4.8 Article

Calcium ion can alleviate ammonia inhibition on anaerobic digestion via balanced-strengthening dehydrogenases and reinforcing protein-binding structure: Model evaluation and microbial characterization

期刊

BIORESOURCE TECHNOLOGY
卷 354, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.biortech.2022.127165

关键词

Anaerobic Digestion Model No.1; Ammonia inhibition; Methanogenesis; Lactate; Functional enzyme

资金

  1. National Key R&D Program of China [2017YFE0133300]
  2. Beijing Nova Program [Z201100006820022]
  3. Na-tional Natural Science Foundation of China [U20B2022]
  4. Key Sci-ence and Technology Development Program of Xinjiang Corps [2021DB006]

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This study combined experimental investigation and model simulation to explore the effect of metal ions on mitigating ammonia inhibition during anaerobic digestion. The results showed that the addition of Ca can increase methane production through enhancing dehydrogenase activity and reinforcing protein binding structure. Gene sequencing results indicated an increase in the activity of acetotrophic and hydrogenotrophic dehydrogenases after Ca addition.
Experimental investigation and model simulation was combined to identify the effect of metal ions on mitigating ammonia inhibition during anaerobic digestion. Five metal ions (Ca, Mg, Cu, Zn, Fe) were tested in reactors with 1 g-glucose/L/d and 5 g-N/L under fed batch operation. Ca addition was considered the optimal approach with a 25% increment in methane production via balanced-strengthening dehydrogenases and reinforcing proteinbinding structure. Gene-sequencing results suggested 50% and 15% increment in acetotrophic-related and hydrogenotrophic-related dehydrogenases, respectively, after Ca addition. The Anaerobic Digestion Model No.1 was modified by introducing lactate-related reactions, syntrophic acetate oxidation process, and kinetic equation of metal ions, with satisfactory predictions of methane and intermediates (R-2 > 0.80). The lowest affinity constant KI_MI value was obtained with Ca supplement, indicating the highest conversion rate of substrates to methane. The model evaluation revealed the balanced ratio on the enzyme contribution of acetotrophic to hydrogenotrophic methanogenesis.

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