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Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates

Many different quantitative techniques have been developed to either assess Environmental Justice (EJ) issues or estimate exposure and dose for risk assessment. However, very few approaches have been applied to link EJ factors to exposure dose estimate and identify potential impacts of EJ factors on...

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Autores principales: Huang, Hongtai, Barzyk, Timothy M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5295275/
https://www.ncbi.nlm.nih.gov/pubmed/28036053
http://dx.doi.org/10.3390/ijerph14010024
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author Huang, Hongtai
Barzyk, Timothy M.
author_facet Huang, Hongtai
Barzyk, Timothy M.
author_sort Huang, Hongtai
collection PubMed
description Many different quantitative techniques have been developed to either assess Environmental Justice (EJ) issues or estimate exposure and dose for risk assessment. However, very few approaches have been applied to link EJ factors to exposure dose estimate and identify potential impacts of EJ factors on dose-related variables. The purpose of this study is to identify quantitative approaches that incorporate conventional risk assessment (RA) dose modeling and cumulative risk assessment (CRA) considerations of disproportionate environmental exposure. We apply the Average Daily Dose (ADD) model, which has been commonly used in RA, to better understand impacts of EJ indicators upon exposure dose estimates and dose-related variables, termed the Environmental-Justice-Average-Daily-Dose (EJ-ADD) approach. On the U.S. nationwide census tract-level, we defined and quantified two EJ indicators (poverty and race/ethnicity) using an EJ scoring method to examine their relation to census tract-level multi-chemical exposure dose estimates. Pollutant doses for each tract were calculated using the ADD model, and EJ scores were assigned to each tract based on poverty- or race-related population percentages. Single- and multiple-chemical ADD values were matched to the tract-level EJ scores to analyze disproportionate dose relationships and contributing EJ factors. We found that when both EJ indicators were examined simultaneously, ADD for all pollutants generally increased with larger EJ scores. To demonstrate the utility of using EJ-ADD on the local scale, we approximated ADD levels of lead via soil/dust ingestion for simulated communities with different EJ-related scenarios. The local-level simulation indicates a substantial difference in exposure-dose levels between wealthy and EJ communities. The application of the EJ-ADD approach can link EJ factors to exposure dose estimate and identify potential EJ impacts on dose-related variables.
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spelling pubmed-52952752017-02-07 Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates Huang, Hongtai Barzyk, Timothy M. Int J Environ Res Public Health Article Many different quantitative techniques have been developed to either assess Environmental Justice (EJ) issues or estimate exposure and dose for risk assessment. However, very few approaches have been applied to link EJ factors to exposure dose estimate and identify potential impacts of EJ factors on dose-related variables. The purpose of this study is to identify quantitative approaches that incorporate conventional risk assessment (RA) dose modeling and cumulative risk assessment (CRA) considerations of disproportionate environmental exposure. We apply the Average Daily Dose (ADD) model, which has been commonly used in RA, to better understand impacts of EJ indicators upon exposure dose estimates and dose-related variables, termed the Environmental-Justice-Average-Daily-Dose (EJ-ADD) approach. On the U.S. nationwide census tract-level, we defined and quantified two EJ indicators (poverty and race/ethnicity) using an EJ scoring method to examine their relation to census tract-level multi-chemical exposure dose estimates. Pollutant doses for each tract were calculated using the ADD model, and EJ scores were assigned to each tract based on poverty- or race-related population percentages. Single- and multiple-chemical ADD values were matched to the tract-level EJ scores to analyze disproportionate dose relationships and contributing EJ factors. We found that when both EJ indicators were examined simultaneously, ADD for all pollutants generally increased with larger EJ scores. To demonstrate the utility of using EJ-ADD on the local scale, we approximated ADD levels of lead via soil/dust ingestion for simulated communities with different EJ-related scenarios. The local-level simulation indicates a substantial difference in exposure-dose levels between wealthy and EJ communities. The application of the EJ-ADD approach can link EJ factors to exposure dose estimate and identify potential EJ impacts on dose-related variables. MDPI 2016-12-28 2017-01 /pmc/articles/PMC5295275/ /pubmed/28036053 http://dx.doi.org/10.3390/ijerph14010024 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Huang, Hongtai
Barzyk, Timothy M.
Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates
title Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates
title_full Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates
title_fullStr Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates
title_full_unstemmed Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates
title_short Connecting the Dots: Linking Environmental Justice Indicators to Daily Dose Model Estimates
title_sort connecting the dots: linking environmental justice indicators to daily dose model estimates
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5295275/
https://www.ncbi.nlm.nih.gov/pubmed/28036053
http://dx.doi.org/10.3390/ijerph14010024
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