Nitrogen (N) is the most critical element limiting agricultural production at a global scale. Despite many efforts, the N use efficiency (NUE) in agriculture remains in a range of less than 50%. Reaching targeted crop yields has resulted in N overuse, which is an economic and environmental concern worldwide. The continuous exploration of innovative solutions has led to the synthesis of novel nanomaterials, resulting in a powerful tool for the development of new technological products. Nanofertilizers are one of the most promising engineered materials that are being tested, either for soil or foliar applications. Encouraging results have been obtained using nanofertilizers in different plant species, however, limited information has been reported about its use in grasslands. Commonly, N is applied to grassland soils as granular fertilizers, which may result in significant losses via surface runoff or leaching, ammonia (NH₃) volatilization and N oxides (N₂O, NO, NO_x) emissions. Nitrogen nanofertilizers are expected to increase NUE by improving the effectiveness of N delivery to plants and reducing N losses to the environment. Information on the efficiency of the use of N nanofertilizers in grasslands species is scarce and the application strategies that can be used to avoid N losses are poorly understood. New scenarios of increasing economic and environmental constraints may represent an opportunity for N nanofertilizers application in grasslands. This article reviews its potential use as an innovative approach to improve NUE and reduce N losses to the wider environment, analyzing potential shortcomings and future considerations for animal food chains.

Manure application to land and deposition of urine and dung by grazing animals are major sources of ammonia (NH₃) and nitrous oxide (N₂O) emissions. Using data on NH₃ and N₂O 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 NH₃ data represent emissions from cattle and swine manures in temperate wet climates, and the N₂O data include cattle, sheep, and swine manure emissions in temperate wet/dry and tropical wet/dry climates. The NH₃ EFs for broadcast cattle solid manure and slurry were 0.03 and 0.24 kg NH₃–N kg^–1 total N (TN), respectively, whereas the NH₃ 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 N₂O–N kg^–1 TN, respectively, whereas in dry climates the EF for cattle manure was 0.0031. The N₂O EFs for cattle urine and dung in wet climates were 0.0095 and 0.002 kg N₂O–N kg^–1 TN, respectively, which were three times greater than for dry climates. The N₂O 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.

Static chambers are often used for measuring nitrous oxide (N₂O) fluxes from soils, but statistical analysis of chamber data is challenged by the inherently heterogeneous nature of N₂O fluxes. Because N₂O chamber measurements are commonly used to assess N₂O mitigation strategies or to determine country‐specific emission factors (EFs) for calculating national greenhouse gas inventories, it is important that statistical analysis of the data is sound and that EFs are robustly estimated. This paper is one of a series of articles that provide guidance on different aspects of N₂O chamber methodologies. Here, we discuss the challenges associated with statistical analysis of heterogeneous data, by summarizing statistical approaches used in recent publications and providing guidance on assessing normality and options for transforming data that follow a non‐normal distribution. We also recommend minimum requirements for reporting of experimental and metadata of N₂O studies to ensure that the robustness of the results can be reliably evaluated. This includes detailed information on the experimental site, methodology and measurement procedures, gas analysis, data and statistical analyses, and approaches to generate EFs, as well as results of ancillary measurements. The reliability, robustness, and comparability of soil N₂O emissions data will be improved through (a) application, and reporting, of more rigorous methodological standards by researchers and (b) greater vigilance by reviewers and scientific editors to ensure that all necessary information is reported in scientific publications.

Nitrous oxide (N₂O), ammonia (NH₃), and methane (CH₄) emissions from the manure management chain of livestock production systems are important contributors to greenhouse gases (GHGs) and NH₃ 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 NH₃ 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 NH₃ emission reporting. This paper describes the “field” database that focuses on N₂O and NH₃ 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 N₂O and NH₃ (56 and 44% of the EF values, respectively). The N₂O 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 NH₃ 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.

Livestock manure management systems can be significant sources of nitrous oxide (N₂O), methane (CH₄), and ammonia (NH₃) emissions. Many studies have been conducted to improve our understanding of the emission processes and to identify influential variables in order to develop mitigation techniques adapted to each manure management step (animal housing, outdoor storage, and manure spreading to land). The international project DATAMAN (http://www.dataman.co.nz) aims to develop a global database on greenhouse gases (N₂O, CH₄) and NH₃ emissions from the manure management chain to refine emission factors (EFs) for national greenhouse gas and NH₃ inventories. This paper describes the housing and outdoor storage components of this database. Relevant information for different animal categories, manure types, livestock buildings, outdoor storage, and climatic conditions was collated from published peer reviewed research, conference papers, and existing databases published between 1995 and 2021. In the housing database, 2024 EFs were collated (63% for NH₃, 19.5% for CH₄, and 17.5% for N₂O). The storage database contains 654 NH₃ EFs from 16 countries, 243 CH₄ EFs from 13 countries, and 421 N₂O EFs from 17 countries. Across all gases, dairy cattle and swine production in temperate climate zones are the most represented animal and climate categories. As for the housing database, the number of EFs for the tropical climate zone is under‐represented. The DATAMAN database can be used for the refinement of national inventories and better assessment of the cost‐effectiveness of a range of mitigation strategies.