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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Small-Scale Irrigation: Improving Food Security under Changing Climate and Water Resource Conditions in Ethiopia

We develop a new systems modeling tool that integrates knowledge from hydrology, agriculture, and economics to understand the effect of small-scale irrigation on food security and groundwater sustainability in Ethiopia. Irrigation is an effective tool to mitigate climate impacts and improve agricultural yields. Small-scale irrigation, such as decentralized groundwater irrigation, is well suited for developing countries where smallholder farming communities are widely dispersed and can only afford small infrastructure investment. We study the underlying interdependencies between food and water systems in Ethiopia, where small-holder agriculture is the foundation of the nation’s economy and climate variability has led to great challenges to its food security. Our coupled market and crop model with groundwater module captures the interdependencies of climate, water availability (including irrigation), crop yield, farmland allocation, crop production, transport and consumption based on a system approach across multiple spatial scales. We study the implication of small-scale irrigation to Ethiopia’s food security and water resource conditions as a “what-if” question by comparing an irrigation scenario to the calibrated baseline in 2015, a year of significant drought and crop failure over a large portion of Ethiopia. Our model offers fresh insights into geographic disparities in outcomes that are driven by baseline climate variability, soil fertility, and market conditions. In general, we find that small-scale irrigation can potentially improve food security through increases in food consumption, but it requires policy support to direct the increases of production to domestic consumption while maintaining a sustainable groundwater condition. By using Ethiopia as an example, we show the strength of our model to study how water infrastructure resources support critical functions and service in water and food systems.

Zhang, Ying↗
DOE OSTI2023

Global warming intensity of biofuel derived from switchgrass grown on marginal land in Michigan

Energy crops for biofuel production, especially switchgrass (Panicum virgatum), are of interest from a climate change perspective. Here, we use outputs from a crop growth model and life cycle assessment (LCA) to examine the global warming intensity (GWI; g CO 2 MJ –1 ) and greenhouse gas (GHG) mitigation potential (Mg CO 2 year –1 ) of biofuel systems based on a spatially explicit analysis of switchgrass grown on marginal land (abandoned former cropland) in Michigan, USA. We find that marginal lands in Michigan can annually produce over 0.57 hm 3 of liquid biofuel derived from nitrogen-fertilized switchgrass, mitigating 1.2–1.5 Tg of CO 2 year –1 . About 96% of these biofuels can meet the Renewable Fuel Standard (60% reduction in lifecycle GHG emissions compared with conventional gasoline; GWI ≤37.2 g CO 2 MJ –1 ). Furthermore, 73%–75% of these biofuels are carbon-negative (GWI less than zero) due to enhanced soil organic carbon (SOC) sequestration. However, simulations indicate that SOC levels would fail to increase and even decrease on the 11% of lands where SOC stocks >>200 Mg C ha –1 , leading to carbon intensities greater than gasoline. Results highlight the strong climate mitigation potential of switchgrass grown on marginal lands as well as the needs to avoid carbon rich soils such as histosols and wetlands and to ensure that productivity will be sufficient to provide net mitigation.

09 BIOMASS FUELS↗
DOE OSTI2024

The impacts of rising vapour pressure deficit in natural and managed ecosystems

Abstract An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land–atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co‐evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluating the economic impact of water scarcity in a changing world

Abstract Water scarcity is dynamic and complex, emerging from the combined influences of climate change, basin-level water resources, and managed systems’ adaptive capacities. Beyond geophysical stressors and responses, it is critical to also consider how multi-sector, multi-scale economic teleconnections mitigate or exacerbate water shortages. Here, we contribute a global-to-basin-scale exploratory analysis of potential water scarcity impacts by linking a global human-Earth system model, a global hydrologic model, and a metric for the loss of economic surplus due to resource shortages. We find that, dependent on scenario assumptions, major hydrologic basins can experience strongly positive or strongly negative economic impacts due to global trade dynamics and market adaptations to regional scarcity. In many cases, market adaptation profoundly magnifies economic uncertainty relative to hydrologic uncertainty. Our analysis finds that impactful scenarios are often combinations of standard scenarios, showcasing that planners cannot presume drivers of uncertainty in complex adaptive systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

How Rains and Floods Become Groundwater: Understanding Recharge Pathways With Stable and Cosmogenic Isotopes

Anthropogenic climate change leads to increased precipitation intensity and exacerbated droughts in California, challenging the reliability and drought resiliency of water supply. Storing floodwater underground via managed aquifer recharge can mitigate these effects through direct infiltration or streambed infiltration. Seasonally dry streams (arroyos) already play an important part in managing groundwater recharge to the Livermore basin (CA). Understanding how, when and where stormwater and arroyo water infiltrate is critical to effectively utilise this strategy. To track water from recent storms (water year 2022–2023, WY23) into the Livermore Valley Groundwater Basin, we analysed stable water isotopes (δ 18 O and δ 2 H) in combination with naturally occurring radioactive isotopic tracers, sulphur-35 ( 35 S, t ½ = 87 days) and tritium ( 3 H, t ½ = 12.3 years). By comparing measurements of δ 18 O, 35 S and 3 H in arroyos to precipitation and groundwater, we classified the relative age and identified source of recharge to 16 wells near two arroyos. Two wells contained water with recent recharge (from WY23) from local precipitation. One well had recent recharge from variable (precipitation and imported water) sources. One well contained imported water recharge. Three wells contained water from mixed recent and older (pre-WY23) waters, from local precipitation sources. Two wells contained recent recharge from local mine settling ponds. Seven wells had older recharge from local precipitation sources. This combination of isotopes allows us to delineate where local and imported water recharges in this highly managed basin and identify locations where managed aquifer recharge is contributing to rapid groundwater infiltration. Our combined interpretation of isotopic water ages and sources in the context of land use shows that local infiltration of precipitation in open spaces is an important recharge mechanism, in addition to the managed arroyo recharge. Finally, a broader familiarity with 35 S will enable more extensive research on the infiltration of urban floodwaters.

58 GEOSCIENCES↗
DOE OSTI2022

Artificial Intelligence for Accelerating Nuclear Applications, Science, and Technology

Artificial intelligence (AI) and machine learning (ML) methods have had significant impacts in science and technology in recent years. These methods for generating models from datasets or logic-based algorithms that emulate aspects of human performance can similarly accelerate the fields of nuclear applications, science, and technology toward the IAEA goals of contributing to peace, health, and prosperity. In order to accomplish advances with AI in general and ML in particular across these fields, IAEA can play a significant role by establishing, hosting and curating centralised resources, including databases, adhering to FAIR (findable, accessible, interoperable and reusable) principles and Open Science best practices, providing stewardship of data sharing, supporting training efforts and development of relevant workforces, as well as enabling connections among the scientific, technology, mathematics, AI and ethics communities. Many areas can benefit from the use of AI in the realm of nuclear applications. In human health, these areas include clinical research, epidemiology, nutrition, medical imaging, radiotherapy and education of health professionals. AI-based tools are also being used to facilitate different clinical tasks in imaging, computer-assisted diagnosis in mammography and lung cancer screening programmes, and dose prediction in nuclear medicine procedures. ML methods in particular may also increase the efficiency and accuracy of the analysis of computerised tomography and dual-energy absorptiometry scans for body composition and bone analysis. The application of AI methods to nuclear and related technologies in food and agriculture can lead to significant advances and improved efficiency in the optimisation of agricultural production, food product development, management of supply chains, food safety and food authenticity control. In the water and environmental sector, AI can help inform policies to mitigate the world’s water problems. The application of AI techniques to hydrology and environmental sciences is expected to improve patterns identification and enable model predictions under a changing climate.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Future increase in compound soil drought-heat extremes exacerbated by vegetation greening

Compound soil drought and heat extremes are expected to occur more frequently with global warming, causing wide-ranging socio-ecological repercussions. Vegetation modulates air temperature and soil moisture through biophysical processes, thereby influencing the occurrence of such extremes. Global vegetation cover is broadly expected to increase under climate change, but it remains unclear whether vegetation greening will alleviate or aggravate future increases in compound soil drought-heat events. Here, using a suite of state-of-the-art model simulations, we show that the projected vegetation greening will increase the frequency of global compound soil drought-heat events, equivalent to 12-21% of the total increment at the end of 21st century. This increase is predominantly driven by reduced albedo and enhanced transpiration associated with increased leaf area. Although greening-induced transpiration enhancement has counteracting cooling and drying effects, the excessive water loss in the early growing season can lead to later soil moisture deficits, amplifying compound soil drought-heat extremes during the subsequent warm season. These changes are most pronounced in northern high latitudes and are dominated by the warming effect of CO 2 . Our study highlights the necessity of integrating vegetation biophysical effects into mitigation and adaptation strategies for addressing compound climate risks.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Assessment of Quantum ML Applicability for Climate Actions: Comparison of the Variational Quantum Classifier and the Quantum Support Vector Classifier with Classical ML Models

Climate change refers to significant and long-term alterations in the Earth’s climate patterns, typically resulting from human activities that increase greenhouse gas emissions. Addressing climate change is not merely an option but a necessity, demanding creative solutions and efforts from individuals, researchers, communities, and governments. Despite the capabilities of machine learning (ML) with data-driven solutions promising to combat climate change-related problems, they face challenges stemming from traditional computational methods and prolonged training times, impeding their practical utility. Recent strides in quantum computing have permeated diverse domains, spanning from manufacturing engineering and pharmaceutical discovery to the latest frontier of detecting climate anomalies. With the potential to substantially reduce time and computational complexity, quantum computing shows promise in addressing climate change impacts. Its distinctive features will enable the concurrent exploration of expansive solution spaces, making it well-suited for analyzing extensive climate datasets, simulating intricate climate models, optimizing resource allocation, and discerning patterns in climate data for mitigation and adaptation endeavors. This study explores the potential of using Quantum machine learning (QML) techniques on climate and weather data obtained from NASA Giovannis. We used two QML algorithms, the Quantum Support Vector Classifier (QSVC) and the Variational Quantum Classifier (VQC) models, using the IBM Qiskit ML 0.7.2 ecosystem. We used an actual 127-Qubit IBM Quantum Computer (IBM 127-qubit Eagle) in this study. The methodology and results sections describe the experiences gained from applying and evaluating quantum ML results on climate and weather data obtained from NASA satellites as a novel practical application of quantum computing.

Earth Observational Data↗
DOE OSTI2024

Choreographing root architecture and rhizosphere interactions through synthetic biology

Abstract Climate change is driving extreme changes to the environment, posing substantial threats to global food security and bioenergy. Given the direct role of plant roots in mediating plant-environment interactions, engineering the form and function of root systems and their associated microbiota may mitigate these effects. Synthetic genetic circuits have enabled sophisticated control of gene expression in microbial systems for years and a surge of advances has heralded the extension of this approach to multicellular plant species. Targeting these tools to affect root structure, exudation, and microbe activity on root surfaces provide multiple strategies for the advancement of climate-ready crops.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2013

Global and Regional Temperature-change Potentials for Near-term Climate Forcers

The emissions of reactive gases and aerosols can affect climate through the burdens of ozone, methane and aerosols, having both cooling and warming effects. These species are generally referred to near-term climate forcers (NTCFs) or short-lived climate pollutants (SLCPs), because of their short atmospheric residence time. The mitigation of these would be attractive for both air quality and climate on a 30-year timescale, provided it is not at the expense of CO2 mitigation. In this study we examine the climate effects of the emissions of NTCFs from 4 continental regions (East Asia, Europe, North America and South Asia) using results from the Task Force on Hemispheric Transport of Air Pollution Source-Receptor global chemical transport model simulations. We address 3 aerosol species (sulphate, particulate organic matter and black carbon - BC) and 4 ozone precursors (methane, reactive nitrogen oxides - NOx, volatile organic compounds VOC, and carbon monoxide - CO). For the aerosols the global warming potentials (GWPs) and global temperature change potentials (GTPs) are simply time-dependent scaling of the equilibrium radiative forcing, with the GTPs decreasing more rapidly with time than the GWPs. While the aerosol climate metrics have only a modest dependence on emission region, emissions of NOx and VOCs from South Asia have GWPs and GTPs of higher magnitude than from the other northern hemisphere regions. On regional basis, the northern mid-latitude temperature response to northern mid-latitude emissions is approximately twice as large as the global average response for aerosol emission, and about 20-30% larger than the global average for methane, VOC and CO emissions. We also found that temperatures in the Arctic latitudes appear to be particularly sensitive to black carbon emissions from South Asia.

climate forcer↗
NASA NTRS2013

Improving Decision-Making Activities for Meningitis and Malaria

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community's capacity to understand, use and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular meningitis and malaria. In this paper, we present the new and improved products that have been developed for: (i) estimating dust aerosol for forecasting risks of meningitis and (ii) for monitoring temperature and rainfall and integrating them into a vectorial capacity model for forecasting risks of malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map Room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.

parasitic diseases↗
DOE OSTI2023

Thermodynamics of Minerals Stable near Earth's Surface

Project “Thermodynamics of Minerals Stable Near the Earth’s Surface” uses specialized calorimetric techniques to obtain new thermochemical data for solid phases of interest in the Earth’s “critical zone”, the near surface regions of the planet most directly affecting and affected by human activity. Major activity was in three areas: manganese oxide materials, aluminum clusters which are precursors to aluminum oxyhydroxide precipitates, and zeolites. All these classes of minerals are potential carriers of heavy metals and radionuclides in the environment, both within their crystal structures and as adsorbed layers or colloids. Their thermodynamic stability, as well as the sequence of stability of competing phases, governs the aqueous solubility of contaminants (and nutrients) in soil, groundwater, and sediments. The thermodynamics of these phases is strongly affected by particle size and crystallinity, since they often occur as very fine particles which do not coarsen in the near-surface environment. Many of these materials exhibit extensive polymorphism, multicomponent solid solution, and variable hydration states. Thus, one must define and systematize important thermodynamic variables, since one cannot make measurements on each and every possible phase, particle size, and composition. A major finding of the work on manganese oxides was labile water-induced oxidation-reduction reactions. These will be studied further by a combination of thermodynamic and synchrotron-based spectroscopic methods, the latter in collaboration with Peggy O’Day at UC Merced. The adsorption of other species, including simple organics, on such redox-active surfaces will also be investigated by a combination of thermochemical and spectroscopic studies. Studies of the energetics of water adsorption on mineral surfaces will be expanded to emphasize the adsorption of CO2 and small organic molecules, relevant to soil, groundwater, and the subsurface environment. Gas adsorption calorimetry, immersion calorimetry, and solution calorimetry will be combined with appropriate analytical and spectroscopic techniques to obtain a comprehensive picture of the interactions and their energetics. The evolution of aqueous aluminum clusters to form aluminum oxyhydroxide precipitates will be studied in detail by a combination of calorimetric and structural methods applied to aqueous samples aged at room temperature. The energetics of new classes of clusters will be explored. The project addresses several common themes relevant to the broad mission of the Department of Energy. Thermochemical data for minerals stable near the Earth’s surface, though still incomplete, are essential for understanding both natural and anthropogenic processes that affect our very existence on this planet. Such data contribute to the fundamental underpinning for mitigation and management strategies for the extraction and use of energy. Fundamental thermodynamic and mechanistic understanding is required to model processes ranging from heavy metal pollution to nuclear waste disposal to climate change.

58 GEOSCIENCES↗
NASA NTRS2021

Finding and Fixing Food System Emissions: The Double Helix of Science and Policy

Improving estimates of greenhouse gas (GHG) emissions from food production, supply, consumption, and disposal is fundamental to identifying effective policy solutions. Through broader awareness of the food-climate nexus, climate mitigation as well as resilience can be enhanced. However, work is needed to address knowledge gaps, promote better policies and improve public understanding of issues related to the food system and climate change. The intention of this paper is not only to highlight the need for better scientific understanding of the processes through which GHGs are emitted—from production to processing, from supply chains and retail to food preparation and waste (figure 1)—but also to integrate science and policy in order to scale up impact on climate change action.

food systems↗
NASA NTRSDate not supplied

From CMS to the U.S. Greenhouse Gas Center – Improved Tracking of Recent Changes in Co 2 and Ch 4 From NASA’s Quasi-Operational Modeling Systems

Reliable, low latency delivery of high quality global flux and concentration information is a growing but still unmet need to advance expanding measurement, monitoring, reporting, and verification efforts that underpin federal climate mitigation strategies. Here we present on progress toward developing space-based greenhouse gas (GHG) monitoring systems that can provide comprehensive information trailing real time by a matter of weeks to a few months. Through support from its Carbon Monitoring System (CMS) program, NASA has developed the capability to assimilate XCO 2 retrievals from the Orbiting Carbon Observatory, 2 (OCO 2 ) into the Goddard Earth Observing System (GEOS) Constituent Data Assimilation System (CoDAS) to create gap-filled, three-dimensional (3D) estimates of CO 2 mixing ratio. When observations are unavailable, concentration fields are further informed by observationally-informed bottom-up flux packages that incorporate remotely sensed fire, nighttime lights, and vegetation observations combined with estimates of atmospheric growth rate based on surface in situ data. The 3D nature of these datasets supports evaluation with independent aircraft data to improve confidence in satellite data, development of new regional modeling approaches, and quantification of the climate impacts of GHGs. The system has recently been expanded to assimilate XCH 4 from ESA’s TROPOspheric Monitoring Instrument (TROPOMI) instrument and is supported by companion efforts to improve delivery of estimates of bottom-up land and ocean fluxes. The quasi-operational GEOS-GHG system is contributing to the recently announced U.S. Greenhouse Gas Center (GHG Center) by delivering information on recent changes in CO 2 and CH 4 emissions and concentrations to support stakeholder and research communities. In this presentation, we provide an overview of the current system configured to support the GHG Center. We highlight examples of how this data contributes to broader NASA initiatives including the Earth Information Center, an innovative virtual and physical exhibit designed to show how NASA data helps the nation combat climate change. We conclude by discussing how innovations in CMS research can address remaining data gaps and modeling challenges to advance operational GHG monitoring in the future.

Lesley Ott↗
DOE OSTI2026

Climate impacts in scenarios: time to close the loop?

Reaching a full understanding of the consequences of climate change for society and ecosystems, and the ensuing needs for adaptation, requires a consideration of the interactions between human and Earth systems. Currently, however, climate research largely separates the influence of society on climate from the influence of climate on society; that is, it doesn’t “close the loop.” A primary example of this approach is the generation and use of earth system model (ESM) simulations in the climate change research community. Large-scale socio-economic models, known as integrated assessment models (IAMs), are used to project emissions and land use change which serve as input to ESMs. ESM projections then serve as input to models of impacts on society and ecosystems. But, according to this modeling chain, those impacts do not affect the emissions and land use that drove the ESMs in the first place. Previous work has not drawn firm conclusions on whether this feedback would be large enough to warrant explicitly accounting for it. Two prominent possibilities, however, are that emissions and land use scenarios representing the high and low ends of the plausible range of future climate change are both too extreme. The high-end scenario may miss damaging impacts that would reduce economic activity, and therefore emissions, while the low-end scenario may ignore climate feedbacks that would make large-scale land-based carbon removal ineffective and therefore would hamper mitigation at the level assumed by the scenario. In this piece, we identify the opportunities and challenges that implementing such feedback loops would face. We argue that recent developments in climate impact research, human system modeling and ESM emulation make the time ripe to use IAMs in a structured model intercomparison exercise. Model intercomparison projects have benefitted the climate modeling community for decade snow, and more recently have also benefitted the impact modeling community. An IAM intercomparison focused on integrating impacts could make large strides in testing the implications of these feedbacks and assessing whether closing the loop would fundamentally change our outlook on future climate changes and their consequences.

Tebaldi, Claudia↗
NASA NTRS2021

GCAP 2.0: A Global 3-D Chemical-Transport Model Framework for Past, Present, and Future Climate Scenarios

This manuscript describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to Phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the preindustrial and recent past. In addition, meteorology is available for the near future and end-of-the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) product and with observational constraints.

Global Change and Air Pollution (GCAP 2.0) model↗
NASA NTRS2022

Future Climate Change Under SSP Emission Scenarios with GISS-E2.1

This paper presents the response to anthropogenic forcing in the GISS-E2.1 climate models for the 21st century Shared Socioeconomic Pathways emission scenarios within the Coupled Model Intercomparison Project Phase 6 (CMIP6). The experiments were performed using an updated and improved version of the NASA Goddard Institute for Space Studies (GISS) coupled general circulation model that includes two different versions for atmospheric composition: A non-interactive version (NINT) with prescribed composition and a tuned aerosol indirect effect and the One-Moment Aerosol model (OMA) version with fully interactive aerosols which includes a parameterized first indirect aerosol effect on clouds. The effective climate sensitivities are 3.0°C and 2.9°C for the NINT and OMA models, respectively. Each atmospheric version is coupled to two different ocean general circulation models: The GISS ocean model (E2.1-G) and HYCOM (E2.1-H). We describe the global mean responses for all future scenarios and spatial patterns of change for surface air temperature and precipitation for four of the marker scenarios: SSP1-2.6, SSP2-4.5, SSP4-6.0, and SSP5-8.5. By 2100, global mean warming ranges from 1.5°C to 5.2°C relative to 1,850–1,880 mean temperature. Two high-mitigation scenarios SSP1-1.9 and SSP1-2.6 limit the surface warming to below 2°C by the end of the 21st century, except for the NINT E2.1-H model that simulates 2.2°C of surface warming. For the high emission scenario SSP5-8.5, the range is 4.6–5.2°C at 2100. Due to about 15% larger effective climate sensitivity and stronger transient climate response in both NINT and OMA CMIP6 models compared to CMIP5 versions, there is a stronger warming by 2100 in the SSP emission scenarios than in the comparable Representative Concentration Pathway (RCP) scenarios in CMIP5. Changes in sea ice area are highly correlated to global mean surface air temperature anomalies and show steep declines in both hemispheres, with the largest sea ice area decreases occurring during September in the Northern Hemisphere in both E2.1-G (−1.21 × 106 km2/°C) and E2.1-H models (−0.94 × 106 km2/°C). Both coupled models project decreases in the Atlantic overturning stream function by 2100. The largest decrease of 56%–65% in the 21st century overturning stream function is produced in the warmest scenario SSP5-8.5 in the E2.1-G model, comparable to the reduction in the corresponding CMIP5 GISS-E2 RCP8.5 simulation. Both low-end scenarios SSP1-1.9 and SSP1-2.6 also simulate substantial reductions of the overturning (9%–37%) with slow recovery of about 10% by the end of the 21st century (relative to the maximum decrease at the middle of the 21st century).

climate models↗
DOE OSTI2021

Coupling plant litter quantity to a novel metric for litter quality explains C storage changes in a thawing permafrost peatland

Abstract Permafrost thaw is a major potential feedback source to climate change as it can drive the increased release of greenhouse gases carbon dioxide (CO 2 ) and methane (CH 4 ). This carbon release from the decomposition of thawing soil organic material can be mitigated by increased net primary productivity (NPP) caused by warming, increasing atmospheric CO 2 , and plant community transition. However, the net effect on C storage also depends on how these plant community changes alter plant litter quantity, quality, and decomposition rates. Predicting decomposition rates based on litter quality remains challenging, but a promising new way forward is to incorporate measures of the energetic favorability to soil microbes of plant biomass decomposition. We asked how the variation in one such measure, the nominal oxidation state of carbon (NOSC), interacts with changing quantities of plant material inputs to influence the net C balance of a thawing permafrost peatland. We found: (1) Plant productivity (NPP) increased post‐thaw, but instead of contributing to increased standing biomass, it increased plant biomass turnover via increased litter inputs to soil; (2) Plant litter thermodynamic favorability (NOSC) and decomposition rate both increased post‐thaw, despite limited changes in bulk C:N ratios; (3) these increases caused the higher NPP to cycle more rapidly through both plants and soil, contributing to higher CO 2 and CH 4 fluxes from decomposition. Thus, the increased C‐storage expected from higher productivity was limited and the high global warming potential of CH 4 contributed a net positive warming effect. Although post‐thaw peatlands are currently C sinks due to high NPP offsetting high CO 2 release, this status is very sensitive to the plant community's litter input rate and quality. Integration of novel bioavailability metrics based on litter chemistry, including NOSC, into studies of ecosystem dynamics, is needed to improve the understanding of controls on arctic C stocks under continued ecosystem transition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗