Net carbon emissions from African biosphere dominate pan-tropical atmospheric CO2 signal

Palmer, Paul I.; Feng, Liang; Baker, D. F.; Chevallier, F.; Bösch, H.; Somkuti, Peter

doi:10.1038/s41467-019-11097-w

Cited by 120 publications

(149 citation statements)

References 64 publications

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“…Thus, the forest die-off in California was not attributed to a single extreme dry and warm event in 2015, but rather to a multiyear deep-rooting-zone drought. A similar phenomenon could have occurred over the tropics, where the lack of recovery in the carbon stocks in 2017 could also be explained by cumulative soil moisture depletion, related to low precipitation and enhanced evapotranspiration effects, particularly in the northern regions of tropical Africa (23). These regions also showed precipitation and cumulative soil moisture deficits, as estimated by the cumulative P − ET values ( fig.…”

Section: Discussionsupporting

confidence: 52%

Tropical forests did not recover from the strong 2015–2016 El Niño event

et al. 2020

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Severe drought and extreme heat associated with the 2015–2016 El Niño event have led to large carbon emissions from the tropical vegetation to the atmosphere. With the return to normal climatic conditions in 2017, tropical forest aboveground carbon (AGC) stocks are expected to partly recover due to increased productivity, but the intensity and spatial distribution of this recovery are unknown. We used low-frequency microwave satellite data (L-VOD) to feature precise monitoring of AGC changes and show that the AGC recovery of tropical ecosystems was slow and that by the end of 2017, AGC had not reached predrought levels of 2014. From 2014 to 2017, tropical AGC stocks decreased by 1.31.21.5 Pg C due to persistent AGC losses in Africa (−0.9−1.1−0.8 Pg C) and America (−0.5−0.6−0.4 Pg C). Pantropically, drylands recovered their carbon stocks to pre–El Niño levels, but African and American humid forests did not, suggesting carryover effects from enhanced forest mortality.

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Section: Discussionsupporting

confidence: 52%

Tropical forests did not recover from the strong 2015–2016 El Niño event

et al. 2020

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“…Compared to peatlands in Equatorial Asia, peat and peat fires in Africa are poorly studied, although recent estimates (Dargie et al 2017;Leifield & Menichetti 2018) indicate that the Congo basin is much richer in peat that presently known (Page et al 2011, FAO/ IIASA/ISRIC/ISSCAS/JRC 2012) and that climate change may induce extensive draught and higher risks of degradation. Palmer et al (2019) reported unexpectedly large net emissions from tropical Africa in recent years especially from western Ethiopia and western tropical Africa, recalling the occurrence there of large soil organic carbon stores and the substantial land use change. Gumbricht et al (2017) recognize that large biases hold in our current understanding of the distribution, area and volumes of tropical peat, and their continental contributions but propose that Southern America could be the region with richest peatlands endowment in the globe.…”

Section: Emissionsmentioning

confidence: 98%

New estimates of greenhouse gas emissions from biomass burning and peat fires using MODIS Collection 6 burned areas

et al. 2020

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The Paris Agreement calls on parties to undertake ambitious efforts to combat climate change by engaging in appropriate policies and measures as put forward through Nationally Determined Contributions (NDCs), to strengthen transparency when reporting their greenhouse gas (GHG) emissions and to increase their mitigation contributions to climate action from 2020. It also calls for regular and transparent monitoring and reporting of the GHG emissions and on the NDCs implementation efforts. Biomass fires significantly affect the GHG atmospheric balance, with fire emissions representing more than 5% of total emissions from agriculture, forestry, and other land use (AFOLU), according to recent estimates produced by the Food and Agriculture Organization (FAO). We update previously published Tier 1 estimates of GHG emissions in FAOSTAT-which had been used in the IPCC AR5 analysis-by using new burned area activity data from the Moderate Resolution Imaging Spectroradiometer (MODIS) known as MCD64A1, Collection 6. The previous FAOSTAT estimates had used as input the Global Fire Emission Database v.4 (GFED4) burned area product, based on older MODIS Collection 5.1 burned area product. In line with differences between the input data used, the new FAOSTAT estimates indicate roughly 30% higher fire emissions globally than previously published. Our analysis also confirms that the FAOSTAT Tier 1 approach produces fire emissions estimates that are comparable to those computed at Tier 3 by GFED, and thus represent a useful complementary tool in support of country GHG reporting.

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“…Previous studies of atmospheric CH 4 using satellite data tend to be global in scope with a posteriori emission estimates inferred over large continental regions (e.g. Fraser et al, 2013;Pandey et al, 2016;Feng et al, 2017), although some studies use satellite data in regional inversions to infer emissions on smaller regional scales (Turner et al, 2015;Ganesan et al, 2017;Miller et al, 2019). Recent work using GOSAT XCH 4 data has suggested that both atmospheric CH 4 mole fractions and CH 4 emissions from the African continent have increased since 2009 (Maasakkers et al, 2019;Miller et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2019

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Abstract. Emissions of methane (CH4) from tropical ecosystems, and how they respond to changes in climate, represent one of the biggest uncertainties associated with the global CH4 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 CH4 columns can help to narrow down some of the uncertainties in the tropical CH4 emission budget. We use proxy column retrievals of atmospheric CH4 (XCH4) from the Japanese Greenhouse gases Observing Satellite (GOSAT) and the nested version of the GEOS-Chem atmospheric chemistry and transport model (0.5∘×0.625∘) to infer emissions from tropical Africa between 2010 and 2016. Proxy retrievals of XCH4 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 (CO2) is known. We explore the sensitivity of inferred a posteriori emissions to this source of systematic error by using two different XCH4 data products that are determined using different model CO2 fields. We infer monthly emissions from GOSAT XCH4 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) Tg yr−1, depending on the proxy XCH4 data used, with larger differences in Northern Hemisphere Africa than Southern Hemisphere Africa. We find a robust positive linear trend in tropical African CH4 emissions for our 7-year study period, with values of 1.5 (1.1–1.9) Tg yr−1 or 2.1 (1.7–2.5) Tg yr−1, depending on the CO2 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 Tg yr−1 between 2011 and 2015 from the Sudd in South Sudan. Using satellite land surface temperature anomalies and altimetry data, we find this increase in CH4 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 CH4 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.

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Net carbon emissions from African biosphere dominate pan-tropical atmospheric CO2 signal

Cited by 120 publications

References 64 publications

Tropical forests did not recover from the strong 2015–2016 El Niño event

Tropical forests did not recover from the strong 2015–2016 El Niño event

New estimates of greenhouse gas emissions from biomass burning and peat fires using MODIS Collection 6 burned areas

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

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