Central Plains Experimental Range Study for Long-Term Agroecosystem Research in Nunn, Colorado The Central Plains Experimental Range (CPER) is a site with the The Long-Term Agroecosystem Research (LTAR) Network, which consists of 18 sites across the continental United States (US) sponsored by the US Department of Agriculture, Agricultural Research Service, universities and non-governmental organizations. LTAR scientists seek to determine ways to ensure sustainability and enhance food production (and quality) and ecosystem services at broad regional scales. They are conducting common experiments across the LTAR network to compare traditional production strategies (“business as usual or BAU) with aspirational strategies, which include novel technologies and collaborations with farmers and ranchers. Within- and cross-site network success towards achieving the desired outcomes of enhancing quality food production and reducing environmental impact requires that LTAR scientists and collaborators have well-timed access to various data. We are striving to create opportunities to package and share long-term legacy observations from each site, with new data and metadata in useable, well documented and consistent formats for them.

No dataset available. This dataset is not publicly accessible because: The dataset was never touched by EPA employees. Data was collected, analyzed, and maintained solely by non-EPA collaborators. It can be accessed through the following means: Dataset can be accessed by contacting the senior PI on the research effort, Kristina Whitworth (Kristina.W.Whitworth@uth.tmc.edu). Format: Dataset was handled solely by non-EPA collaborators on this research effort. EPA employee role on this research effort was purely advisory. This dataset is associated with the following publication: Misra, A., M. Longnecker, K. Dionisio, R. Bornman, G. Travlos, S. Brar, and K. Whitworth. Household fuel use and biomarkers of inflammation and respiratory illness among rural South African Women. ENVIRONMENTAL RESEARCH. Academic Press Incorporated, Orlando, FL, USA, 166: 112-116, (2018).

This dataset provides supporting information for figures in the journal article entitled: Mutagenicity- and Pollutant-Emission Factors of Pellet-Fueled Gasifier Cookstoves: Comparison with Other Combustion Sources. This dataset is associated with the following publication: Champion, W., S. Warren, I. Kooter, W. Preston, T. Krantz, D. DeMarini, and J. Jetter. Mutagenicity- and Pollutant-Emission Factors of Pellet-Fueled Gasifier Cookstoves: Comparison with Other Combustion Sources. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 739(October 15 2020): 139488, (2020).

Phenotypic evaluation of 37 crimson clover (Trifolium incarnatum L.) accessions from the US National Plant Germplasm System. Focus of the trial was on traits important for cover crop performance, including fall emergence, winter survival, flowering time, biomass, nitrogen (N) content in aboveground biomass, and proportion of plant N from biological nitrogen fixation (BNF). Experiments were conducted at the Beltsville Agricultural Research Center (Maryland, USA) across three growing seasons (2012-2013, 2013-2014, 2014-2015). The field design was a randomized complete block design (RCBD) with four replications in each year, except for five accessions planted in 2015, which only had three replications due to limited seed availability. Each plot was a single row 0.6 m in length and 1.5 m between plots. Between 37 and 45 seeds were planted per plot, depending on seed availability in each year. Fall emergence was evaluated in late October of each year by counting the total number of plants in each plot. Winter survival was determined by counting total number of plants per plot in late April divided by the total number of plants counted in the fall. Flowering time was evaluated by recording percent flowering on a per-plot basis on a scale from 0% (no flower buds present) to 100% (all flowers dried up entire length of head). Flowering evaluations took place periodically between late April and early June. In 2013, evaluation took place on six dates: 23 Apr., 9 May, 15 May, 24 May, 30 May, and 4 June. In 2014, evaluation took place on five dates: 28 Apr., 6 May, 13 May, 19 May, and 27 May. In 2015, evaluation took place on eight dates: 25 Apr., 29 Apr., 4 May, 7 May, 11 May, 14 May, 18 May, and 21 May. Frequency of evaluations and total duration of evaluation period varied from year-to-year primarily due to the effects of year-to-year weather variation on the rate of growth and development. Once an accession was rated at 50% or greater for flowering, biomass was collected. All plants in the plot were pulled up with roots attached. Plants were counted and the roots were clipped. All plants within a plot were placed in the same brown paper bag and dried. Dry weight was recorded and plants were ground for laboratory evaluation of nitrogen content, proportion of nitrogen from BNF, and metagenomic analysis. The crimson clover biomass samples were separated into shoots and roots. Shoots were oven dried (60 °C) for approximately 72 h, weighed, and ground to pass a 1.0-mm screen. Tissue C and N concentrations and 15N natural abundance were determined for the shoot material of each accession using a Thermo Delta V Isotope Ratio Mass Spectrometer (Thermo Scientific, Waltham, MA) and Carlo Erba NC2500 Elemental Analyzer (Carlo Erba, Milan, Italy). Isotopic abundance data were expressed as δ15N in parts per thousand (‰), representing the abundance of plant tissue 15N relative to that of atmospheric N2.

Annual data on electricity generating capacity, electricity generation and useful thermal output, fuel receipts, fuel stocks, sales, consumption, and emissions in the United States. Based on Form EIA-861 and Form EIA-860 data. Annual time series extend back to 1994.

The Emissions & Generation Resource Integrated Database (eGRID) is a comprehensive source of data on characteristics of almost all electric power generated in the United States. This data includes capacity; heat input; net generation; associated air emissions of nitrogen oxides, sulfur dioxide, carbon dioxide, methane, nitrous oxide and mercury; emissions rates; resource mix (i.e., generation by fuel type); nonbaseload calculations; line losses (a.k.a., grid gross loss); and many other attributes. The data is provided at the unit and generator levels, as well as, aggregated to the plant, state, balancing authority, eGRID subregion, NERC region, and US levels. As of January 2023, the available editions of eGRID contain data for years 2021, 2020, 2019, 2018, 2016, 2014, 2012, 2010, 2009, 2007, 2005, 2004, and 1996 through 2000.

The current study not only characterizes emissions from three coals (bituminous, sub-bituminous, and lignite), but also investigates the use of instrumentation for improved measurement and monitoring techniques that provide real-time, continuous emissions data. Testing was completed using the U.S. EPA’s Multi-Pollutant Control Research Facility, a pilot-scale coal-fired combustor using industry-standard emission control technologies, in Research Triangle Park, North Carolina. Emissions were calculated based on measurements from the flue gas (pre- and post-electrostatic precipitator), to characterize gaseous species (CO, CO2, O2, NOX, SO2, other acid gases, and several organic HAPs) as well as fine and ultrafine particulate (mass, size distribution, number count, elemental carbon, organic carbon, and black carbon). Comparisons of traditional EPA methods to those made via Fourier Transfer Infrared (FTIR) Spectroscopy for CO, NOX, and SO2 are also reported. This dataset is associated with the following publication: Yelverton, T., A. Brashear, D. Nash, E. Brown, C. Singer, P. Kariher, and J. Ryan. Comparison of gaseous and particulate emissions from a pilot-scale combustor using three varieties of coal. FUEL. Elsevier Science BV, Amsterdam, NETHERLANDS, 215: 572-579, (2018).

Farming Systems Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Morris, Minnesota Tillage is decreasing globally due to recognized benefits of fuel savings and improved soil health in the absence of disturbance. However, a perceived inability to control weeds effectively and economically hinders no-till adoption in organic production systems in the Upper Midwest, USA. A strip-tillage (ST) strategy was explored as an intermediate approach to reducing fuel use and soil disturbance, and still controlling weeds. An 8-year comparison was made between two tillage approaches, one primarily using ST the other using a combination of conventional plow, disk and chisel tillage [conventional tillage (CT)]. Additionally, two rotation schemes were explored within each tillage system: a 2-year rotation (2y) of corn (Zea mays L.), and soybean (Glycine max [L.] Merr.) with a winter rye (Secale cereale L.) cover crop; and a 4-year rotation (4y) of corn, soybean, spring wheat (Triticum aestivum L.) underseeded with alfalfa (Medicago sativa L.), and a second year of alfalfa. These treatments resulted in comparison of four main management systems CT-2y, CT-4y, ST-2y and ST-4y, which also were managed under fertilized and non-fertilized conditions. Yields, whole system productivity (evaluated with potential gross returns), and weed seed densities (first 4 years) were measured. Across years, yields of corn, soybean and wheat were greater by 34% or more under CT than ST but alfalfa yields were the same. Within tillage strategies, corn yields were the same in 2y and 4y rotations, but soybean yields, only under ST, were 29% lower in the fertilized 4y than 2 yr rotation. In the ST-4y system yields of corn and soybean were the same in fertilized and non-fertilized treatments. Over the entire rotation, system productivity was highest in the fertilized CT-2y system, but the same among fertilized ST-4y, and non-fertilized ST-2y, ST-4y, and CT-4y systems. Over the first 4 years, total weed seed density increased comparatively more under ST than CT, and was negatively correlated to corn yields in fertilized CT systems and soybean yields in the fertilized ST-2y system. These results indicated ST compromised productivity, in part due to insufficient weed control, but also due to reduced nutrient availability. ST and diverse rotations may yet be viable options given that overall productivity of fertilized ST-2y and CT-4y systems was within 70% of that in the fertilized CT-2y system. Closing the yield gap between ST and CT would benefit from future research focused on organic weed and nutrient management, particularly for corn.

Life Cycle Analysis (LCA) is a comprehensive form of analysis that utilizes the principles of Life Cycle Assessment, Life Cycle Cost Analysis, and various other methods to evaluate the environmental, economic, and social attributes of energy systems ranging from the extraction of raw materials from the ground to the use of the energy carrier to perform work (commonly referred to as the “life cycle” of a product). Results are used to inform research at NETL and evaluate energy options from a National perspective.

Maps created by the National Renewable Energy Laboratory (NREL). NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy. This data includes maps of regions of the world based on input. The maps are produced by NREL from their GIS software. This is a repository for sharing the maps. The maps show renewable energy use, emissions, biomass, solar power/wind energy, etc. by location (mostly by state). Internet Archive URL: https://web.archive.org/web/2019*/http://nrel.gov/gis/mapsearch

NVND Study for Greenhouse gas Reduction through Agricultural Carbon Enhancement network in Sidney, Montana Management practices, such as irrigation, tillage, cropping system, and N fertilization, may influence soil greenhouse gas (GHG) emissions. We quantified the effects of irrigation, tillage, crop rotation, and N fertilization on soil CO2, N2O, and CH4 emissions from March to November, 2008 to 2011 in a Lihen sandy loam in western North Dakota. Treatments were two irrigation practices (irrigated and non-irrigated) and five cropping systems (conventional-tilled malt barley [Hordeum vulgaris L.] with N fertilizer [CTBFN], conventional-tilled malt barley with no N fertilizer [CTBON], no-tilled malt barley-pea [Pisum sativum L.] with N fertilizer [NTB-PN], no-tilled malt barley with N fertilizer [NTBFN], and no-tilled malt barley with no N fertilizer [NTBON]). The GHG fluxes varied with date of sampling while peaking immediately after precipitation, irrigation, and/or N fertilization events during increased soil temperature. Both CO2 and N2O fluxes were greater in CTBFN under the irrigated condition but CH4 uptake was greater in NTB-PN under the non-irrigated condition than in other treatments. While tillage and N fertilization increased CO2 and N2O fluxes by 8 to 30%, N fertilization and monocropping reduced CH4 uptake by 39 to 40%. The NTB-PN, regardless of irrigation, might mitigate GHG emissions by reducing CO2 and N2O emissions and increasing CH4 uptake relative to other treatments. To account for global warming potential for such a practice, information on productions associated with CO2 emissions along with N2O and CH4 fluxes are needed.

The Rangeland Analysis Platform ( rangelands.app) is a free online application that provides simple and fast access to geospatial vegetation data for U.S. rangelands. The tool was developed to provide landowners, resource managers, conservationists, and scientists access to data that can inform land management planning, decision making, and the evaluation of outcomes. The Rangeland Analysis Platform (RAP) uses innovative cloud computing technology to provide maps and analysis opportunities straight to your desktop, delivered securely and instantaneously. The maps and data provided by RAP are intended to be used alongside local knowledge and site-specific data to inform management actions that improve rangelands and wildlife habitat. Biomass The Rangeland Analysis Platform’s vegetation biomass product provides annual and 16-day aboveground biomass from 1986 to present of: annual forbs and grasses, perennial forbs and grasses, and herbaceous (combination of annual and perennial forbs and grasses). Estimates represent accumulated new biomass throughout the year or 16-day period and do not include biomass accumulation in previous years. Aboveground biomass was calculated by separating net primary production (paritioned by functional group) to aboveground and converting carbon to biomass (Jones et al. 2021, Robinson et al. 2019). Estimates are provided in United States customary units (lbs/acre) to facilitate use. Although these data were produced across a broad region, they are primarily intended for rangeland ecosystems. Biomass estimates may not be suitable in other ecosystems, e.g., forests., and are not to be used in agricultural lands, i.e., croplands. Cover The Rangeland Analysis Platform’s vegetation cover product provides annual percent cover estimates from 1986 to present of: annual forbs and grasses, perennial forbs and grasses, shrubs, trees, and bare ground. The estimates were produced by combining 75,000 field plots collected by BLM, NPS, and NRCS with the historical Landsat satellite record. Utilizing the power of cloud computing, cover estimates are predicted across the United States at 30m resolution, an area slightly larger than a baseball diamond. Partitioned NPP The Rangeland Analysis Platform provides net primary productivity (NPP) estimates from 1986 to present. Estimates are partitioned into the following functional groups: annual forb and grass, perennial forb and grass, shrub, and tree. NPP is the net increase (i.e., photosynthesis minus respiration) in total plant carbon, including above and below ground. NPP data download Partitioned NPP is available as GeoTIFFs from http://rangeland.ntsg.umt.edu/data/rap/rap-vegetation-npp/ and in Google Earth Engine (ImageCollection ‘projects/rap-data-365417/assets/npp-partitioned-v3’).

Find statistics on renewable energy consumption by source type, electric capacity and electricity generation from renewable sources, biomass and alternative fuels. Internet Archive URL: https://web.archive.org/web/*/http://www.eia.gov/renewable/data.cfm

The MCS Data Dashboard is designed to provide near-real-time updates using MCS Installations Database (MID) data, to track the adoption of small-scale renewable installations in the UK. By producing data visualisations, the MCS Data Dashboard paints a dynamic picture of the uptake and distribution of small-scale renewable installations in the UK. It also uncovers insights into the MCS contractor community. Data files for each visualisation are available to download.

(Link to Metadata) The Renewable Energy Atlas of Vermont and this dataset were created to assist town energy committees, the Clean Energy Development Fund and other funders, educators, planners, policy-makers, and businesses in making informed decisions about the planning and implementation of renewable energy in their communities - decisions that ultimately lead to successful projects, greater energy security, a cleaner and healthier environment, and a better quality of life across the state. Energy flows through nature into social systems as life support. Human societies depended on renewable, solar powered energy for fuel, shelter, tools, and other items for most of our history. Today, when we flip on a light switch, turn an ignition or a water faucet, or eat a hamburger, we engage complex energy extraction systems that largely rely on non-renewable energy to power our lives. About 90% of Vermont's total energy consumption is currently generated from non-renewable energy sources. This dependency puts Vermont at considerable risk, as the peaking of world oil production, global financial instability, climate change, and other factors impact the state.

(Link to Metadata) The Renewable Energy Atlas of Vermont and this dataset were created to assist town energy committees, the Clean Energy Development Fund and other funders, educators, planners, policy-makers, and businesses in making informed decisions about the planning and implementation of renewable energy in their communities - decisions that ultimately lead to successful projects, greater energy security, a cleaner and healthier environment, and a better quality of life across the state. Energy flows through nature into social systems as life support. Human societies depended on renewable, solar powered energy for fuel, shelter, tools, and other items for most of our history. Today, when we flip on a light switch, turn an ignition or a water faucet, or eat a hamburger, we engage complex energy extraction systems that largely rely on non-renewable energy to power our lives. About 90% of Vermont's total energy consumption is currently generated from non-renewable energy sources. This dependency puts Vermont at considerable risk, as the peaking of world oil production, global financial instability, climate change, and other factors impact the state.

This dataset is the raw data used to generate Tables and Figures for a peer-reviewed journal article that published in 2020 in the journal Fuel. This dataset is associated with the following publication: Yelverton, T., A. Brashear, D. Nash, J. Brown, C. Singer, P. Kariher, J. Ryan, and P. Burnette. Characterization of emissions from a pilot-scale combustor operating on coal blended with woody biomass. FUEL. Elsevier Science BV, Amsterdam, NETHERLANDS, 264: 0, (2020).