Wetland Emissions Research Articles

Sustained‐Flux Global Warming Potential Driven by Nitrogen Inflow and Hydroperiod in a Model of Great Lakes Coastal Wetlands

AbstractWetlands impact global warming by regulating the atmospheric exchange of greenhouse gases (GHGs), including carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O). We investigated GHG emissions in the Great Lakes coastal wetlands across various hydrologic, temperature, and nitrogen (N) inflow regimes using a process‐based simulation model. We found the emission of CH4, N2O, and sequestration of C (i.e., negative net ecosystem exchange, NEE) in our simulations were all positively related to water residence time and N inflow, primarily due to greater plant productivity and N uptake, which facilitated greater C and N cycling rates in the model. Water level scenarios also had an effect on GHG exchanges by moderating the transitions between aerobic and anaerobic conditions. Temperature effects on GHGs were minimal compared with other factors. The net sustained‐flux global warming potential (SGWP; i.e., sum SGWP of CH4, N2O, and NEE) of wetlands on 20‐year and 100‐year time horizons were both primarily driven by CH4 emissions and strongly controlled by the tradeoffs between CH4 emission and CO2 sequestration, with a negligible amount of simulated N2O emissions. Future research could include model enhancements to provide increased process‐level details on the aerobic‐anaerobic transitions or the direct effects of plants on mediating GHG exchanges. Field studies addressing the interaction of N inflows and water residence time at appropriately large scales are needed to test the complex interactions revealed by our modeling study. Our results highlight the previously under‐appreciated role of nitrogen and water residence time in modulating SGWP in coastal wetlands.

Impact of Spartina alterniflora invasion on soil bacterial community and associated greenhouse gas emission in the Jiuduansha wetland of China

Coastal wetlands are essential sources of greenhouse gases (GHGs) emission, and lots of them are invaded by Spartina alterniflora across different climate zones. We chose Jiuduansha wetland as a typical wetland ecosystem with minimal human activities to study the impacts and interactions between S. alterniflora invasion, soil functional microorganisms, and GHGs emission. Our findings indicated that in comparison to the mudflat and S. mariqueter habitat, the S. alterniflora invasion increased soil carbon dioxide (CO2) emission, which was highly positively related to aboveground biomass, soil organic carbon (SOC), and the ammonium‑nitrogen (NH4+-N) concentration, but negatively related to the nitrate‑nitrogen (NO3–-N) concentration. The relative abundances of soil C-decomposing bacteria increased in S. alterniflora habitat compared with S. mariqueter habitat. Compared with the P. australis habitat, S. alterniflora invasion reduced soil CO2 emission, which was negatively related to salinity. The relative abundances of soil C-fixing bacteria (phylum Chloroflexi) and functional genes (acsA-F and rbcL) decreased in S. alterniflora habitat. Moreover, the S. alterniflora invasion increased soil methane (CH4) emission compared with the S. mariqueter and P. australis habitats, which was positively related to aboveground biomass, SOC and NH4+-N concentration, and negatively related to the NO3–-N concentration. Besides, the relative abundances of CH4 oxidation functional genes were decreased in S. alterniflora habitat compared with the S. mariqueter and P. australis habitats. Meanwhile, the oxidation of CH4 to methanol was mainly regulated by mmoX gene at our study site. Thus, the soil CO2 and CH4 emissions after S. alterniflora invasion were regulated by soil environmental factors and soil C-fixing, C-decomposing, and CH4 oxidation functional microorganisms. Our results are helpful to better understand the mechanisms involved in the impacts of S. alterniflora invasions on GHG emissions in coastal wetlands.

Improved Constraints on Global Methane Emissions and Sinks Using δ 13C-CH4.

We study the drivers behind the global atmospheric methane (CH4) increase observed after 2006. Candidate emission and sink scenarios are constructed based on proposed hypotheses in the literature. These scenarios are simulated in the TM5 tracer transport model for 1984–2016 to produce three‐dimensional fields of CH4 and δ 13C‐CH4, which are compared with observations to test the competing hypotheses in the literature in one common model framework. We find that the fossil fuel (FF) CH4 emission trend from the Emissions Database for Global Atmospheric Research 4.3.2 inventory does not agree with observed δ 13C‐CH4. Increased FF CH4 emissions are unlikely to be the dominant driver for the post‐2006 global CH4 increase despite the possibility for a small FF emission increase. We also find that a significant decrease in the abundance of hydroxyl radicals (OH) cannot explain the post‐2006 global CH4 increase since it does not track the observed decrease in global mean δ 13C‐CH4. Different CH4 sinks have different fractionation factors for δ 13C‐CH4, thus we can investigate the uncertainty introduced by the reaction of CH4 with tropospheric chlorine (Cl), a CH4 sink whose abundance, spatial distribution, and temporal changes remain uncertain. Our results show that including or excluding tropospheric Cl as a 13 Tg/year CH4 sink in our model changes the magnitude of estimated fossil emissions by ∼20%. We also found that by using different wetland emissions based on a static versus a dynamic wetland area map, the partitioning between FF and microbial sources differs by 20 Tg/year, ∼12% of estimated fossil emissions.

Biogeochemistry of Mediterranean Wetlands: A Review about the Effects of Water-Level Fluctuations on Phosphorus Cycling and Greenhouse Gas Emissions

Although Mediterranean wetlands are characterized by extreme natural water level fluctuations in response to irregular precipitation patterns, global climate change is expected to amplify this pattern by shortening precipitation seasons and increasing the incidence of summer droughts in this area. As a consequence, a part of the lake sediment will be exposed to air-drying in dry years when the water table becomes low. This periodic sediment exposure to dry/wet cycles will likely affect biogeochemical processes. Unexpectedly, to date, few studies are focused on assessing the effects of water level fluctuations on the biogeochemistry of these ecosystems. In this review, we investigate the potential impacts of water level fluctuations on phosphorus dynamics and on greenhouse gases emissions in Mediterranean wetlands. Major drivers of global change, and specially water level fluctuations, will lead to the degradation of water quality in Mediterranean wetlands by increasing the availability of phosphorus concentration in the water column upon rewetting of dry sediment. CO2 fluxes are likely to be enhanced during desiccation, while inundation is likely to decrease cumulative CO2 emissions, as well as N2O emissions, although increasing CH4 emissions. However, there exists a complete gap of knowledge about the net effect of water level fluctuations induced by global change on greenhouse gases emission. Accordingly, further research is needed to assess whether the periodic exposure to dry–wet cycles, considering the extent and frequency of the cycles, will amplify the role of these especial ecosystems as a source of these gases and thereby act as a feedback mechanism for global warming. To conclude, it is pertinent to consider that a better understanding about the effect of water level fluctuations on the biogeochemistry of Mediterranean wetlands will help to predict how other freshwater ecosystems will respond.

Atmospheric trace gas trends obtained from FTIR column measurements in Toronto, Canada from 2002-2019

Total columns of C2H2, C2H6, CH4, CH3OH, CO, H2CO, HCl, HCN, HCOOH, HF, HNO3, N2O, NH3 and O3 were retrieved from 2002-2019 using a Fourier transform infrared (FTIR) spectrometer at the University of Toronto Atmospheric Observatory (TAO). Trends and enhancement events were determined by fitting trended Fourier series, and bootstrapping was used to identify the statistical significance. Trends from 2002 to 2019 (%/year, with 2σuncertainties) were found for C2H2 (−1.12 ± 0.30), C2H6 (−0.74 ± 0.73 from 2002–2008 and 1.19 ± 0.27 from 2009–2019), CH4 (0.26 ± 0.10 from 2002–2008 and 0.41 ± 0.03 from 2009–2019), CO (−0.90 ± 0.07), HCN (−0.51 ± 0.21), HCOOH (−2.15 ± 0.64), HF (0.59 ± 0.11), HNO3 (0.36 ± 0.13), N2O (0.28 ± 0.02), NH3 (3.56 ± 0.85), and O3 (0.28 ± 0.19 and −0.05 ± 0.07 for tropospheric and stratospheric columns, respectively). The GEOS-Chem chemical transport model showed that wetland emissions were the largest contributor to CH4 columns measured at TAO (average relative contribution of 31.7%), and that CH4 oxidation was a major source of CO (accounting for 30.9%).

Restored riverine wetlands in a headwater stream can simultaneously behave as sinks of N2O and hotspots of CH4 production

Wetlands can improve water quality, but they are also recognized as important sources of greenhouse gases (GHG) such as nitrous oxide (N2O) and methane (CH4). Emissions of these gases from wetland ecosystems, especially those in headwaters, are poorly understood. Here, we determined monthly concentrations of dissolved N2O and CH4 in a headwater stream of the Taihu Lake basin of China that contains both wetland and non-wetland reaches. Daily GHG dynamics in the wetland reach were also investigated. Riverine N2O and CH4 concentrations generally varied within 10–30 nmol L−1 and 0.1–1.5 μmol L−1, respectively. CH4 saturation levels in the wetland reach were about seven times higher than those in the non-wetland reach, but there was no difference in N2O saturation. In the wetland reach, saturation levels of CH4 peaked in July, coincident with a dip in N2O saturation to levels below its saturated solubility. This underscores that hotspots of CH4 production and sinks for N2O can occur occasionally in wetlands in mid-summer, when vegetative growth and microbial activities are high. Diurnal measurements indicated that CH4 saturation in water flows passing through the wetlands from midnight through the early morning can surge to levels 10 times higher than those detected at other times of the day. Simultaneously, saturation levels of N2O decreased by 75%, indicating a net consumption of N2O. Changes in nutrient supply determined by upstream inflows, as well as dissolved oxygen, pH, and other environmental factors mediated by the wetlands, correlate with the differentiated behavior of N2O and CH4 production in wetlands. Additional work will be necessary to confirm the roles of these factors in regulating GHG emissions in riverine wetlands.

Spatiotemporal Assessment of GHG Emissions and Nutrient Sequestration Linked to Agronutrient Runoff in Global Wetlands

AbstractWetlands play a key role in regulating global greenhouse gas (GHG) emissions but anthropogenic impacts on nutrients may severely alter this balance. Recent assessments indicate that almost 22% of the global wetland area may be affected by agricultural runoff. In this work, we developed and applied a dynamic mechanistic reaction network model of soil organic matter linking the carbon (C), nitrogen (N), and sulfur (S) cycles at 0.5° × 0.5° spatial resolution across the globe. The model was used to estimate GHG emissions and nutrient sequestration rates in wetlands, driven by environmental stressors including N, P, and S fertilization. Wetland annual GHG emissions are estimated to be 136 ± 12.5 Tg C‐CH4, 589 ± 45.8 Tg C‐CO2, and 0.3 ± 0.04 Tg N‐N2O; in contrast, C, N, and S annual sequestration rates are estimated to be 576 ± 88.1 Tg C, 20 ± 4.4 Tg N, and 7.4 ± 0.8 Tg S, between 2000 and 2017. N fertilization inputs were responsible for 13% N2O emissions in wetlands in the Northern Hemisphere, while tropical wetlands were major reservoirs for C, N, and S. Temperature, net primary productivity, and methanogenic microorganisms exert the major control on GHG emissions. Wetland CH4 and CO2 emissions were found to have a hysteretic relationship with seasonal soil temperature, but not N2O. A global‐scale assessment is pivotal for best nutrient management practices, reducing nutrient losses, and controlling gas emissions.

Critical inundation level for methane emissions from wetlands

Global methane (CH4) emissions have reached approximately 600 Tg per year, 20%–40% of which are from wetlands. Of the primary factors affecting these emissions, the water table level is among the most uncertain. Here we conduct a global meta-analysis of chamber and flux-tower observations of CH4 emissions and employ a novel mechanistic model to show that wetlands have maximum emissions at a critical level of inundation and discuss its origin. This maximum arises from an interplay between methanogenesis, methanotrophy, and transport, whose rates vary differently with the inundation level. The specific location of the critical water level above the soil surface may differ depending on wetland characteristics, for example temperature or the presence of macrophytes with aerenchyma. However, data suggest that globally a water level of about 50 cm is the most favorable to CH4 emissions. Keeping the water level away from this critical value could reduce methane emissions in human-made wetlands, which comprise at least one fifth of the global wetland area.

Corrigendum: Extrapolation and Uncertainty Evaluation of Carbon Dioxide and Methane Emissions in the Qinghai-Tibetan Plateau Wetlands Since the 1960s

Wetlands are important modulators of atmospheric greenhouse gas (GHGs) concentrations. However, little is known about the magnitudes and spatiotemporal patterns of GHG fluxes in wetlands on the Qinghai-Tibetan Plateau (QTP), the world’s largest and highest plateau. In this study, we measured soil temperature and the fluxes of carbon dioxide (CO2) and methane (CH4) in an alpine wetland on the QTP from April 2017 to April 2019 by the static chamber method, and from January 2017 to December 2017 by the eddy covariance (EC) method. The CO2 and CH4 emission measurements from both methods showed different relationships to soil temperature at different timescales (annual and seasonal). Based on such relationship patterns and soil temperature data (1960-2017), we extrapolated the CO2 and CH4 emissions of study site for the past 57 years: the mean CO2 emission rate was 1096.59 mg C m-2 h-1 on different measurement methods and timescales, with the range of the mean emission rate from 421.17 to 1754.99 mg C m-2 h-1, while the mean CH4 emission rate was 32.99 mg C m-2 h-1, with the ranges of the mean emission rate from 16.95 to 46.25 mg C m-2 h-1. The estimated regional CO2 and CH4 emissions from permanent wetlands on the QTP were 94.29 and 2.37 Tg C year-1, respectively. These results indicate that uncertainties caused by measuring method and timescale should be fully considered when extrapolating wetland GHG fluxes from local sites to the regional level. Moreover, the results of global warming potential showed that CO2 dominates the GHG balance of wetlands on the QTP.

Global methane budget and trend, 2010–2017: complementarity of inverse analyses using in situ (GLOBALVIEWplus CH<sub>4</sub> ObsPack) and satellite (GOSAT) observations

Abstract. We use satellite (GOSAT) and in situ (GLOBALVIEWplus CH4 ObsPack) observations of atmospheric methane in a joint global inversion of methane sources, sinks, and trends for the 2010–2017 period. The inversion is done by analytical solution to the Bayesian optimization problem, yielding closed-form estimates of information content to assess the consistency and complementarity (or redundancy) of the satellite and in situ data sets. We find that GOSAT and in situ observations are to a large extent complementary, with GOSAT providing a stronger overall constraint on the global methane distributions, but in situ observations being more important for northern midlatitudes and for relaxing global error correlations between methane emissions and the main methane sink (oxidation by OH radicals). The in-situ-only and the GOSAT-only inversions alone achieve 113 and 212 respective independent pieces of information (DOFS) for quantifying mean 2010–2017 anthropogenic emissions on 1009 global model grid elements, and respective DOFS of 67 and 122 for 2010–2017 emission trends. The joint GOSAT+ in situ inversion achieves DOFS of 262 and 161 for mean emissions and trends, respectively. Thus, the in situ data increase the global information content from the GOSAT-only inversion by 20 %–30 %. The in-situ-only and GOSAT-only inversions show consistent corrections to regional methane emissions but are less consistent in optimizing the global methane budget. The joint inversion finds that oil and gas emissions in the US and Canada are underestimated relative to the values reported by these countries to the United Nations Framework Convention on Climate Change (UNFCCC) and used here as prior estimates, whereas coal emissions in China are overestimated. Wetland emissions in North America are much lower than in the mean WetCHARTs inventory used as a prior estimate. Oil and gas emissions in the US increase over the 2010–2017 period but decrease in Canada and Europe. The joint inversion yields a global methane emission of 551 Tg a−1 averaged over 2010–2017 and a methane lifetime of 11.2 years against oxidation by tropospheric OH (86 % of the methane sink).

2010–2015 North American methane emissions, sectoral contributions, and trends: a high-resolution inversion of GOSAT observations of atmospheric methane

Abstract. We use 2010–2015 Greenhouse Gases Observing Satellite (GOSAT) observations of atmospheric methane columns over North America in a high-resolution inversion of methane emissions, including contributions from different sectors and their trends over the period. The inversion involves an analytical solution to the Bayesian optimization problem for a Gaussian mixture model (GMM) of the emission field with up to 0.5∘×0.625∘ resolution in concentrated source regions. The analytical solution provides a closed-form characterization of the information content from the inversion and facilitates the construction of a large ensemble of solutions exploring the effect of different uncertainties and assumptions in the inverse analysis. Prior estimates for the inversion include a gridded version of the Environmental Protection Agency (EPA) Inventory of US Greenhouse Gas Emissions and Sinks (GHGI) and the WetCHARTs model ensemble for wetlands. Our best estimate for mean 2010–2015 US anthropogenic emissions is 30.6 (range: 29.4–31.3) Tg a−1, slightly higher than the gridded EPA inventory (28.7 (26.4–36.2) Tg a−1). The main discrepancy is for the oil and gas production sectors, where we find higher emissions than the GHGI by 35 % and 22 %, respectively. The most recent version of the EPA GHGI revises downward its estimate of emissions from oil production, and we find that these are lower than our estimate by a factor of 2. Our best estimate of US wetland emissions is 10.2 (5.6–11.1) Tg a−1, on the low end of the prior WetCHARTs inventory uncertainty range (14.2 (3.3–32.4) Tg a−1), which calls for better understanding of these emissions. We find an increasing trend in US anthropogenic emissions over 2010–2015 of 0.4 % a−1, lower than previous GOSAT-based estimates but opposite to the decrease reported by the EPA GHGI. Most of this increase appears driven by unconventional oil and gas production in the eastern US. We also find that oil and gas production emissions in Mexico are higher than in the nationally reported inventory, though there is evidence for a 2010–2015 decrease in emissions from offshore oil production.

Attribution of the accelerating increase in atmospheric methane during 2010–2018 by inverse analysis of GOSAT observations

Abstract. We conduct a global inverse analysis of 2010–2018 GOSAT observations to better understand the factors controlling atmospheric methane and its accelerating increase over the 2010–2018 period. The inversion optimizes anthropogenic methane emissions and their 2010–2018 trends on a 4∘×5∘ grid, monthly regional wetland emissions, and annual hemispheric concentrations of tropospheric OH (the main sink of methane). We use an analytical solution to the Bayesian optimization problem that provides closed-form estimates of error covariances and information content for the solution. We verify our inversion results with independent methane observations from the TCCON and NOAA networks. Our inversion successfully reproduces the interannual variability of the methane growth rate inferred from NOAA background sites. We find that prior estimates of fuel-related emissions reported by individual countries to the United Nations are too high for China (coal) and Russia (oil and gas) and too low for Venezuela (oil and gas) and the US (oil and gas). We show large 2010–2018 increases in anthropogenic methane emissions over South Asia, tropical Africa, and Brazil, coincident with rapidly growing livestock populations in these regions. We do not find a significant trend in anthropogenic emissions over regions with high rates of production or use of fossil methane, including the US, Russia, and Europe. Our results indicate that the peak methane growth rates in 2014–2015 are driven by low OH concentrations (2014) and high fire emissions (2015), while strong emissions from tropical (Amazon and tropical Africa) and boreal (Eurasia) wetlands combined with increasing anthropogenic emissions drive high growth rates in 2016–2018. Our best estimate is that OH did not contribute significantly to the 2010–2018 methane trend other than the 2014 spike, though error correlation with global anthropogenic emissions limits confidence in this result.

Structure, diversity and potential metabolic activity of prokaryotic communities of Ebro Delta wetlands (Spain) as revealed by 16S rRNA gene amplicon sequencing

The monitoring of the structure and potential function of the prokaryotic assemblages of aquatic ecosystems can be used for the assessment of ecosystem health. In this work, we analysed by 16S rRNA gene amplicon massive sequencing the aquatic and sediment prokaryotic communities inhabiting three wetlands located in Ebro river Delta (Spain), which differ in their salinity and trophic status. We extracted the DNA from both matrices and sequenced the V4 region of the prokaryotic 16S rRNA gene by Illumina sequencing. The raw sequences obtained were processed and clustered in ZOTUs, which are sequences at 100% identity that were the basis for the structural and statistical analyses. Our results showed that water communities have less diversity and evenness than sediment communities. Moreover, statistical analyses showed that salinity is the main environmental factor that affects the structuration of sediment prokaryotic communities, while seasonality is also a very additional important environmental driver for aquatic communities. We also studied the relationship between the environmental factors and the potential metabolism of the aquatic and sediment prokaryotic communities, specifically for the main metabolic processes of the C-cycle. Focusing on sediment, we observed that methanogenic archaea are present not only in freshwater environments but also in the saline wetlands, though the observed methane emissions decreased with salinity. To explain this, we studied the potential activity of sulfate-reducing bacteria (SRB) and methanogenic archaea inferring the expression of genes dsrB and mcrA, which are gene markers for dissimilatory sulfate reduction and methanogenesis, respectively. We observed that, in saline wetlands, the potential activity of methanogens decreases because SRB bacteria outcompete them due to the higher sulfate availability enhancing sulfate-reduction. In the sediment communities of low salinity wetlands the relevance of methanogens is lower in terms of relative abundance, but the methane emissions are higher due to the lower sulfate availability. On the other hand, aquatic methanotrophic bacteria are very important in the net balance of methane emissions in Ebro Delta wetlands, as their relative abundance in the water column influences the amount of methane that is finally released to the atmosphere. In conclusion, our study deepens in the relationship between prokaryotic community structure and function in deltaic wetlands, giving a comprehensive overview of factors influencing the ecological health and certain processes, such as methane emissions, in deltaic systems.

Rain-fed pulses of methane from East Africa during 2018–2019 contributed to atmospheric growth rate

East Africa is a key location for wetland emissions of methane (CH4), driven by variations in rainfall that are in turn influenced by sea-surface temperature gradients over the Indian Ocean. Using satellite observations of CH4 and an atmospheric chemistry-transport model, we quantified East African CH4 emissions during 2018 and 2019 when there was 3-σ anomalous rainfall during the long rains (March–May) in 2018 and the short rains (October–December) in 2019. These rainfall anomalies resulted in CH4 emissions of 6.2 ± 0.3 Tg CH4 and 8.6 ± 0.3 Tg CH4, in each three month period, respectively, and represent a 10% and 37% increase compared to the equivalent season in the opposite year, when rainfall was close to the long-term seasonal mean. We find the additional short rains emissions were equivalent to over a quarter of the growth in global emissions in 2019, highlighting the disproportionate role of East Africa in the global CH4 budget.

Using satellite data to identify the methane emission controls of South Sudan's wetlands

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) provides observations of atmospheric methane (CH4) at an unprecedented combination of high spatial resolution and daily global coverage. Hu et al. (2018) reported unexpectedly large methane enhancements over South Sudan in these observations. Here we assess methane emissions from the wetlands of South Sudan using 2 years (December 2017–November 2019) of TROPOMI total column methane observations. We estimate annual wetland emissions of 7.4 ± 3.2 Tg yr−1, which agrees with the multiyear GOSAT inversions of Lunt et al. (2019) but is an order of magnitude larger than estimates from wetland process models. This disagreement may be explained by the underestimation (by up to 4 times) of inundation extent by the hydrological schemes used in those models. We investigate the seasonal cycle of the emissions and find the lowest emissions during the June–August season when the process models show the largest emissions. Using satellite-altimetry-based river water height measurements, we infer that this seasonal mismatch is likely due to a seasonal mismatch in inundation extent. In models, inundation extent is controlled by regional precipitation scaled to static wetland extent maps, whereas the actual inundation extent is driven by water inflow from rivers like the White Nile and the Sobat. We find the lowest emissions in the highest precipitation and lowest temperature season (June–August, JJA) when models estimate large emissions. In general, our emission estimates show better agreement in terms of both seasonal cycle and annual mean with model estimates that use a stronger temperature dependence. This suggests that temperature might be a stronger control for the South Sudan wetlands emissions than currently assumed by models. Our findings demonstrate the use of satellite instruments for quantifying emissions from inaccessible and uncertain tropical wetlands, providing clues for the improvement of process models and thereby improving our understanding of the currently uncertain contribution of wetlands to the global methane budget.

A pragmatic protocol for characterising errors in atmospheric inversions of methane emissions over Europe

This study aims at estimating errors to be accounted for in atmospheric inversions of methane (CH4) emissions at the European scale. Four types of errors are estimated in the concentration space over the model domain and at selected measurement sites. Furthermore, errors in emission inventories are estimated at country and source sector scales. A technically ready method is used, which is implemented by running a set of simulations of hourly CH4 mixing ratios for 2015 using two area-limited transport models at three horizontal resolutions with multiple data sets of emissions and boundary and initial conditions as inputs. The obtained error estimates provide insights into how these errors could be treated in an inverse modelling system for inverting CH4 emissions over Europe. The main results show that sources of transport errors may better be controlled alongside the emissions, which differs from usual inversion practices. The average total concentration error is estimated at 29 ppb. The assessed error of total CH4 emissions is 22% and emission errors are heterogeneous at sector (23–49%) and country scales (16–124%), with largest errors occurring in the waste sector due to uncertainties in activity data and emission factors and in Finland due to uncertainties in natural wetland emissions.

Exploring constraints on a wetland methane emission ensemble (WetCHARTs) using GOSAT observations

Abstract. Wetland emissions contribute the largest uncertainties to the current global atmospheric CH4 budget, and how these emissions will change under future climate scenarios is also still poorly understood. Bloom et al. (2017b) developed WetCHARTs, a simple, data-driven, ensemble-based model that produces estimates of CH4 wetland emissions constrained by observations of precipitation and temperature. This study performs the first detailed global and regional evaluation of the WetCHARTs CH4 emission model ensemble against 9 years of high-quality, validated atmospheric CH4 observations from GOSAT (the Greenhouse Gases Observing Satellite). A 3-D chemical transport model is used to estimate atmospheric CH4 mixing ratios based on the WetCHARTs emissions and other sources. Across all years and all ensemble members, the observed global seasonal-cycle amplitude is typically underestimated by WetCHARTs by −7.4 ppb, but the correlation coefficient of 0.83 shows that the seasonality is well-produced at a global scale. The Southern Hemisphere has less of a bias (−1.9 ppb) than the Northern Hemisphere (−9.3 ppb), and our findings show that it is typically the North Tropics where this bias is the worst (−11.9 ppb). We find that WetCHARTs generally performs well in reproducing the observed wetland CH4 seasonal cycle for the majority of wetland regions although, for some regions, regardless of the ensemble configuration, WetCHARTs does not reproduce the observed seasonal cycle well. In order to investigate this, we performed detailed analysis of some of the more challenging exemplar regions (Paraná River, Congo, Sudd and Yucatán). Our results show that certain ensemble members are more suited to specific regions, due to either deficiencies in the underlying data driving the model or complexities in representing the processes involved. In particular, incorrect definition of the wetland extent is found to be the most common reason for the discrepancy between the modelled and observed CH4 concentrations. The remaining driving data (i.e. heterotrophic respiration and temperature) are shown to also contribute to the mismatch with observations, with the details differing on a region-by-region basis but generally showing that some degree of temperature dependency is better than none. We conclude that the data-driven approach used by WetCHARTs is well-suited to producing a benchmark ensemble dataset against which to evaluate more complex process-based land surface models that explicitly model the hydrological behaviour of these complex wetland regions.

Active Methanotrophs in Suboxic Alpine Swamp Soils of the Qinghai-Tibetan Plateau.

Methanotrophs are the only biofilters for reducing the flux of global methane (CH4) emissions in water-logged wetlands. However, adaptation of aerobic methanotrophs to low concentrations of oxygen and nitrogen in typical swamps, such as that of the Qinghai–Tibetan Plateau, is poorly understood. In this study, we show that Methylobacter-like methanotrophs dominate methane oxidation and nitrogen fixation under suboxic conditions in alpine swamp soils. Following incubation with 13C-CH4 and 15N-N2 for 90 days under suboxic conditions with repeated flushing using an inert gas (i.e., argon), microbial carbon and nitrogen turnover was measured in swamp soils at different depths: 0–20 cm (top), 40–60 cm (intermediate), and 60–80 cm (deep). Results show detectable methane oxidation and nitrogen fixation in all three soil depths. In particular, labeled carbon was found in CO2 enrichment (13C-CO2), and soil organic carbon (13C-SOC), whereas labeled nitrogen (15N) was detected in soil organic nitrogen (SON). The highest values of labeled isotopes were found at intermediate soil depths. High-throughput amplicon sequencing and Sanger sequencing indicated the dominance of Methylobacter-like methanotrophs in swamp soils, which comprised 21.3–24.0% of the total bacterial sequences, as measured by 13C-DNA at day 90. These results demonstrate that aerobic methanotroph Methylobacter is the key player in suboxic methane oxidation and likely catalyzes nitrogen fixation in swamp wetland soils in the Qinghai–Tibetan Plateau.

Quantifying sources of Brazil's CH<sub>4</sub> emissions between 2010 and 2018 from satellite data

Abstract. Brazil's CH4 emissions over the period 2010–2018 were derived for the three main sectors of activity: anthropogenic, wetland and biomass burning. Our inverse modelling estimates were derived from GOSAT (Greenhouse gases Observing SATellite) satellite measurements of XCH4 combined with surface data from Ragged Point, Barbados, and the high-resolution regional atmospheric transport model NAME (Numerical Atmospheric-dispersion Modelling Environment). We find that Brazil's mean emissions over 2010–2018 are 33.6±3.6Tgyr-1, which are comprised of 19.0±2.6Tgyr-1 from anthropogenic (primarily related to agriculture and waste), 13.0±1.9Tgyr-1 from wetlands and 1.7±0.3Tgyr-1 from biomass burning sources. In addition, between the 2011–2013 and 2014–2018 periods, Brazil's mean emissions rose by 6.9±5.3Tgyr-1 and this increase may have contributed to the accelerated global methane growth rate observed during the latter period. We find that wetland emissions from the western Amazon increased during the start of the 2015–2016 El Niño by 3.7±2.7Tgyr-1 and this is likely driven by increased surface temperatures. We also find that our estimates of anthropogenic emissions are consistent with those reported by Brazil to the United Framework Convention on Climate Change. We show that satellite data are beneficial for constraining national-scale CH4 emissions, and, through a series of sensitivity studies and validation experiments using data not assimilated in the inversion, we demonstrate that (a) calibrated ground-based data are important to include alongside satellite data in a regional inversion and that (b) inversions must account for any offsets between the two data streams and their representations by models.

Extrapolation and Uncertainty Evaluation of Carbon Dioxide and Methane Emissions in the Qinghai-Tibetan Plateau Wetlands Since the 1960s

Wetlands are important modulators of atmospheric greenhouse gas (GHGs) concentrations. However, little is known about the magnitudes and spatiotemporal patterns of GHGs fluxes in wetlands on the Qinghai-Tibetan Plateau (QTP), the world’s largest and highest plateau. In this study, we measured soil temperature and the fluxes of carbon dioxide (CO2) and methane (CH4) in an alpine wetland on the QTP from April 2017 to April 2019 by the static chamber method, and from January 2017 to December 2017 by the eddy covariance (EC) method. The CO2 and CH4 emission measurements from both methods showed different relationships to soil temperature at different timescales (annual and seasonal). Based on such relationship patterns and soil temperature data (1960–2017), we extrapolated the CO2 and CH4 emissions of study site for the past 57 years: the mean CO2 emission rate was 91.38 mg C m–2 h–1 on different measurement methods and timescales, with the range of the mean emission rate from 35.10 to 146.25 mg C m–2 h–1, while the mean CH4 emission rate was 2.75 mg C m–2 h–1, with the ranges of the mean emission rate from 1.41 to 3.85 mg C m–2 h–1. The estimated regional CO2 and CH4 emissions from permanent wetlands on the QTP were 94.29 and 2.37 Tg C year–1, respectively. These results indicate that uncertainties caused by measuring method and timescale should be fully considered when extrapolating wetland GHGs fluxes from local sites to the regional level. Moreover, the results of global warming potential showed that CO2 dominates the GHG balance of wetlands on the QTP.