A multiple-smoker model for predicting indoor air quality in public lounges

A mathematical multiple-smoker model for predicting the minute-by-minute indoor time series and time-averaged pollutant concentrations from environmental tobacco smoke (ETS) was developed and tested during 10 visits to glass-enclosed public smoking lounges at two international airports in the San Francisco Bay Area. The model is based on the mass balance equation and uses counts of active smokers as input. Its predictions were compared with the time series measurements of carbon monoxide (GO) and respirable suspended particles (RSP). The experimental time series for RSP was determined by averaging the readings (2-min averages) from monitors at three widely-spaced locations in the lounge. At 8 out of the 10 visits, instantaneous CO concentrations also were measured every 2-3 min from a single monitor at the center of the room. The average emission rates per cigarette for CO and RSP for two visits in which the air exchange rates were measured were found to be 11.9 and 1.43 mg/min, respectively, which are consistent with values reported elsewhere in the literature. There was excellent agreement (0-12% error) between the observed RSP and CO concentration time series average and average concentrations predicted by the model for all study visits. Regression results between observed and predicted time series were also excellent. The average difference between the time-averaged RSP concentrations measured at the three widely spaced locations in the room and the average concentration across the room was about 12%. These results suggest that the model can be used by human exposure assessors and smoking lounge designers to predict the average exposures that people will experience for visits of typical duration.