2

China’s energy transition towards carbon neutrality: A multidimensional framework

Zhen Wang, Boshu Li and Yinghao Kong

Introduction

Climate change is reshaping human existence with unprecedented breadth and depth. According to the latest data from the Sixth Assessment Report of the United Nations Intergovernmental Panel on Climate Change (IPCC), global surface temperatures have already risen by 1.15ºC compared with pre-industrial levels. If current emission trajectories persist, the critical threshold of 1.5ºC is projected to be breached between 2030 and 2035 (IPCC 2023). The ecological and environmental challenges posed by climate change may represent the greatest uncertainty confronting human society.

In this context, China, as the world’s largest developing country, has pledged to achieve peak carbon emissions by 2030 and carbon neutrality by 2060. This commitment not only underscores China’s responsibility as a major global power but also necessitates the establishment of a comprehensive low-carbon transformation system encompassing the entire industrial chain. Within this transformative process, the energy sector—recognised as the ‘main battlefield’ for achieving the dual carbon goals—has been undergoing a significant transition from ‘light green’ to ‘deep green’ development. Guided by the new energy security strategy of ‘Four Revolutions and One Cooperation’,¹ substantial progress has been made in transforming energy production and consumption patterns, comprehensively enhancing energy supply security and achieving historic breakthroughs in green and low-carbon energy development. By the end of 2023, China’s energy consumption per unit of GDP had declined by nearly 26 per cent compared with 2013 levels, while carbon dioxide emissions per unit of GDP had decreased by more than 35 per cent. Simultaneously, the share of clean energy consumption rose to 26.4 per cent and the proportion of coal consumption fell cumulatively by 12.1 percentage points. The installed capacity of renewable energy generation reached 1.38 billion kilowatts, accounting for 51.9 per cent of the nation’s total power generation capacity—marking the first time renewable energy capacity surpassed fossil fuel–based power generation capacity.

China’s ongoing energy transition is fundamentally reshaping its energy production and consumption landscape. This transformation not only exerts multidimensional impacts on domestic economic growth, industrial transformation, environmental quality and public health, but also has transcended national boundaries, generating significant international spillover effects through global supply chains, technology diffusion and other channels. From 2013 to 2023, the global share of non-fossil energy consumption increased from 13.6 per cent to 18.5 per cent, with China contributing 45.2 per cent of the global growth in non-fossil energy consumption. In 2023 alone, China accounted for more than half the world’s newly added renewable energy capacity. Driven by stable policy expectations for the energy transition, China has capitalised on its dominant position in clean energy manufacturing to actively promote the international dissemination of green technologies and equipment. Exports of photovoltaic (PV) cells and wind turbines exceeded US$49.76 billion in 2023, with an export volume of approximately 255 gigawatts (GW). By providing economically accessible clean energy solutions to the global market, China has made substantial contributions to global efforts to combat climate change and achieve sustainable development.

Current research has increasingly focused on China’s energy transition and the development trends of its energy sector. Existing studies have examined the latest progress in the energy transition from various perspectives, including industry (He et al. 2022), policy (Li and Taeihagh 2020), technology (Duan et al. 2021) and governance mechanisms (Hepburn et al. 2021). These studies explore the prospects and pathways for transforming energy production and consumption. Notably, regular energy outlook reports published by international organisations (IEA 2024), research institutions (ERI 2024) and energy enterprises (CNEEI 2024) are particularly representative. Based on their respective modelling assumptions and scenario designs, these reports offer diverse pathways and policy recommendations for advancing China’s low-carbon energy transition. However, most of these studies focus primarily on demonstrating the necessity of the energy transition, evaluating its achievements and assessing the feasibility of implementation strategies. They often lack a comprehensive analysis that captures the full spectrum of impacts on the economy, society, environment and climate change (Zhang et al. 2024). Furthermore, forward-looking and systematic research on the spillover effects of China’s exports of new-energy products, such as PV cells and wind turbines, remains limited. As a result, developing an integrated assessment model to evaluate the impacts and spillover effects of China’s energy transition has become critical.

The remainder of this chapter is organised as follows. Section two introduces the integrated assessment modelling framework designed to evaluate the multidimensional impacts and spillover effects of China’s energy transition. This framework integrates multidisciplinary methodologies, addressing the limitations of single-model analyses by employing complex and holistic analytical approaches. Section three examines the cascading effects of China’s energy transition on macroeconomic performance, industrial structure, carbon reduction, pollution mitigation and public health under various scenarios. This section also quantifies the spillover effects of global emission reductions driven by the export of China’s wind power and PV products. Section four concludes by summarising key findings and offering insights and policy recommendations.

Methodology and framework

Comprehensive assessment methodologies typically involve simulating and evaluating the interactions between multiple factors under varying assumptions within a unified framework. This is achieved by linking complex system models across different domains. These methodologies are generally categorised into three types of model: top-down, bottom-up and hybrid. Building on the theoretical foundations of cost–benefit analysis, this study develops a novel integrated assessment model for evaluating the multidimensional impacts and spillover effects of China’s energy transition (Figure 2.1). The framework comprises two modules.

Module I integrates four submodels: a macroeconomic model, an energy system optimisation model, a co-benefits approach and a public health benefit evaluation model. This framework is designed to evaluate the impacts of the energy transition across multiple dimensions under various policy constraint scenarios. The macroeconomic model is a multi-sector, recursive dynamic computable general equilibrium (CGE) model. It simulates and evaluates the effects of economic, social and environmental constraints on overall economic growth, industrial development and labour market dynamics. The energy system optimisation (ESO) model, built on extensive technical data, encompasses the entire energy lifecycle—from extraction, processing and conversion to transportation and end use. It focuses on modelling key energy-consuming and emission-intensive sectors, such as industry, building operations and transportation, to optimise energy transition pathways and estimate the costs of transition under different policy scenarios. Additionally, the framework establishes soft linkages with the greenhouse gas and air pollution interaction and synergies (GAINS) model developed by the International Institute for Applied Systems Analysis (Kilmont 2025) and the public health benefits evaluation (HEL) model. These linkages enable the quantification of the co-benefits of carbon and pollution reduction resulting from the energy transition. Furthermore, the framework provides monetised benefits of public health improvements, offering a more intuitive representation of the synergies between pollution mitigation and health benefits.

Figure 2.1: Integrated assessment framework for modelling multidimensional economic, social and environmental benefits of China’s energy transition

Figure 2.1 illustrates the coupling relationships among the four submodels in Module I. Under the constraints of economic and social development goals, carbon reduction and energy policy, the CGE model generates projections of economic growth and structural adjustments, which are subsequently transmitted to the ESO model as constraints on energy service demand forecasting. The ESO model, optimised to minimise energy system costs, determines long-term transition trends and technological pathways for key energy-consuming and carbon-emitting sectors. Simultaneously, the ESO model provides national energy consumption trajectories to the GAINS model, which simulates and optimises changes in three key air pollutant emissions and particulate matter (PM) 2.5 concentrations. Leveraging the linear and nonlinear exposure-response functions embedded in the HEL model, health impacts—including morbidity and mortality cases—are quantified. These results are then fed back into the CGE model, enabling further analysis of the corresponding economic variation and changes in employment. This iterative process allows policymakers to evaluate the comprehensive costs and benefits of the energy transition from a social perspective. By integrating cross-domain interactions, this framework overcomes the limitations of single-model approaches, offering a more holistic and interdisciplinary perspective on the energy transition and its multidimensional impacts.

Module II defines a country’s export contribution to global emission reductions as the sum of emissions generated in the domestic production process and the emission reductions realised during the use phase in foreign countries. The measurement boundaries and key parameters are illustrated in Figure 2.1. For PV products, production-related emissions can be calculated as the product of net export volumes and carbon emission intensity, as expressed in Equation 2.1.

Equation 2.1

In Equation 2.1, P_j denotes the production-related carbon emissions from the net exports of photovoltaic products in year j, reflecting China’s contribution to global carbon emission reductions during the production phase; i denotes the product type, where i = 1 corresponds to high-purity silicon, i = 2 corresponds to silicon wafers and i = 3 corresponds to PV cells (Liu et al. 2019); j denotes the year, where j = 1 corresponds to 2015 and j = 9 corresponds to 2023. X_ij represents the net export value of product i from China to the world in year j; P_j denotes the price of PV modules in year j; and θ_j denotes the carbon emission intensity of PV modules in year j, with the unit of tonnes of carbon dioxide per megawatt (tCO₂/MW).

To calculate the emission reductions during the use phase, it is essential to determine the amount of electricity generated by all exported products. Since polysilicon and silicon wafers are used in the production of PV cells, their export values must be converted into the equivalent quantity of PV cells. As trade data in commodity trade statistics databases are typically reported in monetary terms, the average price of the products is used to convert monetary values into the corresponding quantity of PV modules. Consequently, the electricity generation capacity of PV modules over their full lifecycle can be calculated using Equation 2.2.

Equation 2.2

In Equation 2.2, T denotes the average available hours of the power-generating equipment in photovoltaic power plants; n denotes the service life of PV power plants; β_j denotes the electricity emission factor in year j; and C_j denotes the potential emission reductions during the use phase of net exported PV products in year j, reflecting China’s contribution to global carbon emission reductions during the use phase.

The total contribution to emission reductions is calculated by summing the emission reduction contributions from the production phase and the use phase, as shown in Equation 2.3. The emission reduction contributions of wind turbine exports are analogous to those of PV products and will not be elaborated further here.

Equation 2.3

Population growth and urbanisation rates are the key factors influencing economic development and energy consumption patterns. The social cost of carbon, which quantifies the economic loss caused per unit of carbon emissions, serves as a critical tool for conducting cost–benefit analyses of the energy transition and climate policies. In this study, we comprehensively compared projections of population growth and urbanisation rates from major institutions, including the United Nations (UNDESA 2024; UN-Habitat 2024) and the National Bureau of Statistics of China. Furthermore, the latest assessments of the social cost of carbon are systematically reviewed (Wang et al. 2022; Ricke et al. 2018). To facilitate cross-sectoral comparisons of the costs and benefits associated with the energy transition and to provide policymakers with intuitive insights, we monetised the health benefits using environmental valuation, such as the value of statistical life (Jin and Zhang 2018). The specific assumptions for these key parameters are presented in Table 2.1. In addition, the data inputs, including input–output tables, energy balances, industrial statistics and carbon intensity data, were sourced from government publications, industry associations and relevant literature (Zheng et al. 2021; Liu et al. 2021; Pan et al. 2022). Emission factors, product lifespans and average annual operating hours were estimated based on industry averages. Air pollutant and carbon emission factors were determined using the latest IPCC Guidelines for National Greenhouse Gas Inventory (IPCC 2019) and data from China’s Carbon Emission Accounts and Datasets (CEADs).²

Table 2.1: Pre-set value of China’s population, urbanisation rate, social cost of carbon and value of statistical life

Parameters	2025	2030	2040	2050	2060
Population (billion)	1.41	1.39	1.36	1.30	1.20
Urbanisation rate (%)	67.2	70.6	75.0	80.0	85.0
Social cost of carbon (US$/tCO2)	26.8	33.2	41.7	74.9	88.2
Value of statistical life (US$ million)	–	–	–	–	1.34

Note: To eliminate the impact of price fluctuations and reflect the real changes in monetised results such as GDP, unless otherwise specified, all monetised values in this study have been adjusted to constant prices using the 2010 price level as the base year.

Source: Authors’ calculations and forecasts.

In addition to examining economic and social impacts, this study focuses on the synergistic emission reductions of three key air pollutants—sulphur dioxide, nitrogen oxides and PM2.5—and their associated public health benefits. Given that PM2.5 pollution is the leading contributor to both mortality and morbidity, the health benefit valuation in this study exclusively targets PM2.5 pollution, drawing on epidemiological principles and insights from the Global Burden of Disease studies (Murray et al. 2020; Xu et al. 2021). The health endpoints and exposure-response coefficients related to PM2.5 pollution are explained in detail in Table 2.2.

Table 2.2: Exposure-response functions for health endpoints related to PM2.5 pollution

Endpoint	Exposure-response functions
	Confidence interval (95%) low	Medium	Confidence interval (95%) high
All causes (China)a	–0.0003	0.0009	0.0018
Chronic obstructive pulmonary diseasesb	Nonlinear function
Lung cancerb
Ischemic heart disease (25y–65y)b
Cardiovascular disease (25y–65y)b
Lower respiratory infectionb

Sources: ^a Cao et al. (2011); ^b Pope et al. (2002).

The primary global spillover effects of China’s energy transition are the impacts on carbon dioxide mitigation in other countries from China’s exports of PV modules and wind turbines. While the term ‘spillover effects’ can encompass a broader range of phenomena, such as international knowledge transfers or shifts in global fossil fuel markets, the scope of this study is focused on the direct impact of technology exports due to limitations in data availability. These spillover effects encompass both the production phase (Yang et al. 2015; Wang 2023) and the use phase. Key parameters influencing these effects include global electricity emission factors, product service lifespans and average annual operating hours, as summarised in Table 2.3.

Table 2.3: Pre-set values of global electricity emission factors, product lifespans and average annual operating hours

Product	Product lifespan (years)	Average annual operating hours (hours/year)	Global electricity emission factor (tCO2/GWh)
Photovoltaic	30	1,700	671
Wind turbines	30	1,900	671

Source: Authors’ calculations and forecasts.

Based on variations in the depth and pace of energy transition, this study develops two scenarios: the current policy scenario (CPS) and the enhanced action scenario (EAS). The divergence between these two scenarios underscores the ‘action gap’ that China must address to accelerate its energy transition and achieve its dual goals of ‘carbon peaking and carbon neutrality’.

The CPS is grounded in China’s 2021 Nationally Determined Contributions (NDCs) under the Paris Agreement and reflects the policy intensity and energy system transformation efforts outlined in sectoral development plans, energy conservation objectives and carbon reduction targets established under the ‘1+N’ policy framework for dual carbon goals. This scenario assumes that emission reduction efforts after 2030 will largely follow the current trajectory. Furthermore, it assumes that the global energy transition will maintain its present momentum, while China’s exports of PV modules and wind turbines will continue to grow at their current rates.

The EAS is designed to capture the policy intensity and energy system transformation efforts necessary to address the constraints imposed by China’s socioeconomic and ecological development goals. Building on the CPS, the EAS further strengthens and updates more ambitious NDC targets and action requirements, while fully leveraging the potential for energy conservation and emission reductions. It also intensifies the stringency and scale of dual carbon-control measures. This scenario is characterised by a substantial increase in the adoption of advanced energy technologies, the penetration of low-carbon technologies and the electrification of end-use energy consumption. Concurrently, the costs of low-carbon energy sources, including wind and solar power, as well as energy storage, continue to decline. These advances collectively facilitate the establishment of a new energy system, thereby supporting the realisation of China’s ‘carbon peak’ and ‘carbon neutrality’ goals. Compared with the CPS, the EAS envisions an accelerated global energy transition, alongside faster growth in China’s PV and wind turbine exports.

Results and discussion

The advancement of the energy transition will play a pivotal role in supporting Chinese-style modernisation and driving industrial transformation. At present, China is in the mid-to-late stages of industrialisation and urbanisation, steadily transitioning towards a high-quality development phase under the guidance of its new development philosophy. In 2024, China’s GDP was projected to reach approximately US$18.9 trillion, reflecting a 5 per cent increase from the previous year. Under both the CPS and the EAS, China’s macroeconomic trajectory is expected to exhibit sustained expansion in scale, accompanied by a gradual deceleration in growth rates (Table 2.4). By about 2035, China’s GDP is anticipated to surpass that of the United States, positioning it as the world’s largest economy.

Table 2.4: Changes in China’s average GDP growth rate

Scenario	2026–30	2031–35	2036–40	2041–50	2051–60
CPS	5.0	4.5	4.5	3.4	2.4
EAS	4.5	3.5	3.5	2.5	1.5

Source: Authors’ calculation.

Against the backdrop of China’s ‘Two Centenary Goals’³ and historical trends in the industrial structure of developed countries, China’s future economic development can be divided into three distinct phases (Figures 2.2a and 2.2b).

Now until 2035

The growth rate and drivers of the economy will enter a critical period of transformation. The share of secondary industry is expected to stabilise and gradually decline, with a steady reduction in the scale of energy-intensive manufacturing industries. Despite this, China will retain its position as a major manufacturing powerhouse, while continuously optimising and upgrading its industrial structure. High-tech manufacturing sectors, including new-energy vehicles and strategic emerging industries, are projected to maintain rapid growth. Meanwhile, tertiary industry will steadily increase its share in the national economy and its contribution to overall economic growth. By 2035, per capita GDP is anticipated to reach the level of moderately developed countries, marking the basic realisation of socialist modernisation and the ‘Beautiful China’ vision.

Figure 2.2a: Changes in the proportions of China’s industrial structure under the CPS

Figure 2.2b: Changes in the proportions of China’s industrial structure under the EAS

Source: Authors’ calculation.

2035–50

During this second phase, economic growth will be predominantly driven by the service sector and domestic consumption. Tertiary industry will consolidate its dominant position, accounting for more than 62 per cent of GDP. Concurrently, manufacturing will undergo a transformation characterised by digitalisation, high-end innovation and green development, elevating China to the ranks of the leading global manufacturing powers.

2050–60

In the third phase, China’s economy is expected to play an increasingly prominent role in driving global development, fostering the emergence of numerous new business formats and innovations. A green economy will take centre-stage globally, with China positioned as a key engine and stabiliser of global economic growth.

The energy transition will catalyse a transformative leap forward in clean energy development. China’s total primary energy consumption (TPEC) is expected to follow a trajectory characterised by sustained growth, followed by a gradual decline. This transition can be attributed to four primary factors: 1) the earlier than anticipated peak in population imposes an upper limit on the expansion of domestic aggregate demand, thereby diminishing its supportive effect on energy consumption; 2) the stabilisation and gradual slowdown of economic growth rates create favourable conditions for controlling total energy consumption; 3) industrial restructuring and upgrading contribute to a progressive reduction in energy intensity across sectors; and 4) technological advancements, coupled with the deepening of demand-side energy conservation behaviours, enhance energy efficiency. Taken together, these factors will significantly decelerate the growth rate of energy consumption, leading to a peak, after which consumption will steadily decline.

Under the CPS, TPEC is projected to rise from 5.97 billion tonnes of standard coal equivalent (btce) in 2024 to 6.21 btce by 2035, after which it will plateau. During this period, energy consumption will gradually decouple from economic growth, declining to 5.42 btce by 2060 (Figure 2.3a). Under the EAS, with the implementation of stricter carbon constraints, improvements in energy efficiency and more intensive demand-side conservation measures, TPEC is expected to peak earlier, in 2030, at a lower level of approximately 5.85 btce. By 2060, it is projected to decrease further, to 4.98 btce (Figure 2.3b).

With the continued advance of the energy transition and the implementation of the ‘carbon peak and carbon neutrality’ goals, China’s energy consumption structure is expected to undergo significant transformations, characterised by three key trends: 1) a gradual, stepwise decline in the shares of coal and oil consumption; 2) natural gas consumption initially increasing before declining; and 3) a rapid and substantial rise in the share of non-fossil energy consumption.

Figure 2.3a: Changes in China’s total primary energy consumption under the CPS

Figure 2.3b: Changes in China’s total primary energy consumption under the EAS

Source: Authors’ calculation.

Under the EAS, the share of non-fossil energy is projected to reach 82 per cent of total energy consumption by 2060, surpassing the policy target of 80 per cent outlined in China’s energy and climate strategies. Meanwhile, considering the dual imperatives of energy security and cost constraints, the phased withdrawal of fossil fuels will adhere to the principle of ‘establishing new energy systems before dismantling old ones’. Coal and oil consumption are expected to peak by about 2025. For natural gas, peak consumption is projected to occur about 2040 under the CPS, while under the EAS, the peak is anticipated to arrive earlier, by approximately 2035. Overall, fossil fuels will continue to play a vital role as a cornerstone of energy security and maintaining a stable energy supply during the transition period.

The energy transition will significantly contribute to the substantial reduction of carbon dioxide emissions while further unlocking the potential for synergistic mitigation of other greenhouse gases (GHGs). The CPS aligns with China’s current stage and characteristics of development, recognising the need for a certain level of carbon emissions to ensure the low-carbon transition of the economy and society before peaking about 2030. Under this scenario, carbon dioxide emissions are expected to peak at approximately 11.4 billion tonnes. From 2030 to 2060, the low-carbon transformation of the energy structure is expected to accelerate under the EAS, with greater efforts directed towards achieving carbon neutrality through enhanced technological efficiency and industrial restructuring. These efforts will contribute significantly to emission reductions, with economic growth increasingly decoupling from energy consumption and carbon emissions. By 2060, carbon dioxide emissions are projected to decline to 830 million tonnes, representing a reduction of 1.02 billion tonnes compared with the CPS (Figure 2.4a).

Carbon dioxide, as the most dominant GHG by emission share, remains the primary driver of global climate change. However, numerous studies underscore the critical role of GHGs other than carbon dioxide, which cannot be overlooked. For instance, nearly one-third of emission reductions in developed countries have been achieved through non–carbon dioxide GHG mitigation (Montzka et al. 2011; Rogelj and Lamboll 2024). Without effective control, non–carbon dioxide GHG emissions are projected to continue rising, potentially offsetting the progress made in reducing carbon dioxide emissions. Under the CPS, non–carbon dioxide GHG emissions are expected to peak about 2035, plateauing before gradually declining, with a peak level of approximately 2.89 gigatonnes of GHG carbon dioxide equivalent. By 2060, these emissions are projected to decrease slowly, to 2.23 gigatonnes of carbon dioxide equivalent. In contrast, the EAS envisions non–carbon dioxide GHGs peaking concurrently with carbon dioxide, achieving a peak reduction of approximately 0.33 gigatonnes of carbon dioxide equivalent compared with the CPS and declining further, to approximately 1.39 gigatonnes of carbon dioxide equivalent by 2060 (Figure 2.4b).

To underscore the indispensable role of non–carbon dioxide GHGs in national climate strategies, China’s updated NDCs should include explicit peak targets for non–carbon dioxide GHGs as soon as possible. Furthermore, carbon neutrality goals should explicitly account for these gases to highlight their integral role in the country’s overall strategy for addressing climate change.

Figure 2.4a: Changes in China’s carbon dioxide emissions under different scenarios

Figure 2.4b: Changes in China’s non–carbon dioxide greenhouse gas emissions under different scenarios

Source: Authors’ calculation.

Concurrent with decarbonisation, the energy transition has also yielded substantial improvements in air quality. Historical evidence indicates that GHG emissions and air pollution challenges in developed countries did not emerge simultaneously. As a result, these two issues have traditionally been treated as separate problems. However, in contemporary China, they are deeply interconnected, representing critical domains for integrated governance. China is currently one of the world’s largest emitters of sulphur dioxide, nitrogen oxides and particulate matter, with ambient concentrations of these pollutants exceeding the safe levels recommended by the World Health Organization (WHO). This has led to a range of environmental and public health issues (Li et al. 2020).

Based on the energy transition scenarios analysed in this study, China’s energy consumption structure is expected to undergo significant transformations in the coming decades. By continuously strengthening source control and implementing comprehensive pollution control measures across key industries, emissions of air pollutants are projected to decline substantially. Under the EAS, greater reductions are achieved than under the CPS, with sulphur dioxide, nitrogen oxides and PM2.5 emissions declining to 920,000 tonnes, 2.19 million tonnes and 630,000 tonnes, respectively, by 2060 (Figure 2.5a). Using these emission reductions as inputs, simulations conducted with the EMEP-CTM atmospheric transport model, integrated into the GAINS framework (Amann et al. 2020), it is projected that annual average PM2.5 concentrations nationally will decrease to 35.4 micrograms per cubic metre (µg/m³) by 2030 and 17.4 µg/m³ by 2060 under the CPS. The EAS reduces PM2.5 concentrations by an additional 2.8 µg/m³ in 2060 compared with the CPS (Figure 2.5b).

Accelerating the energy transition is expected to enable most regions in China to meet the national secondary air quality standard for PM2.5 (≤ 35 µg/m³) by approximately 2030, marking significant progress towards achieving the ‘Beautiful China’ initiative. However, after the initial substantial reductions, the rate of decline in annual average PM2.5 concentrations is expected to slow, making further reductions increasingly challenging. Even under the EAS, China’s PM2.5 concentrations in 2060 are projected to remain well above the revised 2021 WHO guideline of 5 µg/m³. This underscores the need for a scientifically designed, integrated approach that leverages the shared origins of air pollutants and carbon dioxide emissions. By adopting coordinated strategies for long-term decarbonisation and pollution mitigation, China can achieve greater synergies, facilitating fundamental improvements in air quality while advancing its climate goals.

Accelerating the energy transition can significantly enhance public health. The cumulative impacts of air pollution pose pressing challenges to society and public health. In China, approximately 1 million premature deaths annually are attributed to atmospheric pollutant emissions (Wang et al. 2024). This study further estimates the number of premature deaths caused by five PM2.5-related diseases under different scenarios: chronic obstructive pulmonary disease, lung cancer, ischemic heart disease, cerebrovascular disease and lower respiratory infections.

Figure 2.5a: Changes in emissions of sulphur dioxide, nitrogen oxides and PM2.5

Figure 2.5b: Changes in PM2.5 concentration

Source: Authors’ calculation.

Figure 2.6: Changes in premature deaths related to PM2.5 exposure

Source: Authors’ calculation.

Under the EAS, accelerated reductions in PM2.5 concentrations are projected to result in greater improvements in public health. By 2030, the total number of premature deaths is estimated to reach 1.55 million, with 91,000 premature deaths avoided compared with the CPS, underscoring the substantial health benefits of an accelerated transition. By 2060, the health co-benefits of coordinated emission reductions are further amplified, as PM2.5-related premature deaths decrease to 970,000 (Figure 2.6). These findings demonstrate that deep transformations in the energy structure, coupled with stricter end-of-pipe pollution control measures, can generate significant health benefits. Such improvements in air quality can offset much of the employment loss associated with population ageing, highlighting the broader socioeconomic advantages of pursuing an accelerated energy transition.

While the substantial costs of transformative change cannot be overlooked, China’s energy transition offers significant long-term net social benefits. Adopting a social perspective, this study systematically evaluates the potential impacts of China’s energy transition and establishes a cost–benefit analysis framework (Table 2.5). This framework integrates energy, economic, climate and health-related costs and benefits, providing a quantitative assessment of each dimension.

Table 2.5: Cost–benefit analysis framework for China’s low-carbon energy transition

Classification	Composition	Definition
Benefits	Climate benefits	Benefits derived from carbon emission reductions induced by energy transition.
	Health benefits	Monetisation of avoided premature deaths and illnesses resulting from marginal reductions in long-term PM2.5 exposure, due to synergistic effects of carbon reduction and pollution control.
Costs	Energy costs	Changes in energy costs incurred by various technologies and production processes.
	Economic costs	Initial investment and operational maintenance costs associated with deploying energy transition–related technologies.

Source: Authors’ compilation.

Total costs under both the CPS and the EAS are projected to increase steadily, driven by higher economic output, large-scale deployment of cleaner low-carbon technologies and substantial investments in transformative and disruptive innovations. These trends highlight that the energy transition is a sustained, high-investment process, with cumulative costs estimated at US$13.2 trillion under the CPS and US$18.8 trillion under the EAS by 2060 (Figure 2.7). Consequently, policymakers and industry stockholders should act promptly to define future industrial structural layouts, prioritise key directions for breakthroughs in emerging technologies and enhance research and innovation capacities. These measures will help mitigate future cost burdens and maximise potential benefits.

Figure 2.7: Cumulative costs and benefits of China’s energy transition

Source: Authors’ calculation.

Nevertheless, the benefits—particularly those related to climate and public health—are expected to far outweigh the associated costs. Both scenarios yield positive net social benefits, with the EAS demonstrating significantly greater net benefits compared with the CPS. This underscores the importance of accelerating the energy transition and should strengthen policymakers’ confidence and determination to pursue this path. Net social benefits are projected to grow over time: under the EAS, cumulative net social benefits reach US$5.3 trillion in 2030, US$13.6 trillion in 2050 and US$24.8 trillion by 2060. These findings highlight the long-term necessity of implementing comprehensive policy measures to support an accelerated energy transition.

Moreover, a fully realised energy transition is expected to substantially improve socioeconomic footprints, enhance household welfare and boost employment. However, due to data limitations, this study does not quantify these additional economic benefits, suggesting that the net social benefits of the energy transition may be even greater than estimated.

China’s exports of PV and wind turbine technologies have generated significant global emission reduction spillover effects. By 2023, the net exports of Chinese PV modules and critical components had contributed to potential carbon reductions exceeding 20 gigatonnes in other countries over their full lifecycle. Similarly, exports of wind turbines and critical components contributed more than 3 gigatonnes of potential carbon reductions. With the continued advancement of the global energy transition, China’s PV and wind exports are expected to maintain robust growth. Under the CPS, the cumulative carbon reductions from Chinese PV and wind exports are projected to surpass 140 gigatonnes by 2060, including approximately 128 gigatonnes from PV exports (Figure 2.8a) and 12 gigatonnes from wind exports (Figure 2.8b). Under the EAS, these cumulative reductions are expected to exceed 185 gigatonnes by 2060, with PV exports contributing around 170 gigatonnes and wind exports approximately 16 gigatonnes.

More importantly, a combination of factors has driven continuous cost reductions in China’s PV and wind industries, significantly lowering the global costs of the energy transition. According to the International Renewable Energy Agency (IRENA 2024), the global average levelised cost of electricity for solar PV has declined by more than 80 per cent in the past decade, with China playing a pivotal role. Similarly, Wood Mackenzie (Forbes-Cable 2023) reports that the cost of producing one megawatt (MW) of PV electricity in China is 11–64 per cent lower than in other markets. The cost declines in China’s PV and wind sectors can be attributed to three key factors. First, policy initiatives and public awareness campaigns have fostered a broad social consensus about and stable expectations of the energy transition. This has incentivised corporate investment in new-energy technologies. Since 2021, China has consistently ranked first globally in clean energy investment. Second, stable transition expectations have facilitated rapid deployment of new-energy infrastructure, such as wind and solar power. This has created vast opportunities for the adoption of advanced technologies and the upgrading of energy products, effectively reducing costs and promoting economies of scale. Third, China’s robust manufacturing capabilities have enhanced its competitiveness in equipment production, technological research and development (R&D) and industrialisation related to the energy transition. This has enabled the efficient production of high-quality products essential for global energy transition efforts.

Figure 2.8a: Contribution of China’s PV exports to global carbon emission reductions

Figure 2.8b: Contribution of China’s wind turbine exports to global carbon emission reductions

Source: Authors’ calculation.

Conclusions and policy implications

This study develops an innovative integrated assessment modelling framework to evaluate the comprehensive impacts and spillover effects of China’s energy transition. The framework systematically simulates and analyses the multidimensional impacts of varying depths and paces of energy transition on energy and economic systems, climate change, environmental outcomes and public health. A particular focus is placed on assessing the global emission reduction spillover effects of China’s PV and wind turbine exports, enabling a comprehensive evaluation of both the integrated impacts and the spillover effects of China’s energy transition.

Given the substantial net social benefits and significant global carbon emission reduction effects derived from accelerating the energy transition, this study argues that policymakers should maintain strategic resolve in advancing the energy transition and achieving the dual carbon goals (carbon peak and carbon neutrality). In the face of escalating global climate crises and increasing domestic structural emission reduction pressures, China should use its dual carbon goals as a guiding framework to reinforce its strategic commitment to the low-carbon restructuring of its energy system.

Although the energy transition entails incremental investment pressures, the comprehensive benefits—including climate change mitigation, health improvements, job creation and enhanced energy security—are significantly positive and continue to grow over time. To overcome barriers related to low-carbon financing mechanisms, technology diffusion and regulatory systems, China should plan clear and actionable long-term deep decarbonisation pathways for the 2030–60 period. These pathways should align with current energy conservation and carbon reduction policies, the forthcoming 2035 NDC targets and their implementation plans, while also accelerating absolute carbon dioxide emission reductions after 2030. Additionally, China should strengthen the management and control of non–carbon dioxide GHGs, such as methane, nitrous oxide and fluorinated gases, while prioritising R&D of breakthrough technologies for deep emission reductions. Efforts should also be directed towards enhancing agricultural and forestry carbon sinks to achieve economy-wide deep decarbonisation and reduction of all GHGs.

China’s green transformation is globally significant. Leveraging its world-leading industrial scale and technological innovation capabilities, China has established substantial cost advantages in new-energy sectors such as PV module and wind turbine manufacturing. Its export trade not only directly alleviates global financial pressures for the energy transition but also contributes positively to global carbon dioxide emission reductions. To further advance global energy transition efforts, it is recommended to deepen international collaboration along the green industry value chain. Technologically advanced nations could focus on core technology R&D, while emerging economies capitalise on their manufacturing strengths to establish a tiered collaborative network encompassing R&D, manufacturing and application. At the same time, caution is needed to prevent unilateral trade protectionism from driving up transition costs. A tariff preference framework for new-energy products should be developed to transform the production capacity advantages of manufacturing powerhouses such as China into accelerators for global carbon neutrality.

References

Amann, Markus, Gregor Kiesewetter, Wolfgang Schöpp, Zbigniew Klimont, Wilfried Winiwarter, Janusz Cofala, Peter Rafaj, Lena Höglund-Isaksson, Adriana Gomez-Sabriana, Chris Heyes, Pallav Purohit, Jens Borken-Kleefeld, Fabian Wagner, Robert Sander, Hilde Fagerli, Agnes Nyiri, Laura Cozzi, and Claudia Pavarini. 2020. ‘Reducing Global Air Pollution: The Scope for Further Policy Interventions.’ Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2183: 20190331. doi.org/10.1098/rsta.2019.0331.

Cao, Jie, Chunxue Yang, Jianxin Li, Renjie Chen, Bingheng Chen, Dongfeng Gu, and Haidong Kan. 2011. ‘Association between Long-Term Exposure to Outdoor Air Pollution and Mortality in China: A Cohort Study.’ Journal of Hazardous Materials 186, nos 2–3: 1594–600. doi.org/10.1016/j.jhazmat.2010.12.036.

China National Offshore Oil Corporation (CNOOC) Energy Economics Institute (CNEEI). 2024. Energy Outlook 2060. Beijing: CNOOC Energy Economics Institute.

Duan, Hongbo, Sheng Zhou, Kejun Jiang, Christoph Bertram, Mathijs Harmsen, Elmar Kriegler, Detlef P. van Vuuren, Shouyang Wang, Shinichiro Fujimori, Massimo Tavoni, Xi Ming, Kimon Keramidas, Gokul Iyer, and James Edmonds. 2021. ‘Assessing China’s Efforts to Pursue the 1.5ºC Warming Limit.’ Science 372, no. 6540: 378–85. doi.org/10.1126/science.aba8767.

Energy Research Institute (ERI). 2024. China Energy Transformation Outlook 2024. Beijing: Energy Research Institute of the Chinese Academy of Macroeconomic Research.

Forbes-Cable, Malcolm. 2023. Top of the Charts: Five Low-Carbon Tech Trends Worth Tracking. Online post, December. Edinburgh: Wood Mackenzie. www.woodmac.com/horizons/five-low-carbon-tech-trends/.

Global Burden of Disease (GBD) 2019 Risk Factors Collaborators. 2020. ‘Global Burden of 87 Risk Factors in 204 Countries and Territories, 1990–2019: A Systematic Analysis for the Global Burden of Disease Study 2019.’ The Lancet 396, no. 10258: 1223–49. doi.org/10.1016/s0140-6736(20)30752-2.

He, Jiankun, Zheng Li, Xiliang Zhang, Hailin Wang, Wenjuan Dong, Ershun Du, Shiyan Chang, Xunmin Ou, Siyue Guo, Zhiyu Tian, Alun Gu, Fei Teng, Bin Hu, Xiu Yang, Siyuan Chen, Mingtao Yao, Zhiyi Yuan, Li Zhou, Xiaofan Zhao, Ying Li, and Danwei Zhang. 2022. ‘Towards Carbon Neutrality: A Study on China’s Long-Term Low-Carbon Transition Pathways and Strategies.’ Environmental Science and Ecotechnology 9: 100134. doi.org/10.1016/j.ese.2021.100134.

Hepburn, Cameron, Ye Qi, Nicholas Stern, Bob Ward, Chunping Xie, and Dimitri Zenghelis. 2021. ‘Towards Carbon Neutrality and China’s 14th Five-Year Plan: Clean Energy Transition, Sustainable Urban Development, and Investment Priorities.’ Environmental Science and Ecotechnology 8: 100130. doi.org/10.1016/j.ese.2021.100130.

Intergovernmental Panel on Climate Change (IPCC). 2019. 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventory. Geneva: IPCC.

Intergovernmental Panel on Climate Change (IPCC). 2023. Climate Change 2023: Synthesis Report. Geneva: IPCC. doi.org/10.59327/ipcc/ar6-9789291691647.

International Energy Agency (IEA). 2024. World Energy Outlook 2024. Paris: International Energy Agency. www.iea.org/reports/world-energy-outlook-2024.

International Renewable Energy Agency (IRENA). 2024. Renewable Power Generation Costs in 2023. Abu Dhabi: International Renewable Energy Agency. www.irena.org/Publications/2024/Sep/Renewable-Power-Generation-Costs-in-2023.

Jin, Yana, and Shiqiu Zhang. 2018. ‘An Economic Evaluation of the Health Effects of Reducing Fine Particulate Pollution in Chinese Cities.’ Asian Development Review 35, no. 2: 58–84. doi.org/10.1162/adev_a_00114.

Kilmont, Zbigniew. 2025. Greenhouse Gas and Air Pollution Interactions and Synergies (GAINS). Online post. Austria: International Institute for Applied Systems Analysis. iiasa.ac.at/models-tools-data/gains.

Li, Bo-Shu, Yan Chen, Shaohui Zhang, Zheru Wu, Janusz Cofala, and Hancheng Dai. 2020. ‘Climate and Health Benefits of Phasing Out Iron & Steel Production Capacity in China: Findings from the IMED Model.’ Climate Change Economics 11, no. 3: 2041008. doi.org/10.1142/s2010007820410080.

Li, Lili, and Araz Taeihagh. 2020. ‘An In-Depth Analysis of the Evolution of the Policy Mix for the Sustainable Energy Transition in China from 1981 to 2020.’ Applied Energy 263: 114611. doi.org/10.1016/j.apenergy.2020.114611.

Liu, Da, Jinchen Liu, Shoukai Wang, Ming Xu, and Syed Junaid Akbar. 2019. ‘Contribution of International Photovoltaic Trade to Global Greenhouse Gas Emission Reduction: The Example of China.’ Resources, Conservation and Recycling 143: 114–18. doi.org/10.1016/j.resconrec.2018.12.015.

Liu, Zhu, Zhu Deng, Gang He, Hailin Wang, Xian Zhang, Jiang Lin, Ye Qi, and Xi Liang. 2021. ‘Challenges and Opportunities for Carbon Neutrality in China.’ Nature Reviews Earth & Environment 3: 141–55. doi.org/10.1038/s43017-021-00244-x.

Montzka, S.A., E.J. Dlugokencky, and J.H. Butler. 2011. ‘Non-CO₂ Greenhouse Gases and Climate Change.’ Nature 476: 43–50. doi.org/10.1038/nature10322.

Pan, Xiongfeng, Shucen Guo, Haitao Xu, Mengyuan Tian, Xianyou Pan, and Junhui Chu. 2022. ‘China’s Carbon Intensity Factor Decomposition and Carbon Emission Decoupling Analysis.’ Energy 239, Part C: 122175. doi.org/10.1016/j.energy.2021.122175.

Pope, C. Arden, III, Richard T. Burnett, Michael J. Thun, Eugenia E. Calle, Daniel Krewski, Kazuhiko Ito, and George D. Thurston. 2002. ‘Lung Cancer, Cardiopulmonary Mortality, and Long-Term Exposure to Fine Particulate Air Pollution.’ JAMA 287, no. 9: 1132–41. doi.org/10.1001/jama.287.9.1132.

Ricke, Katharine, Laurent Drouet, Ken Caldeira, and Massimo Tavoni. 2018. ‘Country-Level Social Cost of Carbon.’ Nature Climate Change 8: 895–900. doi.org/10.1038/s41558-018-0282-y.

Rogelj, Joeri, and Robin D. Lamboll. 2024. ‘Substantial Reductions in Non-CO₂ Greenhouse Gas Emissions Reductions Implied by IPCC Estimates of the Remaining Carbon Budget.’ Communications Earth & Environment 5: 35. doi.org/10.1038/s43247-023-01168-8.

United Nations Department of Economic and Social Affairs, Population Division (UNDESA). 2024. World Population Prospects 2024: Summary of Results. UN DESA/POP/2024/TR/No. 9. New York: UNDESA. desapublications.un.org/publications/world-population-prospects-2024-summary-results.

United Nations Human Settlements Programme (UN-Habitat). 2024. World Cities Report 2024: Cities and Climate Action. Nairobi: United Nations Human Settlements Programme. unhabitat.org/wcr/.

Wang, Huaibin. 2023. ‘Life Cycle Carbon Footprint and Carbon Emission Reduction Potential of Photovoltaic Power Generation.’ Energy of China 45, no. 8: 34–44.

Wang, Mengya, Yingying Liu, Sumei Li, Parham Azimi, Sha Chen, and Steve Hung Lam Yim. 2024. ‘Air Quality and Health Benefits of Achieving Carbon-Neutrality in Building Sector over Beijing, China.’ Journal of Environmental Management 370: 122652. doi.org/10.1016/j.jenvman.2024.122652.

Wang, Tianpeng, Fei Teng, Xu Deng, and Jun Xie. 2022. ‘Climate Module Disparities Explain Inconsistent Estimates of the Social Cost of Carbon in Integrated Assessment Models.’ One Earth 5, no. 7: 767–78. doi.org/10.1016/j.oneear.2022.06.005.

Xu, Meng, Zhongfeng Qin, and Shaohui Zhang. 2021. ‘Carbon Dioxide Mitigation Co-Effect Analysis of Clean Air Policies: Lessons and Perspectives in China’s Beijing–Tianjin–Hebei Region.’ Environmental Research Letters 16, no. 1: 015006. doi.org/10.1088/1748-9326/abd215.

Yang, Dong, J. Liu, Jianxin Yang, and Ding Ning. 2015. ‘Carbon Footprint of Wind Turbine By Life Cycle Assessment.’ Huanjing Kexue Xuebao/Acta Scientiae Circumstantiae 35, no. 3: 927–34. www.researchgate.net/publication/281961611_Carbon_footprint_of_wind_turbine_by_life_cycle_assessment.

Zhang, Shu, Wenying Chen, Qiang Zhang, Volker Krey, Edward Byers, Peter Rafaj, Binh Nguyen, Muhammad Awais, and Keywan Riahi. 2024. ‘Targeting Net-Zero Emissions While Advancing Other Sustainable Development Goals in China.’ Nature Sustainability 7: 1107–19. doi.org/10.1038/s41893-024-01400-z.

Zheng, Heran, Yangchun Bai, Wendong Wei, Jing Meng, Zhengkai Zhang, Malin Song, and Dabo Guan. 2021. ‘Chinese Provincial Multi-Regional Input–Output Database for 2012, 2015, and 2017.’ Scientific Data 8: 244. doi.org/10.1038/s41597-021-01023-5.

---

1. 1 Since the Eighteenth National Congress of the Communist Party of China (CPC), in the face of changes in energy supply and demand patterns and new trends in international energy development, the CPC Central Committee with President Xi Jinping at its core has proposed a new energy security strategy of ‘four revolutions and one cooperation’ (a revolution in energy consumption, supply, technology and systems, and full-scale international cooperation) to provide a guide for high-quality energy development in the new era.

2. 2 See details at the CEADs website: www.ceads.net.cn/data/emission_factors/.

3. 3 The CPC first proposed the ‘Two Centenary Goals’ in 1997. The first centenary goal was, by 2021—the centenary of the CPC—to build China into a moderately prosperous society in all respects and doubling GDP and per capita income against 2010. The second centenary goal is, by 2049—the centenary of the People’s Republic of China—to build a modern socialist country that is prosperous, strong, democratic, culturally advanced, harmonious and beautiful.