Abstract: Particulate matter with an aerodynamic diameter below 2.5 μm (PM2.5), present in polluted air, has been associated with a large spectrum of health impairments, mainly because of its deep deposition into the lungs. Araraquara City (Southeast Brazil) is surrounded by sugar-cane plantations, which are burned to facilitate the harvesting; this process causes environmental pollution due to the large amounts of soot that are released into the atmosphere. In this work, the elemental composition of PM2.5 was studied in two scenarios, namely in sugar-cane harvesting (HV) and in non-harvesting (NHV) seasons. The sampling strategy included one campaign in each season. PM2.5 was collected using a dichotomous sampler (10 L·min-1, 24 h) with PTFE filters. Information concerning the bulk elemental concentration was provided by energy-dispersive X-ray fluorescence. Enrichment factor analysis indicated that S, Cl, K, Cr, Ni, Cu, Zn, As, Cd and Pb were highly enriched relative to their crustal ratios (to Al). Principal component analysis was used to get some insight about the sources of the elements. Principal component 1 (PC1) explained 30.5% of data variance. The elements that had high loading (>0.7) were: S, Cr, As, and Pb; these are associated with combustion of fossil fuels. In principal component 2 (PC2), Cl, Cu, Zn, and Cd showed high loadings; these elements are associated with biomass burning. The Ni concentration found is three times larger than the threshold of risk for lung cancer, as recommended by the World Health Organization.

Abstract: The radiation damage, in terms of atom displacements, induced by gamma irradiation in LYSO and LuYAP crystals is presented. Sc-44, Na-22 and V-48 are used as gamma sources for this study. The energy of gammas from the electron positron annihilation processes (511 keV) is also included in the study. The atom displacements distributions inside each material are calculated following the Monte Carlo assisted Classical Method introduced by the authors. This procedure also allows to study the atom displacements in-depth distributions inside each crystal. The atom displacements damage in LYSO crystals is found to be higher than in LuYAP crystals, mainly provoked by the displacements of silicon and oxygen atoms. But the difference between atom displacements produced in LYSO and LuYAP decreases when more energetic sources are used. On the other hand, the correlation between the atom displacements and energy deposition in-depth distributions is excellent. The atom displacements to energy deposition ratio is found to increases with more energetic photon sources. LYSO crystals are then more liable to the atom displacements damage than LuYAP crystals. (C) 2015 Elsevier B.V. All rights reserved.

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 analytical methods which are often used for the determination of cocaine in complex biological matrices are a prescreening immunoassay and confirmation by chromatography combined with mass spectrometry. We suggest an ultra-high-pressure liquid chromatography combined with a potentiometric detector, as a fast and practical method to detect and quantify cocaine in biological samples. An adsorption/desorption model was used to investigate the usefulness of the potentiometric detector to determine cocaine in complex matrices. Detection limits of 6.3ngmL(-1) were obtained in plasma and urine, which is below the maximum residue limit (MRL) of 25ngmL(-1). A set of seven plasma samples and 10 urine samples were classified identically by both methods as exceeding the MRL or being inferior to it. The results obtained with the UPLC/potentiometric detection method were compared with the results obtained with the UPLC/MS method for samples spiked with varying cocaine concentrations. The intraclass correlation coefficient was 0.997 for serum (n =7) and 0.977 for urine (n =8). As liquid chromatography is an established technique, and as potentiometry is very simple and cost-effective in terms of equipment, we believe that this method is potentially easy, inexpensive, fast and reliable. Copyright (c) 2014 John Wiley & Sons, Ltd.

Abstract: Selective chromium (Cr) leaching from stainless steel slag (SS slag) by alkali roasting followed by water leaching was investigated. The efficiency of the alkali roasting process for Cr leaching was increased by optimizing the mass ratio of alkaline agents (NaOH, and NaOH-NaNO3) to the slag, roasting temperature and time. At the optimum condition (0.67 mass ratio of NaOH to SS slag, 400 degrees C, 2 h) of NaOH roasting, chromium leaching was around 83%, while the matrix material was dissolved only to a limited extent (Si 8.0%). Mechanical activation of the SS slag prior to roasting reduced the optimum NaOH to SS slag mass ratio to 0.4. The addition of NaNO3 as an oxidant to the NaOH salt increased Cr leaching to 89% after roasting at 400 degrees C for 2 h. The remaining Cr phases in the residue were almost exclusively FeCr alloys. Further chromium dissolution from these alloys is prevented by a passivation layer of Fe oxides as shown by SEM/EDS images. Based on these results, a SS slag recycling process is suggested in which roasting-water leaching followed by water washing to remove Cr yields a residue which has potential for application as a construction material. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: In environmental assessments, the characterization of urban soils relies heavily on invasive investigation, which is often insufficient to capture their full spatial heterogeneity. Non-invasive geophysical techniques enable rapid collection of high-resolution data and provide a cost-effective alternative to investigate soil in a spatially comprehensive way. This paper presents the results of combining multi-receiver electromagnetic induction and stepped-frequency ground penetrating radar to characterize a former garage site contaminated with petroleum hydrocarbons. The sensor combination showed the ability to identify and accurately locate building remains and a high-density soil layer, thus demonstrating the high potential to investigate anthropogenic disturbances of physical nature. In addition, a correspondence was found between an area of lower electrical conductivity and elevated concentrations of petroleum hydrocarbons, suggesting the potential to detect specific chemical disturbances. We conclude that the sensor combination provides valuable information for preliminary assessment of urban soils.

Abstract: Sustainable Materials Management (SMM) strategies, such as reuse, recycling and energy recovery aim, to capture more of the embedded resource or material value in products and waste streams. Reuse, recycling and energy recovery are existing activities in every society but they are poorly reflected in official statistics. Reaching higher levels of reuse, recycling and energy recovery may provide economic and environmental opportunities (i.e., in terms of GDP, jobs, reduced impacts), but not all options will have a net win-win-win property in practice, as they reduce the need for producing new commodities. In open economies, many primary resources, components and products are imported from abroad, and many goods produced are exported abroad. This paper describes a top-down methodology for estimating the substitution potential of intensifying specific SMM-strategies and material efficiency strategies. We combined both regional and multi-regional EE-IO (environmentally extended input-output) models to link industrial sectors to SMM-strategies. Our method enables us to compare the different SMM and material efficiency strategies in terms of the maximum available budgets for reaching them on a break even basis, maximum savings in global warming emissions and substituted employment effects, both through a regional and global perspective. We add a case on Flanders (Northern region in Belgium) to illustrate the methodology. Flanders is currently developing a policy for SMM. Selecting new regional actions for a Sustainable Materials Management policy can benefit from a good understanding of the international entangled value chains. It is important to understand how much of the chain is within reach of domestic policies and also to assess the consequences in terms of potential winners and losers, regarding GDP, jobs and environmental impacts, both domestically and abroad. We illustrated the potential outcomes for Flanders from four generic SMM-strategies: energy recovery, food waste prevention, recycling and reuse. From a strict regional self-interest perspective, it is preferable to substitute foreign value chains with local economic activities. Reuse creates by far the largest budget for new activities to realize the strategy (31.2% of Flemish GDP compared to 8.3% for food waste prevention, 6.2% for energy recovery and 4.2% for recycling). All four strategies have similar and significant potentials to reduce greenhouse gas emissions. However, food waste prevention and reuse have higher potentials to reduce Flemish territorial GHG-emissions. From a pure Flemish employment perspective, the energy recovery and recycling strategies could replace the fewest Flemish jobs, and from a global perspective, all strategies most likely imply losses of jobs abroad. (C) 2015 Elsevier B.V. All rights reserved.

Abstract: Quantitative atomic resolution annular dark field scanning transmission electron microscopy (ADF STEM) has become a powerful technique for nanoparticle atom-counting. However, a lot of nanoparticles provide a severe characterisation challenge because of their limited size and beam sensitivity. Therefore, quantitative ADF STEM may greatly benefit from statistical detection theory in order to optimise the instrumental microscope settings such that the incoming electron dose can be kept as low as possible whilst still retaining single-atom precision. The principles of detection theory are used to quantify the probability of error for atom-counting. This enables us to decide between different image performance measures and to optimise the experimental detector settings for atom-counting in ADF STEM in an objective manner. To demonstrate this, ADF STEM imaging of an industrial catalyst has been conducted using the near-optimal detector settings. For this experiment, we discussed the limits for atom-counting diagnosed by combining a thorough statistical method and detailed image simulations.