Polycyclic aromatic hydrocarbons (PAHs) and volatile organic compounds (VOCs) are important indoor contaminants. Their hydrophobic nature hinders the possibility of biological abatement using biofiltration. Our aim was to establish whether the use of a consortium of Fusarium solani and Rhodococcus erythropolis shows an improved performance (in terms of mineralization rate and extent) towards the degradation of formaldehyde, as a slightly polar VOC; toluene, as hydrophobic VOC; and benzo[α]pyrene (BaP) as PAH at low concentrations compared to a single-species biofilm in serum bottles with vermiculite as solid support to mimic a biofilter and to relate the possible improvements with the surface hydrophobicity and partition coefficient of the biomass at three different temperatures. Results showed that the hydrophobicity of the surface of the biofilms was affected by the hydrophobicity of the carbon source in F. solani but it did not change in R. erythropolis. Similarly, the partition coefficients of toluene and BaP in F. solani biomass (both as pure culture and consortium) show a reduction of up to 38 times compared to its value in water, whereas this reduction was only 1.5 times in presence of R. erythropolis. Despite that increments in the accumulated CO and its production rate were found when F. solani or the consortium was used, the mineralization extent of toluene was below 25%. Regarding BaP degradation, the higher CO production rates and percent yields were obtained when a consortium of F. solani and R. erythropolis was used, despite a pure culture of R. erythropolis exhibits poor mineralization of BaP.

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This work presents a novel, differentiable, way of solving dynamic Flux Balance Analysis (dFBA) problems by embedding flux balance analysis of metabolic network models within lumped bulk kinetics for biochemical processes. The proposed methodology utilizes transformation of the bounds of the embedded linear programming problem of flux balance analysis via a logarithmic barrier (interior point) approach. By exploiting the first-order optimality conditions of the interior-point problem, and with further transformations, the approach results in a system of implicit ordinary differential equations. Results from four case studies, show that the CPU and wall-times obtained using the proposed method are competitive with existing state-of-the art approaches for solving dFBA simulations, for problem sizes up to genome-scale. The differentiability of the proposed approach allows, using existing commercial packages, its application to the optimal control of dFBA problems at a genome-scale size, thus outperforming existing formulations as shown by two dynamic optimization case studies.

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