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Estimating annual N 2 O emissions from agricultural soils in temperate climates
Author(s) -
Roelandt Caroline,
Van Wesemael Bas,
Rounsevell Mark
Publication year - 2005
Publication title -
global change biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.146
H-Index - 255
eISSN - 1365-2486
pISSN - 1354-1013
DOI - 10.1111/j.1365-2486.2005.01025.x
Subject(s) - environmental science , greenhouse gas , grassland , temperate climate , soil water , precipitation , climate change , agriculture , spatial variability , atmospheric sciences , coupled model intercomparison project , climatology , climate model , meteorology , soil science , ecology , geography , statistics , mathematics , geology , biology
The Kyoto protocol requires countries to provide national inventories for a list of greenhouse gases including N 2 O. A standard methodology proposed by the Intergovernmental Panel on Climate Change (IPCC) estimates direct N 2 O emissions from soils as a constant fraction (1.25%) of the nitrogen input. This approach is insensitive to environmental variability. A more dynamic approach is needed to establish reliable N 2 O emission inventories and to propose efficient mitigation strategies. The objective of this paper is to develop a model that allows the spatial and temporal variation in environmental conditions to be taken into account in national inventories of direct N 2 O emissions. Observed annual N 2 O emission rates are used to establish statistical relationships between N 2 O emissions, seasonal climate and nitrogen‐fertilization rate. Two empirical models, MCROPS and MGRASS, were developed for croplands and grasslands. Validated with an independent data set, MCROPS shows that spring temperature and summer precipitation explain 35% of the variance in annual N 2 O emissions from croplands. In MGRASS, nitrogen‐fertilization rate and winter temperature explain 48% of the variance in annual N 2 O emissions from grasslands. Using long‐term climate observations (1900–2000), the sensitivity of the models with climate variability is estimated by comparing the year‐to‐year prediction of the model to the precision obtained during the validation process. MCROPS is able to capture interannual variability of N 2 O emissions from croplands. However, grassland emissions show very small interannual variations, which are too small to be detectable by MGRASS. MCROPS and MGRASS improve the statistical reliability of direct N 2 O emissions compared with the IPCC default methodology. Furthermore, the models can be used to estimate the effects of interannual variation in climate, climate change on direct N 2 O emissions from soils at the regional scale.