Modeling Exposure Close to Air Pollution Sources in Naturally Ventilated Residences: Association of Turbulent Diffusion Coefficient with Air Change Rate

被引:51
作者
Cheng, Kai-Chung [1 ]
Acevedo-Bolton, Viviana [1 ]
Jiang, Ruo-Ting [1 ]
Klepeis, Neil E. [1 ]
Ott, Wayne R. [1 ]
Fringer, Oliver B. [1 ]
Hildemann, Lynn M. [1 ]
机构
[1] Stanford Univ, Dept Civil & Environm Engn, Stanford, CA 94305 USA
关键词
PARTICULATE MATTER; INDOOR POLLUTANT; EXCHANGE-RATES; ROOM;
D O I
10.1021/es103080p
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
For modeling exposure close to an indoor air pollution source, an isotropic turbulent diffusion coefficient is used to represent the average spread of emissions. However, its magnitude indoors has been difficult to assess experimentally due to limitations in the number of monitors available. We used 30-37 real-time monitors to simultaneously measure CO at different: angles and distances from a continuous indoor point source. For 11 experiments involving two houses, with natural ventilation conditions ranging from <0.2 to >5 air changes per h, an eddy diffusion model was used to estimate the turbulent diffusion coefficients, which ranged from 0.001 to 0.013 m(2) s(-1). The model reproduced observed concentrations with reasonable accuracy over radial distances of 0.25-5.0 m. The air change rate, as measured using a SF6 tracer gas release, showed a significant positive linear correlation with the air mixing rate, defined as the turbulent diffusion coefficient divided by a squared length scale representing the room size. The ability to estimate the indoor turbulent diffusion coefficient using two readily measurable parameters (air change rate and room dimensions) is useful for accurately modeling exposures in close proximity to an indoor pollution source.
引用
收藏
页码:4016 / 4022
页数:7
相关论文
共 42 条
  • [1] Acevedo-Bolton V., 2010, THESIS STANFORD U ST
  • [2] MIXING OF A POINT-SOURCE POLLUTANT BY NATURAL-CONVECTION FLOW WITHIN A ROOM
    BAUGHMAN, AV
    GADGIL, AJ
    NAZAROFF, WW
    [J]. INDOOR AIR-INTERNATIONAL JOURNAL OF INDOOR AIR QUALITY AND CLIMATE, 1994, 4 (02): : 114 - 122
  • [3] Bennett JS, 2003, AIHA J-J SCI OCCUP E, V64, P739, DOI 10.1080/15428110308984868
  • [4] A population exposure model for particulate matter:: case study results for PM2.5 in Philadelphia, PA
    Burke, JM
    Zufall, MJ
    Özkaynak, H
    [J]. JOURNAL OF EXPOSURE ANALYSIS AND ENVIRONMENTAL EPIDEMIOLOGY, 2001, 11 (06): : 470 - 489
  • [5] Charbeneau R. J., 2000, GROUNDWATER HYDRAULI, P546
  • [6] Model-based reconstruction of the time response of electrochemical air pollutant monitors to rapidly varying concentrations
    Cheng, Kai-Chung
    Acevedo-Bolton, Viviana
    Jiang, Ruo-Ting
    Klepeis, Neil E.
    Ott, Wayne R.
    Hildemann, Lynn M.
    [J]. JOURNAL OF ENVIRONMENTAL MONITORING, 2010, 12 (04): : 846 - 853
  • [7] Conroy LM., 1995, Appl Occup Environ Hyg, V10, P620, DOI [10.1080/1047322X.1995.10387655, DOI 10.1080/1047322X.1995.10387655]
  • [8] CRANK J, 1975, MATH DIFFUSION, P29, DOI DOI 10.1016/0306-4549(77)90072-X
  • [9] Evaluating Indoor Exposure Modeling Alternatives for LCA: A Case Study in the Vehicle Repair Industry
    Demou, Evangelia
    Hellweg, Stefanie
    Wilson, Michael P.
    Hammond, S. Katharine
    McKone, Thomas E.
    [J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2009, 43 (15) : 5804 - 5810
  • [10] MIXING OF A POINT-SOURCE INDOOR POLLUTANT BY FORCED-CONVECTION
    DRESCHER, AC
    LOBASCIO, C
    GADGIL, AJ
    NAZAROFF, WW
    [J]. INDOOR AIR-INTERNATIONAL JOURNAL OF INDOOR AIR QUALITY AND CLIMATE, 1995, 5 (03): : 204 - 214