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Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation

BACKGROUND: Ultraviolet B (UV-B) radiation plays a multifaceted role in human health, inducing DNA damage and representing the primary source of vitamin D for most humans; however, current U.S. UV exposure models are limited in spatial, temporal, and/or spectral resolution. Area-to-point (ATP) resid...

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Autores principales: VoPham, Trang, Hart, Jaime E., Bertrand, Kimberly A., Sun, Zhibin, Tamimi, Rulla M., Laden, Francine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5121956/
https://www.ncbi.nlm.nih.gov/pubmed/27881169
http://dx.doi.org/10.1186/s12940-016-0197-x
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author VoPham, Trang
Hart, Jaime E.
Bertrand, Kimberly A.
Sun, Zhibin
Tamimi, Rulla M.
Laden, Francine
author_facet VoPham, Trang
Hart, Jaime E.
Bertrand, Kimberly A.
Sun, Zhibin
Tamimi, Rulla M.
Laden, Francine
author_sort VoPham, Trang
collection PubMed
description BACKGROUND: Ultraviolet B (UV-B) radiation plays a multifaceted role in human health, inducing DNA damage and representing the primary source of vitamin D for most humans; however, current U.S. UV exposure models are limited in spatial, temporal, and/or spectral resolution. Area-to-point (ATP) residual kriging is a geostatistical method that can be used to create a spatiotemporal exposure model by downscaling from an area- to point-level spatial resolution using fine-scale ancillary data. METHODS: A stratified ATP residual kriging approach was used to predict average July noon-time erythemal UV (UV(Ery)) (mW/m(2)) biennially from 1998 to 2012 by downscaling National Aeronautics and Space Administration (NASA) Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) gridded remote sensing images to a 1 km spatial resolution. Ancillary data were incorporated in random intercept linear mixed-effects regression models. Modeling was performed separately within nine U.S. regions to satisfy stationarity and account for locally varying associations between UV(Ery) and predictors. Cross-validation was used to compare ATP residual kriging models and NASA grids to UV-B Monitoring and Research Program (UVMRP) measurements (gold standard). RESULTS: Predictors included in the final regional models included surface albedo, aerosol optical depth (AOD), cloud cover, dew point, elevation, latitude, ozone, surface incoming shortwave flux, sulfur dioxide (SO(2)), year, and interactions between year and surface albedo, AOD, cloud cover, dew point, elevation, latitude, and SO(2). ATP residual kriging models more accurately estimated UV(Ery) at UVMRP monitoring stations on average compared to NASA grids across the contiguous U.S. (average mean absolute error [MAE] for ATP, NASA: 15.8, 20.3; average root mean square error [RMSE]: 21.3, 25.5). ATP residual kriging was associated with positive percent relative improvements in MAE (0.6–31.5%) and RMSE (3.6–29.4%) across all regions compared to NASA grids. CONCLUSIONS: ATP residual kriging incorporating fine-scale spatial predictors can provide more accurate, high-resolution UV(Ery) estimates compared to using NASA grids and can be used in epidemiologic studies examining the health effects of ambient UV. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12940-016-0197-x) contains supplementary material, which is available to authorized users.
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spelling pubmed-51219562016-11-30 Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation VoPham, Trang Hart, Jaime E. Bertrand, Kimberly A. Sun, Zhibin Tamimi, Rulla M. Laden, Francine Environ Health Research BACKGROUND: Ultraviolet B (UV-B) radiation plays a multifaceted role in human health, inducing DNA damage and representing the primary source of vitamin D for most humans; however, current U.S. UV exposure models are limited in spatial, temporal, and/or spectral resolution. Area-to-point (ATP) residual kriging is a geostatistical method that can be used to create a spatiotemporal exposure model by downscaling from an area- to point-level spatial resolution using fine-scale ancillary data. METHODS: A stratified ATP residual kriging approach was used to predict average July noon-time erythemal UV (UV(Ery)) (mW/m(2)) biennially from 1998 to 2012 by downscaling National Aeronautics and Space Administration (NASA) Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) gridded remote sensing images to a 1 km spatial resolution. Ancillary data were incorporated in random intercept linear mixed-effects regression models. Modeling was performed separately within nine U.S. regions to satisfy stationarity and account for locally varying associations between UV(Ery) and predictors. Cross-validation was used to compare ATP residual kriging models and NASA grids to UV-B Monitoring and Research Program (UVMRP) measurements (gold standard). RESULTS: Predictors included in the final regional models included surface albedo, aerosol optical depth (AOD), cloud cover, dew point, elevation, latitude, ozone, surface incoming shortwave flux, sulfur dioxide (SO(2)), year, and interactions between year and surface albedo, AOD, cloud cover, dew point, elevation, latitude, and SO(2). ATP residual kriging models more accurately estimated UV(Ery) at UVMRP monitoring stations on average compared to NASA grids across the contiguous U.S. (average mean absolute error [MAE] for ATP, NASA: 15.8, 20.3; average root mean square error [RMSE]: 21.3, 25.5). ATP residual kriging was associated with positive percent relative improvements in MAE (0.6–31.5%) and RMSE (3.6–29.4%) across all regions compared to NASA grids. CONCLUSIONS: ATP residual kriging incorporating fine-scale spatial predictors can provide more accurate, high-resolution UV(Ery) estimates compared to using NASA grids and can be used in epidemiologic studies examining the health effects of ambient UV. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12940-016-0197-x) contains supplementary material, which is available to authorized users. BioMed Central 2016-11-24 /pmc/articles/PMC5121956/ /pubmed/27881169 http://dx.doi.org/10.1186/s12940-016-0197-x Text en © The Author(s). 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
VoPham, Trang
Hart, Jaime E.
Bertrand, Kimberly A.
Sun, Zhibin
Tamimi, Rulla M.
Laden, Francine
Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation
title Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation
title_full Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation
title_fullStr Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation
title_full_unstemmed Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation
title_short Spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation
title_sort spatiotemporal exposure modeling of ambient erythemal ultraviolet radiation
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5121956/
https://www.ncbi.nlm.nih.gov/pubmed/27881169
http://dx.doi.org/10.1186/s12940-016-0197-x
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