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- Mobile Robot Olfaction (4)
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- Warfarin (3)
- Amoxicillin (2)
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Organisationseinheit der BAM
- 1 Analytische Chemie; Referenzmaterialien (14)
- 1.8 Umweltanalytik (11)
- 8 Zerstörungsfreie Prüfung (7)
- 8.1 Sensorik, mess- und prüftechnische Verfahren (7)
- 1.7 Organische Spuren- und Lebensmittelanalytik (3)
- 6 Materialschutz und Oberflächentechnik (3)
- 6.6 Nano-Tribologie und Nanostrukturierung von Oberflächen (3)
- 4 Material und Umwelt (2)
- 1.9 Chemische und optische Sensorik (1)
- 2 Chemische Sicherheitstechnik (1)
Monitoring programs should generate high-quality data on the concentrations of substances and other pollutants in the aquatic environment to enable reliable risk assessment. Furthermore, the need for comparability over space and time is critical for analysis of trends and evaluation of restoration of natural environment. Additionally, research work and exercises at the European level have highlighted that reliable measurements of estrogenic substances at the PNEC level are still challenging to achieve. The project EDC-WFD “Metrology for monitoring endocrine disrupting compounds under the EU Water Framework Directive” aims to develop traceable analytical methods for determining endocrine disrupting compounds and their effects, with a specific focus on three estrogens of the first watch list (17-beta-estradiol (17βE2), 17-alpha-ethinylestradiol (EE2), and estrone (E1)). Estrogens 17-alpha-estradiol (17aE2) and estriol (E3) will be included to demonstrate the reliability of the developed methods - Mass Spectrometry based method and effect-based methods (EBM) - and to support the requirements of Directive 2013/39/EC, Directive 2009/90/EC and Commission Implementation Decision (EU) 2018/840, hence improving the comparability and compatibility of measurement results within Europe. During the EDC-WFD project four EBM will be deeply investigated in order to improve their rationale use and their support in water quality assessment.
Monitoring programs should generate high-quality data on the concentrations of substances and other pollutants in the aquatic environment to enable reliable risk assessment. Furthermore, the need for comparability over space and time is critical for analysis of trends and evaluation of restoration of natural environment. Additionally, research work and exercises at the European level have highlighted that reliable measurements of estrogenic substances at the PNEC level are still challenging to achieve. The project EDC-WFD “Metrology for monitoring endocrine disrupting compounds under the EU Water Framework Directive” aims to develop traceable analytical methods for determining endocrine disrupting compounds and their effects, with a specific focus on three estrogens of the first watch list (17-beta-estradiol (17βE2), 17-alpha-ethinylestradiol (EE2), and estrone (E1)). Estrogens 17-alpha-estradiol (17aE2) and estriol (E3) will be included to demonstrate the reliability of the developed methods - Mass Spectrometry based method and effect-based methods (EBM) - and to support the requirements of Directive 2013/39/EC, Directive 2009/90/EC and Commission Implementation Decision (EU) 2018/840, hence improving the comparability and compatibility of measurement results within Europe. During the EDC-WFD project four EBM will be deeply investigated in order to improve their rationale use and their support in water quality assessment.
Regardless of its ban in agricultural use, the triazine derivative terbutryn is still used as a biocide against biofouling in building materials, such as façade colors and roof tiles. From there, it is washed off and may contaminate soil and surface waters, where it shows ecotoxicological behavior. For understanding of these leaching processes, analytical methods that can detect terbutryn in traces are necessary. In contrast to separation methods (Gas (GC) or liquid chromatography (LC)) coupled to mass spectrometry (MS), enzyme immunoassays (EIAs) have proven to be adequate tools for environmental monitoring. Compared to GC-or LC-MS, they are cheap, require only limited time and experimental expertise and enable high throughput. For quantification of terbutryn, EIAs have been established, with a limit of detection (LOD) of 50 ng L-1. For leaching experiments however, a lower LOD would be advantageous.
For detection of terbutryn we developed a direct competitive ELISA based on a monoclonal antibody: Terbutryn and an enzyme-terbutryn conjugate (“tracer”) compete for the binding sites of the immobilized antibody. The bound tracer converts a colourless substrate into a blue-coloured product, which can be detected via spectrophotometry. For quantification of terbutryn, a sigmoidal calibration curve is used. For establishing of the EIA, a new tracer based on a terbutryn surrogate (“hapten”) was synthesized. After optimization of the experimental conditions, the immunoassay exhibited a more than ten-fold increased sensitivity (LOD: 3 ng L-1), high stability against sample compounds (Ca2+, NaCl) and lower cross-reactivities against structurally related compounds, than reported before. Analysis of spiked samples was possible with high precision (inter-assay CV: < 10 %) and accuracy (recoveries from spiked samples: 89 % ± 10%). We therefore propose it as quick and reliable method for leaching studies of terbutryn out of building materials.
Due to the favorable properties of polymers, their production and thus their input into the environment has increased significantly in recent decades. Currently, FTIR or Raman spectroscopy are mainly applied for the analysis of microplastic particles (MP) in environmental samples. However, these methods have great difficulties in determining metrologically traceable MP values, especially with regard to the limiting values, as preferred in regulation. Therefore, we developed a systematic and fast thermoanalytical method called TED-GC-MS (thermal extraction desorption gas chromatography mass spectrometry), which determines mass contents. Now the current goal is the determination of its process parameters.
This poster illustrates the theoretical requirements for MP analysis (left side) and contrast them with the current state of research (right side).Unexpected practical problems are presented and the relatively new method is discussed concerning the quality requirements of well-established methods such as LC-or GC-MS.
The Motivation of RASEM (Robot-assisted Environmental Monitoring):
Monitoring of the air quality in industrial environments is inevitable to meet safety Standards.
Because of economic and practical reasons, measurements are carried out sparsely in terms of time and space.
Newest developments on the field of low cost sensor technology enable cost efficient long term monitoring of gases and dust
Comparing Nontargeted LC-MS Methods by Co-visualizing Linear Dynamic Range and Chemical Coverage
(2019)
INTRODUCTION
Biological and environmental samples contain thousands of small molecule species that all vary in chemical properties and concentration range. Identifying and quantifying all these chemical entities remains a long-term goal in metabolomics and related systems approaches. Due to its broad selectivity, nontargeted LC-MS is usually the method of choice for broad chemical screening. Optimizing nontargeted LC-MS methods, however, is less straightforward than for targeted methods where sensitivity, specificity, linearity etc. serve as well-established performance criteria. We therefore investigated linear dynamic range (LDR) and chemical classification as alternative performance criteria to guide nontargeted method development.
EXPERIMENTAL METHODS
LDR was defined as the linear portion of a feature’s response curve over multiple concentration levels. Comparing the LDR of features across methods can be expected to be significantly more robust than comparing signal intensities for a single concentration. To determine LDR for all features, a computational workflow was implemented in the R programming language. For estimating the linear portion of a curve, several mathematical approaches including linear, non-linear and piecewise linear regression were evaluated. Chemical classification was based on ClassyFire, which computes chemical classes for a given structure. To avoid false classifications for incorrectly annotated compounds, we took the following statistical approach. For each compound, multiple likely annotation hypotheses were derived using a recently described workflow[2]. All annotation hypotheses were submitted to ClassyFire and obtained classifications were ranked by frequency. The most frequently suggested class was kept for further analysis. Finally, LDR and chemical classes were visualized together on a molecular network, which was constructed using the well-established MS/MS similarity approach.
RESULTS AND DISCUSSION
For technical validation of the workflow, several hundred curve fits obtained from the different regression models were reviewed visually. Piecewise linear regression performed the most reliably with respect to the heterogeneous curve shapes of ‘real-life’ features. Validation of chemical classification was performed against a compound library, which showed that 90% of ~450 library compounds were correctly classified using the described approach. Two liquid chromatography methods (HILIC, RPC) as well as two electrospray ionization variants (low/high-temperature ESI) applied to urinary metabolomics were exemplarily studied to test the workflow. Molecular network visualization indicated that of all analytical setups, HILIC/high temperature ESI performed best in terms of high LDR achieved over a wide range of compound classes. Despite one order of magnitude lower sensitivity, HILIC/low temperature ESI showed similar chemical coverage, except for organic nitrogen compounds that were underrepresented compared to high-temperature ESI. Both RPC setups were inferior to the HILIC setups in terms of high-LDR features, supporting previous findings for the given matrix. The higher relative representation of benzenoids and lipids in RPC demonstrated that the workflow successfully captured expected selectivity differences between chromatographies.
CONCLUSION
When comparing nontargeted LC-MS methods for optimization purposes, ideally all available quantitative and qualitative information should be integrated. The present workflow follows this idea. Visualizing LDR and chemical classes of all features on a molecular network quickly indicated differences in method selectivity that were otherwise difficult to spot. As an automated approach, it is easily applied to repeated optimization steps, enabling effective optimization strategies.
In industrial environments, airborne by-products such as dust and (toxic) gases, constitute a major risk for the worker’s health. Major changes in automated processes in the industry lead to an increasing demand for solutions in air quality management. Thus, occupational health experts are highly interested in precise dust and gas distribution models for working environments. For practical and economic reasons, high-quality, costly measurements are often available for short time-intervals only. Therefore, current monitoring procedures are carried out sparsely, both in time and space, i.e., measurement data are collected in single day campaigns at selected locations only. Real-time knowledge of contaminant distributions inside the working environment would also provide means for better and more economic control of air impurities. For example, the possibility to regulate the workspace’s ventilation exhaust locations can reduce the concentration of airborne contaminants by 50%.
To improve the occupational health and safety of (industrial) workplaces, this work aims for developing a swarm of gas-sensitive aerial nano robots for monitoring indoor air quality and for localizing potential emission sources.
Phosphorus (P) fertilizers from secondary resources became increasingly important in the last years. However, these novel P-fertilizer can also contain toxic pollutants e.g. chromium (Cr) in the hexavalent state (Cr(VI)), which is regulated with low limit values in agricultural products (German fertilizer ordinance limit: 2 mg/kg Cr(VI)). The determination of Cr(VI) in these novel fertilizer matrices can be hampered by redox processes that lead to false results with the standard wet chemical extraction method (German norm DIN EN 15192). Therefore, we analyzed Cr(VI) in various P-fertilizers with the DGT technique. DGT devices equipped with a APA (polyacrylamide) diffusion layer and Cr(VI) selective N-methyl-D-glucamine (NMDG) binding layer were used for the study. After a 24 h conditioning period of the fertilizer at 60% of the water holding capacity (WHC), the fertilizers were brought to 100% WHC, transferred onto the DGT devices and deployed for 24 h at 25°C. The extraction of Cr from the DGT binding layer was carried out with 1 M HNO3 for 24 h. The Cr-concentrations of the extract were determined by means of ICP-MS. We found a good correlation between the standard wet chemical extraction and the DGT method for the whole range of P-fertilizers. However, partly soluble Cr(VI) compounds cannot be detected in full extent by the DGT method that is best suited for mobile Cr(VI). Furthermore, Cr K-edge XANES spectroscopy showed that the Cr(VI)-selective DGT binding layer also adsorbs mobile Cr(III) compounds from acid treatment of phosphates which can therefore cause an overestimation of Cr(VI). The DGT method was very sensitive and in most cases selective for the analysis of Cr(VI) in P-fertilizers made from recycled materials. However, the results of certain types of P-fertilizers containing mobile Cr(III) or partly immobile Cr(VI) show that still some optimization of the method is required to avoid over- or underestimation of Cr(VI).
We report the first results for the immunochemical determination of the β-lactam antibiotic drug amoxicillin (AMX) in water samples by ELISA (enzyme-linked immunosorbent assay). The applied indirect competitive ELISA using a commercially available mouse anti-AMX antibody enables testing for AMX with a limit of detection of around 1 µg/L. Calibration curves of calibrators prepared in different water samples showed equal shape. This underlines the suitability of this assay for the AMX determination in these samples. Furthermore, cross-reactivities of structurally similar β-lactam antibiotics were examined and found to be low for ampicillin, penicillin G and penicillin V. In contrast, carbenicillin was recognized by the antibody even better than AMX indicating a positive effect of an additional carboxyl group on antibody binding. This is promising for further application of this assay, e.g. in the determination of the most relevant hydrolysis product of AMX, amoxicilloic acid.
The development of algorithms for mapping gas distributions and localising gas sources is a challenging task, because gas dispersion is a highly dynamic process and it is impossible to capture ground truth data. Fluid-mechanical simulations are a suitable way to support the development of these algorithms. Several tools for gas dispersion simulation have been developed, but they are not suitable for simulations of large outdoor environments. Here we present a concept of how an existing simulator can be extended to handle both indoor and large outdoor scenarios.
In this paper, we present an autonomous aerial robot to reconstruct tomographic 2D slices of gas plumes in outdoor environments. Our platform, the so-called Unmanned Aerial Vehicle for Remote Gas Sensing (UAV-REGAS) combines a lightweight Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensor with a 3-axis aerial stabilization gimbal for aiming on a versatile octocopter. The TDLAS sensor provides integral gas concentration measurements but no information regarding the distance traveled by the laser diode's beam or the distribution of the gas along the optical path. We complemented the set-up with a laser rangefinder and apply principles of Computed Tomography (CT) to create a model of the spatial gas distribution from these integral concentration measurements. To allow for a rudimentary ground truth evaluation of the applied gas tomography algorithm, we set up a unique outdoor test environment based on two 3D ultrasonic anemometers and a distributed array of 10 infrared gas transmitters. We present first results showing the 2D plume reconstruction capabilities of the system under realistic conditions.
Herein, we present the development of a gas chromatographic method for Determination of warfarin, its TPs, and selected metabolites.
TPs were formed by applying UV-irradiation, ozonation, and an electrochemical cell coupled to mass spectrometry to mimic the oxidative phase I metabolism. The further aim is to use this method for detection and quantification under environmentally relevant conditions, as well as, toxicological assessment.
Ein Vergleich der Gehalte von Difluoressigsäure (DFA) und Trifluoressigsäure (TFA) in Regen- und Oberflächenwässern im Berliner Raum ergab ein TFA/DFA Verhältnis in Regenwasser von 10:1. Im Gegensatz dazu wies Grundwasser aus dem Einzugsbereich einer historischen Kontamination durch Fluorchlorkohlenwasserstoffe (FCKW) ein TFA/DFA-Verhältnis von 1:3 auf. Dies und die ungewöhnlich hohe DFA-Konzentration an dieser Stelle wird vor dem Hintergrund der beobachteten mikrobiellen Abbauprodukte des ursprünglichen eingetragenen FCKW 1,1,2-Trichlor-1,2,2-trifluorethan (R113) diskutiert. Eine mikrobielle Umwandlung des bekannten Abbauproduktes Chlortrifluorethylen (R1113) zur DFA wurde bislang nicht in Umweltkompartimenten beobachtet und wird hier auf Basis bekannter Stoffwechselwege vorgeschlagen.
TFA wurde in Regenwasser, Oberflächenwasser und Grundwasser in vergleichbaren Größenordnungen von ca. 500 ng/L bestimmt. Im Gegensatz dazu wurde DFA in Grundwasserproben im Bereich der Schadstoffquelle der FCKW-Kontamination mit bis zu 2.000 ng/L nachgewiesen. Die Summe von TFA und DFA im Grundwasser korreliert nicht mit dem Eintrag aus Niederschlag und Oberflächenwasser. Darum liegt die Vermutung nahe, dass es für DFA andere Quellen als den direkten Eintrag oder den möglichen Abbauweg über TFA geben muss. DFA ist vermutlich ein Abbauprodukt von R1113. FCKWs, die im ersten Abbauschritt zu 1,1-Difluorethenen metabolisieren, stehen im Verdacht, in der Folge zu DFA zu hydrolysieren. Entscheidend scheint, dass bereits im Ausgangsprodukt ein CF2-Strukturelement enthalten ist, das dann zur Bildung von DFA führen kann. Somit würde aus dem ursprünglichen Eintrag des Kältemittels R113 über schrittweise Dechlorierung via 1,2-Dichlor-1,2,2-Trifluorethan (R123a) und R1113 die Bildung des beobachteten DFA folgen. Es ist also sinnvoll, DFA in die Diskussion zur Regulierung der Endprodukte des Abbaus fluorhaltiger Kälte- oder Lösungsmittel einzubeziehen. Die Ergebnisse wurden im Normausschuss Wasserwesen (NAW) des DIN vorgestellt und es soll ein Arbeitskreis gegründet werden, der ein Normverfahren zur Quantifizierung von TFA und DFA in Wasser erarbeitet. Interessierte Laboratorien sind herzlich eingeladen, die Normungsarbeit zu unterstützen.
Since cereals constitute a staple food worldwide, monitoring of growth, storage and processing represent a perseverative challenge of analytical sciences. Especially during storage infested grains breed fungal clusters (“hot spots”) in which mycotoxins accumulate and can highly exceed allowed maximum levels. Because of their unpredictable presence, analytical procedures – including representative sampling - contain invasive and time intensive steps.
To avoid erroneously negative results in mycotoxin analysis in cereals, the samples´ homogeneous headspace might be investigated instead of analyzing subsamples of the grains. So-called microbial volatile organic compounds (MVOC´s) provide information for instance about the fungal status of grains. Previous investigations revealed trichodiene to be a precursor of trichothecene mycotoxins which comprises more than 180 different compounds. Due to its non-functionalised sesquiterpene structure, quantification of trichodiene using Headspace GC-MS methods is possible. Thereby, it could be used as biomarker for trichothecene contamination of cereals.
Nevertheless, further investigations are necessary. To be able to draw conclusion about the trichothecene content in cereal samples, a possible correlation between trichodiene concentration in the gas phase and trichothecene concentration in the sample must be examined. Realizing this idea would widely extend the applicability of trichodiene and enormously simplify trichothecene detection. Hence, the first step of an ongoing study aims to develop a laboratory reference method using trichodiene as volatile biomarker to quantify trichothecenes in cereals. Both static headspace and SPME-enrichment coupled to gas chromatography with mass spectrometry (GC-MS) were tested and compared. In a second step, this reference method is intended to validate new approaches for fast on-site screening of trichodiene in cereals.
Warfarin, also known as Coumadin is one of the most popular anticoagulant drugs used as a therapeutic in humans to prevent thrombosis, atrial fibrosis, and fibrillation since the 1950s. Because of its ability to hinder blood from clotting by blocking vitamin K-depending carboxylation of blood clotting precursors, it is also used as a rodenticide worldwide. Until today it has been partially substituted by far more potent anticoagulant rodenticides (ARs), so-called superwarfarins. There are numerous references confirming secondary and tertiary poisoning in non-target-animals and wildlife like mammals, birds, and fish associated with ARs. Up to now relatively little is known about persistence and toxicity of transformation products of those AR in the environment and food chain. Herein, warfarin was chosen as a model compound to determine andelucidate TPs which are generated technically and under environment-like conditions. Such as the simulation of the oxidative phase I metabolism by implementing electrochemical flow cells coupled to mass spectrometry (MS). Obtained results are being compared to TPs generated by UVB-irradiation and ozonation.
Analysis and separation of degradation products and TPs were achieved by a variety of gas- and liquid chromatographic techniques coupled to (high resolution) MS.
Das Therapeutikum Warfarin ist bis heute der bekannteste Vertreter der antikoagulanten Rodentizide. In dieser Arbeit wurden Phase I Metabolite mittels einer elektrochemischen Durchflusszelle simuliert und analysiert. Weitere Transformations- und Abbauprozesse wurde durch UV-Bestrahlung und Ozonung generiert, gaschromatographisch getrennt und miteinander verglichen.
Herein we present the data for a newly developed immunoassay for the determination of amoxicillin (AMX) in water samples using a commercially available monoclonal anti-AMX antibody. During optimization and testing of the assay, we observed a significant decrease of the C-value (IC50) of the ELISA calibration curves with aged standard solutions. Running the assay with standard solutions of synthesized AMX hydrolysis products revealed that this decreased C-value could be attributed mainly to the hydrolysis product amoxicilloic acid. Therefore, the limit of detection of the ELISA for AMX determination in water could be enhanced by either hydrolyzing the samples or testing for amoxicilloic acid as marker substance.
Using a swarm of copter-based gas-sensitive aerial nano robots for monitoring indoor air quality is challenging due to, e.g., limited air space in buildings. To avoid an over-regulation of the available indoor air space (e.g., prohibit copters to fly above each other), a safety region around each copter must be defined to guarantee a safe operation of the swarm.
The key contributions of this poster are the realization of experiments that investigate the influence of the rotor downwash on flying vertically displaced nano robots and the development of a model describing the above-mentioned safety region.
A mobile Bruker S2 Picofox TXRF spectrometer has been used in two field campaigns within the EMPIR env07 AEROMET project for the on-site analysis of cascade impactor aerosol samples.The results show that even at moderate air pollution levels – i.e.PM10 fairly below 20 μg/m³ - element mass concentrations in air in the range of 100 pg/m³could be measured in up to 13 size bins after sampling times of less than only 0.5 days.
Nontargeted high-resolution mass spectrometry (HRMS) is widely used for small molecule screening in biotic or abiotic samples. However, HRMS approaches like metabolomics or environmental nontarget screening currently still lack confidence in chemical annotation, i.e. computational structure assignment to all measured mass signals. As a crucial step within the annotation pipeline, molecular weight inference (MWI) deduces a compound’s intact mass from diagnostic mass differences between MS1 peaks, allowing precise database queries in subsequent steps. As the common practice of considering all possible ionization products such as adducts, multimers, multiple charges etc. in MWI suffers from high false positive rates, we aimed at selecting candidate ionization products in a chemically sensitive way. Generally, electrospray ionization produces different types of adducts depending on chromatographic system and sample matrix, necessitating application-specific optimization for optimum MWI performance. To avoid, however, the tedious and potentially biased manual data curation connected to optimization, we established an R-based workflow for automating this task. The workflow consists of two parts. Part 1 creates an MS1 spectral library by performing peak detection, spectral deconvolution and target peak assignment based on density estimation. Part 2 analyzes ion relationships within the library and returns a list of detected ionization products ranked by their frequency. We applied the workflow to a commercial 634-compound library that was acquired for two chromatographic methods (reverse phase, RP; hydrophilic liquid interaction chromatographic, HILIC) and the two ESI modes (positive, negative). As expected, different frequency distributions of ionization products were found for the two chromatographies. Interestingly, however, some of the differences were expected in terms of solvent chemistries (e.g. [M+NH4]+ in ammonium formate-buffered HILIC) while others indicated more complex ion competition (e.g. abundant [M+K]+, [M+2K-H]+ in HILIC). This demonstrated the relevance of this empirical approach. We further show that MWI accuracy clearly benefitted from derived optimized adduct lists – by adding filters or weighting terms – and present FDR calculations supporting this observation. We conclude that chemistry-aware compound annotation based on the combination of high-throughput library acquisition and statistical analysis holds significant potential for further improvements in nontargeted small molecule HRMS.
Despite abundant evidence of the occurrence of microplastics (MP) – these are particles smaller 5 mm – in aquatic environments, little is known about the accumulation of plastic in terrestrial environments, especially in soils.
Possible major input pathways could be the use of plastic mulching, the use of compost, sewage sludge or residues from biogas facilities as fertilizers, as well as littering in urban areas. To estimate the MP pollution, the development of reliable, fast methods for sampling, sample preparation, and detection is needed. The obtained data must be representative of the sampled environmental compartment and measurements from different environmental compartments must be comparable. A first breakthrough is an application of ThermoExtractionDesorption-Gas Chromatography-MassSpectrometry (TED-GC-MS) for the detection of MP, including tire abrasives. This method allows the determination of mass content within a few hours and only a minimum of sample preparation for samples from aquatic environments is needed.
However, in contrast to filtrate samples from aquatic environments, sediment or soil samples need an enrichment of MP. Whereas MP concentration from marine sediments can be obtained by floatation and density Separation techniques using NaCl solutions, the extraction or separation from soils proves to be more difficult, as plastic particles are often part of organo-mineral aggregates within the soil matrix.
The aim of this study is the development of a practicable processing guideline for representatively taken soil samples in order to concentrate microplastics, without complex and time-consuming treatment steps. Dispersants or detergents can be applied to decompose the soil matrix, but each preparation step carries the risk of crosscontamination of the sample and prolongs the preparation procedure.
For this reason, we choose ZnCl2-solution with a density of 1.7 g/cm3, which include the densities of relevant MP types (0.9-1.7 g/cm3). It was tested to achieve both, disaggregation and separation as it decomposes organic material and dissolves carbonates. Also, ZnCl2 is inert to the precipitation of undesirable salts and Carbonates during the process of density separation, as polytungstate solution does. ZnCl2 can be reused after stepwise filtering (7 µm, 1.5 µm, 0.7 µm). Thus, disposal costs can be reduced. Efficiency and reproducibility of the sample preparation as well as the degradation behavior of MP under the present conditions were demonstrated with model samples.
Real sampling campaigns were conducted at several agricultural sites and floodplains in south-west Germany. The sampling was performed according to practice for soil sampling, using adequate sampling strategies (pattern of sampling, number of field samples, homogenization, etc). The lab sample was fractioned into three size classes (5-100 µm, 100-1000 µm, and 1-5 mm). The identification and determination of mass fraction were done using TED-GC-MS.
This paper describes the development of a semi-automatic gas measurement device presenting potentially a broad range of applications, noteworthy in the agricultural sector. Non-reversible fluorescent molecular sensors were designed and syn-thesized. Upon, integration into a hydrogel matrix with an optimal ratio of co-solvents, the sensors reacting selectively to ammonia were illuminated by excitation light to produce a concentration-correlated fluorescence emission. An automated mechanical-elec-trical device initiates a given gas mixture and thus simulates con-centrations similar to a threshold value. The aim of this project is to develop a sensor or a low-cost method which can monitor low concentrations of harmful gases and aid in their elimination or regulation in livestock housing, barns or stables.