A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide

Jie Chen; Kees de Hoogh; John Gulliver; Barbara Hoffmann; Ole Hertel; Matthias Ketzel; Mariska Bauwelinck; Aaron van Donkelaar; Ulla A. Hvidtfeldt; Klea Katsouyanni; Nicole A.H. Janssen; Randall V. Martin; Evangelia Samoli; Per E. Schwartz; Massimo Stafoggia; Tom Bellander; Maciek Strak; Kathrin Wolf; Danielle Vienneau; Roel Vermeulen; Bert Brunekreef; Gerard Hoek

doi:10.1016/j.envint.2019.104934

A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide

Jie Chen, Kees de Hoogh, John Gulliver, Barbara Hoffmann, Ole Hertel, Matthias Ketzel, Mariska Bauwelinck, Aaron van Donkelaar, Ulla A. Hvidtfeldt, Klea Katsouyanni, Nicole A.H. Janssen, Randall V. Martin, Evangelia Samoli, Per E. Schwartz, Massimo Stafoggia, Tom Bellander, Maciek Strak, Kathrin Wolf, Danielle Vienneau, Roel VermeulenBert Brunekreef, Gerard Hoek

Research output: Contribution to journal › Article › peer-review

230 Citations (Scopus)

Original language	English
Article number	104934
Journal	Environment International
Volume	130
DOIs	https://doi.org/10.1016/j.envint.2019.104934
Publication status	Published - Sept 2019

ASJC Scopus Subject Areas

General Environmental Science

Keywords

Fine particles
Land use regression
Machine learning
Nitrogen dioxide

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.envint.2019.104934

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Chen, J., de Hoogh, K., Gulliver, J., Hoffmann, B., Hertel, O., Ketzel, M., Bauwelinck, M., van Donkelaar, A., Hvidtfeldt, U. A., Katsouyanni, K., Janssen, N. A. H., Martin, R. V., Samoli, E., Schwartz, P. E., Stafoggia, M., Bellander, T., Strak, M., Wolf, K., Vienneau, D., ... Hoek, G. (2019). A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide. Environment International, 130, Article 104934. https://doi.org/10.1016/j.envint.2019.104934

Chen, J, de Hoogh, K, Gulliver, J, Hoffmann, B, Hertel, O, Ketzel, M, Bauwelinck, M, van Donkelaar, A, Hvidtfeldt, UA, Katsouyanni, K, Janssen, NAH, Martin, RV, Samoli, E, Schwartz, PE, Stafoggia, M, Bellander, T, Strak, M, Wolf, K, Vienneau, D, Vermeulen, R, Brunekreef, B & Hoek, G 2019, 'A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide', Environment International, vol. 130, 104934. https://doi.org/10.1016/j.envint.2019.104934

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title = "A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide",

keywords = "Fine particles, Land use regression, Machine learning, Nitrogen dioxide",

author = "Jie Chen and {de Hoogh}, Kees and John Gulliver and Barbara Hoffmann and Ole Hertel and Matthias Ketzel and Mariska Bauwelinck and {van Donkelaar}, Aaron and Hvidtfeldt, {Ulla A.} and Klea Katsouyanni and Janssen, {Nicole A.H.} and Martin, {Randall V.} and Evangelia Samoli and Schwartz, {Per E.} and Massimo Stafoggia and Tom Bellander and Maciek Strak and Kathrin Wolf and Danielle Vienneau and Roel Vermeulen and Bert Brunekreef and Gerard Hoek",

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year = "2019",

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doi = "10.1016/j.envint.2019.104934",

language = "English",

volume = "130",

journal = "Environment International",

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T1 - A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide

AU - Chen, Jie

AU - de Hoogh, Kees

AU - Gulliver, John

AU - Hoffmann, Barbara

AU - Hertel, Ole

AU - Ketzel, Matthias

AU - Bauwelinck, Mariska

AU - van Donkelaar, Aaron

AU - Hvidtfeldt, Ulla A.

AU - Katsouyanni, Klea

AU - Janssen, Nicole A.H.

AU - Martin, Randall V.

AU - Samoli, Evangelia

AU - Schwartz, Per E.

AU - Stafoggia, Massimo

AU - Bellander, Tom

AU - Strak, Maciek

AU - Wolf, Kathrin

AU - Vienneau, Danielle

AU - Vermeulen, Roel

AU - Brunekreef, Bert

AU - Hoek, Gerard

PY - 2019/9

Y1 - 2019/9

KW - Fine particles

KW - Land use regression

KW - Machine learning

KW - Nitrogen dioxide

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DO - 10.1016/j.envint.2019.104934

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SN - 0160-4120

VL - 130

JO - Environment International

JF - Environment International

M1 - 104934

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A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide

ASJC Scopus Subject Areas

Keywords

UN SDGs

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