Literature DB >> 15138449

Influence of ambient (outdoor) sources on residential indoor and personal PM2.5 concentrations: analyses of RIOPA data.

Qing Yu Meng1, Barbara J Turpin, Leo Korn, Clifford P Weisel, Maria Morandi, Steven Colome, Junfeng Jim Zhang, Thomas Stock, Dalia Spektor, Arthur Winer, Lin Zhang, Jong Hoon Lee, Robert Giovanetti, William Cui, Jaymin Kwon, Shahnaz Alimokhtari, Derek Shendell, Jennifer Jones, Corice Farrar, Silvia Maberti.   

Abstract

The Relationship of Indoor, Outdoor and Personal Air (RIOPA) study was designed to investigate residential indoor, outdoor and personal exposures to several classes of air pollutants, including volatile organic compounds, carbonyls and fine particles (PM2.5). Samples were collected from summer, 1999 to spring, 2001 in Houston (TX), Los Angeles (CA) and Elizabeth (NJ). Indoor, outdoor and personal PM2.5 samples were collected at 212 nonsmoking residences, 162 of which were sampled twice. Some homes were chosen due to close proximity to ambient sources of one or more target analytes, while others were farther from sources. Median indoor, outdoor and personal PM2.5 mass concentrations for these three sites were 14.4, 15.5 and 31.4 microg/m3, respectively. The contributions of ambient (outdoor) and nonambient sources to indoor and personal concentrations were quantified using a single compartment box model with measured air exchange rate and a random component superposition (RCS) statistical model. The median contribution of ambient sources to indoor PM2.5 concentrations using the mass balance approach was estimated to be 56% for all study homes (63%, 52% and 33% for California, New Jersey and Texas study homes, respectively). Reasonable variations in model assumptions alter median ambient contributions by less than 20%. The mean of the distribution of ambient contributions across study homes agreed well for the mass balance and RCS models, but the distribution was somewhat broader when calculated using the mass balance model with measured air exchange rates.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 15138449     DOI: 10.1038/sj.jea.7500378

Source DB:  PubMed          Journal:  J Expo Anal Environ Epidemiol        ISSN: 1053-4245


  46 in total

1.  Interactions of physical, chemical, and biological weather calling for an integrated approach to assessment, forecasting, and communication of air quality.

Authors:  Thomas Klein; Jaakko Kukkonen; Aslög Dahl; Elissavet Bossioli; Alexander Baklanov; Aasmund Fahre Vik; Paul Agnew; Kostas D Karatzas; Mikhail Sofiev
Journal:  Ambio       Date:  2012-05-25       Impact factor: 5.129

2.  Source apportionment of indoor PM10 in Elderly Care Centre.

Authors:  M Almeida-Silva; T Faria; D Saraga; T Maggos; H T Wolterbeek; S M Almeida
Journal:  Environ Sci Pollut Res Int       Date:  2016-01-12       Impact factor: 4.223

3.  RM-DEMATEL: a new methodology to identify the key factors in PM2.5.

Authors:  Yafeng Chen; Jie Liu; Yunpeng Li; Rehan Sadiq; Yong Deng
Journal:  Environ Sci Pollut Res Int       Date:  2015-03-03       Impact factor: 4.223

4.  Effects of socioeconomic factors and human activities on children's PM(10) exposure in inner-city households in Korea.

Authors:  Hyaejeong Byun; Hyunjoo Bae; Dongjin Kim; Hosung Shin; Chungsik Yoon
Journal:  Int Arch Occup Environ Health       Date:  2010-03-26       Impact factor: 3.015

5.  PM2.5 of ambient origin: estimates and exposure errors relevant to PM epidemiology.

Authors:  Qing Yu Meng; Barbara J Turpin; Andrea Polidori; Jong Hoon Lee; Clifford Weisel; Maria Morandi; Steven Colome; Thomas Stock; Arthur Winer; Jenfeng Zhang
Journal:  Environ Sci Technol       Date:  2005-07-15       Impact factor: 9.028

6.  Exposure assessment, chemical characterization and source identification of PM2.5 for school children and industrial downwind residents in Guangzhou, China.

Authors:  Jia Wang; Senchao Lai; Zhaoyue Ke; Yingyi Zhang; Shasha Yin; Junyu Zheng
Journal:  Environ Geochem Health       Date:  2013-08-11       Impact factor: 4.609

7.  Sources of indoor air pollution in New York City residences of asthmatic children.

Authors:  Rima Habre; Brent Coull; Erin Moshier; James Godbold; Avi Grunin; Amit Nath; William Castro; Neil Schachter; Annette Rohr; Meyer Kattan; John Spengler; Petros Koutrakis
Journal:  J Expo Sci Environ Epidemiol       Date:  2013-10-30       Impact factor: 5.563

8.  Regression calibration in air pollution epidemiology with exposure estimated by spatio-temporal modeling.

Authors:  Donna Spiegelman
Journal:  Environmetrics       Date:  2014-01-21       Impact factor: 1.900

9.  Indoor and outdoor particulate matter and endotoxin concentrations in an intensely agricultural county.

Authors:  Brian T Pavilonis; T Renee Anthony; Patrick T O'Shaughnessy; Michael J Humann; James A Merchant; Genna Moore; Peter S Thorne; Clifford P Weisel; Wayne T Sanderson
Journal:  J Expo Sci Environ Epidemiol       Date:  2013-01-16       Impact factor: 5.563

10.  Predicting residential indoor concentrations of nitrogen dioxide, fine particulate matter, and elemental carbon using questionnaire and geographic information system based data.

Authors:  Lisa K Baxter; Jane E Clougherty; Chritopher J Paciorek; Rosalind J Wright; Jonathan I Levy
Journal:  Atmos Environ (1994)       Date:  2007-10       Impact factor: 4.798

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.