An increase in methane emissions from tropical Africa between 2010 and 2016 inferred from satellite data

• Main Authors: M. F. Lunt, P. I. Palmer, L. Feng, C. M. Taylor, H. Boesch, R. J. Parker
• Format: Article
• Language: English
• Published: Copernicus Publications 2019-12-01
• Series: Atmospheric Chemistry and Physics
• Online Access: https://www.atmos-chem-phys.net/19/14721/2019/acp-19-14721-2019.pdf
• ISSN: 1680-7316; 1680-7324

<p>Emissions of methane (<span class="inline-formula">CH₄</span>) from tropical ecosystems, and how they respond to changes in climate, represent one of the biggest uncertainties associated with the global <span class="inline-formula">CH₄</span> budget. Historically, this has been due to the dearth of pan-tropical in situ measurements, which is particularly acute in Africa. By virtue of their superior spatial coverage, satellite observations of atmospheric <span class="inline-formula">CH₄</span> columns can help to narrow down some of the uncertainties in the tropical <span class="inline-formula">CH₄</span> emission budget. We use proxy column retrievals of atmospheric <span class="inline-formula">CH₄</span> (<span class="inline-formula">XCH₄</span>) from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the nested version of the GEOS-Chem atmospheric chemistry and transport model (<span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M7" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">0.5</mn><msup><mi/><mo>∘</mo></msup><mspace width="0.125em" linebreak="nobreak"/><mo>×</mo><mspace linebreak="nobreak" width="0.125em"/><mn mathvariant="normal">0.625</mn><msup><mi/><mo>∘</mo></msup></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="67pt" height="11pt" class="svg-formula" dspmath="mathimg" md5hash="94db5c4ea3c5edbcf2cb8e6a20a0a27f"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="acp-19-14721-2019-ie00001.svg" width="67pt" height="11pt" src="acp-19-14721-2019-ie00001.png"/></svg:svg></span></span>) to infer emissions from tropical Africa between 2010 and 2016. Proxy retrievals of <span class="inline-formula">XCH₄</span> are less sensitive to scattering due to clouds and aerosol than full physics retrievals, but the method assumes that the global distribution of carbon dioxide (<span class="inline-formula">CO₂</span>) is known. We explore the sensitivity of inferred a posteriori emissions to this source of systematic error by using two different <span class="inline-formula">XCH₄</span> data products that are determined using different model <span class="inline-formula">CO₂</span> fields. We infer monthly emissions from GOSAT <span class="inline-formula">XCH₄</span> data using a hierarchical Bayesian framework, allowing us to report seasonal cycles and trends in annual mean values. We find mean tropical African emissions between 2010 and 2016 range from 76 (74–78) to 80 (78–82)&thinsp;Tg&thinsp;yr<span class="inline-formula">⁻¹</span>, depending on the proxy <span class="inline-formula">XCH₄</span> data used, with larger differences in Northern Hemisphere Africa than Southern Hemisphere Africa. We find a robust positive linear trend in tropical African <span class="inline-formula">CH₄</span> emissions for our 7-year study period, with values of 1.5 (1.1–1.9)&thinsp;Tg&thinsp;yr<span class="inline-formula">⁻¹</span> or 2.1 (1.7–2.5)&thinsp;Tg&thinsp;yr<span class="inline-formula">⁻¹</span>, depending on the <span class="inline-formula">CO₂</span> data product used in the proxy retrieval. This linear emissions trend accounts for around a third of the global emissions growth rate during this period. A substantial portion of this increase is due to a short-term increase in emissions of 3&thinsp;Tg&thinsp;yr<span class="inline-formula">⁻¹</span> between 2011 and 2015 from the Sudd in South Sudan. Using satellite land surface temperature anomalies and altimetry data, we find this increase in <span class="inline-formula">CH₄</span> emissions is consistent with an increase in wetland extent due to increased inflow from the White Nile, although the data indicate that the Sudd was anomalously dry at the start of our inversion period. We find a strong seasonality in emissions across Northern Hemisphere Africa, with the timing of the seasonal emissions peak coincident with the seasonal peak in ground water storage. In contrast, we find that a posteriori <span class="inline-formula">CH₄</span> emissions from the wetland area of the Congo Basin are approximately constant throughout the year, consistent with less temporal variability in wetland extent, and significantly smaller than a priori estimates.</p>