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Temporal trends of persistent organic pollutants: a comparison of different time series models.

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Temporal trends of persistent organic pollutants: a comparison of different time series models. / Venier, Marta; Hung, Hayley; Tych, Wlodek et al.
In: Environmental Science and Technology, Vol. 46, No. 7, 03.04.2012, p. 3928-3934.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Venier, M, Hung, H, Tych, W & Hites, RO 2012, 'Temporal trends of persistent organic pollutants: a comparison of different time series models.', Environmental Science and Technology, vol. 46, no. 7, pp. 3928-3934. https://doi.org/10.1021/es204527q

APA

Venier, M., Hung, H., Tych, W., & Hites, RO. (2012). Temporal trends of persistent organic pollutants: a comparison of different time series models. Environmental Science and Technology, 46(7), 3928-3934. https://doi.org/10.1021/es204527q

Vancouver

Venier M, Hung H, Tych W, Hites RO. Temporal trends of persistent organic pollutants: a comparison of different time series models. Environmental Science and Technology. 2012 Apr 3;46(7):3928-3934. Epub 2012 Mar 20. doi: 10.1021/es204527q

Author

Venier, Marta ; Hung, Hayley ; Tych, Wlodek et al. / Temporal trends of persistent organic pollutants: a comparison of different time series models. In: Environmental Science and Technology. 2012 ; Vol. 46, No. 7. pp. 3928-3934.

Bibtex

@article{08cbf2a883c542d1a0344d0363342346,
title = "Temporal trends of persistent organic pollutants: a comparison of different time series models.",
abstract = "We analyzed the vapor phase atmospheric concentrations of representative persistent chemicals (i.e., α- and γ-hexachlorocyclohexane, phenanthrene, PCB-18 and PCB-52) in samples collected at a remote site near Eagle Harbor, Michigan, and at an urban site in Chicago, Illinois, using four time series models: a modified Clausius-Clapeyron equation, a multiple linear regression that includes both a linear and an harmonic dependence on time, digital filtration (DF), and dynamic harmonic regression (DHR). The results of these different models were evaluated in terms of goodness-of-fit, long-term trends, and halving times. The four approaches all provided highly significant descriptions of the data, with coefficients of determination (R(2)) ranging from 0.33 to 0.96. In general, the DF and DHR methods fit the data better, capturing not only the seasonal variations of the atmospheric concentrations but also smaller scale interannual variations in the long term trends. The halving times calculated using the four methods were generally similar to one another, and they ranged from about 4 years for γ-HCH at Chicago to about 60 years for PCB-52 at Chicago. This analysis showed that each of these four statistical methods for evaluating long-term time series has advantages and disadvantages. The choice of the appropriate method should depend on the output needed, the type of audience, and the availability and usability of the necessary software.",
author = "Marta Venier and Hayley Hung and Wlodek Tych and ROnald Hites",
year = "2012",
month = apr,
day = "3",
doi = "10.1021/es204527q",
language = "English",
volume = "46",
pages = "3928--3934",
journal = "Environmental Science and Technology",
issn = "0013-936X",
publisher = "American Chemical Society",
number = "7",

}

RIS

TY - JOUR

T1 - Temporal trends of persistent organic pollutants: a comparison of different time series models.

AU - Venier, Marta

AU - Hung, Hayley

AU - Tych, Wlodek

AU - Hites, ROnald

PY - 2012/4/3

Y1 - 2012/4/3

N2 - We analyzed the vapor phase atmospheric concentrations of representative persistent chemicals (i.e., α- and γ-hexachlorocyclohexane, phenanthrene, PCB-18 and PCB-52) in samples collected at a remote site near Eagle Harbor, Michigan, and at an urban site in Chicago, Illinois, using four time series models: a modified Clausius-Clapeyron equation, a multiple linear regression that includes both a linear and an harmonic dependence on time, digital filtration (DF), and dynamic harmonic regression (DHR). The results of these different models were evaluated in terms of goodness-of-fit, long-term trends, and halving times. The four approaches all provided highly significant descriptions of the data, with coefficients of determination (R(2)) ranging from 0.33 to 0.96. In general, the DF and DHR methods fit the data better, capturing not only the seasonal variations of the atmospheric concentrations but also smaller scale interannual variations in the long term trends. The halving times calculated using the four methods were generally similar to one another, and they ranged from about 4 years for γ-HCH at Chicago to about 60 years for PCB-52 at Chicago. This analysis showed that each of these four statistical methods for evaluating long-term time series has advantages and disadvantages. The choice of the appropriate method should depend on the output needed, the type of audience, and the availability and usability of the necessary software.

AB - We analyzed the vapor phase atmospheric concentrations of representative persistent chemicals (i.e., α- and γ-hexachlorocyclohexane, phenanthrene, PCB-18 and PCB-52) in samples collected at a remote site near Eagle Harbor, Michigan, and at an urban site in Chicago, Illinois, using four time series models: a modified Clausius-Clapeyron equation, a multiple linear regression that includes both a linear and an harmonic dependence on time, digital filtration (DF), and dynamic harmonic regression (DHR). The results of these different models were evaluated in terms of goodness-of-fit, long-term trends, and halving times. The four approaches all provided highly significant descriptions of the data, with coefficients of determination (R(2)) ranging from 0.33 to 0.96. In general, the DF and DHR methods fit the data better, capturing not only the seasonal variations of the atmospheric concentrations but also smaller scale interannual variations in the long term trends. The halving times calculated using the four methods were generally similar to one another, and they ranged from about 4 years for γ-HCH at Chicago to about 60 years for PCB-52 at Chicago. This analysis showed that each of these four statistical methods for evaluating long-term time series has advantages and disadvantages. The choice of the appropriate method should depend on the output needed, the type of audience, and the availability and usability of the necessary software.

U2 - 10.1021/es204527q

DO - 10.1021/es204527q

M3 - Journal article

VL - 46

SP - 3928

EP - 3934

JO - Environmental Science and Technology

JF - Environmental Science and Technology

SN - 0013-936X

IS - 7

ER -