ALBERT

Notes: Abstract The Gambia has successfully completed a national greenhouse gas emissions inventory based on the results of a study funded by the United Nations Environment Programme (UNEP)/Global Environment Facility (GEF) Country Case Study Program. The concepts of multisectoral, multidisciplinary, and interdisciplinary collaboration were most useful in the preparation of this inventory. New data were gathered during the study period, some through regional collaboration with institutions such as Environment and Development in the Third World (ENDA-TM) Energy Program and the Ecological Monitoring Center in Dakar, Senegal, and some through national surveys and the use of remote sensing techniques, as in the Bushfires Survey. Most of the data collected are used in this paper. The Intergovernmental Panel on Climate Change/Organisation for Economic Co-operation and Development/International Energy Agency (IPCC/OECD/IEA) methodology is used to calculate greenhouse gas emissions. Many of the default data in the IPCC/OECD/IEA methodology have also been used. Overall results indicate that in the biomass sectors (agriculture, forestry, and land-use change) carbon dioxide (CO2) is emitted most, with a total of 1.7 Tg. This is followed by methane (CH4), 22.3 Gg; carbon monoxide (CO), 18.7 Gg; nitrogen oxides (NOx), 0.3 Gg; and nitrous oxide (N2O), 0.014 Gg. The Global Warming Potential (GWP) was used as an index to describe the relative effects of the various gases reported here. Based on the emissions in The Gambia in 1993, it was found that CO2 will contribute 75%, CH4 about 24.5%, and N2O 0.2% of the warming expected in the 100-year period beginning in 1993. The results in this analysis are limited by the shortcomings of the IPCC/OECD/IEA methodology and scarce national data. Because the methodology was developed outside of the developing world, most of its emissions factors and coefficients were developed and tested in environments that are very different from The Gambia. This is likely to introduce some uncertainties into the results of the calculations. Factors and coefficients that are country-or region-specific are likely to provide more accurate results and should be developed. The surveys were conducted either during the wet season or just at the end of the wet season. This seasonal factor should contribute to variations in the results, particularly in the livestock numbers and composition survey. Use of one-time survey data is also likely to introduce uncertainty into the results.