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The analysis of extreme pollution levels: a case study.

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The analysis of extreme pollution levels: a case study. / Coles, S. G.; Pan, F.
In: Journal of Applied Statistics, Vol. 23, No. 2 & 3, 1996, p. 333-348.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Coles, SG & Pan, F 1996, 'The analysis of extreme pollution levels: a case study.', Journal of Applied Statistics, vol. 23, no. 2 & 3, pp. 333-348. https://doi.org/10.1080/02664769624288

APA

Coles, S. G., & Pan, F. (1996). The analysis of extreme pollution levels: a case study. Journal of Applied Statistics, 23(2 & 3), 333-348. https://doi.org/10.1080/02664769624288

Vancouver

Coles SG, Pan F. The analysis of extreme pollution levels: a case study. Journal of Applied Statistics. 1996;23(2 & 3):333-348. doi: 10.1080/02664769624288

Author

Coles, S. G. ; Pan, F. / The analysis of extreme pollution levels: a case study. In: Journal of Applied Statistics. 1996 ; Vol. 23, No. 2 & 3. pp. 333-348.

Bibtex

@article{4a74bf2869f4471da747286102dd5629,
title = "The analysis of extreme pollution levels: a case study.",
abstract = "Our case study focuses on Milan. Italian law specifies strict guidelines for the permissibility of high levels of a variety of air pollutants in cities. In Milan, a highly sophisticated network of recording stations has been constructed to monitor pollutant levels. The aim of this paper is to obtain a summary of the temporal behaviour of the pollutant series, with particular reference to extreme levels. Simple exploratory analysis reveals a number of sources of stochastic variation and possible dependence on covariate effects, which are subsequently modelled, exploiting recent developments in the modelling and inference for temporal extremes. Using this methodology, we examine the issues of data trends, non-stationarity, meteorological effects and temporal dependence, all of which have substantive implications in the design of pollution control regulations. Moreover, the asymptotic basis of these extreme value models justifies the interpretation of our results, even at levels that are exceptionally high.",
author = "Coles, {S. G.} and F. Pan",
year = "1996",
doi = "10.1080/02664769624288",
language = "English",
volume = "23",
pages = "333--348",
journal = "Journal of Applied Statistics",
issn = "1360-0532",
publisher = "Routledge",
number = "2 & 3",

}

RIS

TY - JOUR

T1 - The analysis of extreme pollution levels: a case study.

AU - Coles, S. G.

AU - Pan, F.

PY - 1996

Y1 - 1996

N2 - Our case study focuses on Milan. Italian law specifies strict guidelines for the permissibility of high levels of a variety of air pollutants in cities. In Milan, a highly sophisticated network of recording stations has been constructed to monitor pollutant levels. The aim of this paper is to obtain a summary of the temporal behaviour of the pollutant series, with particular reference to extreme levels. Simple exploratory analysis reveals a number of sources of stochastic variation and possible dependence on covariate effects, which are subsequently modelled, exploiting recent developments in the modelling and inference for temporal extremes. Using this methodology, we examine the issues of data trends, non-stationarity, meteorological effects and temporal dependence, all of which have substantive implications in the design of pollution control regulations. Moreover, the asymptotic basis of these extreme value models justifies the interpretation of our results, even at levels that are exceptionally high.

AB - Our case study focuses on Milan. Italian law specifies strict guidelines for the permissibility of high levels of a variety of air pollutants in cities. In Milan, a highly sophisticated network of recording stations has been constructed to monitor pollutant levels. The aim of this paper is to obtain a summary of the temporal behaviour of the pollutant series, with particular reference to extreme levels. Simple exploratory analysis reveals a number of sources of stochastic variation and possible dependence on covariate effects, which are subsequently modelled, exploiting recent developments in the modelling and inference for temporal extremes. Using this methodology, we examine the issues of data trends, non-stationarity, meteorological effects and temporal dependence, all of which have substantive implications in the design of pollution control regulations. Moreover, the asymptotic basis of these extreme value models justifies the interpretation of our results, even at levels that are exceptionally high.

U2 - 10.1080/02664769624288

DO - 10.1080/02664769624288

M3 - Journal article

VL - 23

SP - 333

EP - 348

JO - Journal of Applied Statistics

JF - Journal of Applied Statistics

SN - 1360-0532

IS - 2 & 3

ER -