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A quantitative risk assessment method based on population and exposure distributions using Australian air quality data
Institution:1. CSIRO Atmospheric Research, Aspendale, Australia;2. University of San Francisco, San Francisco, CA, USA;3. University of Queensland, Australia;1. Medicina de Familia, Centro de Salud Canillejas, Madrid; Grupo de Actividades Preventivas SEMERGEN, España;2. Medicina de Familia, Centro de Salud Los Alpes, Madrid, España;3. Medicina de Familia, Servicio de Urgencias, Hospital Ramón y Cajal, Madrid, España;4. Servicio de Oncología Médica, Hospital del Tajo, Aranjuez, España;1. Pharmaceutical Chemistry Department, Faculty of Pharmacy, Egyptian Russian University, Badr 11829, Egypt;2. Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, Nasr City, Cairo 11751, Egypt
Abstract:This paper develops a practical probabilistic method for assessing aggregate population health risks from different types of population exposures. The method consists of calculating the product of two functions: a population-weighted distribution of concentrations and a concentration-response distribution. This operation yields the corresponding aggregated health-risk distribution function. The method can use alternative exposure-response distributions and populations-specific exposure patterns, depending on the context of the assessment. A deterministic sensitivity analysis is included in the methodological aspects of this research. The distributions of concentrations are generated by combining area-specific population densities with atmospheric concentrations for each of the areas where exposure to air pollutants occurs. The exposure-response functions are developed from the literature. The method is exemplified using alternative exposure probabilities to carbon monoxide, nitrogen dioxide, particulate matter (PM10), and exposure-response models developed specifically for these pollutants for assessing health risks, and applied to data from a number of Australian cities. The results, which hold when the functions are monotonic, show single maximum per pollutant, regardless of the choice of exposure and exposure-response distribution. Although those maxima are often below the Australian Air Pollution Standards, there are instances when this is not the case.
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