Exposure estimation obtaining concentration data

This chapter will focus on PM ambient concentrations, which are key variables for exposure models, and are generally obtained by direct measurements in air quality monitoring stations. However, depending on the location and dimension of the region to be studied, monitoring data could not be sufficient to characterise PM levels or to perform population exposure estimations. Numerical models complement and improve the information provided by measured concentration data. These models simulate the changes of pollutant concentrations in the air using a set of mathematical equations that translate the chemical and physical processes in the atmosphere. 

In addition, existing databases where environmental media and biomonitoring data are collected (such as NHEXAS) could be further studied to estimate exposure and explore the relationships between biomarker concentration and exposure. That information can be used to apportion chemical intake into the different exposure pathways to assist in interpreting population variability, to calculate exposure by combining environmental measurements with survey information to verify estimates of exposure from pharmacokinetic models, and to identify research needs on the basis of discrepancies between estimates obtained from the exposure-pathways analysis and biomonitoring results. 

Evaluation of worker exposure requires samples in the breathing zone and in general room air or rest area. To define a potential hazard, check compliance with regulations or obtain data for control purposes, samples would normally be collected in the vicinity of the operation itself. In general, samples are collected in the vicinity of the workers directly exposed and also workers remote from the exposure who voice complaints. Sample duration requires that the sample contain sufficient matter for an accurate analysis and is based on the sensitivity of the analytical procedure and the estimated air concentration, as well as the current threshold limit value for the contaminant. Table 1 contains appropriate sampling duration, sample flow rates and sample volume. 

Owing to the relatively low LOD obtained by Member States as reported in submitted data, the high number of data points reported below the LOD or LOQ for the four nuts included in this assessment (>60%) and the need to have understandable tables and figures, the upper-bound AFL concentration level was used in the dietary exposure estimates for reporting purposes (GEMS/Food-Euro, 1995). 

For AEGL-3, the 1-h LC50 of 82 ppm for squirrel monkeys (Haun et al. 1970) was reduced by a factor of 3 to estimate a lethality threshold (27.3 ppm). Temporal scaling to obtain time-specific AEGL values was described by C% t=k (where C=exposure concentration, t=exposure duration, and k=a constant). The lethality data for the species tested indicated a near linear relationship between concentration and exposure duration (n=0.97 and 0.99 for monkeys and dogs, respectively). The derived exposure value was adjusted by a total uncertainty factor of 10.2 An uncertainty factor of 3 was applied for... 

Exposure Levels in Environmental Media. Reliable monitoring data for the levels of di- -octylphthalate in contaminated media at hazardous waste sites are needed so that the information obtained on levels of di-ra-octylphthalate in the environment can be used in combination with the known body burden of di-w-octylphthalate to assess the potential risk of adverse health effects in populations living in the vicinity of hazardous waste sites. Di-u-octylphthalate has been detected in ambient air, rain, surface water, groundwater, and sediment. However, as a result of the confusion about the nomenclature for octylphthalate esters, much of the historical monitoring data available actually pertain to the branched isomer, di(2-ethylhexyl)phthalate (Vista Chemical 1992). Therefore, little current information specific to the /1-octyl isomer is available regarding concentrations of the compound in foods, drinking water, and environmental media, particularly with respect to media at hazardous waste sites. The lack of monitoring data precludes the estimation of human exposure via intake of or contact with contaminated media. 

A large number of epidemiology and case-control studies have examined the potential association between oral aluminum exposure and Alzheimer s disease. A number of these studies have been criticized for flawed patient selection, poor comparability of exposed and control groups, poor exposure assessment, poor assessment of health outcomes, and weak statistical correlations (Nieboer et al. 1995 Schupf et al. 1989). Studies conducted by Martyn et al. (1989), McLachlan et al. (1996), and Michel et al. (1990) have found an association between oral exposure to aluminum and an increased risk of Alzheimer s disease. In a survey study conducted by Martyn et al. (1989), the incidence of Alzheimer s disease in individuals under the age of 70 was estimated from computerized tomographic (CT) records. The 1,203 subjects lived in 88 county districts within England and Wales. Data on aluminum concentrations in the municipal water over a 10-year period were obtained from water authorities and water companies. The subjects were classified as having probable Alzheimer s disease, possible Alzheimer s disease, other causes of dementia, or epilepsy. The relative risks of Alzheimer s disease were elevated in the subjects living in districts with aluminum water concentrations of >0.01 mg/L. However, the relative risk exceeded unity only in the subjects with aluminum water concentrations of >0.11 mg/L (relative risk of 1.5, 95% confidence interval of 1.1-2.2). 

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