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DOE OSTI2024

Mechanical suppression of invasive Northern Pike in Box Canyon Reservoir, Washington

Abstract Objective Northern Pike Esox lucius recently invaded Box Canyon Reservoir, Washington, expanding to over 10,000 individuals by 2011. To limit further impacts, a significant reduction in population abundance was required. Project objectives were to reduce relative abundance (catch per unit effort [CPUE]) to less than 1.7 Northern Pike/net (87% reduction) in the core area and to less than 0.5 Northern Pike/net in the northern reservoir section within 3 years and then maintain those abundance targets thereafter. Methods Using gill nets, we conducted intensive annual (2012–2018) suppression each spring, focusing on spawning aggregations in shallow (<2-m), flooded habitats. To evaluate CPUE, a standardized spring pike index netting (SPIN) survey was conducted annually in May and compared to suppression netting CPUE. Result In total, 17,464 Northern Pike were removed in 4868 net sets, with 92.9% captured in the first 3 years, limiting future recruitment. Mean SPIN CPUE in the core area declined from a presuppression (2011) high of 13.2 Northern Pike/net to less than 1.0 Northern Pike/net by 2014. Effort was reduced by up to 80% as the project transitioned from the initial suppression phase (2012–2014) to a control phase (2015–2018), which explored the minimum effort required to maintain abundance targets. A significant rebound in CPUE occurred from 2017 to 2018, indicating that over 267 net sets annually may be required for long-term control. Although the mean CPUE (±95% confidence interval) increased slightly in 2018 (0.6 ± 0.5 Northern Pike/net), the target abundance in the core area was achieved annually from 2013 to 2018. Changes in suppression CPUE reflected those observed in SPIN surveys, further validating the survey and corroborating abundance trends. Conclusion Results demonstrate that the suppression of Northern Pike in large, complex waters is feasible but requires a substantial long-term commitment. We expect the suppression of this invasive species to become standard practice outside of its native range. The methodology and equipment described here could be applied directly or modified by others to suppress Northern Pike.

Bean, Nicholas J.↗

DOE OSTI2021

Evaluating long-term emission impacts of large-scale electric vehicle deployment in the US using a human-Earth systems model

While large-scale adoption of electric vehicles (EVs) globally would reduce carbon dioxide (CO 2 ) and traditional air pollutant emissions from the transportation sector, emissions from the electric sector, refineries, and potentially other sources would change in response. Here, a multi-sector human-Earth systems model is used to evaluate the net long-term emission implications of large-scale EV adoption in the US over widely differing pathways of the evolution of the electric sector. Our results indicate that high EV adoption would decrease net CO 2 emissions through 2050, even for a scenario where all electric sector capacity additions through 2050 are fossil fuel technologies. Greater net CO 2 reductions would be realized for scenarios that emphasize renewables or decarbonization of electricity production. Net air pollutant emission changes in 2050 are relatively small compared to expected overall decreases from recent levels to 2050. States participating in the Regional Greenhouse Gas Initiative experience greater CO 2 and air pollutant reductions on a percentage basis. These results suggest that coordinated, multi-sector planning can greatly enhance the climate and environmental benefits of EVs. Additional factors are identified that influence the net emission impacts of EVs, including the retirement of coal capacity, refinery operations under reduced gasoline demands, and price-induced fuel switching in residential heating and in the industrial sector.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Project developer options to enhance the value of solar electricity as solar and storage penetrations increase

Increasing the penetration of photovoltaics (PV) reduces the marginal grid value of PV electricity. The declining grid value of PV with higher penetration could limit the technology's economic attractiveness and future demand. Various strategies have been proposed for preserving this value. Using a consistent framework, we analyze the net value (accounting for both cost and grid value) of more than ten strategies in the United States. Here, grid value is estimated from coincident wholesale power market prices and PV generation using observed historical prices or modeled future prices with up to 30% PV penetration. We find that established and emerging strategies designed to shift the timing of standalone PV generation at the expense of total generation—including orienting monofacial PV modules west or bifacial modules vertically—result in minor net-value benefits or penalties. Adding energy storage to such systems magnifies the net-value loss, because configurations that change the timing of PV production become redundant when the energy-shifting capabilities of storage are added. The largest net-value gains come from strategies that maximize generation (solar tracking plus oversized PV arrays) in conjunction with storage, especially at high PV penetrations. PV systems are long-lived assets. Our results suggest that efforts to promote generation-maximizing strategies today may yield increasing net-value benefits as PV and storage deployments continue to accelerate in the United States over the coming decades.

14 SOLAR ENERGY↗

DOE OSTI2023

System efficiency of packed bed TES with radial flow vs. axial flow – Influence of aspect ratio

Here, this paper compares the net system efficiency, including thermal efficiency and pressure drop effects, of radial versus axial flow packed beds for thermal energy storage. The traditional packed bed system is a cylindrical geometry where fluid flows axially from one end to another. However, issues of thermal stratification and high-pressure drop have led to recent studies on radial flow systems. One potential benefit is the reduced pressure drop in a radial flow system. This paper compares the performance of radial flow and axial flow systems at a range of aspect ratios (AR = H/D bed ) from 0.21 to 1.92 using a numerical model where the storage volume is held constant in all cases. When the radial flow bed is at a low aspect ratio (short/wide), the thermal front is improved but the pressure drop is high. At a high aspect ratio, the velocity is reduced in radial flow, leading to decreased pressure drop but an increased spreads in the thermal front that lowers thermal efficiency. The opposite trends are noted in axial flow. Thermal efficiencies of 83–91 % were noted for radial flow, while they ranged from 85 to 94 % in axial flow. Net efficiencies including pressure drop ranged from 74 to 82 % for radial flow and 80–87 % for axial flow. In both systems, a peak net efficiency was noted between the highest and lowest aspect ratio. While some aspect ratios with radial flow outperform axial flow from a net efficiency perspective, the results show that the highest net efficiency from axial flow is higher than that from radial flow. Overall, this paper highlights the importance of innovative TES designs and their potential to improve energy efficiency.

25 ENERGY STORAGE↗

DOE OSTI2022

Potential energy savings benefits and limitations of radiative cooling coatings for U.S. residential buildings

We report radiative coatings are a promising strategy to implement passive cooling that provides an eco-friendly pathway to achieve energy efficiency in buildings. This study investigates the benefits and limitations of implementing radiative coatings on the building envelope, particularly the roof, of residential buildings in the United States. The analysis compares the performance of an ideal radiative coating with broadband surface properties to a realistic radiative coating with diffuse and semitransparent properties. To enhance the net energy efficiency of buildings, we carried out a comprehensive parametric analysis comprising key radiation surface properties to maximize cooling energy savings while minimizing heating energy penalties. A countrywide assessment for 68 locations across the United States showed that net energy savings are a strong function of the climatic and atmospheric conditions. Broadly, southern locations showed high overall energy savings whereas northern locations exhibited high overall energy penalties. Locations in International Energy Conservation Code (IECC) climate zones 1A, 2A, and 2B showed a net annual energy savings above 5%, whereas locations in IECC climate zones 5B, 6B, and 7 showed a net annual energy penalty greater than 3%. The hot and dry climate of Phoenix, Arizona, showed the highest overall energy savings of 426 kWh (6.2%). Additionally, the mathematical correlation reveals that the net energy savings of a location is positive only when its average cooling degree days is greater than 5.5 or its average heating degree days is less than 10.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Tetramethylpyrazine inhibits neutrophil extracellular traps formation and alleviates hepatic ischemia/reperfusion injury in rat liver transplantation

Hepatic ischemia/reperfusion injury (IRI) is an adverse effect for liver transplantation which is characterized by immune response mediated inflammation. Recent studies report that neutrophil extracellular traps (NETs) are implicated in hepatic IRI. The aim of this study was to explore the mechanism of action of tetramethylpyrazine (TMP), the main chemical composition of Ligusticum chuanxiong in treatment of ischemic related diseases. Data showed that hepatic IRI increases the leak of alanine aminotransferase (ALT) and aspartate transaminase (AST), and stimulates formation of NETs. Extracellular DNA/NETs assay, hematoxylin-eosin (HE) staining, immunofluorescence assay, terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) and Western blot assay, showed that TMP significantly reduces formation of NETs and alleviates hepatic IRI. Moreover, TMP and Diphenyleneiodonium (DPI) suppressed ROS production in neutrophils. In addition, analysis showed that activation of NADPH oxidase plays a role in formation of NETs triggered by hepatic IRI. Notably, TMP inhibited formation of NETs though inhibition of NADPH oxidase. Additionally, Combination treatment using TMP and DPI was more effective compared with monotherapy of either of the two drugs. These findings show that combination therapy using TMP and DPI is a promising method for treatment hepatic IRI.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Background-Aware 3-D Point Cloud Segmentation With Dynamic Point Feature Aggregation

With the proliferation of LiDAR sensors and 3-D vision cameras, 3-D point cloud analysis has attracted significant attention in recent years. In this article, we propose a novel 3-D point cloud learning network, referred to as dynamic point feature aggregation network (DPFA-Net), by selectively performing the neighborhood feature aggregation (FA) with dynamic pooling and an attention mechanism. DPFA-Net has two variants for semantic segmentation and classification of 3-D point clouds. As the core module of the DPFA-Net, we propose an FA layer, in which features of the dynamic neighborhood of each point are aggregated via a self-attention mechanism. In contrast to other segmentation models, which aggregate features from fixed neighborhoods, our approach can aggregate features from different neighbors in different layers providing a more selective and broader view to the query points and focusing more on the relevant features in a local neighborhood. In addition, to further improve the performance of semantic segmentation, we exploit the background–foreground (BF) information and present two novel approaches, namely, two-stage BF-Net and BF regularization. Experimental results show that the proposed DPFA-Net achieves the state-of-the-art overall accuracy score of 89.22% for semantic segmentation on the Stanford large-scale 3-D Indoor Spaces (S3DIS) dataset and provides consistently satisfactory performance across different tasks of semantic segmentation, part segmentation, and 3-D object classification. Furthermore, our model achieves 93.1% accuracy on the ModelNet40 dataset and provides a mean shape intersection-over-union (IoU) value of 85.5% for part segmentation on the ShapeNet-Part dataset. It is a also computationally more efficient compared to other methods.

3-D↗

DOE OSTI2024

Impact of Sugarcane Cultivation on C Cycling in Southeastern United States Following Conversion From Grazed Pastures

ABSTRACT The expansion of sugarcane, a tropical high‐yielding feedstock, will likely reshape the Southeastern United States (SE US) bioenergy landscape. However, the sustainability of sugarcane, particularly as it displaces grazed pastures, is highly uncertain. Here, we investigated how pasture conversion to sugarcane in subtropical Florida impacts net ecosystem CO 2 exchange (NEE) and net ecosystem carbon (C) balance (NECB). Measurements were made over three full growth cycles (> 3 years) in sugarcane—plant cane, PC; first ratoon cane, FRC; second ratoon cane, SRC—and in improved (IM) and semi‐native (SN) pastures, which make up ca. 37% of agricultural land in the region. Immediately following conversion, PC was a stronger net source of CO 2 than pastures, indicating the importance of CO 2 losses related to land disturbance. Sugarcane, however, shifted to a strong net sink of CO 2 after first regrowth, and overall sugarcane was a stronger net CO 2 sink than pastures. Both stand age and low water availability during cane emergence and tillering substantially decreased its potential gross CO 2 uptake. Accounting for all C gains and removals (i.e., NECB), greater frequency of burn events and repeated harvest increased removals and overall made sugarcane a stronger C source relative to pastures despite substantial C inputs from the previous land use and a stronger CO 2 sink strength. Time since conversion substantially reduced C losses from sugarcane, and the NECB of SRC was similar to that of IM pasture but lower than that of SN pasture, indicating a rapid shift in the NECB of cane. We conclude that the C‐balance implications following conversion will depend on the proportion of IM versus SN pastures converted to sugarcane. Furthermore, our findings suggest that no‐burn harvest management strategies will be critical to the development of a sustainable bioenergy landscape in SE US.

Gomez‐Casanovas, Nuria↗

DOE OSTI2020

Distributed Solar Utility Tariff and Revenue Impact Analysis: A Guidebook for International Practitioners

Depending on a range of technical, economic, policy, regulatory, and market-related factors, the adoption of DPV may have a net positive or negative financial impact on utilities and ratepayers. This guidebook provides a methodological approach for quantifying the net financial impact of DPV on utilities (in the form of “net revenue losses”) and ratepayers (in the form of “net tariff impacts”). Written for technical staff at utilities, regulatory bodies, energy ministries, research institutes, and civil society organizations who wish to better understand the financial impacts of DPV in their jurisdiction, this guidebook can be used to inform important decisions regarding DPV compensation, tariff design, and regulatory cost allocations, among other aspects. It is focused exclusively on customer-sited DPV systems and adopts a primarily cost-based (as opposed to an equally valid value-based) perspective to understanding DPV financial impacts. The approach for calculating net revenue losses can be applied in nearly any utility jurisdiction, regardless of institutional arrangements, business models, or regulatory paradigms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (MEME-CCS)

This effort employs and adapts a rigorous multiscale electricity modeling platform at the National Renewable Energy Laboratory (NREL) to evaluate carbon capture and sequestration (CCS) and negative emissions technologies (NET) from the ARPA-E FLECCS program. NREL's modeling platform includes the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model, which projects future electricity generation mixes at sub-state-level resolution that are downscaled to the unit-level to enable hourly, zonal or nodal electricity production cost modeling in the PLEXOS model. The ReEDS-PLEXOS modeling suite is well-established for examining electric sector futures with high renewable energy penetrations, energy storage, electrification, and distributed generation. The key advancement proposed herein utilizes collaboration with CCS experts at the University of Wyoming (U.WY) and the FLECCS technology development teams to create innovative methods for representing CCS and NET in the ReEDS and PLEXOS models. Expanded technology options and new operational parameterizations are integrated into these models to allow an unprecedented combination of scope and resolution for exploring the future of CCS and NET. The resulting capabilities permit wide-ranging scenario analysis to assess CCS and NET deployment under alternative scenarios of CO2 prices and competitiveness of flexible CCS and NET technologies. We demonstrate sample deployment and operational outcomes to show how these models are being used to assess the future potential for FLECCS technologies and their impacts on the U.S. electricity system. These products will help an emerging CCS/NET industry in the United States by providing economics-driven guidance to technology developers while informing policy and investment decisions in the public and private sectors.

capacity expansion↗

DOE OSTI2023

Flexible Gasification of Coal and Biomass to Generate Carbon Free Electric Power and Hydrogen

This paper describes the development of a coal and biomass-fed plant concept to co-produce electric power and hydrogen with net-negative CO2 emissions under the aegis of the 21st Century Power Plant initiative of the U.S. Department of Energy (DOE), whose goal is to advance innovative power plant concepts that are capable of flexible, net-zero carbon emission operations while producing cost-effective “blue” hydrogen to support economy-wide decarbonization goals. The proposed standalone plant will be in Nebraska, USA. The specified design feedstock is a hybrid blend of Powder River Basin (PRB) subbituminous coal from Wyoming and local Nebraska biomass (corn stover), 50 wt.% each (dry basis). Other potential feedstocks, including woody biomass (eastern red cedar) and waste plastic (auto shredder residue) were evaluated or reviewed as alternates. The proposed process block comprises a high-pressure, oxygen-blown fluidized bed gasifier (GTI Energy U-GAS® process) coupled with water gas shift, the Selexol process for acid gas (H2S and CO2) removal, and pressure-swing adsorption (PSA) to yield 8,500 kg/h of high-purity hydrogen. The off gas from the PSA unit is used in the power block (gas turbine combined cycle) to generate electric power to support the gasification process, hydrogen production, and 50 MWe net electric power to the grid. All major plant equipment including the gasifier, gas cleanup system, and power generation are commercially available and proven in other applications and considered at TRL 8-9. However, gasification of corn stover biomass is considered at TRL 6. Overall thermal efficiency of the plant is 50% (net HHV) with net atmospheric CO2 removal at a rate of 250-300,000 tpa. Design activities necessary to provide input to a FEED study (Phase II of the project), including the development of the Environmental Information Volume (EIV) for the host site, and an investment case, based on a pro-forma pre-FEED level cost estimate, have been completed and are described in detail in this paper.

Gülen, S. Can↗

DOE OSTI2022

Unraveling the effects of management and climate on carbon fluxes of U.S. croplands using the USDA Long-Term Agroecosystem (LTAR) network

Understanding the carbon fluxes and dynamics from a broad range of agricultural systems has the potential to improve our ability to increase carbon sequestration while maintaining crop yields. Short-term, single-location studies have limited applicability, but long-term data from a network of many locations can provide a broader understanding across gradients of climate and management choices. Here we examine eddy covariance measured carbon dioxide (CO 2 ) fluxes from cropland sites across the United States Department of Agriculture's Long-Term Agroecosystem Research (LTAR) network. The dataset was collected between 2001 and 2020, spanning 13 sites for a total of 182 site-years. Average seasonal patterns of net ecosystem CO 2 exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (R eco ) were determined, and subsequent regression analysis on these “flux climatologies” was used to identify relationships to mean annual temperature (MAT), mean annual precipitation (MAP), cropping systems, and management practices. At rainfed sites, carbon fluxes were better correlated with MAP (r2 ≤ 0.5) than MAT (r2 ≤ 0.22). Net carbon balance was different among cropping systems (p < 0.001), with the greatest net carbon uptake occurring in sugarcane (Saccharum spp. hybrids) and the least in soybean (Glycine max) fields. Crop type had a greater effect on carbon balance than irrigation management at a Nebraska site. Across cropping systems, grain crops often had higher GPP and were more likely to have net uptake when compared to legume crops. This multi-site analysis highlights the potential of the LTAR network to further carbon flux research using eddy covariance measurements.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

The path to 2060: Saudi Arabia's long-term pathway for GHG emission reduction

Saudi Arabia, as part of its Saudi Green Initiative, has announced its goal to achieve net zero green-house gas emissions by 2060. This ambitious target underscores the nation's dedication to address-ing climate change. However, there is a significant gap in comprehensive analysis regarding the long-term effects of Saudi Arabia's climate policies and their collective contribution towards the net-zero objective. This study endeavors to bridge this gap through a detailed examination using the GCAM-KSA, a specialized version of the Global Change Analysis Model tailored for Saudi Arabia, employing a multi-sectoral methodology that integrates economic, energy, and land use systems within a coherent framework to assess the impact of climate policies on GHG emissions. Our anal-ysis reveals that reaching net-zero GHG emissions by 2060 is a complex challenge requiring con-certed efforts across all sectors of the economy. While transitioning to low-carbon electricity and improving energy efficiency offer considerable emission reductions, fully decarbonizing the indus-trial and transportation sectors poses a significant hurdle. Our findings suggest that Saudi Arabia must triple its emission reduction commitments in its next Nationally Determined Contributions (NDCs) update to align with its 2060 net-zero goal. Early action and increased ambition could avoid the chances of getting locked into the high emission assets and give enough time to transform the energy system. Furthermore, the adoption and integration of Carbon Dioxide Removal (CDR) tech-nologies are identified as crucial for offsetting residual emissions, especially in sectors that might continue to rely on fossil fuels.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Deep learning inversion of gravity data for detection of CO 2 plumes in overlying aquifers

In this work, we developed an effective U-Net based deep learning (DL) model for inversion of surface gravity data on a rectangular grid to predict 2-D high-resolution subsurface CO 2 distribution along a vertical cross-section due to CO 2 leakage through a wellbore within a deep CO 2 storage reservoir. We used synthetic data to model two types of CO 2 leakage scenarios: one CO 2 plume in a shallow aquifer (single plume case), and two plumes present at different depths (double plume case). The 3-D synthetic plume samples were created by sampling among predetermined CO 2 plume depths, saturations, and volumes. The corresponding surface gravity data on a rectangular grid were generated by a 3-D forward model. The U-Net model detected 72% of single-plume samples, and one or both plumes in 75% of double-plume samples. Most of the undetected single plumes have small gravity field strengths below the typical noise level of 5 μGal. This model generated reproducible, reliable predictions with acceptable errors and demonstrated improved spatial resolution over the conventional least-squares inversion. In contrast to the conventional least-squares inversion, which often overestimates the size of its target and underestimates its density, this U-Net model accurately delineated the boundary of a target. Furthermore, this DL inversion detected deep, small, or low saturation CO 2 plumes that are often more difficult to resolve with conventional gravity inversion methods. We note the limitations of this feasibility study, including the use of synthetic data with regular CO 2 plume shapes, and the prediction of a 2-D plume cross-section rather than the full 3-D plume, as well, we recognize the lower detection fraction for double-plume scenarios. Nevertheless, this study demonstrates that DL gravity inversion is a promising and potentially superior method to conventional least-squares inversion. Our U-Net based deep learning inversion approach may be adapted for inversion of other types of geophysical data. DL inversion can facilitate near real-time monitoring of geologic carbon sequestration to provide site operators with prompt information about subsurface CO 2 distribution for risk management and mitigation.

58 GEOSCIENCES↗

DOE OSTI2024

Electron energy gain due to a laser frequency modulation experienced by electron during betatron motion

Direct laser acceleration of electrons is an important energy deposition mechanism for laser-irradiated plasmas that is particularly effective at relativistic laser intensities in the presence of quasi-static laser-driven plasma electric and magnetic fields. These radial electric and azimuthal magnetic fields provide transverse electron confinement by inducing betatron oscillations of forward-moving electrons undergoing laser acceleration. Electrons are said to experience a betatron resonance when the frequency of betatron oscillations matches the average frequency of the laser field oscillations at the electron position. In this paper, we show that the modulation of the laser frequency as seen by an electron performing betatron oscillations can be another important mechanism for net energy gain that is qualitatively different from the betatron resonance. Specifically, we show that the frequency modulation experienced by the electron can lead to net energy gain in the regime where the laser field performs three oscillations per betatron oscillation. There is no net energy gain in this regime without the modulation because the energy gain is fully compensated by the energy loss. The modulation slows down the laser oscillation near transverse stopping points, increasing the time interval during which the electron gains energy and making it possible to achieve net energy gain.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

A Distributionally Robust Optimization Framework for Stochastic Assessment of Power System Flexibility in Economic Dispatch

Given the complexity of power systems, particularly the high-dimensional variability of net loads, accurately depicting the entire operational range of net loads poses a challenge. To address this, recent methodologies have sought to gauge the maximum range of net load uncertainty across all buses. In this paper, we consider the stochastic nature of the net load and introduce a distributionally robust optimization framework that assesses system flexibility stochastically, accommodating a minimal extent of system violations. We verify the proposed method by solving the flexibility of the economic dispatch problem on four distinct IEEE standard test systems. Compared to traditional deterministic flexibility evaluations, our approach consistently yields less conservative flexibility outcomes.

distributionally robust optimization↗

DOE OSTI2020

Joint Estimation of Behind-the-Meter Solar Generation in a Community

Distribution grid planning, control, and optimization require accurate estimation of solar photovoltaic (PV) generation and electric load in the system. Most of the small residential solar PV systems are installed behind-the-meter making only the net load readings available to the utilities. This paper presents an unsupervised framework for joint disaggregation of the net load readings of a group of customers into the solar PV generation and electric load. Our algorithm synergistically combines a physical PV system performance model for individual solar PV generation estimation with a statistical model for joint load estimation. The electric loads for a group of customers are estimated jointly by a mixed hidden Markov model (MHMM) which enables modeling the general load consumption behavior present in all customers while acknowledging the individual differences. At the same time, the model can capture the change in load patterns over a time period by the hidden Markov states. The proposed algorithm is also capable of estimating the key technical parameters of the solar PV systems. Our proposed method is evaluated using the net load, electric load, and solar PV generation data gathered from residential customers located in Austin, Texas. Testing results show that our proposed method reduces the mean squared error of state-of-the-art net-load disaggregation algorithms by 67%.

behind-the-meter solar generation↗

DOE OSTI2022

Annual carbon sequestration and loss rates under altered hydrology and fire regimes in southeastern USA pocosin peatlands

Peatlands drained for agriculture or forestry are susceptible to the rapid release of greenhouse gases (GHGs) through enhanced microbial decomposition and increased frequency of deep peat fires. We present evidence that rewetting drained subtropical wooded peatlands (STWPs) along the southeastern USA coast, primarily pocosin bogs, could prevent significant carbon (C) losses. To quantify GHG emissions and storage from drained and rewetted pocosin we used eddy covariance techniques, the first such estimates that have been applied to this major bog type, on a private drained (PD) site supplemented by static chamber measurements at PD and Pocosin Lakes National Wildlife Refuge. Net ecosystem exchange measurements showed that the loss was 21.2 Mg CO2 ha –1 year –1 (1 Mg = 10 6 g) in the drained pocosin. Under a rewetted scenario, where the annual mean water table depth (WTD) decreased from 60 to 30 cm, the C loss was projected to fall to 2 Mg CO 2 ha –1 year –1 , a 94% reduction. If the WTD was 20 cm, the peatlands became a net carbon sink (–3.3 Mg CO2 ha –1 year –1 ). Hence, net C reductions could reach 24.5 Mg CO 2 ha –1 year –1 , and when scaled up to the 4000 ha PD site nearly 100,000 Mg CO 2 year –1 of creditable C could be amassed. We conservatively estimate among the 0.75 million ha of southeastern STWPs, between 450 and 770 km 2 could be rewet, reducing annual GHG emissions by 0.96–1.6 Tg (1 Tg = 10 12 g) of CO 2 , through suppressed microbial decomposition and 1.7–2.8 Tg via fire prevention, respectively. Despite covering <0.01% of US land area, rewetting drained pocosin can potentially provide 2.4% of the annual CO 2 nationwide reduction target of 0.18 Pg (1 Pg = 10 15 g). Finally, suggesting pocosin restoration can contribute disproportionately to the US goal of achieving net-zero emission by 2050.

58 GEOSCIENCES↗