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A Model Using Local Weather Data to Determine the Effective Sampling Volume for PCB Congeners Collected on Passive Air Samplers
[Image: see text] We have developed and evaluated a mathematical model to determine the effective sampling volumes (V(eff)) of PCBs and similar compounds captured using polyurethane foam passive air samplers (PUF–PAS). We account for the variability in wind speed, air temperature, and equilibrium pa...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4935961/ https://www.ncbi.nlm.nih.gov/pubmed/26963482 http://dx.doi.org/10.1021/acs.est.6b00319 |
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author | Herkert, Nicholas J. Martinez, Andres Hornbuckle, Keri C. |
author_facet | Herkert, Nicholas J. Martinez, Andres Hornbuckle, Keri C. |
author_sort | Herkert, Nicholas J. |
collection | PubMed |
description | [Image: see text] We have developed and evaluated a mathematical model to determine the effective sampling volumes (V(eff)) of PCBs and similar compounds captured using polyurethane foam passive air samplers (PUF–PAS). We account for the variability in wind speed, air temperature, and equilibrium partitioning over the course of the deployment of the samplers. The model, provided as an annotated Matlab script, predicts the V(eff) as a function of physical-chemical properties of each compound and meteorology from the closest Integrated Surface Database (ISD) data set obtained through NOAA’s National Centers for Environmental Information (NCEI). The model was developed to be user-friendly, only requiring basic Matlab knowledge. To illustrate the effectiveness of the model, we evaluated three independent data sets of airborne PCBs simultaneously collected using passive and active samplers: at sites in Chicago, Lancaster, UK, and Toronto, Canada. The model provides V(eff) values comparable to those using depuration compounds and calibration against active samplers, yielding an average congener specific concentration method ratio (active/passive) of 1.1 ± 1.2. We applied the model to PUF–PAS samples collected in Chicago and show that previous methods can underestimate concentrations of PCBs by up to 40%, especially for long deployments, deployments conducted under warming conditions, and compounds with log Koa values less than 8. |
format | Online Article Text |
id | pubmed-4935961 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-49359612016-07-08 A Model Using Local Weather Data to Determine the Effective Sampling Volume for PCB Congeners Collected on Passive Air Samplers Herkert, Nicholas J. Martinez, Andres Hornbuckle, Keri C. Environ Sci Technol [Image: see text] We have developed and evaluated a mathematical model to determine the effective sampling volumes (V(eff)) of PCBs and similar compounds captured using polyurethane foam passive air samplers (PUF–PAS). We account for the variability in wind speed, air temperature, and equilibrium partitioning over the course of the deployment of the samplers. The model, provided as an annotated Matlab script, predicts the V(eff) as a function of physical-chemical properties of each compound and meteorology from the closest Integrated Surface Database (ISD) data set obtained through NOAA’s National Centers for Environmental Information (NCEI). The model was developed to be user-friendly, only requiring basic Matlab knowledge. To illustrate the effectiveness of the model, we evaluated three independent data sets of airborne PCBs simultaneously collected using passive and active samplers: at sites in Chicago, Lancaster, UK, and Toronto, Canada. The model provides V(eff) values comparable to those using depuration compounds and calibration against active samplers, yielding an average congener specific concentration method ratio (active/passive) of 1.1 ± 1.2. We applied the model to PUF–PAS samples collected in Chicago and show that previous methods can underestimate concentrations of PCBs by up to 40%, especially for long deployments, deployments conducted under warming conditions, and compounds with log Koa values less than 8. American Chemical Society 2016-03-10 2016-07-05 /pmc/articles/PMC4935961/ /pubmed/26963482 http://dx.doi.org/10.1021/acs.est.6b00319 Text en Copyright © 2016 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Herkert, Nicholas J. Martinez, Andres Hornbuckle, Keri C. A Model Using Local Weather Data to Determine the Effective Sampling Volume for PCB Congeners Collected on Passive Air Samplers |
title | A Model Using Local Weather Data to Determine the
Effective Sampling Volume for PCB Congeners Collected on Passive Air
Samplers |
title_full | A Model Using Local Weather Data to Determine the
Effective Sampling Volume for PCB Congeners Collected on Passive Air
Samplers |
title_fullStr | A Model Using Local Weather Data to Determine the
Effective Sampling Volume for PCB Congeners Collected on Passive Air
Samplers |
title_full_unstemmed | A Model Using Local Weather Data to Determine the
Effective Sampling Volume for PCB Congeners Collected on Passive Air
Samplers |
title_short | A Model Using Local Weather Data to Determine the
Effective Sampling Volume for PCB Congeners Collected on Passive Air
Samplers |
title_sort | model using local weather data to determine the
effective sampling volume for pcb congeners collected on passive air
samplers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4935961/ https://www.ncbi.nlm.nih.gov/pubmed/26963482 http://dx.doi.org/10.1021/acs.est.6b00319 |
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