Data and models for characterizing aerosol exposure and dose: Advancements, needs and new directions
P.J. Lioy, P.G. Georgopoulos (EOHSI, UMDNJ - R.W. Johnson Medical School and Rutgers University)
Evaluation of human exposure to complex atmospheric contaminants such as primary and secondary particulate matter (PM) is often based on measured data from fixed ambient monitoring stations. This results in an artificial characterization of human exposures and doses, as the concentrations and physicochemical attributes of pollutants actually inhaled vary significantly and are in general quite different from corresponding outdoor monitor values. MENTOR , the Modeling Environment for Total Risk studies, is an evolving framework that provides a set of novel mechanistically-based modeling tools aiming to improve the assessment of human (both individual and population) exposures and doses to - possibly co-occurring - photochemical pollutants and fine airborne particles.
These new modeling tools are being developed so as to take advantage of, and be used in conjunction with, up-to-date information from a variety of new and evolving databases on emissions of primary particles and of precursors of secondary particles, of human activity patterns, of chemical and size composition for ambient aerosol, of indoor/outdoor relationships of aerosol concentrations and physicochemical attributes, and of dosimetric data for the human lung.
Integration of ambient and microenvironmental information is accomplished using Geographic Information Systems (GIS) and Relational Database Management Systems (RDBMS) tools, to facilitate exposure scenario development and implementation, involving, e.g., the geographic location of individuals and the spatial distribution of populations considered over a variety of time periods.