Difference of performance in response to disease admissions between daily time air quality indices and those derived from average and entropy functions

Abstract

Daily time air quality indices, which can reflect air quality in 1 day, are suitable for identifying daily exposure during conditions of poor air quality. The aim of this study is to compare the main effectiveness of four daily time indices in representing variation in the number of disease admissions. These indices include pollution standard index (PSI), air quality index (AQI) and their respective indices derived from mean and entropy functions: MEPSI and MEAQI. The hourly concentrations of fine particulate matter less than 10 μm in diameter (PM₁₀), PM_2.5, O₃, CO, NO₂ and SO₂ from 1 January 2006 to 31 December 2010 were obtained from 14 air quality monitoring stations owned by the Environmental Protection Administration (EPA) in the Kaoping region, Taiwan.

Instead of circulatory system disease admissions, the indices were correlative with the number of respiratory disease admissions with correlative coefficients of 0.49 to 0.56 (P < 0.05). The daily time air quality indices derived from mean and entropy functions improved their performance of reactive range and air pollution identification. The reactive range of MEPSI and MEAQI was 1.4–3 times that of the original indices. The MEPSI and MEAQI increased identification from 40 to 180 in index scale and revealed one to two additional categories of public health effect information. In comparison with other indices, MEAQI is more effective for application to pollution events with multiple air pollutants.

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