A walk in the PARC: developing and implementing 21st century chemical risk assessment in Europe.

Current approaches for the assessment of environmental and human health risks due to exposure to chemical substances have served their purpose reasonably well. Nevertheless, the systems in place for different uses of chemicals are faced with various challenges, ranging from a growing number of chemicals to changes in the types of chemicals and materials produced. This has triggered global awareness of the need for a paradigm shift, which in turn has led to the publication of new concepts for chemical risk assessment and explorations of how to translate these concepts into pragmatic approaches. As a result, next-generation risk assessment (NGRA) is generally seen as the way forward. However, incorporating new scientific insights and innovative approaches into hazard and exposure assessments in such a way that regulatory needs are adequately met has appeared to be challenging. The European Partnership for the Assessment of Risks from Chemicals (PARC) has been designed to address various challenges associated with innovating chemical risk assessment. Its overall goal is to consolidate and strengthen the European research and innovation capacity for chemical risk assessment to protect human health and the environment. With around 200 participating organisations from all over Europe, including three European agencies, and a total budget of over 400 million euro, PARC is one of the largest projects of its kind. It has a duration of seven years and is coordinated by ANSES, the French Agency for Food, Environmental and Occupational Health & Safety.

Life cycle assessment of municipal waste management options.

To date, landfilling remains the most common waste management practice in Greece in spite of enforced regulations aiming at increasing recycling, pre-selection of waste and energy and material recovery. In this study, selected alternative scenarios aiming at minimizing the unused material fraction to be disposed of in landfills are analyzed, using the life cycle assessment methodology. The methodology was applied in the case of municipal solid waste (MSW) management in Athens and Thessaloniki, with a special focus on energy and material balance, including potential global and local scale airborne emissions. Results are given in the form of indices efficiency, effectiveness, environmental and public health impacts. Material flow accounting, gross energy requirement, emergy intensity, emission and release intensity and morbidity or mortality indicators have been used to support the comparative assessment. However, not all options are equally benign to the local environment and to the health of the local population, since both the former and the latter are still affected by non-negligible local emissions. With regard to public health impacts, adverse effects on respiratory health, congenital malformations, low birth weight and cancer incidence were estimated. A significant and not intuitive result is the fact that life cycle analysis produces different conclusions than a simple environmental impact assessment based only on estimated or measured emissions. Taking into account the overall life cycle of both the waste streams and of the technological systems and facilities envisaged alters the relative attractiveness of the solutions considered.

Assessing and enhancing the utility of low-cost activity and location sensors for exposure studies.

Nowadays, the advancement of mobile technology in conjunction with the introduction of the concept of exposome has provided new dynamics to the exposure studies. Since the addressing of health outcomes related to environmental stressors is crucial, the improvement of exposure assessment methodology is of paramount importance. Towards this aim, a pilot study was carried out in the two major cities of Greece (Athens, Thessaloniki), investigating the applicability of commercially available fitness monitors and the Moves App for tracking people's location and activities, as well as for predicting the type of the encountered location, using advanced modeling techniques. Within the frame of the study, 21 individuals were using the Fitbit Flex activity tracker, a temperature logger, and the application Moves App on their smartphones. For the validation of the above equipment, participants were also carrying an Actigraph (activity sensor) and a GPS device. The data collected from Fitbit Flex, the temperature logger, and the GPS (speed) were used as input parameters in an Artificial Neural Network (ANN) model for predicting the type of location. Analysis of the data showed that the Moves App tends to underestimate the daily steps counts in comparison with Fitbit Flex and Actigraph, respectively, while Moves App predicted the movement trajectory of an individual with reasonable accuracy, compared to a dedicated GPS. Finally, the encountered location was successfully predicted by the ANN in most of the cases.

Quantification and characterization of microplastics in the Thermaic Gulf, in the North Aegean Sea.

The abundance and distribution of microplastics has largely increased during last years and the respective implications on the environment and human health is an emerging field in research. In addition, recent studies in the enclosed Mediterranean Sea in Spain and Italy have shown an extended occurrence of microplastics (MPs) in different sediments of environmental samples. This study is focused on the quantification and the characterization of MPs in the Thermaic Gulf in northern Greece. Briefly, samples from different environmental compartments such as seawater, local beaches and seven commercially available fish species collected and analyzed. MPs particles extracted and classified by size, shape, colour and polymer type. A total of 28,523 microplastic particles recorded in the surface water samples, with their numbers ranging from 189 to 7714 particles per sample. The mean concentration of MPs recorded on the surface water was 1.9 ± 2 items/m3 or 750,846 ± 838,029 items/km2. Beach sediment sample analysis revealed 14,790 microplastic particles, of which 1825 were large microplastics (LMPs, 1-5 mm) and 12,965 were small microplastics (SMPs, <1 mm). Furthermore, beach sediment samples showed a mean concentration of 733.6 ± 136.6 items/m2, with the concentration of LMPs being 90.5 ± 12.4 items/m2 and the concentration of SMPs being 643 ± 132 items/m2. Concerning fish deposition, microplastics were detected in intestines and mean concentrations per species ranged from 1.3 ± 0.6 to 15.0 ± 1.5 items/individual. The differences in microplastic concentrations between species were statistically significant (p < 0.05) and showed that mesopelagic fish contained the highest concentrations, followed by epipelagic species. The most common size fraction found in the data-set was 1.0-2.5 mm, and polyethylene and polypropylene were the most abundant polymer types recorded. This is the first detailed investigation of MPs in Thermaic Gulf, which raises concerns on their potential negative effects.

Multi-city comparative PM2.5 source apportionment for fifteen sites in Europe: The ICARUS project.

PM2.5 is an air pollution metric widely used to assess air quality, with the European Union having set targets for reduction in PM2.5 levels and population exposure. A major challenge for the scientific community is to identify, quantify and characterize the sources of atmospheric particles in the aspect of proposing effective control strategies. In the frame of ICARUS EU2020 project, a comprehensive database including PM2.5 concentration and chemical composition (ions, metals, organic/elemental carbon, Polycyclic Aromatic Hydrocarbons) from three sites (traffic, urban background, rural) of five European cities (Athens, Brno, Ljubljana, Madrid, Thessaloniki) was created. The common and synchronous sampling (two seasons involved) and analysis procedure offered the prospect of a harmonized Positive Matrix Factorization model approach, with the scope of identifying the similarities and differences of PM2.5 key-source chemical fingerprints across the sampling sites. The results indicated that the average contribution of traffic exhausts to PM2.5 concentration was 23.3% (traffic sites), 13.3% (urban background sites) and 8.8% (rural sites). The average contribution of traffic non-exhausts was 12.6% (traffic), 13.5% (urban background) and 6.1% (rural sites). The contribution of fuel oil combustion was 3.8% at traffic, 11.6% at urban background and 18.7% at rural sites. Biomass burning contribution was 22% at traffic sites, 30% at urban background sites and 28% at rural sites. Regarding soil dust, the average contribution was 5% and 8% at traffic and urban background sites respectively and 16% at rural sites. Sea salt contribution was low (1-4%) while secondary aerosols corresponded to the 16-34% of PM2.5. The homogeneity of the chemical profiles as well as their relationship with prevailing meteorological parameters were investigated. The results showed that fuel oil combustion, traffic non-exhausts and soil dust profiles are considered as dissimilar while biomass burning, sea salt and traffic exhaust can be characterized as relatively homogenous among the sites.

Modeling of adipose/blood partition coefficient for environmental chemicals.

A Quantitative Structure Activity Relationship (QSAR) model was developed in order to predict the adipose/blood partition coefficient of environmental chemical compounds. The first step of QSAR modeling was the collection of inputs. Input data included the experimental values of adipose/blood partition coefficient and two sets of molecular descriptors for 67 organic chemical compounds; a) the descriptors from Linear Free Energy Relationship (LFER) and b) the PaDEL descriptors. The datasets were split to training and prediction set and were analysed using two statistical methods; Genetic Algorithm based Multiple Linear Regression (GA-MLR) and Artificial Neural Networks (ANN). The models with LFER and PaDEL descriptors, coupled with ANN, produced satisfying performance results. The fitting performance (R2) of the models, using LFER and PaDEL descriptors, was 0.94 and 0.96, respectively. The Applicability Domain (AD) of the models was assessed and then the models were applied to a large number of chemical compounds with unknown values of adipose/blood partition coefficient. In conclusion, the proposed models were checked for fitting, validity and applicability. It was demonstrated that they are stable, reliable and capable to predict the values of adipose/blood partition coefficient of "data poor" chemical compounds that fall within the applicability domain.

Benefits on public health from transport-related greenhouse gas mitigation policies in Southeastern European cities.

Climate change is a major environmental threat of our time. Cities have a significant impact on greenhouse gas emissions as most of the traffic, industry, commerce and more than 50% of world population is situated in urban areas. Southern Europe is a region that faces financial turmoil, enhanced migratory fluxes and climate change pressure. The case study of Thessaloniki is presented, one of the only two cities in Greece with established climate change action plans. The effects of feasible traffic policies in year 2020 are assessed and their potential health impact is compared to a business as usual scenario. Two types of measures are investigated: operation of underground rail in the city centre and changes in fleet composition. Potential co-benefits from reduced greenhouse gas emissions on public health by the year 2020 are computed utilizing state-of-the-art concentration response functions for PMx, NO2 and C6H6. Results show significant environmental health and monetary co-benefits when the city metro is coupled with appropriate changes in the traffic composition. Monetary savings due to avoided mortality or leukaemia incidence corresponding to the reduction in PM10, PM2.5, NO2 and C6H6 exposure will be 56.6, 45, 37.7 and 1.0 million Euros respectively. Promotion of 'green' transportation in the city (i.e. the wide use of electric vehicles), will provide monetary savings from the reduction in PM10, PM2.5, NO2 and C6H6 exposure up to 60.4, 49.1, 41.2 and 1.08 million Euros. Overall, it was shown that the respective GHG emission reduction policies resulted in clear co-benefits in terms of air quality improvement, public health protection and monetary loss mitigation.

Monitoring of air pollution levels related to Charilaos Trikoupis Bridge.

Charilaos Trikoupis bridge is the longest cable bridge in Europe that connects Western Greece with the rest of the country. In this study, six air pollution monitoring campaigns (including major regulated air pollutants) were carried out from 2013 to 2015 at both sides of the bridge, located in the urban areas of Rio and Antirrio respectively. Pollution data were statistically analyzed and air quality was characterized using US and European air quality indices. From the overall campaign, it was found that air pollution levels were below the respective regulatory thresholds, but once at the site of Antirrio (26.4 and 52.2µg/m3 for PM2.5 and ΡΜ10, respectively) during the 2nd winter period. Daily average PM10 and PM2.5 levels from two monitoring sites were well correlated to gaseous pollutant (CO, NO, NO2, NOx and SO2) levels, meteorological parameters and factor scores from Positive Matrix Factorization during the 3-year period. Moreover, the elemental composition of PM10 and PM2.5 was used for source apportionment. That analysis revealed that major emission sources were sulfates, mineral dust, biomass burning, sea salt, traffic and shipping emissions for PM10 and PM2.5, for both Rio and Antirrio. Seasonal variation indicates that sulfates, mineral dust and traffic emissions increased during the warm season of the year, while biomass burning become the dominant during the cold season. Overall, the contribution of the Charilaos Trikoupis bridge to the vicinity air pollution is very low. This is the result of the relatively low daily traffic volume (~10,000 vehicles per day), the respective traffic fleet composition (~81% of the traffic fleet are private vehicles) and the speed limit (80km/h) which does not favor traffic emissions. In addition, the strong and frequent winds further contribute to the rapid dispersion of the emitted pollutants.

The impact of multi-walled carbon nanotubes with different amount of metallic impurities on immunometabolic parameters in healthy volunteers.

The impact of two types of multi-walled carbon nanotubes (MWCNTs) (12-14 nm) with different content of metallic impurities (purified and unpurified nanotubes) on peroxidation processes, the status of immune cells in healthy volunteers and gene expression combined to pathway analysis was studied in vitro. From the study it was shown that the main mechanism of action for both types of MWCNTs is induction of oxidative stress, the intensity of which is directly related to the amount of metallic impurities. Unpurified MWCNTs produced twice as high levels of oxidation than the purified CNTs inducing thus more intense mitochondrial dysfunction. All the above were also verified by gene expression analysis of 2 different human cellular cultures (lung epithelium and keratinoma cells) and the respective pathway analysis; modulation of genes activating the NFkB pathway is associated to inflammatory responses. This may cause a perturbation in the IL-6 signaling pathway in order to regulate inflammatory processes and compensate for apoptotic changes. A plausible hypothesis for the immunological effects observed in vivo, are considered as the result of the synergistic effect of systemic (mediated by cells of the routes of exposure) and local inflammation (blood cells).

Exposure analysis of accidental release of mercury from compact fluorescent lamps (CFLs).

Mercury release after breakage of compact fluorescent lamps (CFLs) has recently become an issue of public health concern, especially in the case of early life infants. Preliminary, screening type calculations have indicated that there is potential for increased intake of mercury vapor by inhalation after breakage of a CFL. Several experimental and computational studies have shown that, when modeling the breakage of a CFL, the room space must be segregated into different zones, according to the potential of mercury vapor to accumulate in them after accidental release. In this study, a detailed two-zone model that captures the physicochemical processes that govern mercury vapor formation and dispersion in the indoor environment was developed. The mercury fate model was coupled to a population exposure model that accounts for age and gender-related differences in time-activity patterns, as well as country differences in body weight and age distribution. The parameters above are used to determine the intake through inhalation (gas phase and particles) and non-dietary ingestion (settled dust) for each age, gender group and ethnicity. Results showed that the critical period for intake covers the first 4h after the CFL breaks and that room air temperature significantly affects the intake rate. Indoor air concentration of mercury vapor may exceed toxicological thresholds of concern such as the acute Reference Exposure Limit (REL) for mercury vapor set by the Environmental Protection Agency of California. Ingestion intake through hand-to-mouth behavior is significant for infants and toddlers, counting for about 20% of the overall intake. Simple risk reduction measures including increased indoor ventilation followed by careful clean-up of the accident site, may limit dramatically the estimated health risk.

Evaluation of a multiple regression model for the forecasting of the concentrations of NOx and PM10 in Athens and Helsinki.

Forecasting models based on stepwise multiple linear regression (MLR) have been developed for Athens and Helsinki. The predictor variables were the hourly concentrations of pollutants (NO, NO(2), NO(x), CO, O(3), PM(2.5) and PM(10)) and the meteorological variables (ambient temperature, wind speed/direction, and relative humidity) and in case of Helsinki also Monin-Obukhov length and mixing height of the present day. The variables to be forecasted are the maximum hourly concentrations of PM(10) and NO(x), and the daily average PM(10) concentrations of the next day. The meteorological pre-processing model MPP-FMI was used for computing the Monin-Obukhov length and the mixing height. The limitations of such statistical models include the persistence of both the meteorological and air quality situation; the model cannot account for rapid changes (on a temporal scale of hours or less than a day) that are commonly associated, e.g., with meteorological fronts, or episodes of a long-range transport origin. We have selected the input data for the model from one urban background and one urban traffic station both in Athens and Helsinki, in 2005. We have used various statistical evaluation parameters to analyze the performance of the models, and inter-compared the performance of the predictions for both cities. Forecasts from the MLR model were also compared to those from an Artificial Neural Network model (ANN) to investigate, if there are substantial gains that might justify the additional computational effort. The best predictor variables for both cities were the concentrations of NO(x) and PM(10) during the evening hours as well as wind speed, and the Monin-Obukhov length. In Athens, the index of agreement (IA) for NO(x) ranged from 0.77 to 0.84 and from 0.69 to 0.72, in the warm and cold periods of the year. In Helsinki, the corresponding values of IA ranged from 0.32 to 0.82 and from 0.67 to 0.86 for the warm and cold periods. In case of Helsinki the model accuracy was expectedly better on the average, when Monin-Obukhov length and mixing height were included as predictor variables. The models provide better forecasts of the daily average concentration, compared with the maximum hourly concentration for PM(10). The results derived by the ANN model where only slightly better than the ones derived by the MLR methodology. The results therefore suggest that the MLR methodology is a useful and fairly accurate tool for regulatory purposes.