Global Wetland CH4 Emissions Research Articles

Global Wetland Methane Emissions From 2001 to 2020: Magnitude, Dynamics and Controls

AbstractThe large uncertainties in estimating CH4 emissions from wetland ecosystems, the leading natural source to the atmosphere, substantially hinder the quantification of the global CH4 budget. This study used the IBIS‐CH4 (Integrated BIosphere Simulator‐Methane) model, a process‐based model integrating microbial mechanisms associated with CH4 production and oxidation processes, to simulate global wetland CH4 emissions from 2001 to 2020. Initially, we employed the IBIS‐CH4 model to evaluate its performance across 26 diverse wetland sites worldwide. The results showed that the magnitude and seasonality of observed CH4 fluxes over various wetland sites were well reproduced. We then used this model to estimate the annual global wetland CH4 emissions from 2001 to 2020, averaging 152.67 Tg CH4 yr−1, with a range of 135.72–167.57 Tg CH4 yr−1. The estimated global wetland CH4 emissions are generally in agreement with the current bottom‐up estimates (117–256 Tg CH4 yr−1) and closely overlap with independent top‐down estimates (139–183 Tg CH4 yr−1). During 2001–2020, the estimated global wetland CH4 emissions initially showed an increasing trend, followed by a decline. The peak of CH4 emissions reached in 2010, coinciding with the peak of wetland area. The majority of global wetland CH4 emissions were concentrated in tropical regions, which exhibited a clear seasonality and had a peak in July. The impact of meteorological factors on wetland CH4 emissions was greater than that of leaf area index, indicating the importance of soil hydrothermal conditions on wetland CH4 emissions.

Identifying the main drivers of the spatiotemporal variations in wetland methane emissions during 2001–2020

Wetlands act as an important natural source of global methane (CH4). The emission rate of wetland CH4 is jointly affected by climate change, carbon dioxide (CO2) fertilization, and wetland distribution. In this study, we implemented a wetland CH4 emission module into the Yale Interactive Biosphere (YIBs) model to quantify the spatiotemporal variations of global wetland CH4 emissions in 2001–2020. Site-level validations showed that the YIBs model reasonably captures the seasonality and magnitude of CH4 emissions at 28 out of 33 sites with significantly positive correlations and low relative biases. On the global scale, the YIBs predicts an annual mean wetland CH4 emission of 147.5 Tg yr−1 in 2000–2017, very close to the estimate of 147.9 Tg yr−1 from the ensemble of 13 process-based models. Global wetland CH4 emissions showed a positive trend of 0.74 Tg yr−2 in the past 2 decades, leading to an increase of 7.4 Tg yr−1 (5.2%) in 2008–2017 than 2000–2009. Climate change and CO2 fertilization accounted for over 70% of global wetland CH4 emission changes. Among them, the impact of CO2 grew steadily and became the dominant factor after the year 2008. The most significant changes in wetland CH4 emissions were located in the tropical regions following the perturbations in temperature that drives the ecosystem productivity. We found limited changes in CH4 emissions over high latitudes because of the moderate variations in wetland area fraction. The rise of wetland CH4 emissions poses an emerging threat to the global warming and likely escalates the tropospheric air pollutants.

Upscaling Wetland Methane Emissions From the FLUXNET‐CH4 Eddy Covariance Network (UpCH4 v1.0): Model Development, Network Assessment, and Budget Comparison

AbstractWetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data‐driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom‐up estimates of wetland CH4 emissions. Here, we develop a six‐predictor random forest upscaling model (UpCH4), trained on 119 site‐years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET‐CH4 Community Product. Network patterns in site‐level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash‐Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH4 emissions of 146 ± 43 TgCH4 y−1 for 2001–2018 which agrees closely with current bottom‐up land surface models (102–181 TgCH4 y−1) and overlaps with top‐down atmospheric inversion models (155–200 TgCH4 y−1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra‐tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid‐to‐arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253).

Observational constraints reduce model spread but not uncertainty in global wetland methane emission estimates.

The recent rise in atmospheric methane (CH4 ) concentrations accelerates climate change and offsets mitigation efforts. Although wetlands are the largest natural CH4 source, estimates of global wetland CH4 emissions vary widely among approaches taken by bottom-up (BU) process-based biogeochemical models and top-down (TD) atmospheric inversion methods. Here, we integrate in situ measurements, multi-model ensembles, and a machine learning upscaling product into the International Land Model Benchmarking systemto examine the relationship between wetland CH4 emission estimates and model performance. We find that using better-performing models identified by observational constraints reduces the spread of wetland CH4 emission estimates by 62% and 39% for BU- and TD-based approaches, respectively. However, global BU and TD CH4 emission estimate discrepancies increased by about 15% (from 31 to 36 TgCH4 year-1 ) when the top 20% models were used, although we consider this result moderately uncertain given the unevenly distributed global observations. Our analyses demonstrate that model performance ranking is subject to benchmark selection due to large inter-site variability, highlighting the importance of expanding coverage of benchmark sites to diverse environmental conditions. We encourage future development of wetland CH4 models to move beyond static benchmarking and focus on evaluating site-specific and ecosystem-specific variabilities inferred from observations.

Satellite Constraints on the Latitudinal Distribution and Temperature Sensitivity of Wetland Methane Emissions

AbstractWetland methane (CH4) emissions comprise about one‐third of the global CH4 source. The latitudinal distribution and climate sensitivity of wetland CH4 fluxes are the key determinants of the global CH4‐climate feedback. However, large differences exist between bottom‐up estimates, informed by ground‐based flux measurements, and top‐down estimates derived from spaceborne total column CH4. Despite the extensive coverage of satellite CH4 concentration observations, challenges remain with using top‐down estimates to test bottom‐up models, mainly because of the uncertainties in the satellite retrievals, the model representation errors, the variable prior emissions, and the confounding role of the posterior error covariance structures. Here, we use satellite‐based top‐down CH4 flux estimates (2010–2012) to test and refine 42 bottom‐up estimates of wetland emissions that use a range of hypothesized wetland extents and process controls. Our comparison between bottom‐up models and satellite‐based fluxes innovatively accounts for cross‐correlations and spatial uncertainties typically found in top‐down inverse estimates, such that only the information from satellite observations and the atmospheric transport model is kept as a constraint. We present a satellite‐constrained wetland CH4 ensemble product derived from assembling the highest‐performance bottom‐up models, which estimates global wetland CH4 emissions of 148 (117–189, 5th–95th percentile) Tg CH4 yr−1. We find that tropical wetland emissions contribute 72% (63%–85%) to the global wetland total. We also find that a lower‐than‐expected temperature sensitivity agrees better with atmospheric CH4 measurements. Overall, our approach demonstrates the potential for using satellites to quantitatively refine bottom‐up wetland CH4 emission estimates, their latitudinal distributions, and their sensitivity to climate.

Evaluation of CH4MOD<sub>wetland</sub> and Terrestrial Ecosystem Model (TEM) used to estimate global CH<sub>4</sub> emissions from natural wetlands

Abstract. Wetlands are the largest and most uncertain natural sources of atmospheric methane (CH4). Several process-based models have been developed to quantify the magnitude and estimate spatial and temporal variations in CH4 emissions from global wetlands. Reliable models are required to estimate global wetland CH4 emissions. This study aimed to test two process-based models, CH4MODwetland and Terrestrial Ecosystem Model (TEM), against the CH4 flux measurements of marsh, swamp, peatland and coastal wetland sites across the world; specifically, model accuracy and generality were evaluated for different wetland types and in different continents, and then the global CH4 emissions from 2000 to 2010 were estimated. Both models showed similar high correlations with the observed seasonal/annual total CH4 emissions, and the regression of the observed versus computed total seasonal/annual CH4 emissions resulted in R2 values of 0.81 and 0.68 for CH4MODwetland and TEM, respectively. The CH4MODwetland produced accurate predictions for marshes, peatlands, swamps and coastal wetlands, with model efficiency (EF) values of 0.22, 0.52, 0.13 and 0.72, respectively. TEM produced good predictions for peatlands and swamps, with EF values of 0.69 and 0.74, respectively, but it could not accurately simulate marshes and coastal wetlands (EF <0). There was a good correlation between the simulated CH4 fluxes and the observed values on most continents. However, CH4MODwetland showed no correlation with the observed values in South America and Africa. TEM showed no correlation with the observations in Europe. The global CH4 emissions for the period 2000–2010 were estimated to be 105.31 ± 2.72 Tg yr−1 by CH4MODwetland and 134.31 ± 0.84 Tg yr−1 by TEM. Both models simulated a similar spatial distribution of CH4 emissions globally and on different continents. Marshes contribute 36 %–39 % of global CH4 emissions. Lakes/rivers and swamps are the second and third greatest contributors, respectively. Other wetland types account for only approximately 20 % of global emissions. Based on the model applicability, if we use the more accurate model, i.e., the one that performs best as evidenced by a higher model efficiency and a lower model bias, to estimate each continent and wetland type, we obtain a new assessment of 116.99–124.74 Tg yr−1 for the global CH4 emissions for the period 2000–2010. Our results imply that performance at a global scale may conceal model uncertainty. Efforts should be made to improve model accuracy for different wetland types and regions, particularly hotspot regions, to reduce the uncertainty in global assessments.

Global wetland contribution to 2000–2012 atmospheric methane growth rate dynamics

Increasing atmospheric methane (CH4) concentrations have contributed to approximately 20% of anthropogenic climate change. Despite the importance of CH4 as a greenhouse gas, its atmospheric growth rate and dynamics over the past two decades, which include a stabilization period (1999–2006), followed by renewed growth starting in 2007, remain poorly understood. We provide an updated estimate of CH4 emissions from wetlands, the largest natural global CH4 source, for 2000–2012 using an ensemble of biogeochemical models constrained with remote sensing surface inundation and inventory-based wetland area data. Between 2000–2012, boreal wetland CH4 emissions increased by 1.2 Tg yr−1 (−0.2–3.5 Tg yr−1), tropical emissions decreased by 0.9 Tg yr−1 (−3.2−1.1 Tg yr−1), yet globally, emissions remained unchanged at 184 ± 22 Tg yr−1. Changing air temperature was responsible for increasing high-latitude emissions whereas declines in low-latitude wetland area decreased tropical emissions; both dynamics are consistent with features of predicted centennial-scale climate change impacts on wetland CH4 emissions. Despite uncertainties in wetland area mapping, our study shows that global wetland CH4 emissions have not contributed significantly to the period of renewed atmospheric CH4 growth, and is consistent with findings from studies that indicate some combination of increasing fossil fuel and agriculture-related CH4 emissions, and a decrease in the atmospheric oxidative sink.

Emerging role of wetland methane emissions in driving 21st century climate change.

Wetland methane (CH4) emissions are the largest natural source in the global CH4 budget, contributing to roughly one third of total natural and anthropogenic emissions. As the second most important anthropogenic greenhouse gas in the atmosphere after CO2, CH4 is strongly associated with climate feedbacks. However, due to the paucity of data, wetland CH4 feedbacks were not fully assessed in the Intergovernmental Panel on Climate Change Fifth Assessment Report. The degree to which future expansion of wetlands and CH4 emissions will evolve and consequently drive climate feedbacks is thus a question of major concern. Here we present an ensemble estimate of wetland CH4 emissions driven by 38 general circulation models for the 21st century. We find that climate change-induced increases in boreal wetland extent and temperature-driven increases in tropical CH4 emissions will dominate anthropogenic CH4 emissions by 38 to 56% toward the end of the 21st century under the Representative Concentration Pathway (RCP2.6). Depending on scenarios, wetland CH4 feedbacks translate to an increase in additional global mean radiative forcing of 0.04 W·m-2 to 0.19 W·m-2 by the end of the 21st century. Under the "worst-case" RCP8.5 scenario, with no climate mitigation, boreal CH4 emissions are enhanced by 18.05 Tg to 41.69 Tg, due to thawing of inundated areas during the cold season (December to May) and rising temperature, while tropical CH4 emissions accelerate with a total increment of 48.36 Tg to 87.37 Tg by 2099. Our results suggest that climate mitigation policies must consider mitigation of wetland CH4 feedbacks to maintain average global warming below 2 °C.

Methane emissions from global wetlands: An assessment of the uncertainty associated with various wetland extent data sets

A wide range of estimates on global wetland methane (CH4) fluxes has been reported during the recent two decades. This gives rise to urgent needs to clarify and identify the uncertainty sources, and conclude a reconciled estimate for global CH4 fluxes from wetlands. Most estimates by using bottom-up approach rely on wetland data sets, but these data sets show largely inconsistent in terms of both wetland extent and spatiotemporal distribution. A quantitative assessment of uncertainties associated with these discrepancies among wetland data sets has not been well investigated yet. By comparing the five widely used global wetland data sets (GISS, GLWD, Kaplan, GIEMS and SWAMPS-GLWD), it this study, we found large differences in the wetland extent, ranging from 5.3 to 10.2 million km2, as well as their spatial and temporal distributions among the five data sets. These discrepancies in wetland data sets resulted in large bias in model-estimated global wetland CH4 emissions as simulated by using the Dynamic Land Ecosystem Model (DLEM). The model simulations indicated that the mean global wetland CH4 emissions during 2000–2007 were 177.2 ± 49.7 Tg CH4 yr−1, based on the five different data sets. The tropical regions contributed the largest portion of estimated CH4 emissions from global wetlands, but also had the largest discrepancy. Among six continents, the largest uncertainty was found in South America. Thus, the improved estimates of wetland extent and CH4 emissions in the tropical regions and South America would be a critical step toward an accurate estimate of global CH4 emissions. This uncertainty analysis also reveals an important need for our scientific community to generate a global scale wetland data set with higher spatial resolution and shorter time interval, by integrating multiple sources of field and satellite data with modeling approaches, for cross-scale extrapolation.

A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0)

Abstract. Wetland emissions remain one of the principal sources of uncertainty in the global atmospheric methane (CH4) budget, largely due to poorly constrained process controls on CH4 production in waterlogged soils. Process-based estimates of global wetland CH4 emissions and their associated uncertainties can provide crucial prior information for model-based top-down CH4 emission estimates. Here we construct a global wetland CH4 emission model ensemble for use in atmospheric chemical transport models (WetCHARTs version 1.0). Our 0.5° × 0.5° resolution model ensemble is based on satellite-derived surface water extent and precipitation reanalyses, nine heterotrophic respiration simulations (eight carbon cycle models and a data-constrained terrestrial carbon cycle analysis) and three temperature dependence parameterizations for the period 2009–2010; an extended ensemble subset based solely on precipitation and the data-constrained terrestrial carbon cycle analysis is derived for the period 2001–2015. We incorporate the mean of the full and extended model ensembles into GEOS-Chem and compare the model against surface measurements of atmospheric CH4; the model performance (site-level and zonal mean anomaly residuals) compares favourably against published wetland CH4 emissions scenarios. We find that uncertainties in carbon decomposition rates and the wetland extent together account for more than 80 % of the dominant uncertainty in the timing, magnitude and seasonal variability in wetland CH4 emissions, although uncertainty in the temperature CH4 : C dependence is a significant contributor to seasonal variations in mid-latitude wetland CH4 emissions. The combination of satellite, carbon cycle models and temperature dependence parameterizations provides a physically informed structural a priori uncertainty that is critical for top-down estimates of wetland CH4 fluxes. Specifically, our ensemble can provide enhanced information on the prior CH4 emission uncertainty and the error covariance structure, as well as a means for using posterior flux estimates and their uncertainties to quantitatively constrain the biogeochemical process controls of global wetland CH4 emissions.

Interannual variation in methane emissions from tropical wetlands triggered by repeated El Niño Southern Oscillation.

Methane (CH4 ) emissions from tropical wetlands contribute 60%-80% of global natural wetland CH4 emissions. Decreased wetland CH4 emissions can act as a negative feedback mechanism for future climate warming and vice versa. The impact of the El Niño-Southern Oscillation (ENSO) on CH4 emissions from wetlands remains poorly quantified at both regional and global scales, and El Niño events are expected to become more severe based on climate models' projections. We use a process-based model of global wetland CH4 emissions to investigate the impacts of the ENSO on CH4 emissions in tropical wetlands for the period from 1950 to 2012. The results show that CH4 emissions from tropical wetlands respond strongly to repeated ENSO events, with negative anomalies occurring during El Niño periods and with positive anomalies occurring during La Niña periods. An approximately 8-month time lag was detected between tropical wetland CH4 emissions and ENSO events, which was caused by the combined time lag effects of ENSO events on precipitation and temperature over tropical wetlands. The ENSO can explain 49% of interannual variations for tropical wetland CH4 emissions. Furthermore, relative to neutral years, changes in temperature have much stronger effects on tropical wetland CH4 emissions than the changes in precipitation during ENSO periods. The occurrence of several El Niño events contributed to a lower decadal mean growth rate in atmospheric CH4 concentrations throughout the 1980s and 1990s and to stable atmospheric CH4 concentrations from 1999 to 2006, resulting in negative feedback to global warming.

Estimating global natural wetland methane emissions using process modelling: spatio‐temporal patterns and contributions to atmospheric methane fluctuations

AbstractAimThe fluctuations of atmospheric methane (CH4) that have occurred in recent decades are not fully understood, particularly with regard to the contribution from wetlands. The application of spatially explicit parameters has been suggested as an effective method for reducing uncertainties in bottom‐up approaches to wetland CH4 emissions, but has not been included in recent studies. Our goal was to estimate spatio‐temporal patterns of global wetland CH4 emissions using a process model and then to identify the contribution of wetland emissions to atmospheric CH4 fluctuations.LocationGlobal.MethodsA process‐based model integrated with full descriptions of methanogenesis (TRIPLEX‐GHG) was used to simulate global wetland CH4 emissions.ResultsGlobal annual wetland CH4 emissions ranged from 209 to 245 Tg CH4 year−1 between 1901 and 2012, with peaks occurring in 1991 and 2012. There is a decreasing trend between 1990 and 2010 with a rate of approximately 0.48 Tg CH4 year−1, which was largely caused by emissions from tropical wetlands showing a decreasing trend of 0.44 Tg CH4 year−1 since the 1970s. Emissions from tropical, temperate and high‐latitude wetlands comprised 59, 26 and 15% of global emissions, respectively.Main conclusionGlobal wetland CH4 emissions, the interannual variability of which was primary controlled by tropical wetlands, partially drive the atmospheric CH4 burden. The stable to decreasing trend in wetland CH4 emissions, a result of a balance of emissions from tropical and extratropical wetlands, was a particular factor in slowing the atmospheric CH4 growth rate during the 1990s. The rapid decrease in tropical wetland CH4 emissions that began in 2000 was supposed to offset the increase in anthropogenic emissions and resulted in a relatively stable level of atmospheric CH4 from 2000 to 2006. Increasing wetland CH4 emissions, particularly after 2010, should be an important contributor to the growth in atmospheric CH4 seen since 2007.

Physicochemical controls of diffusive methane fluxes in the Okavango Delta, Botswana

Atmospheric methane (CH4) is one of the three key greenhouse gases (GHGs) driving global climate change. The atmospheric concentration of CH4 has increased by about 150 % above pre-industrial levels of 400–700 ppb due to anthropogenic activities. Although tropical wetlands account for 50–60 % of the global wetland CH4 emissions, the biogeochemistry of these wetlands, including controls of CH4 emissions from the systems, is poorly understood compared to temperate wetlands. This has resulted in large inter-model variations of the magnitude and distribution of CH4 emission estimates from these tropical wetlands. A recent study in the Okavango Delta, Botswana, estimated diffusive CH4 flux at 1.8 ± 0.2 Tg year−1, accounting for 2.8 ± 0.3 % of the total CH4 emission from tropical wetlands. In this paper we present an assessment of relationships between diffusive CH4 flux rates and physicochemical variables in the overlying water column to identify and understand regulatory variables for the diffusive CH4 fluxes in the Delta. The results show that diffusive CH4 flux rates from the Delta seem to be controlled by a combination of physicochemical variables. Although site specific fluxes seem to be controlled by different combinations of factors, temperature was the primary predictor of CH4 flux rates at almost all the sampled habitats and sites in the Delta. Most physicochemical variables, especially in the permanent swamps, were correlated with temperature implying that their regulatory effect on diffusive CH4 fluxes could be modified by climate change feedback as well.

Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP)

Abstract. Global wetlands are believed to be climate sensitive, and are the largest natural emitters of methane (CH4). Increased wetland CH4 emissions could act as a positive feedback to future warming. The Wetland and Wetland CH4 Inter-comparison of Models Project (WETCHIMP) investigated our present ability to simulate large-scale wetland characteristics and corresponding CH4 emissions. To ensure inter-comparability, we used a common experimental protocol driving all models with the same climate and carbon dioxide (CO2) forcing datasets. The WETCHIMP experiments were conducted for model equilibrium states as well as transient simulations covering the last century. Sensitivity experiments investigated model response to changes in selected forcing inputs (precipitation, temperature, and atmospheric CO2 concentration). Ten models participated, covering the spectrum from simple to relatively complex, including models tailored either for regional or global simulations. The models also varied in methods to calculate wetland size and location, with some models simulating wetland area prognostically, while other models relied on remotely sensed inundation datasets, or an approach intermediate between the two. Four major conclusions emerged from the project. First, the suite of models demonstrate extensive disagreement in their simulations of wetland areal extent and CH4 emissions, in both space and time. Simple metrics of wetland area, such as the latitudinal gradient, show large variability, principally between models that use inundation dataset information and those that independently determine wetland area. Agreement between the models improves for zonally summed CH4 emissions, but large variation between the models remains. For annual global CH4 emissions, the models vary by ±40% of the all-model mean (190 Tg CH4 yr−1). Second, all models show a strong positive response to increased atmospheric CO2 concentrations (857 ppm) in both CH4 emissions and wetland area. In response to increasing global temperatures (+3.4 °C globally spatially uniform), on average, the models decreased wetland area and CH4 fluxes, primarily in the tropics, but the magnitude and sign of the response varied greatly. Models were least sensitive to increased global precipitation (+3.9 % globally spatially uniform) with a consistent small positive response in CH4 fluxes and wetland area. Results from the 20th century transient simulation show that interactions between climate forcings could have strong non-linear effects. Third, we presently do not have sufficient wetland methane observation datasets adequate to evaluate model fluxes at a spatial scale comparable to model grid cells (commonly 0.5°). This limitation severely restricts our ability to model global wetland CH4 emissions with confidence. Our simulated wetland extents are also difficult to evaluate due to extensive disagreements between wetland mapping and remotely sensed inundation datasets. Fourth, the large range in predicted CH4 emission rates leads to the conclusion that there is both substantial parameter and structural uncertainty in large-scale CH4 emission models, even after uncertainties in wetland areas are accounted for.

The El Niño-Southern Oscillation and wetland methane interannual variability

Global measurements of atmospheric methane (CH4) concentrations continue to show large interannual variability whose origin is only partly understood. Here we quantify the influence of the El Nino-Southern Oscillation (ENSO) on wetland CH4 emissions, which are thought to be the dominant contributor to interannual variability of the CH4 sources. We use a simple wetland CH4 model that captures variability in wetland extent and soil carbon to model the spatial and temporal dynamics of wetland CH4 emissions from 1950-2005 and compare these results to an ENSO index. We are able to explain a large fraction of the global and tropical variability in wetland CH4 emissions through correlation with the ENSO index. We find that repeated El Nino events throughout the 1980s and 1990s were a contributing factor towards reducing CH4 emissions and stabilizing atmospheric CH4 concentrations. An increase in emissions from the boreal region would likely strengthen the feedback between ENSO and interannual variability in global wetland CH4 emissions. Our analysis emphasizes that climate variability has a significant impact on wetland CH4 emissions, which should be taken into account when considering future trends in CH4 sources. Citation: Hodson, E. L., B. Poulter, N. E. Zimmermann, C. Prigent, and J. O. Kaplan (2011), The El Nino-Southern Oscillation and wetland methane interannual variability, Geophys. Res. Lett., 38, L08810, doi:10.1029/2011GL046861.

Quantifying wetland methane emissions with process-based models of different complexities

Abstract. Bubbling is an important pathway of methane emissions from wetland ecosystems. However the concentration-based threshold function approach in current biogeochemistry models of methane is not sufficient to represent the complex ebullition process. Here we revise an extant process-based biogeochemistry model, the Terrestrial Ecosystem Model into a multi-substance model (CH4, O2, CO2 and N2) to simulate methane production, oxidation, and transport (particularly ebullition) with different model complexities. When ebullition is modeled with a concentration-based threshold function and if the inhibition effect of oxygen on methane production and the competition for oxygen between methanotrophy and heterotrophic respiration are retained, the model becomes a two-substance system. Ignoring the role of oxygen, while still modeling ebullition with a concentration-based threshold function, reduces the model to a one-substance system. These models were tested through a group of sensitivity analyses using data from two temperate peatland sites in Michigan. We demonstrate that only the four-substance model with a pressure-based ebullition algorithm is able to capture the episodic emissions induced by a sudden decrease in atmospheric pressure or by a sudden drop in water table. All models captured the retardation effect on methane efflux from an increase in surface standing water which results from the inhibition of diffusion and the increase in rhizospheric oxidation. We conclude that to more accurately account for the effects of atmospheric pressure dynamics and standing water on methane effluxes, the multi-substance model with a pressure-based ebullition algorithm should be used in the future to quantify global wetland CH4 emissions. Further, to more accurately simulate the pore water gas concentrations and different pathways of methane transport, an exponential root distribution function should be used and the phase-related parameters should be treated as temperature dependent.

Sulfur pollution suppression of the wetland methane source in the 20th and 21st centuries.

Natural wetlands form the largest source of methane (CH(4)) to the atmosphere. Emission of this powerful greenhouse gas from wetlands is known to depend on climate, with increasing temperature and rainfall both expected to increase methane emissions. This study, combining our field and controlled environment manipulation studies in Europe and North America, reveals an additional control: an emergent pattern of increasing suppression of methane (CH(4)) emission from peatlands with increasing sulfate (SO(4)(2-)-S) deposition, within the range of global acid deposition. We apply a model of this relationship to demonstrate the potential effect of changes in global sulfate deposition from 1960 to 2080 on both northern peatland and global wetland CH(4) emissions. We estimate that sulfur pollution may currently counteract climate-induced growth in the wetland source, reducing CH(4) emissions by approximately 15 Tg or 8% smaller than it would be in the absence of global acid deposition. Our findings suggest that by 2030 sulfur pollution may be sufficient to reduce CH(4) emissions by 26 Tg or 15% of the total wetland source, a proportion as large as other components of the CH(4) budget that have until now received far greater attention. We conclude that documented increases in atmospheric CH(4) concentration since the late 19th century are likely due to factors other than the global warming of wetlands.