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DOE OSTI2021

The Evolving Solar Energy Innovation Ecosystem in Puerto Rico

This report presents initial findings from the research project, “Developing socially and economically generative, resilient PV-energy systems for low- and moderate-income communities: Applications for Puerto Rico.” This material is based upon work supported primarily by the US Department of Energy’s Office of Energy Efficiency and Renewable Energy under the Solar Energy Technology Office Fiscal Year 2018 Funding Program award number DE-EE0008570 and in part by the National Science Foundation (NSF) and the Department of Energy (DOE) under NSF CA No. EEC-1041895. This project is a joint effort of Arizona State University’s Center for Energy and Society; the University of Puerto Rico-Mayaguez’s Center for Hemispheric Cooperation in Research and Education in Engineering and Applied Science, Sustainable Energy Center, and National Institute for Energy and Island Sustainability; and the National Renewable Energy Laboratory. The project seeks to understand the place of energy in low-income communities in Puerto Rico, the opportunities for solar energy to provide solutions to the energy challenges facing these communities, and the capacity of the solar energy innovation ecosystem in Puerto Rico to deliver relevant solar solutions for these communities. We define the solar energy innovation ecosystem as the diverse actors and stakeholders whose collective networks and actions—and the flows among them of ideas, knowledge, data, influence, money, and equipment, as well as the rules that govern those flows—are essential to the success of renewable energy markets and projects. This report presents results from the first year of the project’s research, which has concentrated on several key goals: (1) characterizing the trajectory of solar energy development in Puerto Rico in the three years since Hurricane María; (2) mapping and characterizing the current solar energy innovation ecosystem in Puerto Rico, including the technical potential for solar energy in Puerto Rico, and the business and policy landscape shaping solar developments; and (3) beginning to characterize the broad landscape of community energy initiatives underway in Puerto Rico. To pursue these goals, we engaged in a systematic review of solar energy developments in Puerto Rico and conducted interviews with over 100 members of the solar energy innovation, including policy, business, finance, research, and civil society leaders, as well as solar users. Solar technical potential data for Puerto Rico was developed by the National Renewable Energy Laboratory (NREL) and is publicly available at: https://data.nrel.gov/submissions/144. The documentation for the NREL dataset is included as Appendix A.

14 SOLAR ENERGY↗

DOE OSTI2020

Robust paths to net greenhouse gas mitigation and negative emissions via advanced biofuels

Biofuel and bioenergy systems are integral to most climate stabilization scenarios for displacement of transport sector fossil fuel use and for producing negative emissions via carbon capture and storage (CCS). However, the net greenhouse gas mitigation benefit of such pathways is controversial due to concerns around ecosystem carbon losses from land use change and foregone sequestration benefits from alternative land uses. Here, we couple bottom-up ecosystem simulation with models of cellulosic biofuel production and CCS in order to track ecosystem and supply chain carbon flows for current and future biofuel systems, with comparison to competing land-based biological mitigation schemes. Analyzing three contrasting US case study sites, we show that on land transitioning out of crops or pasture, switchgrass cultivation for cellulosic ethanol production has per-hectare mitigation potential comparable to reforestation and severalfold greater than grassland restoration. In contrast, harvesting and converting existing secondary forest at those sites incurs large initial carbon debt requiring long payback periods. We also highlight how plausible future improvements in energy crop yields and biorefining technology together with CCS would achieve mitigation potential 4 and 15 times greater than forest and grassland restoration, respectively. Finally, we show that recent estimates of induced land use change are small relative to the opportunities for improving system performance that we quantify here. While climate and other ecosystem service benefits cannot be taken for granted from cellulosic biofuel deployment, our scenarios illustrate how conventional and carbon-negative biofuel systems could make a near-term, robust, and distinctive contribution to the climate challenge.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Produced Water DNA Database (PW-DNA): Utilizing KBase to generate an environmental specific curated molecular database

The deep subsurface is estimated to host the majority of Earth’s microbial biomass yet remains one of the most challenging environments to access and study. One common approach to investigate these microbial communities is through the analysis of produced water from subsurface reservoirs, where researchers can assess water and gas chemistry along with molecular (DNA/RNA) sequence data. Advances in high-throughput sequencing have greatly expanded our understanding of these environments and their biotechnological potential. However, further progress requires large-scale, integrative meta-analyses across diverse datasets. To address this need, we developed the Produced Water-DNA (PW-DNA) Database, a curated, publicly available resource that consolidates microbial DNA/RNA sequences, geochemical data, and relevant metadata from in situ hydrocarbon environments such as coal beds, oil reservoirs, and natural gas systems. The PW-DNA database delivers three core benefits to the research community: (1) it improves data sharing by linking environmental microbial datasets with corresponding geochemical parameters, enabling more robust filtering and analysis; (2) it connects with complementary research databases to promote broader dissemination and interoperability; and (3) it supports technological innovation by serving as a resource for identifying microbial trends and exploring genetic potential. While individual studies have highlighted basin-specific microbial communities and functional redundancy in biogeochemical cycling, a comprehensive, system-wide perspective is needed to better understand connectivity and novelty across subsurface ecosystems. By designing the PW-DNA in the KBase platform, we provide a reproducible, visual framework for integrating large-scale genomic and geochemical data, enabling researchers to perform more informed analyses and experimental design. Ultimately, this resource enhances the ability to identify, characterize, and interpret microbial functions across diverse subsurface environments, thereby accelerating discovery in subsurface microbiology and biotechnology.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Identifying preferential flow from soil moisture time series: Review of methodologies

Abstract Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for continuous monitoring and are relatively easy to implement, these methods have become an important tool for recognizing when, where, and under what conditions PF occurs. The methods seek to identify a pattern or quantification that indicates the occurrence of PF. Most commonly, the chosen signature is either (1) a nonsequential response to infiltrated water, in which soil moisture responses do not occur in order of shallowest to deepest, or (2) a velocity criterion, in which newly infiltrated water is detected at depth earlier than is possible by nonpreferential flow processes. Alternative signatures have also been developed that have certain advantages but are less commonly utilized. Choosing among these possible signatures requires attention to their pertinent characteristics, including susceptibility to errors, possible bias toward false negatives or false positives, reliance on subjective judgments, and possible requirements for additional types of data. We review 77 studies that have applied such methods to highlight important information for readers who want to identify PF from soil moisture data and to inform those who aim to develop new methods or improve existing ones. Core Ideas Soil moisture data can be used to identify the occurrence of preferential flow (PF) and its initiating conditions. Various data‐analysis methods to identify PF differ in susceptibility to error, bias, and subjectivity. These methods can utilize vast amounts of data from soil moisture monitoring networks to develop understanding of when, where, and under what conditions PF occurs. Newly developed methods may lead to better accuracy and reliability, and reduce the need for subjective judgments. Plain Language Summary Preferential flow through soil occurs when a large amount of water is suddenly available, as during an intense storm. This type of flow moves rapidly through the soil in distinct narrow pathways rather than moving evenly throughout the body of soil, with major consequences for groundwater resources, ecosystems, spreading of contaminants, and other vital concerns. Methods of detecting preferential flow have been developed that utilize measurements of soil water content made by sensors installed at various depths. This measurement technology has been widely implemented, many locations now having datasets years in length, and various methods have been developed for using these to identify preferential flow. The various methods are based on different features in the soil moisture records and vary in their advantages and shortcomings. In this review, we explain and evaluate these methods, highlighting important information for their implementation to identify preferential flow from soil moisture data and for efforts to develop new methods or improve existing ones.

Nimmo, John R↗

DOE OSTI2024

Printed Potentiometric Ammonium Sensors for Agriculture Applications

Ammonium (NH 4 + ) concentration is critical to both nutrient availability and nitrogen (N) loss in soil ecosystems but can be highly variable across spatial and temporal scales. For this reason, effectively informing agricultural practices such as fertilizer management and understanding of mechanisms of soil N loss require sensor technologies to monitor ammonium concentrations in real time. Our work investigates the performance of fully printed ammonium ion-selective sensors used in diverse soil environments. Ammonium sensors consisting of a printed ammonium ion-selective electrode and a printed Ag/AgCl reference were fabricated and characterized in aqueous solutions and three different soil types (sand, peat, and clay) under the range of ion concentrations likely to be present in soil (0.01–100 mM). The response of ammonium sensors was further evaluated under variable gravimetric moisture content in the soil to reflect their reliability under field conditions. Ammonium sensors demonstrated a sensitivity of 53.6 ± 5.1 mV/decade when tested in aqueous solution, and a sensitivity of 55.7 ± 11 mV/dec, 57.5 ± 4.1 mV/dec, and 43.7 ± 4 mV/dec was measured in sand, clay, and peat soils, respectively.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

A multi-omic future for microbiome studies

Microbes constitute about a third of the Earth’s biomass and play critical roles in sustaining life. While results from multiple sequence-based studies have illustrated the importance of microbial communities for human health and the environment, additional technological developments are still needed to gain more insight into their functions [1]. To date, the majority of sequencing studies have focused on the 16S rRNA gene as a phylogenetic marker. This approach has enabled exploration of microbial compositions in a range of sample types, while bypassing the need for cultivation. 16S rRNA gene sequencing has also enabled a vast majority of microorganisms never previously isolated in culture to be identified and placed into a phylogenetic context [2]. These technologies have been utilized to map the locations of microbes inhabiting various locations of the body [3]. Similarly, sequencing has been used to determine the identities and distributions of microorganisms inhabiting different ecosystems [4, 5], and efforts in single cell sequencing of the microbiome have helped fill in missing branches of the phylogenetic tree [6].

Environmental Molecular Sciences Laboratory↗

DOE OSTI2016

VOLTTRON™: Tech-to-Market Best-Practices Guide for Small- and Medium-Sized Commercial Buildings

VOLTTRON™ is an open-source distributed control and sensing platform developed by Pacific Northwest National Laboratory for the U.S. Department of Energy. It was developed to be used by the Office of Energy Efficiency and Renewable Energy to support transactive controls research and deployment activities. VOLTTRON is designed to be an overarching integration platform that could be used to bring together vendors, users, and developers and enable rapid application development and testing. The platform is designed to support modern control strategies, including the use of agent- and transaction-based controls. It also is designed to support the management of a wide range of applications, including heating, ventilation, and air-conditioning systems; electric vehicles; and distributed-energy and whole-building loads. This report was completed as part of the Building Technologies Office’s Technology-to-Market Initiative for VOLTTRON’s Market Validation and Business Case Development efforts. The report provides technology-to-market guidance and best practices related to VOLTTRON platform deployments and commercialization activities for use by entities serving small- and medium-sized commercial buildings. The report characterizes the platform ecosystem within the small- and medium-sized commercial building market and articulates the value proposition of VOLTTRON for three core participants in this ecosystem: 1) platform owners/adopters, 2) app developers, and 3) end-users. The report also identifies key market drivers and opportunities for open platform deployments in the small- and medium-sized commercial building market. Possible pathways to the market are described—laboratory testing to market adoption to commercialization. We also identify and address various technical and market barriers that could hinder deployment of VOLTTRON. Finally, we provide “best practice” tech-to-market guidance for building energy-related deployment efforts serving small- and medium-sized commercial buildings.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1975

Continued urbanization of the United States is causing the deterioration of the central city; costly suburban developments; and increases in congestion, pollution, crime, violence and alienation

It is shown that urban sprawl and the abuses of technological industries result in substantial environmental and economic costs at the expense of center city locations and populations. Socioeconomic deterioration and modification of the biosphere triggers climatic and environmental changes leading to ecosystem damage and destruction, health consequences and international conflict.

Source record↗

NASA NTRS2014

The Ecosystems SAR (EcoSAR) an Airborne P-band Polarimetric InSAR for the Measurement of Vegetation Structure, Biomass and Permafrost

EcoSAR is a new synthetic aperture radar (SAR) instrument being developed at the NASA/ Goddard Space Flight Center (GSFC) for the polarimetric and interferometric measurements of ecosystem structure and biomass. The instrument uses a phased-array beamforming architecture and supports full polarimetric measurements and single pass interferometry. This Instrument development is part of NASA's Earth Science Technology Office Instrument Incubator Program (ESTO IIP).

SAR↗

NASA NTRS2020

Snow and Water Imaging Spectrometer: Final Instrument Characterization

The Snow and Water Imaging Spectrometer (SWIS) is a science-grade imaging spectrometer and telescope system suitable for CubeSat applications, spanning a 350-1700 nm spectral range with 5.7 nm sampling, a 10 degree field of view and 0.3 mrad spatial resolution. The system operates at F/1.8, providing high throughput for low-reflectivity water surfaces, while avoiding saturation over bright snow or clouds. The SWIS design utilizes heritage from previously demonstrated instruments on airborne platforms, while advancing the state of the art in compact sensors of this kind in terms of size and spectral coverage. Through frequent repeat observations from space at a moderate spatial resolution, SWIS can address key science questions concerning aquatic and terrestrial ecosystem changes, cryosphere warming and melt behavior, cloud and atmospheric science, and potential impacts of climate change and human activities on the environment. We review the optical design and innovations and key technologies developed for this instrument, as well as its measured optical performance. We discuss the radiometric calibration characterization, including detector linearity, flat field correction, and SNR. Finally, we discuss stray light modeling and the development of a focused ghost removal algorithm, which is tested and supported by laboratory results.

Bellardo, John↗

DOE OSTI2022

In Hot Water! The Challenges and Barriers of Decarbonizing Water Heating in Multifamily Buildings: Preprint

Domestic hot water heating is responsible for 32% of the total energy consumption in multifamily buildings and offers a significant decarbonization opportunity. An extensive market assessment was conducted to understand and document key technical and economic barriers to electrification of domestic water heating in multifamily buildings throughout the U.S. Through the program, 77 interviews were conducted to understand key market drivers and technical challenges associated with electrification of water heating systems in both retrofit and new construction scenarios. Interviewees encompassed a wide range of stakeholders in the ecosystem surrounding water heating systems, including suppliers, manufacturers, designers, owners, utilities, and developers. This paper documents key interview takeaways, including an extensive list of market barriers, technical challenges, and sought-after technology attributes that can inform pertinent design criteria for electric water heating research, development, and deployment efforts. Among economics and energy efficiency features, interviewees overwhelmingly alluded to space constraints, cold air exhaust, and lack of clear guidance regarding distributed versus centralized design selections as key challenges associated with mass adoption of electric water heating. Owners and developers seek systems with minimal footprint, which maximize rentable space and profits. Moreover, distributed heat pump solutions should balance ducting costs that mitigate cold exhaust entrainment into conditioned zones. Lastly, the market needs clear guidance regarding the selection of distributed versus central electric hot water systems.

challenges of water heating electrification↗

DOE OSTI2020

Plant science decadal vision 2020–2030: Reimagining the potential of plants for a healthy and sustainable future

Abstract Plants, and the biological systems around them, are key to the future health of the planet and its inhabitants. The Plant Science Decadal Vision 2020–2030 frames our ability to perform vital and far‐reaching research in plant systems sciences, essential to how we value participants and apply emerging technologies. We outline a comprehensive vision for addressing some of our most pressing global problems through discovery, practical applications, and education. The Decadal Vision was developed by the participants at the Plant Summit 2019, a community event organized by the Plant Science Research Network. The Decadal Vision describes a holistic vision for the next decade of plant science that blends recommendations for research, people, and technology. Going beyond discoveries and applications, we, the plant science community, must implement bold, innovative changes to research cultures and training paradigms in this era of automation, virtualization, and the looming shadow of climate change. Our vision and hopes for the next decade are encapsulated in the phrase reimagining the potential of plants for a healthy and sustainable future. The Decadal Vision recognizes the vital intersection of human and scientific elements and demands an integrated implementation of strategies for research (Goals 1–4), people (Goals 5 and 6), and technology (Goals 7 and 8). This report is intended to help inspire and guide the research community, scientific societies, federal funding agencies, private philanthropies, corporations, educators, entrepreneurs, and early career researchers over the next 10 years. The research encompass experimental and computational approaches to understanding and predicting ecosystem behavior; novel production systems for food, feed, and fiber with greater crop diversity, efficiency, productivity, and resilience that improve ecosystem health; approaches to realize the potential for advances in nutrition, discovery and engineering of plant‐based medicines, and "green infrastructure." Launching the Transparent Plant will use experimental and computational approaches to break down the phytobiome into a "parts store" that supports tinkering and supports query, prediction, and rapid‐response problem solving. Equity, diversity, and inclusion are indispensable cornerstones of realizing our vision. We make recommendations around funding and systems that support customized professional development. Plant systems are frequently taken for granted therefore we make recommendations to improve plant awareness and community science programs to increase understanding of scientific research. We prioritize emerging technologies, focusing on non‐invasive imaging, sensors, and plug‐and‐play portable lab technologies, coupled with enabling computational advances. Plant systems science will benefit from data management and future advances in automation, machine learning, natural language processing, and artificial intelligence‐assisted data integration, pattern identification, and decision making. Implementation of this vision will transform plant systems science and ripple outwards through society and across the globe. Beyond deepening our biological understanding, we envision entirely new applications. We further anticipate a wave of diversification of plant systems practitioners while stimulating community engagement, underpinning increasing entrepreneurship. This surge of engagement and knowledge will help satisfy and stoke people's natural curiosity about the future, and their desire to prepare for it, as they seek fuller information about food, health, climate and ecological systems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Polar primary aerosols across the ocean-sea ice-snow-atmosphere interface: From sources to impacts

Primary aerosols play a critical role in polar climate systems, influencing cloud formation, precipitation, radiative balance, and surface energy budgets. This paper provides a comprehensive synthesis of primary aerosol sources, transformation and removal processes, and broader atmospheric impacts in polar regions, emphasizing their links to ocean and sea ice biogeochemistry. These aerosols (including sea salt, primary organic aerosol, and primary biological aerosol particles) originate from marine and cryospheric environments and are emitted through physical processes, such as wave breaking, bubble bursting, and blowing snow. Emission sources include seawater, sea ice, snow, and freshwater from river discharge and glacial runoff. Once airborne, these particles can serve as a chemical reservoir, influencing atmospheric composition and reactivity, and as seeds for cloud droplet and ice crystal formation, influencing cloud microphysics and polar climate. Despite their importance, many of the processes governing primary aerosol emissions and transformations remain poorly constrained. The most pressing knowledge gaps pertain to emission processes, limited spatiotemporal observational coverage, instrumentation constraints, parameterization development, and the integration of interdisciplinary expertise. To improve our understanding of primary aerosol drivers and their response to climate, future research efforts should prioritize strategically coordinated and cross-disciplinary process studies, advancements in measurement technologies and coverage, and close collaboration between modelers and observational scientists to inform and refine model parameterizations. As polar regions continue to undergo profound changes marked by increased precipitation, reduced sea and land ice, freshening oceans, and shifting ecosystem dynamics, characterizing present-day primary aerosol populations is vital. Improved understanding will be essential for anticipating future changes in aerosol-radiation and aerosol-cloud interactions and their implications for polar and global climate systems.

Aerosol-cloud↗

DOE OSTI2014

An Integrated Study to Analyze Soil Microbial Community Structure and Metabolic Potential in Two Forest Types

Soil microbial metabolic potential and ecosystem function have received little attention owing to difficulties in methodology. In this study, we selected natural mature forest and natural secondary forest and analyzed the soil microbial community and metabolic potential combing the high-throughput sequencing and GeoChip technologies. Phylogenetic analysis based on 16S rRNA sequencing showed that one known archaeal phylum and 15 known bacterial phyla as well as unclassified phylotypes were presented in these forest soils, and Acidobacteria, Protecobacteria, and Actinobacteria were three of most abundant phyla. The detected microbial functional gene groups were related to different biogeochemical processes, including carbon degradation, carbon fixation, methane metabolism, nitrogen cycling, phosphorus utilization, sulfur cycling, etc. The Shannon index for detected functional gene probes was significantly higher (P<0.05) at natural secondary forest site. The regression analysis showed that a strong positive (P<0.05) correlation was existed between the soil microbial functional gene diversity and phylogenetic diversity. Mantel test showed that soil oxidizable organic carbon, soil total nitrogen and cellulose, glucanase, and amylase activities were significantly linked (P<0.05) to the relative abundance of corresponded functional gene groups. Variance partitioning analysis showed that a total of 81.58% of the variation in community structure was explained by soil chemical factors, soil temperature, and plant diversity. Therefore, the positive link of soil microbial structure and composition to functional activity related to ecosystem functioning was existed, and the natural secondary forest soil may occur the high microbial metabolic potential. Although the results can’t directly reflect the actual microbial populations and functional activities, this study provides insight into the potential activity of the microbial community and associated feedback responses of the terrestrial ecosystem to environmental changes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Enhancing Clean Energy Innovation Ecosystem Discovery Tool

During March 2016, the DOE’s Office of Energy Policy and Systems Analysis (EPSA) sought a methodology to identify and quantify the strength of the existing clean energy innovation ecosystems (IE) in the U.S. and their characteristics. Oak Ridge National Lab (ORNL) did a pilot study (Phase 1) and demonstrated the feasibility of an application comprised of natural language processing, link analysis, and other computational techniques to transform text and numerical data into metrics on clean energy innovation activity and geography. The data-collection, ingest and analytics pipelines were combined with an advanced user interface, together known as the Ecosystem Discovery Tool, to enhance DOE’s understanding of existing geographic innovation clusters. During Phase 2 of this project, this tool has been further enhanced by integrating new data sets and through backend software architecture changes, validation and bug fixing, making it a much more robust and powerful application. The tool’s user interface is a lot more intuitive, which enables a user to visualize the IE rankings for various geographic regions(CBSA, state level) for different clean energy technologies and seek automated insights. ORNL also created a DOE-specific dashboard that allows the user to visualize and analyze federal funding from various offices including Energy Efficiency and Renewable Energy(EERE), Office of Electricity(OE), Fossil Energy(FE), and Nuclear Energy(NE). During Phase 1 of this project, EPSA defined a clean energy innovation ecosystem as the overlap of five Ecosystem Components: 1) nascent clean energy Indicators, 2) investors, 3) enabling environment, 4) networking assets and 5) large companies. EPSA and ORNL worked together to collect data for each component: 1) small and medium companies, ARPA-E awardees, SBIR awardees, patents, publications, ERCs for Nascent Clean Energy Indicators; 2) qualified investors; 3) the Clean Edge Policy Index/DSIRE for the Enabling Environment; 4) universities, national laboratories, ERCs and incubators for Networking Assets; and 5) large companies and a subset of the Russell 1000 list for Large Companies. The ORNL team created a visual tool based on Tableau that integrated ecosystem component data to score, rank and map IEs. The tool was created with the flexibility to allow the user to choose the weights of each of the five ecosystem components and the subcomponents. This flexibility allows the user to visualize different subsets and to use the underlying data for different types of analysis. During Phase 2 of this project, the backend database and computation process have undergone major changes to provide a much more refined user-interface and added new features into the scoring algorithm. This phase also involved addition of newer databases such as a list of Energy Research Centers (ERC) ,DSIRE, and funding data from EERE, FE, NE, and OE to provide more granular information and more accurate/better quantification.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

Evaluating the environmental sustainability of biomass-based energy strategy: Using an impact matrix framework

A roadmap for a more sustainable energy strategy is complex, as its development interacts critically with the economic, social, and environmental dimensions of sustainable development. This paper applied an impact matrix method to evaluate the environmental sustainability and to identify the desirable policy objectives of biomass-based energy strategy for the case of Alberta. A matrix with the sustainability domains on one axis and areas of environmental impact on the other was presented to evaluate the nexus effect of policy objectives and bioenergy production. As per to our analysis, economic diversification, technological innovation, and resource conservation came up as the desirable policy objectives of sustainable development for Alberta because they demonstrated environmental benefits in all environmental impact categories, namely climate change, human health, and ecosystem. On the other hand, human health and ecosystem impacts were identified as trade-offs when the policy objectives for sustainability were energy security, job creation, and climate change. Thus, bioenergy can mitigate climate change but may impact human health and ecosystem which then in turn can become issues of concern. Energy strategies may result in shifting of risks from one environmental impact category to another, and from one sustainable domain to another if the technical and policy-related issues are not identified.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

HP-LSP: A reference of land surface phenology from fused Harmonized Landsat and Sentinel-2 with PhenoCam data

Abstract Land surface phenology (LSP) products are currently of large uncertainties due to cloud contaminations and other impacts in temporal satellite observations and they have been poorly validated because of the lack of spatially comparable ground measurements. This study provided a reference dataset of gap-free time series and phenological dates by fusing the Harmonized Landsat 8 and Sentinel-2 (HLS) observations with near-surface PhenoCam time series for 78 regions of 10 × 10 km 2 across ecosystems in North America during 2019 and 2020. The HLS-PhenoCam LSP (HP-LSP) reference dataset at 30 m pixels is composed of: (1) 3-day synthetic gap-free EVI2 (two-band Enhanced Vegetation Index) time series that are physically meaningful to monitor the vegetation development across heterogeneous levels, train models (e.g., machine learning) for land surface mapping, and extract phenometrics from various methods; and (2) four key phenological dates (accuracy ≤5 days) that are spatially continuous and scalable, which are applicable to validate various satellite-based phenology products (e.g., global MODIS/VIIRS LSP), develop phenological models, and analyze climate impacts on terrestrial ecosystems.

Science & Technology - Other Topics↗

DOE OSTI2023

A Large Ensemble Global Dataset for Climate Impact Assessments

We present a self-consistent, large ensemble, high-resolution global dataset of long-term future climate, which accounts for the uncertainty in climate system response to anthropogenic emissions of greenhouse gases and in geographical patterns of climate change. The dataset is developed by applying an integrated spatial disaggregation (SD) - bias-correction (BC) method to climate projections from the MIT Integrated Global System Model (IGSM). Four emission scenarios are considered that represent energy and environmental policies and commitments of potential future pathways, namely, Reference, Paris Forever, Paris 2 °C and Paris 1.5 °C. The dataset contains nine key meteorological variables on a monthly scale from 2021 to 2100 at a spatial resolution of 0.5°x 0.5°, including precipitation, air temperature (mean, minimum and maximum), near-surface wind speed, shortwave and longwave radiation, specific humidity, and relative humidity. We demonstrate the dataset’s ability to represent climate-change responses across various regions of the globe. This dataset can be used to support regional-scale climate-related impact assessments of risk across different applications that include hydropower, water resources, ecosystem, agriculture, and sustainable development.

54 ENVIRONMENTAL SCIENCES↗