Achieving China's energy and climate policy targets in 2030 under multiple uncertainties

Estimate of China's energy carbon emissions peak and analysis on electric power carbon emissions

Role of non-fossil energy in meeting China's energy and climate target for 2020

Exploring more emissions reduction opportunities for China's energy sector and lowering China's decarbonisation costs are essential to fulfilling China's nationally determined contributions (NDCs) and making China's sustainable development more feasible. This study explored emissions reduction opportunities for China's energy sector in international bilateral emissions trading systems (ETSs) using a CGE (computable general equilibrium) model. This study revealed that linking China's ETS to those of regions with lower decarbonisation responsibilities, which tend to be developing regions, could lower China's carbon prices, thus increasing China's domestic energy supply and lowering energy prices (and vice versa). Meanwhile, the volume of emissions from regions linked to China also significantly affected the degree of the change in China's carbon prices. Among these, ETS links to India and Russia could reduce China's carbon price from 7.80 USD/ton under domestic ETS to 2.16 USD/ton and 6.79 USD/ton, allowing the energy sector and energy-intensive sectors to increase greenhouse gas emissions by 1.14% and 7.05%, respectively, without falling short of meeting its NDC targets. In contrast, as a consequence of links with the United States and the European Union, China's carbon price could increase to 5.37 USD/ton and 1.79 USD/ton, respectively, which would limit China's energy and energy-intensive sectors to emitting 5.45% and 2.24% fewer greenhouse gases in order to meet its NDC targets.

Climate change mitigation issues including China’s carbon emission status, the mitigation potential and cost in different sectors, the target of 40%–45% reduction of emission intensity of GDP in 2020 compared with the 2005 level, and conditions and uncertainties of the carbon emission peak are analyzed and assessed in the Third China National Climate Change Assessment Report and summarized in this paper. Economic structure adjustment has played and is expected to continue to play important role for carbon mitigation. Development of nuclear and renewable power would contribute to around 2 billion tons and 3.7 billion tons carbon reductions by 2020 and 2030 respectively. Key energy saving and low carbon technologies in the end-use sectors such as industry, transportation and building are listed and assessed. The mitigation potential and cost curve for steel is provided as an example to show that a large amount of carbon emissions could be reduced with minus mitigation cost partly resulting to energy saved. For industry process, carbon mitigation potentials would be around 420 million tons and 770 million tons by 2020 and 2030 respectively. Carbon mitigation potentials from LULUCF (Land use, land use change and forestry) are still uncertain and needed further research. For the assessment of 45% carbon intensity reduction target in 2020, it is concluded that economic structure adjustment, energy efficiency improvement, development of non-fossil energy, building and transportation would contribute to 33.4%, 28.5%, 20.4% and 17.3% of the total reductions. Assuming GDP growth rate as 6%–7% during 2010–2030, energy intensity reduction rate as 15% during 2015–2020, 14% during 2020–2025, and 13% during 2025–2030, the total primary energy consumption would be around 6 billion tons. To control coal use to less than 50% of the total primary energy consumption, while increasing the share of nature gas to over 10%, and the share of new and renewable energy to 20% or higher, carbon emissions would peak around 2030 at 11 to 12 billion tons. Finally, Climate change mitigation strategies to facilitate the achievement of China’s carbon emission peak target are proposed. It’s also suggested that measures are needed to accelerate the economy restructuring and development modes shift, to control the growth rate of total energy demand, to maintain a sustainable energy system with the new and renewable energy as its main components, and to achieve the carbon emission peak target by sector and region.

Can China achieve its 2030 energy development targets by fulfilling carbon intensity reduction commitments?

Limiting global warming to below 2 °C or 1.5 °C (relative to pre-industrial levels) has been broadly accepted as the long-term target to avert unbearable climate damages (IPCC 2018). To fulfill this climate goal, the world must rapidly reduce GHG emissions (mainly carbon emissions) to or below zero, which relies on implementing concrete emissions control policies and a green transformation (Rogelj et al. 2015), thus imposing severe challenges for countries at all development stages. As one of the fastest-growing economies, China emitted about 10 billion tons of CO2 in 2019, over 28% of global emissions (BP. 2020). Despite a slight decline in 2020, China’s carbon emissions are likely to increase again in the post-COVID-19 era (Le Quere et al. 2021). In 2015, China pledged to peak its carbon emissions by 2030 in its Nationally Determined Contributions (NDC) for the Paris Agreement. In 2020, China updated its climate targets with greater ambitions—a commitment to neutralize its CO2 emissions by 2060. Thus, it is crucial to investigate the design, implementation, and impacts of China’s climate policies, also providing valuable insights for climate governance in other regions. In the recent decades, several policies have helped China achieve its previous climate target, i.e., reducing its carbon intensity by 40–45% in 2020 relative to the 2005 level (Tang et al. 2019). These policies include the energy transition from fossil fuels to renewables (Duan et al. 2019), energy saving associated with efficiency enhancement (Huang et al. 2019), as well as economic transformation by total factor productivity (TFP) improvement (Yang et al. 2021). In the meantime, emerging climate policies such as carbon pricing and renewable energy incentives are expected to play an increasingly important role in reaching ambitious long-term goals (Yuan et al. 2020). With the development of big-data processing and computing technologies, the impacts of these energy and climate policies can be simulated and analyzed using various methodologies, including top-down general equilibrium models (Wu et al. 2020; Yuan et al. 2020), bottom-up technology aggregated models (Wang et al. 2020), climate-economic integrated models (Newbold and Marten 2014; Duan et al. 2019), and state-of-the-art decomposition methods (Chen et al. 2020). These methodologies need to be refined to help assessing different policy goals, particularly given multiple uncertainties (Otto et al. 2015). At the backdrop of these points, we initiated this Topical Collection, which includes six papers. The topics of the selected papers range from relationships between CO2 emissions and economic growth, policy and technology options for green transformation, to spatial inequality of capital distribution towards sustainability all embedded within the context of addressing global climate change from the regional perspective of the world’s largest emitter.

Can the Energy Internet promote China's energy system to achieve carbon emission peak goal?

Synergizing China's energy and carbon mitigation goals: General equilibrium modeling and policy assessment

Effects of climate and energy policy related measures and targets on the future structure of the European energy system in 2020 and beyond

Optimal quota in China's energy capping policy in 2030 with renewable targets and sectoral heterogeneity

How to deal with carbon emissions—a rare externality that spans a large time frame and geographical scope—is a difficult task for the world. This task is particularly challenging for China, mainly in that the country must coordinate dual objectives, including existing economic growth targets and the newly added carbon neutrality goal. Over the past 40 years of reform and opening up, China has been setting economic growth targets and striving to achieve them. In recent years, although growth targets have softened along with the secular decline in potential growth rate, economic growth remains a top priority for China, the world’s largest developing country. We expect China to reach the current standard for a high-income country by the end of the 14th Five-Year Plan period, and to double its GDP or per capita income by 2035. Currently, China is adding a new constraint over the next 40 years. As the world’s largest carbon emitter, China has set out a clear timetable for carbon neutrality—to reduce its carbon emission intensity in 2030 by more than 65% from the 2005 level, and reach the peak of carbon dioxide emissions by 2030 and become carbon neutral by 2060. We note that it will take 71 and 45 years, respectively, for the EU and the US to achieve the carbon neutrality goal from peak carbon emissions (reached by the EU in 1979 and by the US in 2005) to net zero emissions. China’s aggressive timetable to achieve carbon neutrality within 40 years means that the country will face a much steeper slope of carbon emissions than the EU and the US. How will China strike a balance between the objectives of economic growth in the past 40 years and carbon neutrality in the next 40 years? We discuss this issue from an aggregate and a structural point of view. In our aggregate analysis, the most important task is to identify the peak of China’s carbon emissions in 2030. We believe that in order to take economic growth and emission reduction into consideration, it is more appropriate to set the carbon peak target in a range to avoid rigid constraints. From a structural perspective, we discuss how China can achieve its carbon peak and neutrality goals. Under the framework of a “green premium”, we come up with a preliminary idea of “technology + carbon pricing” based on the analysis of eight high-emission industries. We prove that this idea can strike a balance between the constraints of economic growth and carbon neutrality goals through general equilibrium analysis using the computable general equilibrium (CGE) model. Finally, we incorporate social governance into our analysis by discussing the meaning of a negative green premium, and arrive at this formula: the road to carbon neutrality = technology + carbon pricing + social governance.

Carbon pricing is about the explicit pricing of greenhouse gas (GHG) emissions, of which carbon dioxide is the most important. GHG emissions, which are normally measured in tonnes of carbon dioxide equivalent units, are responsible for global warming and hence the greatest environmental externality of our age. Carbon pricing is a mechanism for making society account for the external damage caused by carbon emissions in economic decision making. There are two main ways of pricing carbon dioxide emissions, either via a carbon tax or via the introduction of an emissions trading scheme whereby those emitting carbon into the atmosphere are required to surrender permits which reflect the quantity of emissions they are responsible for. These emission permits are tradeable and hence command a price and, in some respects, operate in a similar way to a carbon tax. Thus, we will discuss both carbon pricing and emissions trading, as the literature on both is closely related. Emissions trading exists for certain other pollutants (such as sulphur dioxide) and we will discuss some of the literature related to this. However, most of the literature on emissions trading relates to carbon dioxide emissions, as these are by far the most valuable traded emissions globally. The literature on carbon pricing and emissions trading is wide ranging and constantly being updated with new analyses. Much of the literature is written by economists who are seeking to apply market-based approaches to the solution of environmental problems. The article starts by looking at the general context in which carbon pricing and emissions trading sits before discussing introductory texts which relate to the subject and going on to introduce the relevant classic literature in environmental economics. It then proceeds to more applied literature, beginning with discussions of early examples of emissions trading and carbon taxation, before continuing to studies of the impact of carbon pricing and emissions trading and those which explain the nature of the schemes we observe. The article continues with literature which looks at the Europe Union Emissions Trading Scheme (EU ETS) for GHGs and other important carbon pricing schemes. It then moves on to the literature on the prospects for a global carbon price, on interactions with other climate policies, on distributional concerns about the imposition of a price on carbon. Finally, it concludes with an introduction to relevant official publications and sources of data on carbon emissions and carbon prices.

Global excessive CO2 emissions have caused serious environmental and health problems, such as global warming, melting glaciers, droughts, floods, and extreme temperatures, and have become a common challenge for the world. China has set a dual carbon goal, with the peak carbon emissions before 2030. In China, the building sector accounts for 50.9% of the country’s carbon emissions. In particular, public buildings are characterized by a high carbon emission intensity, accounting for 38.6% of carbon emissions in the building sector, which affects the achievement of the dual carbon goal in China’s building sector. Establishing a reasonable baseline of carbon emissions contributes to quota management and trading of carbon emissions for public buildings in Tianjin, China, and will ultimately contribute to the reduction of carbon emissions. This study investigates the operational energy consumption and carbon emissions of 721 public buildings in Tianjin (including electricity, natural gas, and district heating). The applicability of the Quartile method and the K-means clustering algorithm was compared to determine the carbon emission baseline of different types of public buildings, such as constraint value, guiding value, and advanced value, based on which the dynamic baseline from 2022 to 2030 was determined. The results show that the advanced value, guiding value, and constraint value of the Tianjin public building carbon emission baseline obtained using the Quartile method are more reasonable than those obtained by the K-means clustering algorithm. Furthermore, the carbon emission baseline in 2030 will be reduced by 3.4~9.2% compared to 2022. This study can guide the formulation of carbon emission trading schemes, and support Tianjin’s building sector to achieve the “carbon peak”.

Carbon emission scenarios of China's power sector: Impact of controlling measures and carbon pricing mechanism

Analysis and forecast of China's energy consumption structure