Emission Allowances Research Articles

Production of Hydrogen from Biomass with Negative CO2 Emissions Using a Commercial-Scale Fluidized Bed Gasifier

Biomass gasification, as a thermochemical method, has attracted interest due to the growing popularity of biofuel production using syngas or pure hydrogen. Additionally, this hydrogen production method, when integrated with CO2 capture, may have negative CO2 emissions, which makes this process competitive with electrolysis and coal gasification. This article presents the results of process and economic analyses of a hydrogen production system integrated with a commercial, fluidized-bed solid fuel gasification reactor (SES technology—Synthesis Energy Systems). With the use of a single gasification unit with a capacity of 60 t/h of raw biomass, the system produces between 72.5 and 78.4 t/d of hydrogen depending on the configuration considered. Additionally, assuming the CO2 emission neutrality of biomass processing, the application of CO2 capture leads to negative CO2 emissions. This allows for obtaining additional revenue from the sale of CO2 emission allowances, which can significantly reduce the costs of hydrogen production. In this analysis, the breakthrough price for CO2 emissions, above which the hydrogen production costs are negative, is USD 240/t CO2.

Carbon emission allowance, global climate risk, and agricultural futures: An extreme spillover analysis in China

The aim of this paper is to investigate the extreme spillover effects between the newly launched China's national carbon emission allowance and agricultural futures markets with the influence of global climate risk. The results show that, first, under both normal and extreme market (climate risk) conditions, the three edible oil futures, i.e., soybean oil, palm oil and rapeseed oil, are strong spillover senders to other agricultural futures. Second, under low and normal climate risk states, climate transition risk is a spillover transmitter, while under high climate risk states, climate physical risk becomes a spillover sender. In addition, the network analysis shows that climate risk is an important information receiving and disseminating node, and large changes in it can lead to increased systemic risk across the network. Finally, China's carbon emission allowance market is always a spillover receiver across different market (climate risk) conditions, and can be used as an appropriate hedging instrument for climate risk and agricultural futures. These findings have valuable implications for both policymakers and agricultural investors.

Contemporaneous and lagged spillovers between agriculture, crude oil, carbon emission allowance, and climate change

In this paper, we examine the contemporaneous and lagged spillovers among the agricultural, crude oil, carbon emission allowance, and climate change markets. Adopting the R2 decomposed connectedness approach, our empirical analysis reveals several key findings. First, the overall total connectedness index (TCI) dynamics have been mainly dominated by contemporaneous effects. Second, there are heterogeneous spillover effects among agricultural markets. Specially, corn, soybean meal, and wheat are the major risk transmitters to this system, while barley, cocoa, and lean hog are the main risk receivers of shocks. Third, we also find that climate change has significant spillovers to other markets.

A Novel Centralized Allocation Data Envelopment Analysis Model for Carbon Emission Allocation Under a Heterogeneous Abatement Cost: Application Within the Chinese Industrial Sector

This paper presents a mathematical approach to analyzing carbon abatement costs and the allocation of carbon emission allowances in China’s industrial sectors. We utilize input–output data from 30 Chinese provinces between 2009 and 2018 to estimate carbon abatement costs by applying the slack-based measure (SBM) efficiency model and its dual form. The SBM model captures inefficiencies and offers a rigorous framework for measuring abatement costs. Using these costs, we develop a centralized allocation data envelopment analysis (DEA) model, which maximizes sectoral benefits through optimal reallocation. This DEA model is formalized as a linear programming problem, with the aim of determining the efficient allocations of carbon allowances while maintaining the system’s economic productivity. Furthermore, we construct intertemporal, interregional, and spatiotemporal allocation DEA models to examine the dynamics of carbon emission allowance allocation over time, space, and combined spatiotemporal dimensions. These models offer insights into the efficiency of carbon markets under varying conditions. Our proposed new mathematical formulations reveal optimal allocation strategies that can balance emission reductions with industrial productivity. This study also provides novel mathematical frameworks for analyzing the carbon allowance distribution and contributions to both the theory and application of mathematical optimization in environmental policy design. Our findings reveal that China’s industrial carbon abatement costs exhibit significant interprovincial and regional differences. Developed provinces with higher levels of industrial development have higher carbon abatement costs, while provinces with less-developed industrial sectors have lower costs. Under the interregional allocation scenario of carbon emission allowances that consider abatement costs, developed provinces have smaller industrial carbon emission reductions, whereas less-developed provinces have larger reductions. In the intertemporal allocation scenario, provinces with larger industrial economies face greater emission reduction tasks. Under the combined interregional and intertemporal allocation scenario, industrial sectors in coastal developed provinces have lower carbon emission reductions, while those in inland less-developed provinces have higher reductions, mirroring the spatial allocation results of carbon emission allowances.

Allocation or Skill? What is Driving Corporate Trading Performance in the EU ETS?

This study empirically analyzes factors related to companies’ profits from trading emission allowances in the European Union Emissions Trading System (EU ETS) for the period from 2005 to 2017 by combining information on trading activities with company characteristics of more than 6,000 companies. The factors considered include net position (i.e., free allocation of allowances minus emissions), strategic skills (i.e., banking of allowances, timing of trading, transaction frequency, use of intermediaries), skill-related structural factors (i.e., number of installations, sector affiliation), market pressure, year, and region effects. The results from estimating a Panel Heckman Selection Model suggest that companies’ profits from buying and selling emission allowances are related to a company’s net position, banking of allowances, timing of trading, and the number of installations. The findings further indicate that companies choose the number of banked allowances efficiently, that is, they take into account the opportunity costs of selling these allowances on the market. JEL Classification: Q48, Q54, Q58

Research on the Correlation Between Carbon Emission Rights and Energy Market: A Case Study of EUA and Oil Market

This study focuses on the importance of the relationship between carbon and oil in the context of global climate change and energy transition. In particular, this paper explores the link between fluctuations in the price of Brent crude oil in the United Kingdom and changes in the European Union Emission Allowances (EUA), which has significant implications for insight into energy market dynamics and policy making. This study uses an autoregressive (VAR) model to analyze the dynamic relationship between the European Union Emission allowances (EUA) market and the oil market from 2018 to 2024. Through Augmented Dickey-Fuller (ADF) stability test, the VAR model is established, the optimal lag order is determined, and the impulse response and Variance decomposition are analyzed. The results show that the EUA market has a short-term positive impact on the response of the oil market. But this effect has diminished over time, indicating the market's ability to self-regulate and stabilize. These findings provide new perspectives for understanding the interaction between global energy markets and environmental policy tools. The findings highlight the importance of considering these market dynamics when developing market strategies and environmental policies.

Carbon disclosures and information asymmetry: Empirical evidence on the importance of text in understanding numerical emission allowance disclosures

AbstractCarbon disclosures are essential for investors to evaluate firms’ efforts to combat climate change. In this study, we focus on a specific type of carbon disclosures—namely, emission allowance disclosures—that capture how firms implement emission reductions under the European Union emission trading system (EU ETS). Given the continuously changing institutional features of the EU ETS and the lack of authoritative guidance on how firms should account for emission allowances in their financial statements, it is exceedingly difficult for investors to understand numerical emission allowance disclosures and to compare them across—and even within—firms. Motivated by this criticism, we hypothesize and find that textual disclosures complementing numerical emission allowance disclosures are associated with lower information asymmetries between firms and their investors. Further analyses show that textual disclosures that: (i) describe the accounting approach, and (ii) contain institutional information on the EU ETS, respectively, are particularly important for improving the information environment of numerical emission allowance disclosures. Overall, our findings suggest that text can improve the understanding of numbers in a carbon disclosure context. Therefore, our study not only contributes to the (industrial ecology) literature but also has important implications for regulators, policymakers, investors, financial analysts, and firms.

Carbon emission reduction dynamic decision-making in the electricity supply chain with different carbon emission allowance principles

To address the impacts of typical principles for allocating initial carbon emission allowance, namely, the grandfathering and benchmarking principles on long-term emission reduction strategies, this paper presents four differential game models for an electricity supply chain consisting of a single electricity supplier and a single electricity retailer. The equilibrium solutions for different models are obtained and comparatively analyzed. The results show that the power supplier exhibits greater emission reduction efforts and, therefore, that the retailer has higher profits under the benchmarking principle than under the grandfathering principle. Moreover, under the two principles, the level of the power supplier’s emission reduction efforts is related to the decision-making modes of the electricity supply chain. Under specific conditions, the power supplier’s profit is also higher under the benchmarking principle than under the grandfathering principle. In addition, this study extends the models to investigate the constrained differential game models and obtains the game equilibrium solutions, which can be proved as saddle point equilibria.

Extreme time-frequency connectedness between energy sector markets and financial markets

The renewable energy market has developed into a distinct asset class that has garnered significant attention from investors worldwide. This study investigates the connectedness between the S&P 500 and various energy sectors, including the Green Bond (Green Bond), S&P GSCI Carbon Emission Allowances Index (GSCI EUA), S&P GSCI Biofuel (GSCI Biofuel), and S&P Global Clean Energy Indices (Global Clean Energy). Combining the quantile connectedness approach of Ando et al. (2022) and the spillover index developed by Chatziantoniou et al. (2022), we investigate the quantile time-frequency connectedness among these markets. Our findings reveal that the impact of tail risk spreading to the energy sector during extremely challenging market conditions is significantly amplified. Most tail risk spillovers between the energy sectors involve short-term risk spillovers, as seen by analyzing the frequency domain. The impact of tail risk spillover is stronger during extreme situations, showing a short-term asymmetry. Global Clean Energy and the S&P 500 play important roles in spreading risk to other sectors, known as tail risk spillover. They add to the overall risk that affects the network system. On the other hand, other energy sectors (GSCI EUA and GSCI Biofuel) as well as green bonds act as net recipients by receiving the risk rather than spreading it further, potentially providing portfolio diversification. It is essential to understand how these key players influence risk in the financial system. Utilizing a variety of techniques to assess portfolio performance shows the importance of understanding the return transmission mechanism in the process of developing a portfolio and suggests that Clean Energy, given its relative independence, may make an excellent diversification investment.

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.

Allocating inter-provincial CEA in China based on the utility perspective --a method for improving the variable weight function

Introduction:At different times, China has pursued different carbon emission reduction targets, so it is crucial to develop a reasonable and flexible allocation scheme for Chinese carbon emissions quotas, referred to as Chinese Emission Allowance (CEA), in order to achieve carbon reduction goals. As important responsible entities for carbon reduction, each province needs to rely on a well-designed CEA allocation scheme to help achieve their emission reduction goals.Methods:Therefore, based on the utility perspective, this paper constructs allocation principles and methods to formulate the inter-provincial CEA allocation scheme for China in 2030. Specifically, the entropy method, SBM model, improved variable weight function, and ARIMA time series model are sequentially adopted to simulate the re-allocation scheme, examine its rationality, and develop CEA allocation schemes under different principles.Results and Discussion:The following conclusions are drawn: 1) The allocation scheme formulated based on historical emission simulation methods, industry benchmark methods, and other current CEA allocation methods has certain irrationality, and future CEA allocation should not follow the original methods; 2) The improved variable weight function is better suited for allocation in CEA than the current original allocation method. The allocation scheme developed under this method, which balances fairness and efficiency principles, is more appropriate for the actual reduction of carbon emissions in China.

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.

Carbon emission constraint: A catalyst for the shift from real economy to financialization?

AbstractThe goals of carbon peak and carbon neutrality have gained significant attention in China. Carbon‐intensive corporates are tasked with decoupling economic growth from carbon emissions. This research examines their potential for financialization based on the compulsory fulfillment requirement of carbon emission allowances and the emission‐free characteristics of financial assets. This research finds that carbon emission policy significantly promotes corporates to allocate more capital toward business operations in the real economy. It leads to an increase in capacity utilization efficiency and profitability for the main business. The findings support that the policy has a positive impact on the real economy.

Global primary aluminum smelters' CO2 mitigation potential and targeted carbon-neutral pathways

The expansion of aluminum smelter capacity generates high CO2 emissions, exhibiting spatiotemporal diversity due to diverse processing routes and technologies. Despite extensive discussions on macro abatement options, facility-specific mitigation potentials and decarbonization strategies remain unclear, which cumulatively affects the progress towards global 1.5 °C and 2 °C warming control targets. This study develops a carbon footprint inventory of 163 primary aluminum smelters in 2022 and analyzes current emission structures concerning location, age, production, and input-output. Then adjust available technologies and efficiencies to match global plant-level decarbonization routes. The potential contributions of each strategy are finally quantified, accounting for significant geographic variations in emissions, thereby supplementing tailored technology transformation pathways for smelters across nine focus regions. The results show that: (1) Young smelters, predominantly in developing regions, are crucial for abatement. Rapid retrofits ahead could save CO2 budgets by 0.6–28.56 Gt, potentially delaying excess emissions under climate targets, particularly with comprehensive retrofits. (2) The paramount technical retrofitting for carbon neutrality differs regionally and evolves. Smelters in developing countries should prioritize renewable energy investment in the immediate future, succeeded by the optimization of power generation infrastructures. To liberate more emission allowances, developed countries ought to contemplate the decommissioning of aged smelters or upgrading through emerging supply-side technologies. (3) Available retrofits can facilitate the aluminum industry's contribution to the 2 °C climate target, whereas addressing the 1.5 °C target will necessitate the adoption of more innovative technologies and materials. This paper endeavors to assist global and regional smelters in developing more targeted decarbonization pathways.

China’s carbon emission allowance prices forecasting and option designing in uncertain environment

China’s carbon emission allowance prices forecasting and option designing in uncertain environment

Carbon emission allowances and Nordic electricity markets: Linkages and hedging analysis

Unlike previous studies which tend to consider only return linkages between European emission allowances and electricity markets, this paper examines return and volatility linkages between the two markets and importantly conducts a hedging analysis. Using a dynamic conditional correlation model and daily price data covering European emission allowances and Nord Pool electricity markets from 28th January 2009 to 22th February 2022, which comprise the second and third phases of the European emission allowances trading system, the main results are summarized as follows: Firstly, volatility and returns flow from the Nordic electricity market to the European emission market, with no evidence of a feedback effect, suggesting that rapid changes in demand for electricity may have forced producers to ramp up carbon-intensive facilities. Secondly, the conditional dynamic correlation between the two markets is weak but varies with time, and its sensitivity to crisis periods is noted. Thirdly, the hedging analysis indicates that Nordic electricity market participants can lower their downside risk by including carbon emission allowances in their portfolios, as evidenced by the effectiveness of hedging returns of the Nordic electricity markets with European allowances, irrespective of the COVID-19 sub-periods.

Carbon Price Forecasting Using Optimized Sliding Window Empirical Wavelet Transform and Gated Recurrent Unit Network to Mitigate Data Leakage

Precise forecasts of carbon prices are crucial for reducing greenhouse gas emissions and promoting sustainable, low-carbon development. To mitigate noise interference in carbon price data, hybrid models integrating data decomposition techniques are commonly utilized. However, it has been observed that the improper utilization of data decomposition techniques can lead to data leakage, thereby invalidating the model’s practical applicability. This study introduces a leakage-free hybrid model for carbon price forecasting based on the sliding window empirical wavelet transform (SWEWT) algorithm and the gated recurrent unit (GRU) network. First, the carbon price data are sampled using a sliding window approach and then decomposed into more stable and regular subcomponents through the EWT algorithm. By exclusively employing the data from the end of the window as input, the proposed method can effectively mitigate the risk of data leakage. Subsequently, the input data are passed into a multi-layer GRU model to extract patterns and features from the carbon price data. Finally, the optimized hybrid model is obtained by iteratively optimizing the hyperparameters of the model using the tree-structured Parzen estimator (TPE) algorithm, and the final prediction results are generated by the model. When used to forecast the closing price of the Guangdong Carbon Emission Allowance (GDEA) for the last nine years, the proposed hybrid model achieves outstanding performance with an R2 value of 0.969, significantly outperforming other structural variants. Furthermore, comparative experiments from various perspectives have validated the model’s structural rationality, practical applicability, and generalization capability, confirming that the proposed framework is a reliable choice for carbon price forecasting.

Extreme co-movements between CO2 emission allowances and commodity markets and their response to economic policy uncertainty

This study employs the generalized extreme value - autoregressive conditional Fréchet - tail quotient correlation coefficient (GEV-AcF-TQCC) analytical framework to investigate the extreme co-movements between the EU carbon futures market and the commodity futures market. Subsequently, it also examines the response of the dynamic tail quotient correlation coefficient (TQCC) values to economic policy uncertainty stemming from the US using the linear Granger causality test. The empirical results demonstrate that the tail risk indices for both upside and downside trends of the two futures markets experience changes most of the time and show drastic changes during extreme events. More importantly, before the outbreaks of the COVID-19 pandemic (from September 2019 to February 2020) and the Russia-Ukraine conflict (from May 2021 to February 2022), the dynamic TQCC values for the downside trends of the two futures markets remain at relatively high levels. Of note, when examining the dynamic TQCC values between GSCI_down and EUA_down, as well as between GSCI_down and EUA_up, it can be observed that these TQCC values rise to higher levels during periods of extreme volatility. However, they quickly decline as the GSCI futures market experiences significant fluctuations during its downside trend. This pattern indicates a tail risk spillover effect from the GSCI futures market to the EUA futures market. Further analysis using the linear Granger causality test reveals that economic policy uncertainty is a significant driver of the extreme co-movements between the EU carbon and the commodity futures markets in most cases, in addition to the extreme co-movements between the downside trend of the EU carbon futures market and the upside trend of the commodity futures market. The insights gained from this study can provide valuable guidance and enlightenment for policymakers, financial investors, and academic researchers in understanding the dynamics of the extreme relationship between the two markets under discussion, and the impacts of economic policy uncertainty on their extreme co-movements.

The Effectiveness of the EU ETS Policy in Changing the Energy Mix in Selected European Countries

In the field of economic analysis, the study of the EU ETS policy has primarily focused on the impact of renewable energy consumption on economic growth, as well as the role of legal and fiscal instruments in the development of clean energy. This study aimed to evaluate the effectiveness of the EU ETS policy in altering the energy mix of selected European countries, providing both cognitive and applicational value. The evaluation of the effectiveness of this policy focused on the structure of the energy mix and the relationship between rising CO2 emission allowance prices and the decreasing share of coal in the energy mix. The goal was achieved through statistical analysis of secondary sources, primarily sourced from Bloomberg (2016–2024). The research findings indicated that changes in the structure of energy sources varied across the studied European countries, due to the adopted energy source utilization strategy, resource availability, and geopolitical situations. Additionally, different correlation values were noted between rising CO2 emission allowance prices and the expected reduction in fossil fuel use. Therefore, the EU ETS policy does not fulfill its assigned role—its implementation contributes to disparities in the economic situations of European economies and creates conditions for unequal competition.

Cooperative operation for multiple virtual power plants considering energy-carbon trading: A Nash bargaining model

With the development of the energy and carbon markets, it has become a trend for multiple virtual power plants (MVPP) that aggregate distributed resources from different regions to participate in market trading through cooperative operation. In order to study the energy-carbon interactions between VPPs and the supply-demand interactions for MVPP and users, this paper introduces a load aggregator (LA) and establishes a cooperative alliance consisting of MVPP and LA. Firstly, a carbon emission allowance allocation and transaction mechanism for MVPP is proposed based on the modified Shapley value method, which considers the impact of energy interactions within the alliance on the carbon emissions. Then, a cooperation model for the MVPP-LA alliance is established based on Nash bargaining theory, and it is decomposed into two subproblems of the maximal alliance benefits and the optimal benefit distribution. In terms of benefit distribution, this paper modifies the bargaining mechanism based on the contribution of each VPP to the alliance benefit. A dynamic penalty factor-based alternating direction method of multipliers (DP-ADMM) is used to solve the two subproblems in a distributed manner. Finally, the validity of the proposed trading mechanism, allocation method and solution algorithm are verified through several cases.