carbon pricing in both economies. While carbon pricing is recognized as a key climate mitigation tool, its effectiveness varies across institutional settings. Through a comparative analysis, this study shows that developmental-state structures—characterized by strong state–industry linkages, the dominance of carbon-intensive industries, and conservative policy design—constrain its effectiveness. Republic of Korea’s Target Management System and Emissions Trading Scheme have not curbed emissions growth, while Taiwan began debating an energy tax as early as 2006 but only institutionalized carbon pricing after the 2023 Climate Change Response Act. The carbon fee, initially planned for 2024, was postponed to 2026 with a low and lenient price. The findings suggest that carbon pricing is mediated by industrial policy priorities, limiting its capacity to drive low-carbon transitions. Full article

Greenhouse gas emissions from heavy-duty vehicles (HDVs) must be drastically reduced. Battery electric trucks (BETs) are the main option for low-carbon road freight transport, but they require recharging infrastructure. However, a thorough cost analysis of public charging is lacking, especially for the Megawatt Charging System (MCS). This study estimates the infrastructure-related levelised cost of megawatt charging for battery electric trucks in Europe based on simulated truck operations and techno-economic modelling. The analysis combines empirical driving data with cost assumptions for MCS infrastructure. The reported values are infrastructure-only costs and include annualised capital expenditure, installation costs, grid connection costs and operating expenditure. They exclude electricity prices, taxes, levies, land costs and operator margins. Low- and high-cost scenarios differ in assumed charger hardware and installation costs, while grid connection costs and utilisation assumptions are held constant across scenarios. The results show that utilisation is the key driver of cost reductions over time. The infrastructure-related levelised cost of MCS declines to 0.03–0.07 EUR/kWh by 2050 under the analysed cost assumptions. The total annual infrastructure costs for Europe are estimated at 6.6–10.8 billion EUR, or 2.9–4.7 EUR cents/km. The results support policy decisions on infrastructure deployment and highlight the importance of coordinated rollout and demand growth. Full article

Uzbekistan has rapidly expanded solar photovoltaic (PV) capacity as part of its transition toward a low-carbon energy system, supported by guaranteed purchase tariffs and an evolving regulatory framework. This paper evaluates the economic feasibility of solar PV investments in Uzbekistan through a combined ex post and ex ante analysis, focusing on both commercial-scale rooftop installations and a proposed large utility-scale floating photovoltaic (FPV) project. Ex post performance data from four commercial rooftop PV systems in Tashkent (20–304 kW) over the period 2024–2025 are analyzed using lifecycle investment appraisal metrics, including the Equivalent Uniform Annual Cost (EUAC)/LCOE framework, Net Present Value (NPV), and Internal Rate of Return (IRR), to benchmark real operating outcomes against modeled expectations. These results are subsequently used to calibrate ex ante simulations for a 491 MW FPV installation planned on the Sardoba reservoir, assessed using RETScreen Expert and a bespoke three-statement financial model incorporating detailed tax, financing, and operational assumptions. The findings indicate that commercial-scale rooftop PV projects in Tashkent operate close to the financial break-even point, with EUAC-based levelized costs of energy broadly aligned with current guaranteed purchase prices for PV electricity, resulting in near-zero NPVs. In contrast, the large-scale Sardoba FPV project demonstrates moderate but positive financial viability, with nominal IRRs of approximately 14–16% and payback periods under ten years at the prevailing tariff levels. Importantly, the monetized value of environmental externalities—primarily avoided CO₂ emissions—amounts to roughly from one quarter to a third of initial capital expenditure, materially enhancing the project’s overall economic value. The results suggest that while large-scale solar projects in Uzbekistan generate limited private financial rents, their societal benefits justify continued policy support, stopping short of additional direct subsidy disbursements but conducive to lower cost-of-capital measures. Full article

Decarbonising municipal solid waste (MSW) is a defining algorithmic challenge for smart cities: waste-to-energy (WtE), composting and material-recovery investments must be committed years ahead under deep uncertainty about household source-separation uptake and the governing policy instruments (landfill taxes, carbon prices, compost subsidies). We present a two-stage stochastic mixed-integer linear programming (MILP) framework, applied to the Attica region of Greece (Athens; 5122 t/day MSW) and calibrated to confirmed 2024 weighbridge data. The contribution is an integration strategy rather than a new technique: endogenous WtE capacity sizing (Special Ordered Sets of Type 2 (SOS2) piecewise-linear cost, economies-of-scale exponent 0.85), the bilinear capacity–build coupling linearised exactly by McCormick envelopes (one factor being binary), and Pigouvian shadow-price recovery of the optimal policy instruments are combined in a single-shot, gap-bounded MILP and embedded in a 10,000-run Latin-hypercube Monte Carlo layer over 12 parameters with Spearman sensitivity indices. The individual components are established; their joint formulation is, to our knowledge, new. The pipeline solves 10,415 MILP instances. Three results are policy-relevant: investment is robust to rollout uncertainty (VSS ≈ €0; EVPI ≈ €5.4 M, 0.15%); the carbon price alone explains ~80% of cost variance (ρ = +0.891); and, under the model’s calibration, the implied Pigouvian-optimal landfill tax (€1100–3300/t) indicates a binding landfill cap is needed to secure diversion. The framework transfers to any metropolitan MSW system facing decarbonisation and circular-economy mandates. Full article

To address the multi-objective conflicts among cost, time, and carbon emissions in Guangxi cross-border container multimodal transport—under the influence of factors such as tariffs, fluctuating customs clearance efficiency, and carbon emission policies—this paper develops a multi-objective optimization model that integrates mixed time windows and scenario analysis. The model incorporates multiple elements, including transportation cost, transshipment cost, tariff cost, time value of cargo, carbon tax cost, in-transit and customs clearance time, and transshipment-related carbon emissions, making it more aligned with real-world cross-border operational scenarios. To effectively solve this complex model, an improved NSGA-II algorithm (I-NSGA2) is designed, which introduces an adaptive crossover and mutation operator along with an elite retention strategy to enhance convergence speed and solution diversity, while embedding a scenario parameter response mechanism to accommodate dynamic fluctuations in key parameters. Subsequently, an evaluation framework is constructed using the entropy weight–TOPSIS method to select recommended routes with favorable cost–time–carbon trade-offs from the Pareto frontier. A case study based on the Nanning–Kuala Lumpur route is conducted for validation. Experimental results demonstrate that the I-NSGA2 algorithm significantly outperforms MOPSO, MOEAD, and the standard NSGA-II in terms of IGD and HV metrics; time-sensitive cargo tends to favor rail-dominated routes, while low-cost cargo prefers combined road–water–rail routes. This study effectively addresses the route selection problem for Guangxi cross-border container multimodal transport under varying key parameters, and also provides a research foundation for optimizing cross-border multimodal transport route selection in other regions. Full article

This study examines the short-run effect of carbon taxation on the growth rate of GDP per capita, the annual first difference in log GDP per capita, using a panel of 16 carbon-pricing economies spanning Europe, the Americas, Asia and Africa over 2020–2024. Country fixed-effects estimation with country-clustered robust standard errors follows formal model selection (F-test, Hausman test), checked for cross-sectional dependence. Three baseline specifications are estimated, Model 3 excluding the COVID-19 dummy as a robustness check; a fourth adds carbon tax interaction terms with inflation, investment, energy intensity and political stability to test whether these factors condition the relationship. A higher carbon tax rate has a small but statistically significant negative effect on growth across all three baseline models (a USD 10 increase implies roughly a 1.2-percentage-point reduction in annual growth, preferred specification); none of the interaction terms is significant, indicating no detectable conditioning effect. Investment shows a robust positive association with growth; inflation, a robust negative one. Energy intensity and the COVID-19 dummy enter with signs contrary to expectations once year fixed effects are excluded, and the carbon tax coefficient loses significance under a lagged specification, cautioning against a strictly causal reading. Findings support pairing carbon tax design with investment and price-stability policies. Full article

Traditional techno-economic assessments of zero-emission mobility frequently rely on static Total Cost of Ownership (TCO) models that fail to capture the concurrent evolution of economic and environmental parameters. To address this research gap, this study develops a novel dynamic multi-objective optimization framework that jointly assesses TCO and Well-to-Wheel (WTW) emissions across the period 2026–2060, capturing the non-linear trade-offs between cost minimization and lifecycle decarbonization. The model developed compares light-duty hydrogen Fuel Cell Electric Vehicles (FCEVs) with diesel, petrol, and battery-electric vehicles (EVs), incorporating time-varying Capital Expenditure (CAPEX) learning curves, fuel price trajectories, carbon pricing effects, and emissions-decay pathways. Hydrogen break-even prices are computed annually against each competing technology to identify the market conditions under which FCEVs become cost competitive. The results show that light-duty hydrogen FCEVs face a substantial entry barrier in 2026, with a TCO of approximately €275,000, far above diesel, petrol and EV alternatives. However, their relative competitiveness improves over time as hydrogen production costs decline and fossil-fuel vehicle costs increase due to the EU ETS2 and Eurovignette CO₂ surcharges. The analysis identifies two key inflection points, that is, light-duty hydrogen FCEVs become more cost effective than petrol vehicles in 2037 and reach parity with EVs in 2046. In emissions terms, light-duty FCEVs occupy a strong position on the low-WTW frontier, while EVs combine the lowest TCO with similarly favorable emissions performance. To bridge the intermediate cost-parity gap and mitigate infrastructure lock-in risks, targeted policy measures, such as carbon-weighted road toll exemptions, upstream fuel-tax subsidies under the EU ETS2 framework, and capital grants for localized commercial fleet refueling units, are essential to accelerate early-stage market industrialization and secure the economic viability of hydrogen mobility. Full article

In the context of global climate change and China’s “Dual Carbon” target, the misallocation of carbon emission reduction responsibilities and low regulatory efficiency urgently require analysis and resolution. Based on China’s 2020 MRIO and carbon emission inventory data, this study integrates multi-regional input–output models and complex network theory to construct an embodied carbon emission (ECE) transfer network at the provincial-industrial level and analyze its structural characteristics. Drawing on complex network control theory, this paper proposes a heuristic node-ranking strategy to identify driver nodes for full controllability of the ECE transfer network and compare its regulatory effect with other topological indicators. The findings reveal: (1) At the provincial level, embodied carbon emissions show a distinct transfer pattern from central provinces to southeast coastal or economically developed regions. Jiangxi, Anhui, Shandong, etc., are net outflow provinces, while Jiangsu, Beijing, Guangdong, etc., are net inflow provinces. (2) At the industrial level, secondary industry is the main net inflow industry, and primary industry is the main net outflow industry. The secondary industries in Guangdong, Henan, etc., have high betweenness centrality, acting as “hub” nodes for carbon transmission. Community detection shows that the largest community in China is centered on the secondary and tertiary industries of Jiangsu, Henan, Guangdong, etc., and the network overall exhibits small-world characteristics. (3) Compared with other control strategies, the designed algorithm achieves the best control effect: it realizes full network controllability with the minimum number of control nodes (26), and the shortest reachable paths from the control node set to non-control nodes, meaning policy signals imposed on control nodes transmit at the fastest speed. (4) Among the control node set, 22 key control nodes are mostly secondary and tertiary industries, located at the center of the transfer network and ranking high in net outflow or inflow, belonging to the core nodes of the ECE transfer network. This study provides a scientific basis and methodological support for clarifying the attribution of carbon transfer responsibilities and formulating differentiated collaborative regulatory policies. This paper establishes a qualitative matching mechanism between network control inputs and carbon tax, emission quotas and industrial regulation to connect controllability theory and practical carbon governance. Full article

Sustainable development views energy as a determinant of the interdependence between economic growth and ecosystem protection, which influences the specificity of energy-production relationships in the hospitality and catering sectors (HoReCa) and the Maintenance, Repair, and Operations (MRO) sector. The primary goal of this study is to identify and assess the structural relationships between environmental, fiscal, production, and energy factors in industrial enterprises and their impact on production and resource potential within the intersectoral network of the HoReCa and MRO sectors, taking into account emission burdens and fiscal instruments. The research procedure utilized partial least squares coherent structural equation modeling (PLSc-SEM). The model was built using Eurostat data from 2008 to 2020 for companies in 23 countries of the European Union. The analysis showed that the energy consumption of the hospitality and catering establishments (HoReCa) is the strongest predictor of MRO sector activity (β = 0.910), whereas the emission intensity of MROs exerts a comparatively minor effect. The results document the dominance of scale over emission intensity in shaping environmental burdens. Furthermore, they confirm the negative impact of environmental taxes on the remuneration fund of highly qualified specialists. The full mediation of operational scale was also demonstrated in the relationships between energy demand, emissions levels, and labor costs. The results of the study clearly indicate the need to integrate building energy policy with the decarbonization of technical services. From a macroeconomic perspective, this approach supports the achievement of sustainable development goals. Implementing predictive maintenance demonstrates a dual synergistic effect, combining maximized resource productivity with a simultaneous reduction in carbon footprint. Full article

Under the growing pressures of climate change and low-carbon transition, economic policy instruments play an important role in shaping technological innovation in renewable energy industries. This study examines the association between research and development (R&D) tax deduction intensity and patent-based low-carbon innovation among Chinese photovoltaic firms. Using a panel of 71 Chinese A-share listed photovoltaic firms during 2019–2024 and two-way fixed effects models, we find no stable association between R&D tax deduction intensity and firms’ overall innovation output. However, after distinguishing innovation types, R&D tax deduction intensity is positively associated with radical innovation output and negatively associated with incremental innovation output, indicating that R&D tax deduction intensity leads to a structural reallocation of innovation resources rather than a simple expansion of innovation quantity. Further results suggest that financing constraints and the external government subsidy intensity shape the marginal effect of R&D tax deduction intensity. Financing constraints exhibit a relatively stable moderating role, while the effect of the government subsidy intensity becomes more evident when firm financing conditions are jointly considered. These findings highlight the need to evaluate energy-transition policies not only by aggregate innovation output, but also by innovation structure, firm heterogeneity, and complementary policy environments. Full article