Carbon Trading Research Articles

Designing a carbon-trading incentive scheme for mode shifts in multi-modal transport systems

The pressing need to reduce greenhouse gas emissions triggers the imperative for efficient travel demand management. Previous studies have explored budget-based and aggregated incentive programs, which place a significant financial burden on governments and tend to be limited in contributing to effective behavior change in practice due to budget issues. This study proposes a personal carbon trading travel incentive (PCTTI) mechanism, to encourage private car commuters shifting to using public transit. The incentive budget for PCTTI is sourced from the revenue generated through selling carbon emission reductions resulting from commuters’ travel mode shifts. To determine the optimal incentives, we developed an incentive scheme optimization model based on the Stackelberg game model. Numerical analysis reveals the significant potential of the PCTTI to reduce carbon emissions and travel costs across various scenarios within a multi-modal transportation system. This potential is evident amidst changes in the fixed costs of car travel, carbon trading prices, the use of different travel modes, the value of time, and the prevalence of electric vehicles. The advantages are most pronounced when the carbon trading price exceeds 40 CNY/ton, and when the usage of public transit, the value of time, and the proportion of electric vehicles each fall below 0.4, 50 CNY/hour, and 0.4, respectively.

Leveraging Digital Technologies for Carbon Footprint Tracking in Perennial Cultivations: A Case Study of Walnut Orchard Establishment in Central Greece

The present paper aims to quantify the carbon emissions associated with the establishment of 15 walnut orchards (“Juglans californica”) in the greater area of Magnisia, Greece, with the use of a carbon footprint tool interconnected to a Farm Management Information System. The data collection spanned the first five years following the planting of the trees, providing a comprehensive view of the emissions during this critical establishment phase. Over the five-year period examined (February 2019–December 2023), the results revealed net carbon emissions amounting to 13.71 tn CO2 eq ha−1, with the calculated emissions showing an increasing trend from the first year through the fifth year. Scope 1 (7.38 tn CO2 eq ha−1) and Scope 2 (3.71 tn CO2 eq ha−1) emissions emerged as the most significant, while irrigation (drip irrigation) and fertilizing practices were identified as the highest contributors to emissions. This study highlights the significance of using integrated digital tools for monitoring the performance of cultivations rather than standalone tools that are currently widely available. Integrated tools that incorporate various applications simplify data collection, encourage accurate record-keeping, and facilitate certification processes. By automating data entry and calculations, these tools reduce human error during agricultural carbon management and save time; thus, the integration of digital monitoring tools is vital in improving data accuracy, streamlining certification processes, and promoting eco-friendly practices, crucial for the evolving carbon market.

The impact of carbon emission trading policy on regional total factor productivity

The impact of carbon emission trading policy on regional total factor productivity

The Impact of Environmental Information Disclosure in the “Carbon Trading Pilot” Project on the Financial Performance of Listed Enterprises in China

The Impact of Environmental Information Disclosure in the “Carbon Trading Pilot” Project on the Financial Performance of Listed Enterprises in China

Low carbon operation and evaluation methods for integrated energy system counting EVs with whole life cycle considering demand response

The integrated energy system has gradually become an effective way of energy saving and emission reduction with the proposal of “dual carbon" target and the continuous promotion of low-carbon development. However, most of the existing studies on demand-side flexible loads only consider flexible power loads, and there are fewer studies on the controllability of thermal loads. This paper proposes a low-carbon and economic optimal scheduling model and evaluation method for integrated energy system considering demand-side response. With the goal of minimizing the total operating cost of the integrated energy system, and taking into account the transferable and curtailing characteristics of the electric and thermal flexible loads, we establish an optimal scheduling model of the integrated energy system considering the user-side flexible loads, and comprehensively evaluate the performance of the system in terms of economic performance, reliability, and environmental performance. The performance of the system is evaluated in terms of economic performance, reliability and environmental performance. The role of flexible loads in improving the economy of the combined supply system is investigated with examples, and the rationality and effectiveness of the study are verified through comparative analysis of different scenarios. The results show that the total cost of the system is reduced by 18.04 %, 9.1 %, 3.35 % and 7.03 % when carbon trading cost and demand-side flexible electric-heat load response are considered at the same time; and the total carbon emission of the system is reduced by 65.28 %, 20.63 %, 3.85 % and 18.03 %, respectively. Considering carbon trading costs and demand-side flexible electric and thermal load response can improve the reliability of the system. The overall reliability of the system is improved by 10 %, 15 %, 16.67 % and 20 % for the four scenarios, respectively.

Assessing the Challenges to Leverage Carbon Markets for Renewable Energy in Developing Countries: A Multi-Criteria Decision-Making Approach

Assessing the Challenges to Leverage Carbon Markets for Renewable Energy in Developing Countries: A Multi-Criteria Decision-Making Approach

A dynamic multi-objective optimization model for inner-industry carbon responsibility allocation based on carbon tax and carbon offsets accounting

The setting of Intergovernmental Panel on Climate Change (IPCC) raises concerns on curbing the excessive carbon emissions, and European Union (EU) has been proactively attempting “green” initiatives striving to achieve carbon neutrality. The current Carbon Border Adjustment Mechanism (CBAM) only works on short-term carbon reduction without much “greenness” investment incentives so far, and few studies focus on the long-standing inner-industrial carbon reduction coordination. To address these issues, this paper creatively presents a dynamic multi-objective carbon responsibility allocation model (CRAM) for EU carbon market, allows the carbon trade with a taxation based on carbon offsets accounting, and considers the final targets of sustainable “greenness” investment incentives. To find the optimal results of the designed dynamic CRAM, an improved KT-NSGA-II algorithm is proposed to detect the Pareto frontiers of each successive periods. Data from EU Cement and Aluminium industries are then selected for empirical analysis to compare the proposed CRAM to conventional CBAM model. The findings demonstrate that the superiority of CRAM in carbon emissions reduction, economic benefits improvement and green invests encouragement. With the adjustment of the inner-industrial carbon allowance trade, total carbon emissions decreased by 28.03% and the “greenness” investment initiative increased by 39.24% in contrast to the CBAM. The sensitivity analysis of the model also provides suggestions on the settings of carbon quota and tax with different industrial production process, and proposes policy recommendations for CRAM implementation.

Strategic investments and portfolio management in interdependent low-carbon electricity and natural gas markets

Addressing global warming necessitates carbon emissions reduction and renewable energy integration within the energy sector. Gas-Fired Power Plants (GFPP) are appealing to investors due to their low emissions and operational flexibility, which are considered necessary characteristics within low-carbon power systems with increasing renewable energy uncertainty. Investing in GFPPs presents intricate challenges due to the increasingly interdependent electricity and natural gas markets, especially in the light of a low-carbon economy. This work addresses these challenges for a strategic agent by proposing a bi-level optimization framework. The upper-level model derives the optimal electricity portfolio management regarding new investments and strategic biddings, while in the lower-level model, the electricity and gas markets are cleared sequentially under a Carbon Emission Trading Scheme (CETS). Case studies on a Pennsylvania-New Jersey- Maryland (PJM) 5-bus power system and an IEEE 24-bus test system demonstrate the applicability and efficacy of the proposed model in capturing the impact of a transitional integrated market framework on GFPPs investments. Also, introducing stochasticity to the model provides a better insight into the contrasting effects of emission allowance trading and gas prices on investment and bidding strategies.

Relegitimising the voluntary carbon market: Visions of digital monitoring, reporting and verification

Relegitimising the voluntary carbon market: Visions of digital monitoring, reporting and verification

A Sustainable Model for Forecasting Carbon Emission Trading Prices

Carbon trading has garnered considerable attention as a pivotal policy instrument for advancing carbon peaking and carbon neutrality, which are essential components of sustainable development. The capacity to precisely anticipate the cost of carbon trading has significant implications for the optimal deployment of market mechanisms, the economic advancement of technological innovations in corporate emissions reduction, and the facilitation of international energy policy adjustments. To this end, this paper proposes a novel and sustainable trading price prediction tool that employs a four-step process: decomposition, reconstruction, prediction, and integration. This innovative approach first utilizes the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), then reconstructs the decomposition set using multi-scale entropy (MSE), and finally uses the Long Short-Term Memory neural network model (LSTM) enhanced by the Grey Wolf Optimizer (GWO) to predict the carbon emission trading price. The experimental results demonstrate that the tool achieves high accuracy for both the EU carbon price series and the carbon price series of China’s seven major carbon trading markets, with accuracy rates of 99.10% and 99.60% in Hubei and the EU carbon trading markets, respectively. This represents an improvement of approximately 3.1% over the ICEEMDAN-LSTM model and 0.91% over the ICEEMDAN-MSE-LSTM model, thereby contributing to more sustainable and efficient carbon trading practices.

An analysis of optimal equilibrium in the carbon trading market - From a tripartite evolutionary game perspective

As the climate crisis intensifies, achieving the global consensus of carbon peaking and carbon neutrality has become imperative. Carbon trading is an important financial measure to address the environmental crisis, and the realization of the dual‑carbon goals requires the cooperation and joint efforts of all parties involved in the carbon emissions trading market. This study constructs a dynamic evolutionary game model involving enterprises, government, and financial institutions while considering consumers' influence. By solving for equilibrium points and conducting numerical simulations, we explore optimal strategy choices for each stakeholder. Our findings reveal that the success of enterprise low-carbon transition is contingent upon market dynamics and requires active cooperation from government, financial institutions, and the public. Furthermore, factors such as financial market efficiency and internal governance capacity significantly impact enterprises' transformation decisions by influencing low-carbon transition costs. Public feedback indirectly affects enterprise decisions through its influence on financial institutions' provision of green services. Additionally, gradual reduction of carbon quotas by government entities facilitates progress toward low-carbon transformation objectives.

EXPERIENCE WITH GREENHOUSE GAS EMISSION ALLOWANCE ALLOCATION AND ANALYSIS OF LESSONS FOR VIET NAM

This study analyzes and synthesizes international experiences in allocating greenhouse gas emission quotas, drawing lessons for Viet Nam's developing carbon market. The research examines emission trading systems (ETS) and quota allocation methods from various countries and regions, including the European Union, Germany, Austria, the United Kingdom, Switzerland, the United States, Canada, Nigeria, Kenya, South Africa, China, Japan, and New Zealand. Key findings highlight the importance of diversifying allocation methods, combining free allocation, auctioning, and benchmarking approaches. The study emphasizes the need for flexibility in system design, adapting to specific economic and social conditions of each country. Lessons learned include prioritizing high-emission reduction potential sectors, setting reasonable emission caps based on actual data, ensuring transparency in information disclosure, and establishing effective monitoring and evaluation mechanisms. The research also stresses the importance of providing technical support to businesses, especially small and medium enterprises, in complying with ETS regulations. Additionally, the study addresses concerns such as preventing carbon leakage, assessing social impacts, and ensuring international compatibility of the system. These insights provide a valuable foundation for Viet Nam to develop an effective greenhouse gas ETS that aligns with national conditions and sustainable development goals.

The phenomenon of China’s carbon accounting policies and practices

Purpose This study aims to explore China’s carbon accounting policies and practices to enhance its carbon accounting and trading practices and achieve carbon neutrality. Design/methodology/approach This study adopts a phenomenological methodology to explore carbon accounting by setting the scope of the phenomenon, establishing research methods, conducting interviews with 30 participants from 14 emitting entities and four accounting firms and establishing methods for data analysis. Five themes were identified using a five-step coding method. Findings The results show no uniformity in the accounting treatment of carbon trading; however, common characteristics exist, and they have generally adopted simplified and conservative accounting methods under China’s emission trading scheme. Their common characteristics are that the granted allowances are not recognised as assets by most emitting entities, emissions allowance assets are measured using the historical cost method, most emitting entities only conduct accounting when there are actual cash flows or outflows with regard to carbon emissions allowance trading, and only a few emitting entities disclose carbon trading information in their financial statements or corporate social responsibility reports. Originality/value This study highlights accountants’ crucial role in carbon activities by guiding emitting entities’ low-carbon initiatives and culture and transforming managers’ mindsets. It also introduces the China Accounting Standards Committee-based accounting methods for allowances and obligations, aiding carbon disclosure quality and sustainability. These findings also inform the carbon accounting standards that may enhance corporate accountability and address climate change.

Potential environmental implications of sandbar afforestation: Insights from ecosystem restoration initiatives in a sandbar of Brahmaputra River Assam, India

Plantation in riverine sandbars offers an excellent opportunity for restoration of ecosystem with a vast potential for enhancing carbon stock. Afforestation on barren islands is challenging task; however, Padmashree Jadav Payeng has single-handedly transformed a sandbar of the river Brahmaputra into a forested landscape in India’s northeastern state of Assam. Such inspiring initiative needs more attention in terms of scientific assessment to quantify ecosystem value and services that can be enriched through such activities. This study uses remote sensing data viz., Landsat4–5TM and Sentinel 2 A data to provide a detailed information on spatio-temporal variability of land use land cover of study region from 1990 to 2021. It aims to conduct a scientific and systematic assessment of biophysical changes that have occurred in the sandbars, understand the status of afforestation, and evaluate the current levels of aboveground biomass (AGB), belowground biomass (BGB), and carbon stock in the selected sandbars. The spatial distribution of AGB, BGB and carbon stock is derived using linear regression model between SAR backscatter and field-based AGB. The results demonstrate that forest cover increased by 31.92 % and sandbar area is reduced by 26.87 % from 1990 to 2021. Spatially derived AGB ranges from 9 to 1295.89 Mg per ha, BGB from 2.35 to 290.50 Mg per ha and carbon stock from 6.18 to 763.34 Mg per ha. Ficus religiosa exhibits a high biomass, ranging from 564.7 Mg per ha to 994.7 Mg per ha, and a high carbon stock, ranging from 8 to 557.30 Mg per ha, attributed to its larger diameter at breast height (DBH). Moreover, phytosociological assessment was conducted for the studied forest, which reveal a total tree species richness of 79. The forest exhibits a total tree density of 395 individuals per hectare. Different biodiversity indices provide a comprehensive understanding of species composition; where results show a Shannon diversity index of 2.81, a Simpson's index of 0.08, a Menhinick's richness index of 2.7, and a Margalef's richness index of 5.26. The article provides detailed information on change in forest cover and present status of AGB, BGB and Carbon stock, providing evidence-based narratives on ecosystem restoration. The initiative by a single person has created a forested landscape and habitat for a large number of wild animals, contributing to better carbon stock and a healthier ecosystem. With regard to the current debate of carbon market, the study suggests the need of instrumentalization of carbon credits for such restoration activities to encourage increase in carbon stock. It also concludes that in-depth research should be taken up on long-term effectiveness of such plantation activities and the potential for scaling up these initiatives for ecosystem restoration in view of climate change mitigation and sustainable forest development.

Endowment effects, expectations, and trading behavior in carbon cap and trade

We explain agents' trading behaviors and market outcomes in the presence of endowment effects intensified by expectations-based loss aversion in carbon cap and trade. Building on Kőszegi and Rabin (2006)’s model with forward-looking reference points, we show how firms' concerns about high future compliance costs (through loss aversion and uncertainty) can cause a gap between Willingness-to-Pay and Willingness-to-Accept for allowances. This leads to limited allowance trading and deviation from the socially desirable paths. The problem can be exacerbated under a substantial proportion of free allocation, a fixed (or inflexible) cap as well as uncertain regulatory ambitions, particularly in emerging economies under a variety of uncertainty. Recognizing the regulator's role in dealing with firms' expectations (or concerns) and facilitating innovation investments, we discuss potential alternative systems (e.g., with auction and flexible supply) for decarbonization that incorporate flexibility in terms of innovation timing and realized costs.

Discussion On The Development Of China's Regional Carbon Market Under The Background Of Double Carbon

Accelerating China's carbon trading market is one of the important means to deal with climate change and achieve the dual carbon goal. Due to the huge differences in China's regional economic development and carbon resource endowment, the impact of the establishment of the national unified carbon trading market on regional economic development is unstable and uncertain. For local governments to make full use of this empty window period, this paper combs the recent development of the carbon market, and discusses the development prospect of China's regional carbon market under the background of carbon trading. The results show that: ①in the current development of the national carbon emission trading market, we can not achieve the carbon unification of the market and abandon the local carbon trading market; ②In the process of regional carbon trading, it can promote the low-carbon development of local economy; ③In the process of regional carbon trading, it can increase the share of clean energy and improve the efficiency of regional ecological and environmental protection. Then, some suggestions are put forward for the development of local carbon trading: ①appropriately expand the pilot scale of local carbon trading, go up and down, and realize the double cycle development of carbon market; ②Strengthen the training of professionals and create an innovative and entrepreneurial business environment; ③build a carbon platform with big data technology and improve the Regional Internet plus carbon enterprise database; ④Actively promote the development of PPP model, explore the carbon sink transaction of cooperation between the government and social capital, continuously improve the regional green and low-carbon development, and jointly promote the realization of the "double carbon goal".

Fuzzy credibility chance-constrained multi-objective optimization for multiple transactions of electricity–gas–carbon under uncertainty

This paper proposes a fuzzy credibility chance-constrained multi-objective optimization model to optimize market transactions in the electricity–gas–carbon sectors under uncertainty. The model aims to maximize the profit of an integrated energy service provider by incorporating a ladder-type carbon trading mechanism, which adjusts carbon prices based on emission levels, and detailed multi-energy flow constraints. To effectively manage uncertainties in electricity, gas, and carbon markets, we derive credibility distributions for uncertain variables and introduce fuzzy credibility chance constraints—tools that assess the likelihood of meeting multiple transactions under uncertainty. The proposed model hedges the risks associated with multiple uncertainties while maximizing the credibility of expected costs, effectively balancing risk and cost. Through simulation analysis on an IEEE 33-node power network and a 32-node heat network, the proposed model achieved a 9.8% reduction in total system cost and an 8.5% reduction in total carbon emissions. Additionally, the model effectively determined credibility levels under different risk preferences, demonstrating its robustness in enhancing electricity–gas–carbon trading and promoting a low-carbon economy. This research provides a novel planning method for formulating trading strategies in multi-energy markets, with significant real-world implications for energy management and environmental sustainability.

Questioning Sustainable Environmental Policies and Practices in Indonesia: Would Durkheim’s Structural Functionalism Theory Have a Relevance?

Indonesia, as a signatory to the UNFCCC and the Paris Agreement, is committed to reducing greenhouse gas (GHG) emissions. These commitments, outlined in Law Number 16 of 2016, include limiting global temperature rise, setting Nationally Determined Contributions (NDC) targets, and developing a long-term strategy for net zero emissions by 2050. To meet these obligations, the Indonesian government has introduced Carbon Economic Value (CEV) policies through Presidential Regulation Number 98 of 2021. These policies aim to reduce GHG emissions by implementing carbon pricing mechanisms such as carbon trading, levies, and performance-based payments. However, the implementation of CEV policies has faced various reactions, including criticism and resistance. Despite these challenges, it's imperative not to hinder the policy's implementation, given its potential to drive significant societal and lifestyle changes towards a greener future. This study analyzes Indonesia's progress in reducing GHG emissions through CEV policies. Using normative legal research and qualitative analysis, it explores the positive impacts of these policies, including their alignment with structural functionalism theory. The study highlights that the implementation of CEV policies as an effort to reduce greenhouse gas emissions in Indonesia through carbon trading mechanisms, carbon taxes, and funding partnerships with developed countries aligns with structural functionalism theory according to Emile Durkheim. This is evidenced by the existence of a clear system (legal and governance) in implementing CEV policies, including regulators (Government), implementers (SOEs, private sector, and society), supervisors (UNFCCC), and program donors (World Bank, IMF), where each entity cooperates in an organized manner in accordance with the provisions of the Paris Agreement 2015 and Presidential Regulation 98 of 2021 continuously according to their respective tasks. This policy also brings about functional social change by promoting a harmonious balance to shift dependence away from fossil fuels towards more environmentally friendly Renewable Energy sources.

Carbon market design and market sentiment

Concerns about systematic price distortions in the EU Emission Trading System (ETS) have risen in recent years. This paper shows how carbon-market design affects the impact of market sentiment, i.e. systematic deviations of price expectations from fundamentals by at least some market participants, on equilibrium prices. The Market Stability Reserve (MSR) of the EU ETS that adjusts supply based on past allowance banking undermines self-stabilization of the carbon market by discouraging rational intertemporal arbitrage. The MSR increases vulnerability of the EU ETS to market sentiments. Initially, the allowance price responds more to distorted expectations while the MSR (partially) prevents the distortion to spread across periods. Making the MSR more responsive to banking decisions increases the likelihood that distorted expectations turn out to be correct ex post. In contrast, a mechanism that adjust the cap based on the current allowance price does not face a trade off between stabilizing prices in the present and the future.

Market-incentivized environmental regulation, industrial agglomeration and the effects on carbon shadow price: Evidence from China's local pilot policies for carbon market construction

Market-incentivized environmental regulation, industrial agglomeration and the effects on carbon shadow price: Evidence from China's local pilot policies for carbon market construction