Skip to main content

Advertisement

Log in

Carbon and precursor gases emission from forest and non-forest land sources in West Africa

  • Original Paper
  • Published:
International Journal of Environmental Science and Technology Aims and scope Submit manuscript

Abstract

African forests make up a significant proportion of global greenhouse gas (GHG) emissions from land-use change, deforestation, agriculture, and forest degradation due to increasing population, settlements, and growing food demand. This study provides detailed information and assesses the contributions of various vegetation classifications on emission estimates from the forest and non-forest lands in the West Africa sub-region between 1990 and 2019 using the inventory-based estimation approach. The savanna and grassland vegetations are the largest sources of estimated emissions with percentage contributions of 39.3% and 33.2%, respectively. The total GHG emissions estimates within the study period were 10.59 Pg for CO2; 19.23 Tg for CH4; 1.37 Tg for N2O; 0.46 Pg for CO and 23.53 Tg for NOX. West Africa is responsible for approximately a fourth of emissions from the northern hemisphere africa sub-region at an average annual emission of 350 Tg/yr. The regional net global warming potential (GWP) between 1990 and 2019 was estimated to be 11.44 Pg and Nigeria had the highest GWP at 18.7% followed closely by Mali and Ghana at 15% and 13.2%, respectively. We have provided detailed country-by-country estimates for important GHG species in various vegetation classifications of West Africa. The results from this study would help to improve GHG accounting from the forest and non-forest areas in West Africa and reduce uncertainties related to it.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Abbreviations

barea:

Burned area

CS:

Closed Shrubland

defrate:

Deforestation rate

GL:

Grassland

HTF:

Humid tropical forest

OF:

Other forests

OS:

Open shrubland

pop:

Population

rain:

Rainfall

REDD:

Reduce emissions from deforestation and forest degradation

Sav:

Savanna

temp:

Temperature

wfem:

Wood fuel removal

WS:

Woody savanna

References

  • Ahmad A, Liu Q-J, Nizami S, Mannan A, Saeed S (2018) Carbon emission from deforestation, forest degradation and wood harvest in the temperate region of Hindukush Himalaya, Pakistan between 1994 and 2016. Land Use Policy 78:781–790

    Article  Google Scholar 

  • Ahmed Z, Wang Z, Ali S (2019) Investigating the non-linear relationship between urbanization and CO2 emissions: an empirical analysis. Air Qual Atmos Health 12(8):945–953

    Article  CAS  Google Scholar 

  • Alcañiz M, Outeiro L, Francos M, Úbeda X (2018) Effects of prescribed fires on soil properties: a review. Sci Total Environ 613:944–957. https://doi.org/10.1016/j.scitotenv.2017.09.144

    Article  CAS  Google Scholar 

  • Andela N, Van Der Werf GR (2014) Recent trends in African fires driven by cropland expansion and El Nino to La Nina transition. Nat Clim Chang 4(9):791

    Article  Google Scholar 

  • Andreae MO, Merlet P (2001) Emission of trace gases and aerosols from biomass burning. Global Biogeochem Cycles 15(4):955–966

    Article  CAS  Google Scholar 

  • Asenso Barnieh BA, Jia L, Menenti M, Zhou J, Zeng Y (2020) Mapping land use land cover transitions at different spatiotemporal scales in West Africa. Sustainability 12(20):8565

    Article  Google Scholar 

  • Barry A, Caesar J, Klein Tank A, Aguilar E, McSweeney C, Cyrille AM, Nikiema M, Narcisse K, Sima F, Stafford G (2018) West Africa climate extremes and climate change indices. Int J Climatol 38:e921–e938

    Article  Google Scholar 

  • Bezirtzoglou C, Dekas K, Charvalos E (2011) Climate changes, environment and infection: facts, scenarios and growing awareness from the public health community within Europe. Anaerobe 17(6):337–340

    Article  Google Scholar 

  • Blignaut JN, Chitiga-Mabugu M, Mabugu R (2005) Constructing a greenhouse gas emissions inventory using energy balances: the case of South Africa for 1998. J Energy S Afr 16:21

    Article  Google Scholar 

  • Bromhead MA (2012) Forest, trees, and woodlands in Africa: an action plan for World Bank engagement.

  • Brown S, Gaston G (1995) Use of forest inventories and geographic information systems to estimate biomass density of tropical forests: application to tropical Africa African greenhouse gas emission inventories and mitigation options: forestry, land-use change, and agriculture. Springer, pp 51–62

    Google Scholar 

  • CILSS (2016) Landscapes of West Africa—a window on a changing world: CILSS Ouagadougou, Burkina Faso.

  • Crippa M, Guizzardi D, Muntean M, Schaaf E, Solazzo E, Olivier J, Vignati E (2018) Fossil CO2 emissions of all world countries. Publications Office of the European Union, Luxembourg

    Google Scholar 

  • Diedhiou A, Bichet A, Wartenburger R, Seneviratne SI, Rowell DP, Sylla MB, Diallo I, Todzo S, N’datchoh ET, Camara M (2018) Changes in climate extremes over West and Central Africa at 15 °C and 2 °C global warming. Environ Res Lett 13(6):065020

    Article  Google Scholar 

  • Dosio A, Mentaschi L, Fischer EM, Wyser K (2018) Extreme heat waves under 15 °C and 2 °C global warming. Environ Res Lett 13(5):054006

    Article  Google Scholar 

  • Endo N, Eltahir EA (2020) Increased risk of malaria transmission with warming temperature in the Ethiopian Highlands. Environ Res Lett 15(5):054006

    Article  Google Scholar 

  • Environ New Nigeria, (2020) How afforetstation combat desrtification in Nigeria. https://www.environewsnigeria.com/how-afforestation-combats-desertification-in-nigeria/

  • FAO (2015) Gobal forest resources assessment 2015. Desk reference: food and agricultural organization rome

  • FAO (2020) Global forest resources assessment 2020: main report. Rome Retrieved from https://doi.org/10.4060/ca9825en

  • FAO (2011) Disaster risk management strategy in West Africa and the Sahel. Retrieved from FAO (2011–2013). Rome, FAO

  • Fatima T, Shahzad U, Cui L (2021) Renewable and nonrenewable energy consumption, trade and CO2 emissions in high emitter countries: does the income level matter? J Environ Plan Manag 64(7):1227–1251

    Article  Google Scholar 

  • Ferguson W (1985) Integrating crops and livestock in West Africa. FAO Animal Production and Health Paper. 41

  • FRA (2015) Global forest reserve assessment, 2015 Desk reference. Food and Agriculture Organization of United Nations. Retrieved from http://www.fao.org/3/a-i4808e.pdf

  • Ganzenmüller R, Pradhan P, Kropp JP (2019) Sectoral performance analysis of national greenhouse gas emission inventories by means of neural networks. Sci Total Environ 656:80–89

    Article  Google Scholar 

  • Giglio L, Boschetti L, Roy DP, Humber ML, Justice CO (2018) The Collection 6 MODIS burned area mapping algorithm and product. Remote Sens Environ 217:72–85

    Article  Google Scholar 

  • Hashmi R, Alam K (2019) Dynamic relationship among environmental regulation, innovation, CO2 emissions, population, and economic growth in OECD countries: a panel investigation. J Clean Prod 231:1100–1109

    Article  Google Scholar 

  • Herrmann SM, Brandt M, Rasmussen K, Fensholt R (2020) Accelerating land cover change in West Africa over four decades as population pressure increased. Commun Earth Environ 1(1):1–10

    Article  Google Scholar 

  • Huisingh D, Zhang Z, Moore JC, Qiao Q, Li Q (2015) Recent advances in carbon emissions reduction: policies, technologies, monitoring, assessment and modeling. J Clean Prod 103:1–12

    Article  CAS  Google Scholar 

  • IEA (2019) World Energy Outlook. Retrieved from

  • IPCC (1996) Land-use change & forestry: revised 1996 IPCC guidelines for national greenhouse gas inventories: reference manual. Retrieved from https://www.ipccnggip.iges.or.jp/public/gl/guidelin/ch5ref1.pdf

  • Isichei AO (1995) Stocks of nitrogen in vegetation and soil in West African moist savannas and potential effects of climate change and land use on these stocks. J Biogeograp 22:393–399

    Article  Google Scholar 

  • Le Stradic S, Buisson E (2020) Restoring savannas and tropical herbaceous ecosystems, Encyclopedia of the Environment, [online ISSN 2555–0950] url : https://www.encyclopedie-environnement.org/en/life/restoring-savannas-and-tropical-herbaceous-ecosystems/

  • Lin B, Xu B (2018) Factors affecting CO2 emissions in China’s agriculture sector: a quantile regression. Renew Sustain Energy Rev 94:15–27

    Article  Google Scholar 

  • Lipsett-Moore GJ, Wolff NH, Game ET (2018) Emissions mitigation opportunities for savanna countries from early dry season fire management. Nat Commun 9(1):1–8

    Article  CAS  Google Scholar 

  • Löf M, Madsen P, Metslaid M, Witzell J, Jacobs DF (2019) Restoring forests: regeneration and ecosystem function for the future. New for 50(2):139–151

    Article  Google Scholar 

  • Marais EA, Wiedinmyer C (2016) Air quality impact of diffuse and inefficient combustion emissions in Africa (DICE-Africa). Environ Sci Technol 50(19):10739–10745

    Article  CAS  Google Scholar 

  • McMurray A, Pearson T, Casarim F (2017) Guidance on applying the Monte Carlo approach to uncertainty analyses in forestry and greenhouse gas accounting. Winrock International, Arlington

    Google Scholar 

  • Ndri AB, Soro TD, Gignoux J, Dosso K, Koné M, Ndri JK, Barot S (2018) Season affects fire behavior in annually burned humid savanna of West Africa. Fire Ecol 14(2):1–11

    Google Scholar 

  • Olaore A, Aja GN (2014) The impact of flooding on the social determinants of health in Nigeria: a case for north-south institutional collaboration to address climate issues. Dev Ctry Stud 4(22):6–13

    Google Scholar 

  • Olivier J, Peters J (2010) No growth in total global CO2 emissions in 2009. Netherlands Environmental Assessment Agency (PBL), Bilthoven

    Google Scholar 

  • Rehman A, Jingdong L, Khatoon R, Hussain I, Iqbal MS (2016) Modern agricultural technology adoption its importance, role and usage for the improvement of agriculture. Life Sci J 14(2):70–74

    Google Scholar 

  • Ren C, Liu S, Van Grinsven H, Reis S, Jin S, Liu H, Gu B (2019) The impact of farm size on agricultural sustainability. J Clean Prod 220:357–367

    Article  Google Scholar 

  • Ringard J, Dieppois B, Rome S, Diedhiou A, Pellarin T, Konaré A, Diawara A, Konaté D, Dje B, Katiellou G (2016) The intensification of thermal extremes in west Africa. Global Planet Change 139:66–77

    Article  Google Scholar 

  • Rocha AAM, Gonçalves E, and De Almeida ES (2018) Agricultural technology and land use: evidence for Brazil.

  • Romijn E, Coppus R, De Sy V, Herold M, Roman-Cuesta RM, Verchot L (2019) Land restoration in Latin America and the Caribbean: an overview of recent, ongoing and planned restoration initiatives and their potential for climate change mitigation. Forests 10(6):510

    Article  Google Scholar 

  • Rossati A (2017) Global warming and its health impact. Int J Occup Environ Med 8(1):7

    Article  Google Scholar 

  • Russo S, Marchese AF, Sillmann J, Immé G (2016) When will unusual heat waves become normal in a warming Africa? Environ Res Lett 11(5):054016

    Article  Google Scholar 

  • Scholes RJ, Archibald S, von Maltitz G (2011) Emissions from fire in Sub-Saharan Africa: the magnitude of sources, their variability and uncertainty. Glob Environ Res 15(1):53–63

    CAS  Google Scholar 

  • Scholes R (1995) Greenhouse gas emissions from vegetation fires in southern Africa African greenhouse gas emission inventories and mitigation options: forestry, land-use change, and agriculture. Springer, pp 63–73

    Google Scholar 

  • Shepard D (2019) Global warming: severe consequences for Africa: new report projects greater temperature increases. Africa Renewal 32(3):34–34

    Article  Google Scholar 

  • Shuman E (2011) Global climate change and infectious diseases. Int J Occup Environ Med IJOEM 2:1

    Google Scholar 

  • Tappan G, Cushing M (2004) Use of SLC-Off Landsat Image Data for monitoring land use/land cover trends in West Africa. US Geological Survey (USGS), Earth Resources Observation and Science (EROS) Data Center, South Dakota

    Google Scholar 

  • Tappan GG, Cushing WM, Cotillon SE, Mathis ML, Hutchinson JA, Herrmann SM, Dalsted KJ (2016) West Africa land use land cover time series: U.S. Geological survey data release,https://doi.org/10.5066/F73N21JF

  • Tongwane MI, Moeletsi ME (2018) A review of greenhouse gas emissions from the agriculture sector in Africa. Agric Syst 166:124–134

    Article  Google Scholar 

  • UN (2019) United Nations, department of economic and social affairs, population division (2019). World Population Prospects 2019, Volume II: demographic profiles (ST/ESA/SER.A/427). Retrieved from https://population.un.org/wpp/Graphs/1_Demographic%20Profiles/Western%20Africa.pdf

  • UNFCCC (2020) Climate change is an increasing threat to Africa.

  • USGS (2021) West Africa: land use and land cover dynamics. Retrieved from https://eros.usgs.gov/westafrica/physical-geography

  • Van der Werf GR, Randerson JT, Giglio L, Collatz G, Mu M, Kasibhatla PS, Morton DC, DeFries R, Jin YV, van Leeuwen TT (2010) Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009). Atmos Chem Phys 10(23):11707–11735

    Article  Google Scholar 

  • Van Marle MJ, Kloster S, Magi BI, Marlon JR, Daniau A-L, Field RD, Arneth A, Forrest M, Hantson S, Kehrwald NM (2017) Historic global biomass burning emissions for CMIP6 (BB4CMIP) based on merging satellite observations with proxies and fire models (1750–2015). Geosci Model Dev 10(9):3329–3357

    Article  Google Scholar 

  • Wang J, Xi F, Liu Z, Bing L, Alsaedi A, Hayat T, Ahmad B, Guan D (2018a) The spatiotemporal features of greenhouse gases emissions from biomass burning in China from 2000 to 2012. J Clean Prod 181:801–808

    Article  CAS  Google Scholar 

  • Wang J, Yue Y, Wang Y, Ichoku C, Ellison L, Zeng J (2018b) Mitigating satellite-based fire sampling limitations in deriving biomass burning emission rates: application to WRF-chem model over the northern sub-Saharan African Region. J Geophys Res Atmos 123(1):507–528

    Article  Google Scholar 

  • Werf GR, Randerson JT, Giglio L, Leeuwen TTV, Chen Y, Rogers BM, Mu M, Van Marle MJ, Morton DC, Collatz GJ (2017) Global fire emissions estimates during 1997–2016. Earth Syst Sci Data 9(2):697–720

    Article  Google Scholar 

  • WHO (2012) Flooding disaster: Nigeria. Public health risk assessment and interventions. World Health Organization, Abuja

  • World Development Indicator (World Bank, 2021a) https://data.worldbank.org/indicator/NY.GDP.MKTP.KD.ZG?locations=ZG

  • World Development Indicator (World Bank, 2021b) https://climateknowledgeportal.worldbank.org/country/nigeria/climate-data-historical

  • Yadav IC, Devi NL (2018) Biomass burning, regional air quality, and climate change. Earth systems and environmental sciences. Edition: encyclopedia of environmental health. Elsevier https://doi.org/10.1016/B978-0-12-409548-9.11022-X.

  • Yang L, Xia H, Zhang X, Yuan S (2018) What matters for carbon emissions in regional sectors? a China study of extended STIRPAT model. J Clean Prod 180:595–602

    Article  Google Scholar 

  • Zhang H, Hu J, Qi Y, Li C, Chen J, Wang X, He J, Wang S, Hao J, Zhang L (2017) Emission characterization, environmental impact, and control measure of PM2. 5 emitted from agricultural crop residue burning in China. J Cleaner Prod 149:629–635

    Article  CAS  Google Scholar 

  • Zhang G, Zhang N, Liao W (2018a) How do population and land urbanization affect CO2 emissions under gravity center change? a spatial econometric analysis. J Clean Prod 202:510–523

    Article  Google Scholar 

  • Zhang W, Lu Z, Xu Y, Wang C, Gu Y, Xu H, Streets DG (2018b) Black carbon emissions from biomass and coal in rural China. Atmos Environ 176:158–170

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The authors wish to thank all who assisted in conducting this work.

Funding

Tertiary Education Trust Fund, DAPM/TETFUND/01/13,Khadijat Abdulkareem Abdulraheem

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to J. A. Adeniran.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Editorial responsibility: Mohamed F. Yassin.

Appendix

Appendix

Table

Table 7 Default value for the amount of fuel actually burnt (i.e. the product of MB and Cf)

7 and

Table 8 Emission factors for various burning types. Source: IPPC (2006). IPCC Guidelines for National Greenhouse Gas Inventories. Agriculture, Forestry and Other Land Use, Volume 4. Generic Methodologies Applicable to Multiple Land-Use Categories, Chapter 2

8 of the IPCC 2006.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Abdulraheem, K.A., Adeniran, J.A. & Aremu, A.S. Carbon and precursor gases emission from forest and non-forest land sources in West Africa. Int. J. Environ. Sci. Technol. 19, 12003–12018 (2022). https://doi.org/10.1007/s13762-022-04304-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13762-022-04304-7

Keywords

Navigation