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This article in JEQ

  1. Vol. 33 No. 6, p. 2333-2342
    Received: Mar 1, 2004

    * Corresponding author(s): Benoit.Gabrielle@grignon.inra.fr


Simulating Urban Waste Compost Effects on Carbon and Nitrogen Dynamics Using a Biochemical Index

  1. Benoît Gabrielle *,
  2. Jeanne Da-Silveira,
  3. Sabine Houot and
  4. Cédric Francou
  1. Environment and Arable Crops Research Unit, Institut National de la Recherche Agronomique, 78850 Thiverval-Grignon, France


Composting has emerged as a valuable route for the disposal of urban waste, with the prospect of applying composts on arable fields as organic amendments. Proper management of urban waste composts (UWCs) requires a capacity to predict their effects on carbon and nitrogen dynamics in the field, an issue in which simulation models are expected to play a prominent role. However, the parameterization of soil organic amendments within such models generally requires laboratory incubation data. Here, we evaluated the benefit of using a biochemical index based on Van Soest organic matter fractions to parameterize a deterministic model of soil C and N dynamics, NCSOIL, as compared with a standard alternative based on laboratory incubation data. The data included C mineralization and inorganic N dynamics in samples of a silt loam soil (Typic Hapludalf) mixed with various types of UWC and farmyard manure. NCSOIL successfully predicted the various nitrogen mineralization–immobilization patterns observed, but underestimated CO2 release by 10 to 30% with the less stable amendments. The parameterization based on the biochemical index achieved a prediction error significantly larger than the standard parameterization in only 10% of the tested cases, and provided an acceptable fit to experimental data. The decomposition rates and C to N ratios of compost organic matter varied chiefly according to the type of waste processed. However, 62 to 66% of their variance could be explained by the biochemical index. We thus suggest using the latter to parameterize organic amendments in C and N models as a substitute for time-consuming laboratory incubations.

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