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Abstract: Microplastics (MPs) that are ubiquitous in aquatic environments and industrial wastewater streams have been identified as key hotspots of MP contamination. It is significantly more effective to remove MPs at these points before they enter municipal wastewater streams. This study is an environmental assessment of a novel pilot plant for the removal of MPs and the chemical oxygen demand (COD) from wastewater with a high MP contamination from a plastics manufacturer in Germany. MP removal is based on physical–chemical agglomeration–fixation by organosilanes. Formed agglomerates are separated using a belt filter. The COD is removed by an adsorption process. The resulting MP removal was 98.0 ± 1.1% by mass and 99.9987 ± 0.0007% by particle count, while the COD was reduced by 96 ± 2.7%. The system’s sustainability is evaluated using the Life Cycle Assessment methodology, evaluating system construction, operation, and end-of-life considerations. The current pilot plant is also compared to an optimized circular and sustainable upgrade, where drivers of environmental burdens are eliminated and collected MPs are reused. Significant reductions in environmental impact categories are achieved and the global warming potential is reduced by 96%. This study provides a sustainability assessment of a novel technology and circular solution to remove MPs from highly polluted industrial wastewater.
Keywords: microplastics, life cycle assessment, impact analysis, removal technology, sustainable process design, carbon footprint, water quality, circular economy
Published in DKUM: 14.03.2025; Views: 0; Downloads: 3
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Abstract: The research aim was to remove as many microfibres, microplastics and harmful bacteria as possible from the polluted water to produce suitable water for reuse. The test water was the effluent from the municipal wastewater treatment plant in Shalek Valley. A pilot plant with a ceramic SiC filter for membrane filtration and ozonation of filtered water was set up to remove suspended solids, micro-fibres, microplastics, and harmful microorganisms. The Microfibers Detection System was developed to identify microfibers on-site. The results showed that the microfiltration system combined with ozone treatment effectively removed total suspended solids, microfibres, microplastics and microorganisms. A detection system method for identifying microfibres and microplastic particles was used to determine how many microfibres and microorganisms were identified by membrane filtration and ozonation. The study showed that membrane filtration successfully removed all microfibres, 88% of total coliforms and 93% of E. coli. After additional ozonation, we achieved a 100% removal rate of total coliforms and a 100% removal rate of E. coli. The treated water (effluent from the municipal wastewater treatment plant) can be used for specific purposes, such as agricultural irrigation or enhancing bathing waters near the plant’s water effluent.
Keywords: microfibres removal, microplastics, microfiltration, ozonation, water reuse
Published in DKUM: 26.09.2024; Views: 0; Downloads: 159
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Abstract: Microplastics are small pieces of plastic (smaller than 5 mm), which can be found in the environment and can be dangerous to living beings. It is expected that the abundance of microplastics will rise in the future. However, there are still no standard protocols for monitoring the microplastic abundance, which should include spectroscopic methods for an automated discrimination in order to produce reliable data. In this work we examined a new approach for microplastic detection based on the photoluminescence (PL) spectroscopy. To test the applicability of the proposed method a low-cost setup was built and characterized. The PL spectra from 27 different materials were collected and compared. The comparison of the spectra shows that the differentiation between samples is possible, especially between the plastic and non-plastic materials. Furthermore, the measured PL spectra also differ for different plastic types and other materials. However, the presence of dyes in plastic samples and incrustation of plastic samples by organic materials can affect the PL spectra and make the recognition troublesome. Disregarding organic materials and dyed plastic, the material differentiation based on the acquired PL spectra using neural networks resulted in 99.3 % accuracy when categorizing samples into plastic and non-plastic materials and 63.1 % accuracy when categorizing samples among different plastic and non-plastic materials. The promising results show that the PL spectroscopy of microplastics could outperform the spectroscopic methods used so far, by means of measurement speed and lateral resolution.
Keywords: microplastics, detection methods, photoluminescence spectroscopy, neural networks
Published in DKUM: 10.08.2016; Views: 1911; Downloads: 171
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