Results for “Pm” — Page 66

DOE OSTI2026

1DPA

This is the mechanical testing data archive from a neutron irradiation campaign of nuclear structural alloys fabricated by powder metallurgy with hot isostatic pressing (PM-HIP). Data in this archive include uniaxial tensile testing data, fractography of selected tensile bars, and nanoindentation. The irradiation campaign was designed to facilitate a direct comparison of PM-HIP to conventional casting or forging. Five common nuclear structural alloys were included in the campaign: 316L stainless steel, SA508 pressure vessel steel, Grade 91 ferritic steel, and Ni-base alloys 625 and 690. Irradiations were carried out in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) to target doses of 1 and 3 displacements per atom (dpa) at target temperatures of 300ºC and 400ºC through the DOE Office of Nuclear Energy, Nuclear Science User Facilities (NSUF) project 15-8242.

Wharry, Janelle↗

DOE OSTI2026

3DPA

This is the mechanical testing data archive from a neutron irradiation campaign of nuclear structural alloys fabricated by powder metallurgy with hot isostatic pressing (PM-HIP). Data in this archive include uniaxial tensile testing data, fractography of selected tensile bars, and nanoindentation. The irradiation campaign was designed to facilitate a direct comparison of PM-HIP to conventional casting or forging. Five common nuclear structural alloys were included in the campaign: 316L stainless steel, SA508 pressure vessel steel, Grade 91 ferritic steel, and Ni-base alloys 625 and 690. Irradiations were carried out in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) to target doses of 1 and 3 displacements per atom (dpa) at target temperatures of 300ºC and 400ºC through the DOE Office of Nuclear Energy, Nuclear Science User Facilities (NSUF) project 15-8242.

Wharry, Janelle↗

DOE OSTI2026

UNIRRADIATED

This is the mechanical testing data archive from a neutron irradiation campaign of nuclear structural alloys fabricated by powder metallurgy with hot isostatic pressing (PM-HIP). Data in this archive include uniaxial tensile testing data, fractography of selected tensile bars, and nanoindentation. The irradiation campaign was designed to facilitate a direct comparison of PM-HIP to conventional casting or forging. Five common nuclear structural alloys were included in the campaign: 316L stainless steel, SA508 pressure vessel steel, Grade 91 ferritic steel, and Ni-base alloys 625 and 690. Irradiations were carried out in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) to target doses of 1 and 3 displacements per atom (dpa) at target temperatures of 300ºC and 400ºC through the DOE Office of Nuclear Energy, Nuclear Science User Facilities (NSUF) project 15-8242.

Wharry, Janelle↗

DOE OSTI2026

UNIRRADIATED

This is the mechanical testing data archive from a neutron irradiation campaign of nuclear structural alloys fabricated by powder metallurgy with hot isostatic pressing (PM-HIP). Data in this archive include uniaxial tensile testing data, fractography of selected tensile bars, and nanoindentation. The irradiation campaign was designed to facilitate a direct comparison of PM-HIP to conventional casting or forging. Five common nuclear structural alloys were included in the campaign: 316L stainless steel, SA508 pressure vessel steel, Grade 91 ferritic steel, and Ni-base alloys 625 and 690. Irradiations were carried out in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) to target doses of 1 and 3 displacements per atom (dpa) at target temperatures of 300ºC and 400ºC through the DOE Office of Nuclear Energy, Nuclear Science User Facilities (NSUF) project 15-8242.

Wharry, Janelle↗

DOE OSTI2020

Using machine learning to derive cloud condensation nuclei number concentrations from commonly available measurements

Cloud condensation nuclei (CCN) number concentrations are an important aspect of aerosol–cloud interactions and the subsequent climate effects; however, their measurements are very limited. We use a machine learning tool, random decision forests, to develop a random forest regression model (RFRM) to derive CCN at 0.4 % supersaturation ([CCN0.4]) from commonly available measurements. The RFRM is trained on the long-term simulations in a global size-resolved particle microphysics model. Using atmospheric state and composition variables as predictors, through associations of their variabilities, the RFRM is able to learn the underlying dependence of [CCN0.4] on these predictors, which are as follows: eight fractions of PM 2.5 (NH 4 , SO 4 , NO 3, secondary organic aerosol (SOA), black carbon (BC), primary organic carbon (POC), dust, and salt), seven gaseous species (NO x , NH 3 , O 3 , SO 2 , OH, isoprene, and monoterpene), and four meteorological variables (temperature (T), relative humidity (RH), precipitation, and solar radiation). The RFRM is highly robust: it has a median mean fractional bias (MFB) of 4.4 % with ≈96.33 % of the derived [CCN0.4] within a good agreement range of -60% 2.5 speciation (NH 4 , SO 4 , NO 3 , and organic carbon (OC)), NO x , O 3 , SO 2 , T, and RH, as well as [CCN0.4] are available. We modify, optimize, and retrain the developed RFRM to make predictions from 19 to 9 of these available predictors. This retrained RFRM (RFRM-ShortVars) shows a reduction in performance due to the unavailability and sparsity of measurements (predictors); it captures the [CCN0.4] variability and magnitude at SGP with ≈67.02 % of the derived values in the good agreement range. This work shows the potential of using the more commonly available measurements of PM 2.5 speciation to alleviate the sparsity of CCN number concentrations' measurements.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A global study of hygroscopicity-driven light-scattering enhancement in the context of other in situ aerosol optical properties

The scattering and backscattering enhancement factors (ƒ(RH) and ƒ b (RH)) describe how aerosol particle light scattering and backscattering, respectively, change with relative humidity (RH). They are important parameters in estimating direct aerosol radiative forcing (DARF). In this study we use the dataset presented in Burgos et al. (2019) that compiles ƒ(RH) and ƒ b (RH) measurements at three wavelengths (i.e., 450, 550 and 700 nm) performed with tandem nephelometer systems at multiple sites around the world. We present an overview of ƒ(RH) and ƒ b (RH) based on both long-term and campaign observations from 23 sites representing a range of aerosol types. The scattering enhancement shows a strong variability from site to site, with no clear pattern with respect to the total scattering coefficient. In general, higher ƒ(RH) is observed at Arctic and marine sites, while lower values are found at urban and desert sites, although a consistent pattern as a function of site type is not observed. The backscattering enhancement ƒ b (RH) is consistently lower than ƒ(RH) at all sites, with the difference between ƒ(RH) and ƒ b (RH) increasing for aerosol with higher ƒ(RH). This is consistent with Mie theory, which predicts higher enhancement of the light scattering in the forward than in the backward direction as the particle takes up water. Our results show that the scattering enhancement is higher for PM 1 than PM 10 at most sites, which is also supported by theory due to the change in scattering efficiency with the size parameter that relates particle size and the wavelength of incident light. At marine-influenced sites this difference is enhanced when coarse particles (likely sea salt) predominate. For most sites, ƒ(RH) is observed to increase with increasing wavelength, except at sites with a known dust influence where the spectral dependence of ƒ(RH) is found to be low or even exhibit the opposite pattern. The impact of RH on aerosol properties used to calculate radiative forcing (e.g., single-scattering albedo, ω 0 , and backscattered fraction, b) is evaluated. The single-scattering albedo generally increases with RH, while b decreases. The net effect of aerosol hygroscopicity on radiative forcing efficiency (RFE) is an increase in the absolute forcing effect (negative sign) by a factor of up to 4 at RH = 90 % compared to dry conditions (RH < 40 %). Because of the scarcity of scattering enhancement measurements, an attempt was made to use other more commonly available aerosol parameters (i.e., ω 0 and scattering Ångström exponent, α sp ) to parameterize ƒ(RH). The majority of sites (75 %) showed a consistent trend with ω 0 (higher ƒ(RH = 85 %) for higher ω 0 ), while no clear pattern was observed between ƒ(RH = 85 %) and αsp. This suggests that aerosol ω 0 is more promising than α sp as a surrogate for the scattering enhancement factor, although neither parameter is ideal. Nonetheless, the qualitative relationship observed between ω 0 and ƒ(RH) could serve as a constraint on global model simulations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

MIXv2: a long-term mosaic emission inventory for Asia (2010–2017)

The MIXv2 Asian emission inventory is developed under the framework of the Model Inter-Comparison Study for Asia (MICS-Asia) Phase IV and produced from a mosaic of up-to-date regional emission inventories. We estimated the emissions for anthropogenic and biomass burning sources covering 23 countries and regions in East, Southeast and South Asia and aggregated emissions to a uniform spatial and temporal resolution for seven sectors: power, industry, residential, transportation, agriculture, open biomass burning and shipping. Compared to MIXv1, we extended the dataset to 2010–2017, included emissions of open biomass burning and shipping, and provided model-ready emissions of SAPRC99, SAPRC07, and CB05. A series of unit-based point source information was incorporated covering power plants in China and India. A consistent speciation framework for non-methane volatile organic compounds (NMVOCs) was applied to develop emissions by three chemical mechanisms. The total Asian emissions for anthropogenic/open biomass sectors in 2017 are estimated as follows: 41.6/1.1 Tg NO x , 33.2/0.1 Tg SO 2 , 258.2/20.6 Tg CO, 61.8/8.2 Tg NMVOC, 28.3/0.3 Tg NH 3 , 24.0/2.6 Tg PM 10 , 16.7/2.0 Tg PM 2.5 , 2.7/0.1 Tg BC (black carbon), 5.3/0.9 Tg OC (organic carbon), and 18.0/0.4 Pg CO 2 . The contributions of India and Southeast Asia were emerging in Asia during 2010–2017, especially for SO 2 , NH 3 and particulate matter. Gridded emissions at a spatial resolution of 0.1° with monthly variations are now publicly available. This updated long-term emission mosaic inventory is ready to facilitate air quality and climate model simulations, as well as policymaking and associated analyses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

The sources and diurnal variations of submicron aerosols in a coastal–rural environment near Houston, US

Aerosol properties were characterized at a rural site southwest of Houston from May to September 2022 during the intensive operation periods (IOPs) of the Tracking Aerosol Convection Interactions ExpeRiment (TRACER). Backward trajectory analysis reveals three major air mass types: marine air mass from the Gulf, urban air mass influenced by urban emissions, and regional air mass. Marine aerosols typically show a bimodal size distribution and have the lowest particle number and mass concentrations of PM 1 (particulate matter with an aerodynamic diameter of less than 1 µm), while aerosols from air masses strongly influenced by urban emissions exhibit the highest concentrations. Organic aerosol (OA) accounts for more than 50 % of PM 1 for urban and regional air masses, whereas sulfate is comparable to OA in marine air masses. Positive matrix factorization (PMF) analysis of aerosol mass spectra identifies 6 OA factors: hydrocarbon-like OA (HOA), OA from the oxidation of monoterpenes (MT-SOA), OA from the reactive uptake of isoprene epoxydiols by acidic sulfate particles (isoprene-SOA), oxygenated OA arising from shipping emissions (shipping-OOA), and two oxygenated OA factors with high O : C ratios (OOA1 and OOA2). OOA2 has the highest O : C ratio and exhibits elevated mass concentration in the afternoon. Similar diurnal variation of highly oxidized OA factors was commonly observed in the Houston area during previous studies and attributed to the SOA formation by photochemistry and mixing from aloft. Here, using air mass backward trajectories and a 1-D box model, we show the diurnal trend of OOA2 mass concentration is instead driven by changes in air mass arriving at the rural site. The air mass changes are likely caused by the shift between land breezes and sea/bay breezes. Within the same air mass type (e.g., either urban or marine air mass), OOA2 mass concentration is largely independent of wind direction and shows essentially no diurnal variation, suggesting OOA2 is related to aged OA with minimal influence by local emissions. This study helps identify the major sources of OA in the Houston region and highlights the impacts of both atmospheric chemistry and meteorology on aerosol properties in the coastal–rural environment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Enhancing characterization of organic nitrogen components in aerosols and droplets using high-resolution aerosol mass spectrometry

This study aims to enhance the understanding and application of the Aerodyne high-resolution aerosol mass spectrometer (HR-AMS) for comprehensive characterization of organic nitrogen (ON) compounds in aerosol particles and atmospheric droplets. To achieve this, we analyzed seventy-five N-containing organic compounds, representing a diverse range of ambient ON types, including amines, amides, amino acids, N-heterocycles, protein, and humic acids. Our results show that ON compounds can produce significant levels of NH x + and NO x + ion fragments, which are typically recognized as ions representative of inorganic nitrogen species. We also discovered the presence of CH 2 N + at m/z = 28.0187, an ion fragment that is rarely quantified in ambient datasets due to substantial interference from air-related N 2 + . As a result, we determined that an updated calibration factor of 0.79 is necessary to accurately quantify ON content using aerosol mass spectrometry. We also assessed the relative ionization efficiencies (RIEs) for different ON species and found that the average RIE of ON compounds (1.52 ± 0.58) aligns with the commonly used default value of 1.40 for organic aerosol (OA). Moreover, through a careful examination of the HR-AMS mass spectral features of various ON types, we propose fingerprint ion series that can aid the ON speciation analysis. The presence of C n H 2n+2 N + ions is closely linked with amines, with CH 4 N + indicating primary amines, C 2 H 6 N + suggesting secondary amines, and C 3 H 8 N + representing tertiary amines. C n H 2n NO + ions (especially for n values of 1–4) are very likely derived from amides. The co-existence of three ions, C 2 H 4 NO 2 + , C 2 H 3 NO + , and CH 4 NO + , serves as an indicator for the presence of amino acids. Additionally, the presence of C x H y N 2 + ions indicates the occurrence of 2N-heterocyclic compounds. Notably, an elevated abundance of NH 4 + is a distinct signature for amines and amino acids, as inorganic ammonium salts produce only negligible amounts of NH 4 + in HR-AMS. Finally, we quantified the ON contents in submicron particles (PM 1 ) and fog waters in Fresno, California and PM 1 in New York City (NYC). Our results revealed the substantial presence of amino compounds in both Fresno and NYC aerosols, whereas concurrently collected fog waters contained a broader range of ON species, including N-containing aromatic heterocycle (e.g., imidazoles) and amides. These findings highlight the significant potential of employing the widespread HR-AMS measurements of ambient aerosols and droplets to enhance our understanding of the sources, transformation processes, and environmental impacts associated with ON compounds in the atmosphere.

54 ENVIRONMENTAL SCIENCES↗

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 OSTI2021

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Gas Adsorption Analyzer

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

3Flex,BET specific surface area and pore volume, A↗

DOE OSTI2021

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) X-Ray Diffraction

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Cryogenic Refrigerator Applied to Freezing Test

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

ARM Data for Examining the Ice-Nucleating Particles from SGP Part II (ExINP-SGP II) Aerodynamic Particle Sizer, Condensation Particle Counter, and Meteorological Instrument Data Analysis

Knowledge of airborne particulate matter (PM), especially the particles that have supermicron diameters, is key for understanding ice-nucleating particles (INPs). Supported by the Atmospheric Radiation Measurement (ARM) user facility, we sampled PM and surface soil materials at the Southern Great Plains observatory (SGP; 36° 36′ 18″ N, 97° 29′ 6″ W) to systematically compare the INP abundance and ice nucleation efficiency of different SGP samples (i.e., airborne versus surface materials). The field campaign, named Examing INP from SGP II (ExINP-SGP II), was conducted from 20 January to 20 April, 2021. Our data analysis products include (1) physical surface sorption characterization data (i.e., BET, pore volume) of two sets of samples -- SGP Soil and USDA, (2) X-ray diffraction spectra for the same two samples, (3) immersion freezing assay-based ice nucleation active mass density data as a function of freezing temperature for both ambient and surface samples, and (4) time-series data of ambient meteorological conditions, concentration particle counter-derived aerosol particle concentration, and aerosol particle sizer measurement during ExINP-SGP II.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2021-2022

Timelapse camera images from Council Mile Marker (MM) 71, Kougarok MM 64, Kougarok Fire Complex (KFC, also referred to as the Garfield Fire Site), and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from August 2021 to July 2022. Ten Wingscape Timelapse Pro cameras, and twenty seven Power-interval Camera Automation Modules (PiCAMs) designed by Brookhaven National Laboratory's Terrestrial Ecosystem Science and Technology (TEST) group were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from Wingscape cameras were recorded at hourly intervals from 11 AM to 2 PM, and images from PiCAMs were recorded at 5 hourly intervals from 12 AM to 8 PM, continuously for 12 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. Additional information available in *.pdf and *.csv files. 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 OSTI2024

Digital camera imagery for vegetation phenology, Seward Peninsula, Alaska, 2022-2023

Timelapse camera images from Council Mile Marker (MM) 71, Kougarok MM 64, Kougarok Fire Complex (KFC), and Teller MM 27 NGEE-Arctic field sites on the Seward Peninsula, Alaska, captured from July 2022 to July 2023. Eight Wingscape Timelapse Pro cameras, and thirty-one Power-interval Camera Automation Modules (PiCAMs) designed by Brookhaven National Laboratory?s Terrestrial Ecosystem Science and Technology (TEST) group were deployed targeting patches of low and tall shrubs (including Alnus sp. and Salix sp.) and general vegetation and landscape views. Images from Wingscape cameras were recorded at hourly intervals from 11 AM to 2 PM, and images from PiCAMs were recorded at 5 hourly intervals from 12 AM to 8 PM, continuously for 12 months and capture vegetation phenology, snow accumulation and snow melt events. This data package includes images (*.jpg), organized by site and camera ID, and metadata with details of the cameras used, number of images recorded, start and end dates, GPS locations and example fields of view. 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 OSTI2024

MSD CoP Webinar: Representing Climate Impacts in Scenaros

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Abstract: Scenarios of future emissions and land use have been most commonly produced without accounting for the effects that climate impacts linked to those emissions and land use changes may have. The questions of how important such impacts could be, at the regional or global scale, has become an increasingly cogent one. Using the Global Change Analysis Model (GCAM), we implement climate impacts on water supply, agricultural productivity, and energy demand driven by climatic impact drivers whose evolution over the 21st century is representative of a climate consistent with GCAM's reference scenario and compare the output to the reference at both regional and global scales. We show that the impacts from the version of GCAM that uses GDP as an exogenous input are not sufficient to bend emission pathways at the global scale. However, we see effects emerge at the regional scale in terms of emissions, among other metrics linked to water, land and energy. We expect the impacts to become more significant at an aggregate, global scale in a forthcoming version of the model with endogenous GDP. Meanwhile, we document the mechanisms that drive the difference at regional scales which could still be significant in their impacts for individual economies and populations. Presenters: Dr. Claudia Tebaldi (Joint Global Change Research Institute, Pacific Northwest National Laboratory) Moderator(s): Jennifer Morris (MSD CoP SSG member), Patrick Reed (MSD CoP Facilitation Team Member, Moderator and Organizer) This webinar was held on: November 5, 2024 from 1 PM - 2:15 PM ET

Climate Scenarios↗