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To achieve the goal of carbon reduction, China has been piloting the Carbon Emission Trading System (CETS) since 2013. As the economy faces a downward trend, it is significant to explore the impact of CETS on business development. There is still debate in academia about whether this policy can boost the level of business development. This paper, based on all A-share data of listed companies in China from 2009 to 2018, uses the Difference in Differences (DID) model to verify the impact of CETS on the input of capital and labor factors and the level of technology in enterprises and discusses the industry heterogeneity of this impact in detail. Placebo tests, propensity score matching, and triple differences ensure the robustness of the conclusions. In further research, this paper decomposes the policy effect of CETS. It regresses the impact of carbon quota prices and carbon market trading scale on business development. The final conclusion is that CETS has a positive impact on the input of capital and labor in enterprises and a negative impact on the level of technology. After distinguishing industries, this conclusion shows differences according to different characteristics of high emissions and low emissions. In addition, the increase in carbon quota prices hinders business development, while the scale of carbon market trading shows an inverted "U" relationship with business development. The article provides meaningful policy references for China and countries in the early stages of CETS construction. [ABSTRACT FROM AUTHOR]

Carbon flow in forest products trade will affect the report of a country's carbon stock. This will have an impact on a country's contribution of carbon flows. Based on the analysis of China's forest product trade, this paper uses the stock-change approach, the production approach and the atmospheric-flow approach to calculate the changes of China's forest products trade carbon flows. Different carbon flow measurement approaches have very different results. From the perspective of the contribution of forest products to carbon flow, the production approach of calculation for forest products trade carbon flow has the largest contribution to atmospheric carbon flows. However, the calculation results of the stock-change approach and the atmospheric-flow approach are just the opposite, that is, the calculation for forest products trade has a negative contribution to China's carbon sinks, and forest products trade has become a source of carbon emissions. [ABSTRACT FROM AUTHOR]

Due to rapid urbanization and increasing energy consumption, human society poses increasing pressure on the surrounding ecosystems that it depends on. As a result, evaluation of urban development should view cities as complex ecosystems including human and natural elements. This paper establishes a carbon balance index (CBI) for an urban ecosystem based on its socio-economic development and land use and land cover change in Xiamen, a rapidly urbanizing coastal city in southeast China. Dynamic changes in CBI can quantitatively indicate the sustainability of the urbanization process from a carbon cycling perspective. Results show that Xiamen's carbon balance condition experienced three stages: the period 1987–2002 where CBI decreased slightly, 1992–2002 where CBI moderately increased from 1.4 to 4.2, and 2003–2011 where CBI rapidly increased from 5.2 to 17.3. The carbon imbalance increased with the expansion of urban scale and urbanization. By stepwise multiple regression analysis, it was found that the main influencing factors of CBI are urbanization rate, industrial coal consumption, length of roadway network and forest area, and city managers should take these factors into consideration to achieve low-carbon city development. Finally, the CBI for the year 2030 is predicted based on CO2emissions and sequestration scenarios. [ABSTRACT FROM AUTHOR]

Using sample firms from eight energy-intensive industries included in the State Council of China's Notice on the Pilot Work of Carbon Emission Trading from 2015 to 2019, this study examines the relationship between environmental legitimacy pressure and impression management of carbon information disclosure, and explores the moderating effect of political connection on this relationship. The baseline results show that environmental legitimacy pressure is positively associated with impression management of carbon information disclosure, and political connection moderates this relationship, that is, the positive association between environmental legitimacy pressure and impression management of carbon information disclosure in politically-connected firms is stronger than that in non-politically-connected firms. The results are robust to various sensitivity tests. Further analyses show that (i) the positive association between environmental legitimacy pressure and impression management of carbon information disclosure in non-state owned enterprises (non-SOEs) is stronger than that in SOEs, (ii) firms facing higher negative environmental legitimacy pressure have stronger motivation to conduct impression management of carbon information disclosure, (iii) firms facing environmental legitimacy pressure conduct both selective disclosure and expressive manipulation but they have stronger motivation to conduct expressive manipulation. This study extends the literature on impression management of carbon information disclosure. The findings in this study provide policy implications not only for China but also for countries with large carbon emission. [ABSTRACT FROM AUTHOR]

To mitigate the detrimental effects of climate change exacerbated by excessive carbon emissions, China has introduced a series of environmental regulations designed to promote low-carbon technology diffusion among enterprises. The existing literature ignores the heterogeneity of the scales of enterprises, making it extremely difficult to put forward targeted policies for enterprises of different scales. In this study, we employ a complex network-based evolutionary game approach to analyze the effect of environmental regulations on the diffusion of low-carbon technology, and thereby determine the relationship between the degree of diffusion and the strength of regulations at different scales of enterprise. The results revealed that with respect to the degree of diffusion, there are significant differences in the sensitivity of enterprises in 20- and 100-scale networks to the imposition of three types of environmental regulation (innovation subsidy, carbon tax, and punishment). When the scale of the network is fixed, fluctuation in the change in degree becomes larger, and even irregular, with an increase in enterprise scale. With an increase in network scale for small, medium, and large enterprises, the range of variation in the degree of diffusion becomes smaller. In small, medium, and large enterprises, when the scale of the network increases from 20 to 100, the degree of diffusion will increase in response to the same strength of innovation subsidy, carbon tax, and punishment. With an increase in innovation subsidies, the diffusion degree of large enterprises will improve slightly. Moreover, for large enterprises, increasing the strength of punishment has no obvious effects with regards to improving the degree of diffusion. At all scales of enterprise, in both the 20- and 100-sacle networks, the degree of diffusion will increase with an increase in the strength of the carbon tax. [ABSTRACT FROM AUTHOR]

We use the 2004–2016 China prefecture-level city data to construct a STIRPAT-based spatial econometric model as an empirical test for the driving factors of city carbon emissions. Results show that China's city carbon emissions exert significant spatial spillover effects and high-emission club agglomeration characteristics. The relationship between city carbon emissions and the city's own economic development has an "inverted U" shape, whereas city carbon emissions and the economic development of neighboring cities exhibit a "J"-shaped relationship. The improvement of energy efficiency is not only conducive to controlling the carbon emissions of the city itself but also beneficial to regulating carbon emissions in neighboring cities. The coal-based energy structure will significantly increase the carbon emissions of the city itself and those of the neighboring cities. Population density will increase the city's own carbon emissions but reduce carbon emissions in neighboring cities due to the siphon effect. Traffic facilitation and industry structure in a city will lead to an increase in carbon emissions in neighboring cities. Foreign direct investment will benefit the city's own carbon emission control. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) formed during coal combustion is responsible for over half of the increase in the greenhouse effect, globally. It is crucial to conduct a comprehensive analysis and accurate prediction for coal production and consumption to optimize coal utilization and control emissions. However, several unstable factors inhibit the accurate forecasting of coal. Therefore, taking into account both effect and efficiency of prediction, the Hubbert model is applied in this study to forecast China's peak coal production, peak year, and future production. Additionally, a combined model, with weights determined by a flower pollination algorithm and no-negative-constraint theory, is proposed to forecast coal consumption, which is superior to that of all individual models. Subsequently, accounting for the vital effect of CO2 from coal combustion on economic issues, correlation analysis and an environmental Kuznets curve (EKC) are applied to quantitatively examine the relationship among coal consumption, economic development, and carbon emissions. The results of this estimation suggest that, compared to the US, China's economic development relies more on coal consumption; however, the EKC indicates that China has still not reached the 'inflection point'. Accordingly, it is essential for policymakers to balance the relationship among coal utilization, economic development, and the environment. [ABSTRACT FROM AUTHOR]