Exploring the trade-offs between electric heating policy and carbon mitigation in China

China’s rapid economic and industrial growth has led to high fossil fuel consumption and rising greenhouse gas and air pollutant emissions, threatening climate and public health. Rural residential heating in Northern China has traditionally relied on low-cost raw coal, which, lacking end-of-pipe controls, emits substantial SO2, NOx, and particulate matter, degrading winter air quality. Since 2015, China has launched Electric Heating Policies (EHPs) to replace raw coal with electric heating to improve air quality, including national and provincial actions to curb high-ash/sulfur coal and reduce rural coal use. While these measures reduce local pollution, they increase electricity demand, often met by coal-fired power plants, risking higher system-wide CO2 emissions. This study quantifies the extent to which EHP may increase national carbon emissions by modeling both the power generation and rural heating sectors, identifying key drivers of regional differences, and evaluating strategies to reconcile clean heating with carbon mitigation.

Prior studies have assessed environmental impacts of China’s residential heating sector, including estimates of carbon and pollutant emissions, policy analyses for emission control, and impacts on health and life expectancy. However, few works have specifically quantified the greenhouse gas impacts of electric heating or examined potential conflicts between EHP and national carbon mitigation goals. This paper addresses that gap by explicitly modeling the CO2 implications of shifting rural heating to electricity and by comparing policy implementation and technology mixes across regions.

The study models CO2 impacts from rural heating electrification by combining bottom-up household heating simulations with a power system unit commitment model and national scaling. - Rural resident data and heating simulation: For Hebei (HB), Henan (HN), Shandong (SD), and Shanxi (SX), the authors compiled rural population, housing size distributions (eight area bins from 15–250 m², with specified shares), and weather from multiple cities per province. Heating energy was simulated using EnergyPlus, setting indoor comfort temperature per China’s Indoor Air Quality Standard (13–17 °C). Two device types were modeled: electric heaters (EHs) with 80% efficiency and air-source heat pumps (HPs) with COP 2.5–4.0. Household coal consumption was derived by converting simulated gas heat to coal using a standard heating value (2.93×10^7 J/kg). Hourly rooftop PV generation profiles (3 kW typical) for each city were taken from NREL PVWatts; average daily 1-kW output: HB 2.07 kWh, HN 2.14 kWh, SD 2.47 kWh, SX 2.28 kWh. Net electric heating load equals electric heating load minus coincident PV. - Electric power system data and dispatch: Provincial thermal generator fleets (counts, capacities, marginal thermal coal consumption rates, TCCR), wind and solar installed capacities, and hourly load data (Nov 1–Dec 31, 2015) were collected. A day-ahead rolling unit commitment (UC) model minimizes generation, startup, and shutdown costs of coal units over 24 hours, subject to power balance (including original load plus net heating load), spinning reserve, generator operating limits, and minimum up/down time constraints. Renewable output and interties are exogenous inputs; transmission/distribution networks are not modeled. Thermal coal use is obtained from the UC outputs and coal price conversion; heating season emissions were scaled by a factor of 2.5 to cover Nov–Mar. - National estimation: Per-capita rural heating coal consumption and per-capita electric heating load derived from the four provinces were used to estimate other Northern provinces’ values given rural populations and policy implementation rates (PIR). Provincial thermal coal use for incremental electric load equals electric heating (MWh) times average provincial TCCR (kg/MWh). CO2 emission factors use coal heating value and carbon content with oxidation rates: raw coal factor e_HCoal = 2.39 tCO2/t (83.7% oxidation) and thermal coal factor e_GCoal = 2.83 tCO2/t (99% oxidation). Total CO2 equals emissions from residual raw coal plus thermal coal for power. - Scenarios and uncertainties: Authors consider PIR uncertainties (45%, 50%, 55% in 2015; 70%±5% in 2020; 90%±5% in 2030) and electric heating mix (EHM) shares of EH, HP, PV-powered EH within ranges EH [80–100%], HP [0–20%], PV [0–10%]. Future rural population projections (2020, 2030) and national generation capacity/load outlooks follow SGERI. - Techno-economic analysis: Household annualized costs include capital (one-off device cost minus one-off subsidy of ¥7400, annualized at 4.85% over 10 years) and electricity bills net of heating discounts and PV subsidies. Assumptions: EH (8 kW) ¥2000, HP (8 kW) ¥28,000, PV (3 kW) ¥5000/kW; retail tariffs (¥/kWh): HB 0.36, HN 0.38, SD 0.39, SX 0.33; electric heating discount 0.12 ¥/kWh. PV subsidy cases: PV-PAP 0.42 ¥/kWh, PV-H 0.37, PV-M 0.18, PV-N 0.

- Provincial impacts (2015 heating season, PIR/EHM uncertainties): Incremental CO2 (megatons) ranges: Hebei 9.32–14.97; Henan 12.32–21.23; Shandong 20.97–32.16; Shanxi 9.21–14.57. Base case (PIR 50%, average EHM): SD 27.63; HB 12.42; HN 17.20; SX 12.15 Mt. - Uncertainty drivers: EHM uncertainty impacts exceed PIR’s: Largest deviations due to PIR vs EHM (Mt): HB 2.46 vs 3.58; HN 3.76 vs 6.22; SD 4.94 vs 6.85; SX 2.54 vs 3.22. - Key factors for provincial diversity: Ambient air temperature (AAT), rural resident population (RRP), and marginal TCCR. Colder provinces require more heat: median winter hourly AAT HN 5.45 °C vs SD −0.56 °C; corresponding single-household daily electric heating: SD 54.35 kWh vs HN 36.71 kWh. Provincial daily average electric heating load (SD) estimated 353.23 GWh (~65.61% of California’s daily average generation in 2015). Marginal TCCR and intensity: HN capacity factor 47.78%, marginal TCCR 275.9 kg/MWh, carbon intensity 397.51 kg/MWh; SX capacity factor 66.33%, marginal TCCR 368 kg/MWh, intensity 635.71 kg/MWh. - National impacts: 2015 incremental CO2 in Northern China base case 135.60 Mt; range 101.69–162.89 Mt (comparable to 31.02–49.69% of France’s 2015 annual emissions). 2020 base 168.80 Mt; range 130.03–197.87 Mt. Due to urbanization (declining rural share), 2030 EHP-induced increment drops to 119.19–177.47 Mt even with higher PIR (~90%). - Grid load increases (base, PIR 50%): Incremental electric load (TWh): HB 24.56; HN 43.27; SD 53.87; SX 19.11. - Energy chain efficiency and coal substitution: Given ~40% generation efficiency, 6–10% T&D loss, and EH efficiency ~80%, electrification with EHs is less efficient than direct coal burning; substituting 1 kg raw coal requires 1.89 kg (HB), 1.68 kg (HN), 1.90 kg (SD), 2.17 kg (SX) of thermal coal. Thermal coal’s CO2 factor (2.83 tCO2/t) exceeds raw coal’s (2.39 tCO2/t). - Low-carbon pathways: • Interprovincial renewable matching: Additional annual renewable energy to fully offset incremental emissions: HB 19.20 TWh (0.60% of 2015 consumption), HN 25.21 TWh (0.71%), SD 36.06 TWh (0.70%), SX 12.28 TWh (0.88%). Marginal CO2 reduction diminishes with higher renewable penetration due to curtailment. • Distributed PV: Adding 10-kW rooftop PV per household lowers incremental emissions by 5.09 Mt (HB), 10.35 Mt (HN), 14.71 Mt (SD), 8.89 Mt (SX); reduction per kW correlates with irradiance (e.g., SD daily average ~2.88 kW/m²) and provincial emission intensity. • Heat pumps: Replacing EHs with HPs (COP 2.5–4.0) substantially reduces emissions. HP share needed for zero incremental emissions: HB 68.33–80.26%; HN 63.56–74.69%; SD 70.67–82.86%; SX 78.28–91.82%. - Costs to households: Raw coal heating costs ¥633.69–¥1222.40 for 333.52–643.37 kg. Electric heating adds capital and electricity bills: EH annualized ¥1583.30–¥3500.05; HP ¥3377.21–¥3990.57 (current HP costs are prohibitive for many households; electricity bill savings do not offset higher CAPEX under assumed tariffs). PV-powered EH costs depend strongly on subsidies: PV-PAP ¥1792.77–¥3413.05; PV-H ¥1975.64–¥3605.11; with reduced subsidy (2019) PV-M ¥2656.17–¥4334.98; no subsidy PV-N ¥3300.87–¥5026.42. In some colder SD cities, PV-PAP can be cheaper than EH due to high heating loads and subsidies; in warmer southern HN cities, EH remains more cost-effective.

The study demonstrates a clear trade-off: while EHPs reduce local air pollution from rural coal combustion, they shift energy use to the power sector where added load is largely met by coal-fired generation, increasing CO2 emissions. Lower system efficiency along the generation–transmission–consumption chain and higher oxidation factors for thermal coal drive the CO2 increase relative to in-home raw coal use. The magnitude of incremental emissions depends on climate (heating needs), rural population adopting electric heating, and marginal coal plant performance (TCCR). Proposed mitigation pathways—coordinating electric heating with surplus interprovincial renewable generation and upgrading from EHs to HPs—can offset or even eliminate the incremental CO2, but exhibit diminishing marginal returns due to renewable curtailment and require high HP penetration (roughly 60–90% by province). Economic analysis indicates that, despite subsidies, electric heating remains more expensive than raw coal for many rural households, especially for HPs, suggesting current incentives are insufficient to enable widespread adoption of low-carbon technologies. Policy implications include evaluating cross-policy interactions (clean heating vs. carbon targets), ensuring sufficient flexible resources and capacity for winter peaks, aligning EHP rollouts with renewable integration strategies, and enhancing incentives to accelerate HP adoption. The findings quantify the potential incompatibility between rapid electric heating expansion and near-term carbon mitigation goals under current grid and cost conditions, and chart practical pathways to reconcile them.

This paper quantifies the CO2 implications of China’s Electric Heating Policy by integrating household heating simulations with a unit commitment model for coal-fired generation, then scaling to Northern China. It finds substantial incremental CO2 emissions from electrifying rural heating under current conditions (roughly 100–200 Mt/year range depending on year and adoption), driven by climate, rural demographics, and marginal coal plant efficiency. Two practical pathways can offset these increases: (1) balancing electric heating loads with interprovincial renewable generation (and distributed PV where feasible), and (2) increasing the share of high-efficiency heat pumps. Techno-economic results highlight that present HP costs and reduced PV subsidies limit uptake without stronger financial support. Future research should incorporate transmission and distribution network constraints to better represent renewable curtailment and carbon outcomes, refine provincial adoption and technology mix scenarios, and evaluate system flexibility enhancements (storage, demand response) that can synergize clean heating and decarbonization.

- Power transmission and distribution networks were not modeled, potentially underestimating renewable curtailment and associated CO2; authors characterize estimates as conservative. - Provincial load data covered only two months (Nov–Dec 2015) and were scaled (×2.5) to approximate the full heating season. - National estimates assumed per-capita heating coal consumption and per-capita electric heating load in the four studied provinces represent other Northern provinces. - Equipment performance parameters (e.g., HP COP 2.5–4.0, EH efficiency 80%) and coal emission factors rely on literature values; actual field performance and fuel quality may vary. - Economic analysis depends on assumed device costs, tariffs, and subsidies, which can change over time and vary regionally.