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Linking environmental effects to health impacts: a computer modelling approach for air pollution

¹ Imperial College London, UK
² Environmental Resources Management, London, UK

Correspondence to:
Correspondence to:
Dr J Mindell
Department of Epidemiology and Public Health, University College London, 1–19 Torrington Place, London WC1E 6BT, UK; j.mindell{at}ucl.ac.uk

Study objective and Setting: To develop a computer model, using a geographical information system (GIS), to quantify potential health effects of air pollution from a new energy from waste facility on the surrounding urban population.

Design: Health impacts were included where evidence of causality is sufficiently convincing. The evidence for no threshold means that annual average increases in concentration can be used to model changes in outcome. The study combined the "contours" of additional pollutant concentrations for the new source generated by a dispersion model with a population database within a GIS, which is set up to calculate the product of the concentration increase with numbers of people exposed within each enumeration district exposure response coefficients, and the background rates of mortality and hospital admissions for several causes.

Main results: The magnitude of health effects might result from the increased PM₁₀ exposure is small—about 0.03 deaths each year in a population of 3 500 000, with 0.04 extra hospital admissions for respiratory disease. Long term exposure might bring forward 1.8–7.8 deaths in 30 years.

Conclusions: This computer model is a feasible approach to estimating impacts on human health from environmental effects but sensitivity analyses are recommended.

Relevance to clinical or professional practice: The availability of GIS and dispersion models on personal computers enables quantification of health effects resulting from the additional air pollution new industrial development might cause. This approach could also be used in environmental impact assessment. Care must be taken in presenting results to emphasise methodological limitations and uncertainties in the numbers.

Abbreviations: GIS, geographical information system; ED, enumeration district

Keywords: air pollution; computer model; environmental exposure; geographical information system; health impacts

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