Modelling Mixed Microbial Culture Polyhydroxyalkanoate Accumulation Bioprocess towards Novel Methods for Polymer Production Using Dilute Volatile Fatty Acid Rich Feedstocks
Abstract
:1. Introduction
2. Materials and Methods
2.1. Biomass from a Lab-Scale SBR
2.2. Biomass from a Pilot-Scale SBR
2.3. Pulse-Stimulation Respiration Experiments
2.4. Analytical Methods
2.5. Dissolved Oxygen and Chemical Oxygen Demand Mass Balance
2.6. Monte Carlo Accumulation Process Simulation
3. Results and Discussion
3.1. Laboratory and Pilot MMC Enrichment Biomass Characterization
3.1.1. Model Evaluation with No Active Aeration
3.1.2. Model Evaluation with Active Aeration
- From Zone 2, the integral of Qos, the cumulative biochemical oxygen demand (BODs) due to substrate removal, was estimated. Then the average yield Yos and the trend of substrate concentration were calculated (Equation (2));
- From Zone 2, the trend of substrate uptake rate as a function of estimated substrate concentration was then used to determine remaining parameters (Equations (6)–(8)). The induction and downshift substrate affinity constants (ki and ks, respectively) were interpolated from the derived trend of substrate uptake rate as a function of interpreted substrate concentration. Remaining parameters were estimated by nonlinear least squares regression analysis (see Figure 4 and Figure 5).
3.1.3. Monte Carlo Simulation of PHA Accumulation in MMC Enrichment Biomass
3.1.4. Future Research Perspectives and Challenges
4. Conclusions
- A property of hysteresis in the dynamic response of MMCs storing PHA could be demonstrated for two distinct enrichment cultures using dissolved oxygen and chemical oxygen demand mass balance experiments.
- This hysteresis could be modelled with readily identifiable parameters using Monod equations describing the distinct upshift and downshift dynamics in substrate uptake rates as a function of substrate concentrations and as a function of time. It was found that the substrate concentration, required to stimulate a substrate uptake rate, was higher than the substrate concentration required to maintain an attained substrate uptake rate.
- The system of equations in numerical simulations suggest for an opportunity to exploit this property of hysteresis in industrial scale bioprocesses for PHA production. MMC PHA production processes can be operated with continuous feeding strategies, even with low concentration feedstocks. The model simulations found that engineered stimulation zones can be applied in continuous flow PHA production bioprocesses as a strategy to reach maximum possible performance in volumetric productivity without sacrificing performance in substrate utilization efficiency.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
ATR-FTIR | attenuated total reflection-FTIR |
BOD | biochemical oxygen demand |
COD | chemical oxygen demand |
DO | dissolved oxygen |
FTIR | Fourier transform infrared spectroscopy |
HRT | hydraulic retention time |
MMC | mixed microbial culture |
PHA | polyhydroxyalkanoate |
PHB | polyhydroxybutyrate |
SBR | sequencing batch reactor |
SRT | solids retention time |
VFA | volatile fatty acid |
VSS | volatile suspended solids |
WWTP | wastewater treatment plant |
PHA accumulation inhibition exponent | |
DO concentration (mgO2/L) | |
apparent maximum DO (saturation) concentration (mgO2/L) | |
exogenous dissolved substrate concentration (mgCOD/L) | |
initial or peak upshift (mgCOD/L) | |
/ | |
aeration oxygen mass transfer coefficient (1/min) | |
Haldane substrate inhibition constant (mgCOD/L) | |
substrate induction constant (mgCOD/L) | |
Monod apparent affinity constant on DO concentration (mgO2/L) | |
Monod apparent downshift affinity constant on substrate concentration (mgCOD/L) | |
Monod apparent upshift affinity constant on peak substrate concentration (mgCOD/L) | |
DO supply rate due to aeration (mgO2/L/min) | |
DO consumption rate due to endogenous respiration (mgO2/L/min) | |
DO consumption rate due to stored PHA (mgO2/L/min) | |
DO consumption reate due to substrate consumption (mgO2/L/min) | |
specific (mgO2/gVSS/min) | |
specific (mgO2/gVSS/min) | |
biomass resting specific substrate uptake rate (mgCOD/gVSS/min) | |
specific substrate uptake rate (mgCOD/gVSS/min) | |
maximum extant specific substrate uptake rate (mgCOD/gVSS/min) | |
initial maximum extant specific substrate uptake rate (mgCOD/gVSS/min) | |
maximum specific substrate uptake rate (mgCOD/gVSS/min) | |
t | time (minutes) |
biomass maximum upshift in specific substrate uptake rate (mgCOD/gVSS/min) | |
active biomass concentration (gVSS/L) | |
PHA concentration (gCOD/L) | |
yield of oxygen consumed with substrate (mgO2/mgCOD) | |
influent feedstock substrate concentration (mgCOD/L) | |
maintenance volume substrate concentration (mgCOD/L) | |
stimulation volume substrate concentration (mgCOD/L) | |
applied fraction of maximum possible organic loading rate | |
ith-active biomass element specific PHA level (/) | |
active biomass maximum PHA level for / | |
HRT in due to (min) | |
HRT in due to (min) | |
number of biomass elements in | |
substrate feed (and effluent) flow rate (L/min) | |
recirculation flow rate (L/min) | |
ith-biomass element maximum specific substrate uptake rate (mgCOD/gVSS/min) | |
maintenance volume (L) | |
stimulation volume (L) | |
element specific active biomass (gVSS/element) | |
element specific PHA content (gPHA/element) |
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Parameter | Units | Laboratory Scale | Pilot Scale |
---|---|---|---|
Temperature | °C | 24.6 ± 0.3 (24) | 23.8 ± 0.6 (17) |
pH (t = 0) | - | 9.2 ± 0.1 (24) | 9.0 ± 0.1 (17) |
Xa | gVSS/L | 1.0 ± 0.1 (11) | 1.71 ± 0.04 (2) |
ka | 1/min | 1.11 ± 0.14 (24) | 0.60 ± 0.15 (17) |
qoe | mgO2/gVSS/min | 0.64 ± 0.12 (24) | 0.25 ± 0.07 (17) |
Yos | gO2/gCOD | 0.26 ± 0.02 (24) | 0.23 ± 0.05 (17) |
ks | mgCOD/L | 2.0 ± 0.7 (24) | 1.8 ± 0.4 (17) |
ku | mgCOD/L | 38 ± 7 (24) | 20 ± 2 (17) |
mgCOD/gVSS/min | 7.4 ± 0.1 (24) | 2.5 ± 0.2 (17) | |
mgCOD/gVSS/min | 21.1 ± 1.1 (24) | 6.8 ± 0.2 (17) |
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Werker, A.; Lorini, L.; Villano, M.; Valentino, F.; Majone, M. Modelling Mixed Microbial Culture Polyhydroxyalkanoate Accumulation Bioprocess towards Novel Methods for Polymer Production Using Dilute Volatile Fatty Acid Rich Feedstocks. Bioengineering 2022, 9, 125. https://doi.org/10.3390/bioengineering9030125
Werker A, Lorini L, Villano M, Valentino F, Majone M. Modelling Mixed Microbial Culture Polyhydroxyalkanoate Accumulation Bioprocess towards Novel Methods for Polymer Production Using Dilute Volatile Fatty Acid Rich Feedstocks. Bioengineering. 2022; 9(3):125. https://doi.org/10.3390/bioengineering9030125
Chicago/Turabian StyleWerker, Alan, Laura Lorini, Marianna Villano, Francesco Valentino, and Mauro Majone. 2022. "Modelling Mixed Microbial Culture Polyhydroxyalkanoate Accumulation Bioprocess towards Novel Methods for Polymer Production Using Dilute Volatile Fatty Acid Rich Feedstocks" Bioengineering 9, no. 3: 125. https://doi.org/10.3390/bioengineering9030125