Mathematical model for optimal operation of an ex-situ hydrogenotrophic methanation bio-trickling filter reactor

To upgrade biogas to biomethane, a mathematical model approach for a hydrogenotrophic methanation process is formulated in a biotrickling filter (BTF) reactor. The model partitions the trickling bed (TB) space in arbitrary levels of possibly different volumes and uses the first Fickian diffusion law along the vertical axis and through the biofilm layer attached to the inert bed material. To calculate gas flows among TB levels, the model is subject to the ideal gas law and to the partial pressures Dalton’s law, assuming a fixed amount of gaseous moles in each TB level. In addition to the available control variables, such as the liquid recirculation rate and the gaseous inflow rate, the gaseous effluent recirculation rate is tested as a new control variable for the model. The simulations performed of the model accurately describe experimental results of an ex-situ hydrogenotrophic methanation in a BTF. Finally, an optimal steady-state operation study for BTFs with certain physicochemical parameters is provided for any TB reactor size, and other operational improvements for the model, such as additional gaseous influent injections along the TB, are outlined. • Fickian diffusion-based mathematical model proposal fits well the experimental data. • Analysis of effluent gaseous recirculation as control variable. • Steady-state operation directive for maximising biomethane productivity and purity.

Authors

Institutions

Publication Details

Journal
Journal of Process Control
Published
2026-01-29
DOI
https://doi.org/10.1016/j.jprocont.2026.103631
Primary Topic
Anaerobic Digestion and Biogas Production
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mathematical model for optimal operation of an ex-situ hydrogenotrophic methanation bio-trickling filter reactor

Alejandro Vargas, Fernando Aarón Ortiz-Ricárdez, Karla María Muñoz-Páez
Journal of Process Control
Anaerobic Digestion and Biogas Production
article

Mathematical model for optimal operation of an ex-situ hydrogenotrophic methanation bio-trickling filter reactor

Alejandro Vargas, Fernando Aarón Ortiz-Ricárdez, Karla María Muñoz-Páez
article en

Abstract

To upgrade biogas to biomethane, a mathematical model approach for a hydrogenotrophic methanation process is formulated in a biotrickling filter (BTF) reactor. The model partitions the trickling bed (TB) space in arbitrary levels of possibly different volumes and uses the first Fickian diffusion law along the vertical axis and through the biofilm layer attached to the inert bed material. To calculate gas flows among TB levels, the model is subject to the ideal gas law and to the partial pressures Dalton’s law, assuming a fixed amount of gaseous moles in each TB level. In addition to the available control variables, such as the liquid recirculation rate and the gaseous inflow rate, the gaseous effluent recirculation rate is tested as a new control variable for the model. The simulations performed of the model accurately describe experimental results of an ex-situ hydrogenotrophic methanation in a BTF. Finally, an optimal steady-state operation study for BTFs with certain physicochemical parameters is provided for any TB reactor size, and other operational improvements for the model, such as additional gaseous influent injections along the TB, are outlined. • Fickian diffusion-based mathematical model proposal fits well the experimental data. • Analysis of effluent gaseous recirculation as control variable. • Steady-state operation directive for maximising biomethane productivity and purity.

Journal of Process ControlVol. 159
Universidad Nacional Autónoma de México (MX)
Openalex Percentile: Top 73%
Anaerobic Digestion and Biogas Production
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.