Concentrations of fine particulate matter (PM2.5) and several of its particle constituents measured outside homes in Houston, Texas, and Los Angeles, California, were characterized using multiple regression analysis with proximity to point and mobile sources and meteorological factors as the independent variables. PM2.5 mass and the concentrations of organic carbon (OC), elemental carbon (EC), benzo-[a]-pyrene (BaP), perylene (Per), benzo-[g,h,i]-perylene (BghiP), and coronene (Cor) were examined. Negative associations of wind speed with concentrations demonstrated the effect of dilution by high wind speed. Atmospheric stability increase was associated with concentration increase. Petrochemical source proximity was included in the EC model in Houston. Area source proximity was not selected for any of the PM2.5 constituents' regression models. When the median values of the meteorological factors were used and the proximity to sources varied, the air concentrations calculated using the models for the eleven PM2.5 constituents outside the homes closest to influential highways were 1.5-15.8 fold higher than those outside homes furthest from the highway emission sources. When the median distance to the sources was used in the models, the concentrations of the PM2.5 constituents varied 2 to 82 fold, as the meteorological conditions varied over the observed range. We found different relationships between the two urban areas, illustrating the unique nature of urban sources and suggesting that localized sources need to be evaluated carefully to understand their potential contributions to PM2.5 mass and its particle constituents concentrations near residences, which influence baseline indoor air concentrations and personal exposures. The results of this study could assist in the appropriate design of monitoring networks for community-level sampling and help improve the accuracy of exposure models linking emission sources with estimated pollutant concentrations at the residential level.

Abstract
 1. Introduction
 2. Materials and Methods
  2.1. Data sources
  2.2. Study area
  2.3. Meteorological data
  2.4. Emission sources
  2.5. Proximity data
  2.6. Statistical analysis
 3. Results
  3.1. Descriptive summary
  3.2. Meteorological variables
  3.3. Source proximity
 4. Discussion
  4.1. Wind speed and stability
  4.2. Effect of wind
  4.3. Effect of atmospheric stability
  4.4. Dewpoint, RH, and precipitation
  4.5. Effect of point sources
  4.6. Effect of highways
 5. Conclusions
 Acknowledgements
 Conflict of interest
 Abbreviations
 REFERENCES

• Jaymin Kwon(California State University, Fresno, Department of Public Health) Corresponding author
• Clifford P. Weisel(Rutgers University, Environmental and Occupational Health Science Institute, Department of Environmental and Occupational Medicine)
• Maria T. Morandi(University of Texas, Health Science Center at Houston, School of Public Health)
• Thomas H. Stock(University of Texas, Health Science Center at Houston, School of Public Health, Epidemiology, Human Genetics & Environmental Sciences)
• Barbara Turpin(University of North Carolina at Chapel Hill, Gillings School of Global Public Health, Environmental Science and Engineering)