Probabilistic modeling of young children's overall lead exposure in France: integrated approach for various exposure media

OBJECTIVES: Emissions of lead into the environment (and thus its environmental concentrations) have decreased in recent years. We sought to estimate the overall lead exposure of children aged 6 months to 6 years (the population group most exposed and most sensitive to lead) in France through the various media (air, food, water, soils, and dust) and the respective contributions of each medium to the total dose. We have focused on the general population, leaving aside specific risk factors such as deteriorated lead paints. METHODS: We used the most recent French intake data for food and water, and a daily ingested quantity selected from the literature for soils and dust. Contamination data came from the first total diet study of contaminant levels in France (2000-2001), from regulatory testing of tap water (2004), a literature review of lead in urban soils, and a pilot study (2005) of lead in dust. Air quality monitoring measurements showed that the contribution of air could now be safely ignored. Weekly exposure doses were estimated with Monte Carlo simulations. RESULTS: Median weekly exposure dose was 7.5 microg/kg bw.week for children aged 6 months to 3 years and 4.7 for those aged from 3-6 years. 95th percentiles were 13.5 and 8.7 microg/kg bw.week. Exposure came mainly from food. The principal uncertainties are associated with quantification limits in food and water, representativeness and traceability of tap water samples, and absence of recent data about urban soil contamination. CONCLUSIONS: These results differ quite notably from earlier estimates and highlight the need, especially for policy-making purposes, to update exposure measurements for this metal.     

An analysis of continuous black carbon concentrations in proximity to an airport and major roadways

Black carbon (BC), a constituent of particulate matter, is emitted from multiple combustion sources, complicating determination of contributions from individual sources or source categories from monitoring data. In close proximity to an airport, this may include aircraft emissions, other emissions on the airport grounds, and nearby major roadways, and it would be valuable to determine the factors most strongly related to measured BC concentrations. In this study, continuous BC concentrations were measured at five monitoring sites in proximity to a small regional airport in Warwick, Rhode Island from July 2005 to August 2006. Regression was used to model the relative contributions of aircraft and related sources, using real-time flight activity (departures and arrivals) and meteorological data, including mixing height, wind speed and direction. The latter two were included as a nonparametric smooth spatial term using thin-plate splines applied to wind velocity vectors and fit in a linear mixed model framework. Standard errors were computed using a moving-block bootstrap to account for temporal autocorrelation. Results suggest significant positive associations between hourly departures and arrivals at the airport and BC concentrations within the community, with departures having a more substantial impact. Generalized Additive Models for wind speed and direction were consistent with significant contributions from the airport, major highway, and multiple local roads. Additionally, inverse mixing height, temperature, precipitation, and at one location relative humidity, were associated with BC concentrations. Median contribution estimates indicate that aircraft departures and arrivals (and other sources coincident in space and time) contribute to approximately 24–28% of the BC concentrations at the monitoring sites in the community. Our analysis demonstrated that a regression-based approach with detailed meteorological and source characterization can provide insights about source contributions, which could be used to devise control strategies or to provide monitor-based comparisons with source-specific atmospheric dispersion models.     

Microsatellite length polymorphisms associated with dispersal-related agonistic onset in male wild house mice (Mus musculus domesticus)

Dispersal propensity, reflecting one of the most decisive mammalian life history traits, has been suggested to vary heritably and to locally adapt to prevailing dispersal conditions in wild house mouse populations. Because individual dispersal propensity highly significantly covaries with the developmental timing of the onset of agonistic interactions between littermate brothers, we used agonistic onset as an endophenotype to explore the potential genetic basis of dispersal-related behavioral variation in male house mice. We found significant covariation of microsatellite marker compositions with the probability of fraternal pairs to exhibit agonistic relationships before the age of 2 months. In particular, the presence of two alleles associated with a serotonin transporter protein gene (Slc6a4) and a testosterone dehydrogenase gene (Cyp3a11), respectively, strongly covaried with the probability of early agonistic onset. These results are congruent with recent findings of microsatellite length polymorphisms marking regulatory variation of gene expression that is relevant for social behavior, including dispersal propensity development, in other mammals. Genetic variability for ontogenetic timing of agonistic onset would be in agreement with genotypic differentiation of the dispersive behavioral syndrome in natural populations that could lead to local adaptation.