Do time-averaged, whole-building, effective volatile organic compound (VOC) emissions depend on the air exchange rate? A statistical analysis of trends for 46 VOCs in U.S. offices
We used existing data to develop distributions of time‐averaged air exchange rates (AER), whole‐building ‘effective’ emission rates of volatile organic compounds (VOC), and other variables for use in Monte Carlo analyses of U.S. offices. With these, we explored whether long‐term VOC emission rates w...
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Veröffentlicht in: | Indoor air 2016-08, Vol.26 (4), p.642-659 |
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description | We used existing data to develop distributions of time‐averaged air exchange rates (AER), whole‐building ‘effective’ emission rates of volatile organic compounds (VOC), and other variables for use in Monte Carlo analyses of U.S. offices. With these, we explored whether long‐term VOC emission rates were related to the AER over the sector, as has been observed in the short term for some VOCs in single buildings. We fit and compared two statistical models to the data. In the independent emissions model (IEM), emissions were unaffected by other variables, while in the dependent emissions model (DEM), emissions responded to the AER via coupling through a conceptual boundary layer between the air and a lumped emission source. For 20 of 46 VOCs, the DEM was preferable to the IEM and emission rates, though variable, were higher in buildings with higher AERs. Most oxygenated VOCs and some alkanes were well fit by the DEM, while nearly all aromatics and halocarbons were independent. Trends by vapor pressure suggested multiple mechanisms could be involved. The factors of temperature, relative humidity, and building age were almost never associated with effective emission rates. Our findings suggest that effective emissions in real commercial buildings will be difficult to predict from deterministic experiments or models. |
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A statistical analysis of trends for 46 VOCs in U.S. offices</title><source>MEDLINE</source><source>Wiley Online Library Journals Frontfile Complete</source><creator>Rackes, A. ; Waring, M. S.</creator><creatorcontrib>Rackes, A. ; Waring, M. S.</creatorcontrib><description>We used existing data to develop distributions of time‐averaged air exchange rates (AER), whole‐building ‘effective’ emission rates of volatile organic compounds (VOC), and other variables for use in Monte Carlo analyses of U.S. offices. With these, we explored whether long‐term VOC emission rates were related to the AER over the sector, as has been observed in the short term for some VOCs in single buildings. We fit and compared two statistical models to the data. In the independent emissions model (IEM), emissions were unaffected by other variables, while in the dependent emissions model (DEM), emissions responded to the AER via coupling through a conceptual boundary layer between the air and a lumped emission source. For 20 of 46 VOCs, the DEM was preferable to the IEM and emission rates, though variable, were higher in buildings with higher AERs. Most oxygenated VOCs and some alkanes were well fit by the DEM, while nearly all aromatics and halocarbons were independent. Trends by vapor pressure suggested multiple mechanisms could be involved. The factors of temperature, relative humidity, and building age were almost never associated with effective emission rates. Our findings suggest that effective emissions in real commercial buildings will be difficult to predict from deterministic experiments or models.</description><identifier>ISSN: 0905-6947</identifier><identifier>EISSN: 1600-0668</identifier><identifier>DOI: 10.1111/ina.12224</identifier><identifier>PMID: 26010216</identifier><language>eng</language><publisher>England: Blackwell Publishing Ltd</publisher><subject>Air Pollution, Indoor - analysis ; Chemical sources ; Commercial buildings ; Emission ; Emissions ; Emissions model ; Environmental Monitoring ; Exchange ; Filtration - statistics & numerical data ; Indoor air quality ; Mathematical models ; Monte Carlo ; Monte Carlo Method ; Office buildings ; Offices ; Organic compounds ; Risk assessment ; Statistical analysis ; United States ; Ventilation rate ; VOCs ; Volatile compounds ; Volatile organic compounds ; Volatile Organic Compounds - analysis ; Workplace - statistics & numerical data</subject><ispartof>Indoor air, 2016-08, Vol.26 (4), p.642-659</ispartof><rights>2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd</rights><rights>2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.</rights><rights>Copyright © 2016 John Wiley & Sons A/S</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fina.12224$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fina.12224$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,776,780,1411,27903,27904,45553,45554</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26010216$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rackes, A.</creatorcontrib><creatorcontrib>Waring, M. S.</creatorcontrib><title>Do time-averaged, whole-building, effective volatile organic compound (VOC) emissions depend on the air exchange rate? A statistical analysis of trends for 46 VOCs in U.S. offices</title><title>Indoor air</title><addtitle>Indoor Air</addtitle><description>We used existing data to develop distributions of time‐averaged air exchange rates (AER), whole‐building ‘effective’ emission rates of volatile organic compounds (VOC), and other variables for use in Monte Carlo analyses of U.S. offices. With these, we explored whether long‐term VOC emission rates were related to the AER over the sector, as has been observed in the short term for some VOCs in single buildings. We fit and compared two statistical models to the data. In the independent emissions model (IEM), emissions were unaffected by other variables, while in the dependent emissions model (DEM), emissions responded to the AER via coupling through a conceptual boundary layer between the air and a lumped emission source. For 20 of 46 VOCs, the DEM was preferable to the IEM and emission rates, though variable, were higher in buildings with higher AERs. Most oxygenated VOCs and some alkanes were well fit by the DEM, while nearly all aromatics and halocarbons were independent. Trends by vapor pressure suggested multiple mechanisms could be involved. The factors of temperature, relative humidity, and building age were almost never associated with effective emission rates. Our findings suggest that effective emissions in real commercial buildings will be difficult to predict from deterministic experiments or models.</description><subject>Air Pollution, Indoor - analysis</subject><subject>Chemical sources</subject><subject>Commercial buildings</subject><subject>Emission</subject><subject>Emissions</subject><subject>Emissions model</subject><subject>Environmental Monitoring</subject><subject>Exchange</subject><subject>Filtration - statistics & numerical data</subject><subject>Indoor air quality</subject><subject>Mathematical models</subject><subject>Monte Carlo</subject><subject>Monte Carlo Method</subject><subject>Office buildings</subject><subject>Offices</subject><subject>Organic compounds</subject><subject>Risk assessment</subject><subject>Statistical analysis</subject><subject>United States</subject><subject>Ventilation rate</subject><subject>VOCs</subject><subject>Volatile compounds</subject><subject>Volatile organic compounds</subject><subject>Volatile Organic Compounds - analysis</subject><subject>Workplace - statistics & numerical data</subject><issn>0905-6947</issn><issn>1600-0668</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNks9u1DAQxiMEokvhwAugkbgUqdn6XxznVK22sBSVVgIKR8txJrsu2Xixk7b7XLwgplt64FRfbHl-3yfNfJNlrymZ0nSOXG-mlDEmnmQTKgnJiZTqaTYhFSlyWYlyL3sR4xUhtOQVf57tMUkoYVROst8nHga3xtxcYzBLbA7hZuU7zOvRdY3rl4eAbYt2cNcI174zg-sQfFia3lmwfr3xY9_AwfeL-TvAtYvR-T5CgxtM376HYYVgXAC8tSvTLxGCGfAYZhCH5BUHZ00HpjfdNroIvoUhJGWE1gcQEpJvBNfD5fTrNFVbZzG-zJ61pov46v7ezy4_vP82_5ifXSxO57Oz3BWMi1wRWVtiiKKVIIqZUrVYNYIRzgtha1pLw6tKVrwtGlvUaErLG2uNoIJWKg1qPzvY-W6C_zViHHTqz2LXmR79GDVVvJBEKvEYlCjJKsGLx6BCyVKUIqFv_0Ov_BjSrHYUI5ViKlFv7qmxXmOjN8GtTdjqfyEn4GgH3KTstg91SvTf7dFpe_Td9ujT89ndIynynSIFhLcPChN-alnystA_zhf604KV4jP7ok_4H2w_w9Y</recordid><startdate>201608</startdate><enddate>201608</enddate><creator>Rackes, A.</creator><creator>Waring, M. S.</creator><general>Blackwell Publishing Ltd</general><general>Hindawi Limited</general><scope>BSCLL</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>7ST</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>KR7</scope><scope>SOI</scope><scope>7X8</scope><scope>7U7</scope></search><sort><creationdate>201608</creationdate><title>Do time-averaged, whole-building, effective volatile organic compound (VOC) emissions depend on the air exchange rate? A statistical analysis of trends for 46 VOCs in U.S. offices</title><author>Rackes, A. ; Waring, M. 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S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Do time-averaged, whole-building, effective volatile organic compound (VOC) emissions depend on the air exchange rate? A statistical analysis of trends for 46 VOCs in U.S. offices</atitle><jtitle>Indoor air</jtitle><addtitle>Indoor Air</addtitle><date>2016-08</date><risdate>2016</risdate><volume>26</volume><issue>4</issue><spage>642</spage><epage>659</epage><pages>642-659</pages><issn>0905-6947</issn><eissn>1600-0668</eissn><abstract>We used existing data to develop distributions of time‐averaged air exchange rates (AER), whole‐building ‘effective’ emission rates of volatile organic compounds (VOC), and other variables for use in Monte Carlo analyses of U.S. offices. With these, we explored whether long‐term VOC emission rates were related to the AER over the sector, as has been observed in the short term for some VOCs in single buildings. We fit and compared two statistical models to the data. In the independent emissions model (IEM), emissions were unaffected by other variables, while in the dependent emissions model (DEM), emissions responded to the AER via coupling through a conceptual boundary layer between the air and a lumped emission source. For 20 of 46 VOCs, the DEM was preferable to the IEM and emission rates, though variable, were higher in buildings with higher AERs. Most oxygenated VOCs and some alkanes were well fit by the DEM, while nearly all aromatics and halocarbons were independent. Trends by vapor pressure suggested multiple mechanisms could be involved. The factors of temperature, relative humidity, and building age were almost never associated with effective emission rates. Our findings suggest that effective emissions in real commercial buildings will be difficult to predict from deterministic experiments or models.</abstract><cop>England</cop><pub>Blackwell Publishing Ltd</pub><pmid>26010216</pmid><doi>10.1111/ina.12224</doi><tpages>18</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Air Pollution, Indoor - analysis Chemical sources Commercial buildings Emission Emissions Emissions model Environmental Monitoring Exchange Filtration - statistics & numerical data Indoor air quality Mathematical models Monte Carlo Monte Carlo Method Office buildings Offices Organic compounds Risk assessment Statistical analysis United States Ventilation rate VOCs Volatile compounds Volatile organic compounds Volatile Organic Compounds - analysis Workplace - statistics & numerical data |
title | Do time-averaged, whole-building, effective volatile organic compound (VOC) emissions depend on the air exchange rate? A statistical analysis of trends for 46 VOCs in U.S. offices |
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