Spatiotemporal Methane Emission From Global Reservoirs

Johnson, Matthew S.; Matthews, E.; Bastviken, David; Deemer, Bridget R.; Du, Jinyang; Genovese, Vanessa

doi:10.1029/2021jg006305

Cited by 34 publications

(64 citation statements)

References 102 publications

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“…We constructed a new freshwater estimate of 79 Tg CH 4 yr −1 consisting of 27 Tg CH 4 yr −1 from rivers (Stanley et al., 2016) quoted in Saunois et al. (2020), 10 Tg CH 4 yr −1 from reservoirs (Johnson et al., 2021), and our new lake estimate of 42 Tg CH 4 yr −1 . This revised freshwater aquatic emission estimate reduces the Saunois et al.…”

Section: Comparison With Other Lake Ch4 Emission Estimatesmentioning

confidence: 99%

“…Where multiple flux observations were reported as single averages, we expanded the compilation to reflect each observation when possible (i.e., when individual observations were reported). Subsequently, data were filtered to exclude indirect measurements (i.e., acoustic methods) and those lacking the necessary information on the time of day and month of year of observation and flux pathway (i.e., diffusive or ebullitive) (Johnson et al, 2021). For the boreal lake data provided in Wik et al (2016) we removed systems identified as Beaver Ponds.…”

Section: Flux Compilation Augmentation Correctionmentioning

confidence: 99%

See 1 more Smart Citation

Methane Emission From Global Lakes: New Spatiotemporal Data and Observation‐Driven Modeling of Methane Dynamics Indicates Lower Emissions

Johnson

Matthews

et al. 2022

JGR Biogeosciences

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Lakes, defined as stable and non-flowing water bodies which are open to the atmosphere (USGS, 2018), are a potentially important source of the greenhouse gas methane (CH 4 ) to the atmosphere. However, estimates of lake emissions over large areas are very uncertain, and the spatiotemporal variability has not yet been fully considered in global estimates (Saunois et al., 2020). The first global estimate of CH 4 emission from lakes, published almost 50 years ago (Ehhalt, 1974) based on two lake measurements and a global lake area of 2.5 × 10 6 km 2 , reported that lakes may emit 1 to 25 Tg CH 4 yr −1 , the range reflecting different assumptions about the fraction of lakes emitting CH 4 (Table 1). A later study (Bastviken et al., 2004) based on flux measurements from 74 lake systems reported that open water portions of lakes emit 6-25 Tg CH 4 yr −1 (Table 1). Subsequent estimates, relying on data from ∼400 or more lake systems, reported 72 Tg CH 4 yr −1 from diffusion and ebullition (Bastviken Abstract Lakes have been highlighted as one of the largest natural sources of the greenhouse gas methane (CH 4 ) to the atmosphere. However, global estimates of lake CH 4 fluxes over the last 20 years exhibit widely different results ranging from 6 to 185 Tg CH 4 yr −1 , which is to a large extent driven by differences in lake areas and thaw season lengths used. This has generated uncertainty regarding both lake fluxes and the global CH 4 budget. This study constrains global lake water CH 4 emissions by using new information on lake area and distribution and CH 4 fluxes distinguished by major emission pathways; ecoclimatic lake type; satellite-derived ice-free emission period length; and diel-and temperature-related seasonal flux corrections. We produced gridded data sets at 0.25° latitude × 0.25° longitude spatial resolution, representing daily emission estimates over a full annual climatological cycle, appropriate for use in global CH 4 budget estimates, climate and Earth System Models, bottom-up biogeochemical models, and top-down inverse model simulations. Global lake CH 4 fluxes are 41.6 ± 18.3 Tg CH 4 yr −1 with approximately 50% of the flux contributed by tropical/subtropical lakes. Strong temperature-dependent flux seasonality and satellite-derived freeze/thaw dynamics limit emissions at high latitudes. The primary emission pathway for global annual lake fluxes is ebullition (23.4 Tg) followed by diffusion (14.1 Tg), ice-out and spring water-column turnover (3.1 Tg), and fall water-column turnover (1.0 Tg). These results represent a major contribution to reconciling differences between bottom-up and top-town estimates of inland aquatic system emissions in the global CH 4 budget.Plain Language Summary A greenhouse gas which contributes significantly to global warming is methane (CH 4 ). Atmospheric concentrations of CH 4 have more than doubled since the pre-industrial era primarily due to emissions from human activities. Inland waters (i.e., wetlands, lakes, rivers, and reservoirs) are significant CH 4 emitters yet stil...

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Section: Comparison With Other Lake Ch4 Emission Estimatesmentioning

confidence: 99%

Section: Flux Compilation Augmentation Correctionmentioning

confidence: 99%

Methane Emission From Global Lakes: New Spatiotemporal Data and Observation‐Driven Modeling of Methane Dynamics Indicates Lower Emissions

Johnson

Matthews

et al. 2022

JGR Biogeosciences

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“…emissions generally increase at lower latitudes (Barros et al, 2011), though more recent global syntheses with a similar spatial sampling bias reported no statistical difference between CH 4 emissions from tropical/subtropical vs. temperate reservoirs (Deemer et al, 2016;Johnson et al, 2021). One unique pathway by which CO 2 and CH 4 are emitted from many reservoirs is degassing (i.e., via turbines or spillways), which can account for over 50% of CH 4 emissions from reservoirs globally (Figure 3) (Harrison et al, 2021).…”

Section: Influence Of Inland Waterbody Types On Relative C Fluxesmentioning

confidence: 98%

“…This high productivity is associated with both a greater amount of autochthonous C preferred for CH 4 production (West et al, 2012) and low oxygen conditions following decomposition that promote CH 4 production. Research focused on CH 4 emissions from tropical reservoirs may bias these patterns as CH 4 emissions generally increase at lower latitudes (Barros et al, 2011), though more recent global syntheses with a similar spatial sampling bias reported no statistical difference between CH 4 emissions from tropical/subtropical vs. temperate reservoirs (Deemer et al, 2016; Johnson et al, 2021). One unique pathway by which CO 2 and CH 4 are emitted from many reservoirs is degassing (i.e., via turbines or spillways), which can account for over 50% of CH 4 emissions from reservoirs globally (Figure 3) (Harrison et al, 2021).…”

Section: Global C Fluxes In Inland Watersmentioning

confidence: 99%

Anthropogenically driven climate and landscape change effects on inland water carbon dynamics: What have we learned and where are we going?

Pilla

Griffiths

et al. 2022

Global Change Biology

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Inland waters serve as important hydrological connections between the terrestrial landscape and oceans but are often overlooked in global carbon (C) budgets and Earth System Models. Terrestrially derived C entering inland waters from the watershed can be transported to oceans but over 83% is either buried in sediments or emitted to the atmosphere before reaching oceans. Anthropogenic pressures such as climate and landscape changes are altering the magnitude of these C fluxes in inland waters. Here, we synthesize the most recent estimates of C fluxes and the differential contributions across inland waterbody types (rivers, streams, lakes, reservoirs, and ponds), including recent measurements that incorporate improved sampling methods, small waterbodies, and dried areas. Across all inland waters, we report a global C emission estimate of 4.40 Pg C/year (95% confidence interval: 3.95–4.85 Pg C/year), representing a 13% increase from the most recent estimate. We also review the mechanisms by which the most globally widespread anthropogenically driven climate and landscape changes influence inland water C fluxes. The majority of these drivers are expected to influence terrestrial C inputs to inland waters due to alterations in terrestrial C quality and quantity, hydrological pathways, and biogeochemical processing. We recommend four research priorities for the future study of anthropogenic alterations to inland water C fluxes: (1) before‐and‐after measurements of C fluxes associated with climate change events and landscape changes, (2) better quantification of C input from land, (3) improved assessment of spatial coverage and contributions of small inland waterbodies to C fluxes, and (4) integration of dried and drawdown areas to global C flux estimates. Improved measurements of inland water C fluxes and quantification of uncertainty in these estimates will be vital to understanding both terrestrial C losses and the “moving target” of inland water C emissions in response to rapid and complex anthropogenic pressures.

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“…Freshwater ecosystems emit large quantities of CH 4 to the atmosphere (currently estimated between 117 and 212 Tg CH 4 yr −1 ; Saunois et al, 2020). Within human-made reservoirs alone, ebullition rates can vary substantially in emissions, ranging from 1 to 1,000 mg CH 4 m −2 d −1 (Deemer et al, 2016) and up to 8.9 Tg CH 4 yr −1 (Johnson et al, 2021). Among the different types of freshwater CH 4 emissions, ebullition can make up anywhere from 0 to 99.6% of total emissions to the atmosphere (Deemer and Holgerson, 2021) and it is considered one of the most uncertain fluxes in both inland water and global CH 4 budgets (Wik et al, 2016;Saunois et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Iterative Forecasting Improves Near-Term Predictions of Methane Ebullition Rates

McClure

Thomas

Lofton

et al. 2021

Front. Environ. Sci.

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Near-term, ecological forecasting with iterative model refitting and uncertainty partitioning has great promise for improving our understanding of ecological processes and the predictive skill of ecological models, but to date has been infrequently applied to predict biogeochemical fluxes. Bubble fluxes of methane (CH4) from aquatic sediments to the atmosphere (ebullition) dominate freshwater greenhouse gas emissions, but it remains unknown how best to make robust near-term CH4 ebullition predictions using models. Near-term forecasting workflows have the potential to address several current challenges in predicting CH4 ebullition rates, including: development of models that can be applied across time horizons and ecosystems, identification of the timescales for which predictions can provide useful information, and quantification of uncertainty in predictions. To assess the capacity of near-term, iterative forecasting workflows to improve ebullition rate predictions, we developed and tested a near-term, iterative forecasting workflow of CH4 ebullition rates in a small eutrophic reservoir throughout one open-water period. The workflow included the repeated updating of a CH4 ebullition forecast model over time with newly-collected data via iterative model refitting. We compared the CH4 forecasts from our workflow to both alternative forecasts generated without iterative model refitting and a persistence null model. Our forecasts with iterative model refitting estimated CH4 ebullition rates up to 2 weeks into the future [RMSE at 1-week ahead = 0.53 and 0.48 loge(mg CH4 m−2 d−1) at 2-week ahead horizons]. Forecasts with iterative model refitting outperformed forecasts without refitting and the persistence null model at both 1- and 2-week forecast horizons. Driver uncertainty and model process uncertainty contributed the most to total forecast uncertainty, suggesting that future workflow improvements should focus on improved mechanistic understanding of CH4 models and drivers. Altogether, our study suggests that iterative forecasting improves week-to-week CH4 ebullition predictions, provides insight into predictability of ebullition rates into the future, and identifies which sources of uncertainty are the most important contributors to the total uncertainty in CH4 ebullition predictions.

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Spatiotemporal Methane Emission From Global Reservoirs

Cited by 34 publications

References 102 publications

Methane Emission From Global Lakes: New Spatiotemporal Data and Observation‐Driven Modeling of Methane Dynamics Indicates Lower Emissions

Methane Emission From Global Lakes: New Spatiotemporal Data and Observation‐Driven Modeling of Methane Dynamics Indicates Lower Emissions

Anthropogenically driven climate and landscape change effects on inland water carbon dynamics: What have we learned and where are we going?

Iterative Forecasting Improves Near-Term Predictions of Methane Ebullition Rates

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