Using Regional Data and Building Leakage to Assess Indoor Concentrations of Particles of Outdoor Origin

Abstract

Time-resolved fine particle concentrations of nitrate, sulfate, and black carbon were examined to assess the appropriateness of using regional data and calculated air exchange rates to model indoor concentrations of particles from outdoor sources. The data set includes simultaneous, sub-hourly aerosol composition measurements at three locations: a regional monitoring site in Fresno, California, inside of an unoccupied residence in Clovis, California, located 6 km northeast of the regional site, and immediately outside of this same residence. Indoor concentrations of PM_2.5 nitrate, sulfate, and black carbon were modeled using varying sets of inputs to determine the influence of three factors on model accuracy: the constraints of the simplified indoor-outdoor model, measured versus modeled air exchange rates, and local versus regional outdoor measurements.

Modeled indoor concentrations captured the lag and attenuation in indoor concentrations as well as the differences among chemical constituents in the indoor-outdoor concentration relationships. During periods when the house was closed and unoccupied, use of air exchange rates calculated from the LBNL infiltration model in place of those directly measured did not contribute significantly to the error in the estimated indoor concentrations. Differences between ambient concentrations at the regional monitoring site and the immediate neighborhood contributed to estimation errors for sulfate and black carbon. Evaporation was the dominant factor affecting indoor nitrate concentrations. Even when limiting the model inputs to concentrations and meteorological parameters measured at the regional monitoring station, the modeled concentrations were more highly correlated with measured indoor concentrations than were the regional measurements themselves.

The authors dedicate this article in memory of Dr. Joan Daisey, who played a key role in the initial phases of this project, and whose vision has guided our work. We thank Jennifer McWilliams and Max Sherman for their review of our use of the LBNL infiltration model. This research was supported by the Assistant Secretary for Fossil Energy, Office of Natural Gas and Petroleum Technology through the National Petroleum Technology Office under U.S. Department of Energy Contract No. DE-AC03-76SF00098, and by the Western States Petroleum Association and the American Petroleum Institute.

Notes

¹Ratio of mean values over 9, 24-hr periods during study.

¹RMS Error = Root mean square of the difference between hourly average of modeled and measured indoor concentrations. Modeling approaches are described in Table 1. Comparison is for periods when doors and windows of Study House were closed (October 10 midnight–October 16 noon, December 22 midnight–December 29 noon, December 31 noon–January 15 midnight).