Climate change presents a global threat, prompting nations to adopt low-carbon development pathways to mitigate its potential impacts. However, current research lacks a comprehensive framework capable of integrating multiple variables and providing dynamic optimization capabilities. This article focuses on designing pathways for developing a low-carbon economy to tackle climate challenges. Specifically, we construct a low-carbon economy model that incorporates economic, environmental, social, energy, and policy factors to analyze the drivers of economic growth and carbon emissions. We utilize economic model predictive control and tracking model predictive control to optimize development pathways aligned with various low-carbon targets, creating and validating a comprehensive framework for low-carbon policy design using historical data from China. This study highlights significant advantages in analyzing low-carbon pathways through advanced techniques like hierarchical regression and model predictive control, providing a robust framework that enhances our understanding of causal relationships within the LCE system, captures system feedback, dynamically optimizes pathways, and accommodates diverse policies within a comprehensive low-carbon economy system.

This study was conducted to understand better how rules influence China's energy performance; this research on these policies' efficacy that facilitating the transition to sustainable energy sources is of tremendous significance, particularly in light of the severe problems climate change poses. To determine whether or not strict regulations are beneficial to China's energy transition efforts, this research makes use of a substantial amount of data about China's environmental laws and environmental transition policies. This paper thoroughly analyses the impact of strict environmental regulations on various energy transition measures. These metrics include the availability of green energy, carbon emissions, and energy efficiency. The results provide insights into how environmental restrictions have affected China's transition to a different energy source. Policymakers and stakeholders may use this information to build efficient plans to expedite the transition to a low-carbon, renewable energy system in China and abroad.

Following the 18th National Congress of the Communist Party of China, the central government elevated the construction of ecological civilization to a central position within national strategy and introduced environmental governance indicators as mandatory criteria for evaluating officials, alongside GDP. These indicators served as an additional "threshold" for performance assessments. In the context of changes in the central government's development ideology and policies, this study utilizes matched data on the turnover of municipal party secretaries and local enterprise carbon emissions from 293 prefecture-level cities in China between 1990 and 2021. The research finds that turnovers of municipal party secretaries after the 18th National Congress have led to a significant reduction in carbon emissions from local enterprises, a trend that was not evident prior to the congress. This effect is more pronounced in situations where official turnover is primarily driven by promotion incentives, and less influenced by collusive behavior between the government and enterprises. Further analysis reveals that the decline in carbon emissions is more significant for private enterprises, non-heavy polluting enterprises, those located in the eastern region, and those in general prefecture-level cities, before and after municipal party secretary turnovers. This study enhances understanding of the relationship between the promotion incentives of Chinese officials and the carbon emissions of local enterprises, offering valuable insights for improving the official promotion assessment system and advancing local carbon reduction efforts.

暂无

China faces significant environmental challenges, including reducing pollutants, improving environmental quality, and peaking carbon emissions. Industrial restructuring is key to achieving both emission reductions and economic transformation. This study uses the Environmentally Extended Multi-Regional Input-Output model and multi-objective optimization to analyze pathways for China’s industrial transformation to synergistically reduce emissions. Our findings indicate that under a compromise scenario, China’s carbon emissions could stabilize at around 10.9 billion tonnes by 2030, with energy consumption controlled at approximately 5 billion tonnes. The Papermaking sector in Guangdong and the Chemicals sector in Shandong are expected to flourish, while the Coal Mining sector in Shanxi and the Communication Equipment sector in Jiangsu will see reductions. The synergy strength between carbon emission reduction and energy conservation is highest at 11%, followed by a 7% synergy between carbon emission and nitrogen oxide reduction. However, significant trade-offs are observed between carbon emission reduction and chemical oxygen demand, and ammonia nitrogen reduction targets at -9%. This comprehensive analysis at regional and sectoral levels provides valuable insights for advancing China’s carbon reduction and pollution control goals.

This paper reconciles the debates on carbon return estimation by introducing the concept of equity duration. Our findings reveal that equity duration effectively captures the multifaceted effects of carbon transition risks. Regardless of whether carbon transition risks are measured by emission level or emission intensity, brown firms earn lower returns than green firms when the equity duration is long due to discount rate channel. This relationship reverses for short-duration firms conditional on the near-term cash flow. Our analysis underscores the pivotal role of carbon transitions' multifaceted effects on cash flow structures in understanding the pricing of carbon emissions.

This paper reconciles the debates on carbon return estimation by introducing the concept of equity duration. We demonstrate that emission level and emission intensity yield divergent results for green firms, driven by inherent data problems. Our findings reveal that equity duration effectively captures the multifaceted effects of carbon transition risks. Regardless of whether carbon transition risks are measured by emission level or emission intensity, brown firms earn lower returns than green firms when the equity duration is long. This relationship reverses for short-duration firms. Our analysis underscores the pivotal role of carbon transitions’ multifaceted effects on cash flow structures in understanding the pricing of carbon emissions.

Fighting global warming has become a vital requirement for environmental sustainability. Green finance has gained popularity as a promising mechanism for transitioning to a lowcarbon economy. Thus, this paper investigates whether excess green financing increases renewable energy capacities and enhances environmental quality from 1992Q1 to 2020Q4 in China, one of the major CO2 emitters. We primarily used the method of moments-quantile regression with fixed-effect models. First, we found nonlinear U-shaped impacts of green finance on wind power capacities in all Chinese regions, thermal power capacities in the Western and Central areas, and hydropower capacities in Eastern China, respectively. Second, we confirmed an inverted U-shaped impact of green finance on CO2 emissions in the Eastern region but U-shaped effects in the Western and Central regions. The impacts of green finance were asymmetrical due to the heterogeneous distributions of renewable energy sources and environmental quality within and between regions. Green finance mostly improved environmental quality when certain conditions and thresholds were met. Third, green finance had substantial marginal effects on environmental quality in the least polluted provinces (Q.20) in Western China and the most polluted provinces (Q.80) in Eastern China. Finally, there were heterogeneous effects of oil prices, urbanization, foreign direct investments, and trade openness on renewable energy consumption and environmental quality across Chinese provinces. Accordingly, this study provides some policy recommendations for China’s sustainable development, a key example from which the international community can adjust its green policies.

This study examines the impact of climate-transition risks on trade credits for Chinese listed companies from 2007-2017. We develop an index of county-level climate-transition risks faced by Chinese-listed companies using data on local carbon emissions and carbon sequestration when moving towards net zero carbon emissions. Our two-way fixed effects OLS regression results find that local firms facing greater climate-transition risks significantly reduce their trade credit financing. Specifically, a one standard deviation of increase in Risk leads to a 0.73% decrease in trade credit. This reduction is more pronounced for state-owned enterprises (SOEs), firms operating in less competitive industries, and those headquartered in regions without carbon trading markets. Our main finding is robust to a battery of sensitivity tests including the use of alternative measures and lagged independent variables. Results on an Instrumental Variable (IV) method and a differences-in-difference (DiD) analysis suggest a causal relationship between climate-transition risks on trade credit. Further analyses reveal two plausible channels for the effect: increased financial distress risk and enhanced access to bank credit.

China’s energy stocks are confronted with significant climate-related challenges. This paper aims to measure the daily climate transition risk in China by assessing the intensity of climate policies. The daily climate physical risk encountered by China’s renewable energy stocks is also measured based on the perspective of temperature change. Then, the partial linear function coefficient model is adopted to empirically investigate the non-linear impacts of climate transition risk and climate physical risk on the return and volatility of renewable energy stocks. The nonlinear moderating effect of climate transition risk is also involved. It is found that: (1) Between 2017 and 2022, the climate transition risk in China exhibited a persistent upward trend, while the climate policies during this period particularly emphasized energy conservation, atmospheric improvements, and carbon emissions reduction. Additionally, the climate physical risk level demonstrated a pattern consistent with a normal distribution. (2) There is a U-shaped nonlinear impact of climate physical risk on the return and volatility of renewable energy stocks. High climate physical risk could not only increase the return of renewable energy stocks but also lead to stock market volatility. (3) Climate transition risk exhibits a U-shaped effect on the return of renewable energy stocks, alongside an inverted U-shaped effect on their volatility. Notably, a high level of climate transition risk not only increases the return of renewable energy stocks but also serves to stabilize the renewable energy stock market. Moreover, the heightened risk associated with climate transition enhances the negative impact of oil price volatility on the yield of renewable energy stocks and, concurrently, leads to an increase in volatility.The strength of this moderating effect is directly correlated with the level of climate risk.