CO2 emission estimates

The historical trends of CO2 emissions in China from 2005 to 2020 were estimated through a bottom-up approach with the MEIC model. The MEIC model(http://www.meicmodel.org) is a dynamic technology-based inventory model developed for China by Tsinghua University2,18,19,20,21,22, including the unified source categorization, emission factor database, technology-based method, and high-resolution emission processing system on the cloud computing platform. This study estimated CO2 emissions originating from fossil fuel combustion and cement production by multiplying activity data by corresponding emission factors:

$${E}_{i,j}={A}_{i,j}times {{{{{{rm{EF}}}}}}}_{i,j}$$

(1)

where Ei,j denotes the CO2 emissions of fossil fuel/industrial product i consumed or produced in sector j, Ai,j denotes the corresponding fuel consumption/industrial production provided by MEIC, and EFi,j denotes CO2 emission factors obtained from Liu et al.44. Supplementary Fig. 2 compares CO2 emission estimated by this study with various data sources.

Estimates of CO2 emission reduction from five co-beneficial measures

This work carried out an ex-post assessment of the CO2 emission reduction co-benefits of clean air measures in China from 2013 to 2020, based on the real implementation rate of each measure collected by the government afterwards. China’s top-down system used the engineering-oriented approach to set air quality targets and prescribe measures to reach the targets. The government inspected the actual progress of the measures regularly to ensure the prescribed measures were effectively implemented, and progress were summarized in statistical reports. This work collected the real implementation rate of clean air measures from provincial self-inspection reports, official news and other investigation reports. Combining the real implementation rate with the MEIC model and the Ministry of Ecology and Environment (MEP) database45, the CO2 emission reduction co-benefits were estimated.

Here we make a more detailed explanation of selected co-beneficial measures in our assessment. Five co-beneficial measures were summarized from Air Pollution Prevention and Control Action Plan46, Three-Year Action Plan for Winning the Blue Sky Defense Battle47, and regional action plans released to address the air pollution in autumn and winter (e.g., Action Plan to Comprehensive Control Autumn and Winter Air Pollution in Beijing-Tianjin-Hebei and Surrounding Regions 2017–201848 and Action Plan to Comprehensive Control Autumn and Winter Air Pollution in Beijing–Tianjin–Hebei Areas and Fenwei Plain 2020–202149). As shown in Supplementary Table 8, only measures implemented for the first time or strengthened (e.g., expanding the scope of management) since 2013 were selected (marked by green and blue shades).

The CO2 emission reduction co-benefits were estimated with Eq. (2).

$$varDelta {E}_{k}=mathop{sum}limits_{i}(varDelta {{{{{rm{A}}}}}}{1}_{i}times {{{{{{rm{EF}}}}}}}_{i})-mathop{sum}limits_{j}(varDelta {{{{{rm{A}}}}}}{2}_{j}times {{{{{{rm{EF}}}}}}}_{j})$$

(2)

where ∆Ek denotes the co-benefits of CO2 emission reduction from measure k, i denotes the reduced fossil fuel/industrial product, j denotes the increased fossil fuel, and ΔA1 and ΔA2 denote the energy/industrial production reduction and the energy increase, respectively, due to measure k. For example, if a coal-fired boiler was replaced by an NG-fired boiler, ΔA1 denotes the annual coal use of the coal-fired boiler, and ΔA2 denotes the annual NG use of the new boiler. EFi was retrieved from Liu et al.44. The measure-specific approaches for energy flow estimation are introduced below.

(a) Upgrades on industrial boilers

Small, polluting coal-fired industrial boilers were replaced by larger boilers or shifted to cleaner energy sources, leading to energy savings attributed to energy efficiency improvement (as indicated in Supplementary Table 9). The eliminated capacities of coal-fired boilers were collected from local self-inspection reports. The coal intensity was assumed as 366 tons coal per MW and 377 tons coal per MW for coal-fired industrial boilers and heating boilers, respectively, according to the estimation of the Beijing Clean Air Action Plan. Of the 424 GW of coal-fired boilers eliminated between 2013 and 2020, 192 GW was completely eliminated, 95 GW was replaced by larger boilers (central heating), and 112 GW was shifted to NG (Supplementary Table 10). The transformation from coal to electricity and biomass fuels was 5.9 GW and 18.5 GW, respectively. 63.6 Mtce coal has been saved by eliminating small coal-fired boilers in 2020.

(b) Phasing out small and polluting factories

Since implementing end-of-pipe pollution control in small and polluting factories was neither practical nor cost-effective, tremendous effort was made to eliminate polluting small factories typically comprising super-emitters. The involved sector includes lime production, brick production, and other industrial processes. These small factories were assumed to be shut down completely, and the coal intensity values of the different products were collected from relevant standards and the Ministry of Ecology and Environment (MEP) database45. Phasing out small industrial furnaces (lime and brick furnaces) played a dominant role, reducing coal use by 22 Mtce in 2020. Coal reduction through the elimination of foundries, nonferrous metal factories, and other non-key industrial processes was estimated based on the reduced production and coal intensity, contributing a reduction of 4.0 Mtce in coal use in 2020 (Supplementary Table 11).

(c) Phasing out outdated industrial capacity

Here, we mainly considered phasing out outdated industrial capacities in four key sectors: coal-fired power plants, iron and steel production (including coking), cement production, and glass production. Outdated capacities were assumed to be replaced by advanced capacities, and energy savings were estimated by the amount of eliminated outdated industrial capacities (provided by local self-inspection reports) and the difference in energy intensity between advanced and outdated technologies. Differences in the energy intensity were collected from the MEP database45. In 2020, phasing out small coal-fired power plants reduced coal use by 25.5 Mtce, while phasing out outdated capacities in the iron and steel production, cement production and glass production sectors reduced coal use by 31.1, 14.3, and 0.19 Mtce, respectively.

(d) Promoting clean fuels in the residential sector

The co-reduction benefits of scattered coal use substitution were estimated by the number of households that replaced coal with cleaner energy, as reported by local governments. According to local self-inspection reports, among 12.7 million rural families involved in scattered coal substitution from 2013 to 2020, 54% of all households switched from coal to NG, 33% switched to electricity, 6% shifted to cleaner coal use, 5% switched to heating, and 1% eliminated coal use. The coal savings originating from scattered coal substitution in rural areas reached 24.7 Mtce in 2020. Scattered coal consumption per household was estimated based on the mean daily coal consumption per household and the central heating duration announced by regional governments (Supplementary Table 12)50,51. The energy efficiencies of different energy are listed in Supplementary Table 13. Biomass fuels are carbon neutral and were therefore not included in our estimates. In addition, the total elimination of coal-fired residential boilers reached 198 GW (Supplementary Table 14), reducing coal consumption by 29.5 Mtce in 2020. This part of calculation method was similar to that of upgrades on industrial boilers.

(e) Retiring yellow-label and old vehicles

This measure corresponds to the strengthening of vehicle emission standards, as reported by Zhang1, retiring over 26.8 million yellow-label and old vehicles from 2013 to 2020. The number of eliminated yellow-label and old vehicles and other parameters were considered to estimate the resultant energy savings:

$${E}_{l}={{{{{rm{VP}}}}}}times {X}_{l}times {{{{{{rm{FE}}}}}}}_{l}times {{{{{{rm{VKT}}}}}}}_{l}$$

(3)

Where l is the vehicle types, VP is the number of eliminated yellow-label vehicles, Xl is the share of vehicle type l, FEl is the fuel economy of vehicle type l, and VKT is the average vehicle mileage of vehicle type l. X, FE, and VKT were estimated with a vehicle emission model20. As indicated in Supplementary Table 15, the energy savings achieved with this measure reached 25.2 Mtce oil in 2020.

Estimates of CO2 emission increase from strengthening industrial emission standards

Besides CO2 emission reduction due to energy-saving or energy transformation measures, this work also takes CO2 emission increase due to strengthening industrial emission standards into consideration. Previous work has demonstrated that this measure was significantly strengthened since 20131. Here, we estimated increased CO2 emission from the wider application of end-of-pipe technologies in four key sectors: coal-fired power plants, iron and steel production, cement production, and industrial boilers.

The method of estimating direct and indirect CO2 emission increase follows Zhao’s work52. Direct CO2 emissions are produced through chemical reactions, which can be estimated from air pollutants emission reduction and chemical equations. Choosing SO2 elimination as an example, direct CO2 emissions are produced through reactions between limestone or slaked lime and SO2. Indirect CO2 emissions are produced due to extra electricity consumption, which were estimated based on the increased capacities attributed to end-of-pipe technologies and the intensity of electricity consumption. Note that due to the similar electricity intensity of various particulate matter (PM) control technologies, the additional CO2 emissions stemming from upgrades to PM control technologies (for example, the shift from electrostatic precipitators (ESP) to fabric filters (FAB) were not calculated. Setting 2012 as the base year, air pollutants emission reduction and increased capacities with end-of-pipe technologies were provided by MEIC. Supplementary Table 1 lists the estimates in the key sectors.

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