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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Towards an open model intercomparison platform for integrated assessment models scenarios

The majority of scenarios in the IPCC database are generated by integrated assessment models (IAMs) and come from model intercomparison projects. However, the way in which the current model intercomparison projects are organized is not open to all IAM teams worldwide. Here we propose a transparent and inclusive platform that is open to anyone with an IAM regarding protocols development, scenario submissions and results evaluation. We discuss the challenges of this approach, particularly human resources and financial support. Here, we identify diversity in the level of model capability and quality of model output as possibly critical issues. Despite such challenges, the IAM community and its scientific activities can improve and benefit from the proposed platform, ultimately contributing to better climate policymaking.

IAM↗
DOE OSTI2024

Decomposing a San Francisco estuary microbiome using long-read metagenomics reveals species- and strain-level dominance from picoeukaryotes to viruses

ABSTRACT Although long-read sequencing has enabled obtaining high-quality and complete genomes from metagenomes, many challenges still remain to completely decompose a metagenome into its constituent prokaryotic and viral genomes. This study focuses on decomposing an estuarine metagenome to obtain a more accurate estimate of microbial diversity. To achieve this, we developed a new bead-based DNA extraction method, a novel bin refinement method, and obtained 150 Gbp of Nanopore sequencing. We estimate that there are ~500 bacterial and archaeal species in our sample and obtained 68 high-quality bins (>90% complete, <5% contamination, ≤5 contigs, contig length of >100 kbp, and all ribosomal and tRNA genes). We also obtained many contigs of picoeukaryotes, environmental DNA of larger eukaryotes such as mammals, and complete mitochondrial and chloroplast genomes and detected ~40,000 viral populations. Our analysis indicates that there are only a few strains that comprise most of the species abundances. IMPORTANCE Ocean and estuarine microbiomes play critical roles in global element cycling and ecosystem function. Despite the importance of these microbial communities, many species still have not been cultured in the lab. Environmental sequencing is the primary way the function and population dynamics of these communities can be studied. Long-read sequencing provides an avenue to overcome limitations of short-read technologies to obtain complete microbial genomes but comes with its own technical challenges, such as needed sequencing depth and obtaining high-quality DNA. We present here new sampling and bioinformatics methods to attempt decomposing an estuarine microbiome into its constituent genomes. Our results suggest there are only a few strains that comprise most of the species abundances from viruses to picoeukaryotes, and to fully decompose a metagenome of this diversity requires 1 Tbp of long-read sequencing. We anticipate that as long-read sequencing technologies continue to improve, less sequencing will be needed.

Lui, Lauren M.↗
DOE OSTI2020

Chapter 4.2 - Preparation of nanoparticles for surface analysis

A variety of methods used to prepare nano-objects for surface analysis are described along with information about when they might be best applied. Intrinsic properties of NPs that complicate their characterization and need to be considered when planning for surface or other analyses of NPs are identified, including challenges associated with reproducible synthesis and functionalization of the particles as well as their dynamic nature. Information about the sample preparation processes, along with analysis data, that need to be added to the collection of material provenance information is identified and examples of protocols that have been successfully used for preparation of nano-objects for surface analysis are included in an annex.

characterization challenges↗
DOE OSTI2022

Statistical framework to assess long-term spatio-temporal climate changes: East River mountainous watershed case study

Abstract Evaluation of long-term temporal and spatial climatic change in mountainous regions is a critical challenge because of the interactive effects of multiple land and climatic factors and processes. Here we present the application of the statistical framework to the assessment of changes of climatic conditions, using data from 17 meteorological stations across the East River watershed near Crested Butte, Colorado, USA, and spanning the period from 1966 to 2021. The framework is developed based on (1) a time-series analysis of daily, monthly, and yearly averaged meteorological parameters (temperature, relative humidity, precipitation, wind speed, etc.), (2) evaluation and time series analysis of potential evapotranspiration (ET o ), actual evapotranspiration (ET), aridity index (AI), standard precipitation index (SPI) and standard precipitation-evapotranspiration index (SPEI), and (3) a temporal-spatial climatic zonation of the studied area based on the hierarchical clustering and PCA analysis of the SPEI, because the SPEI can be considered an integrative characteristic of the changes of climatic conditions. The Budyko model, with the application of the Penman–Monteith equation for the estimation of ET o , was used to determine the ET. The time series analysis of the AI is used to identify the periods with energy limited and water limited conditions. Hierarchical clustering of site locations for the three temporal segments of the SPEI showed a significant temporal-spatial shifts, indicating that dynamic climatic processes drive zonation patterns. Therefore, the watershed climatic zonation requires periodic re-evaluation based on the structural time series analysis of meteorological and water balance data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Effects of raster terrain representation on GIS shortest path analysis

Spatial analysis extracts meaning and insights from spatially referenced data, where the results are highly dependent on the quality of the data used and the manipulations on the data when preparing it for analysis. Users should understand the impacts that data representations may have on their results in order to prevent distortions in their outcomes. We study the consequences of two common data preparations when locating a linear feature performing shortest path analysis on raster terrain data: 1) the connectivity of the network generated by connecting raster cells to their neighbors, and 2) the range of the attribute scale for assigning costs. Such analysis is commonly used to locate transmission lines, where the results could have major implications on project cost and its environmental impact. Experiments in solving biobjective shortest paths show that results are highly dependent on the parameters of the data representations, with exceedingly variable results based on the choices made in reclassifying attributes and generating networks from the raster. Based on these outcomes, we outline recommendations for ensuring geographic information system (GIS) data representations maintain analysis results that are accurate and unbiased.

Medrano, F. Antonio (ORCID:000000025913632X)↗
DOE OSTI2021

Data, Modeling, & Analysis

The project goal includes developing model pathways to improve sustainability of feedstock supply chains to reduce access costs and the environmental footprint. The project aims to harness synergies of production and collection practices and current systems to improve economic and environmental outcomes.

09 BIOMASS FUELS↗
DOE OSTI2024

Plastic Parallel Pathways Platform- 4P Model

The U.S. generates 42 million metric tons of plastic waste each year - the most of any country - of which less than 9% is recycled. This represents an estimated loss of $2.3 billion and 3.4 EJ embodied energy per year. Plastic use reduction, reuse and recycling are thus increasingly important, but making informed policy and research decisions within this space can be challenging given the diverse range of available solutions. Various recycling and waste management options are available for plastics, such as conversion into energy (incineration, pyrolysis, gasification), conversion to lower- or higher-grade plastics (mechanical recycling, chemical or enzymatic depolymerization processes, dissolution) or up-cycling to feedstock chemicals (photo/electro/catalytic methods, pyrolysis, gasification). While many previous publications have investigated a subset of these options, there is currently no modelling platform that can quantitatively assess and compare the economic and environmental impacts of all these different plastic management pathways and their respective products simultaneously. To directly compare the benefits and disadvantages of plastic-to-x technologies, we propose a novel analysis framework: the Plastic Parallel Pathways Platform (4P). 4P will model a systems analysis framework for capturing plastic material flows processed via different waste management scenarios. The total economic cost and greenhouse gas emissions (as well as additional economic, energetic, and environmental metrics indicators) of a given scenario will be calculated enabling comparison to other scenarios, thereby informing decisions on plastic recycling pathways.

circular economy↗
DOE OSTI2020

Assessing health and environmental impacts of solvents for producing perovskite solar cells

Halide perovskites are poised as a game-changing semiconductor system with diverse applications in optoelectronics. Industrial entities aim to commercialize perovskite technologies because of high performance but also because this type of semiconductor can be processed from solution, a feature enabling low cost and fast production. In this work, we analyse the health and environmental impacts of eight solvents commonly used in perovskite processing. We consider first- and higher-order ramifications of each solvent on an industrial scale such as solvent production, use/removal, emissions and potential end-of-life treatments. Further, we consider the energy of evaporation for each solvent, air emission, condensation and subsequent incineration, reuse or distillation for solvent recycling, and apply a full end-of-life analysis. For human health impact, we use the ‘USEtox’ method but also consider toxicity data beyond carcinogenic classifications. We find that dimethyl sulfoxide has the lowest total impact, by being the most environmentally friendly and least deleterious to human health of the solvents considered. The analysis of the effects of these solvents on human health and the environment provides guidance for sustainable development of this new technology.

14 SOLAR ENERGY↗
DOE OSTI2022

USEEIO v2.0, The US Environmentally-Extended Input-Output Model v2.0

USEEIO v2.0 is an environmental-economic model of US goods and services that can be used for life cycle assessment, footprinting, national prioritization, and related applications. This paper describes the development of the model and accompanies the release of a full model dataset as well as various supporting datasets of national environmental totals by US industry. Novel methodological elements since USEEIO v1 models include waste sector disaggregation, final demand vectors for US consumption and production, a domestic form of the model that can be used to separate domestic and foreign impacts, and price adjustment matrices for converting outputs to purchaser price and in various US dollar years. Improvements in modeling national totals of industry and environmental flows are described. The model is validated through reproduction of national totals from input data sources and through analysis of changes from the most recent complete USEEIO model that can be explained based on data updates or method changes. The model datasets can all be reproduced with open source software packages.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Improving Time Step Convergence in an Atmosphere Model With Simplified Physics: The Impacts of Closure Assumption and Process Coupling

Convergence testing is a common practice in the development of dynamical cores of atmospheric models but is not as often exercised for the parameterization of sub-grid physics. An earlier study revealed that the stratiform cloud parameterizations in several predecessors of the Energy Exascale Earth System Model (E3SM) showed strong time-step sensitivity and slower-than-expected convergence when the model's time step was systematically refined. In this work, a simplified atmosphere model is configured that consists of the spectral-element dynamical core of the E3SM atmosphere model coupled with a large-scale condensation parameterization based on commonly used assumptions. This simplified model also resembles E3SM and its predecessors in the numerical implementation of process coupling and shows poor time-step convergence in short ensemble tests. We present a formal error analysis to reveal the expected time-step convergence rate and the conditions for obtaining such convergence. Numerical experiments are conducted to investigate the root causes of convergence problems. We show that revisions in the process coupling and closure assumption help to improve convergence in short simulations using the simplified model; the same revisions applied to a full atmosphere model lead to significant changes in the simulated long-term climate. This work demonstrates that causes of convergence issues in atmospheric simulations can be understood by combining analyses from physical and mathematical perspectives. Addressing convergence issues can help to obtain a discrete model that is more consistent with the intended representation of the physical phenomena.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Time series methods for the analysis of soundscapes and other cyclical ecological data

Biodiversity monitoring has entered an era of ‘big data’, exemplified by a near-continuous collection of sounds, images, chemical and other signals from organisms in diverse ecosystems. Such data streams have the potential to help identify new threats, assess the effectiveness of conservation interventions, as well as generate new ecological insights. However, appropriate analytical methods are often still missing, particularly with respect to characterizing cyclical temporal patterns. Here, we present a framework for characterizing and analysing ecological responses that represent nonstationary, complex temporal patterns and demonstrate the value of using Fourier transforms to decorrelate continuous data points. In our example, we use a framework based on three approaches (spectral analysis, magnitude squared coherence, and principal component analysis) to characterize differences in tropical forest soundscapes within and across sites and seasons in Gabon. By reconstructing the underlying, cyclic behaviour of the soundscape for each site, we show how one can identify circadian patterns in acoustic activity. Soundscapes in the dry season had a complex diel cycle, requiring multiple harmonics to represent daily variation, while in the wet season there was less variance attributable to the daily cyclic patterns. Our framework can be applied to most continuous, or near-continuous ecological data collected at a fine temporal resolution, allowing ecologists to explore patterns of temporal autocorrelation at multiple levels for biologically meaningful trends. Such methods will become indispensable as biological big data are used to understand the impact of anthropogenic pressures on biodiversity and to inform efforts to mitigate them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Investigating the Unique Ability of Trichodesmium To Fix Carbon and Nitrogen Simultaneously Using MiMoSA

The open ocean is an extremely competitive environment, partially due to the dearth of nutrients. Trichodesmium erythraeum, a marine diazotrophic cyanobacterium, is a keystone species in the ocean due to its ability to fix nitrogen and leak 30 to 50% into the surrounding environment, providing a valuable source of a necessary macronutrient to other species. While there are other diazotrophic cyanobacteria that play an important role in the marine nitrogen cycle, Trichodesmium is unique in its ability to fix both carbon and nitrogen simultaneously during the day without the use of specialized cells called heterocysts to protect nitrogenase from oxygen. Here, we use the advanced modeling framework called multiscale multiobjective systems analysis (MiMoSA) to investigate how Trichodesmium erythraeum can reduce dimolecular nitrogen to ammonium in the presence of oxygen. Our simulations indicate that nitrogenase inhibition is best modeled as Michealis-Menten competitive inhibition and that cells along the filament maintain microaerobia using high flux through Mehler reactions in order to protect nitrogenase from oxygen. We also examined the effect of location on metabolic flux and found that cells at the end of filaments operate in distinctly different metabolic modes than internal cells despite both operating in a photoautotrophic mode. These results give us important insight into how this species is able to operate photosynthesis and nitrogen fixation simultaneously, giving it a distinct advantage over other diazotrophic cyanobacteria because they can harvest light directly to fuel the energy demand of nitrogen fixation.

09 BIOMASS FUELS↗
DOE OSTI2020

SNPeffect: identifying functional roles of SNPs using metabolic networks

Genetic sources of phenotypic variation have been a focus of plant studies aimed at improving agricultural yield and understanding adaptive processes. Genome-wide association studies identify the genetic background behind a trait by examining associations between phenotypes and single-nucleotide polymorphisms (SNPs). Although such studies are common, biological interpretation of the results remains a challenge; especially due to the confounding nature of population structure and the systematic biases thus introduced. Here, we propose a complementary analysis (SNPeffect) that offers putative genotype-to-phenotype mechanistic interpretations by integrating biochemical knowledge encoded in metabolic models. SNPeffect is used to explain differential growth rate and metabolite accumulation in A. thaliana and P. trichocarpa accessions as the outcome of SNPs in enzyme-coding genes. To this end, we also constructed a genome-scale metabolic model for Populus trichocarpa, the first for a perennial woody tree. As expected, our results indicate that growth is a complex polygenic trait governed by carbon and energy partitioning. The predicted set of functional SNPs in both species are associated with experimentally characterized growth-determining genes and also suggest putative ones. Functional SNPs were found in pathways such as amino acid metabolism, nucleotide biosynthesis, and cellulose and lignin biosynthesis, in line with breeding strategies that target pathways governing carbon and energy partition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Assessing the Effectiveness of Large-Scale Environmental Restoration: Challenges and Opportunities

A recent National Academies consensus report addresses monitoring and assessment of cumulative effects of large-scale and multiple restoration projects within the context of long-term environmental change. Fines and penalties from the Deepwater Horizon oil spill in the Gulf of Mexico (GoM) have supported hundreds of restoration projects at spatial scales not often possible in the past. Here, in this paper, the report committee members and staff provide personal reflections from our time working on the study. We found that gaps in data collection, issues with data accessibility, and a lack of synthesis and analysis are hindering the ability to answer a basic question: What are the impacts of these many restoration efforts on improving ecosystem health and productivity in the GoM at the regional and Gulf wide scale? Restoration efforts are occurring in environments where many trends are changing and exhibiting higher variability than in the past, suggesting that previously successful restoration practices may no longer be adequate to compensate for the effects of environmental changes and variability. Our proposed approach to these challenges includes employing emerging monitoring technologies; using conceptual models; devising an adaptive management framework; rethinking restoration outcome goals; assessing cumulative effects; and undertaking rigorous synthesis and analysis of existing information on long-term environmental trends and restoration efforts. Restoration scientists and practitioners working in the GoM have an unprecedented opportunity to demonstrate large-scale environmental recovery if advances in monitoring, synthesis, assessment, and action are taken quickly. We are cautiously optimistic that, with mid-course adjustments, continued progress toward large-scale environmental recovery is possible.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Retrofit Energy Analysis and Central Thermal modeling (REACT) v1.0

REACT is a website designed to simplify the analysis and decision-making process for retrofitting existing central plant heating and cooling systems with advanced heat pump technologies. The tool evaluates the technical and economic viability of replacing traditional boilers with various options including water-to-water or air-to-water heat pumps, which can provide efficient and lower-cost heating and cooling. It allows users to compare current central plant configurations with retrofit scenarios, assessing energy consumption, life-cycle costs, and environmental impact. Retrofitting traditional boiler and chiller systems with water-to-water or air-to-water heat pumps can significantly reduce energy consumption and lower lifecycle costs. The REACT provides: User-Friendly Tools: A user friendly web interface for quick, intuitive analysis accessible to non-experts. Advanced Modeling: A Python-powered engine for detailed parametric studies, optimization, and research applications. Comprehensive Analysis: Lifecycle cost evaluation, energy consumption modeling, and environmental impact assessment. Visual Insights: A variety of plots to visualize system performance and design trade-offs. The engine for the website (REACT) bases on several Python libraries, and the website will be hosted on an ETA server.

Kim, Donghun [Lawrence Berkeley National Laborator↗
DOE OSTI2022

Molten salt electrolysis and room temperature ionic liquid electrochemical processes for refining rare earth metals: Environmental and economic performance comparison

Circularizing end of life products such as electronic waste can open a new source for rare earth elements (REEs) that will decrease the demand pressure on conventional virgin production. The last step to produce REEs consists of a refining process to convert rare earth oxide (REO) to REE metal. One promising technology is processing REO via a room temperature ionic liquid, which is characterized by low energy requirements in contrast to existing REEs extraction processes. In this work, life cycle and techno-economic assessments are performed and compared against molten salt electrolysis. Here, the results show that both processes have advantages and disadvantages in terms of environmental performance, and that they are similarly competitive in terms of economic performance. A breakeven analysis suggests that future research should focus on coupling the production of REOs with the refining processes to attempt to lower REO cost and make them economically feasible in the U.S.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Integrating Flow Imaging Analysis and Single-Particle ICP-TOFMS for Comprehensive Micro- and Nanoplastic Characterization

Flow imaging analysis (FIA), provides composition-agnostic morphological characterization. These measurements of particle size and shape are valuable to mass-based analysis, such as single particle inductively coupled plasma time-of-flight mass spectrometry (sp-ICP-TOFMS), which provides quantitative data on elements within particles. Using these two methods together enables informed use of geometric assumptions required by sp-ICP-TOFMS, as particle mass is typically converted to a particle diameter using assumed-spherical geometry. To validate this concept, parallel measurements to determine particle diameters were performed by FIA and sp-ICP-TOFMS on four particle suspensions: 300 nm polystyrene Eu-doped nanoparticles, 1 μm Fe-rich beads, 3 μm four element calibration polystyrene beads and 5 μm polystyrene beads. The Fe-particles obtained the highest percent difference from the manufacturer’s nominal diameter, as the mean diameter obtained by FIA was overestimated by 21% and sp-ICP-TOFMS underestimated the mean diameter by 20.7%. Two types of particles were selected to test the effect of varying the particle number concentrations (PNC) on sizing accuracy, and both methods accurately sized each particle population at the PNC expected. Single particle analysis of carbon has continued to be a popular research topic, with direct applications to environmental pollutants in terms of nano- and micro- plastics. Real-world plastic particles were studied, and FIA’s measured circularity values demonstrated that the particles deviated from spherical geometries, therefore sp-ICP-TOFMS data should be interpreted as mass-based rather than size-based. Combining these techniques enables improved interpretation of particle populations and evaluation of particle sizes.

Szakas, Sarah [ORNL] (ORCID:0000000241332197)↗
DOE OSTI2021

Techno-Economic Analysis and Life Cycle Assessment of Waste Lignin Fractionation and Valorization Using the ALPHA Process

Techno-Economic Analysis (TEA) and Life Cycle Assessment (LCA) were performed on the Aqueous Lignin Purification with Hot Agents (ALPHA) process, which is being investigated for the fractionation and purification of raw, bulk lignins recovered from cellulosic ethanol biorefineries or Kraft pulp mills. Here, ALPHA is proposed for the isolation of lignin from a corn stover-to-ethanol plant into purified low, medium, and high molecular weight (MW) fractions for producing polyurethane foam, activated carbon, and carbon fiber, respectively. A scenario analysis was conducted to determine the effect of ALPHA solvent choice on process economics and environmental performance. Solvent choice was found to have a significant impact on ALPHA, with a minimum selling price of 838/tonne with use of acetic acid vs 463/tonne with ethanol. Conversion of the lignin, processed with ethanol solvent, to high-value products yields 151 million/year in profit, which over 30 years results in a total net present value of 533 million. A life cycle assessment was conducted to determine the “gate-to-gate” greenhouse gas emissions and energy consumption of the lignin-based products compared to fossil-based equivalents. In conclusion, a value allocation scenario was conducted and it was determined that products generated using the ALPHA process with ethanol have similar or lower greenhouse gas emissions than the same products from fossil feedstocks.

09 BIOMASS FUELS↗