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Titanium dioxide nanoparticles (TiO2 NPs) are widely used in a variety of consumer products. Cellular exposure to TiO2 NPs results in complex effects on cell physiology that could impact biological systems. We investigated the behavior of Listeria monocytogenes in intestinal epithelial cells pre-treated with either a low or high (1 and 20 µg/cm2) dose of TiO2 NPs. Our results indicate that the pre-treated cells with a low dose became more permissive to listeria infection; indeed, both adhesion and invasion were significantly increased compared to control. Increased invasion seems to be correlated to cytoskeletal alterations induced by nanoparticles, and higher bacterial survival might be due to the high levels of listeriolysin O that protects L. monocytogenes from reactive oxygen species (ROS). The potential risk of increased susceptibility to L. monocytogenes infection related to long-term intake of nanosized TiO2 at low doses should be considered.

The alkali-activation method allows for obtaining highly porous carbon materials. In this study, we explored the effect of activation temperature and potassium hydroxide concentration on the pore structure of reduced graphene oxide (rGO), as potential membrane material. Above 700 °C, potassium species react with the carbon plane of rGO to form nanopores. This activation process is deeply studied through DSC measurements and isothermal gravimetric analysis. The porosity of the formed materials consists of both micro- and mesopores, with most of the pores having a size smaller than 10 nm. The specific surface area and pore volume increase with increasing the potassium hydroxide/graphene oxide weight ratio (KOH/GO) up to 7 (897 m2∙g−1 and 0.97 cm3∙g−1, respectively). However, for a synthesis mixture with KOH/GO of 10, the specific surface area of the produced material drops to 255 m2∙g−1. The film-forming ability of the porous reduced graphene oxide (PRGO) was tested by drop-casting on porous silicon carbide substrates. In this case, continuous PRGO films were obtained only from dispersions with 5 g∙L−1 GO loading and KOH/GO ≤3. Such films can still have high specific surface area and pore volume (up to 528 m2∙g−1 and 0.53 cm3∙g−1) and main pore volume

Online coupled mesoscale meteorology atmospheric chemistry models have undergone a rapid evolution in recent years. Although mainly developed by the air quality modelling community, these models are also of interest for numerical weather prediction and regional climate modelling as they can consider not only the effects of meteorology on air quality, but also the potentially important effects of atmospheric composition on weather. Two ways of online coupling can be distinguished: online integrated and online access coupling. Online integrated models simulate meteorology and chemistry over the same grid in one model using one main time step for integration. Online access models use independent meteorology and chemistry modules that might even have different grids, but exchange meteorology and chemistry data on a regular and frequent basis. This article offers a comprehensive review of the current research status of online coupled meteorology and atmospheric chemistry modelling within Europe. Eighteen regional online coupled models developed or being used in Europe are described and compared. Topics discussed include a survey of processes relevant to the interactions between atmospheric physics, dynamics and composition; a brief overview of existing online mesoscale models and European model developments; an analysis on how feedback processes are treated in these models; numerical issues associated with coupled models; and several case studies and model performance evaluation methods. Finally, this article highlights selected scientific issues and emerging challenges that require proper consideration to improve the reliability and usability of these models for the three scientific communities: air quality, numerical meteorology modelling (including weather prediction) and climate modelling. This review will be of particular interest to model developers and users in all three fields as it presents a synthesis of scientific progress and provides recommendations for future research directions and priorities in the development, application and evaluation of online coupled models.

In this work, new nanohybrids based on superparamagnetic iron oxide nanoparticles (SPIONs) were elaborated and discussed for the first time as nanovectors of a derivative molecule of trans-resveratrol (RSV), a natural antioxidant molecule, which can be useful for brain disease treatment. The derivative molecule was chemically synthesized (4’-hydroxy-4-(3-aminopropoxy) trans-stilbene: HAPtS) and then grafted onto SPIONs surface using an organosilane coupling agent, which is 3-chloropropyltriethoxysilane (CPTES) and based on nucleophilic substitution reactions. The amount of HAPtS loaded onto SPIONs surface was estimated by thermogravimetric analysis (TGA) and X-ray photoelectron spectroscopy (XPS) analyses at 116 µmol·g−1 SPIONs. The synthesized HAPtS molecule, as well as the associated nanohybrids, were fully characterized by transmission electron microscopy (TEM), XPS, TGA, infrared (IR) and UV-visible spectroscopies, dynamic light scattering (DLS), and zeta potential measurements. The in vitro biological assessment of the synthesized nanohybrid’s efficiency was carried out on C6 glioma cells and showed that the nanovector SPIONs-CPTES-HAPtS do not affect the mitochondrial metabolism (MTT test), but damage the plasma membrane (FDA test), which could contribute to limiting the proliferation of cancerous cells (clonogenic test) at a HAPtS concentration of 50 µM. These nanoparticles have a potential cytotoxic effect that could be used to eliminate cancer cells.

In order to explore future air quality in Europe at the 2030 horizon, two emission scenarios developed in the framework of the Global Energy Assessment including varying assumptions on climate and energy access policies are investigated with an ensemble of six regional and global atmospheric chemistry transport models. A specific focus is given in the paper to the assessment of uncertainties and robustness of the projected changes in air quality. The present work relies on an ensemble of chemistry transport models giving insight into the model spread. Both regional and global scale models were involved, so that the ensemble benefits from medium-resolution approaches as well as global models that capture long-range transport. For each scenario a whole decade is modelled in order to gain statistical confidence in the results. A statistical downscaling approach is used to correct the distribution of the modelled projection. Last, the modelling experiment is related to a hind-cast study published earlier, where the performances of all participating models were extensively documented. The analysis is presented in an exposure-based framework in order to discuss policy relevant changes. According to the emission projections, ozone precursors such as NOx will drop down to 30% to 50% of their current levels, depending on the scenario. As a result, annual mean O3 will slightly increase in NOx saturated areas but the overall O3 burden will decrease substantially. Exposure to detrimental O3 levels for health (SOMO35) will be reduced down to 45% to 70% of their current levels. And the fraction of stations where present-day exceedences of daily maximum O3 is higher than 120 μg m−3 more than 25 days per year will drop from 43% down to 2 to 8%. We conclude that air pollution mitigation measures (present in both scenarios) are the main factors leading to the improvement, but an additional cobenefit of at least 40% (depending on the indicator) is brought about by the climate policy.

The interaction between air quality and climate involves dynamical scales that cover a very wide range. Bridging these scales in numerical simulations is fundamental in studies devoted to megacity/hot-spot impacts on larger scales. A technique based on nudging is proposed as a bridging method that can couple different models at different scales. Here, nudging is used to force low resolution chemical composition models with a run of a high resolution model on a critical area. A one-year numerical experiment focused on the Po Valley hot spot is performed using the BOLCHEM model to asses the method. The results show that the model response is stable to perturbation induced by the nudging and that, taking the high resolution run as a reference, performances of the nudged run increase with respect to the non-forced run. The effect outside the forcing area depends on transport and is significant in a relevant number of events although it becomes weak on seasonal or yearly basis.

A detailed 3-D evaluation of an ensemble of five regional Chemistry Transport Models (RCTM) and one global CTM with focus on free tropospheric ozone over Europe is presented. It is performed over a summer period (June to August 2008) in the context of the GEMS-RAQ project. A data set of about 400 vertical ozone profiles from balloon soundings and commercial aircraft at 11 different locations is used for model evaluation, in addition to satellite measurements with the infrared nadir sounder (IASI) showing largest sensitivity to free tropospheric ozone. In the middle troposphere, the four regional models using the same top and boundary conditions from IFS-MOZART exhibit a systematic negative bias with respect to observed profiles of about −20%. Root Mean Square Error (RMSE) values are constantly growing with altitude, from 22% to 32% to 53%, respectively for 0–2 km, 2–8 km and 8–10 km height ranges. Lowest correlation is found in the middle troposphere, with minimum coefficients (R) between 0.2 to 0.45 near 8 km, as compared to 0.7 near the surface and similar values around 10 km. A sensitivity test made with the CHIMERE mode also shows that using hourly instead of monthly chemical boundary conditions generally improves the model skill (i.e. improve RMSE and correlation). Lower tropospheric 0–6 km partial ozone columns derived from IASI show a clear North-South gradient over Europe, which is qualitatively reproduced by the models. Also the temporal variability showing decreasing ozone concentrations in the lower troposphere (0–6 km columns) during summer is well reproduced by models even if systematic bias remains (the value of the bias being also controlled by the type of used boundary conditions). A multi-day case study of a trough with low tropopause was conducted and showed that both IASI and models were able to resolve strong horizontal gradients of middle and upper tropospheric ozone occurring in the vicinity of an upper tropospheric frontal zone.

We discuss the capability of current state-of-the-art chemistry and transport models to reproduce air quality trends and interannual variability. Documenting these strengths and weaknesses on the basis of historical simulations is essential before the models are used to investigate future air quality projections. To achieve this, a coordinated modelling exercise was performed in the framework of the CityZEN European Project. It involved six regional and global chemistry-transport models (BOLCHEM, CHIMERE, EMEP, EURAD, OSLOCTM2 and MOZART) simulating air quality over the past decade in the Western European anthropogenic emissions hotspots. Comparisons between models and observations allow assessing the skills of the models to capture the trends in basic atmospheric constituents (NO2, O3, and PM10). We find that the trends of primary constituents are well reproduced (except in some countries – owing to their sensitivity to the emission inventory) although capturing the more moderate trends of secondary species such as O3 is more challenging. Apart from the long term trend, the modelled monthly variability is consistent with the observations but the year-to-year variability is generally underestimated. A comparison of simulations where anthropogenic emissions are kept constant is also investigated. We find that the magnitude of the emission-driven trend exceeds the natural variability for primary compounds. We can thus conclude that emission management strategies have had a significant impact over the past 10 yr, hence supporting further emission reductions.

We present a comparison of tropospheric NO2 from OMI measurements to the median of an ensemble of Regional Air Quality (RAQ) models, and an intercomparison of the contributing RAQ models and two global models for the period July 2008–June 2009 over Europe. The model forecasts were produced routinely on a daily basis in the context of the European GEMS ("Global and regional Earth-system (atmosphere) Monitoring using Satellite and in-situ data") project. The tropospheric vertical column of the RAQ ensemble median shows a spatial distribution which agrees well with the OMI NO2 observations, with a correlation r=0.8. This is higher than the correlations from any one of the individual RAQ models, which supports the use of a model ensemble approach for regional air pollution forecasting. The global models show high correlations compared to OMI, but with significantly less spatial detail, due to their coarser resolution. Deviations in the tropospheric NO2 columns of individual RAQ models from the mean were in the range of 20–34% in winter and 40–62% in summer, suggesting that the RAQ ensemble prediction is relatively more uncertain in the summer months. The ensemble median shows a stronger seasonal cycle of NO2 columns than OMI, and the ensemble is on average 50% below the OMI observations in summer, whereas in winter the bias is small. On the other hand the ensemble median shows a somewhat weaker seasonal cycle than NO2 surface observations from the Dutch Air Quality Network, and on average a negative bias of 14%. Full profile information was available for two RAQ models and for the global models. For these models the retrieval averaging kernel was applied. Minor differences are found for area-averaged model columns with and without applying the kernel, which shows that the impact of replacing the a priori profiles by the RAQ model profiles is on average small. However, the contrast between major hotspots and rural areas is stronger for the direct modeled vertical columns than the columns where the averaging kernels are applied, related to a larger relative contribution of the free troposphere and the coarse horizontal resolution in the a priori profiles compared to the RAQ models. In line with validation results reported in the literature, summertime concentrations in the lowermost boundary layer in the a priori profiles from the DOMINO product are significantly larger than the RAQ model concentrations and surface observations over the Netherlands. This affects the profile shape, and contributes to a high bias in OMI tropospheric columns over polluted regions. The global models indicate that the upper troposphere may contribute significantly to the total column and it is important to account for this in comparisons with RAQ models. A combination of upper troposphere model biases, the a priori profile effects and DOMINO product retrieval issues could explain the discrepancy observed between the OMI observations and the ensemble median in summer.

Numerical diffusion induced by advection has a large influence on concentration of substances in atmospheric composition models. At coarse resolution numerical effects dominate, whereas at increasing model resolution a description of physical diffusion is needed. A method to investigate the effects of changing resolution and Courant number is defined here and is applied to the WAF advection scheme (used in BOLCHEM), evidencing a sub-diffusive process. The spread rate from an instantaneous source caused by numerical diffusion is compared to that produced by the physical diffusion necessary to simulate unresolved turbulent motions. The time at which the physical diffusion process overpowers the numerical spread is estimated, and it is shown to reduce as the resolution increases, and to increase with wind velocity.

No abstract available.

The chemopreventive potential of Resveratrol (RV) against bladder cancer and its mechanism of action have been widely demonstrated. The physicochemical properties of RV, particularly its high reactivity and low solubility in aqueous phase, have been limiting factors for its bioavailability and in vivo efficacy. In order to overcome these limitations, its inclusion in drug delivery systems needs to be taken into account. In particular, oil-in-water (O/W) nanoemulsions (NEs) have been considered ideal candidates for RV encapsulation. Since surfactant and oil composition can strongly influence NE features and their application field, a ternary phase diagram was constructed and evaluated to select a suitable surfactant/oil/water ratio. The selected sample was deeply characterized in terms of physical chemical features, stability, release capability and cytotoxic activity. Results showed a significant decrease in cell viability after the incubation of bladder T24 cancer cells with RV-loaded NEs, compared to free RV. The selected NE formulation was able to preserve and improve RV cytotoxic activity by a more rapid drug uptake into the cells. O/W NEs represent an effective approach to improve RV bioavailability.

The aim of this study is to characterize the air quality in a Mediterranean port city. The impact of ship emissions on both gaseous and particulate pollutants has been investigated through an integrated methodology which includes atmospheric flow and dispersion numerical modelling as well as chemical composition and statistical analyses. Specifically, chemical compositional data (ionic fraction, carbonaceous compounds, and metals) of PM2.5 were acquired during an experimental field campaign carried out in the port city of Brindisi (Apulia Region, Southern Italy). The sampling site was located on the roof of a building (ASI) within the port area. Given the complexity of the site in which both domestic buildings and a large industrial area are present, analyses were done by selecting different wind sectors to test different techniques to discriminate between sources. Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) were applied to evaluate statistical differences in the composition of PM2.5 sampled within the area when the sampling site was downwind to the port or to the urban-industrial area. Only LDA allowed to discriminate the separation between urban-industrial and port macroareas. Those results were further confirmed in terms of PM2.5 concentrations directly associated to ship emissions using a coupled modelling approach. The mesoscale model BOLCHEM was used to investigate the contribution of ship emissions both on primary and secondary PM2.5 concentration in the area surrounding the port, as well as on PM10, NOX and O3 concentrations. Then, the model was coupled offline with the local dispersion model ADMS-Urban. The adopted approach was crucial to evaluate the spatial distribution of the impact of ship emissions. BOLCHEM results showed that in the cell of the port the average impact of ship emissions on NOX was 37.6%, and −11.7% on O3. The average impact on PM2.5 was 6.1%, distributed between primary (2.7%) and secondary fraction (3.4%). At local scale, the analysis of high-resolution modelling results obtained from ADMS-Urban highlighted that, at ASI position, the impact of ship emissions on PM2.5 was 6.8% when the sampling site was positioned downwind to the port area and reduced to lower than 3.0% at about 2 km from the sources.