Uncertainties of size measurements in electron microscopy characterization of nanomaterials in foods

Electron microscopy is a recognized standard tool for nanomaterial characterization, and recommended by the European Food Safety Authority for the size measurement of nanomaterials in food. Despite this, little data have been published assessing the reliability of the method, especially for size measurement of nanomaterials characterized by a broad size distribution and/or added to food matrices. This study is a thorough investigation of the measurement uncertainty when applying electron microscopy for size measurement of engineered nanomaterials in foods. Our results show that the number of measured particles was only a minor source of measurement uncertainty for nanomaterials in food, compared to the combined influence of sampling, sample preparation prior to imaging and the image analysis. The main conclusion is that to improve the measurement reliability, care should be taken to consider replications and matrix removal prior to sample preparation

Self-Organizing Maps For Knowledge Discovery From Corporate Databases To Develop Risk Based Prioritization For Stagnation 

Stagnation or low turnover of water within water distribution systems may result in water quality issues, even for relatively short durations of stagnation / low turnover if other factors such as deteriorated aging pipe infrastructure are present. As leakage management strategies, including the creation of smaller pressure management zones, are implemented increasingly more dead ends are being created within networks and hence potentially there is an increasing risk to water quality due to stagnation / low turnover. This paper presents results of applying data driven tools to the large corporate databases maintained by UK water companies. These databases include multiple information sources such as asset data, regulatory water quality sampling, customer complaints etc. A range of techniques exist for exploring the interrelationships between various types of variables, with a number of studies successfully using Artificial Neural Networks (ANNs) to probe complex data sets. Self Organising Maps (SOMs), are a class of unsupervised ANN that perform dimensionality reduction of the feature space to yield topologically ordered maps, have been used successfully for similar problems to that posed here. Notably for this application, SOM are trained without classes attached in an unsupervised fashion. Training combines competitive learning (learning the position of a data cloud) and co-operative learning (self-organising of neighbourhoods). Specifically, in this application SOMs performed multidimensional data analysis of a case study area (covering a town for an eight year period). The visual output of the SOM analysis provides a rapid and intuitive means of examining covariance between variables and exploring hypotheses for increased understanding. For example, water age (time from system entry, from hydraulic modelling) in combination with high pipe specific residence time and old cast iron pipe were found to be strong explanatory variables. This derived understanding could ultimately be captured in a tool providing risk based prioritisation scores

Energy and Utilities Infrastructure: Can All be in One?

In today‘s developed society it is fully expected that every household is provided with general utility products such as heating, lighting, water supply, communication, and waste removal. Provision of these utility products requires large and complex physical, economic and social structures that interact and are interdependent. Furthermore, we underline that each distinct utility product (communication, transportation, water, etc.) provided to our households incurs similar material and embodied energy expenses. But are such structures and their respective expenses really necessary? Or could energy (and other resources) be saved by reducing redundant utility infrastructures, while still maintaining services to the households? Conventional approaches to improved utility provision focus on better management models with optimization, enhanced handling, and increased efficiency in organisations. This paper, on the other hand, presents a novel and radical idea to address this complex problem, by moving from the management level to the scientific & technological level. The paper challenges the need for distinct utility infrastructures for household utility products provision. In particular, the paper discusses the emerging scientific and technological options for using a single energy-provision infrastructure, which would potentially deliver the full set of household utility services

Recovery of metals from waste lithium ion battery leachates using biogenic hydrogen sulfide

Lithium ion battery (LIB) waste is increasing globally and contains an abundance of valuable metals that can be recovered for re-use. This study aimed to evaluate the recovery of metals from LIB waste leachate using hydrogen sulfide generated by a consortium of sulfate-reducing bacteria (SRB) in a lactate-fed fluidised bed reactor (FBR). The microbial community analysis showed Desulfovibrio as the most abundant genus in a dynamic and diverse bioreactor consortium. During periods of biogenic hydrogen sulfide production, the average dissolved sulfide concentration was 507 mg L−1 and the average volumetric sulfate reduction rate was 278 mg L−1 d−1. Over 99% precipitation efficiency was achieved for Al, Ni, Co, and Cu using biogenic sulfide and NaOH, accounting for 96% of the metal value contained in the LIB waste leachate. The purity indices of the precipitates were highest for Co, being above 0.7 for the precipitate at pH 10. However, the process was not selective for individual metals due to simultaneous precipitation and the complexity of the metal content of the LIB waste. Overall, the process facilitated the production of high value mixed metal precipitates, which could be purified further or used as feedstock for other processes, such as the production of steel

Fur : A non-invasive approach to monitor metal exposure in bats

This paper presents a novel assessment of the use of fur as a non-invasive proxy to biomonitor metal contamination in insectivorous bats. Concentrations of metals (cadmium, copper, lead and zinc) were measured using ICP-MS in tissues (kidneys, liver, stomach and stomach content, bones and fur) obtained from 193 Pipistrellus pipistrellus/pygmaeus bats. The bats were collected across a gradient of metal pollution in England and Wales. The utility of small samples of fur as an indicator of metal exposure from the environment was demonstrated with strong relationships obtained between the concentrations of non-essential metals in fur with concentrations in stomach content, kidneys, liver and bones. Stronger relationships were observed for non-essential metals than for essential metals. Fur analyses might therefore be a useful non-invasive proxy for understanding recent, as well as long term and chronic, metal exposure of live animals. The use of fur may provide valuable information on the level of endogenous metal exposure and contamination of bat populations and communities

Modelling both the continual erosion and regeneration of discolouration material in drinking water distribution systems

The erosion of the cohesive layers of particulate matter that causes discolouration in water distribution system mains has previously been modelled using the Prediction of Discolouration in Distribution Systems (PODDS) model. When first proposed, PODDS featured an unvalidated means by which material regeneration on pipe walls could be simulated. Field and laboratory studies of material regeneration have yielded data that suggest that the PODDS formulations incorrectly model these processes. A new model is proposed to overcome this shortcoming. It tracks the relative amount of discolouration material that is bound to the pipe wall over time at each of a number of shear strengths. The model formulations and a mass transport model have been encoded as software, which has been used to verify the model’s constructs and undertake sensitivity analyses. The new formulations for regeneration are conceptually consistent with field and laboratory observed data and has potential value in the proactive management of water distribution systems, such as evaluating change in discolouration risk and planning timely interventions

Evaluation and development of models for estimating the sorption behaviour of pharmaceuticals in soils

Sorption is one of the key process that affects the fate and mobility of pharmaceuticals in the soil environment. Several models have been developed for estimating the sorption of organic chemicals, including ionisable compounds, in soil. However, the applicability of these models to pharmaceuticals has not been extensively tested. In this study, we generated a high-quality dataset on the sorption of twenty-one pharmaceuticals in different soil types and used these data to evaluate existing models and to develop new improved models. Sorption coefficients (Kd) of the pharmaceuticals ranged from 0.2 to 1249.2 L/kg. Existing models were unable to adequately estimate the measured sorption data. Using the data, new models were developed, incorporating molecular and soil descriptors, that outperformed the published models when evaluated against external data sets. While there is a need for further evaluation of these new models against broader sorption datasets obtained at environmentally relevant concentrations, in the future they could be highly useful in supporting environmental risk assessment and prioritization efforts for pharmaceutical ingredients

Balancing employee needs, project requirements and organisational priorities in team deployment

The 'people and performance' model asserts that performance is a sum of employee ability, motivation and opportunity (AMO). Despite extensive evidence of this people-performance link within manufacturing and many service sectors, studies within the construction industry are limited. Thus, a recent research project set out to explore the team deployment strategies of a large construction company with the view of establishing how a balance could be achieved between organisational strategic priorities, operational project requirements and individual employee needs and preferences. The findings suggested that project priorities often took precedence over the delivery of the strategic intentions of the organisation in meeting employees' individual needs. This approach is not sustainable in the long term because of the negative implications that such a policy had in relation to employee stress and staff turnover. It is suggested that a resourcing structure that takes into account the multiple facets of AMO may provide a more effective approach for balancing organisational strategic priorities, operational project requirements and individual employee needs and preferences more appropriately in the future