Modeling indoor particulate exposures in inner-city school classrooms
Outdoor air pollution penetrates buildings and contributes to total indoor exposures. We investigated the relationship of indoor to outdoor particulate matter in inner-city school classrooms. The School Inner City Asthma Study investigates the effect of classroom-based environmental exposures on stu...
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| Veröffentlicht in: | Journal of exposure science & environmental epidemiology 2017-09, Vol.27 (5), p.451-457 |
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| creator | Gaffin, Jonathan M Petty, Carter R Hauptman, Marissa Kang, Choong-Min Wolfson, Jack M Abu Awad, Yara Di, Qian Lai, Peggy S Sheehan, William J Baxi, Sachin Coull, Brent A Schwartz, Joel D Gold, Diane R Koutrakis, Petros Phipatanakul, Wanda |
| description | Outdoor air pollution penetrates buildings and contributes to total indoor exposures. We investigated the relationship of indoor to outdoor particulate matter in inner-city school classrooms. The School Inner City Asthma Study investigates the effect of classroom-based environmental exposures on students with asthma in the northeast United States. Mixed effects linear models were used to determine the relationships between indoor PM
2.5
(particulate matter) and black carbon (BC), and their corresponding outdoor concentrations, and to develop a model for predicting exposures to these pollutants. The indoor–outdoor sulfur ratio was used as an infiltration factor of outdoor fine particles. Weeklong concentrations of PM
2.5
and BC in 199 samples from 136 classrooms (30 school buildings) were compared with those measured at a central monitoring site averaged over the same timeframe. Mixed effects regression models found significant random intercept and slope effects, which indicate that: (1) there are important PM
2.5
sources in classrooms; (2) the penetration of outdoor PM
2.5
particles varies by school and (3) the site-specific outside PM
2.5
levels (inferred by the models) differ from those observed at the central monitor site. Similar results were found for BC except for lack of indoor sources. The fitted predictions from the sulfur-adjusted models were moderately predictive of observed indoor pollutant levels (out of sample correlations: PM
2.5
:
r
2
=0.68, BC;
r
2
=0.61). Our results suggest that PM
2.5
has important classroom sources, which vary by school. Furthermore, using these mixed effects models, classroom exposures can be accurately predicted for dates when central site measures are available but indoor measures are not available. |
| doi_str_mv | 10.1038/jes.2016.52 |
| format | Article |
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2.5
(particulate matter) and black carbon (BC), and their corresponding outdoor concentrations, and to develop a model for predicting exposures to these pollutants. The indoor–outdoor sulfur ratio was used as an infiltration factor of outdoor fine particles. Weeklong concentrations of PM
2.5
and BC in 199 samples from 136 classrooms (30 school buildings) were compared with those measured at a central monitoring site averaged over the same timeframe. Mixed effects regression models found significant random intercept and slope effects, which indicate that: (1) there are important PM
2.5
sources in classrooms; (2) the penetration of outdoor PM
2.5
particles varies by school and (3) the site-specific outside PM
2.5
levels (inferred by the models) differ from those observed at the central monitor site. Similar results were found for BC except for lack of indoor sources. The fitted predictions from the sulfur-adjusted models were moderately predictive of observed indoor pollutant levels (out of sample correlations: PM
2.5
:
r
2
=0.68, BC;
r
2
=0.61). Our results suggest that PM
2.5
has important classroom sources, which vary by school. Furthermore, using these mixed effects models, classroom exposures can be accurately predicted for dates when central site measures are available but indoor measures are not available.</description><identifier>ISSN: 1559-0631</identifier><identifier>EISSN: 1559-064X</identifier><identifier>DOI: 10.1038/jes.2016.52</identifier><identifier>PMID: 27599884</identifier><language>eng</language><publisher>New York: Nature Publishing Group US</publisher><subject>692/699/249/2510/31 ; 692/700/1720 ; 704/106/694/1108 ; 704/172/169/895 ; Air pollution ; Air Pollution, Indoor ; Airborne particulates ; Asthma ; Black carbon ; Buildings ; Classrooms ; Control ; Environmental aspects ; Environmental Exposure ; Environmental monitoring ; Epidemiology ; Exposure ; Health aspects ; Indoor air pollution ; Indoor air quality ; Indoor environments ; Infiltration ; Inner city ; Medicine ; Medicine & Public Health ; Models, Theoretical ; original-article ; Outdoor air quality ; Particulate emissions ; Particulate matter ; Particulate Matter - analysis ; Pollutants ; Pollution levels ; Predictions ; Regression analysis ; Regression models ; School buildings ; Schools ; Studies ; Sulfur ; Urban Population</subject><ispartof>Journal of exposure science & environmental epidemiology, 2017-09, Vol.27 (5), p.451-457</ispartof><rights>Nature America, Inc., part of Springer Nature. 2017</rights><rights>COPYRIGHT 2017 Nature Publishing Group</rights><rights>Copyright Nature Publishing Group Sep 2017</rights><rights>Nature America, Inc., part of Springer Nature. 2017.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c572t-a8f17f502e4ed664b8bb7830e01baebcee5069ec2dc27c19ad90a1b59711c4743</citedby><cites>FETCH-LOGICAL-c572t-a8f17f502e4ed664b8bb7830e01baebcee5069ec2dc27c19ad90a1b59711c4743</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/jes.2016.52$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/jes.2016.52$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>230,314,776,780,881,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27599884$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gaffin, Jonathan M</creatorcontrib><creatorcontrib>Petty, Carter R</creatorcontrib><creatorcontrib>Hauptman, Marissa</creatorcontrib><creatorcontrib>Kang, Choong-Min</creatorcontrib><creatorcontrib>Wolfson, Jack M</creatorcontrib><creatorcontrib>Abu Awad, Yara</creatorcontrib><creatorcontrib>Di, Qian</creatorcontrib><creatorcontrib>Lai, Peggy S</creatorcontrib><creatorcontrib>Sheehan, William J</creatorcontrib><creatorcontrib>Baxi, Sachin</creatorcontrib><creatorcontrib>Coull, Brent A</creatorcontrib><creatorcontrib>Schwartz, Joel D</creatorcontrib><creatorcontrib>Gold, Diane R</creatorcontrib><creatorcontrib>Koutrakis, Petros</creatorcontrib><creatorcontrib>Phipatanakul, Wanda</creatorcontrib><title>Modeling indoor particulate exposures in inner-city school classrooms</title><title>Journal of exposure science & environmental epidemiology</title><addtitle>J Expo Sci Environ Epidemiol</addtitle><addtitle>J Expo Sci Environ Epidemiol</addtitle><description>Outdoor air pollution penetrates buildings and contributes to total indoor exposures. We investigated the relationship of indoor to outdoor particulate matter in inner-city school classrooms. The School Inner City Asthma Study investigates the effect of classroom-based environmental exposures on students with asthma in the northeast United States. Mixed effects linear models were used to determine the relationships between indoor PM
2.5
(particulate matter) and black carbon (BC), and their corresponding outdoor concentrations, and to develop a model for predicting exposures to these pollutants. The indoor–outdoor sulfur ratio was used as an infiltration factor of outdoor fine particles. Weeklong concentrations of PM
2.5
and BC in 199 samples from 136 classrooms (30 school buildings) were compared with those measured at a central monitoring site averaged over the same timeframe. Mixed effects regression models found significant random intercept and slope effects, which indicate that: (1) there are important PM
2.5
sources in classrooms; (2) the penetration of outdoor PM
2.5
particles varies by school and (3) the site-specific outside PM
2.5
levels (inferred by the models) differ from those observed at the central monitor site. Similar results were found for BC except for lack of indoor sources. The fitted predictions from the sulfur-adjusted models were moderately predictive of observed indoor pollutant levels (out of sample correlations: PM
2.5
:
r
2
=0.68, BC;
r
2
=0.61). Our results suggest that PM
2.5
has important classroom sources, which vary by school. Furthermore, using these mixed effects models, classroom exposures can be accurately predicted for dates when central site measures are available but indoor measures are not available.</description><subject>692/699/249/2510/31</subject><subject>692/700/1720</subject><subject>704/106/694/1108</subject><subject>704/172/169/895</subject><subject>Air pollution</subject><subject>Air Pollution, Indoor</subject><subject>Airborne particulates</subject><subject>Asthma</subject><subject>Black carbon</subject><subject>Buildings</subject><subject>Classrooms</subject><subject>Control</subject><subject>Environmental aspects</subject><subject>Environmental Exposure</subject><subject>Environmental monitoring</subject><subject>Epidemiology</subject><subject>Exposure</subject><subject>Health aspects</subject><subject>Indoor air pollution</subject><subject>Indoor air quality</subject><subject>Indoor environments</subject><subject>Infiltration</subject><subject>Inner city</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Models, Theoretical</subject><subject>original-article</subject><subject>Outdoor air quality</subject><subject>Particulate emissions</subject><subject>Particulate matter</subject><subject>Particulate Matter - analysis</subject><subject>Pollutants</subject><subject>Pollution levels</subject><subject>Predictions</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>School buildings</subject><subject>Schools</subject><subject>Studies</subject><subject>Sulfur</subject><subject>Urban 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aspects</topic><topic>Environmental Exposure</topic><topic>Environmental monitoring</topic><topic>Epidemiology</topic><topic>Exposure</topic><topic>Health aspects</topic><topic>Indoor air pollution</topic><topic>Indoor air quality</topic><topic>Indoor environments</topic><topic>Infiltration</topic><topic>Inner city</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Models, Theoretical</topic><topic>original-article</topic><topic>Outdoor air quality</topic><topic>Particulate emissions</topic><topic>Particulate matter</topic><topic>Particulate Matter - analysis</topic><topic>Pollutants</topic><topic>Pollution levels</topic><topic>Predictions</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>School buildings</topic><topic>Schools</topic><topic>Studies</topic><topic>Sulfur</topic><topic>Urban Population</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gaffin, Jonathan 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environmental epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gaffin, Jonathan M</au><au>Petty, Carter R</au><au>Hauptman, Marissa</au><au>Kang, Choong-Min</au><au>Wolfson, Jack M</au><au>Abu Awad, Yara</au><au>Di, Qian</au><au>Lai, Peggy S</au><au>Sheehan, William J</au><au>Baxi, Sachin</au><au>Coull, Brent A</au><au>Schwartz, Joel D</au><au>Gold, Diane R</au><au>Koutrakis, Petros</au><au>Phipatanakul, Wanda</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling indoor particulate exposures in inner-city school classrooms</atitle><jtitle>Journal of exposure science & environmental epidemiology</jtitle><stitle>J Expo Sci Environ Epidemiol</stitle><addtitle>J Expo Sci Environ Epidemiol</addtitle><date>2017-09-01</date><risdate>2017</risdate><volume>27</volume><issue>5</issue><spage>451</spage><epage>457</epage><pages>451-457</pages><issn>1559-0631</issn><eissn>1559-064X</eissn><abstract>Outdoor air pollution penetrates buildings and contributes to total indoor exposures. We investigated the relationship of indoor to outdoor particulate matter in inner-city school classrooms. The School Inner City Asthma Study investigates the effect of classroom-based environmental exposures on students with asthma in the northeast United States. Mixed effects linear models were used to determine the relationships between indoor PM
2.5
(particulate matter) and black carbon (BC), and their corresponding outdoor concentrations, and to develop a model for predicting exposures to these pollutants. The indoor–outdoor sulfur ratio was used as an infiltration factor of outdoor fine particles. Weeklong concentrations of PM
2.5
and BC in 199 samples from 136 classrooms (30 school buildings) were compared with those measured at a central monitoring site averaged over the same timeframe. Mixed effects regression models found significant random intercept and slope effects, which indicate that: (1) there are important PM
2.5
sources in classrooms; (2) the penetration of outdoor PM
2.5
particles varies by school and (3) the site-specific outside PM
2.5
levels (inferred by the models) differ from those observed at the central monitor site. Similar results were found for BC except for lack of indoor sources. The fitted predictions from the sulfur-adjusted models were moderately predictive of observed indoor pollutant levels (out of sample correlations: PM
2.5
:
r
2
=0.68, BC;
r
2
=0.61). Our results suggest that PM
2.5
has important classroom sources, which vary by school. Furthermore, using these mixed effects models, classroom exposures can be accurately predicted for dates when central site measures are available but indoor measures are not available.</abstract><cop>New York</cop><pub>Nature Publishing Group US</pub><pmid>27599884</pmid><doi>10.1038/jes.2016.52</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Journal of exposure science & environmental epidemiology, 2017-09, Vol.27 (5), p.451-457 |
| issn | 1559-0631 1559-064X |
| language | eng |
| recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5340641 |
| source | MEDLINE; SpringerLink Journals - AutoHoldings |
| subjects | 692/699/249/2510/31 692/700/1720 704/106/694/1108 704/172/169/895 Air pollution Air Pollution, Indoor Airborne particulates Asthma Black carbon Buildings Classrooms Control Environmental aspects Environmental Exposure Environmental monitoring Epidemiology Exposure Health aspects Indoor air pollution Indoor air quality Indoor environments Infiltration Inner city Medicine Medicine & Public Health Models, Theoretical original-article Outdoor air quality Particulate emissions Particulate matter Particulate Matter - analysis Pollutants Pollution levels Predictions Regression analysis Regression models School buildings Schools Studies Sulfur Urban Population |
| title | Modeling indoor particulate exposures in inner-city school classrooms |
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