China

Historical emissions data excl. the LULUCF sector for all GHGs was obtained from the PRIMAP-hist national historical emissions time series and covers the period from 1990 to 2022 (Gütschow et al., 2024). This gas-by-gas breakdown by sector: energy, industrial process, agriculture, and waste. Historical emissions data for the LULUCF sector are based on the Chinese inventory as submitted to the UNFCCC for the years 1994, 2005, 2010, 2012, 2014 and 2018 and is not extrapolated onwards due to accounting uncertainties (Government of China, 2023).

As of September 2018, the CAT uses 100-year Global Warming Potentials (GWPs) from the IPCC Fourth Assessment Report (AR4).

We estimated China‘s energy-related CO₂ emission in 2023 based on growth rates on fossil fuel consumptions projected by Global Carbon Budget (Friedlingstein et al., 2023) and the TPED from World Energy Outlook (WEO) (IEA, 2023b) Stated Policies Scenario (STEPS) and China Energy Transformation Outlook (CETO) (ERI et al., 2023) Baseline Scenario (BLS).

For China’s updated NDC targets, we quantify the peaking target, the non-fossil target, renewable energy capacity target, and the carbon intensity target separately. For the quantification of all targets, we also incorporate achievement of the demand-side policies in China’s current policies pathway (CPP).

The elements of China’s targets that we quantify apply to CO₂ only (excl. LULUCF), given the scope of the targets. To calculate total GHG emissions (excl. LULUCF), we add non-CO₂ emissions based on our current policies projections as described below.

Peaking Target:

Since the NDC contains the target of peaking CO₂ emissions before 2030, the implications for what an “NDC scenario” constitutes can be interpreted in a variety of ways—for instance, the least ambitious way would be to assume emissions simply peak by 2030 while a more ambitious interpretation would be to assume that this peaking happens earlier at an arbitrary date. According to our current policy projections, China’s emissions are due to peak around 2025 in both scenarios but either roughly plateau (CPP max) or drop (CPP min). The quantification of the peaking target range is equivalent to the emissions level in our CPP in 2030.

Non-Fossil Target:

China’s NDC non-fossil target has been increased to 25% in 2030 in its updated NDC while China’s 14th FYP includes the now intermediary target of 20% by 2025. In our CPP projections, China is projected to overachieve these targets comfortably.

To calculate energy-related CO₂ emissions based on the 2030 target, we:

- Recalculate the total primary energy demand (TPED) from WEO (IEA, 2023b) STEPS and CETO (ERI et al., 2023) BLS

- Align TPED to the CPP scenarios. Technology shares for non-fossil sources are decreased to achieve the 25% share target (no more, no less), while coal and gas are assumed to replace the gap from decreased non-fossil sources

- Adjust individual non-fossil energy sources equally based on their relative share of non-fossil energy demand in the CPPs

Renewable Capacity Target:

The NDC includes a target of 1,200 GW of wind and solar installed by 2030. In our CPP range, China is projected to overachieve this target comfortably for both technologies. To quantify emission levels under this target, solar and wind capacity is revised downward to 1,200 GW in total according to their respective ratio expected in 2030. Based on CPP min, we expect approximately 330 GW of wind power and 870 GW of solar PV installed in China; based on CPP max, we expect approximately 485 GW of wind power and 715 GW of solar PV installed in China. Like the quantification of the non-fossil share targets, other elements are assumed to be the same as the CPPs. For example, other supply technologies are expected to supply the same amount of power. Overall primary energy demand in the country is also assumed to be the same as the CPPs. We assume that the difference in energy supplied (less wind and solar) is supplied by coal and gas. Given that fossil fuel capacity is not replaced by wind and solar one-for-one, overall power capacity in China’s energy system decreases with the achievement of this target.

Carbon Intensity Targets:

For the calculation of the intensity targets for 2020 and 2030, we use historical emissions data from China’s most recent inventory submission to the UNFCCC and historical GDP data from China’s Statistical Yearbook up to 2018 (China, 2018). For historical years after 2018, we deviate from official Chinese data due to annual inconsistencies; we now apply latest official growth rates from the Chinese government (rather than absolute numbers), validated by international organisations such as the World Bank and IMF, to establish data until the latest historical year. GDP projections until 2030 are mainly based off IMF (2023) until 2028 and supplemented with near-term forecasts from a mix of domestic and international sources (thus establishing an optimistic and pessimistic range for growth). We also integrate the underlying GDP forecast from WEO STEPS 2023 as part of the range (IEA, 2023b). We assume that the carbon intensity target applies to all CO₂ emissions excluding LULUCF. The emissions quantification for carbon intensity targets changes annually, due to updated forecasts in China’s GDP trajectory.

A note on the global aggregation:

China’s rating is based on the two NDC emissions targets which are estimated to have the lowest emission levels: the lower end of the carbon intensity target in 2030 and the upper end of the peaking target (which is the CPP max). We employ this method as we try to capture the likely range of China’s emissions levels when achieving their NDC, but there is uncertainty on absolute emission levels as China has several targets: China’s peaking target is guaranteed to be achieved by definition, but which of China’s remaining NDC targets is achieved (or if they all are) is uncertain.

We exclude the most pessimistic interpretations—target with the highest expected emissions—as we would be assuming they emit more than the CPP analysis shows. We also do not take only the most optimistic interpretation—lower bound of China’s carbon intensity target— as this is not constrained target (fluctuating year to year depending on economic forecasts). If we only took one target, we would then be assuming China’s other quantitative targets are completely null. The emission levels of all of China’s targets are dependent on future developments (e.g., growth in energy consumption, GDP). We thus take a median approach to capture the middle range (median) of the two most stringent targets to be conservative: the minimum of the carbon intensity target and the maximum of the next most ambitious target, the peaking target.

Energy-related CO₂ emissions:

For our current policy projections (CPP), we establish a conservative (CPP max) and optimistic (CPP min) range based on different scenarios projecting the development of China’s energy sector based on policies and developments.

For the CPP max scenario, we start with the CETO (ERI et al., 2023) BLS — developed by projecting current trends in China's energy system development and calibrated to align with the 2°C goal under the Paris Agreement.

The scenario assumes that China meets a range of policy targets including:

• 25% non-fossil share of energy mix by 2030 (Xinhua News Agency, 2021)
• 50% renewable energy capacity by 2025 (SASAC, 2021)
• 39% non-fossil share and 33% RE share (3300 TWh) in electricity generation for 2025 (NDRC and NEA, 2022)
• Reduce energy intensity of economy by 13.5% from 2021 to 2025 (Xinhua News Agency, 2021)

The CETO BLS reveals no short-term projection, only TPEDs for the year of 2025 and 2030. From a conservative perspective, we cannot rule out the possibility that China's emissions will plateau at a high level over the next 5 years. We therefore force the energy-related CO₂ emissions projection for CPP max to stay at 2023 emission level until 2025, and then decline at a rate consistent with the emissions calculated under the CETO BLS.

This scenario describes a least ambitious transition in China’s energy system. The CPP max will miss a range of short-term policy targets including:

• 20% non-fossil share of energy mix by 2025 (Xinhua News Agency, 2021)
• over 50% of incremental electricity consumption is met by renewables from 2021-2025 (NDRC, 2022)
• Reduce CO₂ intensity of economy by 18% from 2021 to 2025 (Xinhua News Agency, 2021)

For the CPP min scenario, we start with the IEA WEO 2023 STEPS —which for China we take as a basis for the current policies scenario as stated policies are highly certain to be achieved in the country— and calculate total primary energy demand (TPED) based on the Chinese methodology of applying the average efficiency of coal-fired power plants to calculate TPED from non-fossil sources (renewables and nuclear) (IEA, 2022b). We start with an efficiency of 305.5 grams coal equivalent (gce) per kWh (around 8.9 MJ/kWh for Chinese coal-fired power plants), based on NDRC (2021), which improves over time to 300 gce/kWh in 2025 and 295 gce/kWh in 2030 based on a conservative scenario from IEA (2021b). This is deemed as an optimistic end of the CPP as it is an ambitious interpretation of current policies and achieves China’s NDC targets. Given that China’s NDC targets are now subsumed under domestic policies, and that China’s current policy developments are highly likely to overachieve its targets, we employ this as a minimum bound.

In addition to the policies in the max scenario and NDC targets, the CPP min additionally integrates:

• Reduce CO₂ intensity of economy by 18% from 2021 to 2025
• Doubling wind and solar generation from 2021 to 2025 (L. Wang, 2022)
• 20% non-fossil share of energy mix by 2025
• over 50% of incremental electricity consumption is met by renewables from 2021-2025

This scenario describes a different projection of China’s energy system, now freed from the national shift from dual-energy to dual-carbon controls (no longer limiting energy demand growth in guidance to policymakers and developers). This scenario shows a growing energy demand off the back of an accelerated power sector transformation: energy demand is met by an exponential rise in renewable (wind and solar) development and integration. Renewables can both meet the rise of demand and also displace fossil fuels, namely coal consumption which drops steeply to 2030.

In both scenarios, supply-side targets such as the production capacity of fossil fuels and installed capacity targets from the 14th FYP on energy are not considered binding as these policies will likely result in excess capacity with uncertain outcomes for emissions.

After integrating the aforementioned policies into the energy sector results, we calculate energy sector emissions using IEA WEO STEPS (IEA, 2022a) emission factors for fossil fuels in both scenarios and account for developments in carbon, capture and storage (CCS) after 2030.

Industrial-process emissions:

We project industrial-process CO₂ emissions by applying growth rates from cement process emissions for the non-OECD region based on the IEA Energy Technology Perspectives 2016 report’s 6DS scenario to our latest 2022 value estimates. CO₂ emissions for industry peak have been revised to peak in 2025, five years earlier than China’s building materials peaking plan (MIIT of China, NDRC, MEE, et al., 2022). According to the China Cement Association, it is predicted that cement clinker will reach peak consumption and production during the "14th FYP" period (2021-2025), with its carbon emissions declining after peaking at approximately 1.45 billion tons (Zhang, 2021).

Other non-CO₂ emissions:

For non-CO₂ emissions from energy, fugitive emissions, agriculture, industrial processes, and waste, we apply sector-specific growth rates for non-CO₂ emissions from (Lin et al., 2019) to our latest 2022 value estimates. This source considers recent policies implemented since 2015, leading to improved certainty on Chinese non-CO₂ emissions in 2030, compared to previous assessments. The reference scenario used assumes that no non-CO₂ mitigation measures will be implemented before 2050, except for efforts made to reach the Montreal Protocol targets for HFCs from HCFC-22 production, which are phased out. We additionally quantify the impacts of the Kigali Amendment on HFCs following the staged phaseout schedule eventually leading to an 80% reduction from baseline levels by 2045.

The officially submitted LTS appears to confirm the commitment covers only carbon dioxide emissions. Due to the 2060 timeframe extending past our scope of analysis, as well as insufficient details in intermediary targets to reach the carbon neutrality target, we take a simplified linear approach for China’s pathway to carbon neutrality.

The government is pursuing expansion of China’s carbon sinks in the LULUCF sector. While specific modelling details of these sinks are not provided, the updated NDC commits to increasing forest stock volume by 6 billion cubic meters from the 2005 level (Government of China, 2022). We regress the historical LULUCF sinks and forest stock volumes to predict the LULUCF sinks up to 2030, assuming a linear increase in forest stock volume from 2018 (the latest available data) to 2030. From 2030 to 2060, we assume the LULUCF sinks will remain constant at approximately -1270 Mt CO₂e, pending new policies beyond 2030.

Emissions until 2030 are established through our current policy projections. For CO₂ (incl. LULUCF), we assume a linear decarbonisation to zero in 2060 from 2030 levels, CO₂ (excl. LULUCF) is thus calculated based on the assumed constant LULUCF sinks. For non-CO₂, we assume a more conservative phaseout path to zero in 2080 from 2030 levels. China’s resulting emissions in 2060 (excl. LULUCF) is then assumed to be the addition of CO₂ (excl. LULUCF) and leftover non-CO₂ GHGs. The pathway for all GHG emissions from 2030 to the emissions in 2060 is linearly interpolated.

As we now use baseline data that already captures impacts from COVID-19, we apply no further methods to estimate COVID-19 related changes in greenhouse gas emissions for China until 2030.

The CAT uses Global Warming Potential (GWP) values from the IPCC's Fourth Assessment Report (AR4) for all its figures and time series. Assessments completed before December 2018 (COP24) used GWP values from the Second Assessment Report (SAR).