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This study aims to examine the impact of the emission allowances granted under California's cap‐and‐trade program (AB 32) – the first major program of its kind in the USA – on the balance sheets and income statements of the S&P 500. So far there has been little discussion of what a cap‐and‐trade program would mean for the US companies' financial statements.

The author states and tests an economic model of the relation between greenhouse gas emissions and financial statement variables at the individual company level and use this model to predict emission allowances and obligations for the S&P 500.

The author's analysis suggests that the average S&P 500 company's balance sheet and net income will be adversely affected under several different accounting treatments for emission allowances, with the greatest impacts in the utilities, energy, and materials sectors.

US and European regulators have yet to set a single standard for emissions accounting. Without a single standard, companies acting in their own interests may use diverse or unclear accounting treatments for similar economic benefits. This can raise the cost of capital and hurt investors.

This is the first study of which the author is aware to document how the emission allowances under the AB 32 cap‐and‐trade program will affect American companies' balance sheets.

This paper aims to investigate the value relevance of the European Emission Allowance (EUA) return and volatility on the equity value of the top listed European Power Generation Firms for the three trading phases of the European Emission Trading Scheme.

The authors use the multifactor financial market model over the period 2005-2016 on daily basis for the return relevance relationship, whereas time series models such as autoregression moving average and generalized autoregressive conditional heteroskedasticity are applied on a weighted average portfolio of the sample firms to test serial correlation and volatility of returns.

The findings are novel in which a positive and significant relevance of EUA return on equity return is shown; however, a vanishing effect is seen as one moves to further trading phases. Another remarkable finding is that the return relationship remains constant until a certain level in EUA price then inverts. Finally, the authors present that EUA is considered a systematic factor as firm and country-specific features are not statistically significant.

At policy level, these findings signal policymakers for an appropriate design of the future trading phases in which they achieve the balance between public interests, as climate risk mitigation by reducing emissions, and the private interests of the market players to support innovative changes.

To the authors’ knowledge, this study would be the first to offer recent and comprehensive findings on the economic and financial implications of the European Emission Trading Scheme for the three trading phases. Additionally, the research offers time series robustness check besides the standard regression analysis and shows that there is an optimal EUA price that triggers polluters’ decision on emission and generation.

The purpose of this paper is to illustrate how emission constraints imposed by the emission trading scheme (ETS) in the European Union, as well as transmissions capacity, can affect the outcome of the generation scheduling. The aim is to demonstrate the application of the generation scheduling tool which includes both the ETS and transmission constraints, and helps evaluate their effect on emission reduction, costs, and generators' behavior and availability. It can also be used to help generators make strategic decisions regarding utilization and purchases of carbon allowances.

The paper extends the generation scheduling formulation to allow for additional constraints modeling. The formulation is based on the mixed integer programming approach with linearization of generation cost and emission functions, and the possibility to split the system into zones in order to investigate transmission congestion.

The paper presents six case studies that include unconstrained and constrained operation, both from the emission and transmission points of view. It also illustrates the effect of free allocations versus auctioning. The case studies look into the system with wind generation that can be constrained due to transmission limits, and their impact on emission reductions. This is often the case in systems where most of the wind generation is located in the area which does not have sufficiently strong links to the rest of the system where the majority of loads are.

The extension of the work will be inclusion of stochastic nature of emission prices and wind availability. It will also be used for further studies on systems with high wind penetration and insufficient transmission capacity.

The generation scheduling tool and the results from the paper could be useful for generators when making decisions on how to use or purchase their emission allocations, as well as for evaluation of the adverse affect of transmission congestion on carbon emission reductions.

This paper aims to find optimal emission reduction investment strategies for the manufacturer and examine the effects of carbon cap-and-trade policy and uncertain low-carbon preferences on emission reduction investment strategies.

This paper studied a supply chain consisting of one manufacturer and one retailer, in which the manufacturer is responsible for emission reduction investment. The manufacturer has two emission reduction investment strategies: (1) invest in traditional emission reduction technologies only in the production process and (2) increase investment in smart supply chain technologies in the use process. Then, three different Stackelberg game models are developed to explore the benefits of the manufacturer in different cases. Finally, this paper coordinates between the manufacturer and the retailer by developing a revenue-sharing contract.

The manufacturer's optimal emission reduction strategy is dynamic. When consumers' low-carbon preferences are low and the government implements a carbon cap-and-trade policy, the manufacturer can obtain the highest profit by increasing the emission reduction investment in the use process. The carbon cap-and-trade policy can encourage the manufacturer to reduce emissions only when the initial carbon emission is low. The emission reduction, order quantity and the manufacturer's profit increase with the consumers' low-carbon preferences. And the manufacturer can adjust the emission reduction investment according to the emission reduction cost coefficient in two processes.

This paper considers the investment of emission reduction technologies in different processes and provides theoretical guidance for manufacturers to make a low-carbon transformation. Furthermore, the paper provides suggestions for governments to effectively implement carbon cap-and-trade policy.

This study aims to form a new concept of power-to-gas-based virtual power plant (GVPP) and propose a low-carbon economic scheduling optimization model for GVPP considering carbon emission trading.

In view of the strong uncertainty of wind power and photovoltaic power generation in GVPP, the information gap decision theory (IGDT) is used to measure the uncertainty tolerance threshold under different expected target deviations of the decision-makers. To verify the feasibility and effectiveness of the proposed model, nine-node energy hub was selected as the simulation system.

GVPP can coordinate and optimize the output of electricity-to-gas and gas turbines according to the difference in gas and electricity prices in the electricity market and the natural gas market at different times. The IGDT method can be used to describe the impact of wind and solar uncertainty in GVPP. Carbon emission rights trading can increase the operating space of power to gas (P2G) and reduce the operating cost of GVPP.

This study considers the electrical conversion and spatio-temporal calming characteristics of P2G, integrates it with VPP into GVPP and uses the IGDT method to describe the impact of wind and solar uncertainty and then proposes a GVPP near-zero carbon random scheduling optimization model based on IGDT.

This study designed a novel structure of the GVPP integrating P2G, gas storage device into the VPP and proposed a basic near-zero carbon scheduling optimization model for GVPP under the optimization goal of minimizing operating costs. At last, this study constructed a stochastic scheduling optimization model for GVPP.

This paper aims to reflect on the special issue that has collected studies by the research community in China pertinent to the country’s recent developments in sustainability accounting, management and policy, as well as to suggest possible future avenues of studies.

This paper articulates the current status of researching sustainability accounting, management and policy in China that is instigated by the country’s regulatory initiatives under its political economy. It highlights the papers accepted for the special issue, their areas of focus and the underlying characteristics.

It points out that the accepted research papers concentrate on issues related to corporate social responsibility disclosures, sustainability reporting and environmental management in China from the perspectives of the domestic stakeholders.

Future studies are likely to be increasingly interdisciplinary in nature and requires academia, policymakers and practitioners to make better collaborative efforts in researching about China’s sustainability and the efficacy of their engagement with stakeholders.

Studies on alignment between China’s further developments and UN’s sustainable development goals (SDGs) are particularly considered desirable as the country continues its globalization initiatives. Education about sustainability accounting for the working professionals and their next generation is much needed for China in support of developing a more sustainable economy aligned with UN's SDGs.

Scholars in China actively developing their research interests in this field reflect critical thinking about the country’s pursuit of sustainable development within a social-political economy that is dissimilar to the West. In the meantime, the country continues to develop into a significant stakeholder of the world’s sustainability implying expectation of transparency in sustainability performance.

With reference to the review exercise conducted for the special issue, it suggests that there are surging interests in researching accountability for sustainability across the local and international communities to facilitate much needed knowledge exchange. The country and indigenous culture of China, as well as its institutions in relation to sustainability, would require much further exploration in our world under globalization.

The purpose of this paper is to examine the suitability of free carbon calculators aimed at the agricultural industry, for use in greenhouse gas (GHG) emission benchmarking, using the European dairy industry as an example.

Carbon calculators which were claimed to be applicable to European dairy farms were identified and tested using six production scenarios based on data from real European farms supplemented using published literature. The resulting GHG emission estimates, together with estimates apportioned using three functional units, were then compared to determine the robustness of the benchmarking results.

It was found that although there was a degree of agreement between the seven identified carbon calculators in terms of benchmarking total farm emissions, once a suitable functional unit was applied little agreement remained. Tools often ranked farms in different orders, thereby calling into question the robustness of benchmarking in the studied sector.

The scenario-based approach taken has identified issues liable to result in a lack of benchmarking robustness within this sector; however, there remains considerable scope to evaluate these findings in the field, both within this sector and others in the agricultural industry.

The results suggest that there are significant hurdles to overcome if GHG emission benchmarking is to aid in driving forward the environmental performance of the dairy industry. In addition, eco-labelling foods based on GHG benchmarking may be of questionable value.

At a time when environmental benchmarking is of increasing importance, this paper seeks to evaluate its applicability to sectors in which there is considerable scope for variation in the results obtained.

The 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).

Adopting 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.

First, 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.

By 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.

This chapter considers the application of climate mitigation policies to the aviation sector with reference to the inclusion of aviation in the EU Emissions Trading System (EU ETS). Assessments of the possible economic impacts of including aviation in the EU ETS are reviewed and an impact analysis using the macroeconometric E3ME model is conducted.

The aviation sector is a significant and rapidly increasing source of GHG emissions. Because international policy measures have not been agreed, the EU has incorporated aviation in the EU ETS. It is therefore important to consider the possible economic effects of the ETS on the aviation industry and the wider economy.

The paper describes the approach used by the EU to include aviation in the EU ETS. Assessments of economic impacts have been made, but have often been limited in their approach. The paper complements the existing literature by including an economic analysis using the E3ME macroeconometric model of the EU that covers 41 industrial sectors including aviation.

Microeconomic and macroeconomic assessments show the economic impacts of including the aviation sector in the EU ETS are small. The negative impacts, if any, on EU GDP and the air transport sector’s economic output are less than 0.1% and 1% respectively. Distortions in competition, both between countries and industrial sectors, are therefore likely to be small.

In the long term (beyond 2020), including aviation in the EU can be seen as a positive move. If and when aviation is fully included in the EU ETS, and when the cost impacts of GHG emissions through permit prices are made evident, it is anticipated that airlines will start monitoring and reducing their GHG emissions by investing in new, less carbon intensive technologies.