Wetland Emissions Research Articles

The Global Methane Budget 2000–2017

Abstract. Understanding and quantifying the global methane (CH4) budget is important for assessing realistic pathways to mitigate climate change. Atmospheric emissions and concentrations of CH4 continue to increase, making CH4 the second most important human-influenced greenhouse gas in terms of climate forcing, after carbon dioxide (CO2). The relative importance of CH4 compared to CO2 depends on its shorter atmospheric lifetime, stronger warming potential, and variations in atmospheric growth rate over the past decade, the causes of which are still debated. Two major challenges in reducing uncertainties in the atmospheric growth rate arise from the variety of geographically overlapping CH4 sources and from the destruction of CH4 by short-lived hydroxyl radicals (OH). To address these challenges, we have established a consortium of multidisciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate new research aimed at improving and regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paper dedicated to the decadal methane budget, integrating results of top-down studies (atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up estimates (including process-based models for estimating land surface emissions and atmospheric chemistry, inventories of anthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated by atmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximum estimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or ∼ 60 % is attributed to anthropogenic sources, that is emissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is 29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009), and 24 Tg CH4 yr−1 larger than the one reported in the previous budget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4 emissions have been tracking the warmest scenarios assessed by the Intergovernmental Panel on Climate Change. Bottom-up methods suggest almost 30 % larger global emissions (737 Tg CH4 yr−1, range 594–881) than top-down inversion methods. Indeed, bottom-up estimates for natural sources such as natural wetlands, other inland water systems, and geological sources are higher than top-down estimates. The atmospheric constraints on the top-down budget suggest that at least some of these bottom-up emissions are overestimated. The latitudinal distribution of atmospheric observation-based emissions indicates a predominance of tropical emissions (∼ 65 % of the global budget, < 30∘ N) compared to mid-latitudes (∼ 30 %, 30–60∘ N) and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methane budget is attributable to natural emissions, especially those from wetlands and other inland waters. Some of our global source estimates are smaller than those in previously published budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due to improved partition wetlands and other inland waters. Emissions from geological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overall discrepancy between bottom-up and top-down estimates has been reduced by only 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methane budget include (i) a global, high-resolution map of water-saturated soils and inundated areas emitting methane based on a robust classification of different types of emitting habitats; (ii) further development of process-based models for inland-water emissions; (iii) intensification of methane observations at local scales (e.g., FLUXNET-CH4 measurements) and urban-scale monitoring to constrain bottom-up land surface models, and at regional scales (surface networks and satellites) to constrain atmospheric inversions; (iv) improvements of transport models and the representation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/or co-emitted species such as ethane to improve source partitioning. The data presented here can be downloaded from https://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from the Global Carbon Project.

Investigating Wetland and Nonwetland Soil Methane Emissions and Sinks Across the Contiguous United States Using a Land Surface Model

AbstractWe estimated the distribution of CH4 emissions and sinks from wetlands (including freshwater and coastal wetlands) and nonwetland (including wet and dry soils) with a newly developed vertically resolved soil CH4 model, integrated into a global land surface model (ISAM). We calibrated and tested this integrated model with CH4 observations at test sites in the Contiguous United States (CONUS). ISAM is applied across the CONUS to estimate CH4 emissions and sinks given both recent past observed climate and wetland extent, and future climate and wetland extent driven by two scenarios, RCP4.5 and RCP8.5. Estimated net CH4 emissions for the 2000s are 13.8 TgCH4 yr−1, mostly from wetland soils. Estimated net emissions under RCP4.5 and RCP8.5 are 30% and 64% higher, respectively, in the 2090s than in the 2000s due to (1) higher temperature and seasonal wetland extent (driven by higher precipitation in the climate scenarios), which increase modeled methanogenic activity more than methanotrophic activity in soils and (2) altered transport in the soil column and exchange with the atmosphere by modeled transport processes (diffusion, ebullition, and aerenchyma transport). Nonwetland soils emit CH4 (1.4 TgCH4 yr−1) in some areas and take up CH4 (−2.9 TgCH4 yr−1) in other areas, resulting in a net estimated sink for the 2000s; the net nonwetland soil sink increases by 15% and 46% by the 2090s under RCP4.5 and RCP8.5, respectively, mainly due to drier soil conditions, which enhances methanotrophic activity and oxidation of CH4 diffused into soil from a future atmosphere with higher CH4 concentration.

Sesquiterpenes dominate monoterpenes in northern wetland emissions

Abstract. We have studied biogenic volatile organic compound (BVOC) emissions and their ambient concentrations at a sub-Arctic wetland (Lompolojänkkä, Finland), which is an open, nutrient-rich sedge fen and a part of the Pallas-Sodankylä Global Atmosphere Watch (GAW) station. Measurements were conducted during the growing season in 2018 using an in situ thermal-desorption–gas-chromatograph–mass-spectrometer (TD-GC-MS). Earlier studies have shown that isoprene is emitted from boreal wetlands, and it also turned out to be the most abundant compound in the current study. Monoterpene (MT) emissions were generally less than 10 % of the isoprene emissions (mean isoprene emission over the growing season, 44 µg m−2 h−1), but sesquiterpene (SQT) emissions were higher than MT emissions all the time. The main MTs emitted were α-pinene, 1,8-cineol, myrcene, limonene and 3Δ-carene. Of SQTs cadinene, β-cadinene and α-farnesene had the major contribution. During early growing season the SQT∕MT emission rate ratio was ∼10, but it became smaller as summer proceeded, being only ∼3 in July. Isoprene, MT and SQT emissions were exponentially dependent on temperature (correlation coefficients (R2) 0.75, 0.66 and 0.52, respectively). Isoprene emission rates were also found to be exponentially correlated with the gross primary production of CO2 (R2=0.85 in July). Even with the higher emissions from the wetland, ambient air concentrations of isoprene were on average > 100, > 10 and > 6 times lower than MT concentrations in May, June and July, respectively. This indicates that wetland was not the only source affecting atmospheric concentrations at the site, but surrounding coniferous forests, which are high MT emitters, contribute as well. Daily mean MT concentrations had high negative exponential correlation (R2=0.96) with daily mean ozone concentrations indicating that vegetation emissions can be a significant chemical sink of ozone in this sub-Arctic area.

Uncertainty Quantification of Global Net Methane Emissions From Terrestrial Ecosystems Using a Mechanistically Based Biogeochemistry Model

AbstractQuantification of methane (CH4) emissions from wetlands and its sinks from uplands is still fraught with large uncertainties. Here, a methane biogeochemistry model was revised, parameterized, and verified for various wetland ecosystems across the globe. The model was then extrapolated to the global scale to quantify the uncertainty induced from four different types of uncertainty sources including parameterization, wetland type distribution, wetland area distribution, and meteorological input. We found that global wetland emissions are 212 ± 62 and 212 ± 32 Tg CH4 year−1 (1Tg = 1012 g) due to uncertain parameters and wetland type distribution, respectively, during 2000–2012. Using two wetland distribution data sets and three sets of climate data, the model simulations indicated that the global wetland emissions range from 186 to 212 CH4 year−1 for the same period. The parameters were the most significant uncertainty source. After combining the global methane consumption in the range of −34 to −46 Tg CH4 year−1, we estimated that the global net land methane emissions are 149–176 Tg CH4 year−1 due to uncertain wetland distribution and meteorological input. Spatially, the northeast United States and Amazon were two hotspots of methane emission, while consumption hotspots were in the Eastern United States and eastern China. During 1950–2016, both wetland emissions and upland consumption increased during El Niño events and decreased during La Niña events. This study highlights the need for more in situ methane flux data, more accurate wetland type, and area distribution information to better constrain the model uncertainty.

Responses of soil CO2 and CH4 emissions to changing water table level in a coastal wetland

Global climate change and in particular sea level rise have resulted in water table level rise in the coastal wetland, which may alter the magnitude and direction of carbon flux. However, the degree to which different water table level affects soil CO2 and CH4 emissions remains uncertain in coastal wetland. Here, a soil microcosm experiment with five water table levels (−40, −30, −20, −10, 0 cm) was conducted in the Yellow River Delta, China. The water table level was controlled by manual. The soil CO2 and CH4 emissions of each water table levels were measured during 150-days incubation in 2018. Our results showed that water table level rise decreased soil CO2 emissions, while increased soil CH4 emissions. However, there was no significant difference in soil CO2 and CH4 emissions from −20 to −40 water table levels, respectively. In addition, water table level rise significant alter soil physical and chemical properties in the uppermost soil layer (0–10 cm) in coastal wetland, in particular soil moisture and salinity, which probably jointly affected soil CO2 and CH4 emissions. Furthermore, cumulative soil CH4 emission was positively significantly correlated to soil organic carbon and total carbon, suggesting that carbon component can supply energy and nutrients and benefit for soil CH4 production. Additionally, there was a significant relationship between cumulative soil CO2 emission and dissolved organic carbon, which indicated that CO2 was mainly contributed from dissolved organic carbon. Cumulative soil CO2 emission was significantly correlated with soil microbial biomass carbon, suggesting that microbial activity played an important role in CO2 emissions in coastal wetlands. Our results also indicate that water table level rise caused by sea level rise may contribute to the storage of soil organic carbon and produces a lower global warming potentials of CH4 and CO2 in the further climate change. Therefore, it is necessary to estimate the effect of hydrological, especially water table level on carbon cycles in coastal wetland when evaluating the climate–carbon feedback scenarios.

Reduced net methane emissions due to microbial methane oxidation in a warmer Arctic

Methane emissions from organic-rich soils in the Arctic have been extensively studied due to their potential to increase the atmospheric methane burden as permafrost thaws1–3. However, this methane source might have been overestimated without considering high-affinity methanotrophs (HAMs; methane-oxidizing bacteria) recently identified in Arctic mineral soils4–7. Herein we find that integrating the dynamics of HAMs and methanogens into a biogeochemistry model8–10 that includes permafrost soil organic carbon dynamics3 leads to the upland methane sink doubling (~5.5 Tg CH4 yr−1) north of 50 °N in simulations from 2000–2016. The increase is equivalent to at least half of the difference in net methane emissions estimated between process-based models and observation-based inversions11,12, and the revised estimates better match site-level and regional observations5,7,13–15. The new model projects doubled wetland methane emissions between 2017–2100 due to more accessible permafrost carbon16–18. However, most of the increase in wetland emissions is offset by a concordant increase in the upland sink, leading to only an 18% increase in net methane emission (from 29 to 35 Tg CH4 yr−1). The projected net methane emissions may decrease further due to different physiological responses between HAMs and methanogens in response to increasing temperature19,20. Models overestimate Arctic methane emissions compared to observations. Incorporating microbial dynamics into biogeochemistry models helps reconcile this discrepancy; high-affinity methanotrophs are an important part of the Arctic methane budget and double previous estimates of methane sinks.

Terrestrial methane emissions from the Last Glacial Maximum to the preindustrial period

Abstract. We investigate the changes in terrestrial natural methane emissions between the Last Glacial Maximum (LGM) and preindustrial (PI) periods by performing time-slice experiments with a methane-enabled version of MPI-ESM, the Max Planck Institute Earth System Model. We consider all natural sources of methane except for emissions from wild animals and geological sources, i.e. emissions from wetlands, fires, and termites. Changes are dominated by changes in tropical wetland emissions, with mid-to-high-latitude wetlands playing a secondary role, and all other natural sources being of minor importance. The emissions are determined by the interplay of vegetation productivity, a function of CO2 and temperature; source area size, affected by sea level and ice sheet extent; and the state of the West African monsoon, with increased emissions from northern Africa during strong monsoon phases. We show that it is possible to explain the difference in atmospheric methane between LGM and PI purely by changes in emissions. As emissions more than double between LGM and PI, changes in the atmospheric lifetime of CH4, as proposed in other studies, are not required.

Country-Scale Analysis of Methane Emissions with a High-Resolution Inverse Model Using GOSAT and Surface Observations

We employed a global high-resolution inverse model to optimize the CH4 emission using Greenhouse gas Observing Satellite (GOSAT) and surface observation data for a period from 2011–2017 for the two main source categories of anthropogenic and natural emissions. We used the Emission Database for Global Atmospheric Research (EDGAR v4.3.2) for anthropogenic methane emission and scaled them by country to match the national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC). Wetland and soil sink prior fluxes were simulated using the Vegetation Integrative Simulator of Trace gases (VISIT) model. Biomass burning prior fluxes were provided by the Global Fire Assimilation System (GFAS). We estimated a global total anthropogenic and natural methane emissions of 340.9 Tg CH4 yr−1 and 232.5 Tg CH4 yr−1, respectively. Country-scale analysis of the estimated anthropogenic emissions showed that all the top-emitting countries showed differences with their respective inventories to be within the uncertainty range of the inventories, confirming that the posterior anthropogenic emissions did not deviate from nationally reported values. Large countries, such as China, Russia, and the United States, had the mean estimated emission of 45.7 ± 8.6, 31.9 ± 7.8, and 29.8 ± 7.8 Tg CH4 yr−1, respectively. For natural wetland emissions, we estimated large emissions for Brazil (39.8 ± 12.4 Tg CH4 yr−1), the United States (25.9 ± 8.3 Tg CH4 yr−1), Russia (13.2 ± 9.3 Tg CH4 yr−1), India (12.3 ± 6.4 Tg CH4 yr−1), and Canada (12.2 ± 5.1 Tg CH4 yr−1). In both emission categories, the major emitting countries all had the model corrections to emissions within the uncertainty range of inventories. The advantages of the approach used in this study were: (1) use of high-resolution transport, useful for simulations near emission hotspots, (2) prior anthropogenic emissions adjusted to the UNFCCC reports, (3) combining surface and satellite observations, which improves the estimation of both natural and anthropogenic methane emissions over spatial scale of countries.

Investigation of the global methane budget over 1980–2017 using GFDL-AM4.1

Abstract. Changes in atmospheric methane abundance have implications for both chemistry and climate as methane is both a strong greenhouse gas and an important precursor for tropospheric ozone. A better understanding of the drivers of trends and variability in methane abundance over the recent past is therefore critical for building confidence in projections of future methane levels. In this work, the representation of methane in the atmospheric chemistry model AM4.1 is improved by optimizing total methane emissions (to an annual mean of 580±34 Tg yr−1) to match surface observations over 1980–2017. The simulations with optimized global emissions are in general able to capture the observed trend, variability, seasonal cycle, and latitudinal gradient of methane. Simulations with different emission adjustments suggest that increases in methane emissions (mainly from agriculture, energy, and waste sectors) balanced by increases in methane sinks (mainly due to increases in OH levels) lead to methane stabilization (with an imbalance of 5 Tg yr−1) during 1999–2006 and that increases in methane emissions (mainly from agriculture, energy, and waste sectors) combined with little change in sinks (despite small decreases in OH levels) during 2007–2012 lead to renewed growth in methane (with an imbalance of 14 Tg yr−1 for 2007–2017). Compared to 1999–2006, both methane emissions and sinks are greater (by 31 and 22 Tg yr−1, respectively) during 2007–2017. Our tagged tracer analysis indicates that anthropogenic sources (such as agriculture, energy, and waste sectors) are more likely major contributors to the renewed growth in methane after 2006. A sharp increase in wetland emissions (a likely scenario) with a concomitant sharp decrease in anthropogenic emissions (a less likely scenario), would be required starting in 2006 to drive the methane growth by wetland tracer. Simulations with varying OH levels indicate that a 1 % change in OH levels could lead to an annual mean difference of ∼4 Tg yr−1 in the optimized emissions and a 0.08-year difference in the estimated tropospheric methane lifetime. Continued increases in methane emissions along with decreases in tropospheric OH concentrations during 2008–2015 prolong methane's lifetime and therefore amplify the response of methane concentrations to emission changes. Uncertainties still exist in the partitioning of emissions among individual sources and regions.

Conversion of coastal wetlands, riparian wetlands, and peatlands increases greenhouse gas emissions: A global meta-analysis.

Land-use/land-cover change (LULCC) often results in degradation of natural wetlands and affects the dynamics of greenhouse gases (GHGs). However, the magnitude of changes in GHG emissions from wetlands undergoing various LULCC types remains unclear. We conducted a global meta-analysis with a database of 209 sites to examine the effects of LULCC types of constructed wetlands (CWs), croplands (CLs), aquaculture ponds (APs), drained wetlands (DWs), and pastures (PASs) on the variability in CO2 , CH4 , and N2 O emissions from the natural coastal wetlands, riparian wetlands, and peatlands. Our results showed that the natural wetlands were net sinks of atmospheric CO2 and net sources of CH4 and N2 O, exhibiting the capacity to mitigate greenhouse effects due to negative comprehensive global warming potentials (GWPs; -0.9 to -8.7 t CO2 -eqha-1 year-1 ). Relative to the natural wetlands, all LULCC types (except CWs from coastal wetlands) decreased the net CO2 uptake by 69.7%-456.6%, due to a higher increase in ecosystem respiration relative to slight changes in gross primary production. The CWs and APs significantly increased the CH4 emissions compared to those of the coastal wetlands. All LULCC types associated with the riparian wetlands significantly decreased the CH4 emissions. When the peatlands were converted to the PASs, the CH4 emissions significantly increased. The CLs, as well as DWs from peatlands, significantly increased the N2 O emissions in the natural wetlands. As a result, all LULCC types (except PASs from riparian wetlands) led to remarkably higher GWPs by 65.4%-2,948.8%, compared to those of the natural wetlands. The variability in GHG fluxes with LULCC was mainly sensitive to changes in soil water content, water table, salinity, soil nitrogen content, soil pH, and bulk density. This study highlights the significant role of LULCC in increasing comprehensive GHG emissions from global natural wetlands, and our results are useful for improving future models and manipulative experiments.

Spatial and temporal variations of the greenhouse gas emissions in coastal saline wetlands in southeastern China.

Coastal wetlands are crucial to global climate change due to their roles in modulating atmospheric concentrations of greenhouse gases (GHGs) (CO2, CH4, N2O). Under a warming climate, we investigated spatial and temporal variations of GHGs emissions over the coastal wetlands in southeastern China during 2012-2014. Five dominant land cover types in coastal wetlands have been considered, including the bare mud flat (BF), the Spartina alterniflora flats (SAF), the Suaeda glauca flats (SGF), the Phragmites australis flat (PAF), and the Scripus triqueter flat (STF). The results showed that the annual average CO2 fluxes were 305.8, 588.8, 370.2, and 136.5mgm-2h-1 from spring to winter. CH4 fluxes presented to be a sink in spring (- 0.02mgm-2h-1), and functioned as a source in the following seasons. Correlation analysis indicated that the surface air temperature and the cumulative precipitation could be two main factors that influenced the seasonal and inter-annual variations of GHGs emissions. In addition, we provided a regional budget of GHGs emissions that suggested the variations of GHGs emissions under a warming climate.

Assessment of the theoretical limit in instrumental detectability of northern high-latitude methane sources using <i>δ</i><sup>13</sup>C<sub>CH4</sub> atmospheric signals

Abstract. Recent efforts have brought together bottom-up quantification approaches (inventories and process-based models) and top-down approaches using regional observations of methane atmospheric concentrations through inverse modelling to better estimate the northern high-latitude methane sources. Nevertheless, for both approaches, the relatively small number of available observations in northern high-latitude regions leaves gaps in our understanding of the drivers and distributions of the different types of regional methane sources. Observations of methane isotope ratios, performed with instruments that are becoming increasingly affordable and accurate, could bring new insights on the contributions of methane sources and sinks. Here, we present the source signal that could be observed from methane isotopic 13CH4 measurements if high-resolution observations were available and thus what requirements should be fulfilled in future instrument deployments in terms of accuracy in order to constrain different emission categories. This theoretical study uses the regional chemistry-transport model CHIMERE driven by different scenarios of isotopic signatures for each regional methane source mix. It is found that if the current network of methane monitoring sites were equipped with instruments measuring the isotopic signal continuously, only sites that are significantly influenced by emission sources could differentiate regional emissions with a reasonable level of confidence. For example, wetland emissions require daily accuracies lower than 0.2 ‰ for most of the sites. Detecting East Siberian Arctic Shelf (ESAS) emissions requires accuracies lower than 0.05 ‰ at coastal Russian sites (even lower for other sites). Freshwater emissions would be detectable with an uncertainty lower than 0.1 ‰ for most continental sites. Except Yakutsk, Siberian sites require stringent uncertainty (lower than 0.05 ‰) to detect anthropogenic emissions from oil and gas or coal production. Remote sites such as Zeppelin, Summit, or Alert require a daily uncertainty below 0.05 ‰ to detect any regional sources. These limits vary with the hypothesis on isotopic signatures assigned to the different sources.

Seasonally Resolved Excess Urban Methane Emissions from the Baltimore/Washington, DC Metropolitan Region.

Urban areas are increasingly recognized as an important source of methane (CH4), but we have limited seasonally resolved observations of these regions. In this study, we quantify seasonal and annual urban CH4 emissions over the Baltimore, Maryland, and Washington, DC metropolitan regions. We use CH4 atmospheric observations from four tall tower stations and a Lagrangian particle dispersion model to simulate CH4 concentrations at these stations. We directly compare these simulations with observations and use a geostatistical inversion method to determine optimal emissions to match our observations. We use observations spanning four seasons and employ an ensemble approach considering multiple meteorological representations, emission inventories, and upwind CH4 values. Forward simulations in winter, spring, and fall underestimate observed atmospheric CH4 while in summer, simulations overestimate observations because of excess modeled wetland emissions. With ensemble geostatistical inversions, the optimized annual emissions in DC/Baltimore are 39 ± 9 Gg/month (1 δ), 2.0 ± 0.4 times higher than the ensemble mean of bottom-up emission inventories. We find a modest seasonal variability of urban CH4 emissions not captured in current inventories, with optimized summer emissions ∼41% lower than winter, broadly consistent with expectations if emissions are dominated by fugitive natural gas sources that correlate with natural gas usage.

Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations

Abstract. Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019).

Significant feedbacks of wetland methane release on climate change and the causes of their uncertainty

Emissions from wetlands are the single largest source of the atmospheric greenhouse gas (GHG) methane (CH4). This may increase in a warming climate, leading to a positive feedback on climate change. For the first time, we extend interactive wetland CH4 emissions schemes to include the recently quantified, significant process of CH4 transfer through tropical trees. We constrain the parameterisations using a multi-site flux study, and biogeochemical and inversion models. This provides an estimate and uncertainty range in contemporary, large-scale wetland emissions and their response to temperature. To assess the potential for future wetland CH4 emissions to feedback on climate, the schemes are forced with simulated climate change using a ‘pattern-scaling’ system, which links altered atmospheric radiative forcing to meteorology changes. We perform multiple simulations emulating 34 Earth System Models over different anthropogenic GHG emissions scenarios (RCPs). We provide a detailed assessment of the causes of uncertainty in predicting wetland CH4–climate feedback. Despite the constraints applied, uncertainty from wetland CH4 emission modelling is greater that from projected climate spread (under a given RCP). Limited knowledge of contemporary global wetland emissions restricts model calibration, producing the largest individual cause of wetland parameterisation uncertainty. Wetland feedback causes an additional temperature increase between 0.6% and 5.5% over the 21st century, with a feedback on climate ranging from 0.01 to 0.11 Wm−2 K−1. Wetland CH4 emissions amplify atmospheric CH4 increases by up to a further possible 25.4% in one simulation, and reduce remaining allowed anthropogenic emissions to maintain the RCP2.6 temperature threshold by 8.0% on average.

Long-term harvesting of reeds affects greenhouse gas emissions and microbial functional genes in alkaline wetlands

Reed (Phragmites australis) is dominant vegetation in alkaline wetlands that is harvested annually due to its economic value. To reveal the effects of harvesting reeds on the emission of greenhouse gases (GHG), the annual soil physicochemical characteristics and flux of GHGs in a reed wetland without harvesting (NHRW) and with harvesting (HRW) were measured. The results showed that after the harvesting of reeds, the total organic carbon (TOC) and total nitrogen (TN) significantly decreased, and soil temperature significantly increased. The annual cumulative N2O emissions decreased from 0.73 ± 0.20 kg ha−1 to −0.57 ± 0.49 kg ha−1 with the harvesting of reeds. The annual cumulative CH4 emissions also decreased from 561.88 ± 18.61 kg ha−1 to 183.13 ± 18.77 kg ha−1 with the harvesting of reeds. However, harvesting of reeds had only a limited influence on the annual cumulative CO2 emissions. A Pearson correlation analysis revealed that the CO2 and N2O emissions were more sensitive to temperature than the CH4 emissions. Both structural equation modeling (SEM) analysis and slurry incubation confirmed that higher temperatures offset the reduction of CO2 emissions after reed harvesting. Metagenomics showed that the abundance of functional genes involved in both GHG sink and source decreased with reed harvesting. This study presents a comprehensive view of reed harvesting on GHG emissions in alkaline wetlands, yielding new insight into the microbial response and offering a novel perspective on the potential impacts of wetland management.

Anthropogenic and Natural Factors Affecting Trends in Atmospheric Methane in Barrow, Alaska

This study examined the long-term trends in Arctic ambient methane (CH4) mixing ratios over 1986–2014 and investigated their potential causes. Significant correlations between carbon monoxide (CO) and CH4 in Barrow, Alaska (r = −0.59, p = 0.007) and Alert, Canada (r = −0.62, p = 0.004) with the strongest correlations occurring in April (r = −0.81, p = 0.000, and r = −0.80, p = 0.000) suggest local to global anthropogenic contributions to ambient CH4 during the cold months. Backward trajectories indicate a significant influence (27% of total trajectories) of local emissions from the Prudhoe Bay Oil Field on ambient CH4 in Barrow in winter, and this influence was dominated by other factors in summer. The mean CH4 wetland emission flux in Barrow over 1986–2014 was estimated to be 0.008 ± 0.002 µg m−2 s−1 while in Tiksi, Russia it was 0.010 µg m−2 s−1 over 2012–2016, which is comparable to the lower end of measurements in the literature. Note that in Barrow, there was a decrease in wetland flux from 0.0083 ± 0.002 µg m−2 s−1 over 1986–1998 to 0.0077 ± 0.002 µg m−2 s−1 from 1999–2006 followed by an increase to 0.0081 ± 0.002 µg m−2 s−1 over 2007–2014. Although the difference between the three values is not statistically significant due to small sample size, it is indicative of possible warm season wetland emissions contributing to the zero-growth period. Strong support for this hypothesis is that these changes are consistent with a concurrent drop in summertime temperature possibly causing a decrease in wetland emissions over 1998–2006 based on the statistically significant correlations between temperature and CH4 during August through November (r ~ 0.36–0.56, p = ≤0.05). In a warming climate, permafrost thawing can increase CH4 wetland emissions and also decrease wetlands making it a complex problem, and, hence, further study is needed to better understand the mechanisms driving long-term trends in Arctic CH4.

Effects of N Addition Frequency and Quantity on Hydrocotyle vulgaris Growth and Greenhouse Gas Emissions from Wetland Microcosms

(1) Background: Increased attention has been paid to atmospheric nitrogen (N) deposition caused by human activities. N deposition quantity has seriously affected plant productivity and greenhouse gas emissions in wetlands, but the effects of N deposition frequency remain unclear. (2) Methods: We assembled microcosms, which contained vegetative individuals (ramets) of Hydrocotyle vulgaris and soil and subjected them to three frequencies (N addition 1, 2, and 14 times during the experimental period) crossed with three quantities (5, 15, and 30 g N m−2 yr−1) for 90 days. (3) Results: The quantity of N addition significantly increased the root, stem biomass, and ramets number of H. vulgaris, but decreased the spike biomass. N addition quantity significantly promoted N2O emission and inhibited CH4 emission but had no significant effect on CO2 emission. The increasing frequency of N addition significantly promoted the root-to-shoot ratio and decreased N2O emission under high N addition quantity. (4) Conclusions: In conclusion, N addition alters the reproductive strategy of H. vulgaris and enhances its invasiveness, promoting N2O emission but not the CO2 equivalent of the H. vulgaris-soil system.

Effect of Nitrification on N2O Emissions and Their Environmental Factors in Saline-alkali Wetlands

Wetlands are important sources and sinks for N2O. Exploring the role of N2O emissions in saline-alkali wetlands has great significance in understanding the nitrification mechanism of N2O production and assessing the role of saline-alkali wetlands in the greenhouse effect. The present study examined the N2O fluxes and environmental factors of a typical Zhalong reed wetland during the growing season. The results suggested that the N2O fluxes tended to decrease in volatility, with the highest value in mid-July. The mean flux of N2O was (37.49±15.75) μg·(m2·h)-1, indicating that the typical Zhalong reed wetland was a source of N2O. The N2O fluxes exhibited a significantly positive correlation with soil temperature at different depths (P<0.05), and the impact of the upper soil temperature on N2O flux was higher than that of deep soil. In the flooding period, the relationship between N2O fluxes and water table depth was negatively correlated (P<0.05). Meanwhile, the TOC and TN contents were lower, and the N2O flux was significantly positively correlated with the NH4+-N content in the 0-40 cm soil layer (P<0.05), but it was not related to NO3--N content. Nitrification was stronger than denitrification. There was a significant positive correlation between ammonia-oxidizing bacterial activity and soil temperature in 0-20 cm layer (P<0.01). Additionally, the activity of ammonia-oxidizing bacteria also presented significantly positive linear correlation with the N2O fluxes (P<0.001), which indicated that the release of N2O in saline-alkali wetlands was greatly affected by nitrification.

Attribution of recent increases in atmospheric methane through 3-D inverse modelling

Abstract. The atmospheric methane (CH4) growth rate has varied considerably in recent decades. Unexplained renewed growth after 2006 followed 7 years of stagnation and coincided with an isotopic trend toward CH4 more depleted in 13C, suggesting changes in sources and/or sinks. Using surface observations of both CH4 and the relative change of isotopologue ratio (δ13CH4) to constrain a global 3-D chemical transport model (CTM), we have performed a synthesis inversion for source and sink attribution. Our method extends on previous studies by providing monthly and regional attribution of emissions from six different sectors and changes in atmospheric sinks for the extended 2003–2015 period. Regional evaluation of the model CH4 tracer with independent column observations from the Greenhouse Gases Observing Satellite (GOSAT) shows improved performance when using posterior fluxes (R=0.94–0.96, RMSE =8.3–16.5 ppb), relative to prior fluxes (R=0.60–0.92, RMSE =48.6–64.6 ppb). Further independent validation with data from the Total Carbon Column Observing Network (TCCON) shows a similar improvement in the posterior fluxes (R=0.87, RMSE =18.8 ppb) compared to the prior fluxes (R=0.69, RMSE =55.9 ppb). Based on these improved posterior fluxes, the inversion results suggest the most likely cause of the renewed methane growth is a post-2007 1.8±0.4 % decrease in mean OH, a 12.9±2.7 % increase in energy sector emissions, mainly from Africa–Middle East and southern Asia–Oceania, and a 2.6±1.8 % increase in wetland emissions, mainly from northern Eurasia. The posterior wetland flux increases are in general agreement with bottom-up estimates, but the energy sector growth is greater than estimated by bottom-up methods. The model results are consistent across a range of sensitivity analyses. When forced to assume a constant (annually repeating) OH distribution, the inversion requires a greater increase in energy sector (13.6±2.7 %) and wetland (3.6±1.8 %) emissions and an 11.5±3.8 % decrease in biomass burning emissions. Assuming no prior trend in sources and sinks slightly reduces the posterior growth rate in energy sector and wetland emissions and further increases the magnitude of the negative OH trend. We find that possible tropospheric Cl variations do not influence δ13CH4 and CH4 trends, although we suggest further work on Cl variability is required to fully diagnose this contribution. While the study provides quantitative insight into possible emissions variations which may explain the observed trends, uncertainty in prior source and sink estimates and a paucity of δ13CH4 observations limit the robustness of the posterior estimates.