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Alternative Approaches to Traditional Net Energy Metering

Most jurisdictions in the United States originally implemented net energy metering (NEM) tariffs to support the deployment and interconnection of distributed generation (DG) resources (e.g., rooftop solar photovoltaic systems). Since then, NEM has proven effective in promoting adoption of DG resources. Recently, due to concerns about sufficient recovery of utilities’ revenue requirements and cost-shifting, there is increasing interest in—or statutory requirements to pursue—alternative compensation approaches, especially in U.S. states and territories with robust growth in distributed solar. Recent increases in other forms of distributed energy resources (DERs) that can potentially send power to the distribution grid (e.g., distributed battery energy storage system (BESS)) are further driving compensation reforms. This brief provides an overview of design elements associated with alternative approaches to traditional NEM, summarizes common arguments for and against them, and identifies implementation issues that utilities may need to address. Although this brief may be most useful in jurisdictions that are interested in or required to move beyond NEM, it is also applicable to those jurisdictions that have already done so—and are looking to further implement reforms to their existing compensation mechanisms. In the broadest sense, there are three primary tariff-related components when interconnecting a DER onto the local utility’s distribution system (adapted from Zinaman et al., 2017): 1. Metering and Billing Arrangements: How utilities measure and bill electricity consumption and production. 2. DER Export Tariff Design: The structure under which utilities compensate customers for electricity they export to the grid. 3. Consumption Tariff Design: The structure under which customers pay for electricity they consume from the grid. When implementing changes to any of these primary tariff-related components, there are likely implications for a utility’s metering system, billing system, and other technology systems. Where applicable, this brief explicitly identifies such implementation challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Small Reactors in Microgrids: Technology Modeling and Selection (Net-Zero Microgrid Program Project Report)

This report demonstrates the capabilities of the net-zero microgrid (NZM) Xendee platform for modeling an SR module with electricity, heat extraction and thermal storage in microgrids configurations. The model effectively captures the most important technical and economic considerations for SR technology specific analysis: cost and operational characteristics of SR technology and financial costs and incentives. The model can analyze multiple scenarios to establish metrics for cost-competitive and zero-carbon microgrids connected to the grid or completely isolated. The model is fully integrated within the Xendee platform for modeling and analysis of clean energy microgrids with storage and generation from renewable energy sources. The model captures the capabilities, constraints, and nuances of SR by incorporating parameters related to plant economics, design efficiency and performance, plant operation and component and fuel lifespan. The cost and operational parameters modeled in the SR module are specific to the technology selected for integration in the microgrid. Cost parameters recognize advanced nuclear technology for modular production and installation based on economies of scale from factory manufacture and related commissioning, and cost reduction through technology maturation—first-of-a-kind (FOAK) and nth-of-a-Kind (NOAK). The cost parameters include installation, operations and maintenance (O&M), fuel refueling cycle, and reactor life. Installation cost reflects economies of scale due to unit sizing at scale and colocation. O&M economies of scale for both fixed- and variable-cost fuel life-cycle costs are incurred at every refueling interval, with separate front- and back-end fuel costs, as well as waste-handling and disposition costs. This report investigates key characteristics of different SR technologies suitable for microgrid applications, including design principles, sizing, coolant properties, temperature ratings, fuel structures, and life-cycle considerations. This also includes fuel technologies applicable to these SR systems, alongside strategies for nuclear-waste and spent-fuel management and approaches to address safety, security, and proliferation challenges. Four primary groups of SR technologies are examined: water-cooled, liquid-metal-cooled, high-temperature gas-cooled, and molten-salt-cooled systems. In this report, an initial guideline for technology selection is established, aligning the characteristics of the technologies with the requirements of microgrids. The selection of technology in a microgrid is influenced by various factors, including financial capacity, location and accessibility, demand type and characteristics, reliability and resilience requirements, area constraints, and the lifespan of the microgrid. The types of electrical and non-electrical applications within the microgrid also play a significant role in technology selection. The characteristics of SRs, such as their smaller size, modularity, transportability, long refueling interval, improved safety features, ability to operate in autonomous or semi-autonomous mode, and provision of high-grade heat, are particularly appealing for microgrids. Furthermore, a list of considerations for implementing SRs in microgrids is outlined. The SR model is created to be continuously improved with the acquisition of actual data on investment and operational costs, experience with supply chains, production at scale, and field deployments. In the near term, performance data on applications in microgrids will become available from lessons learned from laboratory tests, such as those planned for the Microreactor Applications Research Validation and Evaluation Project (MARVEL), led by Idaho National Laboratory (INL). The SR model incorporates scenario data and known SR design specifications, enabling technoeconomic analysis for SR deployment in microgrids. It specifically considers the distinctive attributes of SRs as generators in technoeconomic studies. SRs can be modeled and analyzed with generation from renewable-energy sources, energy storage, and flexible loads over a range of functionality and applications. This offers a comprehensive tool for feasibility studies, scenario development, and sensitivity analysis for “what-if” consideration of any range of assumptions about SRs in microgrids and other aggregations of distributed-energy resources, including virtual power plants.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Near-net shaping of high-density, complex, spatially-tailored ceramics for extreme environments

The purpose of this subcontract is for LLNL to collaborate with the Subcontractor (UCSB) in the areas of binder jet additive manufacturing (BJAM), hot pressing (HP), finite element modeling (FEM), and multi-material sintering studies. LLNL wants to further develop its hot pressing, AM, and modeling capabilities through LLNL’s Early Career Faculty Program. This work will focus on developing a method to hot press complex-shaped ceramic parts through the co-deposition of a structural/functional ceramic and sacrificial mold material in one assembly via multi-material binder jet printing. The method aims to produce dense, near-net shaped parts with applications relevant to a wide variety of fields including aerospace, defense, and energy.

36 MATERIALS SCIENCE↗

BTRIC Technical Support for Appalachia: FY 2024 Summary Report on Net Negative Carbon Building Demonstration with AgPod

This report investigates the effects of various concentrations of CO 2 on the photosynthesis and biomass accumulation of crops growing in an AgPod, using kale as the test crop. In the first year of the study, increasing the CO 2 concentration in the AgPod was found to promote higher photosynthetic rates in kale plants up to 1,300 ppm (the highest CO 2 concentration measured). An interesting finding was that net photosynthetic rates of kale leaves remain unsaturated until reaching unusually high levels of photosynthetically active radiation (PAR, > 1,200 µmol m -1 s -1 ) and CO 2 concentration (> 1,100 ppm). Such high levels of saturating PAR and CO 2 concentration values rarely occur under natural conditions, suggesting a promising potential for carbon capture via enriched controlled environment agriculture (ECEA). During the second year of the study, a second crop was planted to confirm the actual effects on growth with increased CO 2 concentrations. Our results suggest that growing kale plants in the AgPod system at higher CO 2 levels resulted in a successful and highly productive crop, up to three times the amount grown at 415 CO 2 . Further, the kale plants grown under higher CO 2 conditions (1000 ppm) are not CO 2 saturated and can potentially further improve yield at even higher CO 2 environments.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

The Circular Home: Development and Demonstration of a Net Negative Carbon, Reusable Residence

This project started the development of an innovative modular building system intended for residential construction. The project was centered around single-family homes that were carbon-negative cradle-to-grave over a 100 year time frame, which is approximately double the current standard for operational life. The project sought to accomplish this objective by designing the modular home in a manner that ensures circularity, where the main house components can be used over several consecutive 50-year lifespans. To accomplish these objectives, this project utilized integrated design with the inclusion of life-cycle assessment to design the single-family house for architectural, structural, energy, mechanical, thermal, and moisture demands, while ensuring carbon negativity and annual net-zero energy use. The core technology of this project was the use of cross-laminated timber and biogenic materials, such as wood-fiber insulation, in the construction of the modular building units. The robustness and factory manufacturing ability of cross-laminated timber allow for factory construction of most of the home, which minimizes on-site time, saving money and reducing construction waste. During this project, initial milestones were met that delivered the architectural plans for the circular home and an initial structural testing matrix. Compared to current code-built homes, which average 13 kg CO2eq. / ft2 and are demolished at their end of life, the circular home has an estimated -30 kg CO2eq. / ft2 of embodied carbon emissions during its first build iteration. It is estimated that approximately 60%-70% of the total building mass could be reused and/or recycled during subsequent rebuilds. This project was concluded at approximately the 1/3 point and a separate project was established to conclude the remaining milestones. This project promises to benefit the public by delivering another option for single-family, and eventually multi-family, housing using a novel building construction system. The system of reusable modular construction facilitates not only lower emissions during the first building iteration, but also lower emissions during subsequent iterations that drastically reduce waste and help society meet its climate goals. Many other industries, such as clothing and technology sectors, are starting to focus on circularity and this project adds the residential building construction industry to that list.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Net-Zero Lime Kiln and Carbon Removal Facility

The final scientific/technical report for DE-FE0032248. The Project Objective for DE-FE0032248, Net-Zero Lime Kiln and Carbon Removal Facility, was to execute and complete the initial design of a commercial-scale, advanced carbon capture system that separates CO2 with at least 95% capture efficiency from process streams at the Carmeuse Kentucky (KY) lime plant that will be retrofitted to utilize sustainably sourced biomass (SSB) alone or in combination with natural gas, and/or coal, with at least a 20-year available feedstock supply and remaining asset life.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Dynamic Tripolar Strategic Balance: A Net Assessment (Workshop Summary)

On December 9-10, the Center for Global Security Research (CGSR) at Lawrence Livermore National Laboratory (LLNL) hosted a workshop titled “The Dynamic Tripolar Strategic Balance: A Net Assessment.” The discussion was guided by the following key questions: • By what metrics should the strategic balance be assessed? • How dynamic is the balance? How fragile? • Is the United States gaining strategic advantage, losing it, or holding steady, overall? • In order to gain new advantages or re-gain advantages lost, can or should the United States prioritize some domains and accept more risk in others? If so, which ones?

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Dual-loop Solvent-based CCS for Net Negative CO 2 Emissions with Lower Cost

This final technical report details the successful design, construction, and operational validation of an innovative dual-loop CO 2 capture technology designed to achieve deep decarbonization (>99%) from Natural Gas Combined Cycle (NGCC) power plants that results in the electricity with carbon intensity of approximate 42 kg CO 2 -eq/MWh, less than the electricity produced by solar PV. The integrated process couples a primary aqueous solvent (in this project, a water lean solvent – WLS) absorption loop for bulk CO 2 removal with a secondary potassium hydroxide (KOH) polishing loop featuring electrochemical regeneration. This architecture leverages the higher exergy efficiency of the primary loop while utilizing the fastest kinetic of the secondary loop to capture dilute residual CO 2 , achieving an overall capture rate of 99.9% and co-producing pure hydrogen after moisture being condensed and dehydrated. Technical feasibility was established through a comprehensive 2,000-hour experimental campaign on a bench-scale fully-integrated unit (using 4” absorber and 4” stripper) with the feeding flue gas flowrate in the range of 8-20 cfm, confirming the attainment of Technology Readiness Level (TRL) 4. The project executed extensive parametric testing followed by 1,000 hours of continuous steady-state testing, demonstrating exceptional process stability with the electrochemical regenerator exhibiting less than a 10% reduction in electrical conductivity over the duration of the campaign. Operational characterization gathering on the bench unit revealed distinct energy profiles for the hybrid system: the primary loop required approximately 280 kJ mol -1 for bulk removal, while the polishing loop required approximately 1,600 kJ mol -1 specifically when reducing dilute CO 2 concentrations from ~740 ppm down to <50 ppm. (Please note those energy values/numbers can only be viewed as relative relationship and should not be extrapolated as absolute values required for CO 2 capture). Furthermore, dynamic testing validated the system’s flexibility for utility applications, demonstrating a rapid process response time of <30 minutes to changes in flue gas flowrate. Emission monitoring confirmed that the dual-loop architecture effectively mitigates solvent losses, utilizing a water wash to remove entrained aerosols to <1 ppm. The Techno-Economic Analysis (TEA) indicates a cost of capture of $\$$59.3/tonne and a Levelized Cost of Electricity (LCOE) of 71.7 $\$$/MWh at the overall capture efficiency of 99.8% of total carbon in the flue gas stream, with sensitivity analysis identifying an economic optimum when the primary loop captures 97% of the total CO 2 . A Life Cycle Assessment (LCA) confirms the technology’s potential for net-negative emissions, determining a Global Warming Potential (GWP) of 52 kg CO 2 -eq/MWh—significantly lower than the baseline—which further decreases to 42 kg CO 2 -eq/MWh when crediting the displacement of conventional hydrogen production.

03 NATURAL GAS↗

Soil net nitrogen mineralization and leaching under Miscanthus × giganteus and Zea mays

Research objectives were to compare whether miscanthus ( Miscanthus × giganteus Greef et Deu.) would leach less nitrogen (N) than continue maize ( Zea mays, L.) and how soil net N mineralization (Nmin) may explain observed leaching. The experiment included three factors: 1) cropping system (maize, juvenile miscanthus = 1-2 y old, mature miscanthus = 3-4 y old); 2) N fertilization (0 and 224 kg N ha-1); and 3) environment (four site-years at two locations in Iowa, USA that differed in climate and soil fertility). During the 2017 and 2018 growing seasons a variety of soil measurements, including inorganic soil N (ammonium + nitrate), in situ Nmin, and N leaching were taken to better understand the differences in N cycling dynamics associated with each system.

Agriculture, forestry and fisheries↗

Dynamic subcanopy leaf traits drive resistance of net primary production across a disturbance severity gradient

Across the globe, the forest carbon sink is increasingly vulnerable to an expanding array of low- to moderate-severity disturbances. However, some forest ecosystems exhibit functional resistance (i.e., the capacity of ecosystems to continue functioning as usual) following disturbances such as extreme weather events and insect or fungal pathogen outbreaks. Unlike severe disturbances (e.g., stand-replacing wildfires), moderate severity disturbances do not always result in near-term declines in forest production because of the potential for compensatory growth, including enhanced subcanopy production. Community-wide shifts in subcanopy plant functional traits, prompted by disturbance-driven environmental change, may play a key mechanistic role in resisting declines in net primary production (NPP) up to thresholds of canopy loss. However, the temporal dynamics of these shifts, as well as the upper limits of disturbance for which subcanopy production can compensate, remain poorly characterized. In this study, we leverage a 4-year dataset from an experimental forest disturbance in northern Michigan to assess subcanopy community trait shifts as well as their utility in predicting ecosystem NPP resistance across a wide range of implemented disturbance severities. Through mechanical girdling of stems, we achieved a gradient of severity from 0% (i.e., control) to 45, 65, and 85% targeted gross canopy defoliation, replicated across four landscape ecosystems broadly representative of the Upper Great Lakes ecoregion. We found that three of four examined subcanopy community weighted mean (CWM) traits including leaf photosynthetic rate (p = 0.04), stomatal conductance (p = 0.07), and the red edge normalized difference vegetation index (p < 0.0001) shifted rapidly following disturbance but before widespread changes in subcanopy light environment triggered by canopy tree mortality. Surprisingly, stimulated subcanopy production fully compensated for upper canopy losses across our gradient of experimental severities, achieving complete resistance (i.e., no significant interannual differences from control) of whole ecosystem NPP even in the 85% disturbance treatment. Additionally, we identified a probable mechanistic switch from nutrient-driven to light-driven trait shifts as disturbance progressed. Our findings suggest that remotely sensed traits such as the red edge normalized difference vegetation index (reNDVI) could be particularly sensitive and robust predictors of production response to disturbance, even across compositionally diverse forests. The potential of leaf spectral indices to predict post-disturbance functional resistance is promising given the capabilities of airborne to satellite remote sensing. We conclude that dynamic functional trait shifts following disturbance can be used to predict production response across a wide range of disturbance severities.

resistance↗

Current Developments of Carbon Capture Storage and/or Utilization–Looking for Net-Zero Emissions Defined in the Paris Agreement

An essential line of worldwide research towards a sustainable energy future is the materials and processes for carbon dioxide capture and storage. Energy from fossil fuels combustion always generates carbon dioxide, leading to a considerable environmental concern with the values of CO2 produced in the world. The increase in emissions leads to a significant challenge in reducing the quantity of this gas in the atmosphere. Many research areas are involved solving this problem, such as process engineering, materials science, chemistry, waste management, and politics and public engagement. To decrease this problem, green and efficient solutions have been extensively studied, such as Carbon Capture Utilization and Storage (CCUS) processes. In 2015, the Paris Agreement was established, wherein the global temperature increase limit of 1.5 °C above pre-industrial levels was defined as maximum. To achieve this goal, a global balance between anthropogenic emissions and capture of greenhouse gases in the second half of the 21st century is imperative, i.e., net-zero emissions. Several projects and strategies have been implemented in the existing systems and facilities for greenhouse gas reduction, and new processes have been studied. This review starts with the current data of CO2 emissions to understand the need for drastic reduction. After that, the study reviews the recent progress of CCUS facilities and the implementation of climate-positive solutions, such as Bioenergy with Carbon Capture and Storage and Direct Air Capture. Future changes in industrial processes are also discussed.

Regufe, Maria João (ORCID:0000000327748302)↗

A Method of Ground-Based Cloud Motion Predict: CCLSTM + SR-Net

Ground-based cloud images can provide information on weather and cloud conditions, which play an important role in cloud cover monitoring and photovoltaic power generation forecasting. However, the cloud motion prediction of ground-based cloud images still lacks advanced and complete methods, and traditional technologies based on image processing and motion vector calculation are difficult to predict cloud morphological changes. In this paper, we propose a cloud motion prediction method based on Cascade Causal Long Short-Term Memory (CCLSTM) and Super-Resolution Network (SR-Net). Firstly, CCLSTM is used to estimate the shape and speed of cloud motion. Secondly, the Super-Resolution Network is built based on perceptual losses to reconstruct the result of CCLSTM and, finally, make it clearer. We tested our method on Atmospheric Radiation Measurement (ARM) Climate Research Facility TSI (total sky imager) images. The experiments showed that the method is able to predict the sky cloud changes in the next few steps.

54 ENVIRONMENTAL SCIENCES↗

Global and regional variability and change in terrestrial ecosystems net primary production and NDVI: A model-data comparison

The net primary productivity (NPP) is commonly used for understanding the dynamics of terrestrial ecosystems and their role in carbon cycle. We used a combination of the most recent NDVI and model–based NPP estimates (from five models of the TRENDY project) for the period 1982-2012, to study the role of terrestrial ecosystems in carbon cycle under the prevailing climate conditions. We found that 80% and 67% of the global land area showed positive NPP and NDVI values, respectively, for this period. The global NPP was estimated to be about 63 Pg C y -1 , with an increase of 0.214 Pg C y -1 y -1 . Similarly, the global mean NDVI was estimated to be 0.33, with an increasing trend of 0.00041 y-1. The spatial patterns of NPP and NDVI demonstrated substantial variability, especially at the regional level, for most part of the globe. However, on temporal scale, both global NPP and NDVI showed a corresponding pattern of increase (decrease) for the duration of this study except for few years (e.g. 1990 and 1995-98). Generally, the Northern Hemisphere showed stronger NDVI and NPP increasing trends over time compared to the Southern Hemisphere; however, NDVI showed larger trends in Temperate regions while NPP showed larger trends in Boreal regions. Among the five models, the maximum and minimum NPP were produced by JULES (72.4 Pg C y -1 ) and LPJ (53.72 Pg C y -1 ) models, respectively. At latitudinal level, the NDVI and NPP ranges were ~0.035 y -1 to ~-0.016 y -1 and ~0.10 Pg C y -1 y -1 to ~-0.047 Pg C y -1 y -1 , respectively. Overall, the results of this study suggest that the modeled NPP generally correspond to the NDVI trends in the temporal dimension. Lastly, the significant variability in spatial patterns of NPP and NDVI trends points to a need for research to understand the causes of these discrepancies between molded and observed ecosystem dynamics, and the carbon cycle.

54 ENVIRONMENTAL SCIENCES↗

Phase-dependent Photometric and Spectroscopic Characterization of the MASTER-Net Optical Transient J212444.87+321738.3: An Oxygen-rich Mira

We describe the time-dependent properties of a new spectroscopically confirmed Mira variable, which was discovered in 2013 as MASTER-Net Optical Transient J212444.87+321738.3 toward the Cygnus constellation. We have performed long-term optical/near-infrared (NIR) photometric and spectroscopic observations to characterize the object. From the optical/NIR light curves, we estimate a variability period of 465 ± 30 days. The wavelength-dependent amplitudes of the observed light curves range from ΔI ∼ 4 mag to ΔK ∼ 1.5 mag. The (J − K) color index varies from 1.78 to 2.62 mag over phases. Interestingly, a phase lag of ∼60 days between optical and NIR light curves is also seen, as in other Miras. Our optical/NIR spectra show molecular features of TiO, VO, CO, and strong water bands that are a typical signature of oxygen-rich Mira. We rule out S- or C-type as ZrO bands at 1.03 and 1.06 μm and C{sub 2} band at 1.77 μm are absent. We estimate the effective temperature of the object from the Spectral Energy Distribution, and distance and luminosity from standard Period–Luminosity relations. The optical/NIR spectra display time-dependent atomic and molecular features (e.g., TiO, Na i, Ca i, H{sub 2}O, CO), as commonly observed in Miras. Such spectroscopic observations are useful for studying pulsation variability in Miras.

79 ASTRONOMY AND ASTROPHYSICS↗

APOGEE Net: Improving the Derived Spectral Parameters for Young Stars through Deep Learning

Machine learning allows for efficient extraction of physical properties from stellar spectra that have been obtained by large surveys. The viability of machine-learning approaches has been demonstrated for spectra covering a variety of wavelengths and spectral resolutions, but most often for main-sequence (MS) or evolved stars, where reliable synthetic spectra provide labels and data for training. Spectral models of young stellar objects (YSOs) and low-mass MS stars are less well-matched to their empirical counterparts, however, posing barriers to previous approaches to classify spectra of such stars. In this work, we generate labels for YSOs and low-mass MS stars through their photometry. We then use these labels to train a deep convolutional neural network to predict logg, T {sub eff}, and Fe/H for stars with Apache Point Observatory Galactic Evolution Experiment (APOGEE) spectra in the DR14 data set. This “APOGEE Net” has produced reliable predictions of logg for YSOs, with uncertainties of within 0.1 dex and a good agreement with the structure indicated by pre-MS evolutionary tracks, and it correlates well with independently derived stellar radii. These values will be useful for studying pre-MS stellar populations to accurately diagnose membership and ages.

79 ASTRONOMY AND ASTROPHYSICS↗

Climate change impacts on net primary production (NPP) and export production (EP) regulated by increasing stratification and phytoplankton community structure in the CMIP5 models

Abstract. We examine climate change impacts on net primary production (NPP) and export production (sinking particulate flux; EP) with simulations from nine Earth system models (ESMs) performed in the framework of the fifth phase of the Coupled Model Intercomparison Project (CMIP5). Global NPP and EP are reduced by the end of the century for the intense warming scenario of Representative Concentration Pathway (RCP) 8.5. Relative to the 1990s, NPP in the 2090s is reduced by 2–16 % and EP by 7–18 %. The models with the largest increases in stratification (and largest relative declines in NPP and EP) also show the largest positive biases in stratification for the contemporary period, suggesting overestimation of climate change impacts on NPP and EP. All of the CMIP5 models show an increase in stratification in response to surface–ocean warming and freshening, which is accompanied by decreases in surface nutrients, NPP and EP. There is considerable variability across the models in the magnitudes of NPP, EP, surface nutrient concentrations and their perturbations by climate change. The negative response of NPP and EP to increasing stratification reflects primarily a bottom-up control, as upward nutrient flux declines at the global scale. Models with dynamic phytoplankton community structure show larger declines in EP than in NPP. This pattern is driven by phytoplankton community composition shifts, with reductions in productivity by large phytoplankton as smaller phytoplankton (which export less efficiently) are favored under the increasing nutrient stress. Thus, the projections of the NPP response to climate change are critically dependent on the simulated phytoplankton community structure, the efficiency of the biological pump and the resulting levels of regenerated production, which vary widely across the models. Community structure is represented simply in the CMIP5 models, and should be expanded to better capture the spatial patterns and climate-driven changes in export efficiency.

54 ENVIRONMENTAL SCIENCES↗

Global and northern-high-latitude net ecosystem production in the 21st century from CMIP6 experiments

Climate warming is accelerating the changes in the global terrestrial ecosystems and particularly those in the northern high latitudes (NHLs; poleward of 50° N) and rendering the land–atmosphere carbon exchange highly uncertain. The Coupled Model Intercomparison Project Phase 6 (CMIP6) employs the most updated climate models to estimate terrestrial ecosystem carbon dynamics driven by a new set of socioeconomic and climate change pathways. By analyzing the future (2015–2100) carbon fluxes estimated by 10 CMIP6 models, we quantitatively evaluated the projected magnitudes, trends, and uncertainties in the global and NHL carbon fluxes under four scenarios plus the role of NHLs in the global terrestrial ecosystem carbon dynamics. Overall, the models suggest that the global and NHL terrestrial ecosystems will be consistent carbon sinks in the future, and the magnitude of the carbon sinks is projected to be larger under scenarios with higher radiative forcing. By the end of this century, the models on average estimate the NHL net ecosystem productivity (NEP) as 0.54 ± 0.77, 1.01 ± 0.98, 0.97 ± 1.62, and 1.05 ± 1.83 Pg C yr –1 under SSP126, SSP245, SSP370, and SSP585, respectively. The uncertainties are not substantially reduced compared with earlier results, e.g., the Coupled Climate–Carbon Cycle Model Intercomparison Project (C4MIP). Although NHLs contribute a small fraction of the global carbon sink (~13 %), the relative uncertainties in NHL NEP are much larger than the global level. Our results provide insights into future carbon flux evolutions under future scenarios and highlight the urgent need to constrain the large uncertainties associated with model projections for making better climate mitigation strategies.

54 ENVIRONMENTAL SCIENCES↗

A consistent dataset for the net income distribution for 190 countries and aggregated to 32 geographical regions from 1958 to 2015

Abstract. Data on income distributions within and across countries are becoming increasingly important for informing analysis of income inequality and understanding the distributional consequences of climate change. While datasets on income distribution collected from household surveys are available for multiple countries, these datasets often do not represent the same concept of inequality (or income concept) and therefore make comparisons across countries, over time and across datasets difficult. Here, we present a consistent dataset of income distributions across 190 countries from 1958 to 2015 measured in terms of net income. We complement the observed values in this dataset with values imputed from a summary measure of the income distribution, specifically the Gini coefficient. For the imputation, we use a recently developed nonparametric principal-component-based approach that shows an excellent fit to data on income distributions compared to other approaches. We also present another version of this dataset aggregated from the country level to 32 geographical regions. Our dataset is developed for the purpose of calibrating models such as integrated human–Earth system models with detailed data on income distributions. This dataset will enable more robust analysis of income distribution at multiple scales. The latest version of our data are available on Zenodo: https://doi.org/10.5281/zenodo.7093997 (Narayan et al., 2022b).

97 MATHEMATICS AND COMPUTING↗