Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data

[1]  E. A. Sylvestre,et al.  Elimination of Linear Parameters in Nonlinear Regression , 1971 .

[2]  H. Britt,et al.  The Estimation of Parameters in Nonlinear, Implicit Models , 1973 .

[3]  John G. Watson,et al.  The effective variance weighting for least squares calculations applied to the mass balance receptor model , 1984 .

[4]  L. A. Currie,et al.  Interlaboratory comparison of source apportionment procedures: Results for simulated data sets☆☆☆ , 1984 .

[5]  John D. Spengler,et al.  A QUANTITATIVE ASSESSMENT OF SOURCE CONTRIBUTIONS TO INHALABLE PARTICULATE MATTER POLLUTION IN METROPOLITAN BOSTON , 1985 .

[6]  P. Hopke.  Receptor modeling in environmental chemistry , 1985 .

[7]  Lance Wallace,et al.  Emissions of volatile organic compounds from building materials and consumer products , 1987 .

[8]  Ronald C. Henry,et al.  Current factor analysis receptor models are ill-posed , 1987 .

[9]  Steve Selvin,et al.  Exposures to Hydrocarbon Components of Gasoline in the Petroleum Industry , 1987 .

[10]  Judith C. Chow,et al.  The USEPA/DRI chemical mass balance receptor model, CMB 7.0 , 1990 .

[11]  J. Samet,et al.  Variability of measures of exposure to environmental tobacco smoke in the home. , 1990, The American review of respiratory disease.

[12]  R. Henry,et al.  Extension of self-modeling curve resolution to mixtures of more than three components: Part 1. Finding the basic feasible region , 1990 .

[13]  B. Leaderer.  Assessing exposures to environmental tobacco smoke. , 1990, Risk analysis : an official publication of the Society for Risk Analysis.

[14]  James A. Wiley,et al.  Activity patterns of California residents , 1991 .

[15]  T. Cheng.  House staff work hours and moonlighting: what do residents want? A survey of pediatric residents in California. , 1991, American journal of diseases of children.

[16]  C. Proctor,et al.  A comparison of methods of assessing exposure to environmental tobacco smoke in non-smoking British women , 1991 .

[17]  C. W. Sweet,et al.  Toxic volatile organic compounds in urban air in Illinois , 1992 .

[18]  P. L. Jenkins,et al.  Activity patterns of Californians: Use of and proximity to indoor pollutant sources , 1992 .

[19]  Data base development and data analysis for California indoor exposure studies. Volume 1 and volume 2. Final report , 1993 .

[20]  C. Lewis,et al.  Vehicle-Related Hydrocarbon Source Compositions from Ambient Data: The GRACE/SAFER Method. , 1994, Environmental science & technology.

[21]  Chitsan Lin,et al.  Decay-adjusted chemical mass balance receptor modeling for volatile organic compounds , 1994 .

[22]  A. Hodgson,et al.  Toxic Volatile Organic Compounds in Environmental Tobacco Smoke:Emission Factors for Modeling Exposures of California Populations , 1994 .

[23]  P. Paatero,et al.  Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values† , 1994 .

[24]  P. Paatero,et al.  Source identification of bulk wet deposition in Finland by positive matrix factorization , 1995 .

[25]  D. Norbäck,et al.  Occupational exposure to volatile organic compounds (VOCs), and other air pollutants from the indoor application of water-based paints , 1995 .

[26]  Sandro Fuzzi,et al.  Organic components and chemical mass balance of fine aerosol in different areas of Europe , 1998 .

[27]  J. Daisey,et al.  Nicotine as a Marker for Environmental Tobacco Smoke: Implications of Sorption on Indoor Surface Materials. , 1998, Journal of the Air & Waste Management Association.

[28]  P. Hopke,et al.  Receptor Modeling Assessment of Particle Total Exposure Assessment Methodology Data , 1999 .

[29]  Eun Sug Park,et al.  Comparing a new algorithm with the classic methods for estimating the number of factors , 1999 .

[30]  V. Mugica,et al.  Hydrocarbon source apportionment in Mexico City using the chemical mass balance receptor model , 2000 .

[31]  Tai-Yi Yu,et al.  Selection of the scenarios of ozone pollution at southern Taiwan area utilizing principal component analysis , 2000 .

[32]  R. Henry,et al.  Application of SAFER model to the Los Angeles PM10 data , 2000 .

[33]  Philip K. Hopke,et al.  Identification of Sources of Phoenix Aerosol by Positive Matrix Factorization , 2000, Journal of the Air & Waste Management Association.

[34]  Judith C. Chow,et al.  Review of volatile organic compound source apportionment by chemical mass balance , 2001 .

[35]  Exploratory Studies of PM10 Receptor and Source Profiling by GC/MS and Principal Component Analysis of Temporally and Spatially Resolved Ambient Samples , 2001, Journal of the Air & Waste Management Association.

[36]  Shelly L. Miller,et al.  Source apportionment of exposure to toxic volatile organic compounds using positive matrix factorization , 2001, Journal of Exposure Analysis and Environmental Epidemiology.

[37]  Shelly L. Miller,et al.  Source apportionment of exposures to volatile organic compounds: II. Application of receptor models to TEAM study data , 2002 .