Statistical modelling and prediction of atmospheric pollution by particulate material: two nonparametric approaches
✍ Scribed by Claudio Silva; Patricio Pérez; Alex Trier
- Publisher
- John Wiley and Sons
- Year
- 2001
- Tongue
- English
- Weight
- 309 KB
- Volume
- 12
- Category
- Article
- ISSN
- 1180-4009
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✦ Synopsis
Atmospheric particles are one of the main factors of air pollution in Santiago\ Chile[ Inhalation of particulate material is known to lead to serious health problems\ including respiratory illness and complications related thereto[ Vehicular tra.c\ industrial activity and street dust are important sources of atmospheric particles[ The public authorities in Santiago have been monitoring air pollution by means of a network of semi! automatic sampling stations[ At one of these stations\ located near the city centre close to Government House\ both PM1[4 and PM09 particulate material concentrations have been measured continuously for several years[ Here PM1[4 refers to particles having a diameter smaller than 1[4 microns and PM09 corresponds to particles smaller than 09 microns[ Hourly averages of the concentrations are available[ For the present work\ hourly data recorded at intervals of 01 hours have been used[ The aim is to describe and forecast these variables with satisfactory precision\ including critical pollution episodes\ both as a function of previous behaviour and of a set of meteorological variables\ comprising wind speed and direction\ ambient temperature and relative air humidity[ Both non!parametric discriminant analysis and multivariate adaptive regression splines procedures have been applied[ Highly satisfactory classi_cation as well as forecasting results were achieved with these approaches\ respectively[