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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]

The effectiveness of carbon price in emissions trading schemes (ETS) is an important issue in China in the context of its ambitious climate change goals. This paper adopts a staggered difference-in-differences model to estimate whether China's ETS reduced CO2 emissions while maintaining economic growth even under low carbon prices. The results indicate that despite the low carbon prices, the ETS effectively reduced CO2 emissions without undermining the economy. Specifically, an increase of $1 in the carbon price reduced CO2 emissions by 1.69% and increased the per capita GDP by $286. The carbon price primarily achieved emission reduction and promoted economic development through channels, such as technological innovation, foreign direct investment, energy mix, and industrial structure. Carbon leakage to neighboring regions was not evident. Heterogeneity analysis showed that the environmental effects of the carbon price were more pronounced in regions with higher levels of economic development and CO2 emissions. Conversely, the economic effects of the carbon price were more pronounced in regions with lower levels of economic development and CO2 emissions. The carbon price achieved significant economic effects in regions that solely adopted the free allocation mode of emission allowances, while regions that used a combination of free allocation and auctioning experienced substantial emission reduction effects. Despite low carbon prices, China's ETS effectively reduced CO2 emissions without compromising economic growth. This finding provides new empirical evidence for the effectiveness of carbon price as well as decision support for the future promotion of ETS. Technological innovation, FDI, energy mix, and industrial structure are crucial channels through which the carbon price achieves emission reduction and promotes economic development. The absence of carbon leakage to neighboring regions suggests that ETS is an internally effective mechanism for emission control. Heterogeneity analysis showed that regional characteristics and allowance allocation modes can influence the effectiveness of carbon price, thus emphasizing the importance of targeted policy design and appropriate allocation methods. [ABSTRACT FROM AUTHOR]

The integration or segmentation of regional carbon prices implies that barriers may hinder prices from adjusting efficiently and impede linkages between regional carbon markets. Past studies have found that crossregional carbon prices in China tend to diverge, indicating unbalanced regional markets and that carbon cap-and-trade policies may be insufficiently effective. China's carbon trading pilots opened in 2013. Is the integration efficient? This is the research question addressed in this study. This paper uses the carbon prices of four carbon-trading pilot regions in China (i.e. Beijing, Shanghai, Tianjin, and Guangdong) over the period of January 1, 2014, to March 23, 2021, to explore whether prices are correlated across three dimensions: long-term convergence, short-term correlation, and volatility transmission by adopting a vector error correction model with heterogeneous variances. And by using longer-term daily data and empirical tests that can account for the multiple-faceted correlations, this paper provides evidence showing that long-term convergence and risk transfer between the four regional carbon prices exist, which indicates significant regional integration. The results indicate that the price behavior of the Beijing pilot is efficient and that the Shanghai pilot has the lowest volatility. The paper also documents an information transfer pattern. For example, the Beijing pilot is shown to be the leading risk transfer market, whereas the Shanghai pilot is shown to be the market where most risk is transferred. Contrary to findings elsewhere, our main results demonstrate that China's carbon markets exhibit integration efficiency and no imbalance between regions. This may be because the efficiency of China's carbon markets has improved over time. The evidence also implies that if a multi-dimensional correlation has not been considered, it may underestimate the efficiency of regional carbon prices' integration. [ABSTRACT FROM AUTHOR]

Since the implementation of China's clean heating plan in 2017, the progress of natural gas replacing coal for heating is still not ideal. With the proposal of the goal of carbon neutralization and the impact of international war, the price, supply, and demand of natural gas have attracted attention. In case of gas shortage, reasonable schemes are required to be allocated to different industries and categories. Therefore, this research divides the gas field into four levels according to the social utility, and establishes the multi-objective distribution optimization model considering the social and economic benefits. The solution of the model is based on genetic algorithm and realized on MATLAB. Multi-objective optimization strategies and several constraints are used to make the algorithm's process of the search is continuously moving closer to the Pareto optimal front. Taking Beijing as an example, two scenarios are set to simulate and optimize, so as to verify the optimization effect of the model. Better quantitative results are created after reallocation of natural gas. The ideal scenario realizes 5.64% more social benefits than 2019 through additional allocation of 117.288 million cubic meters of reserve gas. The constraint scenario creates 0.67% more social benefits with only 0.07% decrease of the economic benefits. The conclusions show that allocating more gas to three main industries can improve the optimization effect and it is necessary to expand the supply of natural gas reserve volume. This paper provides a new perspective of natural gas allocation category and priority, providing theoretical and practical ideas for the planning of natural gas security emergency plan and the development of gas sales plan. [ABSTRACT FROM AUTHOR]