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Algal Ecology. Jan Stevenson. Micronutrient Deficiency in Soils and Plants. Theocharis Chatzistathis. Principles of Terrestrial Ecosystem Ecology. Plant Physiological Ecology. Hans Lambers. Abid A. Organic Xenobiotics and Plants. Progress in Botany. Wolfram Beyschlag. Enhancing Cleanup of Environmental Pollutants. Naser A. Diversity and Biotechnology of Ectomycorrhizae.

Mahendra Rai. Soil Emission of Nitrous Oxide and its Mitigation. David Ussiri. Plant Adaptation Strategies in Changing Environment. Vertika Shukla. Plant-Based Remediation Processes. Dharmendra Kumar Gupta. Detoxification of Heavy Metals. Reviews of Environmental Contamination and Toxicology Volume David M. Microbes at Work. Ingrid Franke-Whittle.

Biogeochemistry of Trace Elements in the Rhizosphere. Applied Bioremediation and Phytoremediation. Owen P. Pim de Voogt. The Science of Algal Fuels. Richard Gordon. Advances in Applied Bioremediation. Ajay Singh. Advances in Citrus Nutrition. Anoop Kumar Srivastava. Plant Responses to Drought Stress. Ricardo Aroca. Adjuvants for Agrichemicals. Chester L. Green Materials for Energy, Products and Depollution. Molecular Environmental Soil Science. Jianming Xu. Viktor Schauberger. Nutrient Use Efficiency: from Basics to Advances. Amitava Rakshit. Potassium Solubilizing Microorganisms for Sustainable Agriculture.

Vijay Singh Meena. Sanjay Arora. Agro-Environmental Sustainability. Jay Shankar Singh. Mukesh K. Biological Odour Treatment. Nanoscience and Plant—Soil Systems. Mansour Ghorbanpour. This technique can also be combined with a sample plate to enable high-throughput screening. Solid and liquid samples can be measured using Attenuated Total Reflectance IR spectroscopy ATR-IR ; for this, the IR-beam is introduced into a crystal at an angle exceeding the critical angle for internal reflection and thus reflects at least once at the internal surface in contact with the sample.

Depending on the spectral device, dispersive and Fourier-Transform- FT spectrometry can be distinguished. Dispersive spectrometry uses prisms or grates to separate the light into the different wave lengths or wavenumbers; whereas FT spectrometry measures all wave lengths simultaneously as an interferogram which is transferred into the spectrum by a Fourier transformation.

This technique is currently considered the state-of-the-art especially if synchrotron-based sources are used to aquire the spectra e. Over the past decade, a considerable amount of research has been done to develop NIRS applications for soil analysis for a general overview see review by Nduwamungu et al. However, P can be quantified via NIRS if it is bound organically or is tightly associated with other soil properties. Therefore, it is not surprising that only few NIRS models are available to predict concentrations of P t or different P fractions in soil Chang et al. Generally, the quality of NIRS prediction models is assessed using a number of statistical parameters comprising the goodness of fit, r 2 measured vs.

The prediction quality of models increases with r 2 and RPD. According to a review by Malley et al. Nonetheless, ongoing work at the University of Freiburg, Germany, is exploring the potential of NIRS to investigate soil P pools of different availability; the procedures and preliminary findings are described here. Soil samples were dried to reduce the impact of the strong influence of the O—H bond on near IR absorption Malley et al.

Spectra were recorded using a Tensor 37 spectrometer from Bruker Optics Ettlingen, Germany at constant temperature. The whole NIR spectral area was scanned with intervals of 16 wave numbers each interval 64 times and converted via a Fourier-Transformation into one spectrum. A mean spectrum was created for each sample from 5 replicate measurements. Reference data for soil P in fractions of different availability were determined using the sequential extraction method according to Hedley, modified by Tiessen and Moir This chemometric method takes advantage of correlative relationships between the spectral signatures and soil attributes by selecting successive orthogonal factors, which maximize the covariance between the predictor spectra and the laboratory data.

Usually, the first derivative of a spectrum is taken to split it into latent variables using PLSr analyses, which are then included in a regression model for estimating the soil properties. For more details on the PLSr models and their use in soil science, the reader is referred to Viscarra Rossel et al. It should be noted, however, that each PLSr model requires a calibration data set, which may be soil-type specific. Recently, Siebers et al. The data calibration and model development steps utilize, for example, multivariate calibrations, selection of the best fitting model Fig.

As a rule of thumb, at least reference samples should be available for complex samples like soil. Additionally, at least 30 to 40 samples, which are not part of the calibration process, are recommended for model validation. Provided that a sufficient number of reference data is available, the assessment of a variety of parameters is possible with one spectrum. However, the more complex the sample is, the more interference and overlapping of spectral information can occur.

Therefore, developing NIRS-models for estimation of P fractions in soil that contain a wide variety of other organic compounds is challenging. Although some reference analysis is necessary for the calibration, the main advantage of NIRS is the possible replacement of extractions and wet-chemical fractionations by a faster and operationally simpler method. This makes it especially interesting for large scale surveys with many samples, e. Viscarra Rossel et al. Subsequently, Moron and Cozzolino reported that higher r 2 values at least up to 0.

Coefficients of determination exceeding 0. For example, Daniel et al. Since then, however, the use of PLSr has become prevalent.

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Remarkably, with suitable sample pretreatment e. In summary, IR spectroscopy NIRS and MIRS has been reasonably successful in identifying different P species in environmental samples and, in combination with PLSr or related mathematical techniques; it has gained increasing potential for minimum-invasive, high throughput soil P sensing.

Nonetheless, it is still unclear whether successful IR-based evaluations of P bonding forms are always the result of specific vibrations in the MIR or NIR spectra, or the consequence of poorly understood or even spurious relationships with other soil parameters, such as Fe-oxides and soil OM quality. In P research, Raman spectroscopy has been used mainly to understand the nature and importance of chemical bonds, both in P-bearing minerals and between P species and reactive surfaces.

Most Raman measurements are usually carried out with pure minerals or model systems, with only a few using actual soil samples because of the interference by fluorescence. The intensity of the Raman signals resulting from the inelastic scattering depends on the changing of the molecular polarizability during the vibration; this goes with the second power and, fortunately, the P—O symmetric stretching of phosphate is very well detectable using Raman spectroscopy.

In general, Raman spectroscopy is an analytical method that can be employed in the laboratory using probes both for solid and liquid states, whilst portable Raman sensors for use in the field are also vailable described to measure P in soil Bogrekci and Lee , b ; Lee and Bogrekci , The main advantages of Raman measurements include the simple sample preparation, the small amount of analytical material required and the fact that the resulting data can be used without any reprocessing.

If the matrix is very heterogeneous and fluorescent substances are present, extraction steps can be undertaken to isolate the analyte. In pure systems, various band frequencies of different endmember elements Ca, Cd, Pb—Sr of hydroxyapatite can be identified. In soils, Raman spectroscopy was able to trace added hydroxyapatites at a sub-micron grain size and at concentrations down to 0.

Another advantage is the possibility to analyze aqueous solutions—owing to the very weak Raman scattering of water. Due to the excitation using a laser beam, only a very small area of the probe is analyzed. Combinations with optical microscopes normal and confocal Raman microscopy are currently available, as well as those with non-optical microscopic techniques which have a higher resolution and are not limited by the wave length of visible light e. Cusco et al.

Lanfranco et al. Kasioptas et al. A relatively new application is the use of IR and Raman spectroscopy for mapping and imaging Salzer and Siesler , To date, Raman spectroscopy has not been used extensively to characterize soil-inherent P because of the interference of fluorescence effects. The mechanism of fluorescence is very similar to the underlying mechanism of the Raman scattering, but it is much stronger Kizewski et al.

Fluorescing substances therefore disturb the Raman spectra, and among these distorting compounds are all naturally organic materials, thus limiting its application for soil samples. Excitation in the IR frequency range with a FT-spectrometer can remedy this interference because the power of Raman emission increases with the fourth power of the frequency of the source FT-Raman Spectroscopy Aminzadeh , Raman spectroscopy can be applied to investigate the sources, uptake, and release of P in studies that use the O isotope ratios of phosphate as a natural tracer cf. To test the potential of this approach, a heating experiment with 18 O enriched silver phosphate Ag 3 P 18 O 4 was conducted.

Silver phosphate was used because this compound is commonly used to extract phosphate from soil matrices in O-isotope studies cf. The observed wave numbers of the bands are in a good agreement with the calculated values with Eq. Raman spectrum of heated Ag 3 P 18 O 4 and the respective peak shifts due to successive 18 O exchange Lewandowski and Amelung , , unpublished.

The color image of this figure is in the digital version of this article. While the shift of the signal's wavenumber is directly correlated to the number of the exchanged atoms see Eq. Therefore, Fig. In molecules with phosphate groups, the O atoms are not equal and the exact position of the Raman signals also depends on the position of the isotope exchange. This can be shown by quantum-chemical calculations of the peak positions of the O isotopes at different positions in the phosphate. In real Raman spectra these differences are difficult to detect because the signals are broadened by matrix effects.

Raman spectroscopy has also been used to observe mineral replacement reactions, such as the transition of aragonite and calcite into hydroxyapatite by hydrothermal treatment with NH 4 2 HPO 4 Kasioptas et al. In both cases the incorporation of the heavier O isotope into the apatite and carbonate, respectively, was monitored. Furthermore, the exchange kinetics of O isotopes between water and CO was studied Geisler et al.

In all measurements the Raman band of the symmetric vibration of the phosphate or carbonate molecule was the tracer of the isotope exchange mechanism. In summary, Raman spectroscopy is an excellent and novel but as yet underexplored tool in the determination of soil P composition and dynamics. Although the main applications make effective use of model systems, new exciting possibilities in spatial imaging lend the technique to more heterogeneous systems Lanfranco et al. For soil samples some extraction is usually required as a precondition for MS analysis.

Extracts are either separated by chromatography or directly injected into the mass spectrometer. ESI is a soft ionization technique because of minimal fragmentation which facilitates the characterization of intact molecules Banerjee and Mazumdar , It is very sensitive for polar compounds; however, in the positive mode it often leads to multiple charged ions and adducts with alkaline metals, making the determination of molecular species and, thus, spectral evaluation, difficult.

For P analysis this is even more challenging because of the poor ionization efficiency of P-containing compounds resulting in low sensitivity Reemtsma , Very low concentrations of P-containing molecules, e. Therefore, selective isolation and pre-concentration steps to increase P concentration and remove interfering non-P containing dissolved organic matter DOM molecules is usually required.

High resolution mass spectrometry can distinguish among different mass-to-charge ratios within very complex mixtures that comprise upwards of several thousand compounds. Furthermore, a verification of the assigned sum formula by stable isotopic patterns, as often performed for C, N, and S containing compounds, is impossible because 31 P is the only stable P isotope Koch et al.

Therefore, spectra evaluation has not yet routinely included P, although its inclusion does provide a more complete chemical characterization of the sample. Only a few devices can provide this high mass resolution for large molecules such as organic phosphates, i. FT ICR-MS devices deliver unbeaten resolving power and semi-quantitative determination by using a very strong magnetic field to trap the ions inside a vacuum cell Marshall et al.

Orbitrap-MS devises use very strong electric fields and spindle shaped electrodes and TOF-MS use long flight paths to enable quantitative high resolution measurements with high scan rates Hu et al. Therefore, an extensive treatment of spectral data is needed to reduce complexity, and to examine, interpret and visualize this massive molecular-chemical data set with the aim to identify spectral differences among samples.

Modified replot from Abdulla et al. A color image of this figure is in the digital version of this article. Recently, Abdulla et al. Multivariate statistical analysis methods such as principal component analysis or hierarchical clustering analysis also can be used for spectra evaluation Hur et al.

However, only a few studies have looked at the composition of P containing compounds in, e. Conversely, targeted mass spectrometry at normal or high resolution roughly 10 to 50 times lower than ultrahigh resolution provided by the FT ICR-MS devices, described above are commonly used to quantify natural and anthropogenic P-containing compounds in soils, e. Several studies have used MS based techniques to investigate glyphosate and aminomethylphosphonic acid AMPA, glyphosate's primary metabolite concentrations in soils e. For example, Aparicio et al. General overviews on the mobility, leaching and fate of glyphosate have been published by Vereecken and Borggaard and Gimsing By subsequent separation using a reverse phase LC-system, sufficient retention times with good resolution can be achieved Fig.

Together with stable isotopes of glyphosate and AMPA, that serve as internal standards, this approach may yield quantitatively reproducible data with high precision and accuracy in quantification e. Inductively coupled plasma mass spectrometry ICP-MS is another methodological approach to characterize and quantify P in environmental samples. Although ICP-MS has been used mainly for total element quantification in liquid samples, instrument developments and combinations with various separation and sample introduction techniques e. The selected examples of mass spectrometry presented here demonstrate the vast potential of the technique in investigating P compounds in soil, especially in the soil solution.

With an increasing number of instruments becoming available in recent years and in the near future, more applications can be expected. For targeted MS methods, the ever increasing sensitivity of instrumentation enables deeper insight in the fate of specific P compounds in the soil—plant and soil—water systems. However, soil microorganisms constitute not only a substantial part of P in the soil, but are also involved in a number of important processes in the soil P cycle, e. Phospholipids are essential membrane components of all living cells and are characterized by a rapid degradation in soils after cell death due to enzymatic hydrolysis.

Hence, the remaining amount of intact phospholipids in soil is highly correlated with the living soil microbial biomass and can serve as a quantitative measure of the P mic White et al. Phosphatidic acid PA is one of the simplest glycerophospholipids, consisting of two fatty acids esterified to the sn -1 and sn -2 position of a glycerol backbone and a polar phosphate headgroup which is attached to the sn -3 position.

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The diacylglycerol moiety of phosphatidic acid is incorporated into different phospholipids by phosphate ester condensation with different alcohols [e. In addition to the ester-linked glycerophospholipids there are also soil bacteria that occur ubiquitously in soil having ether-linked glycerophospholipids as membrane lipids which are characterized by an ether-linked acyl chain at the sn -1 or sn -2 position. These ether bonds are more resistant to oxidation and high temperatures than ester bonds, and ether bound phospholipids are most prominent in Archae Albers et al.

The distribution of intact polar branched tetraether lipids in peat and soil have been studied e. The co-existence in soil of such a broad range of phospholipid structures is explained by the fact that the different headgroups can be combined with a large number of fatty acids that vary both in chain length and degree of desaturation. Since the fatty acid composition in phospholipids varies widely among different microorganisms, their distribution profiles reflect the soil microbial community structure White et al.

Therefore, phospholipid fatty acid PLFA profiles are widely used as biomarkers of the microbiota in soil Buyer and Sasser , For PLFA analysis by gas chromatography GC , the extracted and separated phospholipids are methanolyzed and the acyl groups are cleaved and converted into their methyl esters. In this approach only the acyl groups, but not the headgroups, can be analyzed. To obtain further structural information within the different phospholipid classes, separation by thin layer chromatography TLC prior to fatty acid methyl ester FAME synthesis is required Wu et al.

Silica gel is most commonly used for this purpose, in combination with different solvent systems Kahn and Williams , Once separated, the acyl groups can be quantified by isolating individual lipids from the silica material Benning and Somerville , However, GC-based methods are unable to provide information about the different molecular species of phospholipids.

As a consequence, further analytical methods have been developed to investigate intact phospholipid molecular structures, as reviewed by Peterson and Cummings Briefly, formic acid is added to the solvent of the first extraction to prevent lipid degradation by lipases during lipid isolation Browse et al. The extracted lipids are subsequently fractionated based on their polarity by solid phase extraction, resulting in an extract highly enriched in phospholipids, which is further characterized by a reduced ion suppression during Q-TOF MS analysis.

For quantitative analysis a phospholipid standard mix is used. In the TOF analyzer, ions are accelerated, separated, and detected at the photomultiplier plate. The quantification of phospholipids is based on precursor ion or neutral loss scanning in relation to internal phospholipids standards of known concentrations Gasulla et al. For each phospholipid class at least two different internal standards are selected, which are absent in soil samples, enabling a very precise and reliable phospholipids quantification.

The concentration of C and Ccontaining molecular species of PC and PE are significantly larger in the arable while the concentrations of Ccontaining molecular species of PC and PE are larger in the forest soils Fig. The total concentrations of PC and PE, as most abundant classes of phospholipids in eukaryotic cells, are significantly larger in the slightly acidic to neutral pH 6. It is a main component of PG in diverse plant materials, with increased concentrations in some arable crops e.


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The Ccontaining molecular species of PC and PE were described as dominant components of phospholids in litter under pine and spruce Wilkinson et al. The data present means and standard deviations of five replicas Siebers et al. However, additional GC MS measurements are required to determine the position of the double bond, which is an additional marker in the PLFA analysis e. This would enable a detailed insight into the composition of phospholipids as part of a fast cycling P o pool in soil and helps to disclose changes in the soil microbial community structure and their adaption to altering environmental conditions such as P-deficiencies.

Nano-scale Secondary Ion Mass Spectrometry NanoSIMS is a destructive mass spectrometric technique linking high-resolution microscopy with elemental and isotopic analysis. However, soil applications of this technique are still in their infancy. This leads to the sputtering of the upper surface of the sample and the release of neutral particles and positively or negatively charged mono-atomic or poly-atomic secondary ions e.

Poly-atomic secondary ions result from recombination reactions of reactive mono-atomic ions McMahon et al. The secondary ions are extracted coaxially and accelerated into the double-focusing sector field mass spectrometer, capable of providing the high mass resolution needed, e. However, beam focussing decreases primary beam intensity and, thus, reduces secondary ion yield.

To prevent atmospheric interference with the primary and secondary ions, the measurements are taken under ultra-high vacuum down to 1. Several sequential images from the same spot can be accumulated and merged after drift correction to improve the signal-to-noise ratio. Static SIMS techniques [ e. By contrast, in dynamic NanoSIMS that uses a high primary ion beam dose, beam impact results in an almost complete fragmentation of all molecules at the sample surface and, thus, rapid surface erosion. This inherently destructive nature of NanoSIMS enables not only the characterization of the P distribution in the surface monolayer, but also 3-dimensional 3D mapping by reconstructing the images obtained from the subsequent scanning cycles.

However, all analyses are affected by element-, isotope- and matrix-dependent sputtering rates, ion yields, and charging effects Winterholler et al. Therefore, absolute quantification as well as the comparison of spatial distribution patterns of different elements by NanoSIMS remain challenges. Attempts to partly overcome such difficulties combine topographical information from atomic force microscopy with NanoSIMS analysis Wirtz et al. More recently, Hatton et al. However, this requires that the observation areas in NanoSIMS reflect the bulk macroscopic properties. Therefore, soil samples are commonly deposited onto the sample holder by drop coating or embedded in ultra-high vacuum resistant resin, thin sectioned, and subsequently polished to attain the desired plane surface for analysis Herrmann et al.

However, optimized preparation protocols for soil samples are still under development; essentially, the procedures are not as straightforward as those for biological samples which have been prepared successfully by ultrafast plunge-freezing techniques e. To prevent charging during analysis, the prepared samples can be sputtered with gold, platinum, or carbon before loading into the NanoSIMS.

In practical measurements, regions of interest are initially selected using the optical cameras, and then these are more accurately observed using the secondary electron image created by scanning the primary ion beam. This gives the opportunity to localise hotspots of P enrichment or sharp and narrow zones of P depletion around roots or fungal hypae and, thus, helps to spatially resolve P depletion and transfer in the plant-soil system. Since there are no other ions or clusters significantly interfering at these masses, high mass resolution is not required. Thus, high transmission rates can be employed to account for the low ionization efficiency and abundance of P compared to C in most soil samples.

The detection limit for P is difficult to determine, since the bulk soil P concentration can be quite misleading with respect to surface P concentrations predominantly accessed by NanoSIMS. Therefore, for soil samples several sequential images are combined to yield images with improved signal - to - noise ratio; an example is provided in Fig.

The same bacteria were also treated with an elevated NaCl mM solution to simulate salt stress not shown. A color image of this figure is in the digital version of the article. However, spatial correlations with other elements such as Fe, Al or Ca may provide information on the chemical coordination of P. However, to the best of our knowledge, this has not yet been done, possibly because 32 P and 33 P are isobaric with the stable S isotopes 32 S and 33 S, respectively.

Therefore, to trace the fate of labelled P, a soil sample must be free of S, since a simple subtraction of images without [showing the natural abundance of 32 S Another possibility may be waiting for the decay of 32 P or 33 P and measuring the spatial distribution of the decay products 32 S or 33 S , and superimposing the natural isotopic S distribution in the soil sample.

The higher secondary ion yield of S isotopes compared to P may be an additional benefit from this approach. To advance this approach requires tracer concentrations and blind correction factors, further methodological test whether such small changes in the abundance of 32 S or 33 S can be detected as well as a systematic assessment of the possible effects of radioactive decay on the binding and fate of the tracer. Since the early s the use of synchrotron radiation electromagnetic radiation produced in a synchrotron has enabled the development and application of several X-ray absorption based spectroscopic and microscopic analytical techniques for P speciation and molecular-scale processes in soil and related samples.

In the last decade, this has been promoted further by the rapid development of the number and capabilities of beamlines, which are, at least partly, dedicated to those types of samples.

Combining spectroscopic and isotopic techniques gives a dynamic view of phosphorus cycling in soil

Essentially, this development is linked with the high brightness and intensity and wide tuneability of X-ray beams using synchrotron radiation. Therefore, a higher sensitivity is achieved compared to conventional X-ray sources e. Most of the X-ray methods are based on the photo-electric effect. Briefly, X-ray photons get absorbed by the target element, thus promoting its core electrons e. Below the element-specific binding energy BE of the core electron, the absorption is small; on the contrary, at energies close to the BE of the core electron, a sharp increase in the absorption occurs. As a consequence, the absorber atom is left in an unstable exited state.

There are three main techniques utilizing the fact that absorption energy, energy of emitted electrons and fluorescence photons are characteristic for an element and its electron configuration: 1 X-ray fluorescence XRF spectroscopy, 2 X-ray absorption spectroscopy XAS , and 3 X-ray photoelectron spectroscopy XPS. Energy dispersive X-ray fluorescence XRF spectroscopy is a fast, non-destructive technique enabling quantitative, but no qualitative, multi-element analyses of environmental samples Bamford et al.

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Although XRF spectroscopy can be carried out with laboratory-based or even handheld X-ray tubes, the utilization of synchrotron radiation as the excitation source is becoming more popular; this is because higher quality better signal-to-noise-radio and more accurate spectra can be recorded as a result of reduced detection limits Sarret et al. This is even more beneficial for soils in which sample matrix effects, causing high background noise levels and reduced sensitivity, constrain the use of XRF Mukhtar and Haswell , XRF spectroscopy is commonly used to determine the total P concentration in environmental samples, such as soil e.

Nevertheless, XRF spectroscopy is often the preferred method due to the ease of sample preparation, and the relatively rapid sample through-put, thus enabling a more cost effective screening of very large sample sets, even in the field e. Synchotron based total X-ray fluorescence TXRF spectroscopy is one of the many varieties of XRF, capable of determining elemental concentrations in the ultra-trace range; indeed, measurements of P t atmospheric aerosol particulates are possible at concentrations as low as 0. This is achieved by decreasing the incidence angle of the incoming beam below the critical angle of total reflection; this minimizes penetration depth, absorption and scattering of the incoming beam in the sample matrix and, thus, reduces background noise and increases sensitivity Wobrauschek , Liquid samples are best suited for TXRF spectroscopy Wobrauschek , , and have been applied for P analysis in soil extracts e.

In a recent study by Towett et al. X-ray absorption spectroscopy is based on measuring the variation of the absorption coefficient of a sample as a function of the applied X-ray energy in order to obtain an absorption spectrum. This can be done either directly or indirectly.

The direct method monitors the intensity of the beam transmitted through the sample transmission mode. Conversely, it should be noted that spectra recorded in FLY mode for highly concentrated and thick samples can be distorted by self-absorption effects e.


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  8. Essentially, these effects are attributed to a reduction in the penetration depth, causing re-absorption of the fluorescence photons; this is not an issue for spectra recorded in TEY mode. Therefore, samples with high P concentrations should be diluted or analyzed using the TEY detection mode. However, it should be noted that for samples where surface structure is different from that of the bulk material, TEY and FLY spectra may differ in their spectral features; this is a direct consequence of the much shallower sampling depth of TEY see above e. Furthermore, due to the generally low penetration depth a few microns of the X-rays used for P XAS measurements, data collection in transmission mode is often impractical.

    The latter condition also enables solid-state in-situ measurements of moist or liquid samples Kelly et al. Liquids must be inserted into a liquid cell Rouff et al. One of the main advantages of XAS is the relatively straightforward preparation, simply by powdering and spreading a few milligrams as a thin film on a double adhesive tape which is attached to a sample holder. The marked increase in intensity around 2, eV corresponds to the P K -edge. The exact ranges depend on the edge probed Fig. The acronyms also provide the names given to the respective XAS techniques i. The XANES region, characterized by relatively intense features, is sensitive to the P oxidation state and local environment of the P atom; i.

    The EXAFS region, the oscillating part of the XAS spectrum resulting from interference between the outgoing and backscattered electron waves, provides local information about P inter-atomic bond distances as well as coordination neighbors and numbers with the absorbing atom e. The experimental curves shown in Fig.

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    The first peak in the Fourier Transform Fig. In the case of soil P analyses, this is even more challenging as the ubiquitous presence of naturally occurring sulfur S can distort the P EXAFS spectra by superimposing spectral features originating from the S K - or L 2,3 -edges appearing only approx. Recently, Abdala et al. Abdala, personal communication. The principal advantage of these two XAS techniques is the recording of element specific spectra that reflect the weighted sum of the local bonding of all P atoms within a sample.

    For soil samples, however, this makes subsequent spectra evaluation complicated because of the vast number of different P species and, thus, P bonds and chemical environments. Therefore, various deconvolution approaches have been applied to extract qualitative and quantitative P data from spectra of samples with unknown P composition. All of these methods are based on spectra of known P o and P i reference compounds that are relevant to soil, and preferably recorded at the same beamline but sometimes also taken from the literature e.

    It is important to differentiate between the capability of XAS to distinguish between spectra of pure P o and P i references compounds and to quantify those compounds also in real mixtures in soil. Initial indications of major P compounds in a sample can be provided by visual comparisons between sample and various reference spectra for the presence or absence of distinctive spectral features such as a pre-edge peak for Fe-associated P see Fig.

    Mathematical deconvolution algorithms are commonly applied to determine the optimum combination of spectra of relevant P reference compounds for extracting quantitative information on individual P species. For spectral recording in FLY mode, it is important that the self-absorption effects are avoided by diluting the P standards in a P-free matrix e. Alternatively, the respective TEY spectra should be used; as discussed previously, unlike FLY spectra these are not affected by self-absorption. The most critical requirement for effective LCF analysis is the appropriate choice of a set of representative P reference compounds.

    Therefore, as well as visual inspection, the selection of P reference compounds should be based on all other available information relevant to the chemical nature of the sample Kelly et al. Additionally, statistical analyses such as principle component analysis PCA and adjacent target transformation TT also have been used to determine the selection of relevant P reference compounds for subsequent LCF analysis e.

    However, the majority of P XANES studies, even those not having used PCA or TT for selection, used not more than four reference compounds for LCF; this appears critical given that several combinations of reference compounds can yield similar fitting results.

    Since the obtained fitting models cannot provide a perfect representation, fitting results must always be cross-checked for their plausibility e.

    Systematic studies to directly validate and improve the precision and accuracy of XAS fitting results are urgently required, as performed for only simple binary mixtures by Ajiboye et al. For example, Eveborn et al. These approaches, however, have not yet been tested.

    Another new promising approach is to employ partial least squares regression PLSr models to deconvolute artificial mixtures of reference compounds; this would use artificially produced mathematical data sets for PLSr calibration of the XANES spectra Siebers et al. Based on promising results obtained with Cd compounds, these researchers adopted this approach to evaluate P K -edge XANES spectra of bone char amended soils, and showed for the first time the formation of a Cd-P-phase by solid-state speciation Siebers et al.

    Regardless of the method used to deconvolute P XAS spectra, the differentiation and detection of individual P species and, therefore, the specificity of XAS, strongly rely on the presence of unique features in the spectra of P reference compounds. This dependency explains the limited specificity of P K -edge XANES spectroscopy, since many soil relevant P species lack clearly distinctive spectral features e. This is not surprising, however, since the majority of P in soil involves P V in the PO 4 tetrahedra. As such, the direct chemical environment around the P atom varies only very slightly and, therefore, only relatively small spectral variations are observed among different soil P species.

    As a rule of thumb, Beauchemin et al. For instance, marked spectral features for Fe- and Al-associated P i have been used to distinguish between P sorption by Fe and Al minerals in artificial mixtures of ferrihydrite and boehmite Khare et al. Furthermore, peak assignment and spectral interpretation can be facilitated by molecular orbital calculations cf.

    Indeed, complementary methods, such as wet cemical analyses or 31 P NMR spectroscopy, clearly show that significant proportions of P o exist in such materials e. This, however, neglects the fact that various metal phytates e. Although still not investigated in detail, it is likely that phytic acid sorbed to Fe-, Al-, and Ca-minerals exhibit similar spectral variations e. Hence, this has to be taken into account during quantitative spectra evaluation in order to avoid misassignment and overestimation of P i associated with Fe, Al, and Ca, since phytic acid is mostly stabilized and accumulated in soils via sorption to Fe-, Al-, and Ca-minerals Celi and Barberies , Due to the inherent P o speciation difficulties, it is advisable to combine P K -edge XANES spectroscopy with complementary methods that are more sensitive to P o chemistry; e.

    The L 2,3 -edge spectra of various P o and P i reference compounds are characterized by more spectral features than the corresponding K -edge spectra Kruse et al. In summary, a full exploration of the far-reaching potential of X-ray absorption spectroscopy requires focused research in the following areas: improved methods for enriching P in the test samples; enhanced sensitivity of beamline endstations; circumvention of self-absorption problems, and of those arising from non-specific spectral features, and improved and validated data evaluation algorithms, including mathematical spectra deconvolution.

    X-ray photoelectron spectroscopy XPS , also termed electron spectroscopy for chemical analysis ESCA , is similarly based on the photoelectric effect as described above. However, in contrast to XAS, a monochromatic X-ray beam e. The obtained BE is characteristic for a given element e. Thus, XPS provides information on the element composition and ratio of the sample e. The oxidation state and variations in the P binding energy i.

    By deconvoluting the XPS spectra into sub-peaks using Gaussian—Lorentzian functions, peak areas of individual P species can be calculated and converted into proportions. This also allows the measurement of diluted samples due to the much higher brilliances of the X-ray source. Furthermore, the possibility of tuning the photon energy of the X-ray beam enables the collection of XPS spectra as a function of photon energy. This can be beneficial since selected P spectral features can be enhanced due to resonance effects if the scanned photon energy range covers an absorption edge of P e.

    Nonetheless, high resolution ResXPS may be a valuable tool for the deconvolution of P peaks at the valence band region, and may improve the understanding of the origin of complex spectral features in P containing compounds. It has to be noted that only electrons from the near surface can be captured by the detector due to the small penetration depth of the emitted photoelectron.

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