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This study delves into the nexus between the efficiency of carbon emission allocation and the efficiency of green development within the context of innovative city construction. Leveraging data from 283 prefecture-level cities and corresponding provincial-level panel data spanning the period from 2005 to 2019 in mainland China, the research employs the zero-sum gain DEA model to compute provincial carbon emission allocation efficiency and allocate allowances. Furthermore, it utilizes the all-factor non-radial directional distance function and the SBM-DEA model to gauge the green development efficiency of prefecture-level cities. The double-difference method is applied to evaluate the impact of innovative city construction on regional green development efficiency. The results indicate that an imbalance between carbon emission allocation efficiency and emission quotas detrimentally affects urban green development. However, technological progress, factor accumulation, and the institutional environment associated with innovative city building mitigate this negative impact. Heterogeneity analysis reveals a differentiated effect of innovative city building on regional green development efficiency. This paper not only explores the concept of achieving an equitable distribution of carbon emission allowances but also examines how innovative city building influences regional green development. By establishing connections between urban policies, the equitable distribution of carbon emission allowances, and regional green development, it introduces a new perspective for promoting high-quality development at the regional level. [ABSTRACT FROM AUTHOR]

Green finance is a financial innovation that directs capital allocation towards green industries. How will this affect regional carbon emissions? Based on the data on green finance and carbon emissions of 30 provinces in China from 2008 to 2019, this paper employs a multivariate linear regression model and a spatial econometric model to empirically study the impact of green finance on carbon emissions. The results find that (1) green finance significantly reduces provincial carbon emissions, specifically through promoting a cleaner energy structure and an advanced industrial structure, as well as improving the quality of green innovation. (2) Heterogeneity exists between regions. In eastern regions and areas characterized by high levels of marketization and minimal fiscal pressure, the role of green finance in promoting provincial carbon emission reduction is more pronounced. (3) Spatial econometric analysis found that green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. Specifically, the flow of green resources and green ideas between provinces facilitates the formation of regional radiation, while green competition generates a siphon effect on neighboring regions. These findings provide some meaningful policy implications to achieve China's dual-carbon goal by promoting green finance. • Green finance has significantly reduced China's provincial carbon emissions. • The upgrading of energy structure and industrial structure is a positive channel to reduce carbon emissions. • Green innovation strengthens the carbon reduction effect of green finance, but reveals the potential "greenwashing". • Green finance has a significant spatial spillover effect on carbon reduction in adjacent regions. • Policymakers should develop flexible, dynamic and coordinated green finance development policies. [ABSTRACT FROM AUTHOR]

Under the goal of "carbon peaking" and "carbon neutrality" in China, it is significant to explore whether emission reduction commitments contribute to carbon risk premium. Therefore, based on a sample of Chinese listed companies that publicly disclosed questionnaires in the CDP from 2009 to 2021, this paper empirically examines the relationship between emission reduction commitments and carbon risk premium and their formation mechanism. The results show that emission reduction commitments can effectively hedge the carbon risk premium, which pass several robustness tests. Specifically, the more comprehensive and ambitious the commitment is, the greater the suppression of the carbon risk premium. The mechanism test shows that disclosing emission reduction commitment information can reduce carbon risk by improving investor confidence and attracting political resources. Differences in enterprise emission levels, regional environmental regulation intensity and green financial development result in different risk-hedging effects of emission reduction commitments. Moreover, the greater the substantial pressure from stakeholders, the greater the tendency for firms to set up emission reduction commitments. Finally, the heterogeneity analysis reveals that confidence level of commitments has a significant impact on risk premium. Specifically, enterprises with SBTi validation, higher CDP ratings and higher target completion are more helpful in curbing carbon risk premium. Our findings contribute to corporate commitment to climate change and complement the carbon risk premium hypothesis. [Display omitted] The possible highlights of this study are as follows. • With the help of forward-looking information on emission reduction commitments, we re-examine the conclusion of the carbon risk premium and find that emission reduction commitments can effectively hedge the risk premium, enriching and developing the carbon risk premium hypothesis • This paper brings commitment levels and carbon emission levels into a unified analytical framework to study the correspondence between emission reduction commitments made under pressure to reduce emissions and the carbon risk premium, providing micro evidence for solving the mystery of the carbon risk premium. • Measure emission reduction commitment indicators from various angles, making the data on emission reduction commitments more objective and scientific. [ABSTRACT FROM AUTHOR]

This paper aims to study the significance of China's Industrial Structure Rationalization (ISR) in reducing carbon emissions. To this end, this study uses panel data from 30 Chinese province from 2000 to 2019 to measure the Industrial Structure Rationalization of each province by calculating the Thiel index, base on which a nonlinear autoregressive lagged distribution (NARDL-PMG) model is established to explore the impacts of industrial structure rationalization on carbon emissions. The results show that: (1) There still exist significant regional differences between Eastern and Central-Western regions in industrial structure as illustrated by the ISR index. The industrial structure in Eastern region is more rational; (2) In the long run, the carbon emission in China will drop when the industrial structure becomes more rational; (3) However, in the short run, the carbon emission in China will increase when the industrial structure becomes more rational. Besides the findings above, the major difference between this paper and the extant researches is that this paper pays attention to the relationship between industrial structure rationalization and environmental quality by investigating the asymmetric influences of industrial structure rationalization index's positive and negative shocks on carbon emission, which lays solid foundations for government aiming to set more detailed policies. • Focus on the impact of rationalization of industrial structure on CO2 emissions. • Focused on the linear relationship between industrial structure and carbon emissions. • Attempts to analyze three regional pairs from the East, Central and West regions. • Provide a reference for developing countries to achieve sustainable development. [ABSTRACT FROM AUTHOR]

Big data industry development and carbon dioxide emissions reduction are the crucial driver and objective functions of economic growth, respectively. Whether the two types of corresponding policies can achieve the "win-win" effect is the key to green development transformation in the future. However, little attention has been paid to the influence of big data industry development on carbon dioxide emissions. Based on the quasi-natural experiment in China's national big data comprehensive experimental area, the paper identifies the causal effect between big data industry development and carbon dioxide emissions. Specifically, the panel data of 282 cities in China spanning from 2010 to 2019 are used in regression analysis. The study reveals that the big data industry development has a substantial impact in reducing carbon dioxide emissions. Meanwhile, the findings are confirmed by a set of rigorous robustness checks. The heterogeneity analyses suggest that the effect of inhibiting carbon dioxide emissions due to the big data industry development is more significant in eastern & central China, and large-sized cities. In addition, the big data industry reduces carbon dioxide emissions through the effects of industrial structure optimization, technological innovation, and resource allocation. Our findings contribute to the nexus between big data industry development and carbon dioxide emissions. In light of these findings, the paper recommends that governments integrate economic growth and environmental protection policies by promoting big data industry development. • The paper provides a novel insight into the CO 2 emission from the perspective of big data industry. • Based on quasi-natural experiment, the paper has identified the causal effect between the big data industry development and CO 2 emissions with the Difference-in-Difference (DID) methodology. • Big data industry development effectively stimulate the reduction of CO 2 emissions. [ABSTRACT FROM AUTHOR]

The comprehensive cohesion of the digital economy, structural deviation adjustment, and green development is a crucial step towards promoting high-quality economic growth and realizing carbon peak and carbon neutrality. This paper probes the impact of intra- and inter-regional digital economy on carbon emissions, considering the mediating effect of structural deviation, utilizing panel data from 267 prefecture-level cities in China spanning the years 2011–2019. The findings reveal the following key insights. First, the connection between the digital economy and carbon emissions within cities follows an inverted "U" shape. In the early stages, the digital economy leads to an average increase in carbon emissions of 0.069%. However, in the later stages, the digitized economy markedly decrease emissions. Second, both the digital economy and carbon emissions exhibit spatial spillover effects. Within the region, DE has a significant nonlinear spillover effect on CO 2 emissions in the neighboring regions, with the spatial decay boundary of this effect extending up to 380 km. Third, analysis of the impact mechanism reveals that the digital economy mitigates local and neighboring carbon dioxide emissions by adjusting structural deviation. Heterogeneity analysis indicates that the digital economy is more likely to have a carbon emission reduction effect in cities that are not involved in the industrial transfer and those that do not belong to the old industrial base. These findings provide a rationale and policy reference for China to harness the opportunities presented by digital economy development and to achieve the "dual-carbon" goal. [ABSTRACT FROM AUTHOR]

Despite ecotourism certification's efficacy as a potential environmental management tool for promoting sustainable development, the applicability of Western ecotourism certification patterns in China and the environmental effects of China's ecotourism certification remain unclear. Based on China's Prototype-zone of National Ecotourism Attractions (PNEA) certification, this paper aims to provide empirical evidence on the causal relationship between ecotourism and low-carbon sustainable development in relation to public environmental concerns. The multiperiod Difference-in-Differences (DID) model is set up to examine the supervision of PNEA certification on regional carbon emissions based on the panel data from 285 Chinese prefecture-level cities in 2011–2017. Results demonstrate that PNEA approval can reduce regional carbon emissions by 1.1% per capita, and this effect would increase over time. Heterogeneity analysis shows that the carbon emission reduction impact is significantly higher on midwestern cities, resource-dependent cities, and cities with net population inflow. Furthermore, the determinants of public environmental concerns, such as PNEA's functions of tourism economic development and environmental education, are crucial for low-carbon sustainable development. The findings quite clearly account for the contributions of ecotourism certification in promoting sustainable development and the benefits of effective policy instruments. • The PNEA certification implemented by China's central government is different from the Western ecotourism certifications. • The approval of China's unique ecotourism certification can reduce regional carbon emissions by 1.1% per capita. • The economic development function and environmental education function are key to promoting public environmental concerns. [ABSTRACT FROM AUTHOR]

Under the goal of "carbon peaking" and "carbon neutrality" in China, it is significant to explore whether green finance contributes to carbon emission reduction. Therefore, based on the panel data of 30 provinces in China from 2005 to 2020, this paper empirically examines the impact of green finance on carbon emissions and its mechanism using the FE model, GMM model, DID, and the mediating effect model. Results find that green finance can significantly promote carbon emissions reduction, and this promotion remains still after robustness tests. The heterogeneity analysis shows that green finance's carbon emission reduction effect is more significant in developed and western regions. Moreover, the results of policy intervention effects confirm that green finance reform and innovation pilot zones (GFRIs) for carbon emission reduction are more pronounced than in other regions. Finally, the mediating effects reveal that industrial structure and green innovation are the core transmission channels through which green finance influences carbon emission reduction. These findings offer meaningful implications for formulating reasonable carbon emission reduction plans and determining the future development direction of green finance. [ABSTRACT FROM AUTHOR]

The construction industry is one of the most energy-intensive industries in China, which contributes to high carbon emissions and hinders efforts to reduce the emissions. The high energy consumption and emission have seriously constrained the growth of low carbon economy in China's construction industry. And reducing the carbon emission from construction industry (CECI) has become the key to sustainable development and the achievement of "double carbon target". The paper firstly decomposes the main influencing factors and calculates their effects by LMDI model. Then, the Tapio decoupling index is used to explore the decoupling relationship between carbon emissions and economic output. Finally, the spatial-temporal evolution of carbon emissions is analyzed through spatial autocorrelation theory. The results show that the carbon emissions from construction industry are highly increased by the construction employment rate (EM), and may be reduced by the energy intensity (EI) and carbon emission efficiency (CI). And the regions with better decoupling status are the eastern and central regions, which have relatively developed construction industry. Moreover, the spatial-temporal characteristic of carbon emissions is "high in the east and low in the west, high in the south and low in the north," showing obviously regional differences. [Display omitted] • Factors about production technology are taken into account, reflecting the characteristics of the construction industry. • Developed regions have better decoupling potential and more responsibility for CO 2. • The spatial distribution is "high in the east and low in the west, high in the south and low in the north". • The provinces in a region have similar decoupling status and carbon emission distribution. [ABSTRACT FROM AUTHOR]

To address the global challenge of climate change and achieve sustainable development, decarbonizing the electric power system in China is considered the most imperative since the power sector is highly related to the decarbonization of other sectors. Significantly, China faces the dual challenges of rapidly growing electricity demand coupling with its commitment to of emission mitigation. This study examines the low-carbon transition and sustainable development of China's power system through 2035 using a multi-stage mixed-integer linear programming generation planning model by matching future demand growth trajectories with the least-cost power supply path. The electric power installed capacity, power generation, carbon emission, power-generating cost, and abatement potentials are analyzed through various scenarios. It is found that China's electricity demand will reach 9800–13300 Terawatt-hours in 2035 due to rapid electrification. Every 1 TWh increase in electricity demand requires 0.41–0.53 GW of newly installed capacity. Reducing the proportion of coal-fired power generation and replacing it with renewable energy is inevitable. However, for every 1 GW of coal power retired, 3.7 GW of renewable energy needs to be built. Incorporating electricity demand-side management is crucial to developing an effective decarbonization pathway for China's power sector, along with inclusive policies and technologies to meet China's requirements for dependable, affordable, and sustainable electricity. The results of this paper can provide a reference for policy makers in China as well as other emerging economies. • China's electricity consumption will continue to rise until 2035 and China will reach emission peak of power sector before 2030. • Meeting China's decarbonization requires gradually reducing coal-fired power capacity by up to the year 2020's 40.5% ty. • Every 1 GW of coal-power retirement requires the construction of 3.7 GW of renewable power capacity. • Demand-side management is crucial to easing high electricity demands for an effective power decarbonization trajectory in China. [ABSTRACT FROM AUTHOR]

Low-carbon manufacturing is an emerging industrial trend and an important way to achieve sustainable development. As the country with the largest manufacturing scale and carbon dioxide emissions, it is of great practical and theoretical significance to study China's low-carbon manufacturing issues. Based on the ternary analysis perspective of simmelian tie, this paper chooses to identify the influencing factors through the technology-organization-environment research framework, and derives the pathways of low-carbon manufacturing through the fuzzy-set qualitative comparative analysis method. The research results show that: (1) Under the low-carbon manufacturing goal, stable industrial chain structure and policy-sensitive are the formation reasons for the simmelian tie. (2) From the perspective of simmelian tie, low-carbon manufacturing will be influenced by the driving role of green technological advances, the supporting role of organizational strategies, and the regulatory role of the policy environment. (3) Manufacturing enterprises' low-carbon pathways are directly related to their industrial chain position. Compared with upstream enterprises, downstream enterprises have more diverse low-carbon manufacturing pathways. (4) Active governmental support can more effectively promote the realization of low-carbon manufacturing than environmental pressure. [Display omitted] [ABSTRACT FROM AUTHOR]

As the climate is warming up and climate disasters occur more frequently, China's carbon peak and carbon neutrality targets are gaining attention, with provinces starting to set carbon peak targets and constantly exploring low carbon economic development opportunities. However, the existing evaluation index system mainly focuses on low carbon cities and green cities, and there is no evaluation index system for carbon peak and carbon neutrality. This study adopts a combination of theoretical and empirical research and draws on domestic and international research results to construct the first index system for evaluating China's provincial carbon peak and carbon neutrality. The evaluation index system includes 18 indicators from three dimensions: climate ambition, low carbon status, and emissions trends. Using this index system, we calculated the carbon peak and carbon neutrality indices of 30 Chinese provinces. Further, the 30 provinces were classified into six categories, and corresponding policy recommendations for achieving the "Dual carbon" targets were put forward. The evaluation index system constructed in this paper can provide a reference for future carbon peak and carbon neutrality assessments. By disclosing the integrated index of each province, we hope to effectively curb the increasing local carbon emissions; avert inaction in areas with good natural endowments; and motivate the advancement of the latter, to boost the implementation of the "Dual carbon" targets coherently for the whole country. [Display omitted] • An integrated evaluation system on China's Provincial "Dual carbon" was proposed. • 30 provinces in mainland China were ranked based on the integrated index. • 6 groups were classified to show provincial differences on dual carbon performance. • Policy recommendations to fulfill China's climate commitment were put forward. [ABSTRACT FROM AUTHOR]

"Carbon Peaking and Carbon Neutrality" is one of the important tasks of China's current and future economic construction and development, but the carbon emission reduction effect of High-speed rail (HSR) has not yet been fully studied. In this paper, based on the panel data of 274 cities in China from 2003 to 2016, we take the opening of HSR in the cities as a "Quasi-natural Experiment", and construct the Multi-period Difference-in-Difference Model to explore whether the opening of HSR can reduce carbon emissions of cities along the route, and use the mediating effect model and moderating effect model to further analyze its internal mechanisms. We find that:①The opening of HSR can significantly reduce the carbon emissions of cities along the route, and the opening of HSR in a city will reduce the carbon emissions of the city by about 2.4% on average, and this carbon emission reduction effect usually manifests significantly in the first year after the opening of HSR, and increases year by year thereafter.②The mechanism test shows that the traffic substitution effect, the optimization of the industrial structure and the promotion of economic agglomeration have partial mediating effect on the influence between the opening of HSR and urban carbon emissions. In addition, the increase in the intensity of government environmental regulations can strengthen the effect of the opening of HSR on reducing urban carbon emissions.③The regional heterogeneity research shows that the opening of HSR has a more significant impact on the carbon emissions of cities in the eastern coastal region and western region of China. Moreover, in the western region, the reduction effect of the opening of HSR on carbon emissions is only reflected in the key cities rather than ordinary prefecture-level cities. This paper provides certain reference significance for promoting low-carbon and green economy and helping China to achieve the "Carbon Neutrality" climate action goal. [ABSTRACT FROM AUTHOR]

Controlling carbon emissions and sustaining growth constitute essential concerns in the post-financial crisis era combined with low-carbon sustainable development. However, the impact of financial development on carbon emissions remains controversial and lacks mechanisms investigation covering finance spatial attributes. Relying on China province's data during 2005–2019, this paper contributes to the literature by constructing multi-spatial models to investigate how financial geo-density mitigates carbon emission intensity and explore the spatial transmission mechanisms. The results reveal that there is a balance between financial geo-density and carbon emission intensity. The intrinsic mechanisms include: (1) raising financial geo-density is accompanied by the law of marginal diminishing carbon emission intensity tendency; (2) high financial geo-density accelerates technological innovation and industrial structure upgrading, thereby decreasing carbon emission intensity, but drives industrial-scale expansion, thereby increasing carbon emission intensity; and (3) financial institution competition and inter-industry linkage notably influence the relationship between financial geo-density and carbon emission intensity, promoting the emission reduction effect of financial geo-density in accelerating technological innovation and industrial structure upgrading, and suppressing the emission increase effect of financial geo-density in driving industrial expansion. Our findings provide new insights for developing systemic emission reduction policies for employing financial sectors as catch-all and integrating industries and competition. • Mechanism analysis of financial geo-density affects carbon emission intensity (IC). • Propose an integrated spatial model including spatial mediated moderating effects. • Financial geo-density drives IC by industrial-scale expansion. • Reduce IC by technological innovation and industrial upgrading. • Financial institution rivalry and inter-industry link mitigate total driven effect. [ABSTRACT FROM AUTHOR]

The carbon emission trading scheme (ETS) is an important market-based tool for achieving carbon neutrality. The existing research on the policy effect of ETS focuses on emission reduction effect and economic effect respectively. In view of this, based on the connotations of green development, we embed fairness toward the environment into the green development system to construct a balanced green development index to measure two dimensions, namely, efficiency and fairness. Theoretically understand the synergistic development effect of economic growth and ecological environment quality produced by the implementation of ETS, and analyze the impact of carbon market on balanced green development. A multiperiod difference-in-differences (DID) model explores the impact of China's carbon ETS on the green equilibrium level by using Chinese provincial panel data for the period 2008–2018. First, the results demonstrate that China's balanced green development level is weakly coordinated overall and there is a global spatial agglomeration effect. Second, the carbon ETS has significantly improved the level of balanced green development which promotes the degree of coordination between green economic growth and environmental fairness, offering an effective path that includes efficiency and fairness for green development. Third, there are regional differences in the impact of the carbon ETS on green equilibrium levels. The effect on the western region of China was significantly higher than that of the central and eastern regions of China. Compared with the existing research, the study breaks the single research perspective. From the perspective of efficiency and fairness, we propose improvements in the construction of a national unified carbon emissions trading market to strengthen the balanced green development. This paper provides a theoretical basis and policy reference for deepening China's green and high-quality development under the "carbon peaking and carbon neutrality" goal. [Display omitted] • Evaluation system of Balanced Green Development Index is constructed. • The system was applied to balance green economic growth with environmental equity. • Emission trading scheme has significantly improved the level of balanced green development. • The promotion effect is more obvious in western China. [ABSTRACT FROM AUTHOR]

The implementation of the carbon trading system has a great impact on all aspects of the economy and society. Agriculture, which accounts for 34% of global carbon emissions, has also been hit hard as a high carbon emitting industry (Crippa M, 2021). This study uses agricultural green total factor productivity as an important indicator of agricultural green sustainable development, and analyzes the impact of China's carbon trading system on agricultural green total factor productivity, which can provide a reference for other countries that want to improve agricultural sustainable development and implement carbon trading. In this paper, the producer theory is used to build the basic model, and the differences-in-differences (DID) method is used to analyze the provincial data samples in China from 2000 to 2020. It is found that: the implementation of carbon trading pilot policy has a significant promotion effect on agricultural green total factor productivity; and after the implementation of carbon trading policy, with the advancement of time, under the constraint of reducing carbon quota, the promotion effect of agricultural green total factor productivity becomes stronger and stronger. Even in the regions without carbon trading pilot program, the policy spillover effect will also be obvious and promote the development of green total factor productivity of agriculture in this area. [ABSTRACT FROM AUTHOR]

Under the dual policy targets of carbon emission peaking (CEP) and industrial green transformation (IGT) in China, where a top-down policy implementation is usually adopted, a more integrative planning mode needs to be constructed for greening industrial development. This paper proposes a technical framework to tackle the weakness faced when integrating IGT-associated issues with CEP factors during the development of IGT options, with an application in the Hohhot–Baotou–Ordos–Yulin (HBOY) city cluster. A CEP-IGT model was built to portray the effects of seven selected indicators on industrial carbon emissions, and help develop six options by defining the transformation strengths of HBOY's energy-intensive industrial system. Particularly, the CEP times and volumes were employed as the criteria for evaluating the IGT options. We found that the regional CEP goal will not be accomplished by even 2035 under the business-as-usual scenario. To halt the emission growth trend will rely much on the structural factors of energy mix and industrial output, which were also determinants of the IGT performance. Option 3, representing a moderate level transformation, was the preferred IGT plan, reaching a peak volume of 255.27 MtCO 2 eq·a−1 in 2026. The preferred plan will result in the replacement of at least 14% of the coal used in thermal power by renewable energy, and an increase in industrial coal-use efficiency by 32.02%. Policy measures need to be implemented to cap the total industrial coal consumption to no more than 2494 Mt and sustain an industrial growth by developing lower-energy or carbon-intensive industries. By 2030, the intensity and volume of industrial carbon emissions will reach 1.89 tCO 2 eq·10,000 CNY−1 and 224.85 MtCO 2 eq·a−1, respectively. This CEP-IGT progress will benefit the goal of being carbon neutral. As such, we concluded that this new framework will aid the IGT planning process, not only improving our understanding of the relationships between carbon emission control and industrial updating levels, but also presenting an integrative path for China's city clusters to promote green, low-carbon industrial development. • A technical framework is raised to tackle the weakness of integrating the CEP factors into IGT planning. • The peaking time and volumes of carbon emissions are used as the criteria for determining the preferred plan. • Both industrial updating and carbon emission control rely on the structural factors. • The preferred Option 3 can achieve the peaking goal in 2026 with a moderate transformation strength. • The new framework presents an integrative path to promote the transformation to green, low-carbon industrial growth. [ABSTRACT FROM AUTHOR]

The development of ports is essential to the competitiveness of cities. Harbor cities in China have put much effort into expanding the business of their ports, ignoring the overlapping of hinterland markets with other ports. Excess resources expended by ports may intensify regional environmental issues, such as carbon emissions. Motivated by the emissions reduction targets proposed by the International Maritime Organization and the urgent need for the development of green and sustainable ports, the Chinese government is trying to draft a carbon constraint policy to prevent the disorderly development of ports. It is thus necessary to study competition strategies under the context of carbon emission constraints. In this paper, the improved Hotelling model is used to describe the competitive relationship between ports. Then, three competition scenarios of the seaports under no carbon emissions policy, a carbon emission cap policy, and a carbon cap-and-trade policy are examined to analyze the effects of carbon emissions policy on port service prices, demand for goods, maximum profits, and social welfare. The results show that (1) from the perspective of port managers, only when government-defined carbon emission limits are lower than the critical value, the carbon cap policy is binding on port competition; when it comes to the cap-and-trade policy, government-defined carbon emission limits only affect profits. (2) From the government's perspective, the cap-and-trade policy maximizes social welfare more than the other policies regardless of the value of government-defined carbon emission limits. [ABSTRACT FROM AUTHOR]