A methodological frame for assessing benzene induced leukemia risk mitigation due to policy measures.

The study relies on the development of a methodology for assessing the determinants that comprise the overall leukemia risk due to benzene exposure and how these are affected by outdoor and indoor air quality regulation. An integrated modeling environment was constructed comprising traffic emissions, dispersion models, human exposure models and a coupled internal dose/biology-based dose-response risk assessment model, in order to assess the benzene imposed leukemia risk, as much as the impact of traffic fleet renewal and smoking banning to these levels. Regarding traffic fleet renewal, several "what if" scenarios were tested.

Assessment of microcystin distribution and biomagnification in tissues of aquatic food web compartments from a shallow lake and evaluation of potential risks to public health.

The objectives of this study were: (1) to examine the distribution and bioaccumulation of microcystins in the main components of the food web (phytoplankton, zooplankton, crayfish, shrimp, mussel, snail, fish, frog) of Lake Pamvotis (NW Greece), (2) to investigate the possibility of microcystin biomagnification and (3) to evaluate the potential threat of the contaminated aquatic organisms to human health. Significant microcystin concentrations were detected in all the aquatic organisms during two different periods, with the higher concentrations observed in phytoplankton and the lower in fish species and frogs. This is the first study reporting microcystin accumulation in the body of the freshwater shrimp Atyaephyra desmsaresti, in the brain of the fish species common carp (Cyprinus carpio) and in the skin of the frog Rana epirotica.

Bayesian algorithm implementation in a real time exposure assessment model on benzene with calculation of associated cancer risks.

The objective of the current study was the development of a reliable modeling platform to calculate in real time the personal exposure and the associated health risk for filling station employees evaluating current environmental parameters (traffic, meteorological and amount of fuel traded) determined by the appropriate sensor network. A set of Artificial Neural Networks (ANNs) was developed to predict benzene exposure pattern for the filling station employees. Furthermore, a Physiology Based Pharmaco-Kinetic (PBPK) risk assessment model was developed in order to calculate the lifetime probability distribution of leukemia to the employees, fed by data obtained by the ANN model.

Measurements of benzene and formaldehyde in a medium sized urban environment. Indoor/outdoor health risk implications on special population groups.

In the present study, the results of a measurement campaign aiming to assess cancer risk among two special groups of population: policemen and laboratory technicians exposed to the toxic substances, benzene and formaldehyde are presented. The exposure is compared to general population risk. The results show that policemen working outdoor (traffic regulation, patrol on foot or in vehicles, etc.

A methodology to estimate benzene concentrations in a town through a traffic model.

In this work an approach is presented that describes the changes of benzene concentration in the air, in relation with the special traffic characteristics of a road. The dominant input parameters of the model are traffic density and the vehicle's type distribution according to seven main categories characterized by different emission factors. The dispersion approach used is a semi-empirical relationship that apart from emission rates requires also wind speed and the direction, as well as the geometrical characteristics of the road.