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Although stronger estimated effects for non-movers may simply reflect improved exposure estimation, evidence of higher risks in men compared with women deserves additional attention.
The first is evaluation/calibration of exposure and/or pharmacokinetic models for improved exposure estimation.
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We urge caution in assuming that currently available remotely sensed AOD can help improve exposure estimation for PM2.5 and particular caution in using AOD to estimate spatial heterogeneity where there is little ground-level PM2.5 data for ground truthing, based on the lack of strong spatial correlation between available AOD retrievals and long-term average PM2.5.
However, a simulation study suggested that improved exposure prediction may not always improve health effect estimation (Szpiro et al. 2011).
With exposure estimates being so critical, consideration was given to atmospheric models of PM and other pollutants that could be wed with health outcomes to improve exposure and risk estimations.
Specific methods for improving heat exposure estimation (for instance the calculation of WBGT from weather station data) and the PHEP is under development and will be tested and promoted as a new tool for improved human exposure assessment.
Clearly, we cannot apply these methods to large numbers of people, but collection of such data even on small subsamples of the population will provide valuable additional information, for example, on within-area variability of both the exposure data and potential confounders, which will help improve the exposure estimation and modeling (Jackson et al. 2006).
These results indicate that, if limited to a single personal measure, descriptive information on important exposure determinants can improve long-term exposure estimation.
Thus, the product nR nO reflects that observers may make repeated observation of the same video frames, which is one way of improving precision of exposure estimations obtained by observation [ 7].
These findings imply that personal exposures can depend on activity patterns and that microenvironmental concentration information can improve the accuracy of personal exposure estimation.
Combining grid-based regional-scale and local-scale dispersion models is a current area of development to improve air quality modeling for exposure estimation.
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