Improving Estimates of Nitrogen Emissions for Life Cycle Assessment of Cropping Systems at the Scale of an Agricultural Territory

Autor: Valérie Viaud, Virginie Parnaudeau, Françoise Vertès, Michael S. Corson, Christian Walter, Hayo M.G. van der Werf, Joël Aubin, Laure Nitschelm
Přispěvatelé: Sol Agro et hydrosystème Spatialisation (SAS), Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST, AGROCAMPUS OUEST, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de la Recherche Agronomique (INRA), INRA, Conseil Regional de Bretagne (Brittany region), Agrocampus Ouest, AGROCAMPUS OUEST-Institut National de la Recherche Agronomique (INRA)
Rok vydání: 2017
Předmět:
Zdroj: Environmental Science & Technology
Environmental Science & Technology, American Chemical Society, 2018, 52 (3), pp.1330-1338. ⟨10.1021/acs.est.6b03865⟩
Environmental Science and Technology
Environmental Science and Technology, American Chemical Society, 2018, 52 (3), pp.1330-1338. ⟨10.1021/acs.est.6b03865⟩
ISSN: 1520-5851
0013-936X
Popis: International audience; In life cycle assessment (LCA), simple models are currently used to estimate cropping system nitrogen (N) emissions on farms. At large spatial scales (e.g., countries), these models are valid. At a smaller spatial scale (e.g., territories), these models may be less accurate, since they completely or partially ignore local conditions such as management practices, soil or climate. The purpose of this study was to consider the variability of those factors when estimating N emissions in LCA at the watershed scale. To this end, Syst’N, decision-support software based on a simulation model of crop and soil N dynamics at field and crop-rotation scales, was applied to predict N emissions from cropping systems in a coastal watershed (Lieue de Grève, France). Syst’N predictions were compared to N emissions estimated by AGRIBALYSE, a static site-dependent method at field and single-crop scales. Syst’N was more sensitive to site-specific soil properties than AGRIBALYSE. Estimates of N emissions that include spatial variability in soil and climate therefore become possible in LCA when a simulation model such as Syst’N is used in the inventory phase.
Databáze: OpenAIRE