A unified strategy for building simple air quality indices
Article first published online: 8 APR 2002
Copyright © 2002 John Wiley & Sons, Ltd.
Volume 13, Issue 3, pages 243–261, May 2002
How to Cite
Bruno, F. and Cocchi, D. (2002), A unified strategy for building simple air quality indices. Environmetrics, 13: 243–261. doi: 10.1002/env.512
- Issue published online: 8 APR 2002
- Article first published online: 8 APR 2002
- Manuscript Revised: 6 AUG 2001
- Manuscript Received: 1 NOV 2000
- Italian Ministry of the University and Scientific and Technological Research
- air quality indices;
- order statistics
Interest in air quality indices has been increasing in recent years. This is strictly connected with the development and the easy availability of web-communication and on-line information. By means of web pages it is indeed possible to give quick and easy-to-consult information about air quality in a specific area. We propose a class of air quality indices which are simple to read and easy to understand by citizens and policy-makers. They are constructed in order to be able to compare situations that differ in time and space. In particular, interest is focused on situations where many monitoring stations are operating in the same area. In this case, which occurs frequently, air pollution data are collected according to three dimensions: time, space and type of pollutant. In order to obtain a synthetic value, the dimensions are reduced by means of aggregation processes that occur by successively applying some aggregating function. The final index may be influenced by the order of aggregation. The hierarchical aggregation here proposed is based on the successive selection of order statistics, i.e. on percentiles and on maxima. The variety of pollutants measured in each area imposes a standardization due to their different effects on the human health. This evaluation comes from epidemiological studies and influences the final value of the index. We propose to use simultaneously more than one index of the selected class and to associate a measure of variability with every index. Such measures of dispersion account for very important additional information. Copyright © 2002 John Wiley & Sons, Ltd.