Performance and Kinetics of Anaerobic Digestion of Sewage Sludge Amended with Zero-Valent Iron Nanoparticles, Analyzed Using Sigmoidal Models DOI Creative Commons
Luiza Usevičiūtė, Tomas Januševičius, Vaidotas Danila

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(6), P. 1425 - 1425

Published: March 13, 2025

Sewage sludge was treated with nanoscale zero-valent iron (nZVI) to enhance biogas and methane (CH4) production, the influence of key parameters on material’s anaerobic digestion (AD) efficiency analyzed using sigmoidal mathematical models. In this study, three dosages nZVI (0.5%, 1.5% 3%) were added system accelerate decomposition process. The results showed that cumulative yield after 41 days increased by 23.9% in reactor a dosage 1.5%. Correspondingly, highest CH4 production enhancement 21.5% achieved compared control. indicated optimal for AD system, as it governed yields maximum removal total volatile solids. Additionally, predict evaluate kinetic parameters, eight models applied. According modified Gompertz, Richards logistic models, shortened lag phase from 11 5 Schnute model provided best fit experimental data due coefficients determination (R2: 0.9997–0.9999 at 3% dosages), well lowest Akaike’s Information Criterion values errors. This demonstrated its superior performance other

Language: Английский

Mathematical Model-Based Optimization of Trace Metal Dosage in Anaerobic Batch Bioreactors DOI Creative Commons
Tina Kegl, P. Balasubramanian,

Bikash Chandra Maharaj

et al.

Bioengineering, Journal Year: 2025, Volume and Issue: 12(2), P. 117 - 117

Published: Jan. 26, 2025

Anaerobic digestion (AD) is a promising and yet complex waste-to-energy technology. To optimize such process, precise modeling essential. Developing complex, mechanistically inspired AD models can result in an overwhelming number of parameters that require calibration. This study presents novel approach considers the role trace metals (Ca, K, Mg, Na, Co, Cr, Cu, Fe, Ni, Pb, Zn) modeling, numerical simulation, optimization process batch bioreactor. In this context, BioModel enhanced by incorporating influence metal activities on chemical, biochemical, physicochemical processes. Trace metal-related are also included calibration all model parameters. The model’s reliability rigorously validated comparing simulation results with experimental data. reveals perturbations 5% parameter values significantly increase discrepancy between simulated up to threefold. Additionally, highlights how additives enhance both quantity quality biogas production. optimal concentrations increased CH4 production 5.4% 13.5%, respectively, while H2, H2S, NH3 decreased 28.2%, 43.6%, 42.5%, respectively.

Language: Английский

Citations

1
Estimating Biogas Production from Organic Waste Through Anaerobic Co-Digestion DOI
Dowan Kim, Junbeum Kim

Journal of Cleaner Production, Journal Year: 2025, Volume and Issue: unknown, P. 145122 - 145122

Published: Feb. 1, 2025

Language: Английский

Citations

1
Sustainability of biomass use for renewable energy DOI

Johana A. Rivaldi,

Rocío E. Cardozo,

Cintia G. Fit

et al.

Elsevier eBooks, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Language: Английский

Citations

0
Performance and Kinetics of Anaerobic Digestion of Sewage Sludge Amended with Zero-Valent Iron Nanoparticles, Analyzed Using Sigmoidal Models DOI Creative Commons
Luiza Usevičiūtė, Tomas Januševičius, Vaidotas Danila

et al.

Energies, Journal Year: 2025, Volume and Issue: 18(6), P. 1425 - 1425

Published: March 13, 2025

Sewage sludge was treated with nanoscale zero-valent iron (nZVI) to enhance biogas and methane (CH4) production, the influence of key parameters on material’s anaerobic digestion (AD) efficiency analyzed using sigmoidal mathematical models. In this study, three dosages nZVI (0.5%, 1.5% 3%) were added system accelerate decomposition process. The results showed that cumulative yield after 41 days increased by 23.9% in reactor a dosage 1.5%. Correspondingly, highest CH4 production enhancement 21.5% achieved compared control. indicated optimal for AD system, as it governed yields maximum removal total volatile solids. Additionally, predict evaluate kinetic parameters, eight models applied. According modified Gompertz, Richards logistic models, shortened lag phase from 11 5 Schnute model provided best fit experimental data due coefficients determination (R2: 0.9997–0.9999 at 3% dosages), well lowest Akaike’s Information Criterion values errors. This demonstrated its superior performance other

Language: Английский

Citations

0