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Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data
Low-cost sensors can be used to improve the temporal and spatial resolution of an individual’s particulate matter (PM) intake dose assessment. In this work, personal activity monitors were used to measure heart rate (proxy for minute ventilation), and low-cost PM sensors were used to measure concent...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085603/ https://www.ncbi.nlm.nih.gov/pubmed/32143455 http://dx.doi.org/10.3390/s20051406 |
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author | Novak, Rok Kocman, David Robinson, Johanna Amalia Kanduč, Tjaša Sarigiannis, Dimosthenis Horvat, Milena |
author_facet | Novak, Rok Kocman, David Robinson, Johanna Amalia Kanduč, Tjaša Sarigiannis, Dimosthenis Horvat, Milena |
author_sort | Novak, Rok |
collection | PubMed |
description | Low-cost sensors can be used to improve the temporal and spatial resolution of an individual’s particulate matter (PM) intake dose assessment. In this work, personal activity monitors were used to measure heart rate (proxy for minute ventilation), and low-cost PM sensors were used to measure concentrations of PM. Intake dose was assessed as a product of PM concentration and minute ventilation, using four models with increasing complexity. The two models that use heart rate as a variable had the most consistent results and showed a good response to variations in PM concentrations and heart rate. On the other hand, the two models using generalized population data of minute ventilation expectably yielded more coarse information on the intake dose. Aggregated weekly intake doses did not vary significantly between the models (6–22%). Propagation of uncertainty was assessed for each model, however, differences in their underlying assumptions made them incomparable. The most complex minute ventilation model, with heart rate as a variable, has shown slightly lower uncertainty than the model using fewer variables. Similarly, among the non-heart rate models, the one using real-time activity data has less uncertainty. Minute ventilation models contribute the most to the overall intake dose model uncertainty, followed closely by the low-cost personal activity monitors. The lack of a common methodology to assess the intake dose and quantifying related uncertainties is evident and should be a subject of further research. |
format | Online Article Text |
id | pubmed-7085603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-70856032020-04-21 Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data Novak, Rok Kocman, David Robinson, Johanna Amalia Kanduč, Tjaša Sarigiannis, Dimosthenis Horvat, Milena Sensors (Basel) Article Low-cost sensors can be used to improve the temporal and spatial resolution of an individual’s particulate matter (PM) intake dose assessment. In this work, personal activity monitors were used to measure heart rate (proxy for minute ventilation), and low-cost PM sensors were used to measure concentrations of PM. Intake dose was assessed as a product of PM concentration and minute ventilation, using four models with increasing complexity. The two models that use heart rate as a variable had the most consistent results and showed a good response to variations in PM concentrations and heart rate. On the other hand, the two models using generalized population data of minute ventilation expectably yielded more coarse information on the intake dose. Aggregated weekly intake doses did not vary significantly between the models (6–22%). Propagation of uncertainty was assessed for each model, however, differences in their underlying assumptions made them incomparable. The most complex minute ventilation model, with heart rate as a variable, has shown slightly lower uncertainty than the model using fewer variables. Similarly, among the non-heart rate models, the one using real-time activity data has less uncertainty. Minute ventilation models contribute the most to the overall intake dose model uncertainty, followed closely by the low-cost personal activity monitors. The lack of a common methodology to assess the intake dose and quantifying related uncertainties is evident and should be a subject of further research. MDPI 2020-03-04 /pmc/articles/PMC7085603/ /pubmed/32143455 http://dx.doi.org/10.3390/s20051406 Text en © 2020 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 Novak, Rok Kocman, David Robinson, Johanna Amalia Kanduč, Tjaša Sarigiannis, Dimosthenis Horvat, Milena Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data |
title | Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data |
title_full | Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data |
title_fullStr | Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data |
title_full_unstemmed | Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data |
title_short | Comparing Airborne Particulate Matter Intake Dose Assessment Models Using Low-Cost Portable Sensor Data |
title_sort | comparing airborne particulate matter intake dose assessment models using low-cost portable sensor data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085603/ https://www.ncbi.nlm.nih.gov/pubmed/32143455 http://dx.doi.org/10.3390/s20051406 |
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