Microplastics – from Anthropogenic to Natural

Hanik, Nils; Amstutz, Véronique; Zinn, Manfred

doi:10.2533/chimia.2019.841

Cited by 6 publications

(2 citation statements)

References 18 publications

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“…showed that the surface water had already become contaminated not only with easily detectable plastic products but also with microplastics (particles smaller than 5 mm) that sediment only slowly. [11] A Swiss study revealed that the river Rhine was found to be more heavily polluted by microplastics than lakes. [12] Recently, microplastics have also been found in Swiss soil.…”

Section: Current State Of Plasticsmentioning

confidence: 99%

Development of Biopolyesters (PHA) as Part of the Swiss Priority Program in Biotechnology

Zinn

2020

Chimia

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The Swiss Priority Program in Biotechnology of the Swiss National Science Foundation that lasted between 1992 and 2001 had a boosting effect on many biotech disciplines and on the developments of polyhydroxyalkanoates (PHAs) in Switzerland in particular. The funding organization led by Prof. Oreste Ghisalba enabled a better understanding of the PHA biosynthesis and the development, as well as the implementation of novel bioprocesses (e.g. two-phase fermentations, multiple nutrient limited growth conditions, multi-stage chemostats, and product formation in different host organisms). However, production of PHA in Switzerland appeared to be impossible for cost reasons due to the strong competition from cheaper, petrol-based plastics. The recent reports on environmental issues with non-degradable plastics has triggered a general change in the perception of biodegradable plastics, giving them an added value and thus justifying a higher price. Ongoing research focuses on the sustainable production of PHAs using carbon waste streams, synthesis gas or even CO2

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Section: Current State Of Plasticsmentioning

confidence: 99%

Development of Biopolyesters (PHA) as Part of the Swiss Priority Program in Biotechnology

Zinn

2020

Chimia

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“…This puts a significant stress on the environment for several reasons: first, plastics are oil-derived polymers, which depend on a very extractive activity that is not only non-renewable but also potentially harmful to the environment [2]. Secondly, many traditional plastics are non-degradable under natural conditions and accumulate in the environment [3]. These materials have to be either recycled (which requires not only energy but also a lot of workforce required for classification, processing and administration), burned for energy recycling (contributing to CO 2 increase in the atmosphere) or stored (which requires an increasing amount of space) [4].…”

Section: Introductionmentioning

confidence: 99%

Modeling of Continuous PHA Production by a Hybrid Approach Based on First Principles and Machine Learning

et al. 2021

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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.

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Synergistic effects of microplastics and cyanotoxins on the demography of the rotifer Brachionus calyciflorus Pallas

Sánchez-Zamora,

Nandini,

Sarma

2024

Chemosphere

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Microplastics – from Anthropogenic to Natural

Cited by 6 publications

References 18 publications

Development of Biopolyesters (PHA) as Part of the Swiss Priority Program in Biotechnology

Development of Biopolyesters (PHA) as Part of the Swiss Priority Program in Biotechnology

Modeling of Continuous PHA Production by a Hybrid Approach Based on First Principles and Machine Learning

Synergistic effects of microplastics and cyanotoxins on the demography of the rotifer Brachionus calyciflorus Pallas

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