Abstract: The growing concern for the increase of the global warming effects due to anthropogenic activities raises the challenge of finding novel technological approaches to stabilize CO2 emissions in the atmosphere and counteract impinging interconnected issues such as desertification and loss of biodiversity. Biological-CO2 mitigation, triggered through biological fixation, is considered a promising and eco-sustainable method, mostly owing to its downstream benefits that can be exploited. Microorganisms such as cyanobacteria, green algae and some autotrophic bacteria could potentially fix CO2 more efficiently than higher plants, due to their faster growth. Some examples of the potential of biological-CO2 mitigation are reported and discussed in this paper. In arid and semiarid environments, soil carbon sequestration (CO2 fixation) by cyanobacteria and biological soil crusts is considered an eco-friendly and natural process to increase soil C content and a viable pathway to soil restoration after one disturbance event. Another way for biological-CO2 mitigation intensively studied in the last few years is related to the possibility to perform carbon dioxide sequestration using microalgae, obtaining at the same time bioproducts of industrial interest. Another possibility under study is the exploitation of specific chemotrophic bacteria, such as Ralstonia eutropha (or picketii) and related organisms, for CO2 fixation coupled with the production chemicals such as polyhydroxyalkanoates (PHAs). In spite of the potential of these processes, multiple factors still have to be optimized for maximum rate of CO2 fixation by these microorganisms. The optimization of culture conditions, including the optimal concentration of CO2 in the provided gas, the use of metabolic engineering and of dual purpose systems for the treatment of wastewater and production of biofuels and high value products within a biorefinery concept, the design of photobioreactors in the case of phototrophs are some of the issues that, among others, have to be addressed and tested for cost-effective CO2 sequestration.

Abstract: The selection and identification of a suitable hydrological model structure is a more challenging task than fitting parameters of a fixed model structure to reproduce a measured hydrograph. The suitable model structure is highly dependent on various criteria, i.e. the modeling objective, the characteristics and the scale of the system under investigation and the available data. Flexible environments for model building are available, but need to be assisted by proper diagnostic tools for model structure selection. This paper introduces a qualitative method for model component sensitivity analysis. Traditionally, model sensitivity is evaluated for model parameters. In this paper, the concept is translated into an evaluation of model structure sensitivity. Similarly to the one-factor-at-a-time (OAT) methods for parameter sensitivity, this method varies the model structure components one at a time and evaluates the change in sensitivity towards the output variables. As such, the effect of model component variations can be evaluated towards different objective functions or output variables. The methodology is presented for a simple lumped hydrological model environment, introducing different possible model building variations. By comparing the effect of changes in model structure for different model objectives, model selection can be better evaluated. Based on the presented component sensitivity analysis of a case study, some suggestions with regard to model selection are formulated for the system under study: (1) a non-linear storage component is recommended, since it ensures more sensitive (identifiable) parameters for this component and less parameter interaction; (2) interflow is mainly important for the low flow criteria; (3) excess infiltration process is most influencing when focussing on the lower flows; (4) a more simple routing component is advisable; and (5) baseflow parameters have in general low sensitivity values, except for the low flow criteria. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: The photocatalytic oxidation of carbon black on TiO2 using nitric oxide as an oxidizing agent was investigated. Layer-wise deposited carbon and TiO2 powder was illuminated with UVA light in the presence of NO at parts per million concentrations in dry and hydrated carrier gas at a temperature of 150 degrees C. Carbon was photocatalytically converted mainly into CO2, and NO mainly into N-2. Carbon oxidation rates of 7.2 mu g/h/mgTiO(2) were achieved in the presence of 3000 ppm NO. Under these experimental conditions in the absence of molecular oxygen, formation of surface nitrates causing TiO2 photocatalyst deactivation is suppressed. Addition of water enhances surface nitrate formation and catalyst deactivation. NO and carbon particulate matter are air pollutants emitted by diesel engines. Elimination of soot collected on a diesel particulate filter through oxidation is a demanding reaction requiring temperatures in excess of 250 degrees C. The present study opens perspectives for a low-temperature regeneration strategy for the diesel particulate filter that simultaneously performs DeNO(x) reactions. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: Red lead, a semiconductor pigment used by artists since antiquity, is known to undergo several discoloration phenomena. These transformations are either described as darkening of the pigment caused by the formation of either plattnerite (β-PbO2) or galena (PbS) or as whitening by which red lead is converted into anglesite (PbSO4) or (hydro)cerussite (2 PbCO3⋅Pb(OH)2; PbCO3). X-ray powder diffraction tomography, a powerful analytical method that allows visualization of the internal distribution of different crystalline compounds in complex samples, was used to investigate a microscopic paint sample from a Van Gogh painting. A very rare lead mineral, plumbonacrite (3 PbCO3⋅ Pb(OH)2⋅PbO), was revealed to be present. This is the first reported occurrence of this compound in a painting dating from before the mid 20th century. It constitutes the missing link between on the one hand the photoinduced reduction of red lead and on the other hand (hydro)cerussite, and thus sheds new light on the whitening of red lead.

Abstract: The development of advanced methods for non-destructive selective imaging of painted works of art at the macroscopic level based on radiation in the X-ray and infrared range of the electromagnetic spectrum are concisely reviewed. Such methods allow to either record depth-selective, element-selective or species-selective images of entire paintings. Camera-based full field methods (that record the image data in parallel) can be discerned next to scanning methods (that build up distributions in a sequential manner by scanning a beam of radiation over the surface of an artefact). Six methods are discussed: on the one hand, macroscopic X-ray fluorescence and X-ray diffraction imaging and X-ray laminography and on the other hand macroscopic Mid and Near Infrared hyper- and full spectral imaging and Optical Coherence Tomography. These methods can be considered to be improved versions of the well-established imaging methods employed worldwide for examination of paintings, i.e., X-ray radiography and Infrared reflectography. Possibilities and limitations of these new imaging techniques are outlined.

Abstract: In this study a numerical groundwater reactive transport model of a shallow groundwater aquifer contaminated with volatile organic compounds is developed. In addition to advective-dispersive transport, the model includes contaminant release from source areas, natural attenuation, abiotic degradation by a permeable reactive barrier at the site, and dilution by infiltrating rain. Aquifer heterogeneity is parameterized using pilot points for hydraulic conductivity, specific yield and groundwater recharge. A methodology is developed and applied to estimate the large number of parameters from the limited data at the field site (groundwater levels, groundwater concentrations of multiple chemical species, point-scale measurements of soil hydraulic conductivity, and lab-scale derived information on chemical and biochemical reactions). The proposed methodology relies on pilot point parameterization of hydraulic parameters and groundwater recharge, a regularization procedure to reconcile the large number of spatially distributed model parameters with the limited field data, a step-wise approach for integrating the different data sets into the model, and high performance computing. The methodology was proven to be effective in reproducing multiple contaminant plumes and in reducing the prior parameter uncertainty of hydraulic conductivity and groundwater recharge. Our results further indicate that contaminant transport predictions are strongly affected by the choice of the groundwater recharge model and flow parameters should be identified using both head and concentration measurements. (C) 2014 Elsevier B.V. All rights reserved.

Abstract: The fate of iron (Fe) may affect that of phosphorus (P) and arsenic (As) in natural waters. This study addresses the removal of Fe, P, and As from streams in lowland catchments fed by reduced, Fe-rich groundwater (average: 20 mg Fe L-1). The concentrations of dissolved Fe (<0.45 mu m) in streams gradually decrease with increasing hydraulic residence time (travel time) of the water in the catchment. The removal of Fe from streamwater is governed by chemical reactions and hydrological processes: the oxidation of ferrous iron (Fe(II)) and the subsequent formation of particulate Fe oxyhydroxides proceeds as the water flows through the catchment into increasingly larger streams. The Fe removal exhibits first-order kinetics with a mean half-life of 12 h, a value in line with predictions by a kinetic model for Fe(II) oxidation. The Fe concentrations in streams vary seasonally: they are higher in winter than in summer, due to shorter hydraulic residence time and lower temperature in winter. The removal of P and As is much faster than that of Fe. The average concentrations of P and As in streams (42 mu g P L-1) and 1.4 mu g As L-1) are 1 order of magnitude below those in groundwater (393 mu g P L-1 and 17 mu g As L-1). This removal is attributed to fast sequestration by oxidizing Fe when the water enters oxic environments, possibly by adsorption on Fe oxyhydroxides or by formation of ferric phosphates. The average P and As concentrations in groundwater largely exceed local environmental limits for freshwater (140 mu g P L-1 and 3 mu g As L((-1)), but in streams, they are below these limits. Naturally occurring Fe in groundwater may alleviate the environmental risk associated with P and As in the receiving streams.

Abstract: A combination of synchrotron radiation (SR) micro X-ray fluorescence (m-XRF) and XRF mode X-ray absorption near edge structure (XANES) measurements at the Cr K-edge already allowed us to establish that the photo-reduction of chromates to Cr(III) compounds is the cause of darkening of chrome yellow pigments (PbCr1-xSxO4, 0 <= x <= 0.8) in a number of paintings by Vincent van Gogh and in corresponding artificially aged paint models. A silicon drift detector (SDD) was employed to record the Cr-K XRF radiation in these X-ray micro beam-based measurements. However, in view of the limited count rate capabilities and collection solid angle of a single device, m-XRF and m-XANES employing single element SDDs (or similar) are primarily suited for collection of spectral data from individual points. Additionally, collection of XRF maps via point-by-point scanning with relatively long dwell times per point is possible but is usually confined to small areas. The development of the 384 silicon-diode array Maia XRF detector has provided valuable solutions in terms of data acquisition rate, allowing for full spectral (FS) XANES imaging in XRF mode, i.e., where spectroscopic information is available at each pixel in the scanned map. In this paper, the possibilities of SR Cr K-edge FS-XANES imaging in XRF mode using the Maia detector are examined as a new data collection strategy to study the speciation and distribution of alteration products of lead chromate-based pigments in painting materials. The results collected from two micro-samples taken from two Van Gogh paintings and an aged paint model show the possibility to perform FS-XANES imaging in practical time frames (from several minutes to a few hours) by scanning regions of sample sizes of the same order (more than 500 mm). The sensitivity and capabilities of FS-XANES imaging in providing representative chemical speciation information at the microscale (spatial resolution from similar to 2 to 0.6 mm) over the entire scanned area are demonstrated by the identification of Cr(OH) 3, Cr(III) sulfates and/or Cr(III) organometallic compounds in the corresponding phase maps, as alteration products. Comparable Cr-speciation results were obtained by performing equivalent higher spatial resolution SR m-XRF/single-point m-XANES analysis using a more conventional SDD from smaller regions of interest of each sample. Thus, large-area XRF mode FS-XANES imaging (Maia detector) is here proposed as a valuable and complementary data collection strategy in relation to “ zoomed-in” high-resolution m-XRF mapping and single-point m-XANES analysis (SDD).

Abstract: Technical progress in the fields of X-ray sources, optics and detectors is constantly enhancing the pace of data acquisition in XRF imaging. This enlarges the size of the hyperspectral datasets and the number of their sub-parts. This paper describes the challenges in processing large XRF datasets featuring several million pixels/spectra and the strategies developed to overcome them. During the investigation of historical paintings by scanning macro-XRF the main challenges are the correct identification of all spectral features in a dataset and its timely processing. For the identification of spectral features different approaches are discussed, i.e. the use of sum spectra, maximum pixel spectra and of chi(2)(r) maps. For the time-efficient, artefact-free evaluation of XRF imaging data, different software packages are evaluated and intercompared (AXIL, PyMCA, GeoPIXE and the in-house written datamuncher). The process of data evaluation is illustrated on a large dataset (3.4 MPixels) acquired during the investigation of a version of Caravaggio's Supper at Emmaus (143 x 199.5 cm(2)). This 17th century painting is currently the largest object entirely scanned with macroscopic XRF.

Abstract: The presence of residues from frequent antibiotic use in animal feed can cause serious health risks by contaminating products for human consumption such as meat and milk. The present article gives an overview of the electrochemical methods developed for the detection of phenicol antibiotic residues (chloramphenicol, thiamphenicol, and florfenicol) in different kinds of foodstuffs. Electrochemical sensors based on different biomolecules and nanomaterials are described. The detection limit of various developed methods with their advantages and disadvantage will be highlighted.