A simple spatio-temporal procedure for the prediction of air pollution levels

• Published in: Journal of chemometrics Vol. 16; no. 12; pp. 623 - 632
• Main Authors: Mendes, Jorge M., Turkman, Kamil F.
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 01.12.2002; Wiley
• Subjects: Applied sciences; Atmospheric pollution; Exact sciences and technology; kriging; multivariate time series; Pollutants physicochemistry study: properties, effects, reactions, transport and distribution; Pollution; spatio-temporal models; Portugal; Europe; Data analysis; spatio-temporal models; multivariate time series; Time series; Air quality; Urban area; Multivariate analysis; Forecast model; Spatial variation; Modeling; Time variation; Kriging; Surveillance; Content; Atmospheric pollution forecasting; Air pollution; Nitrogen dioxide
• ISSN: 0886-9383; 1099-128X
• DOI: 10.1002/cem.766

In this paper we study the spatio‐temporal behaviour of air pollutants measured daily over the city of Lisbon, Portugal. Our specific aim is to predict air pollutant levels in time and space over a fine grid of locations based on observations from a small number of monitoring sites. Our suggested prediction procedure is based on the simple and intuitive idea of first making predictions in time at the monitoring sites and then extending these predictions in space to locations other than the monitoring sites using kriging methods. Copyright © 2002 John Wiley & Sons, Ltd.