The carbon footprint of traditional woodfuels

Abstract

Over half of all wood harvested worldwide is used as fuel, supplying 9% of global primary energy. By depleting stocks of woody biomass, unsustainable harvesting can contribute to forest degradation, deforestation and climate change. However, past efforts to quantify woodfuel sustainability failed to provide credible results. We present a spatially explicit assessment of pan-tropical woodfuel supply and demand, calculate the degree to which woodfuel demand exceeds regrowth, and estimate woodfuel-related greenhouse-gas emissions for the year 2009. We estimate 27–34% of woodfuel harvested was unsustainable, with large geographic variations. Our estimates are lower than estimates from carbon offset projects, which are probably overstating the climate benefits of improved stoves. Approximately 275 million people live in woodfuel depletion ‘hotspots’—concentrated in South Asia and East Africa—where most demand is unsustainable. Emissions from woodfuels are 1.0–1.2 Gt CO2e yr−1 (1.9–2.3% of global emissions). Successful deployment and utilization of 100 million improved stoves could reduce this by 11–17%. At US$11 per tCO2e, these reductions would be worth over US$1 billion yr−1 in avoided greenhouse-gas emissions if black carbon were integrated into carbon markets. By identifying potential areas of woodfuel-driven degradation or deforestation, we inform the ongoing discussion about REDD-based approaches to climate change mitigation.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Mapping of a high-deficit zone in East Africa.
Figure 2: Pan-tropical expected fNRBB2.
Figure 3: Distribution of regional population by expected fNRBB2 decile.
Figure 4: Annual emissions and emission reductions resulting from fulfilling GACC’s objective of 100 million stoves disseminated through interventions with different priorities.
Figure 5: Countries with highest per capita woodfuel demand, highest expected fNRBB2, and highest burden of disease from HAP exposure.

References

  1. 1

    FAOSTAT Forestry Production and Trade (UN FAO, 2013); http://faostat3.fao.org/faostat-gateway/go/to/download/F/*/E

    Google Scholar 

  2. 2

    Renewable Energy Policy Network for the 21st century (REN21) Renewables Global Status Report: 2013 Update Report No. 177 (REN21 Secretariat, 2013)

  3. 3

    Bonjour, S. et al. Solid fuel use for household cooking: Country and regional estimates for 1980–2010. Environ. Health Perspect. 121, 784–790 (2013).

    Article  Google Scholar 

  4. 4

    Lim, S. S. et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990–2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 380, 2224–2260 (2012).

    Article  Google Scholar 

  5. 5

    Rudel, T. K. The national determinants of deforestation in sub-Saharan Africa. Phil. Trans. R. Soc. B 368, 20120405 (2013).

    Article  Google Scholar 

  6. 6

    Bailis, R., Ezzati, M. & Kammen, D. M. Mortality and greenhouse gas impacts of biomass and petroleum energy futures in Africa. Science 308, 98–103 (2005).

    CAS  Article  Google Scholar 

  7. 7

    Bond, T. C. et al. Bounding the role of black carbon in the climate system: A scientific assessment. J. Geophys. Res. 118, 5380–5552 (2013).

    CAS  Google Scholar 

  8. 8

    Ramanathan, V. & Carmichael, G. Global and regional climate changes due to black carbon. Nature Geosci. 1, 221–227 (2008).

    CAS  Article  Google Scholar 

  9. 9

    Eckholm, E. The Other Energy Crisis: Firewood Report No. 22 (Worldwatch, 1975)

  10. 10

    Eckholm, E. Fuelwood: The Energy Crisis That Won’t Go Away (Earthscan, 1984).

    Google Scholar 

  11. 11

    Leach, G. & Mearns, R. Beyond the Woodfuel Crisis: People, Land, and Trees in Africa (Earthscan, 1988).

    Google Scholar 

  12. 12

    Arnold, J. M. & Dewees, P. A. Farms, Trees and Farmers: Responses to Agricultural Intensification (Earthscan, 1997).

    Google Scholar 

  13. 13

    Hansfort, S. & Mertz, O. Challenging the woodfuel crisis in West African woodlands. Hum. Ecol. 39, 583–595 (2011).

    Article  Google Scholar 

  14. 14

    Singh, G., Rawat, G. S. & Verma, D. Comparative study of fuelwood consumption by villagers and seasonal “Dhaba owners” in the tourist affected regions of Garhwal Himalaya, India. Energy Policy 38, 1895–1899 (2010).

    Article  Google Scholar 

  15. 15

    Mayaux, P. et al. State and evolution of the African rainforests between 1990 and 2010. Phil. Trans. R. Soc. B 368, 20120300 (2013).

    Article  Google Scholar 

  16. 16

    Hosonuma, N. et al. An assessment of deforestation and forest degradation drivers in developing countries. Environ. Res. Lett. 7, 044009 (2012).

    Article  Google Scholar 

  17. 17

    Smith, P. et al. in Climate Change 2014: Mitigation of Climate Change (eds Edenhofer, O., Pichs-Madruga, R. & Sokona, Y.) 811–922 (IPCC, Cambridge Univ. Press, 2014).

    Google Scholar 

  18. 18

    Drigo, R. WISDOM Case Studies (2014); http://www.wisdomprojects.net/global/cs.asp

  19. 19

    Statistics Balances (International Energy Agency, 2012); http://www.iea.org/stats/index.asp

  20. 20

    Rogner, H-H. et al. in Climate Change 2007: Mitigation of Climate Change (eds Metz, B. et al.) 95–116 (IPCC, Cambridge Univ. Press, 2007).

    Google Scholar 

  21. 21

    Alliance Mission and Goals (Global Alliance for Clean Cookstoves, 2014); http://www.cleancookstoves.org/the-alliance

  22. 22

    Angelsen, A. et al. Realising REDD+: National Strategy and Policy Options (Center for International Forestry Research (CIFOR), 2009).

    Google Scholar 

  23. 23

    Subramanian, M. Global health: Deadly dinners. Nature 509, 548–551 (2014).

    CAS  Article  Google Scholar 

  24. 24

    Johnson, M., Edwards, R. & Masera, O. Improved stove programs need robust methods to estimate carbon offsets. Climatic Change 102, 641–649 (2010).

    CAS  Article  Google Scholar 

  25. 25

    IEA World Energy Statistics and Balances (International Energy Agency, 2013); http://www.oecd-ilibrary.org/statistics

  26. 26

    UN Statistics Division Energy Statistics Database (United Nations, 2013); http://data.un.org/Explorer.aspx

    Google Scholar 

  27. 27

    Drigo, R. & Salbitano, F. WISDOM for Cities: Analysis of Wood Energy and Urbanization Using WISDOM Methodology (FAO Forestry Department Report, 2008)

  28. 28

    Bailis, R. Modeling climate change mitigation from alternative methods of charcoal production in Kenya. Biomass Bioenergy 33, 1491–1502 (2009).

    CAS  Article  Google Scholar 

  29. 29

    Mwampamba, T. H., Ghilardi, A., Sander, K. & Chaix, K. J. Dispelling common misconceptions to improve attitudes and policy outlook on charcoal in developing countries. Energy Sustain. Dev. 17, 75–85 (2013).

    Article  Google Scholar 

  30. 30

    Global Forest Resources Assessment 2010 (UN FAO, 2010)

  31. 31

    Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).

    CAS  Article  Google Scholar 

  32. 32

    EDGAR Database (European Commission—Joint Research Centre, 2014); http://edgar.jrc.ec.europa.eu/overview.php?v=GHGts1990-2010

  33. 33

    Simon, G. L., Bailis, R., Baumgartner, J., Hyman, J. & Laurent, A. Current debates and future research needs in the clean cookstove sector. Energy Sustain. Dev. 20, 49–57 (2014).

    Article  Google Scholar 

  34. 34

    Bazilian, M., Cordes, L., Nussbaumer, P. & Yager, A. Partnerships for access to modern cooking fuels and technologies. Curr. Opin. Environ. Sustain. 3, 254–259 (2011).

    Article  Google Scholar 

  35. 35

    Peters-Stanley, M., Yin, D., Castillo, S., Gonzalez, G. & Goldstein, A. Maneuvering the Mosaic: State of the Voluntary Carbon Markets 2013 Report No. 105 (Ecosystem Marketplace and Bloomberg New Energy Finance, 2013)

  36. 36

    Masera, O., Ghilardi, A., Drigo, R. & Trossero, M. A. WISDOM: A GIS-based supply demand mapping tool for woodfuel management. Biomass Bioenergy 30, 618–637 (2006).

    Article  Google Scholar 

  37. 37

    European Space Agency GlobCover Portal (European Space Agency, 2011); http://due.esrin.esa.int/globcover/

  38. 38

    Global Ecological Zones (UN FAO, 2011); http://www.fao.org/geonetwork/srv/en/metadata.show?id=1255

  39. 39

    Baccini, A. et al. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Clim. Change 2, 182–185 (2012).

    CAS  Article  Google Scholar 

  40. 40

    Saatchi, S. S. et al. Benchmark map of forest carbon stocks in tropical regions across three continents. Proc. Natl Acad. Sci. 108, 9899–9904 (2011).

    CAS  Article  Google Scholar 

  41. 41

    Duku, M. H., Gu, S. & Hagan, E. B. A comprehensive review of biomass resources and biofuels potential in Ghana. Renew. Sustain. Energy Rev. 15, 404–415 (2011).

    Article  Google Scholar 

  42. 42

    Ajoku, K. in Bioenergy for Sustainable Development in Africa (eds Janssen, R. & Rutz, D.) Ch. 12, 131–146 (Springer, 2012).

    Google Scholar 

  43. 43

    Wheeler, D., Kraft, R. & Hammer, D. Forest Clearing in the Pantropics: December 2005-August 2011 Working Paper 283 (Center for Global Development, 2011)

  44. 44

    Carlson, K. M. et al. Committed carbon emissions, deforestation, and community land conversion from oil palm plantation expansion in West Kalimantan, Indonesia. Proc. Natl Acad. Sci. 109, 7559–7564 (2012).

    CAS  Article  Google Scholar 

  45. 45

    Gatti, L. et al. Drought sensitivity of Amazonian carbon balance revealed by atmospheric measurements. Nature 506, 76–80 (2014).

    CAS  Article  Google Scholar 

  46. 46

    An, L., Linderman, M., Qi, J., Shortridge, A. & Liu, J. Exploring complexity in a human–environment system: An agent-based spatial model for multidisciplinary and multiscale integration. Ann. Assoc. Am. Geogr. 95, 54–79 (2005).

    Article  Google Scholar 

  47. 47

    Bhatt, B. P. & Sachan, M. S. Firewood consumption along an altitudinal gradient in mountain villages of India. Biomass Bioenergy 27, 69–75 (2004).

    Article  Google Scholar 

  48. 48

    Jetter, J. et al. Pollutant emissions and energy efficiency under controlled conditions for household biomass cookstoves and implications for metrics useful in setting international test standards. Environ. Sci. Technol. 46, 10827–10834 (2012).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

This research was funded by the Global Alliance for Clean Cookstoves, an initiative supported by the UN Foundation.

Author information

Affiliations

Authors

Contributions

R.D., R.B., A.G. and O.M. designed the study; R.D. conducted the pan-tropical WISDOM analysis and constructed the NRB model; R.B. calculated GHG emissions and emission reductions; R.D., R.B., A.G. and O.M. wrote the paper.

Corresponding author

Correspondence to Robert Bailis.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Bailis, R., Drigo, R., Ghilardi, A. et al. The carbon footprint of traditional woodfuels. Nature Clim Change 5, 266–272 (2015). https://doi.org/10.1038/nclimate2491

Download citation

Further reading