Regional methane emission from West Siberia mire landscapes

Glagolev, M. V.; Kleptsova, I E; Filippov, Ilya; Maksyutov, Shamil; Machida, Toshinobu

doi:10.1088/1748-9326/6/4/045214

Cited by 100 publications

(137 citation statements)

References 21 publications

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“…There is a need for integration of methane flux measurements on the model of the FLUXNET activity (http://fluxnet.ornl.gov/). This would allow further refinement of the model parameterizations (Turetsky et al, 2014;Glagolev et al, 2011). A comparison of the model ensemble estimates against bottom-up inventory for western Siberia by Glagolev et al (2011) made by Bohn et al (2015) showed that there still is a sizable disagreement between their results.…”

Section: Regional Methane Emissions Per Source Categorymentioning

confidence: 99%

“…This would allow further refinement of the model parameterizations (Turetsky et al, 2014;Glagolev et al, 2011). A comparison of the model ensemble estimates against bottom-up inventory for western Siberia by Glagolev et al (2011) made by Bohn et al (2015) showed that there still is a sizable disagreement between their results. A more complete analysis of the literature for freshwater emissions has led to a 50 % increase of the reported range compared to Kirschke et al (2013).…”

Section: Regional Methane Emissions Per Source Categorymentioning

confidence: 99%

See 1 more Smart Citation

The global methane budget 2000–2012

Saunois

Bousquet

Poulter

et al. 2016

Earth Syst. Sci. Data

947

733

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Abstract. The global methane (CH 4 ) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH 4 over the past decade. Emissions and concentrations of CH 4 are continuing to increase, making CH 4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH 4 sources that overlap geographically, and from the destruction of CH 4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (∼ biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). . Top-down inversions consistently infer lower emissions in China (∼ 58 Tg CH 4 yr −1 , range 51-72, −14 %) and higher emissions in Africa (86 Tg CH 4 yr −1 , range 73-108, +19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models.The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30-40 % on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions.

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Section: Regional Methane Emissions Per Source Categorymentioning

confidence: 99%

Section: Regional Methane Emissions Per Source Categorymentioning

confidence: 99%

The global methane budget 2000–2012

Saunois

Bousquet

Poulter

et al. 2016

Earth Syst. Sci. Data

947

733

View full text Add to dashboard Cite

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“…[8] To begin, we collected direct CH 4 flux chamber measurements of wetland ecosystems in the northern high latitudes from peer-reviewed literature [e.g., Glagolev et al, 2011;Levy et al, 2011]. Our data contain CH 4 flux chamber measurements from 34 sites, covering a range of wetland types under various field conditions (Table 1 and Figure 1).…”

Section: Data Organizationmentioning

confidence: 99%

Estimating wetland methane emissions from the northern high latitudes from 1990 to 2009 using artificial neural networks

Zhu

Zhuang

Qin

et al. 2013

Global Biogeochemical Cycles

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[1] Methane (CH 4 ) emissions from wetland ecosystems in nothern high latitudes provide a potentially positive feedback to global climate warming. Large uncertainties still remain in estimating wetland CH 4 emisions at regional scales. Here we develop a statistical model of CH 4 emissions using an artificial neural network (ANN) approach and field observations of CH 4 fluxes. Six explanatory variables (air temperature, precipitation, water table depth, soil organic carbon, soil total porosity, and soil pH) are included in the development of ANN models, which are then extrapolated to the northern high latitudes to estimate monthly CH 4 emissions from 1990 to 2009. We estimate that the annual wetland CH 4 source from the northern high latitudes (north of 45 N) is 48.7 Tg CH 4 yr À1 (1 Tg = 10 12 g) with an uncertainty range of 44.0~53.7 Tg CH 4 yr À1 . The estimated wetland CH 4 emissions show a large spatial variability over the northern high latitudes, due to variations in hydrology, climate, and soil conditions. Significant interannual and seasonal variations of wetland CH 4 emissions exist in the past 2 decades, and the emissions in this period are most sensitive to variations in water table position. To improve future assessment of wetland CH 4 dynamics in this region, research priorities should be directed to better characterizing hydrological processes of wetlands, including temporal dynamics of water table position and spatial dynamics of wetland areas.Citation: Zhu, X., Q. Zhuang, Z. Qin, M. Glagolev, and L. Song (2013), Estimating wetland methane emissions from the northern high latitudes from 1990 to 2009 using artificial neural networks, Global Biogeochem. Cycles, 27, 592-604,

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“…Globally, wetlands are the largest natural source of CH 4 emissions to the atmosphere (IPCC, 2013). Because wetland CH 4 emissions are highly sensitive to soil temperature and moisture conditions (Saarnio et al, 1997;Friborg et al, 2003;Christensen et al, 2003;Moore et al, 2011;Glagolev et al, 2011;Sabrekov et al, 2014), there is concern that they will provide positive feedback to future climate warming (Gedney et al, 2004;Eliseev et al, 2008;Ringeval et al, 2011). This risk is particularly important in the world's high latitudes because they contain nearly half of the world's wetlands (Lehner and Döll, 2004) and because the high latitudes have been and are forecast to continue experiencing more rapid warming than elsewhere (Serreze et al, 2000;IPCC, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Peatlands are a type of wetland containing deep deposits of highly porous, organic-rich soil, formed over thousands of years under waterlogged and anoxic conditions, which inhibit decomposition (Gorham, 1991;Frolking et al, 2011). Within the porous soil, the water table is often only a few centimeters below the surface, leading to anoxic conditions and CH 4 emissions even when no surface water is present (Saarnio et al, 1997;Friborg et al, 2003;Glagolev et al, 2011). This condition can lead to an underestimation of wetland area when using satellite surface water products as inputs to wetland methane emissions models.…”

Section: Introductionmentioning

confidence: 99%

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

et al. 2015

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Abstract. Wetlands are the world's largest natural source of methane, a powerful greenhouse gas. The strong sensitivity of methane emissions to environmental factors such as soil temperature and moisture has led to concerns about potential positive feedbacks to climate change. This risk is particularly relevant at high latitudes, which have experienced pronounced warming and where thawing permafrost could potentially liberate large amounts of labile carbon over the next 100 years. However, global models disagree as to the magnitude and spatial distribution of emissions, due to uncertainties in wetland area and emissions per unit area and a scarcity of in situ observations. Recent intensive field campaigns across the West Siberian Lowland (WSL) make this an ideal region over which to assess the perPublished by Copernicus Publications on behalf of the European Geosciences Union. T. J. Bohn et al.: Intercomparison of wetland methane emissions modelsformance of large-scale process-based wetland models in a high-latitude environment. Here we present the results of a follow-up to the Wetland and Wetland CH 4 Intercomparison of Models Project (WETCHIMP), focused on the West Siberian Lowland (WETCHIMP-WSL). We assessed 21 models and 5 inversions over this domain in terms of total CH 4 emissions, simulated wetland areas, and CH 4 fluxes per unit wetland area and compared these results to an intensive in situ CH 4 flux data set, several wetland maps, and two satellite surface water products. We found that (a) despite the large scatter of individual estimates, 12-year mean estimates of annual total emissions over the WSL from forward models (5.34 ± 0.54 Tg CH 4 yr −1 ), inversions (6.06 ± 1.22 Tg CH 4 yr −1 ), and in situ observations (3.91 ± 1.29 Tg CH 4 yr −1 ) largely agreed; (b) forward models using surface water products alone to estimate wetland areas suffered from severe biases in CH 4 emissions; (c) the interannual time series of models that lacked either soil thermal physics appropriate to the high latitudes or realistic emissions from unsaturated peatlands tended to be dominated by a single environmental driver (inundation or air temperature), unlike those of inversions and more sophisticated forward models; (d) differences in biogeochemical schemes across models had relatively smaller influence over performance; and (e) multiyear or multidecade observational records are crucial for evaluating models' responses to long-term climate change.

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Regional methane emission from West Siberia mire landscapes

Cited by 100 publications

References 21 publications

The global methane budget 2000–2012

The global methane budget 2000–2012

Estimating wetland methane emissions from the northern high latitudes from 1990 to 2009 using artificial neural networks

WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia

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