Emission Allowances Research Articles

A novel deep learning carbon price short-term prediction model with dual-stage attention mechanism

Carbon price prediction can help participants keep abreast of carbon market dynamics and develop trading strategies. It is challenging for statistical models to accurately capture the nonlinear characteristics of the carbon pricing, and machine learning methods need sophisticated artificial feature engineering. To successfully address these drawbacks, our research suggests a carbon price forecasting model built on a deep learning architecture. Complete Ensemble Empirical Mode Decomposition with Adaptive Noise decomposes historical price to obtain Intrinsic Mode Function and Principal Component Analysis reduces the dimensionality of each influential factor. Dual-Stage Attention-Based Recurrent Neural Network, a Seq2Seq model, made up of an encoder with feature attention and a decoder with temporal attention, is employed to predicted price of the Hubei Carbon Emissions Allowance. The dual-attention mechanism enables preprocessing to be done adaptively and more effectively than manual processing. As shown by statistical analysis and grey correlation analysis, Hubei Carbon Emissions Allowance has a high autocorrelation, and the carbon market, energy and industry, economy, and environment have high to low correlations on it. The accuracy metrics of this framework, Mean Absolute Error = 0.75, Mean Absolute Percentage Error = 1.59 and Root Mean Squared Error = 1.28, are lower than compared models.

From climate risk to the returns and volatility of energy assets and green bonds: A predictability analysis under various conditions

The importance of climate risk as a source of systemic risk for financial markets and the decisions of investors, portfolio managers, and regulators is growing. We examine the directional predictability from two climate risk measures, transition risk and physical risk, to the returns and volatility of European brown and green energy stocks, European carbon emission allowances, and global green bonds. Using daily data, we apply a cross-quantilogram approach in a time-varying setting to measure potential differences in the predictability across quantiles and over various crisis periods. The return predictability results are more pronounced for transition risk than physical risk, especially for brown energy stocks and carbon emission allowances, and they generally vary across periods and markets conditions. The predictability of volatility is also significant at specific time periods and volatility states, especially from transition risk, and the sign of the predictability is positive for brown energy and carbon emission allowances whereas it is negative for green bonds. We show that a lower-than-expected level of discussion about the transition process leads to a heightened volatility of brown energy markets. These findings have important implications regarding climate risks assessment on return and volatility predictability and climate risk and portfolio decarbonization under COP26.

Extreme weather raises the prices of regional emission allowances in China.

Extreme weather is an unexpected shock to the socioeconomic, which is likely to create climate risks in the process of global warming mitigation. The aim of this study is to investigate the impact of extreme weather on prices of China's regional emission allowances, by using the panel data of four representative pilots in China (Beijing, Guangdong, Hubei, and Shanghai) from April 2014 to December 2020. The overall findings reveal that extreme weather, especially extreme heat, has a short-term lagged positive impact on carbon prices. In particular, the specific performance of extreme weather under different conditions is as follows: (i) carbon prices in tertiary-dominated markets are more sensitive to extreme weather, (ii) extreme heat has a positive effect on carbon prices while extreme cold does not, and (iii) the positive impact of extreme weather on carbon market is significantly stronger during compliance periods. This study provides the decision-making basis for emission traders to avoid losses caused by market fluctuations.

A data driven robust optimization model for scheduling near-zero carbon emission power plant considering the wind power output uncertainties and electricity-carbon market

Under the carbon peak and neutrality targets, the power generation industry in China is facing an urgent demand for a low carbon transition and participation in the electricity-carbon market. This paper novelty proposes a near-zero carbon emission power plant (NZCEP) integrating gas turbines, wind turbines, power-to-gas and the carbon capture, utilization and storage system. And a two-stage Data-driven Set based robust optimization (DSRO) model, including a day-ahead dispatching phase and a real-time adjustment phase, is conducted to ensure the consumption of renewable energy resources and to develop the optimal operating strategy for NZCEP participation under the electricity-carbon market. The results demonstrated the following outcomes: (1) NZCEP shows better environmental benefits by reducing carbon emissions and consuming renewable energy resources. (2) the DSRO model can resist the interference of wind power output uncertainties and address the issue of traditional robust models being overly conservative. (3) under the electricity-carbon market, NZCEP shows better economic benefits, which can generate additional revenue from selling surplus carbon emission allowances (CEA). Moreover, when the annual average CEA price reaches 355 CNY/t, the NZCEP will achieve full capital cost recovery.

Carbon emission allowance allocation based on a bi-level multi-objective model in maritime shipping

To mitigate carbon emissions from maritime shipping, this study investigates the strategies and performance of allocating carbon emission allowances (CEAs) with the cap-and-trade mechanism among shipping companies. Using a bi-level model solved by the multi-objective particle swarm optimization algorithm based on Pareto solution set, the interactions between decisions of the government and shipping companies are well characterized. The results of the benchmark scenario indicate that all shipping companies’ optimal carbon emissions decrease annually during the planning period, and a larger company usually exhibits a better emission reduction performance. However, economic benefits of shipping companies and the society display an annually declining trend due to additional carbon emission reduction costs. The sensitivity analysis demonstrates that the decreasing carbon prices lead to more emissions, while the optimal total carbon emissions decrease as carbon reduction costs increase. These findings create implications for multiple stakeholders to formulate their own carbon emissions mitigation strategies under the cap-and-trade mechanism.

Exploring the Relationship between the EU Emissions Trading System and Renewable Energy Development in the EU

This research paper examines the impact of the EU Emissions Trading System (EU ETS) on the development of the renewable energy market in the European Union. Using regression analysis, the study investigates the relationship between the volume of emission permits, EU GDP, and the share of renewables in the overall energy balance. The results reveal that the EU ETS has a significant negative impact on the development of the renewable energy market in the EU, with an increase in the volume of emission permits corresponding to a decrease in the share of renewables. The study also finds that economic growth alone may not necessarily lead to an increase in the share of renewables; however, when combined with other policies and measures, economic growth may promote the development of renewable energy in the EU. The findings suggest that the EU ETS needs to be improved to encourage renewable energy development effectively, and policymakers should consider introducing additional policies and measures to promote the deployment of renewable energy. In addition to analysing the impact of the EU ETS on the renewable energy market, this paper provides an overview of the EU ETS and its challenges. As a cap-and-trade system covering over 11,000 installations across the European Economic Area, the EU ETS has faced challenges from the beginning due to an oversupply of emission allowances. This resulted in a low carbon price insufficient for driving climate change mitigation. To address these issues, the EU ETS Market Stability Reserve (MSR) was established to absorb excess allowances from the market and manage past surpluses. However, the MSR cannot handle sudden shocks or future surpluses. The paper also presents data on the distribution of emission allowances by country and sector. Germany has the most significant emissions under the EU ETS, followed by Italy, Poland, and the United Kingdom. The stationary installations sector, encompassing power plants and other large industrial emitters, received the most allowances, followed by the fuel combustion sector. The data indicates that energy and industry are the largest emitters and thus receive the most ETS allowances. This research contributes to the understanding of the EU ETS and its impact on the development of the renewable energy market in the EU. The results emphasise the need to improve the EU ETS to promote the deployment of renewable energy and suggest that policymakers should consider introducing additional policies and measures to facilitate the transition to a low-carbon economy.

Examining the Drivers of Natural Gas Price in Europe - Focus on the Role of Speculators

This paper examines the role of fundamentals and speculators for the price of natural gas market in Europe expressed in TTF front month index. The Granger causality test is used to investigate the relationship between variables determining supply and demand factors as well as activities of speculators expressed in futures TTF contracts held on ICE exchange, data reported by the European Securities and Markets Authority - ESMA. Existence of unidirectional granger causality was revealed running from prices of oil, temperatures towards prices of natural gas, bidirectional causality was found with prices of coal and emission allowance. No Granger causality was found between storages, PMI, positioning of speculators and natural gas price. Granger causality running from storages to speculators was identified. We concluded this indicates the market positioning of speculators is driven by fundamental factors and it is not the main factor driving the price of natural gas.

Relation of CO2 emission allowance prices and electricity prices in Poland in 2013-2020

This paper investigates the relation between the prices of CO2 emission allowances in the EU ETS (Emission Trading System), and wholesale prices of electricity in Poland. Linear regression models were used to assess carbon price pass-through rate to wholesale electricity prices during the entire III phase of ETS (2013-20). It has been found out that the entire cost of CO2 emission allowances was included in wholesale electricity price. As expected, the peak transmission parameter is higher than the off-peak one. Nevertheless the difference is small, and statistically insignificant, hence the model does not allow for any far-reaching conclusions in this regard. Results show, that electricity producers were able to pass the entire emission related costs to the customers, which might rise a question whether EU ETS is an effective tool to give sufficient incentives to decarbonise electricity production.

Self-Scheduling of a Generation Company with Carbon Emission Trading

A carbon emission trading self-scheduling (CETSS) model was proposed. The proposed model considered not only carbon emission allowance constraints but also carbon emission trading. A new method was presented for solving CETSS problems based on piece-wise linearisation and second-order cone linearisation. The effectiveness and validity of the proposed model and method were illustrated by 10-100 unit systems over 24 hours.

Optimal bidding strategy of a gas-fired power plant in interdependent low-carbon electricity and natural gas markets

This work presents a bi-level optimization framework to determine the optimal bidding strategies for a strategic gas-fired power plant, exerting market power in interdependent pool-based electricity and natural gas markets, under a carbon emission trading scheme (CETS). The upper-level problem aims at maximizing the profits of the strategic player, while at the lower-level problem, the day-ahead electricity and natural gas markets are cleared sequentially, considering the provision of carbon emission allowances for conventional power producers and high penetration of wind power generation. The bi-level formulation is initially recast into a mathematical program with equilibrium constraints (MPEC), using the Karush-Kuhn-Tucker optimality conditions and duality theory, and is further reformulated into a mixed integer linear program. The proposed algorithm is applied to a Pennsylvania-New Jersey-Maryland (PJM) 5-bus power grid, incurred by transmission constraints and a single node natural gas network. Numerical simulations provide CETS-embedded electricity clearing prices and optimal bidding decisions for the strategic gas-fired power plant, under plausible power transmission congestions and natural gas prices increment scenarios.

The EU emissions trading system and airline low-carbon transition: A game-theoretic approach

Aviation is among one of the fastest-growing sources of greenhouse gas emissions (GHG). Thus, transitioning into a more low-carbon approach for future sustainable growth in the airline industry is necessary. Inspired by European Union's GHG emissions trading system that allows automobile makers to “pool” their carbon emissions, we study three emission pooling scenarios for the airline industry. Under the EU emissions trading system (EU ETS), passenger and cargo airlines such as Lufthansa and FedEx can either (1) pay a premium for each ton of carbon dioxide equivalent (CO2eq) they fall short of free allowances (Pay Premium Strategy) or (2) buy allowances from other industries in the EU ETS market (Market-Based Strategy) (3) partnership with other airlines to “pool” their carbon emissions (Cooperative Strategy). These three approaches correspond to different market structures. The latest strategy has a co-opetition relationship between airlines: traditional airlines operating older aircraft purchase emission allowances from airlines operating newer aircraft. The purpose of this paper is to examine the conditions for airlines' paying penalties, purchasing allowances from the ETS market, or cooperation. We demonstrate that the EU ETS will always be detrimental to airlines using older aircraft. A hefty premium may effectively induce airlines to pursue a low-carbon transition plan. Our study shows that the ETS is not a silver bullet; it only works when the premium mechanism is designed properly and a fair market for emission allowances is available.

The Economics of Border Carbon Adjustment: Rationale and Impacts of Compensating for Carbon at the Border

International trade contributes directly to global greenhouse gas emissions, as the carbon content of high-emission products is priced differently in different countries. This phenomenon is termed carbon leakage. Thus, not putting a price on carbon is theoretically equivalent to an export subsidy, although that would be difficult to challenge in the context of multilateral trade law. Leakage can be alleviated by pricing the carbon embedded in imported products through a border carbon adjustment (BCA), be it a tax, a carbon tariff, or a regulation requiring the purchase of emissions allowances. The design of a BCA is a compromise between environmental effectiveness in preventing leakage, economic effectiveness in preserving competitiveness and ensuring acceptability, technical feasibility of the implementation, and World Trade Organization compatibility. An import-limited BCA is more effective than free emissions allowances in reducing leakage, but it does not preserve the export competitiveness of the country imposing it.

Deriving decarbonization targets and pathways – A case study for the automotive industry

Climate models and decarbonization scenarios use carbon budgets to distribute emission allowances and derive reduction targets for sectoral developments to limit global warming. These requirements are often not aligned with corporate climate targets due to missing targeting approaches for sectors and scopes as well as differences between absolute and intensity targets. Therefore, the aim of this paper is the development of an allocation scheme by combining frameworks for CO2eq accounting like the ISO 14040, the Greenhouse Gas Protocol and the IPCC Guidelines for inventory accounting to link sectoral carbon budgets to stages of product life cycles and vice versa. To calculate carbon budgets and reduction targets, a case study for the automotive industry is conducted. Consequently, average data sets of emission reporting, studies and LCAs for material compositions, forecasts on vehicles sales and the shares of electrified products are used. Depending on the applied decarbonization scenarios, different reduction trajectories aligned with pathways to limit global warming well below 2 °C and respectively to 1.5 °C are determined. As a result, the company has to reduce their absolute emissions from 2019 to 2030 by −25% to −46% equal to an intensity target of −32% to −51%.

The Eligibility of Green Bonds as Safe Haven Assets: A Systematic Review

This study follows Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) to examine the existing literature on the connectedness of green bonds with other markets as an attempt to highlight the effectiveness of green bonds in risk management and the benefits associated with incorporating green bonds in investment portfolios. An extensive search of relevant research papers to the scope of the review led to the identification of 31 articles published by February 2022. Our analysis traces the evolution of studies on green bonds’ interactions with other markets, the methodologies and data frequencies used for cross-market relations analysis, and the role of green bonds in portfolio risk management (diversifier, hedge, and safe-haven) in normal and extreme market conditions. The study reports several interesting findings. First, green bonds can be a strategic safe-haven avenue for investors in stocks, dirty energy stocks, and the foreign exchange market in the US and China in extreme market downturns. Second, green bonds demonstrated hedging properties against spillovers from Bitcoin, forex, soft commodities, and CO2 emission allowance. Third, the role of green bonds in the markets of natural gas, industrial metals, and crude oil is limited to a portfolio diversifier in different investment horizons. Fourth, green bonds had no diversification or hedge benefits for investors in conventional bonds. Fifth, the interrelationships between green bonds and most markets’ understudy were influenced by macroeconomic and global factors such as the COVID-19 pandemic, economic policy uncertainty, OVX, and VIX. Our review of the literature also facilitated identification of future research topics. The outcome of the review offers insightful information to investors in green bonds in risk management and assets allocation. Policy makers can benefit from this review in effective policy legislation for the advancement of the green bonds market and acceleration of a smooth transition to a net zero emission economy.

Data-Driven Internal Carbon Pricing Mechanism for Improving Wood Procurement in Integrated Energy and Material Production

More than 25% of the total energy consumption in Finland has been produced with wood fuels. Since 2012, the share has been greater than that of oil, coal, or natural gas. Internal carbon pricing is used to manage the risks in wood procurement after wood import from Russia ended. Further, the EU announced plans to sell more carbon emission permits to fund the EU’s exit from Russian energy. To manage these challenges, a data-driven internal carbon pricing mechanism (DDICPM) has been developed for wood procurement optimization. Particularly, local changes are considered via available information about growth-based carbon sinks (GBCS). The results of the new scenario were compared to the basic national scenario that ensures carbon neutrality in forestry. The DDICPM may provide the optimum wood-procurement operations maintaining carbon neutrality in the integrated energy and material industry (IEMI). In this study, the use of DDICPM increased profitability b 16.2, 16.1, and 16.0% between adapted wood procurement areas at the EU’s emission allowance prices of 30, 65, and 98 € t−1 CO2. The experiments’ results also revealed that the DDICPM could consistently and significantly outperform the conventional solution adopted by the company in terms of economic costs. A significant conclusion is that an increase in profitability is possible if the size of wood procurement areas is allowed to vary optimally with respect to transport distance to take advantage of the GBCS as a new application of the renewable carbon sink.

Closed-Loop Supply Chain Decision-Making and Coordination Considering Fairness Concerns under Carbon Neutral Rewards and Punishments

The cheap price of carbon sink trading in certification emission reduction (CER) makes it more popular than the carbon emission allowance (CEA); trading in carbon-neutral, enterprises are more inclined to purchase carbon sinks to achieve their own carbon neutrality goals and promote decarbonization of the whole chain. Companies urgently need to figure out how to achieve carbon neutrality with government rewards and punishments. Moreover, as an important factor affecting the effectiveness of supply chain, it is particularly important to study how to coordinate fairness concerns of such objects. Therefore, a centralized and two-stage Stackelberg game model of a closed-loop supply chain (CLSC) of one manufacturer and one retailer is constructed, and the cost-sharing contract, revenue-sharing contract, and cost–revenue-sharing contract are used to coordinate it, taking into account the fairness concerns of downstream enterprises while pursuing carbon neutrality, ensuring the overall benefits of the supply chain, and considering the impact of government subsidies and rewards and punishments on the carbon neutrality of the supply chain. Research shows that (1) compared with the other two contracts, the cost–revenue-sharing contract performs better and can effectively achieve the Pareto optimum; (2) the cost-sharing contract performs better in accomplishing the carbon neutrality of the CLSC; (3) excessively high carbon sink prices are not only detrimental to enterprise efficiency, but also to the realization of carbon neutrality goal; and (4) higher supply chain utility is pursued by enterprises when the unit reward and punishment are not great enough; otherwise, carbon neutrality is pursued. The research results can not only provide decision support for the product pricing, carbon sink reserve and contract design of CLSC enterprises under the goal of carbon neutrality, but can also provide a reference for the setting of government subsidies and rewards and punishment.

Environmental and Accounting Regulation: Lessons from The EU ETS

Environmental regulation potentially has a relevant role in reducing the negative effects of the firms’ economic activities on the environment and thus in improving firms’ environmental performance. However, environmental regulation can impose binding reduction targets of pollution, which can negatively affect firms' financial performance. Additionally, the institutional framework of the environmental regulation potentially affects the representation of firms’ environmental perfomance in their financial statements. Against this background, the purpose of this paper is two-fold. First, it aims to investigate the effectiveness of the European Union Emissions Trading Scheme (EU ETS) in promoting companies’ environmental and financial performance. Second, it aims to investigate how EU ETS affects the representation of environmental performance inside firms’ financial statements. To reach our aim, we follow two main stages of analysis. First, with descriptive statistics and archival data analysis, we investigate the effects of the EU ETS institutional framework on firms’ environmental and financial performance. Secondly, we develop a comparative analysis of the IAS/IFRS and Italian accounting standards concerning the recording of emission allowances. Our findings show that the EU ETS is a flexible regulation, which is effective at improving firms’ environmental performance and at safeguarding firms’ financial performance. Additionally, we find that under IAS/IFRS and Italian accounting standards, the environmental performance is included in the financial statements by recognizing the cost for polluting on an accrual basis.

Can green assets hedge against economic policy uncertainty? Evidence from China with portfolio implications

This paper examines whether green assets can hedge against economic policy uncertainty (EPU) via asymmetric time-varying connectedness and EGARCH models. Using daily data in China spanning from March 2014 to June 2022, we find that (1) an evident asymmetric connectedness exists between green assets and EPU. (2) Green bond, carbon emission allowances and some green stocks can act as hedging or safety-haven assets against EPU, and the conclusion remains robust to an alternative proxy of EPU. (3) The minimum variance and connectedness portfolios provide superior performance during pre- and post-COVID-19 periods, respectively, thereby carrying substantial portfolio implications.

Carbon allowance approach for capital-constrained supply chain under carbon emission allowance repurchase strategy

PurposeThe purpose of this study is to investigate which of the two carbon allowance allocation methods (CAAMs), i.e. grandfathered system carbon allowance allocation (GCAA) and baseline system carbon allowance allocation (BCAA), is more beneficial to capital-constrained supply chains under the carbon emission allowance repurchase strategy (CEARS).Design/methodology/approachAdopting CEARS to ease the capital-constrained supply chains, this study develops two-period game models with manufacturers as leaders and retailers as followers from the perspective of profit and social welfare maximization under two CAAMs (GCAA and BCAA), where the first period produces normal products, and the second period produces low-carbon products.FindingsFirst, higher carbon-saving can better use CEARS and achieve a higher supply chain profit under the two CAAMs. However, the higher the end-of-period carbon price is, the lower the social welfare is. Second, when carbon-saving is small, GCAA achieves both economic and environmental benefits; BCAA reduces carbon emissions at the expense of economic benefit. Third, the supply chain members gain higher profits and social welfare under GCAA, so the government and supply chain members are more inclined to choose GCAA.Originality/valueBy analyzing the profits and total carbon emissions of capital-constrained supply chains under GCAA and BCAA, this study provides theoretical references for retailers and capital-constrained manufacturers. In addition, by comparing the difference in social welfare under GCAA and BCAA, it provides a basis for the government to choose a reasonable CAAM.

Research on the pricing strategy of park electric vehicle agent considering carbon trading

The large-scale use of electric vehicles provides the strong support for the realization of the decarbonization in the energy sectors. With the maturity of the carbon trading market, a large number of decentralized electric vehicles play an important role in the carbon market because of their zero emission characteristics. However, how the decentralized electric vehicles participate in the carbon market is a challenge in the present world. For the purpose of reducing the load peak-valley difference and guiding a large number of electric vehicles in the park to charge in an orderly manner, we put forward a pricing strategy for the park electric vehicle agent under the background of “carbon peaking and carbon neutralization”. A two-level Stackelberg game model is developed, in which the upper level maximizes the profits of park electric vehicle agent and the lower level minimizes the charging cost of the electric vehicle owners. The park electric vehicle agent participates in the carbon market by selling the carbon emission allowances owned by electric vehicles in the park to obtain subsidies and increase profits. The optimal pricing strategy of the electric vehicle agent can effectively guide the decentralized electric vehicle users in the park to participate in the electricity and carbon market transactions and reduce the peak-valley load difference. The commercial solver CPLEX based on YALMIP is used to solve the model, and a case study is given to verify the feasibility and validity of the proposed scheme.