Abstract
LCA outputs are often presented as point estimates measuring potential impacts although average impacts values may be misleading to rank different options, especially in the case of agricultural products. In an LCA study comparing different slurry application techniques, NH3 and N2O emissions have been estimated through two approaches, experimental data collected from the literature and mathematical simulations over different soil and climate conditions. Both approaches lead to similar ranges of emissions; however the simulation-based approach allows us to construct a probability distribution of emissions whereas the limited number of experimental studies leads only to the definition of a range of emissions. A better knowledge of the variability of emissions helps the practitioner to sort alternatives and to detect situations where they are not discernable. Moreover the knowledge of the distribution and of its most impacting sources of variability leads to the definition of more informative and significant typologies.
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References
Finnveden G, Hauschild MZ, Ekvall T, Guinée J, Heijungs R, Hellweg S, Koehler A, Pennington D, Suh S (2009) Recent developments in Life Cycle Assessment. J Environ Manage 91(1):1–21.
Björklund AE (2002) Survey of approaches to improve reliability in LCA. Int J Life Cycle Assess 7(2):64–72.
Langevin B, Basset-Mens C, Lardon L (2010) Inclusion of the variability of diffuse pollutions in LCA for agriculture: the case of slurry application techniques. J Cleaner Prod 18(8):747–755.
Galloway JN, Cowling EB, Seitzinger SP, Socolow, RH (2002) Reactive nitrogen: Too much of a good thing ?. Ambio 31(2):60–63.
Langevin B (2010) Prise en compte de la variabilité des émissions au champ dans l’Analyse de Cycle de Vie des systèmes agricoles. Application à l’épandage de lisier. Dissertation, École Nationale Supérieure d'Arts et Métiers, Paris
Brisson N, Mary B, Ripoche D, Jeuffroy MH, Ruget F, Nicoullaud B, Gate P, Devienne-Barret F, Antonioletti R, Durr C, Richard G, Beaudoin N, Recous S, Tayot X, Plenet D, Cellier P, Machet JM, Meynard JM, Delécolle R (1998) STICS: A generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn. Agron Sust Dev 18(5–6):311–346.
Génermont S, Cellier P (1997) A mechanistic model for estimating ammonia volatilization from slurry applied to bare soil. Agricultural and Forest Meteorology 88(1–4):145–167.
Le Cadre E, (2004) Modélisation de la volatilisation de l’ammoniac en interaction avec les processus chimiques et biologiques du sol: le modèle Volt’Air. Dissertation, INA-PG, Paris, France
O'Sullivan MF, Henshall JK, Dickson JW (1999) A simplified method for estimating soil compaction. Soil Tillage Res 49(4):325–335.
Wösten JHM, Lilly A, Nemes A, Le Bas C (1999) Development and use of a database of hydraulic properties of European soils. Geoderma 90(3–4):169–185.
Schaap MG, Leij FJ, Van Genuchten MT (2001) Rosetta: A computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions. J Hydrol 251(3–4):163–176.
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Langevin, B., Lardon, L., Basset-Mens, C. (2011). The Use of Models to Account for the Variability of Agricultural Data. In: Finkbeiner, M. (eds) Towards Life Cycle Sustainability Management. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1899-9_29
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DOI: https://doi.org/10.1007/978-94-007-1899-9_29
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