Visible near-infrared diffuse reflectance spectroscopy and portable X-ray fluorescence spectroscopy for rapid compost analysis

Quantitative and qualitative evaluation of compost is necessary in order to provide consumers with basic knowledge about the product’s composition, and to protect public health and the environment by preventing the spread of contaminated material. Current methods for analysis of basic compost properties give accurate results but are time consuming and require numerous laboratory procedures. This study evaluated the use of visible near-infrared diffuse reflectance spectroscopy (VisNIR DRS) for organic matter (OM) determination and field portable X-ray fluorescence (PXRF) spectroscopy for determination of elemental composition of composted materials. These technologies were evaluated as alternatives to standard laboratory methods for their use in rapid in situ analysis. Thirty-six compost samples from a wide range of feedstocks were gathered and tested with VisNIR DRS and PXRF. For VisNIR DRS, the influence of sample moisture on scanning results was evaluated and the use of raw reflectance, first-derivatives, and second-derivatives of the reflectance spectra were compared. Partial least squares regression (PLS) and principal component regression (PCR) were used to build regression models of VisNIR DRS scans and lab measured OM. For PXRF, the influences of sample moisture, particle size, inter-elemental interactions, and OM on PXRF scanning results were investigated. Results from the VisNIR DRS study produced a promising r2 value of 0.82 and residual prediction deviation (RPD) value of 1.72 for the oven–dried first-derivative PLS model. Results indicate that VisNIR DRS shows great promise as a technique for analysis of OM content of dried compost samples, however further investigation with a larger sample set is necessary before VisNIR DRS can replace laboratory methods. Results of PXRF for elemental analysis were most promising for dried samples and for determining the elements Ca, Cr, Cu, Fe, K, Mn, P, and Zn. Arsenic detection was found to be greatly limited due to the influence of elevated Pb concentrations in the samples. Additionally, sample moisture, particle size, and OM were found to have varying influences on PXRF scan results for different elements. Compost elemental screening and definitive quantification of certain elements via PXRF is recommended by this study

The applicability of spectroscopy methods for estimating potentially toxic elements in soils: state-of-the art and future trends

Potentially toxic elements (PTEs) in soils pose severe threats to the environment and human health. It is therefore imperative to have access to simple, rapid, portable, and accurate methods for their detection in soils. In this regard, the review introduces recent progresses made in the development and applications of spectroscopic methods for in situ semi-quantitative and quantitative detection of PTEs in soil and critically compares them to standard analytical methods. The advantages and limitations of these methods are discussed together with recent advances in chemometrics and data mining techniques allowing to extract useful information based on spectral data. Furthermore, the factors influencing soil spectra and data analysis are discussed and recommendations on how to reduce or eliminate their influences are provided. Future research and development needs for spectroscopy techniques are emphasized, and an analytical framework based on technology integration and data fusion is proposed to improve the measurement accuracy of PTEs in soil

X-Ray Fluorescence Applications in Mudrock Characterization: Investigations into Middle Devonian Stratigraphy, Appalachian Basin, USA

Mudrocks are characterized by nanometer-scale pore sizes and nano-darcy permeability, which plays a significant role in hydrocarbon flow during production. Resulting from these characteristics, mudrocks were exclusively considered a source rock, which charged overlying, more porous mediums. Hydraulic fracturing, a technology used to create artificial fractures to liberate hydrocarbons from the reservoir, enabled natural gas to be produced from mudrock reservoirs economically. Over the last fifteen years, this technology motivated research efforts to understand reservoir characteristics of mudrock. These investigations significantly improved our knowledge of mudrock systems, but have also highlighted key areas that are undeveloped and/or where conflicting hypotheses exist. Utilizing wave-dispersive X-ray fluorescence (XRF) and high-resolution handheld energy-dispersive X-ray fluorescence (hhEDXRF) datasets collected from seven middle Devonian core throughout the Appalachian basin, this dissertation focuses on three areas of mudrock research: (1) development of mudrock calibrations to increase the analytical quality of hhEDXRF datasets, (2) investigation into the relationship between chemical composition of the host rock and natural fracture presence, and (3) assessment of the relationship between paleo-depositional conditions and organic carbon enrichment. This research indicates that lithology-specific calibrations significantly increase the analytical quality of hhEDXRF datasets, natural fractures preferential concentrate in zones of similar composition in a predictable manner, and an interplay of limited dilution and a robust anoxia-productivity feedback mechanism controlled organic carbon enrichment within middle Devonian mudrock of the Appalachian basin

X-Ray Fluorescence (XRF) Analyzer - Theory, Utility, and QA/QC for Environmental and Commercial Product Samples in Cambodia

Laboratory facilities in developed countries provide a variety of options for analysis of environmental samples and commercial commodities that could impact human health. The same is not true in developing countries and there is a great need to identify technologies that could be used to provide robust, accurate, cost-effective analysis that minimizes the need for extensive technical training. An X-ray Fluorescence (XRF) analyzer seems to be an analytical technique that could be such a tool for developing countries. Therefore, the objective of this thesis was to assess the performance and utility of a handheld, portable XRF unit in analyzing different types of environmental and commercial commodity samples in Cambodia. Because a number of different materials were analyzed, this thesis has a slightly different format than typical. Each of the following three chapters has its own methodology, results and discussion sections. This approach was taken because the materials analyzed and methods for sampling the materials were so different, it was clearer to separate the analyses into separate, individual chapters. This abstract provides a brief overview of each chapter. 1. Chapter One The need to have a more robust, cost effective and less time-consuming form for environmental samples in the field where samples could not be brought in for the laboratory analysis led to the manufacture of a first X-ray fluorescence (XRF) analyzer. This first chapter outlines the theory of the XRF, its advantages and limitations, and provides some QA/QC of a handheld XRF (XL3t 900, Billerica, MA) on skin whiteners, which were purchased and donated by university students for mercury levels. The results showed that up to 98 samples (16%) of creams analyzed contained mercury higher than 20 ppm, and 64 concoctions out of 192 samples were contaminated with more than 20 ppm mercury. Although there were suppressions (20%) of mercury at concentrations near 15,000 ppm (i.e. an under-estimation), the XRF proved to be an excellent tool capable of detecting metals; particularly mercury in semi-solid solutions. 2. Chapter Two Phnom Penh, the capital city of Cambodia, is home to some 1.4 million people and undergoing urbanization. In spite of its urbanization, Phnom Penh has yet to have a primary wastewater treatment plant and adequate sewage drainage system in place. There are two main interceptor sewer channels that drain wastewater and storm water from the southern part of the city into a natural wetland, Boeung Cheung Ek. These two sewer channels are the Tum Pun Sewer System and the Meanchey Sewer System. These are open sewer systems which collect all types of industrial, hospital, institutional and household wastes, and in turn discharge into the wetland. In Cambodia data related to metals contamination in sediment and street dust are very limited. So, this chapter of the thesis seeks to determine metal concentrations, spatial patterns and sources in sewer, wetland and street dust samples. Metals levels also are compared with United States Environmental Protection Agency (USEPA), New York State Department of Environmental Conservation (NYSDEC), and Provincial Sediment Quality (PSQ), Ontario, Canada guidelines. The results showed that although there are elevated metal concentrations in the sewer and wetland sediments and street dust samples, they are still lower than those reported elsewhere such as in Hong Kong, Greece, China, Korea, the US, and Malaysia. One sewer site (M1) had significantly higher metals levels than any other site of the two sewer systems, because it is geographically surrounded by industries and factories. The metal concentrations, especially Pb, Zn, and Cu, decreased with distance from this site. The levels of Pb in street dust appeared higher in high-density traffic areas and decreased with distance from the busy traffic streets. Although leaded gasoline can be a source of lead in street dust and sediments, Cambodia apparently complies with the EU guideline on the level of lead use in gasoline. In addition to leaded gasoline, diesel fuel can also contain metals but the levels are subject to further analysis. Other sources of metals in street dust include tire abrasion, brake lining and transmission oil. To reduce the levels of metals, the two sewer systems should be dredged periodically. The dredging also would increase channel flow capacity during storm events. Source tracking of metals should be conducted in more detail to inform management strategies. For the management of street dust, street sweeping and washing may be effective means to allay the metal toxicity levels. 3. Chapter Three Lead (Pb), which is a potentially hazardous toxicant, can be an additive agent of jewelry items and children’s toys. It is added to polyvinylchloride (PVC) pipes, so that it would provide rigidity, lower manufacturing costs and resistance to sunlight. Lead also has been a paint additive and this is of great concern in North America. Cambodia imports most of its consumer goods from other countries, but the regulatory inspection on imported products is not strictly enforced due to the lack of customs inspection tools, facilities and trained professionals. The purpose of this chapter is to assess jewelry items, children’s toys and paints for potential metal contamination from various markets in Phnom Penh, Cambodia and Bangkok, Thailand by means of the handheld X-ray fluorescence (XRF) analyzer. The results indicated that significant levels of Pb were used in the products (up to 43% in jewelry items and 4.3% in paints). These findings suggested that more restrictive regulations on the sales and use of toxic products should be imposed, so that health risks can be minimized. The XRF was manufactured, and over the years, has been re-engineered to provide the features necessary to operate in the field where laboratory-based assays not are suited. The XRF has some limitations for some elements like Cr and Hg in soils, the analyses of which necessitate laboratory-based verification such as an AAS or ICP. It also does not have the capacity to assess the degree of dermal and oral absorption of metals, although these aspects are still evolving. Nonetheless, the XRF would be an ideal tool for on-site and in situ investigation in Cambodia; particularly for customs officers, environmental researchers and engineers

Using Portable X-ray Fluorescence to Predict Physical and Chemical Properties of California Soils

Soil characterization provides the basic information necessary for understanding the physical, chemical, and biological properties of soils. Knowledge about soils can in turn be used to inform management practices, optimize agricultural operations, and ensure the continuation of ecosystem services provided by soils. However, current analytical standards for identifying each distinct property are costly and time-consuming. The optimization of laboratory grade technology for wide scale use is demonstrated by advances in a proximal soil sensing technique known as portable X-ray fluorescence spectrometry (pXRF). pXRF analyzers use high energy Xrays that interact with a sample to cause characteristic reflorescence that can be distinguished by the analyzer for its energy and intensity to determine the chemical composition of the sample. While pXRF only measures total elemental abundance, the concentrations of certain elements have been used as a proxy to develop models capable of predicting soil characteristics. This study aimed to evaluate existing models and model building techniques for predicting soil pH, texture, cation exchange capacity (CEC), soil organic carbon (SOC), total nitrogen (TN), and C:N ratio from pXRF spectra and assess their fittingness for California soils by comparing predictions to results from laboratory methods. Multiple linear regression (MLR) and random forest (RF) models were created for each property using a training subset of data and evaluated by R2 , RMSE, RPD and RPIQ on an unseen test set. The California soils sample set was comprised of 480 soil samples from across the state that were subject to laboratory and pXRF analysis in GeoChem mode. Results showed that existing data models applied to the CA soils dataset lacked predictive ability. In comparison, data models generated using MLR with 10-fold cross validation for variable selection improved predictions, while algorithmic modeling produced the best estimates for all properties besides pH. The best models produced for each property gave RMSE values of 0.489 for pH, 10.8 for sand %, 6.06 for clay % (together predicting the correct texture class 74% of the time), 6.79 for CEC (cmolc/kg soil), 1.01 for SOC %, 0.062 for TN %, and 7.02 for C:N ratio. Where R2 and RMSE were observed to fluctuate inconsistently with a change in the random train/test splits, RPD and RPIQ were more stable, which may indicate a more useful representation of out of sample applicability. RF modeling for TN content provided the best predictive model overall (R2 = 0.782, RMSE = 0.062, RPD = 2.041, and RPIQ = 2.96). RF models for CEC and TN % achieved RPD values \u3e2, indicating stable predictive models (Cheng et al., 2021). Lower RPD values between 1.75 and 2 and RPIQ \u3e2 were also found for MLR models of CEC, and TN %, as well as RF models for SOC. Better estimates for chemical properties (CEC, N, SOC) when compared to physical properties (texture), may be attributable to a correlation between elemental signatures and organic matter. All models were improved with the addition of categorical variables (land-use and sample set) but came at a great statistical cost (9 extra predictors). Separating models by land type and lab characterization method revealed some improvements within land types, but these effects could not be fully untangled from sample set. Thus, the consortia of characterizing bodies for ‘true’ lab data may have been a drawback in model performance, by confounding inter-lab errors with predictive errors. Future studies using pXRF analysis for soil property estimation should investigate how predictive v models are affected by characterizing method and lab body. While statewide models for California soils provided what may be an acceptable level of error for some applications, models calibrated for a specific site using consistent lab characterization methods likely provide a higher degree of accuracy for indirect measurements of some key soil properties

Near-Infrared Spectroscopy Combined with Multivariate Tools for Analysis of Trace Metals in Environmental Matrices

Environmental contamination by trace elements is becoming increasingly important problem worldwide. Trace metals such as cadmium, copper, lead, chromium, and mercury are major environmental pollutants that are predominantly found in areas with high anthropogenic activities. Therefore, there is a need for rapid and reliable tools to assess and monitor the concentration of heavy metal in environmental matrices. A nondestructive, cost-effective, and environmentally friendly procedure based on near-infrared reflectance spectroscopy (NIRS) and chemometric tools has been used as alternative technique for the simultaneous estimation of various heavy metal concentrations in environmental sample. The metal content is estimated by assigning the absorption features of metals associated with molecular vibrations of organic and inorganic functional groups in organic matter, silicates, carbonates, and water at 780–2500 nm in the near-infrared region. This chapter, reviewed the application of NIRS combined with chemometric tools such as multiple linear regression (MLR), principal component regression (PCR), and partial least squares (PLS) regression. The disadvantages and advantages of each chemometric tool are discussed briefly

CMB7 receptor modelling of airborne particulate matter in the Vaal Triangle

Bibliography: pages 86-90.The primary aim of the Vaal Air Monitoring (YAM) programme was to do a one year source apportionment study of airborne particulate matter in the Vaal Triangle. The V AM programme was undertaken by Mintek, in South Africa. Three receptor sites were set up, oneea.ch in the Central Business District (CBD) of Vereeniging, Vanderbijlpark and Sasolburg. For this thesis, CMB7 receptor modelling was performed on fifteen samples from the V AM study representing the pre-, mid-, and post-winter periods. Five samples from each receptor site were modelled following the United States Environmental Protection Agency (US-EPA)PM10 protocol. PM10 size selected particulates were collected on 47 mm Teflon and quartz fibre filter substrates over one week sampling periods. Thirty three chemical species were analysed for use in the Chemical Mass Balance receptor model. Teflon filters were used for inorganic elemental analysis. Inorganic elements were determined by energy dispersive X-Ray Fluorescence (EDXRFS), inductively coupled plasma mass spectrometry (ICP-MS) and Atomic Absorption Spectrometry (AAS). The quartz fibre filters were used for the determination of water soluble ions and carbon by Ion Chromatography (IC), and Thermal Optical Reflectance (TOR) respectively. Elemental and ion analyses were done at Mintek. Carbon analyses by TOR were done at the Desert Research Institute (ORI) in Reno Nevada, USA. Generally sample preparation and analysis of filter substrates followed ORI guidelines Where required, in-house methods developed at Mintek were successfully applied

Estrategias verdes para el análisis de muestras alimentarias y medioambientales

Los retos actuales de la Química Analítica Verde son el desarrollo, y su implementación en el análisis de rutina, de nuevas metodologías “verdes”, que sean más sostenibles con el medio ambiente. Por ello, el objetivo de esta tesis es desarrollar métodos de análisis directos mediante el empleo de la fluorescencia de rayos X en la determinación del perfil mineral y fomentar el uso del Smartphone como una herramienta de análisis complementaria a las técnicas convencionales en la determinación de compuestos de interés en muestras de alimentos y medioambientales. La presente tesis se estructura en 7 capítulos que de acuerdo con su temática pueden clasificarse en dos apartados: 1. Análisis de alimentos mediante fluorescencia de rayos X, técnica aplicada al análisis de la composición mineral en cacaos solubles, leches infantiles, frutas y legumbres. 2. Análisis mediante Smartphone, técnica desarrollada para la determinación del contenido de clorofila en hojas de cítricos y la determinación de compuestos polares totales (TPC) en aceite de girasol usado. Esta Tesis Doctoral se basa en la idea del desarrollo y optimización de métodos directos aplicando el concepto de la Química Analítica Verde, reduciendo el coste y el tiempo del análisis, así como el volumen de los reactivos empleados y de los residuos generados. En los primeros cinco capítulos de la tesis se analiza el perfil mineral en alimentos empleando la espectrometría de emisión óptica con plasma de acoplamiento inductivo (ICP-OES) como técnica de referencia. En el caso del análisis de clorofila (capítulo 6) se ha empleado como técnica de referencia la espectroscopia UV-Vis, se han realizado calibraciones con los datos de los dispositivos portátiles Chlorophyll Content Meter (CCM) y Soil Plant Analysis Development (SPAD) y las fotografías realizadas con el fin de predecir la concentración de clorofila en las hojas analizadas. En el trabajo del análisis de TPC en aceite (capítulo 7) se ha empleado el dispositivo portátil TESTO-270 como técnica de referencia. La Química Analítica Verde se basa en el empleo de metodologías analíticas más sostenibles con el medio ambiente y surge como respuesta a la demanda de métodos más rápidos, con un menor consumo de reactivos, una menor generación de residuos o sustitución de reactivos peligrosos por otros menos tóxicos, manteniendo a su vez las propiedades analíticas. El proceso de la generación del espectro de rayos X consta de 2 partes: la excitación, en la que la radiación primaria de rayos X incide sobre un electrón de las capas internas del átomo y se produce su expulsión, quedando así el átomo en estado excitado; y la emisión, en la que este átomo excitado tiende a volver a su estado más estable (estado fundamental), por lo que se producen saltos de los electrones que ocupan niveles más externos para cubrir los huecos en las capas internas. La excitación que se produce por el bombardeo de electrones se denomina excitación primaria, característica de los tubos de rayos X, y la emisión de otra radiación X, que se conoce como radiación secundaria, es la que se emplea para el análisis químico en los equipos de fluorescencia de rayos X. Hoy en día existen más de 3500 millones de usuarios de Smartphone en todo el mundo y este dispositivo se ha convertido en una herramienta indispensable en nuestras vidas. Sin embargo, este dispositivo móvil no solo sirve para la comunicación, fin con el que se diseñó en un principio, sino que nos permiten realizar cualquier tipo de acción y, si nos centramos en el campo de la ciencia con este pequeño dispositivo se pueden determinar y cuantificar analitos sin perder las propiedades analíticas a día de hoy.Los Smartphones se han convertido en una herramienta complementaria y verde de las técnicas convencionales en el análisis de sustancias y en los últimos años el empleo del Smartphone como herramienta analítica ha crecido de forma exponencial debido a su capacidad de realizar análisis in situ y a la no destrucción de las muestras. En el caso de determinaciones colorimétricas es necesario el uso de reactivos y de una preparación específica de la muestra, por lo que en estos casos no sería una herramienta tan “verde”

A review of atmospheric aerosols in Antarctica: from characterization to data processing

One of the major problems of the present era is air pollution, not only for its impact on climate change but also for the diseases provoked by this scourge. Among the most concerning air pollutants is particulate matter, since it can travel long distances and affect the entire globe. Antarctica is extremely sensitive to climate change and essential for regulating temperature and permitting life on Earth. Therefore, air quality studies in this region are extremely important. The aim of this review is to present the work conducted on the identification and detection of aerosols and particulate matter in the Antarctic region in the last 20 years. These studies revealed a large number of organic and inorganic species. Organochlorine pesticides or polychlorinated biphenyls represent almost 50% of the organic fraction detected in Antarctica. Furthermore, heavy metals such as Hg and Pb were also found in the region related to anthropogenic activities. To summarize, this work detailed different analytical techniques and data processing to help characterize Antarctic aerosols and their potential sources

Prediction of soil properties for agricultural and environmental applications from infrared and X-ray soil spectral properties

Many of today?s most pressing problems facing developing countries, such as food security, climate change, and environmental protection, require large area data on soil functional capacity. Conventional assessments (methods and measurements) of soil capacity to perform specific agricultural and environmental functions are time consuming and expensive. In addition, repeatability, reproducibility and accuracy of conventional soil analytical data are major challenges. New, rapid methods to quantify soil properties are needed, especially in developing countries where reliable data on soil properties is sparse, and to take advantage of new opportunities for digital soil mapping. Mid infrared diffuse reflectance spectroscopy (MIR) has already shown promise as a rapid analytical tool and there are new opportunities to include other high-throughput techniques, such as total X-ray fluorescence (TXRF), and X-ray diffraction (XRD) spectroscopy. In this study TXRF and XRD were tested in conjunction with IR to provide powerful diagnostic capabilities for the direct prediction of key soil properties for agricultural and environmental applications especially for Sub-Saharan Africa (SSA) soils. Optimal combinations of spectral methods for use in pedotransfer functions for low cost, rapid prediction of chemical and physical properties of African soils as well as prediction models for soil organic carbon and soil fertility properties (soil extractable nutrients, pH and exchangeable acidity) were tested in this study. These state-of-the-art methods for large-area soil health measurement and monitoring will aid in accelerating economic development in developing sub-Saharan Africa countries with regards to climate change, increasing water scarcity and impacts on local and global food security as well as sustainable agricultural production and ecosystem resilience in the tropics. This study has developed and tested a method for the use of TXRF for direct quantification of total element concentrations in soils using a TXRF (S2 PICOFOXTM) spectrometer and demonstrated that TXRF could be used as a rapid screening tool for total element concentrations in soils assuming sufficient calibration measures are followed. The results of the current study have shown that TXRF can provide efficient chemical fingerprinting which could be further tested for inferring soil chemical and physical functional properties which is of interest in the African soil context for agricultural and environmental management at large scale. Further, this thesis has helped to improve understanding of the variation and patterns of element concentration data for 1034 soil samples from 34 stratified randomly-located 100-km2 ?sentinel? sites across SSA and explored the link between variability of soil properties and climate, parent material, vegetation types and land use patterns with the help of Random Forests statistics. Our results of total element concentration were within the range reported globally for soil Cr, Mn, Zn, Ni, V, Sr, and Y and in the high range for Al, Cu, Ta, Pb, and Ga. There were significant variations (P < 0.05) in total element composition within and between the sites for all the elements analysed. In addition, the greatest proportion of total variance and number of significant variance components occurred at the site (55-88%) followed by the cluster nested within site levels (10-40%). Our results also indicated that the strong observed within site as well as between site variations in many elements can serve to diagnose their soil fertility potential. Explorations of the relationships between element composition data and other site factors using ?randomForest? statistics have demonstrated that all site and soil-forming factors have important influence on total elemental concentrations in the soil with the most important variables explaining the main patterns of variation in total element concentrations being cluster, topography, landuse, precipitation and temperature. However, the importance of cluster can be explained by spatial correlation at distances of <1 km. This study has also analysed the potential of combining analyses undertaken using MIR spectroscopy and TXRF on 700 soil samples from 44 ?sentinel? sites distributed across SSA. MIR prediction models for soil organic carbon, and other soil fertility properties (such as soil extractable nutrients, pH, exchangeable acidity and soil texture) were developed using Random Forests (RF) regression and the current study has added total element concentration data to the residuals of the MIRS predictions to test how they can improve the MIR prediction accuracies. The RF approach out-perfomed the conventional partial least squares regression (PLSR) on simultaneous determination of soil properties; and in addition, RF results were also easily interpretable, computationally much faster and did not rely on data transformations or any other assumptions about data distributions compared to PLSR. With respect to the potential of combining TXRF and MIR spectra, including total element concentration data from TXRF analysis in the RF models significantly reduced root mean square error of prediction by 63% for Ecd, 54% for Mehlich-3 S, and 53% for Mehlich-3 Na. Thus, TXRF spectra were a useful supplement to improve prediction of soil properties not well predicted by MIRS. The prediction improvement from including TXRF was due to detection of a few outliers that did not appear as MIR spectral outliers. MIR showed remarkable ability to capture total elemental composition effects on physico-chemical soil properties but TXRF may have potential for outlier detection in large studies. This study has also helped to develop high-throughput spectral analytical methods and provided recommendations on optimal spectral analytical methods for the Globally Integrated Africa Soil Information Service (AfSIS) Project. Successfully developed methods in this study will become part of the standard AfSIS procedures.Viele der heutigen dringendsten Problemfelder der Entwicklungsländer wie Gewährleistung der Ernährungssicherheit, Anpassung an Klimawandel und verbesserter Umweltschutz erfordern umfangreiche, flächendeckende Daten über die funktionelle Kapazität von Böden. Herkömmliche Verfahren (Methoden und Messungen) zur Bestimmung von spezifischen landwirtschaftlichen und ökologischen Bodenfunktionen sind zeitaufwendig und teuer. Neben den Kosten sind die Wiederholbarkeit, Reproduzierbarkeit und Genauigkeit von herkömmlichen analytischen Methoden große Herausforderungen. Neue, schnelle Methoden zur Quantifizierung von Bodeneigenschaften sind notwendig, vor allem in Entwicklungsländern, wo zuverlässige Daten über Bodenqualität schwer zu beschaffen sind, und um die Vorteile der neuen Möglichkeiten einer digitalen Bodenkartierung auszunutzen. Infrarot-Spektroskopie mit diffuser Reflexion (IR) hat bereits gute Ergebnisse als ein schnelles Analyse-Instrument gezeigt und es gibt neue Möglichkeiten, um andere Hochdurchsatz-Techniken wie die Total-Röntgenfluoreszenz (TXRF) und Röntgenbeugungs-Spektroskopie (XRD) einzusetzen. In dieser Studie wurden TXRF und XRD in Verbindung mit IR getestet, um leistungsstarke Diagnosefunktionen für die direkte Vorhersage der wichtigsten funktionellen Eigenschaften von Böden für Landwirtschaft und Umwelt-Anwendungen besonders für die Böden Afrikas südlich der Sahara zur Verfügung zu stellen. In dieser Studie wurden optimale Kombinationen von spektralen Methoden getestet, die für den Einsatz in Pedotransferfunktionen mit niedrigen Kosten, einer schnellen Vorhersage der chemischen und physikalen Eigenschaften der afrikanischen Böden, sowie in Prognosemodellen für organischen Kohlenstoff im Boden und die Bestimmung von Bodenfruchtbarkeitsparametern (extrahierbare Nährstoffe, pH-Wert und austauschbare Säuren) geeignet sind. Diese aktuellen Methoden zur großflächigen Messung und Überwachung der Bodengesundheit können dazu beitragen, die wirtschaftliche Entwicklung in den Ländern Afrikas südlich der Sahara positiv zu fördern, besonders in Bezug auf den Klimawandel, die lokale und globale Ernährungssicherheit sowie die Nachhaltigkeit der landwirtschaftlichen Produktion und der Stabilität der Ökosysteme. In diese Studie wurde zunächst ein Verfahren zur Verwendung von TXRF zur direkten Quantifizierung der gesamten Elementkonzentration in 15 Bodenproben unter Verwendung eines TXRF (S2 PICOFOXTM) Spektrometers entwickelt und mit 20 weiteren Bodenproben getestet. Die Ergebnisse zeigten, dass bei ausreichender Kalibrierung TXRF als ein schnelles Screening-Werkzeug für die meisten Elemente verwendet werden kann. Die Ergebnisse der aktuellen Studie haben ausserdem gezeigt, dass TXRF effiziente chemische Fingerabdrücke liefern kann, die zum Ableiten von chemischen und physikalischen Bodeneigenschaften dienen können. Diese Arbeit hat weiter dazu beigetragen, den Zusammenhang zwischen Variabilität der Bodeneigenschaften und Klima, Bodenausgangsmaterial, Vegetationstypen und Landnutzung mit Hilfe von TXRF, XRD und IR-spektralen Methoden zu verstehen. Dafür wurden 1034 Bodenproben analysiert, die im Rahmen des ?Africa Soil Information Service? (AfSIS) Projektes von 34 randomisiert ausgewählten stratifizierten Standorten von jeweils 100 km2 in zahlreichen Länders Afrikas südlich der Sahara entnommen wurden. Die Ergebnisse der Gesamt-Elementkonzentrationen dieser Bodenproben lagen im Bereich der dokumentierten Konzentrationen für die Elemente Cr, Mn, Zn, Ni, V, Sr und Y, lagen aber höher als gewöhnlich für die Elemente Al, Cu, Ta, Pb, and Ga. Signifikante Unterschiede (P < 0,05) der Gesamt-Elementkonzentrationen wurden sowohl innerhalb als auch zwischen den beprobten 34 Standorten gefunden. Die Variabilität war deutlich grösser zwischen den 34 Standorten (55-88 % Varianz) als innerhalb der Standorte (10-40 % Varianz). Mit Hilfe von ?Random Forests?-Regressionen konnte gezeigt werden, dass die Gesamt- Elementkonzentrationen der untersuchten Bodenproben von umweltbezogenen Standortvariablen wie Topographie und Landnutzungstyp als auch Klimafaktoren wie Temperatur und Niederschlag wesentlich beeinflusst werden. In einem weiteren Schritt wurde die Aussagekraft einer Kombination von MIR und TXRF-Methoden und der ?Random Forests?-Regression anhand von 700 Bodenproben von 44 Standorten in Afrika südlich der Sahara getestet. Dazu wurden zunächst MIR-Vorhersagemodelle für organischen Bodenkohlenstoff und andere Bodenfruchtbarkeitsparameter (extrahierbare Nährstoffe, pH-Wert und austauschbare Säuren) mit Hilfe von ?Random Forests? (RF)-Regressionen entwickelt. Durch Einbringen der Gesamtelement-Daten zu den Residuen der IR-Vorhersagen konnten die MIR-Regressionsmodelle signifikant verbessert werden. Im Vergleich zu der gewöhnlich benutzten ?partial least square?-Regression (PLSR) zeigte die entwickelte RF-Regression deutlich bessere Ergebnisse, war schneller anzuwenden und einfacher zu interpretieren und war nicht auf zeitaufwändige und fehleranfällige Datentransformationen wie die PLSR angewiesen. Durch die Kombination von TXRF- und MIR-Spektren konnte ausserdem die Vorhersage-Genauigkeit der Bodenparameter deutlich verbessert werden, z.B. für Ecd um 63%, Mehlich-3 S um 54%, Mehlich-3 Na um 53% verglichen zur alleinigen Nutzung der MIRS-Spektren. Zusammenfassend hat die vorliegende Studie dazu beigetragen, neue spektrale Bodenanalysemethoden mit hohem Durchsatz zu entwickeln und Empfehlungen für die optimierte Anwendung dieser Methoden zu erarbeiten, die bereits erfolgreich von dem oben erwähnten AfSIS-Projekt übernommen und in die Standard-AfSIS Verfahren integriert worden sind