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Transient Microsite Models of Denitrification: II. Model Results
Author(s) -
McConnaughey P. K.,
Bouldin D. R.
Publication year - 1985
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj1985.03615995004900040020x
Subject(s) - denitrification , chemistry , saturation (graph theory) , michaelis–menten kinetics , diffusion , nitrate , thermodynamics , analytical chemistry (journal) , nitrogen , mathematics , chromatography , physics , organic chemistry , combinatorics , enzyme assay , enzyme
Solutions to four models of denitrification are presented. The models are based on four coupled reaction‐diffusion equations, each model describing a different type of reaction term. The equations were solved by standard finite‐difference methods and a boundary tracking technique when needed. For a chosen test problem, the zero‐order model predicted sequential reduction of nitrogenous species, a N 2 /N 2 O ratio of 0.17, and relatively high transient NO ‐ 2 levels. The Michaelis‐Menten model with threshold and concentration‐dependent NO ‐ 3 and NO ‐ 2 inhibition of N 2 O reduction predicted N 2 /N 2 O ratios of 19.15 and 6.69, respectively. The competitive inhibition model predicted a N 2 /N 2 O ratio of 0.23 and N 2 evolution followed N 2 O. A sensitivity analysis of the Michaelis‐Menten model with concentration‐dependent inhibition showed that the species of gaseous N evolved depended strongly on NO ‐ 3 levels in the soil. N 2 /N 2 O ratios were also influenced by O 2 fluxes, diffusion coefficients, and diffusion distances that affect anaerobic volume and solute transport. The predicted N 2 /N 2 O ratios were less sensitive to the Michaelis‐Menten kinetic parameters V i max and K i M where i = nitrate, nitrite, or nitrous oxide. The qualitative behavior of gaseous N evolution as a function of nitrate levels, gaseous oxygen concentration, and depth of saturation predicted by the models agrees with data in the literature.