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Cited by 411Electric Vehicles and InfrastructureIntegrated Energy Systems OptimizationEnergy, Environment, and Transportation Policies

Net emission reductions from electric cars and heat pumps in 59 world regions over time

Open access
Knobloch, Florian, Hanssen, Steef V., Lam, Aileen, Pollitt, Hector, Salas, Pablo, Chewpreecha, Unnada, Huijbregts, Mark A. J., Mercure, Jean-Francois·2020·Nature Sustainability
DOI 10.1038/s41893-020-0488-7PMC PMC7308170
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Abstract

Electrification of passenger road transport and household heating features prominently in current and planned policy frameworks to achieve greenhouse gas emissions reduction targets. However, since electricity generation involves using fossil fuels, it is not established where and when the replacement of fossil fuel-based technologies by electric cars and heat pumps can effectively reduce overall emissions. Could electrification policy backfire by promoting their diffusion before electricity is decarbonised? Here, we analyse current and future emissions trade-offs in 59 world regions with heterogeneous households, by combining forward-looking integrated assessment model simulations with bottom-up life-cycle assessment. We show that already under current carbon intensities of electricity generation, electric cars and heat pumps are less emission-intensive than fossil fuel-based alternatives in 53 world regions, representing 95% of global transport and heating demand. Even if future end-use electrification is not matched by rapid power sector decarbonisation, it likely avoids emissions in almost all world regions.

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Crossref · 10.1038/s41893-020-0488-7

Cites

56 of 56 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

14 of 63 cited sources checked · 1 supported · 0 flagged · accuracy not yet measured

  • Premisecitation

    Only two studies extend EV life-cycle analysis into the future.

    “For the case of EVs, only two studies extend the analysis into the future9,26.”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [9] Cox, B., Mutel, C. L., Bauer, C., Mendoza Beltran, A. & van Vuuren, D. P. Uncertain environmental footprint of current and future battery electric vehicles. Environ. Sci. Technol. 52, 4989–4995 (2018). source
    • cites [26] Mercure, J.-F. et al. Environmental impact assessment for climate change policy with the simulation-based integrated assessment model E3ME-FTT-GENIE. Energy Strategy Rev. 20, 195–208 (2018). source

      Section 4.2 models future electric-vehicle diffusion and associated changes in fuel use and emissions, so the paper does extend EV-related analysis into the future. Our copy does not establish that this is an EV life-cycle analysis or that only two studies do so. (LLM, conf=0.84)

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  • Premisecitation

    Markets are highly diverse due to varying preferences, incomes, household characteristics, and attraction to energy-intense luxury items.

    “Markets are highly diverse, due to varying preferences, incomes, household characteristics, and attraction to energy-intense luxury items29.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [29] Mercure, J.-F., Lam, A., Billington, S. & Pollitt, H. Integrated assessment modelling as a positive science: private passenger road transport policies to meet a climate target well below 2 °C. Climatic Change 151, 109–129 (2018). source

      The ‘A bounded-rational discrete choice model with heterogenous agents’ section says vehicle consumers are highly heterogeneous and links their differing tastes to income and other socioeconomic factors. The transport-database section distinguishes large-engine ‘Lux’ vehicles, but the paper does not specifically identify household characteristics or attraction to energy-intensive luxury items as causes of market diversity. No page numbers are available in our copy. (LLM, conf=0.85)

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  • Premisecitation

    Real-world fuel use and resulting use-phase CO2 emissions of petrol cars exceed official manufacturer ratings by an average margin of 10-40%, based on empirical studies in Europe, the USA and China.

    “Real-world fuel use and resulting use-phase CO2 emissions of petrol cars are widely recognized to exceed official manufacturer ratings, by an average margin of 10-40% (based on empirical studies in Europe, the USA and China)53–57.”
    Quote in the paperSubstantial claim1 of 5 sources checked
    • cites [53] Duarte, G. O., Gonçalves, G. A. & Farias, T. L. Analysis of fuel consumption and pollutant emissions of regulated and alternative driving cycles based on real-world measurements. Transp. Res. D 44, 43–54 (2016). source
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      The Introduction and Summary discussion and conclusions (pages unavailable) report that real-world fuel consumption and CO2 emissions exceed certification values for European passenger cars, with reported gaps ranging from about 10% in earlier studies to 30–40% in 2014–2015. The paper does not establish that 10–40% is an average margin specifically for petrol cars across Europe, the USA and China; section 2.3 says no extensive US studies of the real-world-versus-laboratory divergence exist. (LLM, conf=0.88)

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    • cites [56] Light-Duty Automotive Technology, Carbon Dioxide Emissions, and Fuel Economy Trends—1975 Through 2014 (US Environmental Protection Agency, 2018); https://go.nature.com/2HXxrja

      Not checked in the free run.

    • cites [57] Solid and Gaseous Bioenergy Pathways: Input Values and GHG Emissions (Joint Research Centre of the European Commission, 2014); https://go.nature.com/397sRLk

      Not checked in the free run.

  • Premisecitation

    For cars, the distribution of current sales was derived from detailed market data on vehicle sales (2004-2012), compiled by matching sales data to manufacturer data for thousands of individual vehicle models in 18 countries, and extrapolated for countries where data is missing.

    “For cars, the distribution of current sales was derived from detailed market data on vehicle sales (years 2004-2012), which we compiled by matching sales data to manufacturer data for thousands of individual vehicle models currently on the market in 18 countries, and we extrapolated these values for countries where data is missing29,30.”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [29] Mercure, J.-F., Lam, A., Billington, S. & Pollitt, H. Integrated assessment modelling as a positive science: private passenger road transport policies to meet a climate target well below 2 °C. Climatic Change 151, 109–129 (2018). source

      The FTT: transport database section (page unavailable) says 2012 registrations were matched model by model to vehicle prices, with data from 18 representative regions used as proxies elsewhere. It also says historical vehicle-category shares cover 2004–2012. It does not establish that sales data for that entire period were matched to manufacturer data for thousands of individual models. (LLM, conf=0.85)

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    • cites [30] Knobloch, F., Pollitt, H., Chewpreecha, U., Daioglou, V. & Mercure, J.-F. Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5 °C. Energy Effic. 12, 521–550 (2019). source

      The Energy demand section (page not provided) describes data on residential heating, not car sales. Searches for vehicle-model sales, manufacturer data, the 2004–2012 period, and 18-country coverage found no passage addressing the attributed method. (LLM, conf=0.78)

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  • Findingown data

    In almost all regions, temporary increases are outweighed by emission reductions in subsequent years.

    “In almost all regions, such temporary increases are outweighed by emission reductions in subsequent years.”
    Quote in the paperSubstantial claim
  • May combine two claims. 35
  • Classified as probably not a substantial claim. 13

  • May combine two claims.

    Premisereasoning

    Those two future EV studies do not consider regional differences, heterogeneous technology choices by consumers, or the electrification of heating, and thus cannot adequately inform national policy-making.

    “However, they do not consider regional differences around the globe, heterogeneous technology choices by consumers or the electrification of heating, and thus cannot adequately and comprehensively inform policy-making processes at the national level.”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [9] Cox, B., Mutel, C. L., Bauer, C., Mendoza Beltran, A. & van Vuuren, D. P. Uncertain environmental footprint of current and future battery electric vehicles. Environ. Sci. Technol. 52, 4989–4995 (2018). source
    • cites [26] Mercure, J.-F. et al. Environmental impact assessment for climate change policy with the simulation-based integrated assessment model E3ME-FTT-GENIE. Energy Strategy Rev. 20, 195–208 (2018). source

      Section 4.4 compares E3ME-FTT-GENIE with other models, and section 4.8 describes its usefulness for policy-making. Neither identifies the two EV studies or says that they omit regional differences, heterogeneous consumer choices, or heating electrification, or that they cannot adequately inform national policy. I searched for those omissions and the claimed policy-making limitation. (LLM, conf=0.72)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    Multi-sectoral mitigation scenarios have identified electrification as a robust policy strategy, but typically focus on a context of rapid power sector decarbonisation.

    “Multi-sectoral mitigation scenarios (such as those reviewed by the IPCC) have identified electrification as a robust policy strategy, but typically focus on a context of rapid power sector decarbonisation3,13.”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [3] Clarke, L. E. et al. in Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) 413–510 (IPCC, Cambridge Univ. Press, 2014); https://doi.org/10.1017/CBO9781107415416.012 source
    • cites [13] Mercure, J.-F., Pollitt, H., Bassi, A. M., Viñuales, J. E. & Edwards, N. R. Modelling complex systems of heterogeneous agents to better design sustainability transitions policy. Glob. Environ. Change 37, 102–115 (2016). source

      Section 3.3 describes a scenario with 90% electricity-sector decarbonisation and says mitigation must also involve end-use sectors, notably transport. It does not identify electrification as a robust policy strategy or establish that multi-sectoral scenarios typically assume rapid power-sector decarbonisation. The indexed passage provides no page number. (LLM, conf=0.78)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    Existing life-cycle studies of EVs and HPs are limited to the present situation and mostly focus on a few regions or global averages.

    “This is different to existing life-cycle studies of EVs and HPs, which are limited to the present situation, and mostly focus on a few regions or global averages (see refs.15–23 for studies on EVs, and refs.10,24,25 on HPs).”
    Quote in the paperSubstantial claim1 of 10 sources checked
    • cites [15] Miotti, M., Supran, G. J., Kim, E. J. & Trancik, J. E. Personal vehicles evaluated against climate change mitigation targets. Environ. Sci. Technol. 50, 10795–10804 (2016). source
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    • cites [18] Jochem, P., Babrowski, S. & Fichtner, W. Assessing CO2 emissions of electric vehicles in Germany in 2030. Transp. Res. A 78, 68–83 (2015). source

      The Introduction (page unavailable) says earlier EV analyses usually examine electricity generation at a highly aggregated level, supporting the claim about limited geographic detail. It does not establish that existing EV life-cycle studies are limited to the present; this paper itself assesses EV emissions in Germany in 2030. The sentence assigns heat-pump studies to other references, not this source. (LLM, conf=0.78)

      Experimental — accuracy not yet measured
    • cites [19] Wu, Y. et al. Energy consumption and CO2 emission impacts of vehicle electrification in three developed regions of China. Energy Policy 48, 537–550 (2012). source
    • cites [20] Archsmith, J., Kendall, A. & Rapson, D. From cradle to junkyard: assessing the life cycle greenhouse gas benefits of electric vehicles. Res. Transp. Econ. 52, 72–90 (2015). source
    • cites [21] Hawkins, T. R., Gausen, O. M. & Strømman, A. H. Environmental impacts of hybrid and electric vehicles—a review. Int. J. Life Cycle Assess. 17, 997–1014 (2012). source
    • cites [22] Woo, J., Choi, H. & Ahn, J. Well-to-wheel analysis of greenhouse gas emissions for electric vehicles based on electricity generation mix: a global perspective. Transp. Res. D 51, 340–350 (2017). source
    • cites [23] Saner, D. et al. Is it only CO2 that matters? A life cycle perspective on shallow geothermal systems. Renew. Sustain. Energy Rev. 14, 1798–1813 (2010). source
    • cites [10] Mattinen, M. K., Nissinen, A., Hyysalo, S. & Juntunen, J. K. Energy use and greenhouse gas emissions of air-source heat pump and innovative ground-source air heat pump in a cold climate. J. Ind. Ecol. 19, 61–70 (2014). source

  • May combine two claims.

    Findingcitation

    In the current trajectory, EVs are projected to account for 19% of global passenger road transport in 2050 (1% in 2030), and HPs for 16% of global residential heat demand (7% in 2030), with considerable variation between regions.

    “EVs are projected in the current trajectory to account for 19% of global passenger road transport in 2050 (1% in 2030), and HPs for 16% of global residential heat demand (7% in 2030)28, also with considerable variation between regions (Supplementary Tables 3 and 4).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [28] Mercure, J.-F. & Lam, A. The effectiveness of policy on consumer choices for private road passenger transport emissions reductions in six major economies. Environ. Res. Lett. 10, 064008 (2015). source

      The Introduction discusses transport emissions and replacing combustion engines with hybrid and electric systems, while Data and results describes vehicle sales in six economies. Searches for the stated 2030 and 2050 EV shares and for heat-pump shares found no passage reporting these global projections; our copy therefore does not verify the figures or regional variation. (LLM, conf=0.76)

      Experimental — accuracy not yet measured

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Assumed conversion efficiencies for fossil-fuel heating systems were 75% for oil and gas, 86% for advanced oil systems, and 90% for advanced gas systems.

    “We assumed conversion efficiencies of 75% for oil and gas heating systems, 86% for advanced oil systems, and 90% for advanced gas systems63.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [63] Hauck, M., Steinmann, Z. J. N., Laurenzi, I. J., Karuppiah, R. & Huijbregts, M. A. J. How to quantify uncertainty and variability in life cycle assessment: the case of greenhouse gas emissions of gas power generation in the US. Environ. Res. Lett. 9, 074005 (2014). source

      The System description (p. 3) concerns natural-gas power plants generating electricity, not oil or gas heating systems. The Reduction potential section (p. 7) discusses power-plant efficiencies but gives none of the claimed 75%, 86%, or 90% heating-system assumptions; searches for those values and systems found no matching passage. (LLM, conf=0.76)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Study design and conductcitation

    The E3ME-FTT-GENIE model's representation of technology uptake in transport and heating is strongly empirical, based on detailed regional datasets on consumer markets, and simulates technology diffusion profiles consistent with historical observations.

    “This model’s representation of technology uptake in transport and heating is strongly empirical, based on detailed regional datasets on consumer markets, and simulates technology diffusion profiles consistent with historical observations (see Methods)29–31.”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites [29] Mercure, J.-F., Lam, A., Billington, S. & Pollitt, H. Integrated assessment modelling as a positive science: private passenger road transport policies to meet a climate target well below 2 °C. Climatic Change 151, 109–129 (2018). source

      Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

      Experimental — accuracy not yet measured
    • cites [30] Knobloch, F., Pollitt, H., Chewpreecha, U., Daioglou, V. & Mercure, J.-F. Simulating the deep decarbonisation of residential heating for limiting global warming to 1.5 °C. Energy Effic. 12, 521–550 (2019). source

      Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

      Experimental — accuracy not yet measured
    • cites [31] Holden, P. B. et al. Climate–carbon cycle uncertainties and the Paris Agreement. Nat. Clim. Change 8, 609–613 (2018). source

  • Classified as probably not a substantial claim.

    Premisecitation

    For heating systems, current and future sales were simulated by E3ME-FTT (from 2015-2050), according to available data on fuel use and technology stocks (1990-2014).

    “For heating systems, current and future sales were simulated by E3ME-FTT (from 2015-2050), according to available data on fuel use and technology stocks (years 1990-2014)31,66.”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [31] Holden, P. B. et al. Climate–carbon cycle uncertainties and the Paris Agreement. Nat. Clim. Change 8, 609–613 (2018). source
    • cites [66] Mercure, J.-F. Fashion, fads and the popularity of choices: micro-foundations for diffusion consumer theory. Struct. Change Econ. Dyn. 46, 194–207 (2018). source

      Section 3.4 (p. 10) discusses a general technology-diffusion model, and the References (p. 22) list a separate E3ME-FTT-GENIE paper. Our copy does not describe simulations of heating-system sales, a 2015–2050 projection, or the use of 1990–2014 fuel-use and technology-stock data; searches for those terms found no supporting passage. (LLM, conf=0.75)

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  • May combine two claims.

    Premisecitation

    FTT models are characterised by strong path-dependence of projected technology diffusion, equivalent to strong autocorrelation in time, as typically found in technology transitions, and for that reason provide a good representation of the inertia embedded in technological systems.

    “FTT models are characterised by strong path-dependence of projected technology diffusion (equivalent to strong autocorrelation in time), as it is typically found in technology transitions68,69, and for that reason, provides a good representation of the inertia embedded in technological systems.”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [68] Wilson, C. Up-scaling, formative phases, and learning in the historical diffusion of energy technologies. Energy Policy 50, 81–94 (2012). source
    • cites [69] Mercure, J.-F. FTT:Power: a global model of the power sector with induced technological change and natural resource depletion. Energy Policy 48, 799–811 (2012). source

  • May combine two claims.

    Findingown data

    In 2015, current electric cars and heat pumps have lower life-cycle emission intensities than new petrol cars and fossil boilers in 53 of 59 world regions, covering 95% of global road transport demand and 96% of global heat demand.

    “We show that already under current carbon intensities of electricity generation, electric cars and heat pumps are less emission-intensive than fossil fuel-based alternatives in 53 world regions, representing 95% of global transport and heating demand.”
    • Also stated in: § Current emission intensities in transport and heating · plain
      “Accordingly, we find that current models of EVs and HPs have lower life-cycle emission intensities than current new petrol cars and fossil boilers in 53 of 59 world regions, accounting for 95% of global road transport demand and 96% of global heat demand in 2015 (Supplementary Figure 1).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    Under the current technological trajectory, mean emission intensities of EVs are projected to be around 20% lower in 2030 and 30% lower in 2050 relative to 2015.

    “Due to a combination of both effects, mean emission intensities of EVs are projected to be around 20% lower in 2030 (relative to 2015), and 30% lower in 2050 (weighted by transport demand in 2015).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    On global average in 2015, EVs result in 31% lower emissions per vehicle-kilometre compared to petrol cars, and HPs are on average 35% lower than fossil boilers.

    “On global average in 2015, EVs result in 31% lower emissions per vehicle-kilometre compared to petrol cars (each region weighted by its transport demand), and the emission intensity of HPs is on average 35% lower than that of fossil boilers (regions weighted by their heat demand) (Supplementary Table 6).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    In 2015, this happens in regions accounting for 43% of global demand in road transport (23 regions) and 80% in household heating (28 regions).

    “In 2015, this happens in regions accounting for 43% of global demand in road transport (23 regions), and 80% in household heating (28 regions).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Current and future life-cycle emissions from electric vehicles and heat pumps are on average lower than those from new petrol cars and fossil boilers, both globally and in most individual countries.

    “Overall, we find that current and future life-cycle emissions from EVs and HPs are on average lower than those of new petrol cars and fossil boilers - not just on the global aggregate, but also in most individual countries.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Averaged over all regions, new petrol cars in 2050 will emit 20% less emissions per vehicle-kilometre than in 2015, and new fossil boilers will be 15% less emissions intensive.

    “Averaged over all regions, new petrol cars in 2050 will emit 20% less emissions per vehicle-kilometre than in 2015, and new fossil boiler will be 15% less emissions intensive (weighted by service demand in 2015), with large variations between regions.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Efficient new petrol cars can cause less emissions than average EVs, and efficient new gas boilers can outperform average HPs.

    “Efficient new petrol cars can cause less emissions than average EVs, and efficient new gas boilers can outperform average HPs (indicated in yellow in Fig. 3-5).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    As EVs and HPs replace fossil-based technologies over time, production emissions are projected to grow from around 25% of total road transport emissions in 2015 to 35-38% in 2050, and from 1% of total heating emissions in 2015 to 2-9% in 2050.

    “As EVs and HPs replace fossil-based technologies over time, production emissions are projected to grow from around 25% of total road transport emissions in 2015 to 35-38% in 2050, and from 1% of total heating emissions in 2015 to 2-9% in 2050 (Supplementary Figure 4).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    By 2045 and 2035, respectively, EVs and HPs in the current trajectory are on average less emission intensive than fossil alternatives in all world regions.

    “By 2045 and 2035, respectively, EVs and HPs in the current trajectory are on average less emission intensive than fossil alternatives in all world regions (Supplementary Figure 1).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    Production emissions are currently around 30% higher for EVs than for petrol cars (at the average global electricity mix), and fifteen times higher for HPs than for fossil boilers (mainly from refrigerant liquid leakage).

    “This is due to (i) reduced use-phase emissions from electricity and (ii) increased production emissions, which are currently around 30% higher for EVs than for petrol cars (at the average global electricity mix), and fifteen times higher for HPs than for fossil boilers (mainly from the leakage of refrigerant liquid).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    Mean intensities of HPs are projected to decrease 30% below their 2015 value by 2030 and 40% by 2050.

    “Mean intensities of HPs are projected to decrease 30% below their 2015 value by 2030, and 40% by 2050 (weighted by heat demand in 2015).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    The 1100 and 1000 gCO2eq/kWh thresholds roughly correspond to the emission intensity of older coal power plants and are higher than the estimated life-cycle emission intensity of more than 90% of global electricity generation in 2015.

    “This roughly corresponds to the emission intensity of older coal power plants34, and is higher than the estimated life-cycle emission intensity of more than 90% of global electricity generation in 2015 (Supplementary Table 2).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [34] Ciez, R. E. & Whitacre, J. F. Examining different recycling processes for lithium-ion batteries. Nat. Sustain. 2, 148–156 (2019). source

  • May combine two claims.

    Findingreasoning

    As of 2015, this applies to 5% of global road transport demand (5 regions) and 4% of global heating demand (6 regions).

    “As of 2015, this applies to 5% of global road transport demand (5 regions) and 4% of global heating demand (6 regions) (Fig. 5).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingnone given

    In the 2°C scenario, the market share of EVs increases to 50% by 2050 (1% in 2030) and of HPs to 35% by 2050 (12% in 2030).

    “The policies will take some time to change the technology mix in transport and heating, but they eventually increase the market share of EVs to 50% by 2050 (1% in 2030), and of HPs to 35% by 2050 (12% in 2030).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Both EVs and HPs reduce global emissions in all scenarios and at all times: EVs by up to -1.5 GtCO2/y (-29% of total passenger road transport emissions without use of EVs), and HPs by up to -0.8 GtCO2/y (-46% of total residential heating emissions without use of HPs).

    “We find that both EVs and HPs reduce global emissions in all scenarios and at all times (Fig. 6): EVs by up to -1.5 GtCO2/y (-29% of total passenger road transport emissions without use of EVs), and HPs by up to -0.8 GtCO2/y (-46% of total residential heating emissions without use of HPs).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    These thresholds roughly correspond to the emission intensity of gas power plants and are lower than the average emission intensity of global electricity generation in 2015 (around 740 gCO2eq/kWh).

    “These thresholds roughly correspond to the emission intensity of gas power plants34, and are lower than the average emission intensity of global electricity generation in 2015 (around 740 gCO2eq/kWh, Supplementary Table 2).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [34] Ciez, R. E. & Whitacre, J. F. Examining different recycling processes for lithium-ion batteries. Nat. Sustain. 2, 148–156 (2019). source

  • Classified as probably not a substantial claim. May combine two claims.

    Findingnone given

    In the 2°C scenario, the power sector's carbon intensity decreases 44% by 2030 and 74% by 2050 relative to 2015.

    “In the ‘2°C scenario’, the power sector’s carbon intensity decreases 44% by 2030, and 74% by 2050 (relative to 2015).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    This most favourable case applies in regions accounting for 52% of global demand for passenger road transport (31 regions) and 16% of global demand for household heating (25 regions).

    “This is the case in regions accounting for 52% of global demand for passenger road transport (31 regions), and in regions with 16% of global demand for household heating (25 regions).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Passenger road transport and household heating together generate 24% of global fuel-combustion emissions and are the two major sources of direct carbon emissions by households.

    “Combined, they generate 24% of global fuel-combustion emissions and are the two major sources of direct carbon emissions by households1–5.”
    Quote in the paperSubstantial claim0 of 5 sources checked
    • cites [1] de Coninck, H. et al. in Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) 313–443 (IPCC, WMO, 2018).

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [2] International Energy Agency Global EV Outlook 2017 (IEA/OECD, 2017).

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [3] Clarke, L. E. et al. in Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) 413–510 (IPCC, Cambridge Univ. Press, 2014); https://doi.org/10.1017/CBO9781107415416.012 source
    • cites [4] Kennedy, C. Key threshold for electricity emissions. Nat. Clim. Change 5, 179–181 (2015). source
    • cites [5] Rogelj, J. et al. in Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) 93–174 (IPCC, WMO, 2018).

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    Emission intensities in the power sector widely differ across the globe and will change over time.

    “Emission intensities in the power sector widely differ across the globe and will change over time3.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [3] Clarke, L. E. et al. in Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O. et al.) 413–510 (IPCC, Cambridge Univ. Press, 2014); https://doi.org/10.1017/CBO9781107415416.012 source

  • Probably not a substantial claim: may not pass S4 (based).

    Study design and conductreasoning

    Cumulative net changes can be approximated based on the region-specific means of distributed intensities.

    “Cumulative net changes can then be approximated based on the region-specific means of distributed intensities.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Meeting policy objectives in E3ME is not achieved by maximising or minimising a target function; instead, the model is run iteratively until the target would be met with a chosen set of policies.

    “Meeting policy objectives (such as emissions targets) is not achieved by means of maximising or minimising some target function (such as welfare or costs). Instead, the model is run iteratively until the target would be met with a chosen set of policies.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationnone given

    Although the combination of policies in the 'end-use without power policies' scenario is unlikely in the real world, the scenario serves as a worst case analysis.

    “Although such a combination of policies is unlikely in the real world, the scenario serves as a worst case analysis.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Electric vehicle electricity use per vehicle-kilometre in 2015 had a median of 0.19 kWh/v-km (5th-95th percentile 0.13-0.24), and in 2040 a median of 0.15 kWh/v-km (5th-95th percentile 0.10-0.19) under the 'most likely automation' scenario, including auxiliary power demand and charging losses.

    “Ranges of current and future electricity use per vehicle-kilometre were based on estimates by Cox et al.51 for 2015 (median: 0.19 kWh/v-km; 5th-95th percentile range: 0.13-0.24 kWh/v-km) and 2040 (median: 0.15 kWh/v-km; 5th-95th percentile range: 0.10-0.19 kWh/v-km, based on the ‘most likely automation’ scenario), including auxiliary power demand and charging losses.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites Cox et al.51

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    For fossil-fuel heating production, electricity requirements are 37 kWh per kW of installed capacity (0.001 kWh/kWhth), and emissions of other sources are 30 kg CO2eq per kW (0.8 gCO2eq/kWhth).

    “Electricity requirements (including background processes) are 37 kWh per kW of installed capacity (0.001 kWh/kWhth, based on the same lifetimes and operating hours as for HPs), and emissions of other sources are 30 kg CO2eq per kW (0.8 gCO2eq/kWhth)52.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [52] Zhang, S. et al. Real-world fuel consumption and CO2 emissions by driving conditions for light-duty passenger vehicles in China. Energy 69, 247–257 (2014). source

  • May combine two claims.

    Premisecitation

    For battery production, non-electricity emissions were estimated at 3,200 kgCO2eq (21.3 gCO2eq/v-km), and battery cell electricity requirements at 5,000 kWh (0.034 kWh/v-km).

    “For the battery production, non-electricity emissions were estimated at 3,200 kgCO2eq (21.3 gCO2eq/v-km), and battery cell electricity requirements at 5,000 kWh (0.034 kWh/v-km)51.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [51] Wernet, G. et al. The ecoinvent database version 3 (part I): overview and methodology. Int. J. Life Cycle Assess. 21, 1218–1230 (2016). source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    FTT models are well suited to analyse existing technological trajectories as observed in recent historical data.

    “It is thus well suited to analyse existing technological trajectories as observed in recent historical data.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    For producing a medium-sized petrol car (1,600 kg), electricity requirements were estimated at 9,200 kWh (0.061 kWh/v-km), and emissions from other sources at 5,900 kgCO2eq (40 gCO2eq/v-km).

    “Electricity requirements for producing a medium-sized car (curb weight 1,600 kg) were estimated at 9,200 kWh (0.061 kWh/v-km), and emissions from other sources at 5,900 kgCO2eq (40 gCO2eq./v-km)52.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [52] Zhang, S. et al. Real-world fuel consumption and CO2 emissions by driving conditions for light-duty passenger vehicles in China. Energy 69, 247–257 (2014). source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    All policies included in the scenarios are designed to match as closely as possible real-world policy instruments.

    “All policies included in the scenarios are designed to match as closely as possible real-world policy instruments, for example energy taxes, vehicle taxes, feed-in tariffs, subsidies, direct regulation or efficiency standards.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    Future heat pump efficiencies were estimated to improve by 30-50% until 2030 and 40-60% until 2050, according to the same literature source.

    “The same literature source estimated that future efficiencies of HPs will improve by 30-50% until 2030, and 40-60% until 2050.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [33] Schlömer, S. et al. in Climate Change 2014: Mitigation of Climate Change (eds. Edenhofer, O. et al.) 1329–1356 (IPCC, Cambridge Univ. Press, 2014).

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    For heat pump production and end-of-life, non-electricity emissions were estimated at 830 kg CO2eq per kW of installed capacity, of which 750 kg CO2eq stem from refrigerant leakage over the entire life-cycle.

    “For the production and end-of-life stage of HPs, we estimated emissions from non-electricity sources at 830 kg CO2eq per kW of installed capacity52. 750 kg CO2eq of these emissions stem from the leakage of refrigerant liquids over the entire life-cycle, all included here in the production emissions.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [52] Zhang, S. et al. Real-world fuel consumption and CO2 emissions by driving conditions for light-duty passenger vehicles in China. Energy 69, 247–257 (2014). source

  • Classified as probably not a substantial claim.

    Interpretationnone given

    For region-wide effects, what matters is the sum over all individual choices of cars and heating systems within one region in any given year.

    “While many combinations are possible, what matters for region-wide effects is the sum over all individual choices of cars and heating systems within one region in any given year.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    The three scenarios were chosen to simulate the emission trade-offs from electrification as realistically as possible, given likely current trajectory, hypothetical ambitious climate policies, and a worst-case scenario without power sector decarbonisation.

    “These scenarios were chosen so that they allowed to simulate the emission trade-offs from electrification as realistically as possible, given (i) what is likely from a current perspective, (ii) what would be likely in a (hypothetical) case of ambitious climate policies around the globe, and (iii) a worst-case scenario in which end-use electrification is not matched by power sector decarbonisation.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductreasoning

    A sensitivity analysis for a range of life-cycle parameters was included because electricity requirements and embodied emissions of production processes can be subject to uncertainty.

    “As electricity requirements and embodied emissions of the production processes can be subject to uncertainty, we included a sensitivity analysis for a range of life-cycle parameters (Supplementary Figures 5 and 6).”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Premiseown data

    FTT models project the uptake of energy technologies in the future until 2050, by extending the current trajectory of technological change with a diffusion algorithm calibrated on datasets of technology uptake in recent history (up to 2012 for power and transport, 2014 for heating).

    “The FTT (Future Technology Transformation) family of models project the uptake of energy technologies in the future until 2050, by extending the current trajectory of technological change with a diffusion algorithm, which is calibrated on datasets of technology uptake in recent history (up to 2012 for power and transport, 2014 for heating) (Supplementary Tables 4 and 5).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    The model is a discrete choice model in which choice options are weighted by their own popularity, a method that generates endogenous S-shaped technology diffusion curves.

    “The model is a discrete choice model in which choice options are weighted by their own popularity, a method that generates endogenous S-shaped technology diffusion curves67.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [67] Rogers, E. M. Diffusion of Innovations (Simon and Schuster, 2010).

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The E3ME model is regularly used in policy analyses and impact assessments for the European Commission and elsewhere.

    “The model is regularly used in policy analyses and impact assessments for the European Commission and elsewhere73,74.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [73] Mercure, J.-F. et al. in Study on the Macroeconomics of Energy and Climate Policies (European Commission, DG Energy, 2016).

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites [74] E3ME Manual, Version 6 (Cambridge Econometrics, 2014); https://go.nature.com/2T1FIsO

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

45 of 45

  • The paper relies on this without support.

    The spatial resolution of 59 world regions is considerably higher than any previous forward-looking life-cycle study of electric vehicles or heat pumps.

    “Our analysis disaggregates global demand into 59 world regions, a spatial resolution which is considerably higher than in any previous forward-looking life-cycle study of EVs or HPs.”

  • The authors state this as an assumption.

    The structure of all sales remains distributed over time; people would not suddenly all buy economic small engine cars.

    “While the mean efficiencies in each region can change over time, we assumed that the structure of all sales remains distributed, i.e. that people would not suddenly all buy economic small engine cars.”

  • The authors state this as an assumption.

    The average insulation efficiency of buildings gradually increases over time.

    “For the heating sector, we furthermore assumed that the average insulation efficiency of buildings gradually increases over time (see Supplementary Methods 3).”

  • The authors state this as an assumption.

    Agents make comparisons between technology options that they individually see as available in their respective national markets, structured by pair-wise comparisons of distributed preferences.

    “We assume that agents make comparisons between technology options that they individually see as available in their respective national markets, which we structure by pair-wise comparisons of distributed preferences.”
4 of 4

Cites

Flagged first, then by citations

Research works printed but not linked: 12

  1. Energy Agenda—Towards a Low-Carbon Energy Supply (Ministry of Economic Affairs of the Netherlands, 2017); https://go.nature.com/385jsT9
  2. Proposal for a Directive of the European Parliament and of the Council on the Promotion of the Use of Energy from Renewable Sources—Analysis of the Final Compromise Text with a View to Agreement (Council of the European Union, 2018); https://go.nature.com/37XxTbO
  3. McGee, P. Electric cars’ green image blackens beneath the bonnet. Financial Times (8 November 2017); https://go.nature.com/3cf8YUf
  4. Sinn, H.-W. Are electric vehicles really so climate friendly? The Guardian (25 November 2019); https://go.nature.com/396bqup
  5. Cox, B., Mutel, C. L., Bauer, C., Mendoza Beltran, A. & van Vuuren, D. P. Uncertain environmental footprint of current and future battery electric vehicles. Environ. Sci. Technol. 52, 4989–4995 (2018). · DOI · Paper page
  6. Light-Duty Automotive Technology, Carbon Dioxide Emissions, and Fuel Economy Trends—1975 Through 2014 (US Environmental Protection Agency, 2018); https://go.nature.com/2HXxrja
  7. Solid and Gaseous Bioenergy Pathways: Input Values and GHG Emissions (Joint Research Centre of the European Commission, 2014); https://go.nature.com/397sRLk
  8. Well-to-Wheels Analysis of Future Automotive Fuels and Powertrains in the European Context (Joint Research Centre of the European Commission, 2014); https://go.nature.com/394f2xd
  9. Upstream Emissions of Fossil Fuel Feedstocks for Transport Fuels Consumed in the European Union (International Council on Clean Transportation (ICCT), 2014); https://go.nature.com/3cd7Lgp
  10. Knobloch, F., Mercure, J.-F., Pollitt, H., Chewpreecha, U. & Lewney, R. in Technical Study on the Macroeconomics of Energy and Climate Policies (European Commission, DG Energy, 2017); https://go.nature.com/3cdndJl
  11. Cambridge Econometrics in Final Report for the European Commission (DG Energy, 2013); https://go.nature.com/2PvVFoK
  12. E3ME Manual, Version 6 (Cambridge Econometrics, 2014); https://go.nature.com/2T1FIsO

Cited by

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Related

Authors
Knobloch, F., Hanssen, S. V., Lam, A., Pollitt, H., Salas, P., Chewpreecha, U., Huijbregts, M. A. J., & Mercure, J.-F.
Affiliations
  • Radboud University Nijmegen (NL)
  • University of Macau (MO)
  • University of Cambridge (GB)
  • Cambridge Econometrics (United Kingdom) (GB)
Corresponding author
Knobloch, Florian
ORCID
Venue
Nature Sustainability
Publisher
Springer Science and Business Media LLC
Published
2020-03-23
Volume
3
Issue
6
Pages
437-447
ISSN
2398-9629 (ISSN-L)
DOI
10.1038/s41893-020-0488-7
PMC
PMC7308170
OpenAlex
W3006678403
Cited by
407
References
55
Citations by year
2026: 64 · 2025: 73 · 2024: 67 · 2023: 80 · 2022: 63 · 2021: 40 · 2020: 20
FWCI
17.43
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Sustainability (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • Open Research Exeter (University of Exeter) (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Figshare (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion, other-oa)
Funders
  • European Commission (647224, HORIZON2020, 689150)
  • Engineering and Physical Sciences Research Council (EP/K007254/1, EP/N002504/1)
  • Economic and Social Research Council (ES/N013174/1)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Integrated Energy Systems Optimization
  • Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Energy, Environment, and Transportation Policies
Keywords
electric vehicles, heat pumps, greenhouse gas emissions, power sector decarbonization, transport decarbonization, household heating, electrification policy, life cycle assessment, integrated assessment models

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read under definition version 3 (extract-v3) on 2026-09-28.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-09-28.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

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