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This paper aims to analyze the role and advantages of knowledge resources in the carbon emission reduction of the industrial chain, and how it can be used to promote the carbon emission reduction of the industrial chain, so that the industry can better achieve the saving of energy and the reduction of emission.

This paper argues that the traditional resource-plundering industrial chain production method can no longer meet the needs of sustainable development of the green and low-carbon industrial chain, and builds the coupling and coordination of knowledge technology innovation drive and industrial chain carbon emission reduction mechanism, in the four dimensions of industrial chain organization, government support, internet support and staff brainstorming, put forward suggestions for knowledge resources to drive carbon emission reduction in the industrial chain.

This paper holds that the use of knowledge resource advantages can better help industrial chain enterprises to carry out technological innovation, knowledge resource digital platform construction, knowledge resource overflow and transfer, application and management of network information technology, so as to reduce carbon emission in industrial chain.

This paper contributes to the discussion about the high-quality implementation of the revitalization strategy of the industrial chain and also deepens research on the knowledge resource-driven carbon emission reduction of the industrial chain. Further, this paper enriches the role of knowledge resources in the industrial industry, and the theoretical results support the advantages of knowledge resource in the field of chain carbon emission reduction.

Carbon emission is one of the most important issues threatening the existence of the world. Mostly carbon emission induced climate change disrupts human and nature balance. Carbon emission occurs as a result of practices that are dependent on human activities or not. One of the actors causing carbon emissions is production companies. The companies are working toward reducing carbon emissions. However, although these efforts reduce carbon emissions in the short term, carbon emissions continue in the long term. Therefore, the present study aims to determine the importance of carbon emission in terms of sustainable economic development. Depending on this purpose, production companies in Chile were included in the scope of research for 1990–2019. Based on these data, the study has been tested by Toda Yamamoto causality analysis. Result shows that carbon emissions are not the primary cause of sustainable economic development. In this context, governments need to focus on other issues that have a stronger causal relationship with sustainable economic development. However, studies should be conducted to determine the importance of other activities of companies for sustainable economic development. Hereby, the amount of carbon emission will be reduced and deficiencies in factors affecting sustainable economic development will be identified.

Production-related industrial zones, super structures and infrastructures are constructed by the construction industry. Nearly all industries and their environmental emissions are influenced by the construction industry including its sub-industries, companies and their supply chains. Furthermore, cities play an important role in economic growth. Cities are hubs for productivity, production, supply and demand, and innovation with the help of their human capital and built environment (e.g. offices, factories, industrial zones, infrastructures, etc.).

Industrial growth fosters urbanisation which is vital for the supply side in the economy to reach to the human resources. Urbanisation which supports industrial growth obstacles industries’ efficiency due to urbanisation problems (e.g. traffic, air and water pollution, health problems).

Construction industry and its sub-industries affect total factor productivity growth in nearly all industries. Construction industry can be a facilitator industry for economic growth and industrial growth considering total factor productivity growth and environment aspects. All industries’ green and sustainable total factor productivity growth can be supported by rethinking construction industry, its sub-industries and their outputs (e.g. construction materials, built environment, cities) as well as construction project management processes.

This chapter aims to introduce carbon capturing smart construction industry model to foster green and sustainable total factor productivity growth of industries. This chapter emphasises current and potential roles of construction industry, its sub-industries and their outputs in fostering other industries’ growth through green and sustainable total factor productivity growth. It focusses on carbon capturing technologies and design at different levels. Furthermore, this chapter emphasises cities’ role in green and sustainable total factor productivity growth. This chapter provides recommendations for construction industry policies and carbon capturing cities/built environment model to solve urbanisation problems and to foster industrial growth and green and sustainable total factor productivity growth. This chapter is expected to be useful to all stakeholders of the construction industry, policy makers, and researchers in the relevant field.

The coal-fired power plants have been confronted with new operation challenge since the unified carbon trading market was launched in China. To make the optimal decision for the carbon emissions and power production has already been an important subject for the plants. Most of the previous studies only considered the market prices of electricity and coal to optimize the generation plan. However, with the opening of the carbon trading market, carbon emission has become a restrictive factor for power generation. By introducing the carbon-reduction target in the production decision, this study aims to achieve both the environmental and economic benefits for the coal-fired power plants to positively deal with the operational pressure.

A dynamic optimization approach with both long- and short-term decisions was proposed in this study to control the carbon emissions and power production. First, the operation rules of carbon, electricity and coal markets are analyzed, and a two-step decision-making algorithm for annual and weekly production is presented. Second, a production profit model based on engineering constraints is established, and a greedy heuristics algorithm is applied in the Gurobi solver to obtain the amounts of weekly carbon emission, power generation and coal purchasing. Finally, an example analysis is carried out with five generators of a coal-fired power plant for illustration.

The results show that the joint information of the multiple markets of carbon, electricity and coal determines the real profitability of power production, which can assist the plants to optimize their production and increase the profits. The case analyses demonstrate that the carbon emission is reduced by 2.89% according to the authors’ method, while the annual profit is improved by 1.55%.

As an important power producer and high carbon emitter, coal-fired power plants should actively participate in the carbon market. Rather than trade blindly at the end of the agreement period, they should deeply associate the prices of carbon, electricity and coal together and realize optimal management of carbon emission and production decision efficiently.

This paper offers an effective method for the coal-fired power plant, which is struggling to survive, to manage its carbon emission and power production optimally.

This study investigates the association between debt overhang and carbon emissions (both direct and indirect emissions) using a sample of US publicly listed firms.

The study applies generalized least squares (GLS) regression analyses to a sample of 2,043 US firm-year observations over a period of 14 years from 2007 to 2020. The methods include contemporaneous effect, lagged effect, alternative measures of carbon emissions and debt overhang, intensive versus non-intensive analysis, channel analysis, firm fixed effects, change analysis, controlling for credit rating analysis, propensity score matching approach, instrumental variable analysis with industry and year fixed effect.

This study's findings reveal that the debt overhang problem increases carbon emissions. This finding holds when the authors use alternative measures of carbon emissions and debt overhang. The authors find that carbon abatement investment is a channel that is negatively impacted by debt overhang, which in turn increases carbon emissions. This study's results are robust for several endogeneity tests, including firm fixed effects, change analysis, propensity score matching approach and two-stage least squares (2SLS) instrumental variable analysis.

The outcome of this research has policy implications for several stakeholders, including investors, firms, market participants and regulators. This study's findings offer insights for investors and firms, helping them allocate resources effectively and make financing decisions aimed at reducing carbon emissions. Regulators and policymakers can also use the findings to formulate policies that promote alternative sustainable finance practices.

The outcome of this research is likely to help firms develop their understanding of the debt overhang problem and undertake strategies that yield a significant amount of funding to invest in reducing carbon emissions.

Oversupplied emission basically will create a global economic downturn, which will lead to the implications for the climate action more broadly. Though the pandemic has test the resilience of carbon initiatives, there is urgency in identifying the carbon tax to strengthen as jurisdiction around the world ambitious in adopting and mitigating the targets as an introductory of the associated policy tools. Based on different situations and disciplines, the carbon tax model is simulated in different ways. The purpose of this study is to compare the available approaches that have been utilised by researchers and to determine the methods that suitable the most. The carbon tax and its influence on the construction sector are being benchmark and discussed as the whole of this document. A bibliometric approach is the method in this study in between the keyword of a carbon tax and the construction industry based on the data available in database of Scopus and Web of Science to foresee the interconnection between the knowledge of understanding and definition. The definition of carbon tax is the Pigovian tax that is designed to reduce the greenhouse gases (GHGs) emitted with aim to act as a green tax and been paid by the industries that emitted GHGs as for the carbon emission reduction agenda. The implementation is parallel to the other government policies and in sync to the sustainable development goals.

This paper aims to examine the effect of carbon emissions on audit fees. The authors hypothesize that firms in cities with higher carbon emission levels have lower reporting transparency, higher return volatility or are subject to higher reputation risk, causing them to be charged higher audit fees for auditing services.

The authors use panel data of 25,960 firm-year observations from a sample of Chinese firms. The carbon emission data for each Chinese city are obtained from the China Emission Accounts and Datasets for Emerging Economies. This paper adopts a multiple regression model to study the impact of carbon emissions on audit fees.

The authors find that firms located in cities with higher carbon emission levels and firms with more carbon emissions are charged, on average, a higher audit fee. This audit fee effect of carbon risk is transmitted by lessened information transparency and elevated financial risk within these firms. This paper shows that auditors consider carbon risk in their audit fee decisions and other factors that could influence audit risk and effort.

This study draws a connection between carbon emissions and audit fees. It is especially relevant due to the increasing importance of environmental factors in the audit risk assessment. In addition, the findings suggest that a firm implementing a proactive environmental strategy benefits the economy and decreases the costs to the firm for services such as auditing.

This study aims to empirically examine the influence of financial constraints on firm carbon emissions. In addition to the role of financial constraints in firm-level carbon emissions, this study also examines this influence in the presence of governance, environmental orientation and firm-level attributes.

Using pooled ordinary least square, this study examines the impact of financial constraints on firm-level carbon emissions using a panel of 1,536 US firm-year observations from 2008 to 2019. This study also used two-step generalized method of moment–based dynamic panel data and two-stage least square approaches to address potential endogeneity. The results are robust to endogeneity and collinearity issues.

The results suggest that financial constraints enhance the carbon emissions of the firms. The economic significance of financial constraints on carbon emissions is more pronounced for the firms that do not report environment-related expenditure investment and those that are highly leveraged. The authors further document that firms with a nondiverse gender board signify a statistically significant impact of financial constraints on carbon emissions. These results are also economically significant, as one standard deviation increase in financial constraints is associated with a 3.340% increase in carbon emissions at the firm level.

Some implicit and explicit factors like corporate emissions policy and culture may condition the relationship of financial constraints with carbon emissions. Therefore, it would be worthwhile to consider these factors for future research. In addition, it is beneficial to identify the thresholds and/or quantiles at which financial constraints may significantly make a difference in enhancing carbon emissions.

The findings offer policy implications for investment in stakeholder engagement for capital acquisitions, thereby effectively enforcing environmental innovation and leading to a reduction in carbon emissions.

This study integrated governance and environment-oriented variables in the model to empirically examine the role of financial constraints on the carbon emissions of the firms in the USA over and above what has already been documented in the earlier literature.

To better understand the impact of choosing a carbon data provider for the estimated portfolio emissions across four asset classes. This is important, as prior literature has suggested that Environmental, Social and Governance scores across providers have low correlation.

The authors compare carbon data from four data providers for developed and emerging equity markets and investment grade and high-yield corporate bond markets.

Data on scope 1 and scope 2 is similar across the four data providers, but for scope 3 differences can be substantial. Carbon emissions data has become more consistent across providers over time.

The authors examine the impact of different carbon data providers at the asset class level. Portfolios that invest only in a subset of the asset class may be affected differently. Because “true” carbon emissions are not known, the authors cannot investigate which provider has the most accurate carbon data.

The impact of choosing a carbon data provider is limited for scope 1 and scope 2 data for equity markets. Differences are larger for corporate bonds and scope 3 emissions.

The authors compare carbon accounting metrics on scopes 1, 2 and 3 of corporate greenhouse gas emissions carbon data from multiple providers for developed and emerging equity and investment grade and high yield investment portfolios. Moreover, the authors show the impact of filling missing data points, which is especially relevant for corporate bond markets, where data coverage tends to be lower.

Rapidly increasing the proportion of installed wind power capacity with zero carbon emission characteristics will help adjust the energy structure and support the realization of carbon neutrality targets. The intermittency of wind resources and fluctuations in electricity demand has exacerbated the contradiction between power supply and demand. The time-of-use pricing and supply-side allocation of energy storage power stations will help “peak shaving and valley filling” and reduce the gap between power supply and demand. To this end, this paper constructs a decision-making model for the capacity investment of energy storage power stations under time-of-use pricing, which is intended to provide a reference for scientific decision-making on electricity prices and energy storage power station capacity.

Based on the research framework of time-of-use pricing, this paper constructs a profit-maximizing electricity price and capacity investment decision model of energy storage power station for flat pricing and time-of-use pricing respectively. In the process, this study considers the dual uncertain scenarios of intermittency of wind resources and random fluctuations in power demand.

(1) Investment in energy storage power stations is the optimal decision. Time-of-use pricing will reduce the optimal capacity of the energy storage power station. (2) The optimal capacity of the energy storage power station and optimal electricity price are related to factors such as the intermittency of wind resources, the unit investment cost, the price sensitivities of the demand, the proportion of time-of-use pricing and the thermal power price. (3) The carbon emission level is affected by the intermittency of wind resources, price sensitivities of the demand and the proportion of time-of-use pricing. Incentive policies can always reduce carbon emission levels.

This paper creatively introduced the research framework of time-of-use pricing into the capacity decision-making of energy storage power stations, and considering the influence of wind power intermittentness and power demand fluctuations, constructed the capacity investment decision model of energy storage power stations under different pricing methods, and compared the impact of pricing methods on optimal energy storage power station capacity and carbon emissions.

1. Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

2. Investment strategy of energy storage power stations on the supply side of wind power generators.

3. Impact of pricing method on the investment decisions of energy storage power stations.

4. Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

5. A two-stage wind power supply chain including energy storage power stations.

Electricity pricing and capacity of energy storage power stations in an uncertain electricity market.

Investment strategy of energy storage power stations on the supply side of wind power generators.

Impact of pricing method on the investment decisions of energy storage power stations.

Impact of pricing method, energy storage investment and incentive policies on carbon emissions.

A two-stage wind power supply chain including energy storage power stations.