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Greenhouse Gas Emissions from Croplands

    This download provides three datasets aggregated from the original output of the 172 crops; total emissions from croplands, per kilocalorie emissions from croplands and per food kilocalorie emissions from cropland.

    Dairy Gas Emissions Model (DairyGEM)

      The Dairy Gas Emissions Model (DairyGEM) uses process level simulation and process related emission factors to predict ammonia, hydrogen sulfide, VOC and greenhouse gas emissions along with the carbon, energy and water footprints of dairy production systems.

      Data from: Underestimation of N2O emissions in a comparison of the DayCent, DNDC, and EPIC 1 models

        Process-based models are increasingly used to study mass and energy fluxes from agro-ecosystems, including nitrous oxide (N2O) emissions from agricultural fields. This data set is the output of three process-based models – DayCent, DNDC, and EPIC – which were used to simulate fluxes of N2O from dairy farm soils. The individual models' output and the ensemble mean output were evaluated against field observations from two agricultural research stations in Arlington, WI and Marshfield, WI. These sites utilize cropping systems and nitrogen fertilizer management strategies common to Midwest dairy farms.

        NUOnet (Nutrient Use and Outcome Network) database

          The Nutrient Uptake and Outcomes (NUOnet) database will be able to help establish baselines on nutrient use efficiencies; processes contributing to nutrient losses; and processes contributing to optimal crop yield, nutritional and organoleptic quality. This national database could be used to calculate many different environmental indicators from a comprehensive understanding of nutrient stocks and flows.

          Data from: Gas emissions from dairy barnyards

            To assess the magnitude of greenhouse gas (GHG) fluxes, nutrient runoff and leaching from dairy barnyards and to characterize factors controlling these fluxes, nine barnyards were built at the U.S. Dairy Forage Research Center Farm in Prairie du Sac, WI (latitude 43.33N, longitude 89.71W). The barnyards were designed to simulate outdoor cattle-holding areas on commercial dairy farms in Wisconsin. Each barnyard was approximately 7m x 7m; areas of barnyards 1-9 were 51.91, 47.29, 50.97, 46.32, 45.64, 46.30, 48.93, 48.78, 46.73 square meters, respectively. Factors investigated included three different surface materials (bark, sand, soil) and timing of cattle corralling. Each barnyard included a gravity drainage system that allowed leachate to be pumped out and analyzed. Each soil-covered barnyard also included a system to intercept runoff at the perimeter and drain to a pumping port, similar to the leachate systems.

            Low-Disturbance Manure Incorporation

              The LDMI experiment (Low-Disturbance Manure Incorporation) was designed to evaluate nutrient losses with conventional and improved liquid dairy manure management practices in a corn silage (*Zea mays*) / rye cover-crop (*Secale cereale*) system. The improved manure management treatments were designed to incorporate manure while maintaining crop residue for erosion control. Field observations included greenhouse gas (GHG) fluxes from soil, soil nutrient concentrations, crop growth and harvest biomass and nutrient content, as well as monitoring of soil physical and chemical properties. Observations from LDMI have been used for parameterization and validation of computer simulation models of GHG emissions from dairy farms (Gaillard et al., submitted). The LDMI experiment was performed as part of the Dairy CAP.

              Manure application methods for alfalfa-grass

                The MAMA experiment (Manure Application Methods for Alfalfa-Grass), from the USDA-ARS research station in Marshfield, WI was designed to evaluate nutrient and pathogen losses with conventional and improved liquid dairy manure management practices for alfalfa-grass production. Observations from MAMA have also been used for parameterization and validation of computer simulation models of greenhouse gas (GHG) emissions from dairy farms.

                Effects of tannin in dairy cow diets and land application of manure on soil gas fluxes and nitrogen dynamics

                  This experiment was designed to determine if tannin concentration and nitrogen (N) content of field-applied dairy cow manure influences greenhouse gas (GHG) emissions from soil, soil N mineralization, and plant productivity. The data presented include experimental design, soil physical characteristics, gas fluxes, soil nitrogen at 0-10 cm depth, soil nitrogen at 10-20 cm depth, chemical characteristics of dairy manure, and crop yield and biomass characteristics.

                  Data from: U.S. Agriculture and Forestry Greenhouse Gas Inventory: 1990-2013

                    The report 'U.S. Agriculture and Forestry Greenhouse Gas Inventory: 1990-2013' serves to estimate U.S. GHG emissions for the agricultural sector, to quantify uncertainty in emission estimates, and to estimate the potential of agriculture to mitigate U.S. GHG emissions. This dataset contains zipped, tabulated data from the figures and tables, and maps of the entire report. Data are presented for Cropland Soils (N2O), Enteric Fermentation (CH4), Managed Livestock Waste (CH4 + N2O), Grazed Lands (CH4 + N2O), Rice Cultivation + Residue Burning (CH4 + N2O), Energy Use, Forests, Harvested Wood, Urban Trees, and Agricultural Soils. Please refer to the report for full descriptions of and notes on the data.