Fine and ultrafine particle exposures on 73 trips by car to 65 non-smoking restaurants in the San Francisco Bay Area.

A number of studies indicate cooking is a major source of exposure to particulate matter, but few studies have measured indoor air pollution in restaurants, where cooking predominates. We made 73 visits by car to 65 different non-smoking restaurants in 10 Northern California towns while carrying portable continuous monitors that unobtrusively measured ultrafine (down to 10 nm) and fine (PM2.5 ) particles to characterize indoor restaurant exposures, comparing them with exposures in the car. The mean ultrafine number concentrations in the restaurants on dinner visits averaging 1.4 h was 71 600 particles/cm3 , or 4.3 times the mean concentration on car trips, and 12.3 times the mean background concentration in the residence. Restaurants that cooked dinner in the same room as the patrons had higher ultrafine concentrations than restaurants with separate kitchens. Restaurant PM2.5 mass concentrations averaged 36.3 µg/m3 , ranging from 1.5 to 454 µg/m3 , but were relatively low on most visits: 43% of the indoor means were below 10 µg/m3 and 66% were below 20 µg/m3 , with 5.5% above 100 µg/m3 . Exposure to fine and ultrafine particles when visiting a restaurant exceeded the exposure a person received while traveling by car to and from the restaurant.

Identifying and quantifying secondhand smoke in source and receptor rooms: logistic regression and chemical mass balance approaches.

Identifying and quantifying secondhand tobacco smoke (SHS) that drifts between multiunit homes is critical to assessing exposure. Twenty-three different gaseous and particulate measurements were taken during controlled emissions from smoked cigarettes and six other common indoor source types in 60 single-room and 13 two-room experiments. We used measurements from the 60 single-room experiments for (i) the fitting of logistic regression models to predict the likelihood of SHS and (ii) the creation of source profiles for chemical mass balance (CMB) analysis to estimate source apportionment. We then applied these regression models and source profiles to the independent data set of 13 two-room experiments. Several logistic regression models correctly predicted the presence of cigarette smoke more than 80% of the time in both source and receptor rooms, with one model correct in 100% of applicable cases. CMB analysis of the source room provided significant PM2.5 concentration estimates of all true sources in 9 of 13 experiments and was half-correct (i.e., included an erroneous source or missed a true source) in the remaining four. In the receptor room, CMB provided significant estimates of all true sources in 9 of 13 experiments and was half-correct in another two.

Controlled experiments measuring personal exposure to PM2.5 in close proximity to cigarette smoking.

Few measurements of exposure to secondhand smoke (SHS) in close proximity to a smoker are available. Recent health studies have demonstrated an association between acute (<2 h) exposures to high concentrations of SHS and increased risk of cardiovascular and respiratory disease. We performed 15 experiments inside naturally ventilated homes and 16 in outdoor locations, each with 2-4 non-smokers sitting near a cigarette smoker. The smoker's and non-smokers' real-time exposures to PM2.5 from SHS were measured by using TSI SidePak monitors to sample their breathing zones. In 87% of the residential indoor experiments, the smoker received the highest average exposure to SHS, with PM2.5 concentrations ranging from 50-630 µg/m(3) . During the active smoking period, individual non-smokers sitting within approximately 1 m of a smoker had average SHS exposures ranging from negligible up to >160 µg/m(3) of PM2.5 . The average incremental exposure of the non-smokers was higher indoors (42 µg/m(3) , n = 35) than outdoors (29 µg/m(3) , n = 47), but the overall indoor and outdoor frequency distributions were similar. The 10-s PM2.5 averages during the smoking periods showed great variability, with multiple high concentrations of short duration (microplumes) both indoors and outdoors.

Concentration and composition of atmospheric aerosols from the 1995 SEAVS experiment and a review of the closure between chemical and gravimetric measurements.

We summarize the results from the various measurements and the inter-sampler comparisons from Southeastern Aerosol and Visibility Study (SEAVS), a study with one of its objectives to test for closure among chemical, gravimetric and optical measurements of atmospheric aerosol particles. Sulfate and organics are the dominant components of the SEAVS fine particles (nominally, particles with aerodynamic diameter < or = 2.5 microns) but between 28 and 42% (range over various samplers) of the gravimetrically measured total fine particle concentration is unidentified by the chemical measurements. Estimates of water associated with inorganic components and measurement imprecision do not totally explain the observed difference between gravimetric and chemical measurements. We examine the theoretical and empirical basis for assumptions commonly made in the published literature to extrapolate total fine particle concentration on the basis of chemical measurements of ions, carbon and elements. We then explore the more general question of closure using the SEAVS data as well as data from other, similar studies reported in the literature. In so combining the SEAVS measurements with other similar studies, we find a strong association between organic carbon and the unidentified component, that is, the fraction of the total fine particle concentration not identified by chemical measurements. We offer several tenable hypotheses for the relationship between the organic and unidentified components that deserve to be tested in future work. Specifically, we hypothesize that (1) errors in the sampling and analysis of organic carbon; (2) estimates of organic mass from measurements of organic carbon; and/or (3) water absorption by organics may all contribute to the observed relationship.

Investigations of the proximity effect for pollutants in the indoor environment.

More than a dozen indoor air quality studies have reported a large discrepancy between concentrations measured by stationary indoor monitors (SIMs) and personal exposure monitors (PEMs). One possible cause of this discrepancy is a source proximity effect, in which pollutant sources close to the respondent cause elevated and highly variable exposures. This paper describes three sets of experiments in a home using real-time measurements to characterize and quantify the proximity effect relative to a fixed distant location analogous to a SIM. In the first set of experiments, using sulfur hexafluoride (SF6) as a continuously emitting tracer pollutant from a point source, measurements of pollutant concentrations were made at different distances from the source under different air exchange rates and source strengths. A second set of experiments used a continuous point source of carbon monoxide (CO) tracer pollutant and an array of high time resolution monitors to collect simultaneous concentration readings at different locations in the room. A third set of experiments measured particle count density and particle-bound polycyclic aromatic hydrocarbon (PAH) concentrations emitted from a continuous particle point source (an incense stick) using two particle counters and two PAH monitors, and included human activity periods both before and during the source emission period. Results from the SF6 and CO experiments show that while the source is emitting, a source proximity effect can be seen in the increases in the mean and median and in the variability of concentrations closest to the source, even at a distance of 2.0 m from the source under certain settings of air exchange rate and source strength. CO concentrations at locations near the source were found to be higher and more variable than the predictions of the mass balance model. For particles emitted from the incense source, a source proximity effect was evident for the fine particle sizes (0.3 to 2.5 microm) and particle-bound PAH up to at least 1.0 m from the source. Analysis of spatial and temporal patterns in the data for the three tracer pollutants reveal marked transient elevations of concentrations as seen by the monitor, referred to as "microplumes," particularly at locations close to the source. Mixing patterns in the room show complex patterns and directional effects, as evidenced by the variable intensity of the microplume activity at different locations. By characterizing the spatial and temporal variability of pollutant concentrations in the home, the proximity effect can be quantified, leading to improved indoor monitoring designs and models of human exposure to air pollutants.

A mathematical model for predicting trends in carbon monoxide emissions and exposures on urban arterial highways.

The roadway is one of the most important microenvironments for human exposure to carbon monoxide (CO). To evaluate long-term changes in pollutant exposure due to in-transit activities, a mathematical model has been developed to predict average daily vehicular emissions on highways. By utilizing measurements that are specific for a given location and year (e.g., traffic counts, fleet composition), this model can predict emissions for a specific roadway during various time periods of interest, allowing examination of long-term trends in human exposure to CO. For an arterial highway in northern California, this model predicts that CO emissions should have declined by 58% between 1980 and 1991, which agrees fairly well with field measurements of human exposure taken along that roadway during those two years. An additional reduction of up to 60% in CO emissions is predicted to occur between 1991 and 2002, due solely to the continued replacement of older cars with newer, cleaner vehicles.