
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Greenhouse gas emissions from natural ecosystems and agricultural lands in sub-Saharan Africa: synthesis of available data and suggestions for further research

handle: 10568/83301
Greenhouse gas emissions from natural ecosystems and agricultural lands in sub-Saharan Africa: synthesis of available data and suggestions for further research
Abstract. This paper summarizes currently available data on greenhouse gas (GHG) emissions from African natural ecosystems and agricultural lands. The available data are used to synthesize current understanding of the drivers of change in GHG emissions, outline the knowledge gaps, and suggest future directions and strategies for GHG emission research. GHG emission data were collected from 75 studies conducted in 22 countries (n = 244) in sub-Saharan Africa (SSA). Carbon dioxide (CO2) emissions were by far the largest contributor to GHG emissions and global warming potential (GWP) in SSA natural terrestrial systems. CO2 emissions ranged from 3.3 to 57.0 Mg CO2 ha−1 yr−1, methane (CH4) emissions ranged from −4.8 to 3.5 kg ha−1 yr−1 (−0.16 to 0.12 Mg CO2 equivalent (eq.) ha−1 yr−1), and nitrous oxide (N2O) emissions ranged from −0.1 to 13.7 kg ha−1 yr−1 (−0.03 to 4.1 Mg CO2 eq. ha−1 yr−1). Soil physical and chemical properties, rewetting, vegetation type, forest management, and land-use changes were all found to be important factors affecting soil GHG emissions from natural terrestrial systems. In aquatic systems, CO2 was the largest contributor to total GHG emissions, ranging from 5.7 to 232.0 Mg CO2 ha−1 yr−1, followed by −26.3 to 2741.9 kg CH4 ha−1 yr−1 (−0.89 to 93.2 Mg CO2 eq. ha−1 yr−1) and 0.2 to 3.5 kg N2O ha−1 yr−1 (0.06 to 1.0 Mg CO2 eq. ha−1 yr−1). Rates of all GHG emissions from aquatic systems were affected by type, location, hydrological characteristics, and water quality. In croplands, soil GHG emissions were also dominated by CO2, ranging from 1.7 to 141.2 Mg CO2 ha−1 yr−1, with −1.3 to 66.7 kg CH4 ha−1 yr−1 (−0.04 to 2.3 Mg CO2 eq. ha−1 yr−1) and 0.05 to 112.0 kg N2O ha−1 yr−1 (0.015 to 33.4 Mg CO2 eq. ha−1 yr−1). N2O emission factors (EFs) ranged from 0.01 to 4.1 %. Incorporation of crop residues or manure with inorganic fertilizers invariably resulted in significant changes in GHG emissions, but results were inconsistent as the magnitude and direction of changes were differed by gas. Soil GHG emissions from vegetable gardens ranged from 73.3 to 132.0 Mg CO2 ha−1 yr−1 and 53.4 to 177.6 kg N2O ha−1 yr−1 (15.9 to 52.9 Mg CO2 eq. ha−1 yr−1) and N2O EFs ranged from 3 to 4 %. Soil CO2 and N2O emissions from agroforestry were 38.6 Mg CO2 ha−1 yr−1 and 0.2 to 26.7 kg N2O ha−1 yr−1 (0.06 to 8.0 Mg CO2 eq. ha−1 yr−1), respectively. Improving fallow with nitrogen (N)-fixing trees led to increased CO2 and N2O emissions compared to conventional croplands. The type and quality of plant residue in the fallow is an important control on how CO2 and N2O emissions are affected. Throughout agricultural lands, N2O emissions slowly increased with N inputs below 150 kg N ha−1 yr−1 and increased exponentially with N application rates up to 300 kg N ha−1 yr−1. The lowest yield-scaled N2O emissions were reported with N application rates ranging between 100 and 150 kg N ha−1. Overall, total CO2 eq. emissions from SSA natural ecosystems and agricultural lands were 56.9 ± 12.7 × 109 Mg CO2 eq. yr−1 with natural ecosystems and agricultural lands contributing 76.3 and 23.7 %, respectively. Additional GHG emission measurements are urgently required to reduce uncertainty on annual GHG emissions from the different land uses and identify major control factors and mitigation options for low-emission development. A common strategy for addressing this data gap may include identifying priorities for data acquisition, utilizing appropriate technologies, and involving international networks and collaboration.
- Universidad Politécnica de Madrid Spain
- CGIAR France
- CGIAR France
- CGIAR Consortium France
- Hawassa University Ethiopia
Soil Science, Environmental engineering, Carbon Dynamics in Peatland Ecosystems, Greenhouse gas, Environmental protection, Environmental science, Methane Emissions, Agricultural and Biological Sciences, Life, QH501-531, greenhouse gases, Biology, QH540-549.5, Ecosystem, agriculture, QE1-996.5, Global and Planetary Change, Nitrous oxide, Ecology, FOS: Environmental engineering, Life Sciences, Geology, Agriculture, food security, climate change, Carbon dioxide, Emissions, FOS: Biological sciences, Carbon dioxide equivalent, Global Methane Emissions and Impacts, Environmental Science, Physical Sciences, Soil Carbon Dynamics and Nutrient Cycling in Ecosystems, Methane
Soil Science, Environmental engineering, Carbon Dynamics in Peatland Ecosystems, Greenhouse gas, Environmental protection, Environmental science, Methane Emissions, Agricultural and Biological Sciences, Life, QH501-531, greenhouse gases, Biology, QH540-549.5, Ecosystem, agriculture, QE1-996.5, Global and Planetary Change, Nitrous oxide, Ecology, FOS: Environmental engineering, Life Sciences, Geology, Agriculture, food security, climate change, Carbon dioxide, Emissions, FOS: Biological sciences, Carbon dioxide equivalent, Global Methane Emissions and Impacts, Environmental Science, Physical Sciences, Soil Carbon Dynamics and Nutrient Cycling in Ecosystems, Methane
2 Research products, page 1 of 1
- 2002IsAmongTopNSimilarDocuments
- 2002IsAmongTopNSimilarDocuments
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).85 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
