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AbstractThe increasing threat of forest fires on a global scale is not only a matter of concern due to the potential harm they may cause to both human and animal life but also due to their significant role in exacerbating climate change. In light of these circumstances, one might inquire as to whether forest soil can self‐ignite and, if so, under what conditions and at what temperatures this phenomenon may occur. This question is being addressed in the German pilot “Fire science of wildfires and safety measures” of the EU project TREEADS, and the first results are presented below. The importance of basic research into the self‐ignition of forest soil cannot be underestimated, as it provides crucial knowledge to prevent forest fires and protect human and animal health. Furthermore, mitigating the occurrence of forest fires can also play a role in reducing greenhouse gas emissions, contributing to global efforts to combat climate change. The procedure of the hot storage test is an effective means of determining whether a material can self‐ignite. During the investigation of six soil samples, it was found that five of them were indeed capable of self‐ignition. In addition to determining whether the material ignites, the modified hot storage test also analyzed the resulting smoke gases and measured their concentration. The research question of whether regional forest soil is capable of self‐ignition can be answered with yes based on these initial tests. Further experiments are needed to determine if self‐ignition causes forest fires.
Inputs of plastic impurities into the environment via the application of fertilizers are regulated in Germany and the EU by means of ordinances. Robust and fast analytical methods are the basis of legal regulations. Currently, only macro- and large microplastic contents (>1 mm) are measured. Microplastics (1–1,000 µm), are not yet monitored. Thermal analytical methods are suitable for this purpose, which can determine the mass content and can also be operated fully automatically in routine mode. Thermal extraction desorption-gas chromatography/mass spectrometry (TED-GC/MS) allows the identification of polymers and the determination of mass contents in solid samples from natural environments. In accordance with the German or European Commission (EC) Fertiliser Ordinance, composting plants should be monitored for microplastic particles with this method in the future. In this context a compost plant was sampled. At the end of the rotting process, the compost was sieved and separated in a coarse (>1 mm) and a fine fraction (<1 mm). The fine fraction was processed using density separation comparing NaCl and NaI as possible salt alternative and screened for microplastic masses by TED-GC/MS with additional validation and quality assurance experiments. With TED-GC/MS total microplastics mass contents of 1.1–3.0 μg/mg in finished compost could be detected with polyethylene mainly. What differs much to the total mass of plastics in the coarse fraction with up to 60 μg/mg, which were visually searched, identified via ATR-FTIR and gravimetrically weighted.
Per- and polyfluoroalkyl substances (PFAS) are a large group of more than 10,000 anionic, cationic, zwitterionic or neutral organofluorine surfactants. As a result of continuous and prolific use, mainly in aviation firefighting foams, thousands of industrial and military installations have been found to contain contaminated soil, groundwater and surface water. While liquid chromatography tandem mass spectrometry (LC-MS/MS) is commonly used technique to characterize targeted PFAS in environmental samples, there are more than 10,000 different PFAS known, which have various headgroups and properties. Therefore, several analytical techniques are available to analyse various groups or pools of PFAS or “all” PFAS as a sum parameter. Current decontamination strategies of PFAS-burdened soils mainly consist of adsorption methods using adsorbents for fixation of PFAS in the ground. A second option is the utilization of a “pump and treat” process, cycling polluted soils through a washing plant leading to the concentration of the pollutants in the fine fraction. Both approaches are cost-intensive and not intended for the direct decomposition of all PFAS contaminants. Hence, there is a great demand for innovative developments and chemical treatment technologies, dealing with new strategies of tackling the PFAS problem. Previously, mechanochemical treatment of polychlorinated organic compounds in soils showed an efficient dechlorination. Thus, we investigated mechanochemical treatment of PFAS contaminated soils with various additives in a ball mill and analyzed the PFAS defluorination with gas chromatography mass spectrometry (GC-MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS), respectively, as well es the fluoride mineralization by ion chromatography (IC) and fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy.
The amount of plant-available phosphorus (P) in soil strongly influences the yield of plants in agriculture. Therefore, various simple chemical extraction methods have been developed to estimate the plant-available P pools in soil. More recently, several experiments with the DGT technique have shown that it has a much better correlation to plant-available P in soils than standard chemical extraction methods (e.g. calcium-acetate-lactate (CAL), Colwell, Olsen, water) when soils with different characteristics are considered. However, the DGT technique cannot give information on the plant-available P species in the soil. Therefore, we combined DGT with solution 31P nuclear magnetic resonance (NMR) spectroscopy. This was achieved by using a modified DGT device in which the diffusive layer had a larger pore size, the binding layer incorporated an adsorption material with a higher capacity, and the device had a larger exposure area. The spectroscopic investigation was undertaken after elution of the deployed DGT binding layer in a NaOH solution. Adsorption tests using solutions of known organic P compounds showed that a sufficient amount of these compounds could be adsorbed on the binding layer in order for them to be analyzed by solution 31P NMR spectroscopy. Furthermore, various intermediates of the hydrolysis of trimetaphosphate in soil could be also analyzed over time.
In precision agriculture, the estimation of soil parameters via sensors and the creation of nutrient maps are a prerequisite for farmers to take targeted measures such as spatially resolved fertilization. In this work, 68 soil samples uniformly distributed over a field near Bonn are investigated using laser-induced breakdown spectroscopy (LIBS). These investigations include the determination of the total contents of macro- and micronutrients as well as further soil parameters such as soil pH, soil organic matter (SOM) content, and soil texture. The applied LIBS instruments are a handheld and a platform spectrometer, which potentially allows for the single-point measurement and scanning of whole fields, respectively. Their results are compared with a high-resolution lab spectrometer.
The prediction of soil parameters was based on multivariate methods. Different feature selection methods and regression methods like PLS, PCR, SVM, Lasso, and Gaussian processes were tested and compared. While good predictions were obtained for Ca, Mg, P, Mn, Cu, and silt content, excellent predictions were obtained for K, Fe, and clay content. The comparison of the three different spectrometers showed that although the lab spectrometer gives the best results, measurements with both field spectrometers also yield good results. This allows for a method transfer to the in-field measurements
Per- and polyfluoroalkyl substances (PFASs) are a group of anthropogenic contaminates associated with persistent, bioaccumulative and toxic properties. Mostly, target-based approaches (e.g., LC-MS/MS) are utilized for the analysis of PFASs in the environment. Target approaches are limited to a few selected PFASs and therefore underestimate the total PFAS burden. Analytical approaches based on total fluorine for PFAS sum parameter analysis become increasingly important to indicate realistic PFAS pollution levels.
Recently high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) turned out to be a sensitive and highly selective tool for fluorine determination. The method is based on the in situ formation of diatomic gallium-mono fluoride (GaF) in a graphite furnace at a temperature of 1550°C. The molecular absorption of GaF can be detected at its most sensitive wavelength at 211.248 nm providing limits of quantification in the low µg F/L range. HR-CS-GFMAS analysis can be combined with the extractable organically bound fluorine (EOF) approach whereas PFASs are extracted from liquid or solid samples using organic solvents and/or solid phase extraction (SPE).
In this presentation the applicability of HR-CS-GFMAS for organic fluorine analysis in various environmental sample including (1) water samples, (2) soil samples and (3) plant samples is demonstrated.
(1) We investigated EOF concentrations in water bodies in Berlin, Germany and used additional PFAS target analysis for a PFAS mass balance approach. EOF concentrations were in the expected range for an urban river system. However, downstream of an effluent discharge, the EOF increased by one order of magnitude from 40 to 574 ng F/L. Target analysis determined mostly short-chained perfluorinated carboxylic acids and sulfonic acids, which however only made up less than 10% of the EOF. This study highlights that EOF screening using HR-CS-GFMAS is useful and advantageous compared to target analysis to identify pollution sites in urban water systems.
(2) For soil samples, we optimized a fast and simple PFAS extraction method for EOF determination. The developed extraction method consists of a liquid-solid extraction without any additional SPE for fluoride removal. We investigated different soil samples using the optimized method with and without an additional SPE clean-up step and revealed a drastic underestimation of EOF mass fractions using SPE. The optimized method is a valuable screening tool for fast PFAS monitoring.
(3) For plant samples, we conducted a study on the uptake and fate of PFASs in bean plants. For PFAS mass balancing HR-CS-GFMAS analysis was combined with LC-MS/MS analysis. PFASs were spiked as mixtures of known and unknown composition. Short-chained PFASs were determined with high mass fractions mainly in the fruits of the investigated plants while long-chained PFASs were mainly determined in roots. Overall, both methods indicate comparable results with target analysis being more reliable for known PFAS contamination and EOF/HR-CS-GFMAS analysis being more valuable to identify PFAS exposure of unknown composition.
For the first time, µ-X-ray fluorescence (µ-XRF) mapping combined with fluorine K-edge µ-X-ray absorption near-edge structure (µ-XANES) spectroscopy was applied to depict per- and polyfluoroalkyl substances (PFAS) contamination and inorganic fluoride in samples concentrations down to 100 µg/kg fluoride. To demonstrate the matrix tolerance of the method, several PFAS contaminated soil and sludge samples as well as selected consumer product samples (textiles, food contact paper and permanent baking sheet) were investigated. µ-XRF mapping allows for a unique element-specific visualisation at the sample surface and enables localisation of fluorine containing compounds to a depth of 1 µm. Manually selected fluorine rich spots were subsequently analysed via fluorine K-edge µ-XANES spectroscopy. To support spectral interpretation with respect to inorganic and organic chemical distribution and compound class determination, linear combination (LC) fitting was applied to all recorded µ-XANES spectra. Complementarily, solvent extracts of all samples were target-analysed via LC-MS/MS spectrometry. The detected PFAS sum values range from 20 to 1136 µg/kg dry weight (dw). All environmentally exposed samples revealed higher concentration of PFAS with a chain length >C8 (e.g. 580 µg/kg dw PFOS for Soil1), whereas the consumer product samples showed a more uniform distribution with regard to chain lengths from C4 to C8. Independent from quantified PFAS amounts via target analysis, µ-XRF mapping combined with µ-XANES spectroscopy was successfully applied to detect both point-specific concentration maxima and evenly distributed surface coatings of fluorinated organic contaminants in the corresponding samples.
Per- and polyfluoroalkyl substances (PFAS) are a group of anionic, cationic and zwitterionic synthetic products, in which the hydrogen atoms on the carbon skeleton of at least one carbon atom have been completely replaced by fluorine atoms and which include more than 4730 compounds, depending on the definition. As a result of continuous and prolific use, mainly in aviation firefighting foams, thousands of industrial and military installations have been found to contain contaminated soil, groundwater and surface water. Furthermore, current decontamination strategies of PFAS-burdened soils mainly consist of adsorption methods using adsorbents for fixation of PFAS in the ground. Hence, there is a great demand for innovative developments and chemical treatment technologies, dealing with new strategies of tackling the PFAS problem. Thus, we investigated mechanochemical treatment of PFAS contaminated soils with various additives in a ball mill and analyzed the PFAS defluorination. In this presentation the advantages of fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy for various environment samples are shown.
Inductively coupled plasma mass spectrometry (ICP-MS) emerged as a powerful technique for trace analysis of soil due to its multi-element capability, high sensitivity and low sample consumption. However, despite its success and widespread use, ICP-MS has several persistent drawbacks, such as high argon gas consumption, argon-based polyatomic interferences and the need for complicated RF-power generators. Unlike argon-based ICP, the nitrogen microwave inductively coupled atmospheric pressure mass spectrometry (MICAP-MS) uses nitrogen as plasma gas, which eliminates high operating costs associated with argon-gas consumption as well as the argon-based interferences1. In this work, the applicability of MICAP-MS for elemental analysis in different matrices is investigated. For this purpose, reference soil samples and steel samples are digested with aqua regia and used for analysis. Concentrations of selected elements are determined using MICAP-MS and validated with ICP-MS und certified values. Sensitivities, limits of detection and gas consumption for both methods are compared and discussed in detail. Performance of MICAP-MS under different nitrogen plasma gas concentrations is investigated and compared. Moreover, the performance of MICAP-MS in alloy matrices is investigated and discussed.
Detailed knowledge about soil composition is an important prerequisite for many applications, for example precision agriculture. Current standard laboratory methods are complex and time-consuming but could be complemented by non-invasive optical techniques. Its capability to provide a molecular fingerprint of individual soil components makes Raman spectroscopy a very promising candidate. A major challenge is strong fluorescence interference inherent to soil, but this issue can be overcome effectively using shifted excitation Raman difference spectroscopy (SERDS). A customized dual-wavelength diode laser emitting at 785.2 and 784.6 nm was used to investigate 117 soil samples collected from an agricultural field along a distance of 624 m and down to depths of 1 m. To address soil spatial heterogeneity, a raster scan approach comprising 100 measurement spots per sample was applied. Based on the Raman spectroscopic fingerprint extracted from intense fluorescence interference by SERDS, 13 mineral soil constituents were identified, and even closely related molecular species could be discriminated, for example polymorphs of titanium dioxide and calcium carbonate. For the first time, the capability of SERDS is demonstrated to predict the calcium carbonate content as an important soil parameter using partial least squares regression (R2 = 0.94, root mean square error of cross-validation RMSECV = 2.1%). Our findings demonstrate that SERDS can extract a wealth of spectroscopic information from disturbing backgrounds enabling qualitative and quantitative soil analysis. This highlights the large potential of SERDS for precision agriculture but also in further application areas, for example geology, cultural heritage and planetary exploration.