RT Journal Article
SR Electronic
T1 Assessment of exposure to mercury from industrial emissions: comparing “distance as a proxy” and dispersion modelling approaches
JF Occupational and Environmental Medicine
JO Occup Environ Med
FD BMJ Publishing Group Ltd
SP 380
OP 388
DO 10.1136/oem.2006.026781
VO 64
IS 6
A1 Susan Hodgson
A1 Mark J Nieuwenhuijsen
A1 Roy Colvile
A1 Lars Jarup
YR 2007
UL http://oem.bmj.com/content/64/6/380.abstract
AB Background: The Runcorn area, north-west England, contains many pollution sources, the health effects of which have been under discussion for over 100 years. Preliminary investigations revealed an excess risk of mortality from kidney disease in people living nearest to several point sources of pollution, using distance as a proxy for exposure. Ongoing epidemiological investigations into the effect of ambient mercury exposure on dose and renal effect required a more refined assessment of exposure. Methods: Atmospheric dispersion modelling was used to assess mercury dispersion from three mercury-emitting sources (including a large chlor alkali plant), based on knowledge of emissions, local meteorology and topography. Results: The model was sensitive to various input parameters, with different dispersion patterns and ground-level concentrations, and therefore different exposed populations identified when different input parameters were defined. The different approaches to exposure assessment also had an impact on the epidemiological findings. The model output correlated well with weekly monitoring data collected in the local area, although the model underestimated concentrations in close proximity to the chlor alkali plant. The model identified that one point source did not contribute significantly to ground-level mercury concentrations, so that inclusion of this source when using the “distance as a proxy” approach led to significant exposure misclassification. Conclusions: The model output indicates that assessment of ambient exposure should give consideration to the magnitude of emissions, point source characteristics, local meteorology and topography to ensure that the most appropriate exposure classification is reached. Even if dispersion modelling cannot be undertaken, these data can be used to inform and improve the distance as a proxy approach, and improve the interpretability of the epidemiological findings.