Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Pervasive over-crediting from cookstove offset methodologies


Cookstove carbon offset projects can progress multiple Sustainable Development Goals (SDGs), including climate, energy, health, gender, poverty and deforestation. However, project emission reductions must be accurately or conservatively estimated to avoid undermining climate action and long-term SDG financing. Here we conduct a comprehensive, quantitative, quality assessment of offsets by comparing five cookstove methodologies with published literature and our own analysis. We find misalignment, in order of importance, with fraction of non-renewable biomass, firewood–charcoal conversion, stove adoption, stove usage, fuel consumption, stacking (using multiple stoves), rebound and emission factors. Additionality, leakage, permanence and overlapping claims require more research. We estimate that our project sample is over-credited 9.2 times. Gold Standard’s metered methodology, which directly monitors fuel use, is most aligned with our estimates (1.5 times over-credited) and has the largest potential for emission abatement and health benefit. We provide recommendations to align methodologies with current science and SDG progress.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type



Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Transitions from baseline to project fuels by cookstove carbon offset projects.
Fig. 2: Issued credits across the VCM and our sample.
Fig. 3: Over/under-crediting across factors.

Data availability

All data and code are publicly available online at

Code availability

All data and code are publicly available online at


  1. Abbafati, C. et al. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 396, 1223–1249 (2020).

    Article  Google Scholar 

  2. Bailis, R., Drigo, R., Ghilardi, A. & Masera, O. The carbon footprint of traditional woodfuels. Nat. Clim. Change 5, 266–272 (2015).

    Article  CAS  ADS  Google Scholar 

  3. Defining clean fuels and technologies. World Health Organization (2021).

  4. So I., Haya, B. & Elias, M. Voluntary registry offsets database v.8. University of California, Berkeley (2023).

  5. Stapp, J. et al. Little evidence of management change in California’s forest offset program. Commun. Earth Environ. 4, 331 (2023).

    Article  ADS  Google Scholar 

  6. Haya, B. Policy Brief: the California Air Resources Board’s US Forest Offset Protocol Underestimates Leakage (Goldman School of Public Policy, University of California, Berkeley, 2019);

  7. Haya, B. et al. Quality assessment of REDD+ carbon credit projects. Berkeley carbon trading project. Goldman School of Public Policy, University of California, Berkeley (2023).

  8. West, T. A. P. et al. Action needed to make carbon offsets from forest conservation work for climate change mitigation. Science 381, 873–877 (2023).

    Article  CAS  PubMed  ADS  Google Scholar 

  9. Cames, M. et al. How additional is the clean development mechanism? Analysis of the application of current tools and proposed alternatives. DG CLIMA (2016).

  10. Haya, B. K. Carbon Offsetting: An Efficient Way to Reduce Emissions or to Avoid Reducing Emissions? An Investigation and Analysis of Offsetting Design and Practice in India and China. PhD thesis, University of California, Berkeley (2010).

  11. Bailis, R., Wang, Y., Drigo, R., Ghilardi, A. & Masera, O. Getting the numbers right: revisiting woodfuel sustainability in the developing world. Environ. Res. Lett. 12, 115002 (2017).

  12. Ramanathan, T. et al. Wireless sensors linked to climate financing for globally affordable clean cooking. Nat. Clim. Change 7, 44–47 (2017).

    Article  ADS  Google Scholar 

  13. Freeman, O. E. & Zerriffi, H. How you count carbon matters: implications of differing cookstove carbon credit methodologies for climate and development cobenefits. Environ. Sci. Technol. 48, 14112–14120 (2014).

  14. Sanford, L. & Burney, J. Cookstoves illustrate the need for a comprehensive carbon market. Environ. Res. Lett. 10, 084026 (2015).

  15. Simon, G. L., Bumpus, A. G. & Mann, P. Win–win scenarios at the climate–development interface: challenges and opportunities for stove replacement programs through carbon finance. Glob. Environ. Change 22, 275–287 (2012).

    Article  Google Scholar 

  16. Lee, C. M., Chandler, C., Lazarus, M. & Johnson, F. X. Assessing the climate impacts of cookstove projects: issues in emissions accounting. Chall. Sustain. 1, 53–71 (2013).

    Google Scholar 

  17. Reduced emissions from cooking and heating—technologies and practices to displace decentralized thermal energy consumption (TPDDTEC). The Gold Standard Foundation (2021).

  18. The Gold Standard simplified methodology for clean and efficient cookstoves. The Gold Standard Foundation (2022).

  19. AMS-II.G.: energy efficiency measures in thermal applications of non-renewable biomass version 12.0. Clean Development Mechanism (2022).

  20. AMS-I.E.: switch from non-renewable biomass for thermal applications by the user version 12.0. Clean Development Mechanism (2021).

  21. Methodology for metered and measured energy cooking devices. The Gold Standard Foundation (2022).

  22. Krumpal, I. Determinants of social desirability bias in sensitive surveys: a literature review. Qual. Quant. 47, 2025–2047 (2013).

    Article  Google Scholar 

  23. Kar, A., Brauer, M., Bailis, R. & Zerriffi, H. The risk of survey bias in self-reports vs. actual consumption of clean cooking fuels. World Dev. Perspect. 18, 100199 (2020).

    Article  Google Scholar 

  24. Wilson, D. L. et al. in Technologies for Development (eds Hostettler S. et al.) 211–221 (Springer, 2015).

  25. Simons, A. M., Beltramo, T., Blalock, G. & Levine, D. I. Using unobtrusive sensors to measure and minimize Hawthorne effects: evidence from cookstoves. J. Environ. Econ. Manage. 86, 68–80 (2017).

  26. Shankar, A. V. et al. Everybody stacks: lessons from household energy case studies to inform design principles for clean energy transitions. Energy Policy 141, 111468 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Hanna, R., Duflo, E. & Greenstone, M. Up in smoke: the influence of household behavior on the long-run impact of improved cooking stoves. Am. Econ. J. Econ. Policy 8, 80–114 (2016).

    Article  Google Scholar 

  28. Burwen, J. & Levine, D. I. A rapid assessment randomized-controlled trial of improved cookstoves in rural Ghana. Energy Sustain Dev. 16, 328–338 (2012).

    Article  Google Scholar 

  29. Beltramo, T., Blalock, G., Harrell, S., Levine, D. & Simons, A. M. The effects of fuel-efficient cookstoves on fuel use, particulate matter, and cooking practices: results from a randomized trial in rural Uganda. UC Berkeley Center for Effective Global Action (2019).

  30. Rosa, G. et al. Assessing the impact of water filters and improved cook stoves on drinking water quality and household air pollution: a randomised controlled trial in Rwanda. PLoS ONE 9, e91011 (2014).

    Article  PubMed  PubMed Central  ADS  Google Scholar 

  31. Bensch, G. & Peters, J. The intensive margin of technology adoption—experimental evidence on improved cooking stoves in rural Senegal. J. Health Econ. 42, 44–63 (2015).

    Article  PubMed  Google Scholar 

  32. Ruiz-Mercado, I., Masera, O., Zamora, H. & Smith, K. R. Adoption and sustained use of improved cookstoves. Energy Policy 39, 7557–7566 (2011).

    Article  CAS  Google Scholar 

  33. Islam, M. M. et al. Assessing the effects of stove use patterns and kitchen chimneys on indoor air quality during a multiyear cookstove randomized control trial in rural India. Environ. Sci. Technol. 56, 8326–8337 (2022).

    Article  CAS  PubMed  ADS  Google Scholar 

  34. García-Frapolli, E. et al. Beyond fuelwood savings: valuing the economic benefits of introducing improved biomass cookstoves in the Purépecha Region of Mexico. Ecol. Econ. 69, 2598–2605 (2010).

    Article  Google Scholar 

  35. Agurto Adrianzén, M. Social capital and improved stoves usage decisions in the Northern Peruvian Andes. World Dev. 54, 1–17 (2014).

    Article  Google Scholar 

  36. Jeuland, M., Soo, J. S. T. & Shindell, D. The need for policies to reduce the costs of cleaner cooking in low income settings: implications from systematic analysis of costs and benefits. Energy Policy 121, 275–285 (2018).

    Article  Google Scholar 

  37. Ruiz-Mercado, I., Canuz, E., Walker, J. L. & Smith, K. R. Quantitative metrics of stove adoption using stove use monitors (SUMs). Biomass Bioenergy 57, 136–148 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Pine, K. et al. Adoption and use of improved biomass stoves in rural Mexico. Energy Sustain. Dev. 15, 176–183 (2011).

    Article  Google Scholar 

  39. Pattanayak, S. K. et al. Experimental evidence on promotion of electric and improved biomass cookstoves. Proc. Natl Acad. Sci. USA 116, 13282–13287 (2019).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  40. MP88: meeting report/recommendations to the executive board. CDM Methodologies Panel (2022).

  41. Life cycle assessment of cooking fuel systems in India, China, Kenya, and Ghana. US Environmental Protection Agency (2021).

  42. Wathore, R., Mortimer, K. & Grieshop, A. P. In-use emissions and estimated impacts of traditional, natural- and forced-draft cookstoves in rural Malawi. Environ. Sci. Technol. 51, 1929–1938 (2017).

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  43. Stockwell, T. et al. Estimating under- and over-reporting of drinking in national surveys of alcohol consumption: identification of consistent biases across four English-speaking countries. Addiction 111, 1203–1213 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Ezzati, M., Martin, H., Skjold, S., Hoorn, S. V. & Murray, C. J. L. Trends in national and state-level obesity in the USA after correction for self-report bias: analysis of health surveys. J. R. Soc. Med. 99, 250–257 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  45. Concept Note CDM-MP85-A07. Analysis and Options Regarding Caps Used in AMS-I.E, AMS-II.G and TOOL30 Version 01.0 (Clean Development Mechanism, 2013);

  46. Daioglou, V., van Ruijven, B. J. & van Vuuren, D. P. Model projections for household energy use in developing countries. Energy 37, 601–615 (2012).

    Article  Google Scholar 

  47. Tool 30: calculation of the fraction of non-renewable biomass (version 3). Clean Development Mechanism (2020).

  48. Ghilardi, A. et al. Spatiotemporal modeling of fuelwood environmental impacts: towards improved accounting for non-renewable biomass. Environ. Model Softw. 82, 241–254 (2016).

    Article  Google Scholar 

  49. Floess, E. et al. Scaling up gas and electric cooking in low- and middle-income countries: climate threat or mitigation strategy with co-benefits? Environ. Res. Lett. 18, 034010 (2023).

    Article  ADS  Google Scholar 

  50. Whitman, T. L. & Lehmann, C. J. Systematic under and overestimation of GHG reductions in renewable biomass systems. Clim. Change 104, 415–422 (2011).

    Article  CAS  ADS  Google Scholar 

  51. Huang, Y. et al. Global radiative effects of solid fuel cookstove aerosol emissions. Atmos. Chem. Phys. 18, 5219–5233 (2018).

    Article  CAS  ADS  Google Scholar 

  52. Bailis R., et al. Enhancing clean cooking options in peri-urban Kenya: a pilot study of advanced gasifier stove adoption. Environ. Res. Lett. 15, 084017 (2020).

  53. Forum on natural capital accounting for better policy decisions: taking stock and moving forward. World Bank Group (2017).

  54. Dufournaud, C. M., Quinn, J. T. & Harrington, J. J. A partial equilibrium analysis of the impact of introducing more-efficient wood-burning stoves into households in the Sahelian Region. Environ. Plan. Econ. Space 26, 407–414 (1994).

    Article  Google Scholar 

  55. Lambe, F. et al. Opening the black pot: a service design-driven approach to understanding the use of cleaner cookstoves in peri-urban Kenya. Energy Res. Soc. Sci. 70, 101754 (2020).

    Article  Google Scholar 

  56. ISO/IEC 17029:2019 general principles and requirements for validation and verification bodies. ISO (2019).

  57. Khavari, B., Ramirez, C., Jeuland, M. & Fuso Nerini, F. A geospatial approach to understanding clean cooking challenges in sub-Saharan Africa. Nat. Sustain. 6, 447–457 (2023).

    Article  Google Scholar 

  58. Bakhtary, H., Tierney, M., Galt, H. & Gill-Wiehl, A. More than just a Carbon Project: How Clean Cooking Projects Certified Under the Gold Standard Approach SDG Claims (Climate Focus, 2023);

  59. Gill-Wiehl, A. & Kammen, D. M. A pro-health cookstove strategy to advance energy, social and ecological justice. Nat. Energy 7, 999–1002 (2022).

  60. The handbook for programme of activities: practical guidance to successful implementation. Climate Focus (2011).

  61. Fitzpatrick, D. in Analog Design and Simulation Using OrCAD Capture and PSpice 2nd edn (ed Fitzpatrick, D.) 151–164 (Newnes, 2018).

  62. Robinson, B. L., Clifford, M. J., Hewitt, J. & Jewitt, S. Cooking for communities, children and cows: lessons learned from institutional cookstoves in Nepal. Energy Sustain. Dev. 66, 1–11 (2022).

    Article  Google Scholar 

  63. Gill-Wiehl, A., Hogan, M. & Haya, B. A comprehensive quality assessment of cookstoves carbon credits. Golman School of Public Policy, University of California, Berkeley (2023).

Download references


The research that led to these results received funding from the Center for African Studies, University of California, Berkeley (A.G.-W.), Carbon Direct (B.K.H.), (D.K.), Katherine Lau Family Foundation (A.G.-W. and D.K.), the National Science Foundation’s Graduate Researcher Fellowship Program (A.G.-W.), the Mulago Foundation/Better Cooking Company (A.G.-W.) and the Zaffaroni Family Foundation (D.K.). We thank A. Haya for help with initial data collection. We also thank Calyx Global and D. Lee. A.G.-W. thanks I. Ray and A. Hubbard for additional advising support.

Author information

Authors and Affiliations



A.G.-W. and B.K.H. co-led the research design. A.G.-W. compiled the data, conducted the analysis and co-led the write up of the paper. B.K.H. originated the idea and co-led the write up of the paper. D.K. contributed to the research design and write up, as well as funding the work.

Corresponding author

Correspondence to Annelise Gill-Wiehl.

Ethics declarations

Competing interests

A.G.-W. has received research support from Better Cooking Company Limited, whose leadership also provided comments on a draft of the manuscript. B.K.H. has received research support from Carbon Direct. D.K. declares no competeing interests.

Peer review

Peer review information

Nature Sustainability thanks Philippe Delacote, Ben Groom and Bruno Marino for their contribution to the peer review of this work.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary extended methods, Figs. 1–3, Tables 1–23, discussion of health benefits, co-benefits, methodology equations and methodology surveys; our sample of projects; studies included in our adoption, usage, stacking, additionality and leakage investigations; overview of monitoring types; additional results: all over-crediting results; sensitivity analysis; MCM histogram; location analysis.

Reporting Summary

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gill-Wiehl, A., Kammen, D.M. & Haya, B.K. Pervasive over-crediting from cookstove offset methodologies. Nat Sustain 7, 191–202 (2024).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing