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This paper investigates the optimal strategies for an economic constrained closed-loop supply chain network. Manufacturers are classified into two categories namely low-emission manufacturers and high-emission manufacturers, and are subject to two greenhouse gas (GHG) emission control policies. Low-emission manufacturers are equipped with green production technologies to achieve ecological goals. All manufacturers are responsible in recycling and remanufacturing processes. New products and remanufactured products are homogeneous, and have the same sales price in the demand markets. Based on the variational inequality (VI) theory, we obtain the control equilibrium conditions of the non-cooperative game theory model for each firm. We further solve the model with the modified projection algorithm, and statically analyze and compare the influence of relevant parameters such as carbon quota, consumers’ low carbon preference and recovery rate on the network state through numerical examples. The results show that the GHG emission constraint may stimulate manufacturers to increase green technology investment level. Moreover, the introduction of reverse channel will promote resource recycling, but impair manufacturers’ profits. The promotion of consumer's environmental protection awareness has positive influence on the operation of supply chain network. In general, there is a conflict between economic goals and ecological ones. However, the developed model proves that economic goals and ecological ones can be realized consistently under certain conditions.

[EN] Rapid economic development usually leads to serious environmental pollution problems. In order to solve the problem of pollutant emission in sustainable industrial development, it is urgent to examine the implementation effect of emissions trading policy (ETP) and its impact on green industrial development. This study adopts China's ETP as a case study and selects provincial panel data from 2004 to 2018. We first use a non-radial, non-directed, slack-based measure-directional distance function (SBM-DDF) to measure industrial green innovation efficiency. Then we use a difference in differences (DID) model to empirically test the emissions reduction effect of China's policy and whether it promotes industrial green innovation. Thereafter, results show that: (1) the ETP reduces sulfur dioxide (SO2) emissions indicating the effectiveness of the policy; (2) the policy significantly improves industrial green innovation efficiency, meaning it promotes the sustainable development of the economy; (3) heterogeneity analysis highlights that ETP produces greater benefits for the most polluted regions of China which have more strict environmental regulations. The study examines the effect of emissions trading policy implementation from a new perspective. The study also provides a reference point for China to further refine its policy mechanisms and for other countries to formulate suitable ETP., This work was supported by the National Social Science Fund projects [No. 20BJY010]; National Social Science Fund Postfinancing projects [No. 19FJYB017]; Sichuan-Tibet Railway Major Fundamental Science Problems Special Fund [No. 71942006]; Qinghai Natural Science Foundation [grant numbers 2020-JY-736]; List of Key Science and Technology Projects in China's Transportation Industry in the International Science and Technology Cooperation Project [No. 2018-GH-006 and grant numbers 2019-MS5-100]; Shaanxi Social Science Fund [No. 2017S004]; Xi'an Construction Science and Technology Planning Project [No. SZJJ201915 and No. SZJJ201916]; Fundamental Research for Funds for the Central Universities (Humanities and Social Sciences), Chang'an University [No. 300102231641, 300102230612, 300102281669, 300102230503].

Climate change has caused great pressure on the air transport sector. European airlines are subject to a pioneering CO2 emissions regime. This paper sets out, first, to ascertain whether the European aviation sector has adapted since the launch of the European Union (EU) Emissions Trading Scheme (ETS). Second, based on the answer to the above, we predict the situation of the sector in the medium and long term. The study sample was formed by the top 10 European airlines. The years covered are those since the inclusion of the airline sector in the emissions regime (2012–2019). Clusters were defined by eco-efficiency level using K-means cluster analysis and the Markov model was applied to predict future behaviour. The results have shown, on the one hand, that the larger airlines were the most eco-efficient throughout the study period. On the other hand, companies focused on a low-cost strategy have behaved worse since, although they have also experienced significant improvements in their use of air traffic capacity, even above the large airlines, they have not evolved to a higher level of CO2 emission efficiency and even getting worse in some cases. However, in the medium and long term, our estimate for the sector is a trend towards minimal eco-efficiency in CO2 emissions. As governments continue to increase emission limitation requirements, in order not to jeopardise the sustainability of the aviation sector, it is advisable to encourage investments in the development of biofuels and their supply chain, international agreements to optimise flight routes or projects to improve the energy efficiency of new engines.

An emissions trading scheme (ETS) is widely regarded as a cost-effective instrument for curbing global climate change. In 2011, China, the world’s leading carbon emitter, introduced ETS pilots in seven cities/provinces. Subsequent studies have debated their effectiveness, especially in terms of their economic performance. This article investigates whether China’s ETS pilots have successfully balanced carbon emission reductions and economic growth. For this, we apply an extended synthetic control method for multiple treated units that relaxes the parallel trends assumption required by the difference-in-differences estimation commonly used in the field The results show that overall CO2 emissions decreased by approximately 1,165.72 Mt from 2011 to 2015, representing 12.78% of the pilot regions’ total industrial CO2 emissions. As for the ETS pilots’ economic performance over this period, we find that there was a loss in the value of industrial output totalling approximately RMB5,608.88 billion. That said, the economic loss was short term in nature and decreased over time. Regions showed heterogeneous responses to the ETS pilots. Although all of them experienced a decline in CO2 emissions, Beijing and Shanghai showed the fastest reduction, while Guangdong showed the largest reduction. Losses in industrial output were concentrated in Guangdong (RMB7,416.66 billion; 4.64% of the region’s total industrial output) and Shanghai (RMB701.28 billion; 4.08%); the other regions saw economic losses only in the first two years after ETS implementation. These findings suggest that policy makers should consider a gradual (rather than a radical) ETS policy and make firm subsidies part of their battery of instruments in the early stage of establishing a nationwide ETS.

This paper discusses the impact of cap-and-trade mechanisms, including grandfathering and benchmarking mechanisms, on renewable energy investments and marketing efforts in the electricity market. The current system constructs a two-level electricity supply chain, with a leader's electricity generator and a follower's electricity retailer. Based on the analysis framework of the game theory, the optimal solutions under the grandfathering mechanism and benchmarking mechanism are compared. The results are as follows. First, grandfathering and benchmarking are both conducive to the investment of renewable energy. Further, the benchmarking mechanism is more conducive to investments. Second, benchmarking is beneficial to marketing efforts, while grandfathering is not. Third, the grandfathering mechanism and benchmarking mechanism are conducive to the improvement of market demands. Further, grandfathering produces more total carbon emissions, while benchmarking reduces the total carbon emissions.

According with a growing sense of climate change in recent decades, an increasing number of works have focused on the impacts of climate on tourism. However, few studies to date have investigated the impacts of various emissions policies on tourism, leading to an ambiguous understanding of tourism adaption to emissions policy change. Here this study attempted to provide a framework to guide future research on tourism change under the leading emissions policies worldwide (i.e. the carbon tax and emissions trading scheme). Regarding the policy setting, this study suggests both the policy diversification within the emissions trading scheme or carbon tax and their comprehensive study. Regarding the research subject, this study recommends taking into account overall or sectoral impacts on different tourism economic and environmental variables. Moreover, future efforts should be devoted to not only simulating future change but also quantifying the actual impacts on tourism based on existing data. Regarding the methodology, this study strongly recommends four methods for assessing the impacts of emissions policies on tourism, including the augmented computable general equilibrium model, dynamic stochastic general equilibrium model, difference-in-differences method, and regression discontinuity method.

In recent years, as a result of the rapid increase in population and industrial development, the need for energy has increased. Many investments are made especially for electrical energy which is an inevitable requirement for the industry. Most of these investments are made by using fossil resources in countries’ lands. Fossil sources are known to be consumable as well as too poisonous gases they give to the atmosphere during energy production. This situation causes global climate change. To prevent climate change, the carbon emitted to the atmosphere has to be brought under a certain control mechanism. In this context, the first Kyoto Protocol and then Paris Climate Agreement was signed. Under these agreements, countries will be responsible for the level of their greenhouse gases in the atmosphere. This situation led to the carbon trade among countries. This situation accelerated the transition of countries from fossil sources to renewable energy sources. In this study, the effect of hydroelectric power plants, one of the renewable energy sources, on carbon emissions was investigated. According to the results, based on fossil sources of 408,533.57 tCO2 per year from Turkey Gokcekaya dam has been shown to reduce the carbon footprint.

One of the biggest challenges facing the tourism industry is carbon dioxide emissions resulting from the greenhouse gases emitted from aviation indispensable for tourism. Thus, governments have introduced emission permits trading to the aviation industry. However, as this is in the introductory stages, it is unclear how this environmental policy will influence tourism and the environment and whether the policy can contribute to the decarbonisation of the aviation industry. Using an R&D-based growth model considering aviation for tourism, this study investigates how introducing emissions permit trading in aviation influences tourism-led growth and sustainable tourism. Domestic tourism aviation, and not international tourism aviation, was considered because it is estimated that the former short-distance aviation movements emit more greenhouse gases than the latter. The findings demonstrate that fewer permits lead to sustainable tourism despite a generous permit allocation for the manufacturing sector if the goal of tourism-led growth is excluded. This is because the policy improves environmental quality and results in a trade-off between tourism consumption and the economic growth rate. For a generous permit allocation in aviation, the policy leads to decreased tourism consumption and pollution-intensive aviation. These findings imply that emissions permit trading between the aviation and manufacturing sectors inhibits the compatibility of tourism-led growth and sustainable tourism. Finally, this study suggests that sustainable tourism could be realised when manufacturing countries such as Germany and the UK increase aviation permits, while tourism countries such as Spain and Italy decrease aviation permits.

We study profit allocation rules for joint replenishment among retailers under a carbon cap-and-trade policy. In particular, we consider retailers’ altruistic behavior when designing the profit allocation rules. We show that joint replenishment can increase participants’ total profit and reduce their total amount of carbon emissions. To allocate the total profit from joint replenishment to the retailers, we introduce a joint replenishment game with the carbon cap-and-trade policy. We show this game is convex and propose a profit allocation rule lying in the core of this game. Based on this, we further design an altruistic profit allocation rule by categorizing retailers into efficient ones and non-efficient ones, with the efficient retailers being altruistic who will transfer their surplus carbon allowance to those non-efficient ones. We show that our proposed altruistic profit allocation rule lies in the core of this game. Moreover, we derive results concerning how much carbon allowance, to whom and at what price retailers are willing to transfer in the grand coalition, by considering their altruistic parameters. Our results show that the retailer with the highest altruistic parameter value obtains all the surplus carbon allowance from other retailers, and this particular retailer transfers his surplus carbon allowance to the retailer with the second-highest altruistic parameter value. These results indicate that people do not help other people uniformly; rather, they do so according to the generosity of other people. Based on these results, we derive another altruistic profit allocation rule which also belongs to the core of the game.

The e-waste problem needs be tackled under a global framework, based upon the understanding that e-waste is a global issue and thus a shared responsibility. To illustrate this point, a cost-benefit analysis of metal recovery from e-waste was conducted with Europe, North America and China as representative regions of e-waste producers. The final profit associated with the entire e-waste recycling process was estimated by deducing the energy costs of metal recovery from the revenues of the manually dismantling stage and the metal recovery stage. Then, the potential job opportunities were estimated based on the final profit from the local e-waste recycling and average wage per year. Overall, profits of manually dismantling 1 ton of e-waste varied widely, but the final profits were positive. The potential job opportunities generated by local e-waste recycling ranged from 4.65 × 105 person/year for North America to 2.03 × 106 for China person/year. According to our study, the environmental load of 1 kg of e-waste would be 1–9 USD, indicating that this is the cost required to offset the environmental consequences of each kilogram of e-waste. By applying environmental load to per capita, the concept can act as a tool to encourage countries to fairly share the environmental responsibility of e-waste based on their e-waste generation. Based on this, we propose an e-waste emissions trading system that set a cap on the total amount of e-waste that could be generated globally and per country, to reduce e-waste and carbon emissions.

Taking China’s recent SO2 Emissions Trading Pilot as a quasi-natural experiment on changing regulatory stringency and using large panel data of Chinese industrial enterprises for 1998–2007, this study identifies the productivity effects of this market-based environmental regulation by employing a difference-in-difference-in-differences design. Our results suggest that the market-based environmental regulation has exerted significant productivity-enhancing effects across all types of industrial enterprises, with stronger effects associated with privately owned, more productive, and less pollution-intensive enterprises. We also identify a dynamic productivity-enhancing effect that tends to decay slowly over time. The SO2 Emissions Trading Pilot, as a market-based environmental regulation, allows more flexible mechanisms for production adjustment and innovation than do conventional command-and-control regulations. Thus, our results provide evidence supporting the narrow but strong version of the Porter Hypothesis that strict but flexible environmental regulations are more likely to trigger positive productivity effects.

In this study, three models are developed to optimize the inventory level and technology investment under a carbon tax, cap-and-trade, and strict carbon limit regulations. The study considers warehouse operations and transportation logistic systems as the sources of emissions. Several examples are presented, followed by sensitivity analysis for different scenarios. The result shows that under the carbon regulations, profit and carbon emission reduction is proportional to the green technology investment, while demand increase with the green technology promotion. Further analysis has shown that for the carbon tax system policy, the carbon price has influenced the total profit significantly. The decreasing emission level results in a higher profit, while the carbon cap and the carbon limit do not affect the total profit significantly.

As the largest carbon emitter, China has launched the emissions trading scheme (ETS) in 2013. Since then, whether ETS in China really help reduce carbon emissions has become a hot-button issue. By far, scholars tend to offer the macro-level empirical evidence, and the conclusions are at best mixed. Therefore, we try to reveal the effect of China's ETS from the micro level by focusing on the policy executors, herein the pilot firms. Based on the data of listed firms from 2009 to 2017, we employ the Propensity Score Matching–Difference in Differences method (PSM-DID) to estimate the causal effect of ETS. The results suggest that ETS has come into play to a certain extent (a reduction of 129.588 million tons' carbon emissions), but the effect attenuates over time. Meanwhile, the effect is more pronounced among small-scale firms and non-state-owned firms, as well as those pilot regions adopting systems of ex-post allowance allocation. Therefore, in the process of the national ETS, ex-post allowance allocation should be widely promoted, and more attentions should be given to effectively stimulating the emission reduction capacity of large-scale firms and state-owned firms.

This paper investigates a remanufacturing closed-loop supply chain under the cap-and-trade regulation, where the collecting operations can be carried out by a manufacturer or a retailer or a third party. We construct models with and without remanufacturing to show the value of remanufacturing. The results indicate that remanufacturing can effectively improve the level of carbon emission reduction and the profits of the manufacturer and the retailer. For models with remanufacturing, we find that, interestingly, the result in the previous literature does not always hold. Specifically, the manufacturer will choose the third-party collecting mode when the unit carbon emissions in take-back process in the retailer collecting mode are much larger than those in the third-party collecting mode and the unit cost savings are relatively low, otherwise the manufacturer will choose the retailer collecting mode. As the numerical analysis shown, when the manufacturer subjects to a stringent emission control, total carbon emissions are always the lowest in the third-party collecting mode. The manufacturer's optimal collecting mode, whether is the retailer collecting mode or the third-party collecting mode, may result in the most carbon emissions when the carbon price is relatively low or the carbon intensity is high.

The petroleum refining sector is energy intensive and has been identified as one of the target industries for CO2 emissions control by China’s emissions trading scheme. A detailed accounting of the cost of emissions reduction is of great significance for the petroleum refining sector to comply with emission reduction target. In this paper, six categories of CO2 abatement technologies are identified in China’s petroleum refining sector, their CO2 emissions reduction cost as well as the potential are estimated using a bottom-up method. Most of the technologies in the sector are cost-effective, which has contributed approximately 76.4% of sectoral total emissions reduction. New equipment technology provides the greatest contribution to emissions reduction, while new materials technology offers the lowest contribution. The implementation of the emissions trading scheme will increase the potential for emissions reduction only if the CO2 price can be higher than 200 CNY/t. Given the amount of emissions reduction that technologies can provide will not exceed 40% of the total emissions; firms must find more diversified ways when facing more stringent emissions control.

We study the determinants of aviation CO2 emissions by designing an econometric model applied to a panel data set covering all flights departing from Lombardy, Italy over the 1997–2011 period. We consider two dimensions of CO2 emissions: total and per available seat kilometer. The latter is a measure of emission efficiency. We focus on different categories of determinants: technical progress; aircraft and network carrier management; policy/business decisions that may not be oriented to limiting CO2, but may indirectly affect it by offsetting projected outcomes of policies adopted to reduce emissions (e.g., the EU Emission Trading Scheme (ETS) or the ICAO Carbon Offsetting and Reduction Scheme for International Aviation); and others. We find that although aircraft size increases total emissions, it reduces emissions per available seat kilometers (ASK), while the route distance increases total emissions and decreases emissions per ASK, implying that CO2 is less of a problem for long-haul connections. Technical progress decreases CO2 emissions per ASK with an estimated elasticity equal to −0.06%. Last, liberalization in the EU market has generated the development of low-cost carriers, which in turn have lowered CO2 emission per ASK, that is, liberalization in Europe has brought the collateral effect of reducing the CO2 externality per passenger.

In response to the deteriorating environmental pollution, China has formulated a series of environmental regulation policies. However, political centralization and economic decentralization have subjected the local governments (LGs) to the dual constraints of environmental protection and economic development during the implementation of environmental regulation, which has resulted in the failure of conventional environmental regulation. To this end, the central government (CG) has established a central environmental protection inspection system (CEPIS). However, the existing literature has insufficiently studied the role and policy tools of the CG for inspecting the LGs and the polluting enterprises (PEs) to implement environmental regulation, and lacked systematic analysis of the strategic interactions and policy effects caused by CEPIS. Evolutionary game theory (EGT) provides a powerful tool with which to unpack the interactive strategies of Multi-Agent in China. By exploring the evolution of different participants’ behavior and their evolutionary stable strategy (ESS), EGT enables a robust, quantitative analysis of this three-party game. Simultaneously, some numerical examples serve to verify the theoretical results and support four key insights. First, the selection of environmental strategies manifests in a dynamic process of constant adjustment and optimization. Second, the whole evolutionary game system can converge on an ideal state under certain conditions. Third, increasing the investments in the special transfer payments of environmental protection, expanding the scale of emissions trading market, and improving the emission reduction benefits can motivate the PEs to reduce their emissions and the LGs to perform their duties. Fourth, in some scenarios, simply increasing the political penalties for the LGs fails to motivate the LGs to perform their duties. This research can provide the evolutionary mechanism and broaden our understanding of relationship between environmental regulation and emission reduction strategies. Related implications are finally proposed, which can offer valuable guidance on reforming the environmental regulation and improve market outcomes in China.

Considering the importance of waste sorting and treatment in the development of an ecological civilization, empirically evaluating the environmental impact of such programs is particularly important. This study uses Xiao'er Township in Gong County, Sichuan Province, China as a case study to analyze and estimate the carbon emission reduction effects of the township's pilot waste sorting program. Using the five-point sampling method, samples of waste are collected, reviewed, and measured for their major components and other key indicators. Additionally, questionnaire surveys and interviews are conducted in the township, along with investigations into existing records and other relevant information. The study adopts the solid waste management-greenhouse gas (SWM-GHG) calculator to study the township data. The case study results imply that proper waste sorting and treatment methods in villages and townships could play a major role in the reduction of carbon emission. Specifically, after implementing waste sorting in Xiao'er, annual carbon emissions were reduced by 2081 tons—equivalent to the electricity consumption of a family of three people for 1718 years, or the amount of CO2 emitted by 264 1.6L vehicles driving once around the Earth. In the optimal scenario simulation, increasing the recycling of wet waste and recyclable waste further, the level of carbon emission reduction in Xiao'er could reach up to 4482 tons per year. According to the international general carbon trade price, this is equivalent to adding 44,820 US dollars to the GDP, or to an annual saving of 5.71 million kWh. If these waste management methods are expanded to villages and townships across China, then the carbon emissions reduced in a year would be equal to the CO2 emitted from electricity generation in Beijing for over a year. Based on these findings, this paper provides three policy recommendations for effective carbon emission reduction: increasing residents' environmental protection awareness over the long term, boosting funding support and enhancing the construction of supporting facilities, and strengthening governance and institutional capacity for waste sorting and treatment.

Effective analysis and forecasting of carbon prices, which is an essential endeavor for the carbon trading market, is still considered a difficult task because of the nonlinearity and nonstationarity inherent in carbon prices. Previous studies have failed at the analysis and interval prediction of carbon prices and are limited to point forecasts. Therefore, an improved carbon price analysis and forecasting system that consists of an analysis module and a forecasting module is established in this study; more importantly, the forecasting module includes point forecasting and interval forecasting as well. Aimed at investigating the characteristics of the carbon price series, a chaotic analysis based on the maximum Lyapunov exponent is performed, the determination of appropriate distribution functions based on our newly proposed hybrid optimization algorithm is conducted, and different distribution functions are effectively designed in the analysis module. Furthermore, in the point forecasting model, the phase space reconstruction technique is applied to reconstruct the sequences decomposed by variational mode decomposition due to the chaotic characteristics of the carbon price series, and the reconstructed sequences are considered as the optimal input–output variables of the forecasting model. Then, an adaptive neuro-fuzzy inference system model is trained by the newly proposed hybrid optimization algorithm, which is developed for the first time in the domain of carbon price point forecasting. Moreover, based on the results of point forecasting and the distribution function of the carbon price series determined by the analysis module, the interval forecasting results can be obtained and implemented to provide more reliable information for decision making. Empirical results based on the carbon price data of the European Union Emissions Trading System and Shenzhen of China demonstrate that the proposed system achieves better results than other benchmark models in point forecasting as well as interval forecasting.

This paper presents a systematic literature review on carbon-constrained operations models. First, carbon constraints are defined and categorized into three genres: policy-driven, market-driven, and nature-driven. Second, business strategies for fulfilling carbon constraints are summarized and classified into three main groups: internal emissions abatement, collaborative emissions abatement, and carbon compensation. Subsequently, ten specific types of carbon-constrained operations models are studied in support of these business strategies. Lastly, the research trend is analyzed and a conceptual studying framework is proposed. The results show that the policy-driven carbon constraints are the primary carbon considerations in operations models, with the emissions trading scheme and the carbon tax taking first and second place, respectively. In addition, the focus of carbon-constrained operations models evolves from short-term to long-term strategies, from internal to collaborative abatement strategies, and from simple to more practical models. From the carbon constraint modeling perspective, future studies regarding the coexistence of multiple carbon constraints and their interactive effects might have interesting results. From the business strategy perspective, the collaborative emissions abatement models, especially horizontal co-opetition mechanisms, remain to be further explored.

The price of permits in the European Union Emissions Trading System (EU ETS) has historically been highly sensitive and prone to jumps. We consider different stochastic processes to model the price of permits, and show that the Variance Gamma (VG) model provides the best fit for the price distribution, among a selection of infinite activity processes. Using this result as a starting point, we assess the effects of the EU ETS in delivering low-carbon investments at the firm level, by modeling a price taker electricity producer subject to the EU ETS jurisdiction. We compute, via Least Squares Monte Carlo, the value of the real option the greenhouse gas emitter has, consisting in the opportunity to switch from its current high-carbon technology to a cleaner one. We use a VG specification for carbon prices, and a mean-reverting (Brennan-Schwartz) process for the price of fuel. Moreover, we further analyze the investment decision problem, in case of a CO 2 price stabilization mechanism in the form of a price floor, by explicitly computing the expected value of the investment project by means of Fourier methods. Our results show that the introduction of the price stabilization mechanism significantly affects the timing of the investment decision, and supports emission-related investments.

The Paris Agreement established a new mechanism by which a country can offset some of its emissions reductions in other countries. Its design is still under negotiation. While taking advantage of cheaper abatement opportunities enables efficiency gains, the impact on the price volatility in the emission trading schemes is unclear. We conduct an empirical analysis of the short-term impacts of these credits on the standard carbon markets, using the European Union experience with accepting credits for compliance in the second phase of its scheme. With vector-autoregressive models allowing regime changes at a priori unknown dates, we analyze the structural relationship between the prices of allowances and credits. Although one might expect that the allowance and credit markets influence one another, we find that, before November 2011, knowing the credit price variations helps to better predict the allowance price variations while, after November 2011, it is the opposite. We explain this by expectations and restrictions regarding credits. For the transmission of shocks and the impact on volatility, the influence is mainly from allowances to credits. The allowance price volatility explains between 56% and 72% of the credit volatility whereas the latter explains less than 2% of the former.

Australian climate change policy has been applied haphazardly to Australia’s electricity markets for almost two decades. Federal and state level emissions trading frameworks have been introduced and subsequently repealed. Several studies have pointed to the significant costs imposed by such policy discontinuity. This article demonstrates that the use of production subsidies has also resulted in a ‘disorderly’ transition and has broken the link between the financial incentives for decarbonisation activities and the physical needs of the electricity system. We evaluate the various options for correcting this by introducing a stable, long-term climate change policy that integrates efficiently with electricity policy objectives. By applying a broad assessment framework, we are able to establish that a market mechanism aimed at pricing the externality implied by an independently set carbon budget is the most efficient policy response.

The availability of green electricity, changes to the Emission Trading Scheme (ETS) system and technological breakthroughs will determine how the steel industry will evolve in the coming decades. The blast furnace (BF) technology will continue to dominate steel production in the coming decade and the only way to substantially reduce the associated CO2 emissions is to combine it with Carbon Capture and Utilization (CCU) and/or Carbon Capture and Storage (CCS). CCU options that do not require a lot of hydrogen and with high added value are logical step stones towards production of bulk chemicals and even fuels such as oxymethylene ethers. BF waste gas recycling and conversion will require a multisectoral approach creating new dependencies between the steel, energy, and chemical sectors. Energy efficient, cheap and CO2 free hydrogen production using green electricity is the ultimate solution to drive this transition. This hydrogen could on the long term also open the door to replace blast furnaces by hydrogen-based steel making. However, today it makes economically more sense to use thermally produced hydrogen by (bio)methane pyrolysis or steam reforming, potentially electrified and intensified, rather than from water electrolysis. Having novel and existing elements from the chemical engineers' toolbox such as artificial intelligence, catalysis and reaction engineering, process intensification principles and multiscale modeling and design, should bring these emerging technologies within reach by the end of the next decade.

Knowledge-based experts contribute to climate change policy change. However, the issue of how the role, membership, and structure of expert networks change over a policy cycle remains poorly explained, undermining the case for recognizing a dynamic and inclusive evidence base containing power. This article traces the development of a Chinese emission trading scheme and analyses the changing conditions for knowledge production, acquisition and delivery to shed light on governance. In-depth interviews with 62 experts and other actors were conducted and analyzed using a framework comprising three policy sub-processes, three drivers of change, and five groups of actors. Between 2012 and 2017, the emission trading scheme experienced three stages of development. The initial planning process utilized strategic, system-level inputs from elite experts, learning from applied research and international experience. Emerging priorities arising from policy implementation and diffusion strengthened the role of those who are well versed in the practice and/or industry and enabled broad-base participation. The study enhances our understanding of expert involvement as a continuous, dynamic, and adaptive process amenable to the developmental needs of policy. Findings can inform discussions on the implications of shifting policy priorities and needs for knowledge-producing organizations and for broadening the evidence base of policy.

This paper investigates the volatility spillover effects and dynamic correlations between China’s emissions allowances and fossil energy markets by employing the dynamic conditional correlation (DCC) generalized autoregressive conditional heteroscedasticity (GARCH) model. Thermal coal futures, South Sea crude oil and liquefied natural gas markets confirm short-term and long-term persistence on the Beijing, Shanghai, Guangdong and Shenzhen emissions allowances pilots, while those fossil energy markets demonstrate long-term persistence on Hubei’s emissions allowances pilot. The dynamic correlations between fossil energy and regional emissions allowance markets exhibit slight time-varying trends, and their dynamic correlations are at lower levels in the period considered. The prohibition of cross-region emissions allowance flow, inefficient dynamic linkage and poor price pass-through between the two markets may result in lower volatility spillover effects and dynamic correlations.

Due to lower-cost energy supplies elsewhere, Europe needs resource efficient technologies to safeguard the competitiveness of its energy-intensive industries. The technical feasibility of the CCU value chain components (carbon capture, transportation and utilization) has been widely studied in literature. However infrastructural, regulatory and business strategic issues have received less attention. A review of the relevant policies (e.g. European Emissions Trading Scheme, Renewable Fuels and Waste Directives) has been performed. Stakeholder engagement and the stakeholder influence mapping was used to examine potential climate change, circular economy, renewable energy and regional industrial development policies that can support CO2 utilization value chains. The main contribution of the paper is to outline potential benefits of policies to foster the production and uptake of CO2-derived products such as methanol, polyurethane and mineral construction aggregates. Another outcome is to illustrate the role of key policy-making stakeholders in assessing the suitability of current statutes and the impact of potential changes. An important finding was that the development of connectivity infrastructure is a key missing enabler and more attention to policy on infrastructure is required. Finally, the work examines the justification for a CO2 Utilization Directive, comparable to the Carbon Capture and Storage Directive, but considering the current complexity of the European Union (EU) policy landscape.

Cap-and-trade is regarded as the most effective approach to control and reduce greenhouse gas emission. How to perform the reallocation in a fair way is very critical to control total amount of emissions and improve trade mechanism. It has been proved that data envelopment analysis (DEA) is an effective way for reallocation. The objective of the present paper is to develop a centralized DEA model to reallocate emission permits in the cap and trade system based on countries efficiencies. Presented model considers all decision making units (DMUs) together and improves whole efficiency of them by reducing total emission permit as undesirable outputs. Also, this model determines amount of emitted gases that can be reduced without reducing other outputs. To demonstrate the applicability of model, a case study is presented. Sensitivity analysis is carried out to investigate the impact of the some parameters on the results.

Scholars and policy makers put great emphasis on analyzing the mitigation effect of an emissions trading scheme (ETS), while empirical researches on the mitigation effects of China's pilot ETSs are both thin and with significant limitations. This paper tries to analyze this issue from the perspective of industrial sub-sectors at the provincial level. We first calculate the carbon emissions of 37 individual industrial sub-sectors in each of China's 26 provinces from 2005 to 2015, covering both direct and indirect emissions. Cautiously identifying the industrial sub-sectors covered by China's pilot ETSs, we explore the causal impact of China’s pilot ETSs on reducing carbon emissions at the initial stage (2013–2015) and analyze the paths of achieved emission reductions, applying a difference-in-difference (DID) model and a combination of DID estimator and propensity score matching technique. Our results yield robust evidence that China's pilot ETSs have significantly promoted carbon emission reductions of the covered industrial sub-sectors, and this impact has presented an overall enhanced trend according to year-by-year analysis. The results also show that the pilot ETSs have failed to enable covered industrial sub-sectors to effectively cut carbon intensity and the impact on carbon intensity is not obvious in any of the first three years, and the carbon emission reductions have mainly been achieved through the decreased outputs of industrial sub-sectors. China's policy makers should tighten the free allowance allocation approaches in order to facilitate low-carbon technology innovations and reduce carbon intensity of industrial sectors.

In this paper, an analysis of the integration of a carbon capture unit and a power to fuel system for methanol synthesis with a coal power plant is presented from the energetic, environmental and economic standpoints. The study is carried out in three different sections. In the first part, the impact of the integration of a carbon capture system (CCS) and of a power to fuel plant (PtF) for methanol production is investigated in terms of plant average efficiency, fuel consumption, CO2 emissions. In the second part, the annual fixed and variable costs of the power plant, and the annual cost of electricity (COE) are assessed for different plant configurations. Additionally, future scenarios are analyzed considering the impact of European policies on the CO2 emission’s cost, defined by the European Emission Trading System (ETS). Finally, an economic feasibility analysis of the power to fuel plant is performed and the methanol production is evaluated. Moreover, a sensitivity analysis is carried out to evaluate the impact of the most affecting parameters (electrical energy cost, the methanol selling price and the capital cost of the electrolyzer) in terms of Internal Rate of Return (IRR).

The global shipping industry contributes a significant part of global greenhouse gas (GHG) and atmospheric pollutant emissions, which would cause serious problems to environment and residents’ health in coastal areas. Shore Side Electricity (SSE) is an efficient energy means for CO2 emission reduction worldwide. However, enormous initial investment, high electricity sale price and charging caused delays set the barriers for the implementation of SSE. This paper proposes a framework for assessing the economic feasibility of SSE investment considering environmental and techno-economic factors. Besides, carbon trading is also integrated in this framework to improve the profitability of SSE investment. Finally, the Port of Shanghai is selected for case study, and 3 scenarios are designed to investigate the economic viability. Results indicate that the income of reduced CO2 emission trading only contributes a little to the overall income, and the port needs to make profits through electricity sale in order to avoid great financial losses. Besides, a more radical investment plan could have better financial performance and more CO2 emission reduction for the port. The conclusions can facilitate policy makers to make SSE promotion policies, that providing subsidies on electricity price may be more useful than just financing the facilities’ implementation.

In this paper we consider, from an environmental policy-maker perspective, how carbon reduction policies impact the economic competitiveness of the manufacturing sector. Specifically, we focus on flowshop scheduling – which typically aims to minimize makespan for purely economic objectives – and consider how three common carbon reduction policies – namely, taxes on emissions, baselines on emissions, and emissions trading schemes – can create competitive green flowshops that balance minimization of makespan and carbon emissions. The goal is to enable policy-makers to understand how to set policies and control parameters to achieve environmental objectives while ensuring global economic competitiveness of industry. We initially present a set of mixed-integer linear programming (MILP) models for flowshop scheduling problems operating in a regulated environment in which each carbon reduction policy is adopted. We then introduce a bi-objective scheduling framework for the corresponding problem to obtain alternative solutions under each policy. These models and their computational results however, are not the main focus of the study, but are presented as a means to demonstrate how green policies co-exist with economic objectives, with policy-makers in control of the balance. To this end, based on financial data from Australia’s carbon emissions profile, we provide a policy-oriented analysis of the models, and some managerial insights into the effect of scheduling strategies on carbon emissions under different reduction policies. These insights offer support to both environmental policy-makers and corporate production and sustainability managers to determine whether it is technically feasible and profitable to replace traditional scheduling strategies with environmentally friendly scheduling strategies.

Motivated by a unique legislative practice targeted at increasing new energy vehicles consumption with carbon regulation in China, we study how the program works and how the manufacturer responds. Different from former cash subsidies provided for the buyers, this program intends to stimulate the consumption of green vehicles on the manufacturer side. In this paper, a product differential model on traditional gasoline vehicles (GVs) and new energy vehicles (EVs) is analyzed within a cap and trade regulation system with carbon quota solely provided for EVs. We first examine the effectiveness of carbon regulation program under the case when the manufacturer focuses on primary consumer segment, and the optimal pricing and production strategies are derived. Then, we investigate the firm’s strategic decision of whether or not to enter the replacement market with limited total carbon emission. We have the following main findings. (1) Results show that with the increase in carbon quota for EVs, both the market share of EVs and the manufacturer’s profit increase. However, the change of total consumer surplus is not certain; (2) In this new cap and trade system, with a larger market coverage, the development of a trade old-for-new market brings a greater firm profit which is not affected by the total emission cap. We also find that consumers’ green preference is positive on increasing the demand of EVs, while it is uncertain on the firm’s profit; (3) Importantly, we find that when the carbon quota of new energy vehicles is below a threshold, as the carbon price increases, the demand for GVs increases while the demand for EVs decreases. Therefore, in the formulation of the carbon allowance carbon policy, the impact of carbon price should be fully considered.

Global warming has become one of the most popular topics on this planet in the past decades, since it is the challenge that needs the efforts from the whole mankind. Maritime transportation, which carries more than 90% of the global trade, plays a critical role in the contribution of green house gases (GHGs) emission. Unfortunately, the GHGs emitted by the global fleet still falls outside the emission reduction scheme established by the Kyoto Protocol. Alternative solutions are therefore strongly desired. Several market-based measures are proposed and submitted to IMO for discussion and evaluation. In this paper, we choose to focus on one of these measures, namely Maritime Emissions Trading Scheme (METS). An optimization model integrating the classical fleet composition and deployment problem with the application of ETS (global or regional) is proposed. This model is used as a tool to study the actual impact of METS on fleet operation and corresponding CO2 emission. The results of the computational study suggest that in the short term the implementation of METS may not guarantee further emission reduction in certain scenarios. However, in other scenarios with low bunker price, high allowance cost or global METS coverage, a more significant CO2 decrease in the short term can be expected.

In the context of cap-and-trade regulation, this paper develops the models of evolutionary game between governments and manufacturers, and analyzes the impacts of government policy on the decisions of manufacturers and the dynamic tendency of cap-and-trade market. It investigates the impacts of government policies on carbon trading market under two scenarios: the static carbon trading price and the dynamic carbon trading price. Under dynamic carbon trading price, the equilibrium strategy of the evolutionary game can be obtained. Then a numerical example is examined with system dynamics simulation. It is shown that, when governments implement the static carbon trading price, the evolutionary game cannot reach the stability. Under the dynamic carbon trading price, the evolutionary game has the evolutionary stable strategy. Dynamic carbon trading pricing policy is effective in accelerating the carbon reduction. Moreover, the probability of manufacturers introducing green technology is negatively correlated with governmental intervention costs and positively correlated with governmental penalty for manufacturers’ speculations.

In response to the rapid growth of environmental problems related to air transportation including emissions and noise, aviation authorities and industries have implemented stricter environmental regulations and targets in the early 2000s to encourage airlines to become greener. Different emission mitigation measures to achieve these targets have been developed. This study introduces a new mitigation measure. In addition to minimizing the total cost of flow and establishing hubs, the measure aims at minimizing the greenhouse gas emissions, fuel consumption and noise in the design of airline hub-and-spoke network. We develop a multi-objective mixed integer-programming model and use several methodologies to determine the best design. Our computational results are based on the CAB data set for the domestic US aviation sector. For assessing the value of the new mitigation measure, we develop cumulative marginal abatement cost curves for reducing the projected annual CO 2 emissions from 2020 to 2050 for the domestic US air transportation. Our results indicate that using the new measure can cost-effectively decrease the projected cumulative (2020–2050) CO 2 emissions by more than 250 and 200 million tonnes relative to the classical model, which relies on minimizing the total cost of flow and opening hubs only. We conclude that the new measure not only provides a practical solution for the airlines facing high fuel cost, emission trading schemes or carbon tax systems but it can also play an important role in achieving sustainable and environmental-friendly targets.

This paper discusses different decarbonisation scenarios for an existing district heating (DH) network supplied by coal-fired combined heat and power plants in Germany. Integrating higher shares of renewable heat is indispensable in reaching the climate goal and CO2 emission reduction targets. The study analyses the technical and economic aspects of integrating various technologies such as solar thermal, biomass boilers, waste incineration plant and heat pumps into the existing DH network, with the main focus on large-scale heat pumps. The approach consists of two main steps. First, we forecast future heat demand and the potential to extend the DH system by simulating the evolution and energy consumption of the city's building stock. Second, we use a supply dispatch model with hourly resolution to calculate alternative scenarios and sensitivities for the supply mix with a focus on heat pumps. Our results show that, under the current regulatory and economic framework, large-scale heat pumps are not cost competitive with the existing coal-fired CHP units. However, redesigning the regulatory framework and optimising heat pump design and operation could achieve cost parity. The CO2 price induced by the EU emissions trading scheme will most likely not be a sufficient incentive in short and medium term.

Market-based mechanisms, especially emission trading schemes, are proposed as a means to control system-wide aviation emissions. Although auctioning has gained some recent popularity, free allocation of emission allowances is still favored by many to incentivize airlines’ participation in the outset of an emission trading program. However, current methods for free allocation – grandfathering method and benchmarking method – have their limitations, such as placing heavy workload on regulators and a lack of transparency and flexibility. To overcome some of the limitations, this paper proposes a multi-stakeholder dynamic optimization method from a system-of-systems perspective. The method delegates part of the regulators’ responsibility to airlines, and grants airlines flexibility to plan, negotiate, and request for emission allowances. The inclusion of the regulators’ allowance allocation decision-making and airlines’ fleet allocation decision-making ensures a holistic understanding of the problem. Specifically, the method combines transfer contract coordination mechanism and approximate dynamic programming to coordinate the allowance consumption between the participants. We apply the method to a ten-route air transportation network where two representative airlines compete for the allowances. The results demonstrate that the total network-wise profit from each airline’s independent decisions can approach the globally efficient solution in an ideal centralized case without violating the emission constraint.

Carbon emission verification is one of the key factors required for proper implementation of a cap-and-trade (C&T) system. However, to obtain more revenue, emission generating companies (GCs) may collude with third-party verifiers (3 PVs) and conceal real carbon emission data. Based on actual practice of Shenzhen's C&T system, a three-player game model has been devised in this paper to analyze the behaviors among GCs, 3 PVs and government. Given the government's current piecewise linear re-verification policy, the optimal reported carbon intensity for GCs has been provided. Our research reveals that if the actual carbon intensity is larger than historical carbon intensity GCs may report less carbon intensity and conceal actual carbon emission. To deal with this issue, a new exponential re-verification policy is proposed. Based on authentic data from Shenzhen's C&T system, the experimental results show that the government should devote more attention to GCs with a decreasing industrial product output value-added (IVA) than to those with high carbon emissions when selecting GCs for re-verification. Our experiments also illustrate that the new policy outperforms the current one on both total concealed amount of carbon emission and total re-verification cost if the initial re-verification probability is set within a specific range.

Europe 2020 strategy highlighted that sustainable consumption and production requires resource and energy efficiency. In terms of sustainability in energy, carbon footprint, conservation, efficient energy use, and emissions trading are some major concerns. Under the Kyoto Protocol, a trading market mechanism is developed as a policy of reducing the emissions of greenhouse gases in each country. Firms are always considering whether the investment cost on emission reduction matches the benefit. One possible practice is to look for energy savings that are able to offset additional costs from the sustainability investment. This paper aims to establish such a sustainability investment decision model, which uses dynamic programming for solutions to minimize cost. The purpose is to effectively reduce emissions produced during production through investment in energy-saving, high productivity equipment and allocation of production capacity considering emissions (or so-called carbon) trading market price, greenhouse gas emission credits or caps given by the government, inventory cost, and production cost. Management-oriented implications are proposed following analysis of the results of detailed numerical examples.

This paper argues that attempts to transform Australia's urban environment into a sufficiently sustainable one has been misdirected. The ‘green rating tool,’ industry's adherence to relevant standards and governmental policies represent the primary means of effecting the sustainability transition. However, only high-profile commercial building owners seem interested in being green-rated; the actual end-users of buildings are far less committed (e.g. employees ensconced in commercial buildings and residential home occupiers). Through a systematic review of 103 journal articles published on the topic of end-users and sustainability transition, original findings are presented. The findings reveal that most residential end-users do not purchase green homes and without their ‘buy-in,’ sustainability transition across Australia will continue to fail. This paper offers a critical analysis of the status-quo, identifying where the effort to generate a sustainable urban environment has been misdirected, what challenges prevail, and why residential end-users have been overlooked. In looking for a way forward that engages end-users, the paper proposes that financial incentives for the purchase of low-carbon buildings must be introduced into the residential real-estate market. And the modeling for this rebate is discussed in terms of emissions trading schemes or carbon tax.

We investigate the bidirectional interactions between trading behaviors and carbon prices in the first carbon market, i.e., European Union Emissions Trading Scheme (EU ETS). The trading behaviors of the emitting companies are classified into ‘compliance trading’ and ‘non-compliance trading’ based on their positions, and the behaviors of financial intermediaries are quantified according to the changes in their inventories. We use two AR-EGARCH models and an ARMA-GARCH model to assess the bidirectional interactions between trading behaviors and carbon prices, and three empirical findings are derived. First, since emitting companies can predict their actual demand of a complete phase, ‘compliance trading’ is not affected by the annual nominal compliance demand of allowances, while ‘non-compliance trading’ is influenced by financial intermediaries' inventories and ‘compliance trading’. Second, the allowance prices do have asymmetry effects on the volatilities of emitting companies' trading behaviors. Third, ‘compliance trading’ and the inventories of the financial intermediaries explain the trend of carbon prices, while ‘non-compliance trading’ explains the volatility of carbon prices. The findings could provide valuable managerial implications for managing the carbon markets.

China is introducing a national carbon emission trading system (ETS), with details yet to be finalized. The ETS is expected to cover only the major emitters but it is often argued that a more comprehensive system will achieve the emission goals at lower cost. We first examine an ETS that covers both electricity and cement sectors and consider an ambitious cap starting in 2017 that will meet the official objective to reduce the carbon-GDP intensity by 60–65% by 2030 compared to 2005 levels. The two ETS-covered industries are compensated with an output-based subsidy to represent the intention to give free permits to the covered enterprises. We then consider a hybrid system where the non-ETS sectors pay a carbon tax and share in the CO2 reduction burden. Our simulations indicate that hybrid systems will achieve the same CO2 goals with lower permit prices and GDP losses. We also show how auctioning of the permits improves the efficiency of the ETS and the hybrid systems. Finally, we find that these CO2 control policies are progressive in that higher income households bear a bigger burden.

The establishment of an emissions trading scheme (ETS) in China creates the potential for a “least cost” solution for achieving the greenhouse gas (GHG) emissions reductions required for China to meet its Paris Agreement pledges. China has pledged to reduce CO 2 intensity by 60–65% in 2030 relative to 2005 and to stop the increase in absolute CO 2 emissions around 2030. In this series of studies, we enhance the MIT Economic Projection and Policy Analysis (EPPA) model to include the latest assessments of the costs of power generation technologies in China to evaluate the impacts of different potential ETS pathways on deployment of carbon capture and storage (CCS) technology. This paper reports the results from baseline scenarios where power generation prices are assumed to be homogeneous across the country for a given mode of generation. We find that there are different pathways where CCS might play an important role in reducing the emission intensity in China's electricity sector, especially for low carbon intensity targets consistent with the ultimate goals of the Paris Agreement. Uncertainty about the exact technology mix suggests that decision makers should be wary of picking winning technologies, and should instead seek to provide incentives for emission reductions. While it will be challenging to meet the CO 2 intensity target of 550 g/kWh for the electric power sector by 2020, multiple pathways exist for achieving lower targets over a longer timeframe. Our initial analysis shows that carbon prices of 35–40$/tCO 2 make CCS technologies on coal-based generation cost-competitive against other modes of generation and that carbon prices higher than 100$/tCO 2 favor a major expansion of CCS. The next step is to confirm these initial results with more detailed modeling that takes into account granularity across China's energy sector at the provincial level.

This study exploits the incomplete participation requirements of the European Union Emissions Trading System (EU ETS) to investigate the policy's causal effect on outward foreign direct investment (FDI) decisions of German multinational firms. Using a combination of difference-in-differences with bias-corrected matching, our baseline specification indicates that the sample average treatment effect is very small and levels out at −0.2%, but its standard error is large (0.16). Looking at a sub-sample of firms which can be considered as geographically more mobile because they are supposedly less capital-intensive, we find that a small number of EU ETS regulated firms have increased their FDI outside the EU by 52 % ± 47 % compared to a counterfactual scenario. Paradoxically, relocating firms neither operate in the targeted energy-intensive sectors, nor are they emission-intensive. The small emissions share of these footloose firms indeed indicates a limited potential for policy-induced leakage of emissions. On the extensive margin, we find that all EU ETS firms on average have increased the number of their affiliates outside the EU by 28 % ± 24 % relative to control firms. This causal change in network structures of multinational firms outside the EU is suggestive of endeavors undertaken by regulated firms to facilitate relocations in the future.

It is widely accepted that the firms included in an emissions trading scheme (ETS) come mostly from oligopolistic industries. The “exclusionary manipulation” of these heterogeneous emitters can distort both output and permit markets and lead to differences in abatement technology adoption. We studied the impacts of asymmetric firms' market power on the diffusion of abatement technologies. A model for technology adoption among heterogeneous firms has been established, which takes into account diversity in production capacity and the integration of firms' strategic behaviour in both the carbon permit and the output markets. Our model reveals that, considering the direct and strategic effects in adoption benefits, firms' production capacity can directly determine their sequence order of adoption, and their market power can accelerate the diffusion of a new abatement technology. A case study of an energy-intensive sector in China is illustrated to support the conclusions derived from the model and help policymakers better understand the diffusion of abatement technologies under imperfect market structure.

Summarization: This study analyses the profitability of firms participating in the European Union Emissions Trading Scheme during the period from 2006 to 2014, covering the three phases of the scheme. The analysis covers a large dataset from 19 European Union countries and with five different modelling specifications. The examined models use firm-specific attributes, country-level data about the economic environment and energy-related characteristics. In particular, the influences of time/firm/country characteristics on profitability are examined by performing cross-classified multilevel modelling. The empirical results show that both economic and energy-related variables significantly influence firms' profitability. Measures such as reducing environmental impacts (verified emissions and allowances allocated) or increasing energy efficiency should be taken into consideration in decision-making for the firm's profitability improvement. Παρουσιάστηκε στο: Energy Policy

Several industries locate a pre-assigned number of facilities in order to determine a transportation way for optimizing the objective functions simultaneously. The multi-objective transportation-p-facility location problem is an optimization based model to integrate the facility location problem and the transportation problem under the multi-objective environment. This study delineates the stated formulation in which we need to seek the locations of p-facilities in the Euclidean plane, and the amounts of transported products so that the total transportation cost, transportation time, and carbon emission cost from existing sites to p-facilities will be minimized. In fact, variable carbon emission under carbon tax, cap and trade regulation is considered due to the locations of p-facilities and the amounts of transported flow. Thereafter, a hybrid approach is improved based on an alternating locate-allocate heuristic and the neutrosophic compromise programming to obtain the non-dominated solution. Additionally, the performance of our findings are evaluated by an application example. Furthermore, a sensitivity analysis is incorporated to explore the resiliency of the designed model. Finally, conclusions and further research areas conclude the paper.

This study utilizes the data envelopment analysis technique with materials balance condition to evaluate the inherent trade-offs between environmental and cost outcomes among different types of energy consumptions in China’s construction industry. Environmental and cost efficiency that is decomposed into technical efficiency and allocative efficiency are estimated, and the possible environmental impact and economic cost of reallocating energy inputs for improving efficiency are obtained. The estimation results show that: i) China’s construction industry has the ability to produce its current level of industrial added value with fewer CO2 emissions and fewer energy input cost through removing technical inefficiency and adjusting energy consumption structure. ii) There are 31.9% and 6.1% reduction potentials on CO2 emissions if this industry attained the most environmentally efficient and the most costly efficient situation, respectively. iii) The average shadow cost of CO2 emissions reduction in this industry is very low, suggesting that it should control CO2 emissions through optimizing energy consumption structure and improving energy efficiency, instead of relying on end-of-pipe emission abatement technologies or emission trading systems.