Heavy metal bioavailability and bioaccessibility in soil

This chapter considers the use of a variety of approaches to assess either the bioavailability or the bioaccessibility of metals in soil. The bioavailability of metals from soils is considered with respect to a series of single-extraction methods, including the use of ethylenediaminetetraacetic acid (EDTA), acetic acid, diethylenetriaminepentaacetic acid (DTPA), ammonium nitrate, calcium chloride and sodium nitrate. Then, a procedure for the recovery of metals using a three-stage sequential extraction protocol is described. Two alternate approaches for assessing the environmental health risk to humans by undertaking in vitro gastrointestinal extraction (also known as the physiologically based extraction test, PBET) are considered. Finally, two acid digestion protocols that allow the pseudo-total metal content of samples to be assessed are provided. In all cases details of how the different approaches can be performed are provided, including the specific reagents required (and their preparation), details of the different extraction and acid digestion protocols to be followed and suitable analytical details to allow the measurement of metals by inductively coupled plasma mass spectrometry (ICP-MS) with/without a collision/reaction cell. A detailed Notes section provides experimental details to guide the reader through some of the practical aspects of the procedures. Finally, some experimental results are provided as evidence of the suitability of the approaches described including single-extraction data, using EDTA and acetic acid, for metals in CRM BCR 700. In addition, in vitro gastrointestinal extraction data are provided for metals in CRM SRM 1570A (spinach leaves). The influence of time on the intestinal fluid phase on the recovery of metals in CRM SRM 1570A (spinach leaves) and CRM INCT-TL-1 (tea leaves) is investigated, as well as the repeatability in terms of recovery of metals from soil over a 3-week period by in vitro gastrointestinal extraction

Towards a nanospecific approach for risk assessment.

In the current paper, a new strategy for risk assessment of nanomaterials is described, which builds upon previous project outcomes and is developed within the FP7 NANoREG project. NANoREG has the aim to develop, for the long term, new testing strategies adapted to a high number of nanomaterials where many factors can affect their environmental and health impact. In the proposed risk assessment strategy, approaches for (Quantitative) Structure Activity Relationships ((Q)SARs), grouping and read-across are integrated and expanded to guide the user how to prioritise those nanomaterial applications that may lead to high risks for human health. Furthermore, those aspects of exposure, kinetics and hazard assessment that are most likely to be influenced by the nanospecific properties of the material under assessment are identified. These aspects are summarised in six elements, which play a key role in the strategy: exposure potential, dissolution, nanomaterial transformation, accumulation, genotoxicity and immunotoxicity. With the current approach it is possible to identify those situations where the use of nanospecific grouping, read-across and (Q)SAR tools is likely to become feasible in the future, and to point towards the generation of the type of data that is needed for scientific justification, which may lead to regulatory acceptance of nanospecific applications of these tools.The research leading to these results has been partially funded by the European Union Seventh Framework Programme (FP7/ 2007e2013) under the project NANoREG (A common European approach to the regulatory testing of nanomaterials), grant agreement 310584.info:eu-repo/semantics/publishedVersio

A new perceptual model for audio coding based on spectro-temporal masking

In psychoacoustics, considerable advances have been made recently in developing computational models that can predict the discriminability of two sounds taking into account spectro-temporal masking effects. These models operate as artificial observers by making predictions about the discriminability of arbitrary signals [e.g. Dau et al. J. Acoust. Soc. Am. 99, Vol. 36(15), 1996]. Therefore, such models can be applied in the context of a perceptual audio coder. A drawback, however, is the computational complexity of such advanced models, especially because the model needs to evaluate each quantization option separately. In this contribution a model is introduced and evaluated that is a computationally lighter version of the Dau model but maintains its essential spectro-temporal masking predictions. Listening test results in a transform coder setting show that the proposed model outperforms a conventional purely spectral masking model and the original model proposed by Dau

Knowledge gaps in risk assessment of nanosilica in food: evaluation of the dissolution and toxicity of different forms of silica

This manuscript describes the follow-up study of our previous publication on the presence and risks of nanosilica in food. New information on the presence of nanosilica in the gastrointestinal tract is evaluated and information on nanosilica and synthetic amorphous silica (SAS) is compared to assess its relevance for risk assessment of nanosilica in food. Irrespective of whether SAS should be regarded as a nanomaterial or a non-nanoform of silica, a comparison to nanosilica is relevant to determine whether there are differences in physicochemical properties, which may lead to differences in toxicity. Based on this comparison, knowledge gaps are identified and recommendations for a targeted approach to facilitate risk assessment of nanosilica in food are given. Considering the discussion to which extent nanomaterials with (slightly) different physicochemical characteristics can be grouped for risk assessment - the sameness issue - actual exercises as presented in this manuscript are highly relevant for bringing this discussion forward

Fast and Accurate Identification of Thermal Dynamics for Precision Motion Control: Exploiting Transient Data and Additional Disturbance Inputs

Thermally induced deformations are becoming increasingly important for the control performance of precision motion systems. The aim of this paper is to identify the underlying thermal dynamics in view of precision motion control. Identifying thermal systems is challenging due to strong transients, large time constants, excitation signal limitations, large environmental disturbances, and temperature dependent behavior. An approach for non-parametric identification is developed that is particularly suitable for thermal aspects in mechatronic systems. In particular 1) reduced experiment time is achieved by utilizing transient data in the identification procedure. 2) an approach is presented that exploits measured ambient air temperature fluctuations as additional inputs to the identification setup. 3) the non-parametric model, obtained through 1) and 2), is used as a basis for parameter estimation of a grey-box parametric model. The presented methods form a complete framework that facilitates the implementation of advanced control techniques and error compensation strategies by providing high-fidelity models, enabling increased accuracy and throughput in high precision motion control

Characterization of Titanium Dioxide Nanoparticles in Food Products: Analytical Methods To Define Nanoparticles

Titanium dioxide (TiO2) is a common food additive used to enhance the white color, brightness, and sometimes flavor of a variety of food products. In this study 7 food grade TiO2 materials (E171), 24 food products, and 3 personal care products were investigated for their TiO2 content and the number-based size distribution of TiO2 particles present in these products. Three principally different methods have been used to determine the number-based size distribution of TiO2 particles: electron microscopy, asymmetric flow field-flow fractionation combined with inductively coupled mass spectrometry, and single-particle inductively coupled mass spectrometry. The results show that all E171 materials have similar size distributions with primary particle sizes in the range of 60–300 nm. Depending on the analytical method used, 10–15% of the particles in these materials had sizes below 100 nm. In 24 of the 27 foods and personal care products detectable amounts of titanium were found ranging from 0.02 to 9.0 mg TiO2/g product. The number-based size distributions for TiO2 particles in the food and personal care products showed that 5–10% of the particles in these products had sizes below 100 nm, comparable to that found in the E171 materials. Comparable size distributions were found using the three principally different analytical methods. Although the applied methods are considered state of the art, they showed practical size limits for TiO2 particles in the range of 20–50 nm, which may introduce a significant bias in the size distribution because particle