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At least 19 records

Greenhouse Rhizobox Experiment with Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry data, Seward Peninsula, Alaska, 2024

Data collected from a greenhouse rhizobox experiment (2024) using soils and plants collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by porewater samplers (rhizons). Gas data consists of CO2 and CH4 surface soil fluxes measured with an FTIR (Fourier-transformed infrared red) analyzer. Plant and root data consists of biomass, root length. This study is a part of 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).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2 and CH4?Description of the contents of this data package: Rhizobox2024_Data.csv: This dataset contains plant, water and gas data. No software is needed to utilize them.nga535_flmd.csv: The file contains file level metadatanga535.dd.csv: This file contains the data dictionaryMethods.pdf: This file contains the data collection methods

54 ENVIRONMENTAL SCIENCES↗

Plant Characteristics, Porewater, Gas Flux, and Soil Biogeochemistry at Council Road Site Mile Marker 71, Seward Peninsula, Alaska, 2023

Data collected at Council, AK (64°51’35.0”N 163°41’59.1”W) during a summer campaign in 2023. Water data consists of soil porewater collected by centrifuging soil cores and also by field collection with porewater samplers (rhizons). Gas data consists of CO2, CH4 and N2O surface soil fluxes measured with a portable FTIR analyzer. Plant and root data consists of biomass, root length, diameter and mass. Soil data consists of total C and N. Air, water and soil samples span two main locations: a thermokarst wetland and an upland tussock. 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).This dataset was generated to broadly address the following research question: how will climate change (i.e., thawing permafrost, landscape change) alter the ecosystem flux (sink versus source) of important greenhouse gases such as CO2, CH4 and N2O?Description of the contents of this data package: This dataset contains 5 different individual .csv files containing plant, soil, water and gas data. No software is needed to utilize them. PFTCover: Plant functional type ground cover in 1x1 meter plots. SoilCores: Solidphase and porewater phase soil biogeochemical variablesPlantData: Above and belowground plant traits. GasFlux: Surface plant-soil gas measurementsFieldPorewater: Field collected porewater biogeochemical variables

54 ENVIRONMENTAL SCIENCES↗

Leaf Optical Properties in Higher Plants: Linking Spectral Characteristics with Plant Stress

A number of studies have addressed responses of leaf spectral reflectance, transmittance, or absorptance to physiological stress. Stressors included dehydration, ozone, herbicides, disease, insufficient mycorrhizae and N fertilization, flooding and insects. Species included conifers, grasses, and broadleaved trees. Increased reflectance with maximum responses near 700 nm wavelength occurred in all cases. Varying the chlorophyll content in leaves or pigment extracts can simulate this effect. Thus, common optical responses to stress result from decreases in leaf chlorophyll contents or the capacity of chloroplasts to absorb light. Leaf optic can be quite sensitive to any stressor that alters soil-plant-atmosphere processes.

Carter, Gregory A.↗

Flight Performance of a Jet Power Plant: operating characteristics of a jet power plant as a function of altitude - III

The performance of a jet power plant consisting of a compressor and a turbine is determined by the characteristic curves of these component parts and is controllable by the characteristics of the compressor and the turbine i n relation t o each other. The normal. output, overload, and throttled load of the Jet power plant are obtained on the basis of assumed straight-line characteristics.

Weinig, F.↗

A study of poultry processing plant noise characteristics and potential noise control techniques

The noise environment in a typical poultry processing plant was characterized by developing noise contours for two representative plants: Central Soya of Athens, Inc., Athens, Georgia, and Tip Top Poultry, Inc., Marietta, Georgia. Contour information was restricted to the evisceration are of both plants because nearly 60 percent of all process employees are stationed in this area during a normal work shift. Both plant evisceration areas were composed of tile walls, sheet metal ceilings, and concrete floors. Processing was performed in an assembly-line fashion in which the birds travel through the area on overhead shackles while personnel remain at fixed stations. Processing machinery was present throughout the area. In general, the poultry processing noise problem is the result of loud sources and reflective surfaces. Within the evisceration area, it can be concluded that only a few major sources (lung guns, a chiller component, and hock cutters) are responsible for essentially all direct and reverberant sound pressure levels currently observed during normal operations. Consequently, any effort to reduce the noise problem must first address the sound power output of these sources and/or the absorptive qualitities of the room.

Wyvill, J. C.↗

Existing Hydropower Assets (EHA) Puerto Rico Plant Database Extension

This dataset is an extension and subset of the Existing Hydropower Assets (EHA) Plant Database, 2025, released by Oak Ridge National Laboratory through HydroSource covering hydropower plants in Puerto Rico. The extension enhanced EHA to support modeling performed under the Department of Energy Hydropower Office's SECURE Water Act Section 9505 Fourth Assessment (9505). Included is a spatial dataset containing the location of the powerhouse and plant characteristics and a spatial dataset containing the location of the point-of-diversion and plant characteristics. Enhancements made in this dataset from EHA include updating plant’s spatial locations to explicitly represent the location of the powerhouse; identifying a plant’s point-of-diversion (source of water) spatial location; adding additional plants not included in the 2025 EHA, and revising attributes with updated information.

Broman, Daniel P [Pacific Northwest National Labor↗

Existing Hydropower Assets (EHA) Hawaii Plant Database Extension

This dataset is an extension and subset of the Existing Hydropower Assets (EHA) Plant Database, 2025, released by Oak Ridge National Laboratory through HydroSource covering hydropower plants in Hawaii. The extension enhanced EHA to support modeling performed under the Department of Energy Hydropower Office's SECURE Water Act Section 9505 Fourth Assessment (9505). Included is a spatial dataset containing the location of the powerhouse and plant characteristics and a spatial dataset containing the location of the point-of-diversion and plant characteristics. Enhancements made in this dataset from EHA include updating plant’s spatial locations to explicitly represent the location of the powerhouse; identifying a plant’s point-of-diversion (source of water) spatial location; adding Intertie Region as and attributes, and revising the County, Pt_Own, OwType, and Dam_Own attributes with updated information.

Broman, Daniel P [Pacific Northwest National Labor↗

Existing Hydropower Assets (EHA) Alaska Plant Database Extension

This dataset is an extension and subset of the Existing Hydropower Assets (EHA) Plant Database, 2025, released by Oak Ridge National Laboratory through HydroSource covering hydropower plants in Alaska. The extension enhanced EHA to support modeling performed under the Department of Energy Hydropower Office's SECURE Water Act Section 9505 Fourth Assessment (9505). Included is a spatial dataset containing the location of the powerhouse and plant characteristics and a spatial dataset containing the location of the point-of-diversion and plant characteristics. Enhancements made in this dataset from EHA include updating plant’s spatial locations to explicitly represent the location of the powerhouse; identifying a plant’s point-of-diversion (source of water) spatial location; adding State of Alaska Plant ID, Intertie Region, and Alaska Energy Region as attributes, and revising the County, Pt_Own, OwType, and Dam_Own attributes with updated information.

Broman, Daniel P [Pacific Northwest National Labor↗