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Land Use Regression Models for Ultrafine Particles in Six European Areas
[Image: see text] Long-term ultrafine particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land use regression (LUR) models were developed and evaluated for six European areas based on repeated 30 min monitoring following standardized protocols. In each a...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American
Chemical Society
2017
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5362744/ https://www.ncbi.nlm.nih.gov/pubmed/28244744 http://dx.doi.org/10.1021/acs.est.6b05920 |
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author | van Nunen, Erik Vermeulen, Roel Tsai, Ming-Yi Probst-Hensch, Nicole Ineichen, Alex Davey, Mark Imboden, Medea Ducret-Stich, Regina Naccarati, Alessio Raffaele, Daniela Ranzi, Andrea Ivaldi, Cristiana Galassi, Claudia Nieuwenhuijsen, Mark Curto, Ariadna Donaire-Gonzalez, David Cirach, Marta Chatzi, Leda Kampouri, Mariza Vlaanderen, Jelle Meliefste, Kees Buijtenhuijs, Daan Brunekreef, Bert Morley, David Vineis, Paolo Gulliver, John Hoek, Gerard |
author_facet | van Nunen, Erik Vermeulen, Roel Tsai, Ming-Yi Probst-Hensch, Nicole Ineichen, Alex Davey, Mark Imboden, Medea Ducret-Stich, Regina Naccarati, Alessio Raffaele, Daniela Ranzi, Andrea Ivaldi, Cristiana Galassi, Claudia Nieuwenhuijsen, Mark Curto, Ariadna Donaire-Gonzalez, David Cirach, Marta Chatzi, Leda Kampouri, Mariza Vlaanderen, Jelle Meliefste, Kees Buijtenhuijs, Daan Brunekreef, Bert Morley, David Vineis, Paolo Gulliver, John Hoek, Gerard |
author_sort | van Nunen, Erik |
collection | PubMed |
description | [Image: see text] Long-term ultrafine particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land use regression (LUR) models were developed and evaluated for six European areas based on repeated 30 min monitoring following standardized protocols. In each area; Basel (Switzerland), Heraklion (Greece), Amsterdam, Maastricht, and Utrecht (“The Netherlands”), Norwich (United Kingdom), Sabadell (Spain), and Turin (Italy), 160–240 sites were monitored to develop LUR models by supervised stepwise selection of GIS predictors. For each area and all areas combined, 10 models were developed in stratified random selections of 90% of sites. UFP prediction robustness was evaluated with the intraclass correlation coefficient (ICC) at 31–50 external sites per area. Models from Basel and The Netherlands were validated against repeated 24 h outdoor measurements. Structure and model R(2) of local models were similar within, but varied between areas (e.g., 38–43% Turin; 25–31% Sabadell). Robustness of predictions within areas was high (ICC 0.73–0.98). External validation R(2) was 53% in Basel and 50% in The Netherlands. Combined area models were robust (ICC 0.93–1.00) and explained UFP variation almost equally well as local models. In conclusion, robust UFP LUR models could be developed on short-term monitoring, explaining around 50% of spatial variance in longer-term measurements. |
format | Online Article Text |
id | pubmed-5362744 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | American
Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-53627442017-03-24 Land Use Regression Models for Ultrafine Particles in Six European Areas van Nunen, Erik Vermeulen, Roel Tsai, Ming-Yi Probst-Hensch, Nicole Ineichen, Alex Davey, Mark Imboden, Medea Ducret-Stich, Regina Naccarati, Alessio Raffaele, Daniela Ranzi, Andrea Ivaldi, Cristiana Galassi, Claudia Nieuwenhuijsen, Mark Curto, Ariadna Donaire-Gonzalez, David Cirach, Marta Chatzi, Leda Kampouri, Mariza Vlaanderen, Jelle Meliefste, Kees Buijtenhuijs, Daan Brunekreef, Bert Morley, David Vineis, Paolo Gulliver, John Hoek, Gerard Environ Sci Technol [Image: see text] Long-term ultrafine particle (UFP) exposure estimates at a fine spatial scale are needed for epidemiological studies. Land use regression (LUR) models were developed and evaluated for six European areas based on repeated 30 min monitoring following standardized protocols. In each area; Basel (Switzerland), Heraklion (Greece), Amsterdam, Maastricht, and Utrecht (“The Netherlands”), Norwich (United Kingdom), Sabadell (Spain), and Turin (Italy), 160–240 sites were monitored to develop LUR models by supervised stepwise selection of GIS predictors. For each area and all areas combined, 10 models were developed in stratified random selections of 90% of sites. UFP prediction robustness was evaluated with the intraclass correlation coefficient (ICC) at 31–50 external sites per area. Models from Basel and The Netherlands were validated against repeated 24 h outdoor measurements. Structure and model R(2) of local models were similar within, but varied between areas (e.g., 38–43% Turin; 25–31% Sabadell). Robustness of predictions within areas was high (ICC 0.73–0.98). External validation R(2) was 53% in Basel and 50% in The Netherlands. Combined area models were robust (ICC 0.93–1.00) and explained UFP variation almost equally well as local models. In conclusion, robust UFP LUR models could be developed on short-term monitoring, explaining around 50% of spatial variance in longer-term measurements. American Chemical Society 2017-02-28 2017-03-21 /pmc/articles/PMC5362744/ /pubmed/28244744 http://dx.doi.org/10.1021/acs.est.6b05920 Text en Copyright © 2017 American Chemical Society This is an open access article published under a Creative Commons Non-Commercial No Derivative Works (CC-BY-NC-ND) Attribution License (http://pubs.acs.org/page/policy/authorchoice_ccbyncnd_termsofuse.html) , which permits copying and redistribution of the article, and creation of adaptations, all for non-commercial purposes. |
spellingShingle | van Nunen, Erik Vermeulen, Roel Tsai, Ming-Yi Probst-Hensch, Nicole Ineichen, Alex Davey, Mark Imboden, Medea Ducret-Stich, Regina Naccarati, Alessio Raffaele, Daniela Ranzi, Andrea Ivaldi, Cristiana Galassi, Claudia Nieuwenhuijsen, Mark Curto, Ariadna Donaire-Gonzalez, David Cirach, Marta Chatzi, Leda Kampouri, Mariza Vlaanderen, Jelle Meliefste, Kees Buijtenhuijs, Daan Brunekreef, Bert Morley, David Vineis, Paolo Gulliver, John Hoek, Gerard Land Use Regression Models for Ultrafine Particles in Six European Areas |
title | Land
Use Regression Models for Ultrafine Particles
in Six European Areas |
title_full | Land
Use Regression Models for Ultrafine Particles
in Six European Areas |
title_fullStr | Land
Use Regression Models for Ultrafine Particles
in Six European Areas |
title_full_unstemmed | Land
Use Regression Models for Ultrafine Particles
in Six European Areas |
title_short | Land
Use Regression Models for Ultrafine Particles
in Six European Areas |
title_sort | land
use regression models for ultrafine particles
in six european areas |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5362744/ https://www.ncbi.nlm.nih.gov/pubmed/28244744 http://dx.doi.org/10.1021/acs.est.6b05920 |
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