A novel mathematical approach for the understanding and optimization of two-phase partitioning bioreactors devoted to air pollution control

Abstract

Two-phase partitioning bioreactors (TPPBs) support the removal of volatile organic compounds (VOCs) from contaminated gaseous emissions at unprecedented rates and concentrations. TPPBs are biological multiphase systems provided with a non-aqueous phase (NAP) with high affinity for the target VOC. Although modeling of TPPBs is a research field that has rapidly evolved, recent experimental findings such as the direct VOC uptake from liquid NAPs and the quantification of simultaneous partial mass transfer coefficients have not been incorporated yet in a comprehensive mathematical description. In this work, a mathematical description of TPPBs, including continuous aqueous phase renewal and potential VOC uptake directly from the NAP, was developed. Model simulations indicated that TPPB performance can be enhanced by improving the partial mass transfer coefficient between the gas and the NAP (by increasing the contact between the gas and the NAP). The model also showed that microorganisms with half-saturation constants < 5 g m -3and ability to take up VOC directly from the NAP can boost significantly TPPB performance. The present modeling platform was tested against experimental data from literature for methane, hexane and dichloromethane and no parameter fitting was carried out.

Enhanced styrene removal in a two-phase partitioning bioreactor operated as a biotrickling filter: Towards full-scale applications

“…Thus, when the biomass-loaded silicone oil was added, the bioreactor was inoculated. Hydrophobic biomass attached to silicone oil was expected to improve the TPPB performance by allowing the direct pollutant uptake from silicone oil, avoiding the additional NAP-tobiomass mass transfer step as previously reported [17,25,26]. Furthermore, the microbial communities able to grow immersed in silicone oil must also exhibit a higher tolerance to styrene due to the process selection used for inoculation.…”

Biological technologies for the treatment of atmospheric pollutants

“…The Monod equation constitutes the simplest way to describe the microbial growth although, in some instances, toxicity issues or the effect of oxygen-limiting conditions must be included in the description of the microbial growth rate [102]. Thus, terms accounting for microbial inhibition (yielding the so-called Haldane-Andrews kinetic model, Equation (6)) and the effect of oxygen limitation (yielding the so-called double Monod kinetics, Equation (7)) can be added to Equation (5) as follows:…”

Determination and Analysis of Kinetic Parameters of Heterotrophic Bacteria in Mathematical Simulation

“…The amount of microbial reduce is another part of the decomposition produces slow biodegradable organic matter Xs, Xs is hydrolyzed to produce new microorganisms for the growth of other microorganisms that is regeneration. When the matrix has consumed completely, the Ss formed by the hydrolysis of the attenuated product Xs become the matrix of the remaining microbial growth (Dorado et al, 2015). At the time the oxygen consumed is only caused by the Ss produced by this partial hydrolysis that is only depends on the growth of the heterotrophic bacteria.…”

“…If the Ss produced by the hydrolysis of Xs and the Ss consumed by the microorganisms are equal (Eqs. [3][4][5][6].…”

“…From the above equations (Eqs. [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18], the maximum rate of growth is calculated from the slope as shown in the following table. From Table 3 it can be seen that the results of the maximum specific growth rate of heterotrophic bacteria show that the use of BI-2000 electrolyte respiration rate analyzer, the range is large and the range is roughly 7.72 d-1-10.05 d-1, the average is 8.6 d -1 compared with ASM1 model.…”