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DOE OSTI2022

GREET-Based Interactive Life-Cycle Assessment of Biofuel Pathways: User Manual

An interactive, web-based tool was developed to streamline the process design for biofuel pathways that the Department of Energy’s (DOE) Bioenergy Technologies Office (BETO) is developing. The tool utilizes the latest life-cycle analysis (LCA) data in the Greenhouse gases, Regulated Emissions, and Energy use in Technologies (GREET) model developed by Argonne National Laboratory (Argonne National Laboratory, 2021). It provides techno-economic analysis (TEA) modelers with a interative interface that generates real-time LCA results based on life-cycle inventory (LCI) data and generates useful insights into key emissions drivers. Economic implications of the LCA results are also included in the tool. Overall, the tool aims to assist TEA researchers with the development of economically viable and environmentally beneficial biofuel technologies. This manual introduces the interface and analysis capabilities of the tool.

09 BIOMASS FUELS↗
DOE OSTI2024

Life Cycle Inventory Availability: Status and Prospects for Leveraging New Technologies

The demand for life cycle assessments (LCA) is growing rapidly, which leads to an increasing demand of life cycle inventory (LCI) data. While the LCA community has made significant progress in developing LCI databases for diverse applications, challenges still need to be addressed. This perspective summarizes the current data gaps, transparency, and uncertainty aspects of existing LCI databases. Additionally, we survey and discuss novel techniques for LCI data generation, dissemination, and validation. We propose key future directions for LCI development efforts to address these challenges, including leveraging scientific and technical advances such as the Internet of Things (IoT), machine learning, and blockchain/cloud platforms. Adopting these advanced technologies can significantly improve the quality and accessibility of LCI data, thereby facilitating more accurate and reliable LCA studies.

blockchain platforms↗
DOE OSTI2020

Task 12 PV Sustainability - Life Cycle Inventories and Life Cycle Assessments of Photovoltaic Systems

Life Cycle Assessment (LCA) is a structured, comprehensive method of quantifying material- and energy-flows and their associated impacts in the life cycles of products (i.e., goods and services). One of the major goals of IEA PVPS Task 12 is to provide guidance on assuring consistency, balance, transparency and quality of LCA to enhance the credibility and reliability of the results. The current report presents the latest consensus life cycle inventories among the authors, PV LCA experts in North America, Europe, Asia and Australia. At this time consensus is limited to four technologies for which there are well-established and up-to-date life cycle inventory (LCI) data (mono- and multi-crystalline Si, CdTe, CIGS, as well as one emerging technology (perovskite silicon tandem). LCIs are necessary for LCA and the availability of such data is often the greatest barrier for conducting LCA. The Task 12 LCA experts have put great efforts in gathering and compiling the LCI data presented in this report. These include detailed inputs and outputs during manufacturing of cell, wafer, module, and balance-of-system (i.e., structural and electrical components) that were estimated from actual production and operation facilities. In addition, data are presented to enable analyses of various types of PV installations; these include operational data of rooftop and ground-mount PV systems and country-specific PV-mixes. The LCI datasets presented in this report are the latest that are available to the public describing the status in 2018 for crystalline Si (some manufacturing data from 2011 were not updated), 2015 and 2017-2018 for CdTe, 2010 for CIGS, 2010 for HCPV, and 2017 for perovskite silicon tandem technology.

14 SOLAR ENERGY↗
DOE OSTI2025

Uncertainty in inventories for life cycle assessment: State‐of‐the‐art, challenges, and new technologies

Uncertainty is a critical factor that can hinder the quality and potential applications of life cycle assessment (LCA) results. A prominent source of uncertainty stems from the life cycle inventory (LCI) data. Various methodologies exist to estimate the uncertainty associated with LCI data, primarily based on the widely used structured pedigree matrix approach or the computationally intensive Monte Carlo simulation. This perspective review explores how new technologies (e.g., computational algorithms and data collection methods) from data science and related fields can contribute to identifying, quantifying, and reducing uncertainty in LCI modeling. A brief overview of the sources of uncertainty in LCI modeling and how they are addressed in current LCA practice is provided. Additionally, several new technologies are identified, and the potential benefits of their implementation in reducing uncertainties in LCI modeling are discussed. This perspective review concludes by identifying potential areas that require further development for these technologies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Comparative Life Cycle Analysis of Scalable Single-Junction and Tandem Perovskite Solar Cell (PSC) Systems

Efficient, low-cost solar cells based upon perovskites have the potential to transform the US and global energy portfolio and improve energy security if they can be manufactured in an environmentally sustainable manner. However, previous life cycle analyses (LCA) of perovskite solar cells (PSC) used lab recipes to project the environmental impact of industrial PSC production – using materials and processes that may not be representative of industrial productions due to high material waste and complex synthesis – and such studies were limited to a few single-junction technologies. Thus, the goal of this project was threefold: a) to review the most promising for industrial production single-junction and tandem PSC technologies, b) to build life-cycle materials inventories that reflect scalable production of these technologies, and c) to conduct comprehensive life-cycle analysis of these technologies and compare their environmental impact with those of established commercial technologies. In response, this project identified challenges for fabrication transitioning from laboratory to sustainable industrial production, developed life-cycle inventory (LCI) data for scaling to industrial production four promising single-junction and three tandem PSC systems and produced life-cycle-investigations using, as metrics, a complete spectrum of energy, environmental and ecological impact indicators. Special focus was given to the use of lead, silver and indium in PSC. The project used the Life Cycle Assessment (LCA) methodology as standardized by the Society of Environmental Toxicology and Chemistry (SETAC), ISO standards 14040 and 14044, and the International Energy Agency PVPS Task 12 LCA guidelines. LCA allows the calculation of a number of energy and environmental and impact categories, including energy cumulative energy demand (CED), global warming potential (GWP), human toxicity potential (HTP), eco-toxicity potential (ETP), abiotic resource depletion potential (ADP), acidification potential (AP), ozone depletion potential (ODP), photochemical oxidation potential (POP), eutrophication potential (EP). In addition to those, we calculated the Energy Pay-Back Time (EPBT) and the Energy Return On Investment (EROI). We provide LCA impacts for complete perovskite PV systems – including balance of system components – installed at three irradiation levels and considering reference and future potential module efficiencies. Finally, a sensitivity analysis on perovskite lifetime has been performed, considering 10, 20 and 30 years. Contribution analysis of the impacts of each material and layer of PSC shows, that the use of Pb in metalorganic PSC does not result in significant environmental impacts as the major contributions to environmental indicators arise from the use of Ag and encapsulation materials. Solution-based PSC manufacturing was found to be less impactful to the environment than vapor-based fabrication, and roll-to-roll (RtR) printing uses less energy and generates the lowest emissions. PSC produced with RtR manufacturing could reach the same Energy Return on Energy Investment (EROI) as that of crystalline-Si PV within 12 years of life, whereas the most energy demanding spray coating on rigid substrates, would require a 20-yr life to match the EROI of 30-yr lasting silicon PV. This work lays the foundation for sustainability investigations in a comparative context of large-scale production and deployment of PSC. The results of this project have the potential to have a significant impact on the future of PV manufacturing, by providing industry, policy-makers, and academia with insights necessary to choose which, if any, lead-based solar cell life cycles are environmentally sustainable.

14 SOLAR ENERGY↗
DOE OSTI2022

Clean Energy Education and Training Resources and Opportunities in New York's Southern Tier Region

New York's Southern Tier Region is experiencing high growth and investment in the clean energy sector and is anticipating more jobs to come in energy efficiency, renewable energy, and manufacturing in the coming years. The Network for a Sustainable Tomorrow (NEST) is a nonprofit network of programs working to develop a regional backbone system for education and training programs as well as curricula to support the workforce needed for the region's growing industries to succeed. Through its participation in the US Department of Energy's Better Buildings Workforce Accelerator, NEST requested technical assistance in conducting a landscape and needs assessment of the region's existing clean energy education and workforce development assets. This report supports NEST's efforts by providing a baseline of clean energy employment data, an inventory and gap analysis of the education and workforce development assets currently available and serving the Southern Tier Region, and case studies of innovative and successful regional clean energy education and workforce coalitions from around the county.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Life Cycle Analysis of Greenhouse Gas Emissions of Clean Fuels with the R&D GREET 2024 Model

This document summarizes research on the life cycle greenhouse gas (GHG) emissions rates from the production and use of clean fuels to support a new version of the Research and Development Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (R&D GREET) model, R&D GREET 2024 In this effort, Argonne National Laboratory (ANL) focuses on clean fuel pathways that are readily available in the market or are emerging in the near term. The selected pathways represent clean fuel technologies that convert biomass- and/or waste-based feedstocks to liquid and/or gaseous fuels for the transportation sector and other potential uses. The pathways are configured in R&D GREET 2024 with up-to-date feedstock-to-fuel life cycle inventory (LCI) data. Additionally, a new tab has been added to R&D GREET 2024 called “Clean Fuels” which allows the user to easily change inputs and access LCA results. Argonne does not warrant that the results presented in this report are consistent with the requirements of any particular regulatory or incentive program. Users interested in specific programs that reference GREET are encouraged to review guidance specific to those programs if and when it is available to determine appropriate means of compliance and contact the relevant responsible agencies for those specific policies or programs.

09 BIOMASS FUELS↗
DOE OSTI2025

Expansion and Update of the R&D Feedstock Carbon Intensity Calculator (FD-CIC) for R&D GREET 2025

The R&D Feedstock Carbon Intensity Calculator (R&D FD-CIC) is a transparent and easy-touse tool to estimate feedstock-specific carbon intensity (CI) of biofuel feedstocks, and to examine potential CI variations of different farming practices to grow agricultural feedstocks for biofuel production. The objective of the tool is to assess potential effects of different farming practices with underlined factors to reduce uncertainties in such assessment and help R&D activities. The original work and early versions of R&D FD-CIC were supported by Advanced Research Projects Agency–Energy (ARPA-E) of the Department of Energy, with recent support by the Bioenergy Technologies Office of the Department of Energy. The tool uses life cycle inventory (LCI) data of key farming inputs from the R&D Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) model. The system boundary of R&D FD-CIC covers the cradle-to-farm-gate activities, including upstream emissions related to farming input manufacturing and feedstock production.

09 BIOMASS FUELS↗
DOE OSTI2022

Soil Temperature and Moisture, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2016-2023

Daily averages of soil temperature and moisture measured once every hour at different heights located at Intensive Monitoring Stations at Teller Road Mile Marker 27 site. Data are retrieved annually from 2016-2023. This is the final update to this dataset: no changes to previous data files with the addition of 2022-2023 data files. Data files have header rows, NaN fields indicate invalid or missing data, and negative vertical offsets are above ground. UPDATED 2025-07: Seven new data files collected in 2022-2023 were added and no previously archived data were changed. This represents the final collection of data and text in the title was changed to reflect the defined timespan. Other files that were added: file-level metadata, a data dictionary, a site location map, and a data file inventory by year. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Sensitivity of Regional WRF‐Chem Air Quality and Weather Simulations to Biomass‐Burning Emission Data Sets: A Case Study of the Impact of Canadian Wildfire on the US°

This study focuses on the period from June 26 to 29, 2023, when record‐breaking Canadian wildfires severely impacted air quality in the Midwest United States. Using the Weather Research and Forecasting Model with Chemistry (WRF‐Chem) and four biomass‐burning data sets (Fire Inventory from NCAR version 1, Fire Inventory from NCAR version 2.5, Quick Fire Emissions Data set [QFED], and Regional ABI‐VIIRS Emission), we analyzed aerosol transport from Canada to the US and assessed the model's accuracy in predicting PM 2.5 , O 3 , CO and aerosol weather feedback. Model simulations were compared with ground‐based and remote sensing observations as well as field measurements from the Community Research on Climate and Urban Science (CROCUS) project. Our findings show that the movement of a low‐pressure system from the Great Lakes to the Atlantic, combined with the high‐pressure system over the Atlantic, caused the transport of aerosols from Canadian wildfires to the US. Results show WRF‐Chem significantly underestimated key atmospheric components: aerosol optical depth (AOD) by over 50%, PM 2.5 by 65%–90% and peak O 3 concentrations by 50%–55% across four biomass burning data sets. Additionally, CO and NO 2 concentrations were underpredicted. The substantial underestimation of PM 2.5 led to an overestimation of temperature by up to 3.6 °C primarily due to excessive downward shortwave radiation, which resulted from the underestimation of direct aerosol effects and an increase in sensible heat flux. Among the biomass‐burning data sets, QFED produced the most accurate AOD and PM 2.5 predictions due to improved wildfire emission estimates, leading to a 1.0 to 1.5 °C reduction in temperature overestimation during the daytime. These findings underscore the need for improving wildfire emission estimates for trace gases and aerosols to enhance air quality and weather feedback predictions.

WRF-chem model↗
DOE OSTI2023

The HTAP_v3 emission mosaic: merging regional and global monthly emissions (2000–2018) to support air quality modelling and policies

This study, performed under the umbrella of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP), responds to the global and regional atmospheric modelling community's need of a mosaic emission inventory of air pollutants that conforms to specific requirements: global coverage, long time series, spatially distributed emissions with high time resolution, and a high sectoral resolution. The mosaic approach of integrating official regional emission inventories based on locally reported data, with a global inventory based on a globally consistent methodology, allows modellers to perform simulations of high scientific quality while also ensuring that the results remain relevant to policymakers. HTAP_v3, an ad hoc global mosaic of anthropogenic inventories, has been developed by integrating official inventories over specific areas (North America, Europe, Asia including Japan and South Korea) with the independent Emissions Database for Global Atmospheric Research (EDGAR) inventory for the remaining world regions. The results are spatially and temporally distributed emissions of SO 2 , NO $x$ , CO, non-methane volatile organic compounds (NMVOCs), NH 3 , PM 10 , PM 2.5 , black carbon (BC), and organic carbon (OC), with a spatial resolution of 0.1º × 0.1º and time intervals of months and years, covering the period 2000–2018. The emissions are further disaggregated into 16 anthropogenic emitting sectors. This paper describes the methodology applied to develop such an emission mosaic, reports on source allocation, differences among existing inventories, and best practices for the mosaic compilation. One of the key strengths of the HTAP_v3 emission mosaic is its temporal coverage, enabling the analysis of emission trends over the past 2 decades. The development of a global emission mosaic over such long time series represents a unique product for global air quality modelling and for better-informed policymaking, reflecting the community effort expended by the TF-HTAP to disentangle the complexity of transboundary transport of air pollution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The HTAP_v3.2 emission mosaic: merging regional and global monthly emissions (2000–2020) to support air quality modelling and policies

This study, performed under the umbrella of the Task Force on Hemispheric Transport of Air Pollution (TF-HTAP), responds to the need of the global and regional atmospheric modelling community of having a mosaic emission inventory of air pollutants that conforms to specific requirements: global coverage, long time series, spatially distributed emissions with high time resolution, and a high sectoral resolution. The mosaic approach of integrating official regional emission inventories based on locally reported data, with a global inventory based on a globally consistent methodology, allows modellers to perform simulations of a high scientific quality while also ensuring that the results remain relevant to policymakers. HTAP_v3.2, an ad-hoc global mosaic of anthropogenic inventories, is an update to the HTAP_v3 global mosaic inventory and has been developed by integrating official inventories over specific areas (North America, Europe, Asia including China, Japan and Korea) with the independent Emissions Database for Global Atmospheric Research (EDGAR) inventory for the remaining world regions. The results are spatially and temporally distributed emissions of SO 2 , NO x , CO, NMVOC, NH 3 , PM 10 , PM 2.5 , Black Carbon (BC), and Organic Carbon (OC), with a spatial resolution of 0.1 × 0.1° and time intervals of months and years covering the period 2000–2020 (https://doi.org/10.5281/zenodo.17086684, Crippa, 2025, https://edgar.jrc.ec.europa.eu/dataset_htap_v32, last access: 27 October 2025). The emissions are further disaggregated to 16 anthropogenic emitting sectors. This paper describes the methodology applied to develop such an emission mosaic, reports on source allocation, differences among existing inventories, and best practices for the mosaic compilation. One of the key strengths of the HTAP_v3.2 emission mosaic is its temporal coverage, enabling the analysis of emission trends over the past two decades. The development of a global emission mosaic over such long time series represents a unique product for global air quality modelling and for better-informed policy making, reflecting the community effort expended by the TF-HTAP to disentangle the complexity of transboundary transport of air pollution.

Guizzardi, Diego [European Commission, Ispra (Ital↗
DOE OSTI2025

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Tree Inventory

This is the tree inventory (diameter, species, and live/dead status) data from the Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment is part of the COMPASS-FME (Coastal Observations, Mechanisms, and Predictions Across Systems and Scales: Field Measurements and Experiments; see https://compass.pnnl.gov/FME/COMPASSFME) project. It addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in eastern Maryland, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments.This dataset includes:- An overall dataset README file.- The tree inventory data in both "wide" and "long" forms. These contain the same information but are structured differently, with the former more useful for human viewers and the latter more amenable for programmatic analyses.- A key to the species/genus codes used, which follow the U.S. Department of Agriculture's PLANTS schema (https://plants.usda.gov/).- A copy of the R code used to generate the wide- and long-form data files.All files are comma-separated value (CSV) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

City and County Commercial Building Inventories

The Commercial Building Inventories provide modeled data on commercial building type, vintage, and area for each U.S. city and county. Please note this data is modeled and more precise data may be available through county assessors or other sources. Commercial building stock data is estimated using CoStar Realty Information, Inc. building stock data. This data is part of a suite of state and local energy profile data available at the "State and Local Energy Profile Data Suite" link below and builds on Cities-LEAP energy modeling, available at the "EERE Cities-LEAP Page" link below. Examples of how to use the data to inform energy planning can be found at the "Example Uses" link below.

Array↗
DOE OSTI2020

A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): an application of the Community Emissions Data System (CEDS)

Global anthropogenic emission inventories remain vital for understanding the sources of atmospheric pollution and the associated impacts on the environment, human health, and society. Rapid changes in today's society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx; CO; SO2; NH3; non-methane volatile organic compounds, NMVOCs; black carbon, BC; organic carbon, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture; energy generation; industrial processes; on-road and non-road transportation; separate residential, commercial, and other sectors (RCO); waste; solvent use; and international shipping) and four fuel categories (total coal, solid biofuel, the sum of liquid-fuel and natural-gas combustion, and remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes monthly global gridded (0.5°?×?0.5°) emission fluxes for each compound, sector, and fuel type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default scaling procedure, and modifications to the final procedures for emissions gridding and aggregation. Relative to the previous CEDS inventory (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel types and source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), and emissions from the waste sector. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS (last access: 1 December 2020). The CEDSGBD-MAPS emission inventory dataset (both annual country-total and monthly global gridded files) is publicly available under https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020c).

Mcduffie, Erin↗
DOE OSTI2023

Data Steward Team Wall-to-Wall Inventory Status Update October - December 2023 [Slides]

7 Wall-to-wall inventories were completed between October 2 – December 11, 2023. The team viewed 12 technical areas. A total of 280 containers were verified against current WCATS data. We worked with WMCs team to schedule for all waste throughout WFO FOD. WMCs are doing an incredible job with keeping up with all their locations; The team only found one discrepancy that was resolved the same day, and The WMC also took the time to explain their process on how containers are labeled with closure days and why it was labeled as such.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Data Steward Team Wall-To-Wall Inventory Status Update July - September 2023 [Slides]

8 Wall-to-wall inventories were completed between July 3rd – September 20th, 2023. The scheduling was broken down by FODs, and the team completed UI and IF. The team viewed 12 sites across 7 technical areas. A total of 249 containers were verified against current WCATS data. 2 containers were unable to be verified due to lack of WMC response. We worked with WMCs and Environmental Stewardship teams this quarter to schedule the wall-to-wall inventories. Discrepancies that were found were fixed by the WMCs in a timely manner. Most of the discrepancies were Labeling issues which were resolved the day of the walk down or within a week.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗