Cited by 467Climate Change Policy and EconomicsSustainability and Climate Change GovernanceEnergy, Environment, Economic Growth

The DOI matches its Crossref record; 33 of the 34 references it cites were found in a registry or an index; none of the 21 sources its claims cite is checked for support yet.

Taking stock of national climate policies to evaluate implementation of the Paris Agreement

Open access

Abstract

Many countries have implemented national climate policies to accomplish pledged Nationally Determined Contributions and to contribute to the temperature objectives of the Paris Agreement on climate change. In 2023, the global stocktake will assess the combined effort of countries. Here, based on a public policy database and a multi-model scenario analysis, we show that implementation of current policies leaves a median emission gap of 22.4 to 28.2 GtCO 2 eq by 2030 with the optimal pathways to implement the well below 2 °C and 1.5 °C Paris goals. If Nationally Determined Contributions would be fully implemented, this gap would be reduced by a third. Interestingly, the countries evaluated were found to not achieve their pledged contributions with implemented policies (implementation gap), or to have an ambition gap with optimal pathways towards well below 2 °C. This shows that all countries would need to accelerate the implementation of policies for renewable technologies, while efficiency improvements are especially important in emerging countries and fossil-fuel-dependent countries.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Using a policy inventory and multi-model scenario analysis, current national climate policies leave a median 2030 emissions gap of 22.4 GtCO2eq with well-below-2 °C pathways and 28.2 GtCO2eq with 1.5 °C pathways. Full implementation of conditional NDCs would reduce the 2 °C gap by a third but still leave a significant ambition gap.

Key findings

  • Global greenhouse gas emissions under the National policies scenario reach 59.3 GtCO2eq (58.4–63.7) by 2030, a 5.3% (3.8%–7.9%) reduction relative to No new policies; this covers 15.4% (10.8%–19.0%) of the gap to the 2 °C pathway and 11% (7.6%–15.9%) to the 1.5 °C pathway.
  • The total 2030 emissions gap between National policies and cost-optimal pathways is 22.4 GtCO2eq (13.6–29.6) for 2 °C and 28.2 GtCO2eq (19.8–42.2) for 1.5 °C. Full conditional NDCs give 51.9 GtCO2eq (50.4–57.4) in 2030, leaving an implementation gap of 7.7 GtCO2eq (5.3–9.7); the 2 °C gap is reduced by a third, leaving a median ambition gap of 16.5 GtCO2eq (6.4–21.0) for 2 °C and 21.2 GtCO2eq (12.2–31.6) for 1.5 °C.
  • For seven large economies, policy implementation reduces national emissions by 0% to 9% (median) relative to No new policies. Implementation gaps with NDCs range from 3% (3–7%) for the Russian Federation to 28% (22–37%) for the United States; China, India, Japan, and the Russian Federation are projected to come close to their NDC targets, while Brazil, the European Union, and the United States are further removed.
  • Closing the global gap by 2030 requires increasing the low-carbon share of final energy by 6.9 pp (4.0%–12.3%) and improving energy intensity by 9.6% (4.8%–24.7%) for 2 °C; for 1.5 °C, these values are 13.0% (7.2%–24.0%) and 17.5% (12.5%–26.8%).

Methods

  • Multi-model scenario analysis using nine global integrated assessment models and ten national models, starting from SSP2, with five scenarios: No new policies, National policies, NDCs, 2 °C, and 1.5 °C.
  • National policies were selected from an open-access policy database, based on high-impact policies for G20 economies, with a cut-off date of 31 December 2016; results are presented globally and for Brazil, China, the European Union, India, Japan, the Russian Federation, and the United States.
  • Results use medians and 10th–90th percentile ranges across models; gaps are decomposed using Kaya identity indicators, and 2 °C/1.5 °C scenarios use carbon budgets of 1000 GtCO2 and 400 GtCO2 for 2011–2100, respectively.

Limitations

  • The paper states that the analysis is limited to national policies and NDCs for G20 economies representing 75% of total 2010 greenhouse gas emissions; countries with high-impact policies but not included represent around 5% of global 2010 emissions.
  • The paper states that the policy inventory covers implemented and planned national policies up to 2017, with a cut-off date of 31 December 2016, so very recent policy updates or planned policies in the pipeline were not included.
  • The paper states that IAMs differ in aggregation and policy representation, often assume one central planner, and have limited ability to reflect social and economic dynamics of developing and transition economies; cost-optimal 2 °C/1.5 °C pathways may imply higher costs in low-income regions unless complemented by financial transfers. Evident from the text: NDC targets for China and India could not be translated into one specific absolute greenhouse gas emission level, and AFOLU emission estimates are inherently uncertain.

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Integrity signals

Registry

Crossref · 10.1038/s41467-020-15414-6

Cites

33 of 33 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Fig. 1 Greenhouse gas emissions on a global level and seven large countries under different scenarios. a Global greenhouse gas emissions for total greenhouse gases (in GtCO2eq) and nine integrated assessment models between 2010 and 2030. b Average greenhouse gas emissions (in MtCO2eq) of all models by 2010, 2015 and 2030 for CO2 emissions per sector and total non-CO2 emissions (blue), including the 10th–90th percentile ranges for total greenhouse gas emissions of the multi-model ensemble (error bars). CO2 emissions have been separated into those related to energy supply (red), transport (dark orange), buildings (light orange), industry (yellow) and AFOLU (agriculture, afforestation, forestry and land-use change) (green). National models are China-TIMES and IPAC for China, GCAM-USA for the United States, PRIMES for the EU, AIM India and India MARKAL for India, RU-TIMES for the Russian Federation, BLUES for Brazil and AIM/Enduse and DNE21 + for Japan. For both panels, CO2 equivalent greenhouse gases have been calculated using the 100-year Global Warming Potential from the IPCC Fourth Assessment Report. The data is available in the source data.
Fig. 1 Greenhouse gas emissions on a global level and seven large countries under different scenarios. a Global greenhouse gas emissions for total greenhouse gases (in GtCO2eq) and nine integrated assessment models between 2010 and 2030. b Average greenhouse gas emissions (in MtCO2eq) of all models by 2010, 2015 and 2030 for CO2 emissions per sector and total non-CO2 emissions (blue), including the 10th–90th percentile ranges for total greenhouse gas emissions of the multi-model ensemble (error bars). CO2 emissions have been separated into those related to energy supply (red), transport (dark orange), buildings (light orange), industry (yellow) and AFOLU (agriculture, afforestation, forestry and land-use change) (green). National models are China-TIMES and IPAC for China, GCAM-USA for the United States, PRIMES for the EU, AIM India and India MARKAL for India, RU-TIMES for the Russian Federation, BLUES for Brazil and AIM/Enduse and DNE21 + for Japan. For both panels, CO2 equivalent greenhouse gases have been calculated using the 100-year Global Warming Potential from the IPCC Fourth Assessment Report. The data is available in the source data.CC BY · PubMed Central
Fig. 2 Final energy and the low-carbon share of final energy on the global level and seven large countries under different scenarios. Average total final energy for 2010, 2015 and 2030 of nine global integrated assessment models is subdivided into sectors: transport, buildings, industry and other. Total final energy includes the 10th to 90th percentile ranges for total final energy (error bars). The black dots/triangles indicate final energy based on national model estimates (China-TIMES and IPAC for China, GCAM-USA for the United States, PRIMES for the European Union, AIM India and India MARKAL for India, RU-TIMES for the Russian Federation, BLUES for Brazil and AIM/Enduse and DNE21 + for Japan). The data is available in the source data.
Fig. 2 Final energy and the low-carbon share of final energy on the global level and seven large countries under different scenarios. Average total final energy for 2010, 2015 and 2030 of nine global integrated assessment models is subdivided into sectors: transport, buildings, industry and other. Total final energy includes the 10th to 90th percentile ranges for total final energy (error bars). The black dots/triangles indicate final energy based on national model estimates (China-TIMES and IPAC for China, GCAM-USA for the United States, PRIMES for the European Union, AIM India and India MARKAL for India, RU-TIMES for the Russian Federation, BLUES for Brazil and AIM/Enduse and DNE21 + for Japan). The data is available in the source data.CC BY · PubMed Central
Fig. 3 Indicators derived from Kaya identity and costs per GDP between 2010 and 2030 on a global level and for seven large countries under different scenarios. The median (lines) and 10th–90th percentile ranges (areas) from nine integrated global assessment models on emissions, energy mix and efficiency gaps and mitigation costs per GDP. These gaps are represented by total greenhouse gas emissions (MtCO2eq), low-carbon share of final energy (%), final energy intensity in GDP (TJ/USD2010) and total mitigation costs per GDP (%) between national policies and well below 2 °C scenarios. The data is available in the source data.
Fig. 3 Indicators derived from Kaya identity and costs per GDP between 2010 and 2030 on a global level and for seven large countries under different scenarios. The median (lines) and 10th–90th percentile ranges (areas) from nine integrated global assessment models on emissions, energy mix and efficiency gaps and mitigation costs per GDP. These gaps are represented by total greenhouse gas emissions (MtCO2eq), low-carbon share of final energy (%), final energy intensity in GDP (TJ/USD2010) and total mitigation costs per GDP (%) between national policies and well below 2 °C scenarios. The data is available in the source data.CC BY · PubMed Central
Fig. 4 Cumulative CO2 emissions in the period 2011–2050 period relative to 2010 emissions on the global level and for seven large countries under different scenarios. The box plots indicate the median, 25th to 75th percentile range, while the black data points show the full global model range. The brown coloured markers indicate the results from the national models. The data is available in the source data.
Fig. 4 Cumulative CO2 emissions in the period 2011–2050 period relative to 2010 emissions on the global level and for seven large countries under different scenarios. The box plots indicate the median, 25th to 75th percentile range, while the black data points show the full global model range. The brown coloured markers indicate the results from the national models. The data is available in the source data.CC BY · PubMed Central
Fig. 5 Decomposition of total median emission growth between 2015 and 2030 under National policies scenario, error bars range between 10th to and 90th percentiles. The data is available in the source data.
Fig. 5 Decomposition of total median emission growth between 2015 and 2030 under National policies scenario, error bars range between 10th to and 90th percentiles. The data is available in the source data.CC BY · PubMed Central

Verification

Claims the paper makes

34 Own result · 13 Not checked yet · 13 No basis given · 12 Own interpretation · 4 Own method

Verify all 21 references — free account

Show all 41 claims

  • Probably not a substantial claim. 16
  • It may state two separate claims as one. 27
35 of 35
  • The paper relies on this without support.

    The success of the Paris Agreement critically depends on the implementation of climate policies at the national level.

    “While this objective is formulated at the global level, the success of the agreement critically depends on the implementation of climate policies at the national level.”
  • The authors state this as an assumption.

    Countries pursue the same national efforts between 2030 and 2050 under the National policies scenario by keeping total percentage emission reductions relative to the No new policies scenario constant.

    “and in addition assume countries pursue the same national efforts between 2030 and 2050 under the National policies scenario by keeping total percentage emission reductions relative to the No new policies scenario constant.”
  • The authors state this as an assumption.

    The 2 °C and 1.5 °C pathways are calculated assuming cost-optimal implementation.

    “In all, 2 °C and 1.5 °C pathways in this study are calculated assuming cost-optimal implementation”
  • The authors state this as an assumption.

    If a policy instrument would end before the policy target year, the instrument is assumed to continue until the target year of the aspirational goal.

    “If the policy instrument would end before the policy target year, we assumed continuation of this instrument until the target year of the aspirational goal.”
  • The authors state this as an assumption.

    Where a G20 country is part of a larger model region, the policy indicator is aggregated by assuming business-as-usual for those countries without policies and implementation of the policy for countries with policies.

    “In case a G20 country is part of a larger model region, the policy (indicator) is aggregated by assuming business-as-usual for those countries without policies, and implementation of the policy for countries with policies32.”
  • The authors state this as an assumption.

    Equivalent effort after 2030 is assumed, defined as a constant percentage reduction relative to the No new policies scenario or similar forms of continued ambition.

    “The national policies were implemented for the period from 2010 to 2030, and equivalent effort was assumed after 2030.”
6 of 6

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4 of 4

Citations

Cites

Show all 34 references

Research works printed but not linked: 4

  1. IPCC. Chapter 2: Mitigation Pathways Compatible with 1.5 °C in the Context of Sustainable Development (IPCC, 2018).
  2. Blanco, G. et al. In Climate Change 2014: Mitigation of Climate Change (Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2014).
  3. Kitous, A., Keramidas, K., Vandyck, T. & Saveyn, B. GECO 2016. Global Energy and Climate Outlook. Road from Paris. Impact of Climate Policies on Global Energy Markets in the Context of the UNFCCC Paris Agreement. JRC Science for policy report. https://doi.org/10.2791/662470 (2016). · DOI
  4. FAOSTAT. Food and agriculture data, http://faostat3.fao.org/home/E. Vol. 2017 FAOSTAT provides free access to food and agriculture (FAOSTAT, 2017).

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Metadata

Authors
Roelfsema, M., van Soest, H. L., Harmsen, M., van Vuuren, D. P., Bertram, C., den Elzen, M., Höhne, N., Iacobuta, G., Krey, V., Kriegler, E., Luderer, G., Riahi, K., Ueckerdt, F., Després, J., Drouet, L., Emmerling, J., Frank, S., Fricko, O., Gidden, M., Humpenöder, F., Huppmann, D., Fujimori, S., Fragkiadakis, K., Gi, K., Keramidas, K., Köberle, A. C., Aleluia Reis, L., Rochedo, P., Schaeffer, R., Oshiro, K., Vrontisi, Z., Chen, W., Iyer, G. C., Edmonds, J., Kannavou, M., Jiang, K., Mathur, R., Safonov, G., & Vishwanathan, S. S.
Affiliations
  • Utrecht University (NL)
  • Netherlands Environmental Assessment Agency (NL)
  • Leibniz Association (DE)
  • NewClimate Institute (DE)
  • International Institute for Applied Systems Analysis (AT)
  • European Commission (BE)
  • RFF-CMCC European Institute on Economics and the Environment (IT)
  • Kyoto University (JP)
  • National Technical University of Athens (GR)
  • Research Institute of Innovative Technology for the Earth (JP)
  • Universidade Federal do Rio de Janeiro (BR)
  • Tsinghua University (CN)
  • Joint Global Change Research Institute (US)
  • National Development and Reform Commission (CN)
  • Energy and Resources Institute (IN)
  • Indian Institute of Management Ahmedabad (IN)
Corresponding author
Roelfsema, Mark
Venue
Nature Communications
Published
2020-04-29
Volume
11
Issue
1
Pages
2096-2096
ISSN
2041-1723 (ISSN-L)
OpenAlex
W3021969666
Cited by
467
References
34
Citations by year
2026: 51 · 2025: 78 · 2024: 79 · 2023: 77 · 2022: 76 · 2021: 85 · 2020: 20
FWCI
54.85
Type
journal article
Language
en
Open access
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Socio-Environmental Systems Modeling (acceptedVersion, cc-by)
  • IIASA PURE (International Institute of Applied Systems Analysis) (acceptedVersion)
  • Institutional Repositories DataBase (IRDB) (submittedVersion, cc-by)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
  • RENATE (submittedVersion, cc-by-nc-nd)
  • Joint Research Centre (European Commission) (submittedVersion)
  • Publication Database PIK (Potsdam Institute for Climate Impact Research (PIK)) (submittedVersion, other-oa)
  • Kyoto University Research Information Repository (Kyoto University) (submittedVersion, cc-by)
  • VU Research Portal (submittedVersion)
  • Spiral (Imperial College London) (submittedVersion, cc-by)
  • Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
  • RENATE (cc-by)
Funders
  • Environmental Restoration and Conservation Agency (2-1702, 2-1908)
  • European Commission (21020701/2017/770447/SER/CLIMA.C.1 EuropeAid/138417/DH/SER/MulitOC, HORIZON2020, 642147, 821471)
  • Indian Institute of Management Ahmedabad
  • Tsinghua University
  • Korea Advanced Institute of Science and Technology
  • National Research University Higher School of Economics
  • Environment and Climate Change Canada
  • National Development and Reform Commission
  • International Institute for Applied Systems Analysis
  • Institut Teknologi Bandung
  • National Cancer Institute
Topics
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Climate Change Policy and Economics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Sustainability and Climate Change Governance
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Energy, Environment, Economic Growth
Keywords
Paris Agreement, Nationally Determined Contributions, climate policy implementation, emissions gap, Global Stocktake, 2°C target, 1.5°C target, renewable energy deployment, energy efficiency, emerging markets, climate change mitigation

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