Emissions of N2O and NO from fertilized fields: summary of available measurement data

Information from 846 N2O emission measurements in agricultural fields and 99 measurements for NO emissions was summarized to assess the influence of various factors regulating emissions from mineral soils. The data indicate that there is a strong increase of both N2O and NO emissions accompanying N application rates, and soils with high organic-C content show higher emissions than less fertile soils. A fine soil texture, restricted drainage, and neutral to slightly acidic conditions favor N2O emission, while (though not significant) a good soil drainage, coarse texture, and neutral soil reaction favor NO emission. Fertilizer type and crop type are important factors for N2O but not for NO, while the fertilizer application mode has a significant influence on NO only. Regarding the measurements, longer measurement periods yield more of the fertilization effect on N2O and NO emissions, and intensive measurements (=1 per day) yield lower emissions than less intensive measurements (2–3 per week). The available data can be used to develop simple models based on the major regulating factors which describe the spatial variability of emissions of N2O and NO with less uncertainty than emission factor approaches based on country N inputs, as currently used in national emission inventories

Modelling global annual N2O and NO emissions from fertilized fields

Information from 846 N2O emission measurements in agricultural fields and 99 measurements for NO emissions was used to describe the influence of various factors regulating emissions from mineral soils in models for calculating global N2O and NO emissions. Only those factors having a significant influence on N2O and NO emissions were included in the models. For N2O these were (1) environmental factors (climate, soil organic C content, soil texture, drainage and soil pH); (2) management-related factors (N application rate per fertilizer type, type of crop, with major differences between grass, legumes and other annual crops); and (3) factors related to the measurements (length of measurement period and frequency of measurements). The most important controls on NO emission include the N application rate per fertilizer type, soil organic-C content and soil drainage. Calculated global annual N2O-N and NO-N emissions from fertilized agricultural fields amount to 2.8 and 1.6 Mtonne, respectively. The global mean fertilizer-induced emissions for N2O and NO amount to 0.9% and 0.7%, respectively, of the N applied. These overall results account for the spatial variability of the main N2O and NO emission controls on the landscape scal

Global data set of derived soil properties, 0.5-degree grid (ISRIC-WISE)

The World Inventory of Soil Emission Potentials (WISE) database currently contains data for over 4300 soil profiles collected mostly between 1950 and 1995. This database has been used to generate a series of uniform data sets of derived soil properties for each of the 106 soil units considered in the Soil Map of the World (FAO-UNESCO, 1974). These data sets were then linked to a 1/2 degree ... longitude by 1/2 degree latitude version of the edited and digital Soil Map of the World (FAO, 1995) to generate GIS raster image files for the following variables: Total available water capacity (mm water per 1 m soil depth) soil organic carbon density (kg C/m**2 for 0-30cm depth range) soil organic carbon density (kg C/m**2 for 0-100cm depth range) soil carbonate carbon density (kg C/m**2 for 0-100cm depth range) soil pH (0-30 cm depth range) soil pH (30-100 cm depth range) Data Citation: The data set should be cited as follows: Batjes, N. H. (ed). 2000. Global Data Set of Derived Soil Properties, 0.5-Degree Grid (ISRIC-WISE). Available on-line from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A

SoilGrids: using big data solutions and machine learning algorithms for global soil mapping

The SoilGrids system (www.soilgrids.org) uses machine learning algorithms to predict soil type and basic soil properties at seven depths on global extent. These algorithms (i.e., random forests, gradient boosting) are trained with soil observations assembled from 150 000 locations across the globe as stored in WoSIS ..