1.4 Prozessanalytik
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Eingeladener Vortrag
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Mobile proximal gamma-ray spectrometry (GS) is an emerging approach to estimate soil texture directly in the field. It relies on gamma radiation emitted during the natural decay of potassium-40 (K-40) and other isotopes. The K-40 counts are correlated with total K content, mineralogical soil composition and therefore with soil texture. Yet, it is not clear if K fertilisation impacts the ratio of K-40 to total K which would necessitate to take the fertilisation history into account for soil sensing applications. To elucidate this question, a well-documented long-term experiment was selected. The soils of the Rengen grassland experiment (55 plots) were investigated for total K (XRF-K) and for K-40 via mobile proximal GS. No significant differences in XRF-K and K-40 were found between the treatments with and without K fertilisation, although formely published results point to negative and positive K balances, respectively. Fertiliser analysis revealed a ratio of K-40 to total K that was almost identical to the natural abundance of 0.0117%. It was concluded that it is not necessary to take K fertilisation history into account when predicting soil texture from mobile proximal GS on agricultural land for, e.g., precision farming purposes.
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
This study uses conventional 87Sr/86Sr and 143Nd/144Nd isotope and interelement ratios of Ca, Sr, K, Mn, Mg and Ti as fingerprints for provenancing ordinary Portland cements (OPC). Herein, the first database of Sr and Nd isotope ratios investigated in OPCs, stemming from 29 cement plants located worldwide, was created. The results show that the Sr isotope ratios of OPCs are higher than those of seawater from the observed geological period. The spread of 143Nd/144Nd in OPCs is not as large as the spread for 87Sr/86Sr isotope ratios. However, the combination of both Sr and Nd isotope ratios provides the potential for distinguishing between cements of different production sites. Most of the OPCs investigated have measurable differences in their 87Sr/86Sr and 143Nd/144Nd isotope ratios, which can be employed as a valuable analytical fingerprinting tool. In the case of equivocal results, divisive hierarchical clustering was employed to help overcome this issue. The construction of geochemical profiles allowed the computing of suitably defined distances between cements and clustering them according to their chemical similarity. By applying this methodology, successful fingerprinting was achieved in 27 out of the 29 ordinary Portland cements that were analysed.
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.
Around 2.5 million tons of municipal sewage sludge (dry matter) are produced in Ger-many every year. The disposal or recycling of this mass often confronts plant operators with considerable problems. In addition to organic substances, sewage sludges also contain important inorganic nutrients that can be recycled. Due to the finite nature of phosphorus as a resource and in favor of natural material cycles, it makes sense to utilize the phosphorus bound in sewage sludge. Therefore, Phosphorus recycling from sewage sludge will be obligatory in Germany from 2029. However, the pollutants pre-sent in sewage sludge, such as heavy metals and organic trace pollutants, are prob-lematic. In many cases, the sewage sludge is incinerated, removing organic compo-nents, and leaving a mineral residue. Various processes exist for the reprocessing of sewage sludge ashes. Reliable analytics and process monitoring are required for all of them.
In this context, the first and most important task of BAM regarding new materials or processes is safety in technology and chemistry through validated and correct analyt-ics. Since there are no reference materials for sewage sludge ashes so far, it is not possible to make any statements about the extent to which the measured values of the comparative measuring methods are correct at all. Therefore, suitable, and representa-tive reference materials are indispensable for the validation of the measurement results and the quality assurance during the entire recycling process. Great care is required to select and prepare these reference materials. The reference materials must corre-spond in matrix to the samples that are to be investigated in the industrial process. An iron-rich and an aluminum-rich sewage sludge ash from mono-incineration plants were selected for this purpose. 10 kg of each sewage sludge ash were homogenized, char-acterized, and prepared. The main, minor and trace element compositions of the sew-age sludge ashes are determined by different measuring methods. The candidate ref-erence materials will be available as BAM-U200 und BAM-U201.
Knowing the exact nutrient composition of organic fertilizers is a prerequisite for their appropriate application to improve yield and to avoid environmental pollution by over-fertilization.
Traditional standard chemical analysis is cost and time-consuming and thus it is unsuitable for a rapid analysis before manure application. As a possible alternative, a handheld X-ray fluorescence (XRF) spectrometer was tested to enable a fast, simultaneous, and on-site analysis of several elements.
A set of 62 liquid pig and cattle manures as well as biogas digestates were collected, intensively homogenized and analysed for the macro plant nutrients phosphorus, potassium, magnesium, calcium, and sulphur as well as the micro nutrients manganese, iron, copper, and zinc using the standard lab procedure. The effect of four different sample preparation steps (original, dried, filtered, and dried filter residues) on XRF measurement accuracy was examined. Therefore, XRF results were correlated with values of the reference analysis. The best R2 s for each element ranged from 0.64 to 0.92. Comparing the four preparation steps, XRF results for dried samples showed good correlations (0.64 and 0.86) for all elements. XRF measurements using dried filter residues showed also good correlations with R2 s between 0.65 and 0.91 except for P, Mg, and Ca. In contrast, correlation Analysis for liquid samples (original and filtered) resulted in lower R2 s from 0.02 to 0.68, except for K (0.83 and 0.87, respectively). Based on these results, it can be concluded that handheld XRF is a promising measuring system for element analysis in manures and digestates.
Für die Rückführung von aus Rückbauprojekten anfallender künstlicher Mineralwolle in ihren Herstellungsprozess ist es notwendig, Stein- und Glaswolle zu unterscheiden und voneinander getrennt zu halten. Zu diesem Zweck wurde das Potential von NIR-Spektroskopie (NIRS) für einen werks- oder baustellenseitigen Einsatz getestet. NIRS wird aufgrund kurzer Messzeiten, minimaler Probenvorbereitung und hoher Robustheit der Spektrometer häufig in der Prozessanalytik eingesetzt. Untersucht wurden 70 verschiedene Mineralwollen, wobei sich der Probenumfang sowohl aus werksneuen Proben mit Herstellerangaben als auch unbekannten Proben ohne Spezifikation zusammensetzen, die auf verschiedenen Baustellen in den Jahren 2016–2017 entnommen oder von Deponien zur Verfügung gestellt worden waren. Als Referenzmethode wurde die Röntgenfluoreszenzanalyse verwendet, um den Mineralwolle-Typ über den Elementgehalt nach VDI 3492 zu identifizieren. Mit Hilfe eines multivariaten Datenanalyseverfahrens konnte schließlich eine Methode etabliert werden, die eine zuverlässige Identifikation von unbekannten Mineralwollen anhand deren NIR-Spektren als Stein- bzw. Glaswolle ermöglicht.
Gegenstand dieser Arbeit ist die Untersuchung eines bestehenden pyrometallurgischen Prozesses zur Rückgewinnung von Tantal und Niob aus metallurgischen Reststoffen mit vorwiegend niedriger Wertstoffkonzentration.
Zur näheren Erforschung der im vorliegenden Stoffsystem ablaufenden Reduktionsprozesse wurden in einem Elektrolichtbogenofen Schmelzversuche im Pilotmaßstab durchgeführt. Als Reduktionsmittel diente Koks, welcher mithilfe einer Argon-gespülten Eisenlanze in die flüssige mineralische Schmelze eingebracht wurde. Während der Reduktionsbehandlung werden Refraktärmetalle wie Tantal und Niob in ihre Carbide überführt und anschließend in der erschmolzenen eisenbasierten Metallphase am Boden des Reaktors angereichert. Neben Tantal und Niob gelangt auch ein Teil des im Einsatzmaterial enthaltenen Titans als unerwünschtes Begleitelement in die Metallphase.
Sein Großteil verbleibt jedoch als Oxid in der Schlacke und wird dort hauptsächlich im Mineral Perowskit (CaTiO3) gebunden. Die erstarrten Schlackeproben wurden mit verschiedenen Methoden wie Röntgenfluoreszensanalyse, Röntgenbeugung und Rasterelektronenmikroskopie mit gekoppelter energiedispersiver Röntgenanalyse untersucht, um die Bildung tantalhaltiger Mineralphasen zu verschiedenen Stadien des Reduktionsprozesses zu verfolgen.
Die hier gewonnenen Erkenntnisse zeigen, dass weniger die durch das Einblasen von Koks verursachte Reduktionsreaktion, sondern das Absinken der tantalreichen Eisentröpfchen in der flüssigen mineralischen Schmelze, gefolgt von ihrer Anreicherung in die Metallphase, für die Kinetik ausschlaggebend ist.
Within the framework of precision agriculture, the determination of various soil properties is moving into focus, especially the demand for sensors suitable for in-situ measurements. Energy-dispersive X-ray fluorescence (EDXRF) can be a powerful tool for this purpose. In this study a huge diverse soil set (n = 598) from 12 different study sites in Germany was analysed with EDXRF. First, a principal component analysis (PCA) was performed to identify possible similarities among the sample set.
Clustering was observed within the four texture classes clay, loam, silt and sand, as clay samples contain high and sandy soils low iron mass fractions. Furthermore, the potential of uni- and multivariate data evaluation with partial least squares regression (PLSR) was assessed for accurate Determination of nutrients in German agricultural samples using two calibration sample sets. Potassium and iron were chosen for testing the performance of both models. Prediction of these nutrients in 598 German soil samples with EDXRF was more accurate using PLSR which is confirmed by a better overall averaged deviation and PLSR should therefore be preferred.
Gegenstand der vorzustellenden Arbeiten ist die Prüfung der Umwelt-beständigkeit und -verträglichkeit von Materialien und Produkten hinsichtlich der Emission von potenziellen Schadstoffen in die Umwelt. Hierzu werden chemisch-physikalische Einflüsse (Bewitterung) und mikrobielle Beanspruchungen an Modellmaterialien evaluiert. So werden die Freisetzungsraten von Schadstoffen in Abhängigkeit der Beanspruchung beschrieben. Als Modellmaterialien kommen die Polymere Polystyrol (PS) und Polypropylen (PP) zum Einsatz. Synergistische Effekte der Bewitterungsparameter und der mikrobiologischen Beanspruchung sollen dabei ebenso betrachtet werden, wie die gezielte Alterung. Auch findet eine Beschreibung des Verhaltens der ausgetragenen Schadstoffe in den Umweltkompartimenten Boden oder Wasser statt. Hier sind mit Hilfe der zu entwickelnden Screening- und non-Target-Analyseverfahren die Transformation und der Metabolismus durch Mikroorganismen zu beschreiben. Aus den Ergebnissen sollen Korrelationen zwischen den künstlichen Alterungsverfahren und realen Szenarien abgeleitet werden.