Identification of microplastics in wastewater after cascade filtration using Pyrolysis-GC-MS.

The combination of a representative microplastic sampling method and a fast-quantitative analysis using Pyrolysis-GC-MS (Py-GC-MS) for investigation of the microplastic load and mass balances is presented in this work. A representative microplastic filtration requires a method allowing quick extraction of the sample. The developed steel based cascadic microplastic filtration uses steel basket filters with mesh sizes of 100 µm, 50 µm and 10 µm and a mean recovery of 86 % without cross contamination was achieved. Thermoanalytical methods have the advantage of minimal sample preparation with short analysis times. The presented platinum filament-based Py-GC-MS method requires little sample preparation and quantification limits for polystyrene (PS) and polyethylene (PE) were 0.03 µg and 1 µg absolute, respectively. The relative standard deviation of the analytical method is 11 %. The combined method allows representative sampling and analysis of MP from water bodies and waste water treatment plants within 48 h. •Presentation of a validated steel based cascadic microplastic filtration plant.•Fast and reproduceable Py-GC-MS analysis method for microplastic.•Py-GC-MS allows microplastic analysis with little sample preparation.

Hydrophobicity-water/air-based enrichment cell for microplastics analysis within environmental samples: A proof of concept.

The analysis of microplastics in sediments, soils or beach samples is commonly paired with a separation step to enrich microplastics or to remove non-plastics, respectively. Those steps are often very time consuming and are performed in presence of high concentrated solvents. The latter are also suspected to corrode or decompose the analyte particles, which hamper further identification processes. This paper describes a new fast and effective microplastics separation apparatus for analytical issues that was based on hydrophobic adhesion of microplastics and fine air bubbles. The presented prototype could successfully enrich over 90 %wt of 30ppmw microplastics in 200 g sand in 20 min. Additionally, it could be demonstrated that the new separation technique was very suitable for further microplastics identification by FTIR microscopy. In this context, a sample with different polymers and matrix components was analyzed and the results were presented within this article. •Microplastics were enriched selectively by hydrophobic adhesion.•No additional chemicals except water and air were used.•Separation took only 20 min and 90 %wtof microplastics were recovered.

Automated rapid & intelligent microplastics mapping by FTIR microscopy: A Python-based workflow.

The analysis of environmental microplastic particles using FTIR microscopy is a challenging task, due to the very high number of individual particles within a single sample. Therefore, automatable, fast and robust approaches are highly requested. Micro particles were commonly enriched on filters, and sub- or the whole filter area was investigated, which took more than 20h and produced millions of data, which had to be evaluated. This paper presents a new approach of such filter area analysis using an intelligent algorithm to measure only those spots on a filter that would produce evaluable FTIR data. Empty spaces or IR absorbers like carbon black particles were not measured which successfully reduced the total analysis time from 50h to 7h. The presented method is based on system independent Python workflow and can easily be implemented on other FTIR systems. •Fast and intelligent FTIR microscopy area mapping without FPA detector•Total time reduction from 50 h to 7 h•Platform independent approach based on Python.

Robust Automatic Identification of Microplastics in Environmental Samples Using FTIR Microscopy.

The analysis of microplastics is mainly performed using Fourier transformation infrared spectroscopy/microscopy (FTIR/ µFTIR). However, in contrast to most aspects of the analysis process, for example, sampling, sample preparation, and measurement, there is less known about data evaluation. This particularly critical step becomes more and more important if a large number of samples has to be handled. In this context, it is concerning that the commonly used library searching is not suitable to identify microplastics from real environmental samples automatically. Therefore, many spectra have to be rechecked by the operator manually, which is very time-consuming. In this study, a new fully automated robust microplastics identification method is presented that assigns over 98% of microplastics correctly. The main concept of this new method is to detect and numerically describe the individual vibrational bands within an FTIR absorbance spectrum by curve fitting, which leads to a very compact and highly characteristic peak list. This list allows very accurate and robust library searching. The developed approach is based on the already published microplastics identification algorithm (µIDENT) and extends and improves the field of application to µFTIR data with a special focus on relevant broad, overlapped, or complex vibrational bands.

On-line electrolytic dissolution for soluble aluminium determination in high-silicon steel/electrical sheet by ED-FIA-ICP-OES.

Soluble aluminium (Al(sl)) in high silicon alloys is determined by electrolytic dissolution flow injection analysis (ED-FIA) and inductive coupled plasma with optical emission spectrometry (ICP-OES). Skipping the time consuming sample preparation known from acid hydrolysis reduces the required time per determination from 15 to 4 min. A new calculation procedure is used to compensate the discrepancy in matters of dissolution between acid hydrolysis and electrolytic dissolution. Samples with a known silicon content (2,5 and 3,1 wt%) are used to determine the differences of dissolved material and to calculate a correction factor. In a working range of 200-350 ppm aluminium in high silicon steel, there is a standard deviation of 7 ppm for a measurement series of 19 samples (max deviation 19 ppm).

Concentration-Gradient-Method for sulphur and strontium isotope ratio determination by quadrupole-based inductively coupled plasma mass spectrometry in gypsum.

RATIONALE: The concentration-gradient-method (CGM) was previously introduced as a precise and accurate method for isotope ratio determination by quadrupole-based inductively coupled plasma mass spectrometry (ICP-QMS). The investigation of its potential and advantages in the analysis of analytes with a poor signal-noise ratio (S/N) is important to establish routine isotope ratio analysis industrial applications on these widely used instruments. METHODS: The CGM was applied on isotope measurements of Sr near its limit of quantification (LOQ) and of sulphur where there was a massively interfered 32 S isotope signal in gypsum samples of different origin, in order to demonstrate the advantages of the CGM over the commonly used measurement and evaluation approach. The comparison between the CGM and the classical measurement and evaluation approach was performed with high and low concentration Sr standard solutions, to prove the robustness of the isotope ratio determination. RESULTS: In both cases the CGM reached a recovery rate of approximately 103 %, whereas the classical approach became increasingly inaccurate at lower S/N (recovery of 123 %). In the case of sulphur isotope ratio determination only the CGM enabled a differentiation between geogenic and flue gas desulphurisation plant-originated gypsum samples. CONCLUSIONS: The robustness of the CGM approach was illustrated for gypsum samples with trace strontium concentration and its general applicability to the determination of sulphur isotope ratios by means of quadrupole-based ICP-MS was demonstrated using the example of sulphur in gypsum.

Strontium carbonate precipitation as a sample preparation technique for isotope ratio analysis of Sr in mineral water and wine by quadrupole-based inductively coupled plasma mass spectrometry.

RATIONALE: The defined origin of food products is nowadays often seen as a marker of quality. Stontium (Sr) isotope ratio determination can be used to verify the origin of such food products and it has thus become an important technique. Wine samples in particular are often investigated using this technique. Sr isotopic ratio measurements are often disturbed by isobaric Rb interference, making a separation procedure necessary. In this investigation a very simple and effective procedure for the separation of Rb+ and Sr2+ ions for Sr isotope ratio determination in mineral water and wine samples was developed. METHODS: The classical Sr-carbonate precipitation reaction for the separation of Sr2+ ions from highly soluble Rb+ ions was used. For liquid samples, such as mineral water or wine, a prior digestion is not required. This sample preparation procedure was successfully applied for Sr isotope measurements on a widely available quadrupole-based inductively coupled plasma mass spectrometry (ICP-MS) device in combination with the Concentration-Gradient-Method (CGM). RESULTS: The separation achieved Sr/Rb concentration ratios of 50,000 to 150,000 in water and wine samples. The addition of Ca2+ ions to co-precipitate with the traces of Sr improved the Rb separation and the reproducibility of isotope ratio determination to an uncertainty of ±0.4 ‰ (single standard deviation). This sample preparation approach achieved 2 to 6 times better Rb separation than the commonly applied ion-exchange resin materials. CONCLUSIONS: The quality of the separation is only limited by the number of precipitation repetitions. Moreover, the applicability of quadrupole-based ICP-MS for the characterisation of samples with respect to their origin by means of Sr isotope ratio determination was demonstrated.

A New Chemometric Approach for Automatic Identification of Microplastics from Environmental Compartments Based on FT-IR Spectroscopy.

One key step studying interactions of microplastics with our ecological system is to identify plastics within environmental samples. Aging processes and surface contamination especially with biofilms impede this characterization. A complex and time-consuming cleaning procedure is a common solution for this problem. However, it implies an artificial change of sample composition with a risk of losing important information or even damaging microplastic particles. In the present work, we introduce a new chemometric approach to identify heavily weathered and contaminated microplastics without any cleaning. The main idea of this concept is based on an automated curve fitting of most relevant vibrational bands to calculate a highly characteristic fingerprint that contains all vibrational band area ratios. This new data set will be used to estimate the similarity of samples and reference standards for identification. A total of 300 individual naturally weathered plastic particles were measured with Fourier transformation infrared spectroscopy in attenuated total reflection mode (FT-IR ATR) and identified successfully with the new method. To that end, all samples were compared with a selection of common reference plastics and bio polymers. As it turns out, the accuracy of identification rises significantly from 76% by means of conventional library searching algorithms to 96% by identifying microplastics with our new method. Therefore, the new approach can be a useful tool to compare and describe similarities of FT-IR spectra of microplastics, which may improve further research studies on this topic.

Antiquarian books as source of environment historical water data.

Historical environment considerations are inevitable also for modern environmental analysis. They alone allow evaluation of anthropogenic impact into the environment. To receive information about the historical environment situation in inhabited regions, we approached this task by examining historical well dated and locatable products of the Homo faber. The work introduced here uses books as a source of environment historical data specially for the environmental compartment of water. The paper of historical books, dated by their printing and allocated by their watermark(1) (Wasserzeichensammlung Piccard, Piccard online, Hauptstaatsarchiv Stuttgart, ) is a trap for traces of heavy metals contaminating their production water in historical times. Great amounts of water were brought into contact with the paper pulp in the historical paper mill process. The cellulose of the pulp acts as an ion exchange material for heavy metals, forming a dynamic equilibrium. A well defined pulp production process, starting with used clothes, allows estimation of the concentration of historical heavy metals (Cu(2+), Pb(2+), Zn(2+), Cd(2+)) in the production water (river water). Ancient papers from well dated books are eluted without destruction of their paper and the resulting solution is analysed by ETAAS and inverse stripping voltammetry to determine the historical impact of metals. Afterwards in a flow system the eluted paper spot is equilibrated with different concentrations of heavy metals (Cu(2+), Pb(2+), Zn(2+), Cd(2+)) to plot the adsorption isotherm of that very spot. Both data together allows a calculation of the heavy metal content of the historical river. For different waters of Germany and the Netherlands of the 16th-18th Century the heavy metal load could be estimated. The resulting concentrations were mostly similar to the level of modern surface waters, but in the case of the Dutch waters of the 17th Century, they were e.g. for Pb(2+) significantly higher than modern values.