Quantifying fine particle emission events from time-resolved measurements: Method description and application to 18 California low-income apartments.

PM2.5 exposure is associated with significant health risk. Exposures in homes derive from both outdoor and indoor sources, with emissions occurring primarily in discrete events. Data on emission event magnitudes and schedules are needed to support simulation-based studies of exposures and mitigations. This study applied an identification and characterization algorithm to quantify time-resolved PM2.5 emission events from data collected during 224 days of monitoring in 18 California apartments with low-income residents. We identified and characterized 836 distinct events with median and mean values of 12 and 30 mg emitted mass, 16 and 23 minutes emission duration, 37 and 103 mg/h emission rates, and pseudo-first-order decay rates of 1.3 and 2.0/h. Mean event-averaged concentrations calculated using the determined event characteristics agreed to within 6% of measured values for 14 of the apartments. There were variations in event schedules and emitted mass across homes, with few events overnight and most emissions occurring during late afternoons and evenings. Event characteristics were similar during weekdays and weekends. Emitted mass was positively correlated with number of residents (Spearman coefficient, ρ=.10), bedrooms (ρ=.08), house volume (ρ=.29), and indoor-outdoor CO2 difference (ρ=.27). The event schedules can be used in probabilistic modeling of PM2.5 in low-income apartments.

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.

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.

Proper Orthogonal Decomposition Methods for the Analysis of Real-Time Data: Exploring Peak Clustering in a Secondhand Smoke Exposure Intervention.

This work explores a method for classifying peaks appearing within a data-intensive time-series. We summarize a case study from a clinical trial aimed at reducing secondhand smoke exposure via the installation of air particle monitors in households. Proper orthogonal decomposition (POD) in conjunction with a k-means clustering algorithm assigns each data peak to one of two clusters. Aversive feedback from the monitors increased the proportion of short-duration, attenuated peaks from 38.8% to 96.6%. For each cluster, a distribution of parameters from a physics-based model of airborne particles is estimated. Peaks generated from these distributions are correctly identified by POD/clustering with >60% accuracy.

Validity of the uniform mixing assumption: determining human exposure to environmental tobacco smoke.

When using the mass balance equation to model indoor air quality, the primary assumption is that of uniform mixing. Different points in a single compartment are assumed to have the same instantaneous pollutant concentrations as all other points. Although such an assumption may be unrealistic, under certain conditions predictions (or measurements) of exposures at single points in a room are still within acceptable limits of error (e.g., 10%). In this article, three studies of the mixing of environmental tobacco smoke (ETS) pollutants are reviewed, and data from several other ETS field studies are presented. Under typical conditions for both short sources (e.g., 10 min) and the continuous sources of ETS in smoking lounges, I find that average exposure concentrations for a single point in a room represent the average exposure across all points in the room within 10% for averaging times ranging from 12 to 80 min. I present a method for determining theoretical estimates of acceptable averaging times for a continuous point source.

An introduction to the indirect exposure assessment approach: modeling human exposure using microenvironmental measurements and the recent National Human Activity Pattern Survey.

Indirect exposure approaches offer a feasible and accurate method for estimating population exposures to indoor pollutants, including environmental tobacco smoke (ETS). In an effort to make the indirect exposure assessment approach more accessible to people in the health and risk assessment fields, this paper provides examples using real data from (italic>a(/italic>) a week-long personal carbon monoxide monitoring survey conducted by the author; and (italic>b(/italic>) the 1992 to 1994 National Human Activity Pattern Survey (NHAPS) for the United States. The indirect approach uses measurements of exposures in specific microenvironments (e.g., homes, bars, offices), validated microenvironmental models (based on the mass balance equation), and human activity pattern data obtained from questionnaires to predict frequency distributions of exposure for entire populations. This approach requires fewer resources than the direct approach to exposure assessment, for which the distribution of monitors to a representative sample of a given population is necessary. In the indirect exposure assessment approach, average microenvironmental concentrations are multiplied by the total time spent in each microenvironment to give total integrated exposure. By assuming that the concentrations encountered in each of 10 location categories are the same for different members of the U.S. population (i.e., the NHAPS respondents), the hypothetical contribution that ETS makes to the average 24-hr respirable suspended particle exposure for Americans working their main job is calculated in this paper to be 18 microg/m3. This article is an illustrative review and does not contain an actual exposure assessment or model validation.

The effect of cigar smoking on indoor levels of carbon monoxide and particles.

To provide new information on environmental tobacco smoke (ETS) levels from cigars, we conducted three types of experiments: (1) Measurements of carbon monoxide (CO) during 15 controlled experiments in an office where several cigar brands were machine-smoked; (2) Measurements of CO or respirable suspended particles (RSP) and particle-bound polycyclic aromatic hydrocarbons (PAH) in a residence where two cigars were smoked by a person; and (3) Measurements of CO during two studies at cigar social events (where there were up to 18 cigars being smoked at a time) in which an investigator wore a concealed personal exposure monitor. Average concentrations of CO at the cigar social events were comparable to, or larger than, those observed on a freeway during rush hour traffic. A mass balance model that has been used successfully to predict ETS from cigarettes is used in this paper to obtain CO, RSP, and PAH emission factors (emission rate [mg/min], total mass emitted [mg], and emissions per mass smoked [mg/g]). The calculated emission factors show that the cigar can be a stronger source of CO than the cigarette. In contrast, the cigar may have fewer emissions of RSP and PAH per gram of consumed tobacco than the cigarette, but its size and longer smoking time results in greater total RSP and PAH emissions than for a single cigarette.

The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants.

Because human activities impact the timing, location, and degree of pollutant exposure, they play a key role in explaining exposure variation. This fact has motivated the collection of activity pattern data for their specific use in exposure assessments. The largest of these recent efforts is the National Human Activity Pattern Survey (NHAPS), a 2-year probability-based telephone survey (n=9386) of exposure-related human activities in the United States (U.S.) sponsored by the U.S. Environmental Protection Agency (EPA). The primary purpose of NHAPS was to provide comprehensive and current exposure information over broad geographical and temporal scales, particularly for use in probabilistic population exposure models. NHAPS was conducted on a virtually daily basis from late September 1992 through September 1994 by the University of Maryland's Survey Research Center using a computer-assisted telephone interview instrument (CATI) to collect 24-h retrospective diaries and answers to a number of personal and exposure-related questions from each respondent. The resulting diary records contain beginning and ending times for each distinct combination of location and activity occurring on the diary day (i.e., each microenvironment). Between 340 and 1713 respondents of all ages were interviewed in each of the 10 EPA regions across the 48 contiguous states. Interviews were completed in 63% of the households contacted. NHAPS respondents reported spending an average of 87% of their time in enclosed buildings and about 6% of their time in enclosed vehicles. These proportions are fairly constant across the various regions of the U.S. and Canada and for the California population between the late 1980s, when the California Air Resources Board (CARB) sponsored a state-wide activity pattern study, and the mid-1990s, when NHAPS was conducted. However, the number of people exposed to environmental tobacco smoke (ETS) in California seems to have decreased over the same time period, where exposure is determined by the reported time spent with a smoker. In both California and the entire nation, the most time spent exposed to ETS was reported to take place in residential locations.