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Manure application to land and deposition of urine and dung by grazing animals are major sources of ammonia (NH 3 ) and nitrous oxide (N 2 O) emissions. Using data on NH 3 and N 2 O emissions following land-applied manures and excreta deposited during grazing, emission factors (EFs) disaggregated by climate zone were developed, and the effects of mitigation strategies were evaluated. The NH 3 data represent emissions from cattle and swine manures in temperate wet climates, and the N 2 O data include cattle, sheep, and swine manure emissions in temperate wet/dry and tropical wet/dry climates. The NH 3 EFs for broadcast cattle solid manure and slurry were 0.03 and 0.24 kg NH 3 -N kg -1 total N (TN), respectively, whereas the NH 3 EF of broadcast swine slurry was 0.29. Emissions from both cattle and swine slurry were reduced between 46 and 62% with low-emissions application methods. Land application of cattle and swine manure in wet climates had EFs of 0.005 and 0.011 kg N 2 O-N kg -1 TN, respectively, whereas in dry climates the EF for cattle manure was 0.0031. The N 2 O EFs for cattle urine and dung in wet climates were 0.0095 and 0.002 kg N 2 O-N kg -1 TN, respectively, which were three times greater than for dry climates. The N 2 O EFs for sheep urine and dung in wet climates were 0.0043 and 0.0005, respectively. The use of nitrification inhibitors reduced emissions in swine manure, cattle urine/dung, and sheep urine by 45-63%. These enhanced EFs can improve national inventories; however, more data from poorly represented regions (e.g., Asia, Africa, South America) are needed., (© 2021 The Authors. Journal of Environmental Quality published by Wiley Periodicals LLC on behalf of American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.)

Nitrous oxide (N 2 O), ammonia (NH 3 ), and methane (CH 4 ) emissions from the manure management chain of livestock production systems are important contributors to greenhouse gases (GHGs) and NH 3 emitted by human activities. Several studies have evaluated manure-related emissions and associated key variables at regional, national, or continental scales. However, there have been few studies focusing on the drivers of these emissions using a global dataset. An international project was created (DATAMAN) to develop a global database on GHG and NH 3 emissions from the manure management chain (housing, storage, and field) to identify key variables influencing emissions and ultimately to refine emission factors (EFs) for future national GHG inventories and NH 3 emission reporting. This paper describes the "field" database that focuses on N 2 O and NH 3 EFs from land-applied manure and excreta deposited by grazing livestock. We collated relevant information (EFs, manure characteristics, soil properties, and climatic conditions) from published peer-reviewed research, conference papers, and existing databases. The database, containing 5,632 observations compiled from 184 studies, was relatively evenly split between N 2 O and NH 3 (56 and 44% of the EF values, respectively). The N 2 O data were derived from studies conducted in 21 countries on five continents, with New Zealand, the United Kingdom, Kenya, and Brazil representing 86% of the data. The NH 3 data originated from studies conducted in 17 countries on four continents, with the United Kingdom, Denmark, Canada, and The Netherlands representing 79% of the data. Wet temperate climates represented 90% of the total database. The DATAMAN field database is available at http://www.dataman.co.nz., (© 2020 The Authors. Journal of Environmental Quality published by Wiley Periodicals LLC on behalf of American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.)

Terrestrial ecosystems, both natural ecosystems and agroecosystems, generate greenhouse gases (GHGs). The chamber method is the most common method to quantify GHG fluxes from soil-plant systems and to better understand factors affecting their generation and mitigation. The objective of this study was to review and synthesize literature on chamber designs (non-flow-through, non-steady-state chamber) and associated factors that affect GHG nitrous oxide (N 2 O) flux measurement when using chamber methods. Chamber design requires consideration of many facets that include materials, insulation, sealing, venting, depth of placement, and the need to maintain plant growth and activity. Final designs should be tailored, and bench tested, in order to meet the nuances of the experimental objectives and the ecosystem under study while reducing potential artifacts. Good insulation, to prevent temperature fluctuations and pressure changes, and a high-quality seal between base and chamber are essential. Elimination of pressure differentials between headspace and atmosphere through venting should be performed, and designs now exist to eliminate Venturi effects of earlier tube-type vent designs. The use of fans within the chamber headspace increases measurement precision but may alter the flux. To establish best practice recommendations when using fans, further data are required, particularly in systems containing tall plants, to systematically evaluate the effects that fan speed, position, and mixing rate have on soil gas flux., (© 2020 The Authors. Journal of Environmental Quality published by Wiley Periodicals LLC on behalf of American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.)

Adequately estimating soil nitrous oxide (N 2 O) emissions using static chambers is challenging due to the high spatial variability and episodic nature of these fluxes. We discuss how to design experiments using static chambers to better account for this variability and reduce the uncertainty of N 2 O emission estimates. This paper is part of a series, each discussing different facets of N 2 O chamber methodology. Aspects of experimental design and sampling affected by spatial variability include site selection and chamber layout, size, and areal coverage. Where used, treatment application adds a further level of spatial variability. Time of day, frequency, and duration of sampling (both individual chamber closure and overall experiment duration) affect the temporal variability captured. We also present best practice recommendations for chamber installation and sampling protocols to reduce further uncertainty. To obtain the best N 2 O emission estimates, resources should be allocated to minimize the overall uncertainty in line with experiment objectives. Sometimes this will mean prioritizing individual flux measurements and increasing their accuracy and precision by, for example, collecting four or more headspace samples during each chamber closure. However, where N 2 O fluxes are exceptionally spatially variable (e.g., in heterogeneous agricultural landscapes, such as uneven and woody grazed pastures), using available resources to deploy more chambers with fewer headspace samples per chamber may be beneficial. Similarly, for particularly episodic N 2 O fluxes, generated for example by irrigation or freeze-thaw cycles, increasing chamber sampling frequency will improve the accuracy and reduce the uncertainty of temporally interpolated N 2 O fluxes., (© 2020 The Authors. Journal of Environmental Quality © 2020 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.)

Nitrous oxide (N 2 O) emission from agricultural soils represents a significant source of greenhouse gas to the atmosphere. We evaluated the suitability of a modified Soil and Water Assessment Tool (SWAT) model to estimate the N 2 O flux from the application of solid manure at two grassland sites (North Wyke [NW] and Pwllpeiran [PW]) in the United Kingdom. The simulated N 2 O emissions were validated against field observations measured in 2011 and 2012 for model calibration and validation, respectively. The SWAT model predicts water-filled pore space (WFPS) very well with Nash-Sutcliffe efficiency (NSE), R 2 , RMSE, and percentage bias (PBIAS) values of 0.67, .72, 0.06, and 3.64, respectively, during the calibration period for NW site, whereas it gives 0.68, .69, 0.07, and 3.04, respectively during the validation period. At PW, the model predicted the NSE, R 2 , RMSE, and PBIAS of 0.55, .69, 0.04, and -4.5, respectively, during calibration and 0.63, .71, 0.05, and -2.6, respectively, during the validation period. Compared with WFPS, the model resulted in a slightly lower fit for N 2 O emissions for NW (NSE = 0.47, R 2  = .63 during calibration, and NSE = 0.55, R 2  = .58 during validation) and for PW (NSE = 0.54, R 2  = .71 for calibration, and NSE = 0.47, R 2  = .69 for validation). Results revealed that the SWAT model performed reasonably well in representing the dynamics of N 2 O emissions after solid manure application to grassland., (© 2020 The Authors. Journal of Environmental Quality © 2020 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.)