Approaching national climate targets in China considering the challenge of regional inequality

Nations worldwide have pledged climate mitigation actions, but achieving national targets depends on regional actions. Significant economic, social, and technological disparities exist among regions, especially in developing economies like China. Aggressive or uniform climate policies may hinder economic growth and exacerbate regional inequality, jeopardizing national climate pledges. Existing literature proposes national or regional emission reduction targets based on equity principles, but these often fail to outline economically optimal emission reduction pathways. Top-down or bottom-up models offer valuable insights into carbon emission reduction pathways for multiple regions but don't necessarily maximize economic benefits while addressing regional inequality. This study addresses this gap by proposing a strategy that balances regional equality and national economic efficiency in achieving China's ambitious carbon neutrality goals. China's commitment to peak carbon emissions by 2030 and achieve carbon neutrality by 2060 provides a compelling case study due to its substantial regional heterogeneity. Approximately two-thirds of Chinese provinces have independently proposed carbon reduction targets, mostly aiming for a pre-2030 peak. This study will analyze regional cost-effective strategies for approaching China's climate targets, providing valuable insights for other developing countries with similar challenges.

Prior research has explored climate mitigation strategies at global and national scales, proposing national or regional targets based on various equity principles. While these studies provide static carbon quotas or intensity targets, they fail to define economically optimal emission reduction pathways for individual regions. Other studies have developed top-down or bottom-up models to derive carbon emission reduction pathways, considering socio-economic and technological diversity. However, these primarily focus on technological cost minimization or market equilibrium, often overlooking the need for economically optimal regional pathways that maximize national and regional economic benefits while addressing regional inequality. This research builds upon this foundation by explicitly integrating economic optimality and equity considerations into the pathway design for a more comprehensive and effective approach.

The study employs a two-stage modeling approach. First, it uses the National Energy Technology Model (C³IAM/NET) to determine the optimal national carbon peak and carbon neutrality pathway for China. This model incorporates uncertainties in future energy demand based on different socio-economic development scenarios and considers the potential of carbon sinks. The model optimizes the technology portfolio across various energy sectors to minimize total cost while meeting national targets. Second, to address regional inequality, a regional maturity index is developed using the TOPSIS method. This index evaluates each region's capacity and potential for carbon emission reduction based on socio-economic, technological, and resource factors. The Multi-regional Collaborative Optimization of Emission Pathway (Mr. COEP) model is then developed, integrating the national pathway from C³IAM/NET and the regional maturity index. This nonlinear model optimizes carbon emissions and energy consumption pathways for each region, aiming to maximize national and regional economic benefits while incorporating the regional maturity index as a constraint. This ensures that regions with higher maturity scores (i.e., better equipped for rapid emissions reductions) take on greater responsibility while those with lower maturity scores have more flexible pathways. The Mr. COEP model considers constraints on national energy consumption and carbon emissions, regional GDP growth, energy consumption by type (coal, oil, gas, non-fossil), and carbon intensity. A nonlinear relationship between socio-economic development, technology, and energy consumption is also incorporated, using an extended Kuznets curve model. The model is solved using GAMS 24.8.3 and CONOPT Optimizer. Four scenarios are compared: (1) all provinces uniformly achieving peak carbon emissions before 2030 (AP30), (2) following current independently set targets (FCT), (3) only energy-intensive provinces peaking before 2030 (EIP30), and (4) the collaborative optimization scenario (COP) incorporating the regional maturity index.

The C³IAM/NET model projects that China needs to peak its carbon emissions before 2029, with a maximum of approximately 12.2 billion tons of CO₂ (including industrial process emissions). The optimal national pathway indicates a plateau period (2025-2035) with a gradual emissions reduction after peaking, followed by rapid declines from 2035 to 2060. Coal, oil, and natural gas will account for a significant proportion of energy consumption until 2030, but non-fossil energy’s share will increase substantially after 2030. The study highlights substantial regional disparities in carbon mitigation capabilities. A regional maturity index was developed to quantify these differences. More developed provinces show higher tertiary industry shares, lower energy intensity, and advanced technologies. Less developed provinces rely on heavy industry, outdated technologies, and high energy intensity. Comparing the four scenarios, the collaborative optimization (COP) strategy yields the highest cumulative GDP (1.54% higher than the AP30 scenario). Under the COP scenario, 27 out of 30 provinces gain economically. In contrast, the FCT scenario (following independently set targets) results in a 101.2 trillion RMB GDP reduction. The COP strategy recommends a phased carbon peak timeline, with some advanced provinces peaking as early as 2027, others by 2030, and less-developed provinces by 2034 at the latest. The study also provides province-specific targets for carbon intensity reduction and energy structure adjustments. Advanced provinces are encouraged to increase non-fossil energy share rapidly while energy-supplying provinces maintain a high share of coal for energy security reasons. The study suggests adjustments to existing provincial targets for carbon peak years and non-fossil energy proportions to improve economic efficiency and equity.

This study's findings demonstrate that a collaborative approach that accounts for regional heterogeneity is crucial for maximizing economic benefits and ensuring equity in China's climate transition. Ignoring regional disparities and implementing uniform or independently determined targets can lead to significant economic losses for many provinces and the country as a whole. The COP strategy, by integrating economic optimality and regional equity considerations, offers a feasible and effective pathway toward carbon neutrality. The findings underscore the importance of flexible, context-specific policies tailored to each region's economic development stage, resource endowment, and technological capabilities. The results have implications for other developing countries facing similar challenges, highlighting the need for collaborative strategies that ensure both national climate goals and equitable regional development are achieved.

This research presents a novel approach to optimizing regional carbon mitigation strategies in the context of national climate targets, specifically using China as a case study. By incorporating a regional maturity index and utilizing the C³IAM/NET and Mr. COEP models, the study identifies a collaborative optimization strategy that maximizes overall economic benefits while ensuring regional equity. The findings suggest that a phased approach to carbon peaking, tailored to each region’s unique characteristics, is more effective than uniform or independently set targets. Future research could explore the sensitivity of the results to various model parameters and uncertainties, investigate the potential role of policy instruments in implementing the proposed strategy, and examine the social and environmental co-benefits of this approach.

The study relies on specific model assumptions and data inputs, which may affect the results' precision. Uncertainties in future economic growth, technological advancements, and policy implementation are not fully captured. The model focuses primarily on economic aspects, and a comprehensive evaluation of social and environmental impacts needs further investigation. The regional maturity index uses a selection of readily available indicators, so some other potentially relevant factors might not be fully captured in this index.