Impact of time–activity patterns on personal exposure to black carbon

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Title: Impact of time–activity patterns on personal exposure to black carbon
Authors: Dons, Evi1,2 evi.dons@vito.be, Int Panis, Luc1,2, Van Poppel, Martine1, Theunis, Jan1, Willems, Hanny1, Torfs, Rudi1, Wets, Geert2
Source: Atmospheric Environment. Jul2011, Vol. 45 Issue 21, p3594-3602. 9p.
Subjects: Carbon-black, Air pollution, Traffic engineering, Global Positioning System, Pocket computers, Participant observation
Abstract: Abstract: Time–activity patterns are an important determinant of personal exposure to air pollution. This is demonstrated by measuring personal exposure of 16 participants for 7 consecutive days: 8 couples of which one person was a full-time worker and the other was a homemaker; both had a very different time–activity pattern. We used portable aethalometers to measure black carbon levels with a high temporal resolution and a PDA with GPS-logger and electronic diary. The exposure to black carbon differs between partners by up to 30%, although they live at the same location. The activity contributing most to this difference is transport: Average exposure in transport is 6445 ng m−3, followed by exposure during shopping (2584 ng m−3). Average exposure is lowest while sleeping (1153 ng m−3) and when doing home-based activities (1223 ng m−3). Full-time workers spend almost twice as much time in transport as the homemakers. As a result of the study design we measured in several different homes, shops, cars, etc. enabling a better insight in true overall exposure in those microenvironments. Other factors influencing personal exposure are: background concentrations and location of residence in an urban, suburban or rural environment. [Copyright &y& Elsevier]
Copyright of Atmospheric Environment is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: Engineering Source
An: 60790800
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PubTypeId: academicJournal
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  Data: Impact of time–activity patterns on personal exposure to black carbon
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  Data: Abstract: Time–activity patterns are an important determinant of personal exposure to air pollution. This is demonstrated by measuring personal exposure of 16 participants for 7 consecutive days: 8 couples of which one person was a full-time worker and the other was a homemaker; both had a very different time–activity pattern. We used portable aethalometers to measure black carbon levels with a high temporal resolution and a PDA with GPS-logger and electronic diary. The exposure to black carbon differs between partners by up to 30%, although they live at the same location. The activity contributing most to this difference is transport: Average exposure in transport is 6445 ng m−3, followed by exposure during shopping (2584 ng m−3). Average exposure is lowest while sleeping (1153 ng m−3) and when doing home-based activities (1223 ng m−3). Full-time workers spend almost twice as much time in transport as the homemakers. As a result of the study design we measured in several different homes, shops, cars, etc. enabling a better insight in true overall exposure in those microenvironments. Other factors influencing personal exposure are: background concentrations and location of residence in an urban, suburban or rural environment. [Copyright &y& Elsevier]
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  Data: <i>Copyright of Atmospheric Environment is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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        Value: 10.1016/j.atmosenv.2011.03.064
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        Text: English
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      – SubjectFull: Air pollution
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      – SubjectFull: Traffic engineering
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      – TitleFull: Impact of time–activity patterns on personal exposure to black carbon
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              Text: Jul2011
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              Y: 2011
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