@article{e45a4e032ea5476783ea604fa0ebada3,
title = "Monitoring urban environmental pollution by bivariate control charts: New methodology and case study in Santiago, Chile",
abstract = "Particulate matter (PM) pollution is a serious environmental problem. Santiago of Chile is one of the most polluted cities in the world in terms of PM2.5 and PM10. Monitoring of environmental risk is useful for detecting and preventing adverse effects on human health in highly polluted cities. In this paper, we propose a methodology for monitoring PM pollution in Santiago based on bivariate quality control charts and an asymmetric distribution. A simulation study is carried out to evaluate performance of the proposed methodology. A case study with PM pollution real-world data from Santiago is provided, which shows that the methodology is suitable to alert early episodes of extreme air pollution. The results are in agreement with the critical episodes reported with the current model used by the Chilean health authority.",
keywords = "Hotelling statistic, R software, air pollution, bivariate nonnormal distributions, bootstrapping, maximum likelihood and Monte Carlo methods, process control",
author = "Carolina Marchant and V{\'i}ctor Leiva and George Christakos and Cavieres, {M. Fernanda}",
note = "Funding Information: Direcci{\'o}n de Investigaci{\'o}n of the Universidad Cat{\'o}lica del Maule, Chile, Grant/Award Number: 20-2018; National Commission for Scientific and Technological Research of Chile under Fondecyt, Grant/Award Number: 1160868; National Science Foundation of China, Grant/Award Number: 41671399 Funding Information: The authors thank the editors and reviewers for their constructive comments on an earlier version of this manuscript. The research was partially supported by the Direcci{\'o}n de Investigaci{\'o}n of the Universidad Cat{\'o}lica del Maule, Chile, under Grant 20-2018 (C. Marchant), the National Commission for Scientific and Technological Research of Chile under Fondecyt Grant 1160868 (V. Leiva), and the National Science Foundation of China under Grant 41671399 (G. Christakos). Funding Information: The authors thank the editors and reviewers for their constructive comments on an earlier version of this manuscript. The research was partially supported by the Direcci?n de Investigaci?n of the Universidad Cat?lica del Maule, Chile, under Grant 20-2018 (C. Marchant), the National Commission for Scientific and Technological Research of Chile under Fondecyt Grant 1160868 (V. Leiva), and the National Science Foundation of China under Grant 41671399 (G. Christakos). Publisher Copyright: {\textcopyright} 2018 John Wiley & Sons, Ltd.",
year = "2019",
month = aug,
doi = "10.1002/env.2551",
language = "English",
volume = "30",
journal = "Environmetrics",
issn = "1180-4009",
number = "5",
}