Allowance Prices Research Articles

Heterogeneous response of the stock market to CO2 emissions in China

CO2 emissions have been a great challenge in China, especially in recent years. Meanwhile, the CO2 emissions allowance price cannot accurately reflect the CO2 emissions information in China because of the limited efficiency in China’s carbon market. Accordingly, this study constructs a CO2 emissions index and provides an empirical investigation of the heterogeneous response of stock markets to CO2 emissions. With a quantile regression approach, we document that the effect of CO2 emissions on stock returns is significant in 2021, while it is insignificant in 2019 and 2020. In addition, its influence is more significant at the upper and lower quantiles than at the median quantile. Our findings indicate that investors and the government should pay more attention to carbon risk in the future and under extreme market conditions.

Efficiency of Polish Energy Companies in the Context of EU Climate Policy

The purpose of this article is to assess the impact of carbon allowances on the financial performance and strategic behavior of Polish energy companies listed on the Warsaw Stock Exchange, with a particular focus on the period when the price of these allowances increased. The eight largest Polish energy companies were surveyed, and the research period covered the period of 2010–2021. The research process used an analysis of financial condition and its determinants in the current and long-term perspective. In the current approach, the following were used: sales margin, operating margin, and cost and revenue structure. In the long-term approach, an assessment of the regularity of the capital structure and debt ratios was used. In both research perspectives, the results were confronted with the structure of power generation sources and the segmentation of the core business, including production, distribution, and trading. The results allow us to conclude that the increase in the price of emission allowances has adversely and most strongly affected companies focused on energy generation from high-carbon sources.

Optimal reduction and equilibrium carbon allowance price for the thermal power industry under China’s peak carbon emissions target

As the largest source of carbon emissions in China, the thermal power industry is the only emission-controlled industry in the first national carbon market compliance cycle. Its conversion to clean-energy generation technologies is also an important means of reducing CO2 emissions and achieving the carbon peak and carbon neutral commitments. This study used fractional Brownian motion to describe the energy-switching cost and constructed a stochastic optimization model on carbon allowance (CA) trading volume and emission-reduction strategy during compliance period with the Hurst exponent and volatility coefficient in the model estimated. We defined the optimal compliance cost of thermal power enterprises as the form of the unique solution of the Hamilton–Jacobi–Bellman equation by combining the dynamic optimization principle and the fractional Itô’s formula. In this manner, we obtained the models for optimal emission reduction and equilibrium CA price. Our numerical analysis revealed that, within a compliance period of 2021–2030, the optimal reductions and desired equilibrium prices of CAs changed concurrently, with an increasing trend annually in different peak-year scenarios. Furthermore, sensitivity analysis revealed that the energy price indirectly affected the equilibrium CA price by influencing the Hurst exponent, the depreciation rate positively impacted the CA price, and increasing the initial CA reduced the optimal reduction and the CA price. Our findings can be used to develop optimal emission-reduction strategies for thermal power enterprises and carbon pricing in the carbon market.

Risk Spillover Effect and Trading Strategy between Carbon Emission Allowance and Carbon-Neutral Index

An index based on the carbon-neutral concept stock pool is built, and GARCH-dynamic Copula-CoVaR is used to study the risk spillover effect between the carbon market and the carbon-neutral index. The results show as follows. 1) There is a bi-directional risk spillover between the national carbon emission allowance market and the carbon-neutral index, and the positive correlation is becoming increasingly significant. 2) The correlation between the local carbon market and the carbon-neutral index is weak, and there is an asymmetric risk spillover relationship between them: the former can have a one-way risk impact on the latter. 3) In general, the carbon-neutral index is a net risk receiver, and carbon-neutral concept enterprises face the risk of carbon emission allowance price fluctuation in the process of green transformation. In addition, drawing on the research ideas existed, appropriate “brown assets” and “green assets” in the carbon market and stock market are found, and trading strategies including hedging and pair trading are designed, providing new ideas for investors’ asset allocation.

Sustainability, emission trading system and carbon leakage: An approach based on neural networks and multicriteria analysis

Two transitions, green and digital, are changing the operations and strategies of industrial systems. At the same time, businesses are challenged to be globally competitive. Europe has a very ambitious agenda as it aims to be the first climate-neutral continent in 2050. The european emissions trading scheme (EU ETS) has proven to have facilitated the reduction of significant amounts of greenhouse gas emissions, but the risk of carbon leakage is present. This work seeks to explore these issues and their relationships. Through the use of a long short-term memory (LSTM) neural network, a model is built to determine the price of european union allowance (EUA) as a function of different financial energy futures. The results show that the model is very robust and the EUA tends to vary between 78 and 91 €/tCO2. In addition, a multi-criteria decision analysis (MCDA) is applied to identify the best policy alternatives to enable businesses subject to the EU ETS to be competitive in global markets. The analysis is carried out with the help of academic and industrial experts and it emerges that the criteria considered most relevant are two: (i) public expenditure and its expected benefits and (ii) the industrial ecosystem. The policy implications identify that bonuses should be provided to businesses for innovative solutions that protect both the energy and raw material components. The framework of the 3E (Energy Efficiency, Renewable Energy, and Circular Economy) are critical to businesses' long-term strategies, flanked by digital development.

Exploring the link between the EU emissions trading system and net-zero emission neighbourhoods

Climate policy is transforming the energy system and the building sector. Since these sectors overlap, we need to understand how the short-term operational link between them impact their long-term development subject to overlapping climate policies. This paper investigates how the integrated development of the European heat and electricity system is influenced by net-zero emission neighbourhoods that compensate own carbon emissions with local renewable energy. The study is made in the context of EUs emission trading system. In our approach, we soft-link two mathematical programming models to couple energy transition policies at the European level with the neighbourhood scale. Results suggest that zero emission neighbourhoods make European decarbonisation more cost-efficient. When low carbon energy technologies in neighbourhoods become competitive, investments in large-scale technologies are reduced on the European level, including nuclear and fossil gas power and heating. Thus, early policy support to neighbourhood technologies could prevent stranded assets later in the transition. Further, results imply that more stringent emission caps earlier could help avoiding CO2 allowance price spikes later.

Valuation of Ecosystem Services Based on EU Carbon Allowances-Optimal Recovery for a Coal Mining Area.

This paper presents a new way of valuing ecosystem services based on the price of EU carbon dioxide emission allowances. Its main advantage is that it facilitates the monetisation of non-provisioning ecosystem services, which is the Achilles heel of current frameworks. The research approach is built on the notion that land rehabilitation and ecological restoration involve trade-offs between ecosystem services. A quantitative assessment (valuation) of these trade-offs is necessary to make sound decisions. However, using different valuation methods to estimate monetary values creates a non-comparability in the valuation process that is difficult to correct. To address this problem, in the first place, the propagation of imprecise preference statements in hierarchical weighting is proposed, avoiding the non-comparability caused by the different current approaches while reducing the effort of preference elicitation. In the second place, to achieve consistency, monetisation of all non-provisioning ecosystem services was carried on the above comparison and the monetary valuation of the attribute with the most direct and market-related valuation possible: carbon sequestration, using the EU Emissions Trading System. A former coal mining area exemplifies the valuation of ecosystem services provided by alternative ecological restoration scenarios. The aim is to estimate their contribution to human well-being, understand the incentives faced by decision makers to manage ecosystems in different ways and assess the values of alternative solutions. An exercise is then carried out to show that the price of EU carbon permits (as of December 2021) after the price escalation that coincides with phase 4 of the allocation of allowances under the EU Emissions Trading System can be estimated by prioritising biodiversity over other ecosystem services.

Merging Climate Action with Energy Security through CCS—A Multi-Disciplinary Framework for Assessment

Combining biomass-fired power generation with CO2 capture and storage leads to so-called negative CO2 emissions. Negative CO2 emissions can already be obtained when coal is co-fired with biomass in a power plant with CCS technology. The need for bioenergy with CO2 capture and storage has been identified as one of the key technologies to keep global warming below 2 °C, as this is one of the large-scale technologies that can remove CO2 from the atmosphere. According to the definition of bioenergy with CO2 capture and storage, capturing and storing the CO2 originating from biomass, along with the biomass binding with carbon from the atmosphere as it grows, will result in net removal of CO2 from the atmosphere. Another technology option for CO2 removal from the atmosphere is direct air capture. The idea of a net carbon balance for different systems (including bioenergy with CO2 capture and storage, and direct air capture) has been presented in the literature. This paper gives a background on carbon dioxide removal solutions—with a focus on ecology, economy, and policy-relevant distinctions in technology. As presented in this paper, the bioenergy with CO2 capture and storage is superior to direct air capture for countries like Poland in terms of ecological impact. This is mainly due to the electricity generation mix structure (highly dependent on fossil fuels), which shifts the CO2 emissions to upstream processes, and relatively the low environmental burden for biomass acquisition. Nevertheless, the depletion of non-renewable natural resources for newly built bioenergy power plant with CO2 capture and storage, and direct air capture with surplus wind energy, has a similar impact below 0.5 GJ3x/t of negative CO2 emissions. When the economic factors are a concern, the use of bioenergy with CO2 capture and storage provides an economic justification at current CO2 emission allowance prices of around 90 EUR/t CO2. Conversely, for direct air capture to be viable, the cost would need to be from 3 to 4.5 times higher.

Review of Closed SCO2 and Semi-Closed Oxy–Fuel Combustion Power Cycles for Multi-Scale Power Generation in Terms of Energy, Ecology and Economic Efficiency

Today, with the increases in organic fuel prices and growing legislative restrictions aimed at increasing environmental safety and reducing our carbon footprint, the task of increasing thermal power plant efficiency is becoming more and more topical. Transforming combusting fuel thermal energy into electric power more efficiently will allow the reduction of the fuel cost fraction in the cost structure and decrease harmful emissions, especially greenhouse gases, as less fuel will be consumed. There are traditional ways of improving thermal power plant energy efficiency: increasing turbine inlet temperature and utilizing exhaust heat. An alternative way to improve energy efficiency is the use of supercritical CO2 power cycles, which have a number of advantages over traditional ones due to carbon dioxide’s thermophysical properties. In particular, the use of carbon dioxide allows increasing efficiency by reducing compression and friction losses in the wheel spaces of the turbines; in addition, it is known that CO2 turbomachinery has smaller dimensions compared to traditional steam and gas turbines of similar capacity. Furthermore, semi-closed oxy–fuel combustion power cycles can reduce greenhouse gases emissions by many times; at the same time, they have characteristics of efficiency and specific capital costs comparable with traditional cycles. Given the high volatility of fuel prices, as well as the rising prices of carbon dioxide emission allowances, changes in efficiency, capital costs and specific greenhouse gas emissions can lead to a change in the cost of electricity generation. In this paper, key closed and semi-closed supercritical CO2 combustion power cycles and their promising modifications are considered from the point of view of energy, economic and environmental efficiency; the cycles that are optimal in terms of technical and economic characteristics are identified among those considered.

The role of output-based emission trading system in the decarbonization of China's power sector

The emission trading system (ETS) is a key policy for China to achieve carbon neutrality. China's national ETS started operation and covered the power sector first, which will promote its transformation. This study explores how China's national ETS can support the future decarbonization of the power system. With benchmark tightening, China's ETS can cost-effectively peak CO2 emissions of the power sector before 2030 and reduce 13% of the total emissions by 2035, compared to a No-Carbon-Pricing Scenario. Under the ETS, the allowance price would rise gradually to 350 yuan/tCO2 by 2035. The main driving factor for emissions reduction would be improving the efficiency of coal-fired power generation between 2020 and 2025 and deploying carbon capture and storage (CCS) from 2030, respectively. Fuel-switching away from coal is limited under the ETS with technology-specific benchmarks and free allocation. Regional distributional effects could arise under the ETS. Regions with a higher share of ultra-supercritical units could have allowance surpluses at the beginning, while only regions with CCS-equipped coal-fired units have the potential to gain high allowance surpluses by 2035.

Modeling volatility and dependence of European carbon and energy prices

We study the prices of European Emission Allowances (EUA), whereby we analyze their uncertainty and dependencies on related energy prices (natural gas, coal, and oil). We propose a probabilistic multivariate conditional time series model with a VECM-Copula-GARCH structure which exploits key characteristics of the data. Data are normalized with respect to inflation and carbon emissions to allow for proper cross-series evaluation. The forecasting performance is evaluated in an extensive rolling-window forecasting study, covering eight years out-of-sample. We discuss our findings for both levels- and log-transformed data, focusing on time-varying correlations, and in view of the Russian invasion of Ukraine.

CO2 price effects on the electricity market and greenhouse gas emissions levels: an application to the Spanish market

This research proposes an empirical method to estimate the impact on the wholesale electricity market of an increase in the price of CO2 emission allowances. The current literature in this field is mainly focused on long-term simulation analyses, while this study carries out a short-term analysis with microdata from the electricity market. A higher price of CO2 implies an increase in the electricity generation costs of polluting units and therefore an increase in the price of the electricity market. When CO2 becomes more expensive, polluting electricity generators are shifted in the hourly electricity supply curve towards less competitive positions (in favour of less polluting/cheaper units). Displaced polluting units could even be taken out of the market, which would imply a reduction in CO2 emissions. These short-term movements can be reproduced with our microdata of the day-ahead electricity market –data Provided by the Spanish Market Operator (OMIE). According to our results, increases in the carbon price of 10, 20, or 30 € per ton, respectively, cause increases of 1.8%, 4.2% and 5.3% in the electricity price (year 2018), while the negative effect on emissions is relatively small. Our analysis concludes with the estimation of an ARIMA-SARIMA model that looks for the main determinants of the variations in the hourly energy prices and the carbon emissions. The estimations show that the marginal supply technology in the electricity market is important in explaining these variations.Graphical abstract

Restoring Coal Mining-Affected Areas: The Missing Ecosystem Services.

Multi-criteria decision analysis and cost-benefit analysis, either individually or in combination, have been used as the preferred tools to develop ecosystem services valuation, presenting significant discrepancies and variations between the calculated values. To counteract this problem, a new framework was developed based on a hierarchical weighting of the non-provisioning ecosystem services, using biodiversity as the reference ecosystem service since it is the easiest to apprehend. Their monetisation was made using the average price of EU carbon dioxide emission allowances during 2019 and 2020, obtaining reasonable and comparable results in line with what was expected for the study region. However, the revised EU Emissions Trading System Directive, which will apply from 2021-2030, generated a price escalation of carbon allowances, making it necessary to adjust or rethink the proposed framework. To achieve this goal, the paper proposes the introduction of new vectors or "missing ecosystem services" to counterbalance efforts to eliminate carbon dioxide emissions without necessarily removing humans from the equation: welfare and human health. As the linkages regarding ecosystem health, ecological restoration and human health are not well known, only welfare was incorporated into the framework. The results were highly satisfactory, in line with what was expected for the study region and the ones obtained before the price escalation of carbon allowances that started in 2021.

The first compliance cycle of China’s National Emissions Trading Scheme: insights and implications

China’s national Emissions Trading Scheme (ETS), the largest ETS in terms of the amount of CO2 regulated, was launched on the trading platform operated by the Shanghai Environment and Energy Exchange (SEEE) on July 16th 2021, and has successfully completed its first compliance cycle on December 30th, 2021. During the operation of its first cycle, China’s national ETS differs from other international ETSs in many aspects, including trading products and participants, allowance allocation method, compliance term, and offset mechanism, leading to certain unique trading patterns. Some unique settings are worth noticing including key emitters dominated by state-owned enterprises (SOEs) who also dominate transactions, large-scale power groups’ carbon strategies, allowances for 2 years of 2019 and 2020 being processed in one compliance period and allowed inter-year banking of allowances. All these have led to trading patterns characterized by cyclical demand-driven trading, insufficient trading capabilities of regulated entities, stable allowance price and an increased price of CCER. Nonetheless, the successful running of its first compliance cycle offers invaluable experience for future ETS development in operational mechanism improvement, sector coverage expansion, allocation optimization, and introduction of different types of market players and tradable products, and provides a good reference for future international expansion.

Sieve bootstrap inference for linear time-varying coefficient models

We propose a sieve bootstrap framework to conduct pointwise and simultaneous inference for time-varying coefficient regression models based on a local linear estimator. The asymptotic validity of the sieve bootstrap in the presence of autocorrelation is established. The bootstrap automatically produces a consistent estimate of nuisance parameters, both at the interior and boundary points. In addition, we develop a bootstrap-based test for parameter constancy and examine its asymptotic properties. An extensive simulation study demonstrates a good finite sample performance of our methods. The proposed methods are applied to assess the price development of CO2 certificates in the European Emissions Trading System. We find evidence of time variation in the relationship between allowance prices and their fundamental price drivers. The time variation might offer an explanation for previous contradicting findings using linear regression models with constant coefficients.

Techno-economic modelling of the Baltic CCUS onshore scenario

Techno-economic modelling of the Baltic onshore CO2 transport, storage, and utilization scenario included HeidelberCement-owned Kunda Nordic Cement (KNC) plant, the main Estonian cement producer, four Estonian and one Latvian power plant and CO2 mineral carbonation of the oil shale ash, as possible CO2 use option. In 2019 nearly 6.5 Mt of oil shale ash (OSA) was produced in Estonia from energy production. Estonian OSA could be used as an effective sorbent in the proposed CO2-mineralization process, using CO2 from flue gas and producing precipitated CaCO3 (PCC) of high quality. Mineral carbonation of 0.42 Mt CO2 using 3.8 Mt of fresh OSA and about 6.33 Mt CO2 produced annually by five Estonian and one Latvian plant transported by pipeline for storage into the North-Blidene structure in western Latvia are combined in the CCUS scenario. Cambrian Deimena Formation reservoir sandstone is located at the depth of 1035-1150 m in the selected saline aquifer. The average optimistic storage capacity of about 270 Mt allows planning CCUS project for 30 years. The share of the Estonian emissions avoided and stored in Latvia is 86.5 %, including 8.2 % by KNC, while Latvian stored emissions will compose 13.5 %. Annually 6.8 Mt CO2 could be captured, transported and injected, including 6 Mt CO2 avoided using transport and storage and 0.42 Mt CO2 avoided using MC of Estonian OSA. During 30 years nearly 204 Mt CO2 will be captured, used and stored, while 193 Mt CO2 could be avoided. The total average transport and storage (T&S) cost of the scenario is 18.4 €/t CO2 injected. This cost depends on the transport distance, according to the applied methodology, and it is the most expensive for the Eesti Energia PPs. The lowest T&S cost of 5.54 €/t CO2 injected will have Latvenergo TEC-2 PP located at a smaller distance from the storage site. At the price of EEAP (CO2 Emission Allowance Price in EU ETS) of 40 €/t CO2 and 50 €/t PCC, the CCUS scenario could be beneficial for three Eesti Energia and Latvenergo TEC-2 power plants. For the KNC and VKG Energia plants without CO2 use options, the higher EEAP of about 48-50 €/t CO2 is needed to cover all CCUS costs including capture, compression, transport, storage and monitoring. The transport and storage costs are distance-dependent, as pipelines are the most expensive part of the transport, storage and monitoring costs. At the present EEAP of about 90 €/t CO2, all the participating plants will get benefits from the proposed scenario.This study is supported by CLEANKER project, which has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement n. 764816.

Carbon market volatility analysis based on structural breaks: Evidence from EU-ETS and China

In recent years, carbon market transactions have become more active. The number of countries participating in carbon market regulation is increasing, and the carbon market’s overall turnover continues to grow. It is important to study the features of carbon allowance price volatility for the stable development of the carbon market. This paper constructs a modified ICSS-GARCH model to analyze the volatility of carbon price returns and the dynamic characteristics of price fluctuations in the emissions trading system of the European Union (EU-ETS) and the Chinese carbon pilot markets in Hubei. The results show that fluctuations in carbon price returns have a leverage effect and that the impact of negative news on the market is stronger than that of positive news. The international climate and energy conferences, abnormal changes in traditional energy prices, and global public health emergencies all affect volatility and cause shocks to the carbon trading market. The modified ICSS-GARCH model with structural breaks can reduce the pseudovolatility of the return series to a certain extent and can improve the accuracy of the model. This research can give policymakers some implications about how to develop the carbon market and help market participants control the risks of fluctuations in carbon allowances. Regulators should enhance carbon price monitoring and focus on short-term shocks in the carbon market to reduce trading risks. The Chinese carbon market should strengthen the system design and develop carbon financial derivatives.

Optimal dynamic regulation of carbon emissions market

AbstractIn this article, we deal with optimal dynamic carbon emission regulation of a set of firms. On the one hand, the regulator dynamically allocates emission allowances to each firm. On the other hand, firms face idiosyncratic, as well as common, economic shocks on emissions, and they have linear quadratic abatement costs. Firms can trade allowances so as to minimize total expected costs, which arise from abatement, trading, and terminal penalty. Using variational methods, we first exhibit in closed form the market equilibrium in function of the regulator's dynamic allocation. We then solve the Stackelberg game between the regulator and the firms. The result is a closed‐form expression of the optimal dynamic allocation policies that allow a desired expected emission reduction. The optimal policy is unique in the presence of market impact. In absence of market impact, the optimal policy is nonunique, but all the optimal policies share common properties. The optimal policies are fully responsive, and therefore induce a constant abatement effort and a constant price of allowances. Our results are robust to some extensions, like different penalty functions.

Does carbon price volatility affect European stock market sectors? A connectedness network analysis

We investigate how the volatility of carbon emission allowance (EUA) prices affects European stock market sectors. We employ a connectedness network analysis on prices of EUA futures and FTSE stock market sector indices and find that the EUA is mostly a net receiver of volatility connectedness and significantly receives volatility across most sectors during the recent European energy crisis.

Negative price spiral caused by renewables? Electricity price prediction on the German market for 2030

Logistic regression models were built and used to show the influence of energy sources, fuel, emission prices and time variables on low and negative price events. The models were tuned and validated with data from 2019 to 2021. The results show that volatile generation of wind and solar power raises the likelihood of low and negative electricity prices. Flexible power sources such as gas power plants, as well as high grid load and conventional generation, relate to higher, more stable market prices. Higher CO2 allowance prices also reduce the likelihood of negative prices, as flexible gas power plants with lower CO2 emissions compared to inflexible coal power plants are more flexible. The biggest influence of the Covid-19-pandemic was on the grid load in 2020 and 2021, which dropped heavily and lowered the electricity price on the market. The prediction analysis shows that in 2030 more low and negative price events will occur if the power supply does not become more flexible. Gas power plants, especially gas turbine peaker plants, help to reduce low prices in the future.