Search Results (165)

To meet the goals of the Paris Agreement of avoiding dangerous climate change, decarbonisation of the global economy needs to proceed around three to five times faster over the coming decade than over the past two decades. This poses a great challenge for policy. Carbon pricing has often been put forward as the most efficient, or cost-effective, policy for achieving decarbonisation. This paper uses a stylised agent-based model to investigate whether implementing non-equilibrium dynamics and endogenous innovation results in more effective emission reductions for carbon tax compared with emission trading schemes. We find that the implementation of a carbon price is not policy-agnostic and that a carbon tax achieves faster emissions reduction, lower cumulative emissions, and lower cumulative (potentially wasted) investment in fossil fuel assets than a cap-and-trade policy with the same average carbon price. While a comparison between carbon pricing and alternative policies is outside the scope of this paper, we consider the broader policy implications that may be drawn from a new theoretical explanation for the difference in performance of the alternative carbon pricing approaches, and suggest that the traditional view that policy should aim to minimise the marginal emissions abatement cost is mistaken. Full article

Globally, greenhouse gas (GHG) emissions have risen dramatically due to accelerated industrialization, excessive fossil fuel extraction, and agricultural activities, leading to global warming and ecosystem collapse. Achieving net-zero carbon emissions has therefore become a crucial global priority. Despite substantial international efforts, only a small number of countries have achieved carbon neutrality so far, with the majority aiming to do so by 2050 or 2060. Progress remains hindered by fragmented international coordination and inadequate integration of mitigation and adaptation co-benefits. However, agriculture is a major carbon emitter with significant mitigation potential. Attaining local carbon neutrality in agricultural landscapes is highly costly and strongly impacted by the spatial heterogeneity of GHG emissions and the diversity of available mitigation possibilities. This sector remains a major contributor to methane (CH₄) and nitrous oxide (N₂O) emissions, mainly through enteric fermentation and fertilizer use, and thus must be prioritized in global carbon neutrality strategies. Tactics such as improved livestock management, reduced use of synthetic fertilizers, conservation agriculture, afforestation, and renewable energy adoption can reduce emissions. These technical approaches should be supported by effective policy instruments, like carbon taxes, cap-and-trade schemes, low-carbon practice subsidies, and regulatory frameworks. Together, these measures can enable a transition toward long-term sustainability in agriculture by balancing emissions with removals through enhanced carbon sinks and credible offset mechanisms. Full article

This article integrates sustainability principles into a three-echelon supply chain for deteriorating items with imperfect quality, consisting of a single vendor, a third-party logistics enterprise (3PL), and a single buyer, with a focus on balancing economic efficiency with environmental responsibility. The vendor is assumed to operate an imperfect production system, resulting in products of imperfect quality. The 3PL undertakes all transportation activities, while the buyer conducts a quality inspection process to detect defective items, which is subject to Type-I and Type-II errors. Aside from that, the inventory model also assesses carbon emissions arising from various operational activities including energy usage during production, warehousing, and disposal processes, and fuel consumption in transportation, for which the above members of the supply chain are accountable. Afterward, carbon management policies such as a carbon tax and carbon cap-and-trade are considered to regulate total supply chain emissions. The objective is to minimize the joint expected total cost by simultaneously optimizing shipment frequencies and the replenishment cycle for the buyer within carbon emission constraints. An iterative solution procedure is developed to address the problem. A numerical example and sensitivity analysis are provided to demonstrate the model’s applicability and to explore the influence of critical parameters. Finally, the study presents managerial insights, along with conclusions and recommendations for future research directions. Full article

This study investigates trade-in channel selection in a closed-loop supply chain under a hybrid carbon policy framework that integrates cap-and-trade and carbon taxation. Game-theoretic models are developed for three manufacturer-led channels: manufacturer trade-in (M-CX), retailer trade-in (R-CX), and third-party trade-in (T-CX). The analysis examines pricing strategies, profitability, and carbon emission reductions across these channels. The key findings are as follows: (1) Carbon tax consistently compresses manufacturer profits, whereas cap-and-trade mechanisms exhibit a non-linear U-shaped effect. Manufacturer profits remain highest under the M-CX channel, irrespective of policy intensity. (2) Retail prices are most sensitive to carbon policies under the T-CX channel, where trade-in rebates increase with carbon intensity. The R-CX channel sustains higher retail prices and rebates than M-CX, while T-CX surpasses both under conditions of high carbon intensity. (3) Carbon emission reductions decline sharply under M-CX and R-CX as policy stringency increases. In contrast, the T-CX channel establishes a buffering mechanism through rising rebates, exhibiting the slowest rate of decline. At low carbon intensity, T-CX yields the lowest reduction levels; however, under high intensity, it overtakes the other channels to achieve the highest reduction. This study offers insights for manufacturers’ channel selection and government policy coordination under hybrid carbon regulation regimes. Full article

Under the background of the carbon cap and trading mechanism, the shipping logistics service supply chain faces pressure to reduce carbon emissions, and artificial intelligence technology provides a new technological path for emission reduction. In the context of a carbon cap-and-trade system, this study examines a shipping logistics service supply chain comprising a service provider and a service integrator, where the provider adopts AI technologies for direct emission reduction and the integrator contributes indirectly. It investigates optimal decision-making under two models: a single emission-reduction model (only provider uses AI) and a joint-emission-reduction model (both adopt AI), while also exploring one-way and two-way cost-sharing contracts between them. The study establishes these models to analyze the impact of cost-sharing contracts on emission reduction levels, total service volume, and profits, and further examines how government regulation of carbon trading prices can promote reduction. Findings reveal that cost-sharing contracts effectively enhance emission reduction, output, and member benefits; one-way contracts are conducive to operations, while two-way contracts are effective only within a small cost-sharing ratio range. The joint model outperforms the single model under specific parameter thresholds, and cost-sharing ratios influence decentralized versus centralized decision-making. Government carbon price regulation can encourage reduction but must consider its effects on low-carbon logistics volume and profits. Full article

To enhance the low-carbon operational performance of integrated energy systems (IESs) under multi-source uncertainties, this study proposes a bilevel stochastic optimization framework incorporating a dynamic mean–CVaR risk model and a tiered carbon pricing mechanism. The upper level adopts an improved NSGA-II to jointly optimize economic cost, carbon emissions, and system flexibility through capacity planning decisions. The lower level performs scenario-based operation evaluation with a time-varying risk aversion coefficient, enabling differentiated risk responses across operating periods. A stepwise carbon price function and a capped carbon revenue mechanism are introduced to represent real carbon market regulations and avoid excessive emission reduction benefits. Multidimensional uncertainty scenarios—covering renewable variability, load fluctuations, and market price disturbances—are generated for risk-aware evaluation. Simulation results show that the proposed approach effectively reduces cost and emission volatility and achieves a more balanced trade-off between economy and low-carbon performance compared with conventional static-risk models. Sensitivity analyses further reveal that increased risk aversion shifts system operation strategies from economy-oriented to robustness-oriented modes, highlighting the importance of dynamic risk modeling and carbon policy design for future low-carbon multi-energy systems. Full article

Within closed-loop supply chains (CLSCs), limited attention has been given to firms’ production and abatement decisions involving carbon permit transfer between an original equipment manufacturer (OEM) and an independent remanufacturer (IR) under a cap-and-trade policy (CTP). Several questions remain unresolved: How does CTP reshape production and abatement decisions through carbon permit transfer under binding emission constraints? Can such regulation reallocate abatement responsibilities between firms and generate environmental and economic benefits? To address these questions, this paper develops a constrained Cournot game model capturing competitive interactions between an OEM and an IR under regulation. The results show that CTP reallocates abatement responsibilities toward the firm with a lower abatement difficulty, inducing full abatement as a corner solution. When remanufactured products exhibit a high low-carbon level, a moderate increase in cap stringency promotes remanufacturing output and market share. By contrast, once full abatement is reached, stricter regulation expands output. Moreover, when remanufacturing features substantial cost savings and a high low-carbon level, CTP consistently improves social welfare. This study provides insights into how cap-and-trade policies shape production and abatement decisions in CLSCs. Full article

In this study, we develop a game-theoretic optimization framework to analyze competing vessels’ technology choices between shore power (SP) and low-sulfur fuel oil (LSFO) within a maritime supply chain which is regulated by a cap-and-trade mechanism. Using a Stackelberg game approach, we construct two models—one port-led and the other vessel-led—to derive closed-form equilibrium for pricing, service quantities, profits, emissions, and social welfare. The results reveal three key findings. First, the leader in either Stackelberg structure always achieves higher profits, while total supply chain profits remain identical across power structures. Second, at low carbon prices, LSFO-equipped vessels provide more services and earn higher profits due to cost advantages. As the carbon price rises—which directly incentivizes emission reduction and accelerates maritime decarbonization—SP becomes more attractive and eventually dominates in profitability despite higher initial investment. Notably, although SP has lower unit emissions, its total emissions may surpass those of LSFO at certain carbon-price thresholds because the SP-equipped vessel optimally expands output. Third, intensified competition reduces service quantities, profits, and emissions, with a more substantial reduction effect on LSFO vessels. Overall, our results provide mathematically grounded insights for optimizing low-carbon technology adoption in maritime transport and offer actionable policy implications for carbon pricing that balance environmental objectives and supply chain efficiency. This research contributes specifically to the United Nations’ Sustainable Development Goals (SDGs), specifically SDG 13 (Climate Action) and SDG 9 (Industry, Innovation and Infrastructure). Full article

The previous studies have suggested that the cap-and-trade carbon emissions trading scheme (ETS) was effective in reducing greenhouse gas emissions and atmospheric pollution. Are there other environmental benefits of this policy? This research question remains unanswered in the literature. Our study reports that China’s carbon ETS significantly improved the land surface ecological quality (LSEQ). The study analyzes the data of 328 Chinese cities during 2005–2020. A difference-in-differences (DID) regression model is used for quantitative policy evaluation. The land surface ecological quality is measured by a synthetic indicator of the remote sensing ecological index (RSEI). There are three main findings. (1) On average, the carbon ETS improved the land surface ecological quality index by 0.0113, which contributed 51% of the ecological quality improvement in ETS-implementing regions in the post-policy period. The positive effect of the policy increased over time. (2) The implementation of the carbon ETS reduced pollution emissions, promoted green innovation, and expanded the share of land with natural vegetation coverage. These phenomena provide explanations for why the policy improved the land surface ecological quality. (3) The policy effect exhibited some heterogeneities contingent on local climatic conditions. The effect was stronger in regions with more precipitation, shorter sunlight duration, and higher temperature. Full article

The true contribution of economics to climate policy is marred by many misconceptions. This paper aims to help non-experts better understand economic insights by progressively introducing key concepts. We start with perfectly functioning markets, where prices act as powerful guides to channel scarce resources toward their best use from a social point of view. We then recognize that, in many real cases, markets fail to deliver their promise because prices are either absent or do not reflect social values. Anthropogenic greenhouse gas emissions constitute a particularly acute type of market failure affecting both the whole world and future generations. The fundamental source of this failure is the absence of a price on emissions, and economic research has followed two major routes. On the one hand, economists run complex simulation models to estimate the missing price, which can be used as a social yardstick to guide policy choices. On the other hand, they evaluate policy instruments able to reorient market forces toward more climate protection. Two instruments with a strong potential to influence behavior deserve particular attention: the carbon tax and cap-and-trade (or emissions trading) systems. Despite practical complications and the lack of international coordination, both policies have recently made encouraging progress. Full article

Growing climate concerns and rising consumer awareness of sustainability have reshaped strategic interactions in platform-based supply chains. This study examines how a manufacturer and an e-commerce platform make channel and fulfillment decisions under cap-and-trade regulation. The manufacturer chooses between non-encroachment and agency encroachment, while the platform decides between conventional and sustainable fulfillment. To capture the dynamic adaptation of boundedly rational agents, we develop an evolutionary game model (EGT) and characterize the evolutionary stable strategies. The findings indicate the following: (1) Platform investment in sustainable fulfillment exerts a strategic stabilizer effect, effectively protecting the reselling channel by reducing the manufacturer’s incentive to encroach even under moderate commission rates; (2) there exists a regulatory substitution effect between carbon pricing and commissions, where high carbon prices force manufacturers to encroach for survival, while low commissions encourage encroachment for profit; (3) consumer sensitivity exhibits a critical threshold behavior, where a synchronized transition to joint sustainability is impossible unless awareness exceeds a specific tipping point. Managerial insights suggest that platforms should view green logistics as a retention strategy to prevent channel fragmentation, while policymakers must coordinate carbon taxation with consumer awareness campaigns to avoid locking the system into non-green equilibria. Full article

Effective implementation of silvopastoralism, a key Nature-Based Solution for Europe’s climate goals, is hindered by a lack of decision-support tools clarifying trade-offs between efficiency and extent of carbon sequestration. To address this, we developed a multi-objective scenario analysis (4064 scenarios) to identify optimal strategies for silvopastoral expansion across the EU27 Mediterranean bioregion. We found an inverse relationship defining a clear trade-off: scenarios achieving the highest mean sequestration (up to 2.5 Mg CO₂ ha⁻¹ year⁻¹) are spatially limited, whereas those maximising total gains (approaching 10⁷ Mg CO₂ year⁻¹ in total) do so by incorporating vast areas, lowering mean rates. This trade-off is formalised by a Pareto front, from which we defined a best-balanced optimal scenario and three policy regimes (conservative, balanced, expansive). Progressing across the front involved shifting from converting primarily shrubby and sparsely vegetated lands to incorporating grasslands and mixed agro-systems. At the NUTS2 level, Spain and Greece emerged as hotspots. Notably, converting arable land was not a primary contributor to carbon gains, as the marginal carbon benefit on these productive soils is lower than on marginal lands due to their higher baseline soil carbon levels, indicating that large-scale implementation can focus on marginal lands to avoid conflicts with food security. While subject to uncertainties of the underlying land-use and carbon models, this analysis demonstrates that our framework enables policymakers to select spatially explicit strategies aligned with specific budget or sequestration goals. These insights can inform CAP eco-schemes and national LULUCF strategies. The resulting maps and code are freely available. Full article

As low-carbon supply chains increasingly integrate green transition strategies with digital transformation, coordinating high-cost green technology investments with data-driven marketing (DDM) becomes a complex managerial task. While these dual investments are essential for market growth, the inherent tension between economic efficiency and fairness concerns often triggers strategic friction phenomenon whose impact under cap-and-trade regulations remains insufficiently explored. This paper investigates the strategic implications of fairness concerns in a low-carbon supply chain in which a manufacturer invests in carbon emission reduction and a retailer engages in data-driven marketing (DDM), under a cap-and-trade regulation. We formulate four Stackelberg game models—Neutral Benchmark (NF), Retailer Fairness (RF), Manufacturer Fairness (MF), and Bilateral Fairness (BF)—to analyze the interplay between behavioral equity and economic efficiency. The main analytical results indicate that (1) fairness concerns universally function as an “efficiency tax” on the supply chain system, where the rational benchmark consistently yields the highest system efficiency. In contrast, bilateral fairness concerns lead to the worst performance due to double friction effects. (2) Counter-intuitively, the retailer can “weaponize” fairness concerns to extract surplus from the leader. Specifically, in environments with high carbon emission reduction costs, a fairness-concerned retailer compels the manufacturer to grant significant wholesale price concessions, thereby achieving higher profits than in a purely rational setting. (3) The manufacturer’s fairness creates a “Benevolence Trap” for the follower; to balance equity, a fair manufacturer tends to underinvest in green technologies, which severely contracts market demand and, unlike the retailer fairness scenario, fails to yield economic benefits for the retailer. (4) A critical “regime-switching” dynamic exists regarding the carbon trading price. While the retailer benefits from fairness strategies in nascent carbon markets, a pivot to rationality becomes optimal as carbon prices surge and efficiency dividends dominate. These findings offer novel managerial insights for supply chain members to navigate behavioral complexities and for policymakers to align incentive mechanisms. Full article

The paper introduces a real-time digital-twin controller that manages evacuation routes while operating GEEM for emergency energy management during building fires. The system consists of three interconnected parts which include (i) a physics-based hazard surrogate for short-term smoke and temperature field prediction from sensor data (ii), a router system that manages path updates for individual users and controls exposure and network congestion (iii), and an energy management system that regulates the exchange between PV power and battery storage and diesel fuel and grid electricity to preserve vital life-safety operations while reducing both power usage and environmental carbon output. The system operates through independent modules that function autonomously to preserve operational stability when sensors face delays or communication failures, and it meets Industry 5.0 requirements through its implementation of auditable policy controls for hazard penalties, fairness weight, and battery reserve floor settings. We evaluate the controller in co-simulation across multiple building layouts and feeder constraints. The proposed method achieves superior performance to existing AI/RL baselines because it reduces near-worst-case egress time ($T_{95}$ and worst-case exposure) and decreases both event energy $E_{\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{n}\mathrm{t}}$ and CO₂-equivalent ${{CO}_2}_{\mathrm{e}\mathrm{v}\mathrm{e}\mathrm{n}\mathrm{t}}$ while upholding all capacity, exposure cap, and grid import limit constraints. A high-VRE, tight-feeder stress test shows how reserve management, flexible-load shedding, and PV curtailment can achieve trade-offs between unserved critical load $U_{\mathrm{e}\mathrm{n}\mathrm{e}\mathrm{r}\mathrm{g}\mathrm{y}}$ and emissions. The team delivers implementation details together with reporting templates to assist researchers in reaching reproducibility goals. The research shows that emergency energy systems, which integrate evacuation systems, achieve better safety results and environmental advantages that enable smart-city integration through digital thread operations throughout design, commissioning, and operational stages. Full article

In order to study how the production network, energy network, and carbon trading network interact with each other in the process of distributed energy sharing in industrial parks under the carbon emissions trading mechanism, this paper constructs a supernetwork model of distributed energy sharing in industrial parks by using variational inequality, analyzes the behavioral patterns of each participant in the pursuit of their own interests and their impact on the equilibrium state of the network, and obtains the conditions for the network to reach an equilibrium state. Then, the projection correction algorithm is applied to solve the model in equilibrium, and the optimal decisions of product trading volume, distributed energy low carbon level, and carbon trading are obtained. Finally, through numerical examples, the influence of the carbon cap and carbon trading price on the network equilibrium decision is analyzed. The results show that the government’s elevation of the carbon emission cap for enterprises will reduce the enthusiasm for distributed energy sharing in industrial parks and expand the polarization of enterprise profits. A higher carbon trading price will increase the carbon trading cost of enterprises, which has a negative impact on distributed energy sharing in industrial parks. Full article