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Water Science & Technology
Article . 2018 . Peer-reviewed
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Water Science & Technology
Article . 2018 . Peer-reviewed
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Sensitivity analysis for an elemental sulfur-based two-step denitrification model

Authors: Kostrytsia, A.; Papirio, S.; Mattei, M. R.; Frunzo, L.; Lens, P. N. L.; Esposito, G.;

Sensitivity analysis for an elemental sulfur-based two-step denitrification model

Abstract

Abstract A local sensitivity analysis was performed for a chemically synthesized elemental sulfur (S0)-based two-step denitrification model, accounting for nitrite (NO2−) accumulation, biomass growth and S0 hydrolysis. The sensitivity analysis was aimed at verifying the model stability, understanding the model structure and individuating the model parameters to be further optimized. The mass specific area of the sulfur particles (a*) and hydrolysis kinetic constant (k1) were identified as the dominant parameters on the model outputs, i.e. nitrate (NO3−), NO2− and sulfate (SO42−) concentrations, confirming that the microbially catalyzed S0 hydrolysis is the rate-limiting step during S0-driven denitrification. Additionally, the maximum growth rates of the denitrifying biomass on NO3− and NO2− were detected as the most sensitive kinetic parameters.

Country
Italy
Keywords

Elemental sulfur, Environmental Engineering, Biological surface-based hydrolysis; Elemental sulfur; Mathematical modeling; Sensitivity analysis; Two-step autotrophic denitrification; Environmental Engineering; Water Science and Technology, Two-step autotrophic denitrification, Bioreactors, European Joint Doctorates, European Commission, Knowmad Institut, Biological surface-based hydrolysis, Nitrites, Netherlands, Water Science and Technology, Aurora Universities Network, EC, Nitrates, H2020, Energy Research, Denitrification, Mathematical modeling, Sensitivity analysis, Sulfur

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    8
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Average
Green
gold