Search Results (5)

The number of bioprocesses for the circular economy of organic waste has grown in recent years. Implementation of new processes and technologies should consider occupational health and safety issues from the initial design stages. Among the process hazards analysis techniques, HAZard and OPerability (HAZOP) methodology is widely used for studying both the process’s hazards and their operability problems, by exploring the effects of any deviations from design conditions. In the present study, a modified version of HAZOP methodology has been applied to a three-steps process developed at pilot scale in the Treviso municipal wastewater treatment plant in order to produce polyhydroxyalkanoate (PHA) as the final high value product. This paper shows the results of HAZOP analysis applied to the first process step (acidogenic fermentation) aimed at volatile fatty acids production. The analysis has been applied to the process conditions corresponding to the maximum PHA content in the biomass. The HAZOP study results showed that this methodology allowed a comprehensive exploration of conventional chemical engineering process hazards and biological hazards. Final piping and instrumentation diagrams (P&IDs) for acidogenic fermentation have been designed, identifying all prevention measures aimed at managing the hazard and operability issues. The P&ID shows the interconnection of equipment and the instrumentation required for controlling the process. Full article

This paper focuses on the design of soft sensors for on-line monitoring of the biotechnological process of biopolymer production, in which biopolymers are accumulated in bacteria as an intracellular energy storage material. The proposed soft sensors for on-line estimation of the biopolymer concentration represent an interesting alternative to the traditional off-line analytical techniques of limited applicability for real-time process control. Due to the complexity of biochemical reactions, which make it difficult to create reasonably complex first-principle mathematical models, a data-driven approach to the design of soft sensors has been chosen in the presented study. Thus, regression methods were used in this design, including multivariate statistical methods (PLS, PCR). This approach enabled the creation of soft sensors using historical process data from fed-batch cultivations of the Pseudomonas putida KT2442 strain used for the production of medium-chain-length polyhydroxyalkanoates (mcl-PHAs). Specifically, data from on-line measurements of off-gas composition analysis and culture medium capacitance were used as input to the soft sensors. The resulting soft sensors allow not only on-line estimation of the biopolymer concentration, but also the concentration of the cell biomass of the production bacterial culture. For most of these soft sensors, the estimation error did not exceed 5% of the measurement range. In addition, soft sensors based on capacitance measurement were able to accurately detect the end of the production phase. This study thus offers an innovative and practically relevant contribution to the field of monitoring of bioprocesses used for the production of medium-chain-length biopolymers. Full article

Polyhydroxyalkanoates (PHA) are renewable alternatives to traditional oil-derived polymers. PHA can be produced by different microorganisms in continuous culture under specific media composition, which makes the production process both promising and challenging. In order to achieve large productivities while maintaining high yield and efficiency, the continuous culture needs to be operated in the so-called dual nutrient limitation condition, where both the nitrogen and carbon sources are kept at very low concentrations. Mathematical models can greatly assist both design and operation of the bioprocess, but are challenged by the complexity of the system, in particular by the dual nutrient-limited growth phenomenon, where the cells undergo a metabolic shift that abruptly changes their behavior. Traditional, non-structured mechanistic models based on Monod uptake kinetics can be used to describe the bioreactor operation under specific process conditions. However, in the absence of a model description of the metabolic phenomena inside the cell, the extrapolation to a broader operation domain (e.g., different feeding concentrations and dilution rates) may present mismatches between the predictions and the actual process outcomes. Such detailed models may require almost perfect knowledge of the cell metabolism and omic-level measurements, hampering their development. On the other hand, purely data-driven models that learn correlations from experimental data do not require any prior knowledge of the process and are therefore unbiased and flexible. However, many more data are required for their development and their extrapolation ability is limited to conditions that are similar to the ones used for training. An attractive alternative is the combination of the extrapolation power of first principles knowledge with the flexibility of machine learning methods. This approach results in a hybrid model for the growth and uptake rates that can be used to predict the dynamic operation of the bioreactor. Here we develop a hybrid model to describe the continuous production of PHA by Pseudomonas putida GPo1 culture. After training, the model with experimental data gained under different dilution rates and medium compositions, we demonstrate how the model can describe the process in a wide range of operating conditions, including both single and dual nutrient-limited growth. Full article

Waste of industrial origin produced from synthetic materials are a serious threat to the natural environment. The ending resources of fossil raw materials and increasingly restrictive legal standards for the management of plastic waste have led to research on the use of biopolymers, which, due to their properties, may be an ecological alternative to currently used petrochemical polymers. Polyhydroxyalkanoates (PHAs) have gained much attention in recent years as the next generation of environmentally friendly materials. Currently, a lot of research is being done to reduce the costs of the biological process of PHA synthesis, which is the main factor limiting the production of PHAs on the industrial scale. The volatile fatty acids (VFAs) produced by anaerobic digestion from organic industrial and food waste, and various types of wastewater could be suitable carbon sources for PHA production. Thus, reusing the organic waste, while reducing the future fossil fuel, originated from plastic waste. PHA production from VFAs seem to be a good approach since VFAs composition determines the constituents of PHAs polymer and is of great influence on its properties. In order to reduce the overall costs of PHA production to a more reasonable level, it will be necessary to design a bioprocess that maximizes VFAs production, which will be beneficial for the PHA synthesis. Additionally, a very important factor that affects the profitable production of PHAs from VFAs is the selection of a microbial producer that will effectively synthesize the desired bioproduct. PHA production from VFAs has gained significant interest since VFAs composition determines the constituents of PHA polymer. Thus far, the conversion of VFAs into PHAs using pure bacterial cultures has received little attention, and the majority of studies have used mixed microbial communities for this purpose. This review discusses the current state of knowledge on PHAs synthesized by microorganisms cultured on VFAs. Full article

Polyhydroxyalkanoates (PHAs) are a group of biopolymers produced in various microorganisms as carbon and energy reserve when the main nutrient, necessary for growth, is limited. PHAs are attractive substitutes for conventional petrochemical plastics, as they possess similar material properties, along with biocompatibility and complete biodegradability. The use of PHAs is restricted, mainly due to the high production costs associated with the carbon source used for bacterial fermentation. Cyanobacteria can accumulate PHAs under photoautotrophic growth conditions using CO₂ and sunlight. However, the productivity of photoautotrophic PHA production from cyanobacteria is much lower than in the case of heterotrophic bacteria. Great effort has been focused to reduce the cost of PHA production, mainly by the development of optimized strains and more efficient cultivation and recovery processes. Minimization of the PHA production cost can only be achieved by considering the design and a complete analysis of the whole process. With the aim on commercializing PHA, this review will discuss the advances and the challenges associated with the upstream processing of cyanobacterial PHA production, in order to help the design of the most efficient method on the industrial scale. Full article