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To understand the potential exposure to tobacco smoke in Washoe County (Reno/Sparks), Nevada casinos by measuring air quality in smoking areas relative to non-smoking/non-gaming areas in which minors may be present. To act as a pilot study in community-based health research and policy campaigns by evaluating low-cost air monitors to measure personal secondhand smoke (SHS) exposure. We used customized mobile apps, AtmoTube PRO Air Monitors, and hand clickers to measure the timing and minute-by-minute levels of PM2.5 (a tobacco smoke marker). The app was used to record the number of smokers, minors, and total patrons associated with ~10-minute sequential time periods in standardized casino locations, including outdoor areas, slots, tables, restaurants, bars/lounges, arcades, among others. Between April and May 2022, we successfully visited 14 casinos and 18 distinct types of indoor casino locations. We found high PM2.5 peaks in casino locations even with zero, or a low percentage of, observed active smokers, including in both gaming/non-gaming areas. Indoor areas, regardless of smoking/non-smoking areas, consistently had higher PM2.5 levels than outdoor background levels. Indoor locations had median PM2.5 levels up to 18 times higher than the lowest outdoor background levels. Minors were present throughout all casino locations, and thus were likely exposed to elevated PM2.5 levels. Potential PM2.5 exposures due to smoking can be high regardless of ventilation systems. Small proportions of smokers in a location can lead to high levels of exposure. Establishing comprehensive smoke-free casinos is the only way to protect against SHS harms.

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Low-cost monitors have made it possible for the first time to measure indoor PM2.5 concentrations over extended periods of time (months to years). Coupled with concurrent outdoor measurements, these indoor measurements can be divided into particles entering the building from outdoors and particles generated from indoor activities. Indoor-generated particles are not normally considered in epidemiological studies, but they can have health effects (e.g., passive smoking and high-temperature cooking). We employed The Random Component Superposition (RCS) regression model to estimate infiltration factors for up to 790 000 matched indoor and outdoor sites. The median infiltration factors for subgroups in the 3-state region ranged between 0.22 and 0.24, with an interquartile range (IQR) of 0.13-0.40. These infiltration factors allowed calculation of both the indoor-generated and outdoor-infiltrated PM2.5 . Indoor-generated particles contributed, on average, 46%-52% of total indoor PM2.5 concentrations. However, the site-specific fractional contribution of these indoor sources to total indoor PM2.5 ranged from near-zero to nearly 100%. The influence of indoor-generated particles on potential exposures varied widely relative to outdoor concentrations. The greatest influence of indoor-generated particles occurred at low-to-moderate daily mean outdoor PM2.5 levels around 6 µg/m3 and was negligible at outdoor concentrations >20 µg/m3 . Epidemiological studies incorporating only estimated exposures due to the particles of ambient origin may benefit from the newly available knowledge of long-term indoor-generated particle concentrations.

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Large quantities of real-time particle data are becoming available from low-cost particle monitors. However, it is crucial to determine the quality of these measurements. The largest network of monitors in the United States is maintained by the PurpleAir company, which offers two monitors: PA-I and PA-II. PA-I monitors have a single sensor (PMS1003) and PA-II monitors employ two independent PMS5003 sensors. We determine a new calibration factor for the PA-I monitor and revise a previously published calibration algorithm for PA-II monitors (ALT-CF3). From the PurpleAir API site, we downloaded 83 million hourly average PM2.5 values in the PurpleAir database from Washington, Oregon, and California between 1 January 2017 and 8 September 2021. Daily outdoor PM2.5 means from 194 PA-II monitors were compared to daily means from 47 nearby Federal regulatory sites using gravimetric Federal Reference Methods (FRM). We find a revised calibration factor of 3.4 for the PA-II monitors. For the PA-I monitors, we determined a new calibration factor (also 3.4) by comparing 26 outdoor PA-I sites to 117 nearby outdoor PA-II sites. These results show that PurpleAir PM2.5 measurements can agree well with regulatory monitors when an optimum calibration factor is found.

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Few studies have examined the relative effectiveness of reinforcing versus aversive consequences at changing behavior in real-world environments. Real-time sensing devices makes it easier to investigate such questions, offering the potential to improve both intervention outcomes and theory. This research aims to describe the development of a real-time, operant theory-based secondhand smoke (SHS) intervention and compare the efficacy of aversive versus aversive plus reinforcement contingency systems. Indoor air particle monitors were placed in the households of 253 smokers for approximately three months. Participants were assigned to a measurement-only control group (N = 129) or one of the following groups: 1.) aversive only (AO, N = 71), with aversive audio/visual consequences triggered by the detection of elevated air particle measurements, or 2.) aversive plus reinforcement (AP, N = 53), with reinforcing consequences contingent on the absence of SHS added to the AO intervention. Residualized change ANCOVA analysis compared particle concentrations over time and across groups. Post-hoc pairwise comparisons were also performed. After controlling for Baseline, Post-Baseline daily particle counts (F = 6.42, p = 0.002), % of time >15,000 counts (F = 7.72, p < 0.001), and daily particle events (F = 4.04, p = 0.02) significantly differed by study group. Nearly all control versus AO/AP pair-wise comparisons were statistically significant. No significant differences were found for AO versus AP groups. The aversive feedback system reduced SHS, but adding reinforcing consequences did not further improve outcomes. The complexity of real-world environments requires the nuances of these two contingency systems continue to be explored, with this study demonstrating that real-time sensing technology can serve as a platform for such research.

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BACKGROUND: Previous secondhand smoke (SHS) reduction interventions have provided only delayed feedback on reported smoking behaviour, such as coaching, or presenting results from child cotinine assays or air particle counters. DESIGN: This SHS reduction trial assigned families at random to brief coaching and continuous real-time feedback (intervention) or measurement-only (control) groups. PARTICIPANTS: We enrolled 298 families with a resident tobacco smoker and a child under age 14. INTERVENTION: We installed air particle monitors in all homes. For the intervention homes, immediate light and sound feedback was contingent on elevated indoor particle levels, and up to four coaching sessions used prompts and praise contingent on smoking outdoors. Mean intervention duration was 64 days. MEASURES: The primary outcome was 'particle events' (PEs) which were patterns of air particle concentrations indicative of the occurrence of particle-generating behaviours such as smoking cigarettes or burning candles. Other measures included indoor air nicotine concentrations and participant reports of particle-generating behaviour. RESULTS: PEs were significantly correlated with air nicotine levels (r=0.60) and reported indoor cigarette smoking (r=0.51). Interrupted time-series analyses showed an immediate intervention effect, with reduced PEs the day following intervention initiation. The trajectory of daily PEs over the intervention period declined significantly faster in intervention homes than in control homes. Pretest to post-test, air nicotine levels, cigarette smoking and e-cigarette use decreased more in intervention homes than in control homes. CONCLUSIONS: Results suggest that real-time particle feedback and coaching contingencies reduced PEs generated by cigarette smoking and other sources. TRIAL REGISTRATION NUMBER: NCT01634334; Post-results.

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Cannabis use is increasing and cannabis is typically consumed by smoking. This study explored how indoor secondhand cannabis smoke (SCS) was associated with child health. As part of a larger trial, air particle monitors were placed in 298 homes of families with at least one cigarette smoker and one child under 14 years old in San Diego County, California. Assessment included past 7-day indoor cigarette and cannabis use, the youngest child's exposure to cigarette smoke, and 5 smoke-related past-year child health outcomes: emergency department use for coughing/difficulty breathing; physician diagnosis of ear infection, bronchitis/bronchiolitis, asthma, or eczema/atopic dermatitis. An ordinal measure of adverse health outcomes (0, 1, or ≥2) was regressed on reported indoor cannabis smoking-the main measure of exposure (yes/no). Of 221 parents/guardians asked about cannabis use, 192 (86.9%) provided all required data, and 29 (15.1%) reported indoor cannabis smoking; reports were supported by air particle data. Homes without indoor smoking had lower average 7-day particle concentrations (1968 particles/0.01ft3) than homes with cannabis smoking only (3131 particles/0.01ft3), cigarette smoking only (3095 particles/0.01ft3), or both cigarette and cannabis smoking (6006 particles/0.01ft3). Odds of reporting a greater number of adverse health outcomes were 1.83 (95% CI = 0.89-3.80, p = 0.10) times higher for children of families with indoor cannabis smoking vs families without cannabis smoking, after controlling for exposure to cigarette smoke and other covariates. Our results do not indicate a statistically significant association. However, the magnitude of the (non-significant) association between indoor cannabis smoking and adverse health outcomes warrants more studies.

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Adaptive behavioral interventions that automatically adjust in real-time to participants' changing behavior, environmental contexts, and individual history are becoming more feasible as the use of real-time sensing technology expands. This development is expected to improve shortcomings associated with traditional behavioral interventions, such as the reliance on imprecise intervention procedures and limited/short-lived effects. JITAI adaptation strategies often lack a theoretical foundation. Increasing the theoretical fidelity of a trial has been shown to increase effectiveness. This research explores the use of shaping, a well-known process from behavioral theory for engendering or maintaining a target behavior, as a JITAI adaptation strategy. A computational model of behavior dynamics and operant conditioning was modified to incorporate the construct of behavior shaping by adding the ability to vary, over time, the range of behaviors that were reinforced when emitted. Digital experiments were performed with this updated model for a range of parameters in order to identify the behavior shaping features that optimally generated target behavior. Narrowing the range of reinforced behaviors continuously in time led to better outcomes compared with a discrete narrowing of the reinforcement window. Rapid narrowing followed by more moderate decreases in window size was more effective in generating target behavior than the inverse scenario. The computational shaping model represents an effective tool for investigating JITAI adaptation strategies. Model parameters must now be translated from the digital domain to real-world experiments so that model findings can be validated.

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INTRODUCTION: Exposure to fine particulate matter in the home from sources such as smoking, cooking, and cleaning may put residents, especially children, at risk for detrimental health effects. A randomized clinical trial was conducted from 2011 to 2016 to determine whether real-time feedback in the home plus brief coaching of parents or guardians could reduce fine particle levels in homes with smokers and children. DESIGN: A randomized trial with two groups-intervention and control. SETTING/PARTICIPANTS: A total of 298 participants from predominantly low-income households with an adult smoker and a child aged <14 years. Participants were recruited during 2012-2015 from multiple sources in San Diego, mainly Women, Infants and Children Program sites. INTERVENTION: The multicomponent intervention consisted of continuous lights and brief sound alerts based on fine particle levels in real time and four brief coaching sessions using particle level graphs and motivational interviewing techniques. Motivational interviewing coaching focused on particle reduction to protect children and other occupants from elevated particle levels, especially from tobacco-related sources. MAIN OUTCOME MEASURES: In-home air particle levels were measured by laser particle counters continuously in both study groups. The two outcomes were daily mean particle counts and percentage time with high particle concentrations (>15,000 particles/0.01 ft3). Linear mixed models were used to analyze the differential change in the outcomes over time by group, during 2016-2017. RESULTS: Intervention homes had significantly larger reductions than controls in daily geometric mean particle concentrations (18.8% reduction vs 6.5% reduction, p<0.001). Intervention homes' average percentage time with high particle concentrations decreased 45.1% compared with a 4.2% increase among controls (difference between groups p<0.001). CONCLUSIONS: Real-time feedback for air particle levels and brief coaching can reduce fine particle levels in homes with smokers and young children. Results set the stage for refining feedback and possible reinforcing consequences for not generating smoke-related particles. TRIAL REGISTRATION: This study is registered at www.clinicaltrials.gov NCT01634334.

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Children are at risk for adverse health outcomes from occupant-controllable indoor airborne contaminants in their homes. Data are needed to design residential interventions for reducing low-income children's pollutant exposure. Using customized air quality monitors, we continuously measured fine particle counts (0.5 to 2.5 microns) over a week in living areas of predominantly low-income households in San Diego, California, with at least one child (under age 14) and at least one cigarette smoker. We performed retrospective interviews on home characteristics, and particle source and ventilation activities occurring during the week of monitoring. We explored the relationship between weekly mean particle counts and interview responses using graphical visualization and multivariable linear regression (base sample n = 262; complete cases n = 193). We found associations of higher weekly mean particle counts with reports of indoor smoking of cigarettes or marijuana, as well as with frying food, using candles or incense, and house cleaning. Lower particle levels were associated with larger homes. We did not observe an association between lower mean particle counts and reports of opening windows, using kitchen exhaust fans, or other ventilation activities. Our findings about sources of fine airborne particles and their mitigation can inform future studies that investigate more effective feedback on residential indoor-air-quality and better strategies for reducing occupant exposures.

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Most casinos owned by sovereign American Indian nations allow smoking, even in U.S. states such as California where state laws restrict workplace smoking. Collaborations between casinos and public health workers are needed to promote smoke-free policies that protect workers and patrons from secondhand tobacco smoke (SHS) exposure and risks. Over seven years, a coalition of public health professionals provided technical assistance to the Redding Rancheria tribe in Redding, California in establishing a smoke-free policy at the Win-River Resort and Casino. The coalition provided information to the casino general manager that included site-specific measurement of employee and visitor PM2.5 personal exposure, area concentrations of airborne nicotine and PM2.5, visitor urinary cotinine, and patron and staff opinions (surveys, focus groups, and a Town Hall meeting). The manager communicated results to tribal membership, including evidence of high SHS exposures and support for a smoke-free policy. Subsequently, in concert with hotel expansion, the Redding Rancheria Tribal Council voted to accept a 100% restriction of smoking inside the casino, whereupon PM2.5 exposure in main smoking areas dropped by 98%. A 70% partial-smoke-free policy was instituted ~1 year later in the face of revenue loss. The success of the collaboration in promoting a smoke-free policy, and the key element of air quality feedback, which appeared to be a central driver, may provide a model for similar efforts.

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Real-time particle monitors are essential for accurately estimating exposure to fine particles indoors. However, many such monitors tend to be prohibitively expensive for some applications, such as a tenant or homeowner curious about the quality of the air in their home. A lower cost version (the Dylos Air Quality Monitor) has recently been introduced, but it requires appropriate calibration to reflect the mass concentration units required for exposure assessment. We conducted a total of 64 experiments with a suite of instruments including a Dylos DC1100, another real-time laser photometer (TSI SidePak™ Model AM-510 Personal Aerosol Monitor), and a gravimetric sampling apparatus to estimate Dylos calibration factors for emissions from 17 different common indoor sources including cigarettes, incense, fried bacon, chicken, and hamburger. Comparison of minute-by-minute data from the Dylos with the gravimetrically calibrated SidePak yielded relationships that enable the conversion of the raw Dylos particle counts less than 2.5 µm (in #/0.01 ft(3)) to estimated PM2.5 mass concentration (e.g. µg m(-3)). The relationship between the exponentially-decaying Dylos particle counts and PM2.5 mass concentration can be described by a theoretically-derived power law with source-specific empirical parameters. A linear relationship (calibration factor) is applicable to fresh or quickly decaying emissions (i.e., before the aerosol has aged and differential decay rates introduce curvature into the relationship). The empirical parameters for the power-law relationships vary greatly both between and within source types, although linear factors appear to have lower uncertainty. The Dylos Air Quality Monitor is likely most useful for providing instantaneous feedback and context on mass particle levels in home and work situations for field-survey or personal awareness applications.

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UNLABELLED: As indoor smoking bans have become widely adopted, some U.S. communities are considering restricting smoking outdoors, creating a need for measurements of air pollution near smokers outdoors. Personal exposure experiments were conducted with four to five participants at six sidewalk bus stops located 1.5-3.3 m from the curb of two heavily traveled California arterial highways with 3300-5100 vehicles per hour. At each bus stop, a smoker in the group smoked a cigarette. Gravimetrically calibrated continuous monitors were used to measure fine particle concentrations (aerodynamic diameter < or = 2.5 microm; PM2.5) in the breathing zones (within 0.2 m from the nose and mouth) of each participant. At each bus stop, ultrafine particles (UFP), wind speed, temperature, relative humidity, and traffic counts were also measured. For 13 cigarette experiments, the mean PM2.5 personal exposure of the nonsmoker seated 0.5 m from the smoker during a 5-min cigarette ranged from 15 to 153 microg/m3. Of four persons seated on the bench, the smoker received the highest PM2.5 breathing-zone exposure of 192 microg/m3. There was a strong proximity effect: nonsmokers at distances 0.5, 1.0, and 1.5 m from the smoker received mean PM2.5 personal exposures of 59, 40, and 28 microg/m3, respectively, compared with a background level of 1.7 microg/m3. Like the PM2.5 concentrations, UFP concentrations measured 0.5 m from the smoker increased abruptly when a cigarette started and decreased when the cigarette ended, averaging 44,500 particles/cm3 compared with the background level of 7200 particles/cm3. During nonsmoking periods, the UFP background concentrations showed occasional peaks due to traffic, whereas PM2.5 background concentrations were extremely low. The results indicate that a single cigarette smoked outdoors at a bus stop can cause PM2.5 and UFP concentrations near the smoker that are 16-35 and 6.2 times, respectively, higher than the background concentrations due to cars and trucks on an adjacent arterial highway. IMPLICATIONS: Rules banning smoking indoors have been widely adopted in the United States and in many countries. Some communities are considering smoking bans that would apply to outdoor locations. Although many measurements are available of pollutant concentrations from secondhand smoke at indoor locations, few measurements are available of exposure to secondhand smoke outdoors. This study provides new data on exposure to fine and ultrafine particles from secondhand smoke near a smoker outdoors. The levels are compared with the exposure measured next to a highway. The findings are important for policies that might be developed for reducing exposure to secondhand smoke outdoors.

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BACKGROUND: Residential natural gas cooking burners (NGCBs) can emit substantial quantities of pollutants, and they are typically used without venting range hoods. OBJECTIVE: We quantified pollutant concentrations and occupant exposures resulting from NGCB use in California homes. METHODS: A mass-balance model was applied to estimate time-dependent pollutant concentrations throughout homes in Southern California and the exposure concentrations experienced by individual occupants. We estimated nitrogen dioxide (NO2), carbon monoxide (CO), and formaldehyde (HCHO) concentrations for 1 week each in summer and winter for a representative sample of Southern California homes. The model simulated pollutant emissions from NGCBs as well as NO2 and CO entry from outdoors, dilution throughout the home, and removal by ventilation and deposition. Residence characteristics and outdoor concentrations of NO2 and CO were obtained from available databases. We inferred ventilation rates, occupancy patterns, and burner use from household characteristics. We also explored proximity to the burner(s) and the benefits of using venting range hoods. Replicate model executions using independently generated sets of stochastic variable values yielded estimated pollutant concentration distributions with geometric means varying by <10%. RESULTS: The simulation model estimated that-in homes using NGCBs without coincident use of venting range hoods-62%, 9%, and 53% of occupants are routinely exposed to NO2, CO, and HCHO levels that exceed acute health-based standards and guidelines. NGCB use increased the sample median of the highest simulated 1-hr indoor concentrations by 100, 3,000, and 20 ppb for NO2, CO, and HCHO, respectively. CONCLUSIONS: Reducing pollutant exposures from NGCBs should be a public health priority. Simulation results suggest that regular use of even moderately effective venting range hoods would dramatically reduce the percentage of homes in which concentrations exceed health-based standards.

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For an actively emitting source such as cooking or smoking, indoor measurements have shown a strong "proximity effect" within 1 m. The significant increase in both the magnitude and variation of concentration near a source is attributable to transient high peaks that occur sporadically-and these "microplumes" cause great uncertainty in estimating personal exposure. Recent field studies in naturally ventilated rooms show that close-proximity concentrations are approximately lognormally distributed. We use the autocorrelated random walk method to represent the time-varying directionality of indoor emissions, thereby predicting the time series and frequency distributions of concentrations close to an actively emitting point source. The predicted 5-min concentrations show good agreement with measurements from a point source of CO in a naturally ventilated house-the measured and predicted frequency distributions at 0.5- and 1-m distances are similar and approximately lognormal over a concentration range spanning three orders of magnitude. By including the transient peak concentrations, this random airflow modeling method offers a way to more accurately assess acute exposure levels for cases where well-defined airflow patterns in an indoor space are not available.

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Interventions are needed to protect the health of children who live with smokers. We pilot-tested a real-time intervention for promoting behavior change in homes that reduces second hand tobacco smoke (SHS) levels. The intervention uses a monitor and feedback system to provide immediate auditory and visual signals triggered at defined thresholds of fine particle concentration. Dynamic graphs of real-time particle levels are also shown on a computer screen. We experimentally evaluated the system, field-tested it in homes with smokers, and conducted focus groups to obtain general opinions. Laboratory tests of the monitor demonstrated SHS sensitivity, stability, precision equivalent to at least 1 µg/m(3), and low noise. A linear relationship (R(2) = 0.98) was observed between the monitor and average SHS mass concentrations up to 150 µg/m(3). Focus groups and interviews with intervention participants showed in-home use to be acceptable and feasible. The intervention was evaluated in 3 homes with combined baseline and intervention periods lasting 9 to 15 full days. Two families modified their behavior by opening windows or doors, smoking outdoors, or smoking less. We observed evidence of lower SHS levels in these homes. The remaining household voiced reluctance to changing their smoking activity and did not exhibit lower SHS levels in main smoking areas or clear behavior change; however, family members expressed receptivity to smoking outdoors. This study established the feasibility of the real-time intervention, laying the groundwork for controlled trials with larger sample sizes. Visual and auditory cues may prompt family members to take immediate action to reduce SHS levels. Dynamic graphs of SHS levels may help families make decisions about specific mitigation approaches.

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Indoor sources can greatly contribute to personal exposure to particulate matter less than 2.5 µm in diameter (PM2.5). To accurately assess PM2.5 mass emission factors and concentrations, real-time particle monitors must be calibrated for individual sources. Sixty-six experiments were conducted with a common, real-time laser photometer (TSI SidePak™ Model AM510 Personal Aerosol Monitor) and a filter-based PM2.5 gravimetric sampler to quantify the monitor calibration factors (CFs), and to estimate emission factors for common indoor sources including cigarettes, incense, cooking, candles, and fireplaces. Calibration factors for these indoor sources were all significantly less than the factory-set CF of 1.0, ranging from 0.32 (cigarette smoke) to 0.70 (hamburger). Stick incense had a CF of 0.35, while fireplace emissions ranged from 0.44-0.47. Cooking source CFs ranged from 0.41 (fried bacon) to 0.65-0.70 (fried pork chops, salmon, and hamburger). The CFs of combined sources (e.g., cooking and cigarette emissions mixed) were linear combinations of the CFs of the component sources. The highest PM2.5 emission factors per time period were from burned foods and fireplaces (15-16 mg min(-1)), and the lowest from cooking foods such as pizza and ground beef (0.1-0.2 mg min(-1)).

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The complex composition of secondhand smoke (SHS) provides a range of constituents that can be measured in environmental samples (air, dust and on surfaces) and therefore used to assess non-smokers' exposure to tobacco smoke. Monitoring SHS exposure (SHSe) in indoor environments provides useful information on the extent and consequences of SHSe, implementing and evaluating tobacco control programmes and behavioural interventions, and estimating overall burden of disease caused by SHSe. The most widely used markers have been vapour-phase nicotine and respirable particulate matter (PM). Numerous other environmental analytes of SHS have been measured in the air including carbon monoxide, 3-ethenylpyridine, polycyclic aromatic hydrocarbons, tobacco-specific nitrosamines, nitrogen oxides, aldehydes and volatile organic compounds, as well as nicotine in dust and on surfaces. The measurement of nicotine in the air has the advantage of reflecting the presence of tobacco smoke. While PM measurements are not as specific, they can be taken continuously, allowing for assessment of exposure and its variation over time. In general, when nicotine and PM are measured in the same setting using a common sampling period, an increase in nicotine concentration of 1 µg/m(3) corresponds to an average increase of 10 µg/m3 of PM. This topic assessment presents a comprehensive summary of SHSe monitoring approaches using environmental markers and discusses the strengths and weaknesses of these methods and approaches.

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BACKGROUND: Nearly all California casinos currently allow smoking, which leads to potentially high patron exposure to secondhand tobacco smoke pollutants. Some argue that smoking restrictions or bans would result in a business drop, assuming > 50% of patrons smoke. Evidence in Nevada and responses from the 2008 California tobacco survey refute this assertion. The present study investigates the proportion of active smokers in southern California tribal casinos, as well as occupancy and PM(2.5) levels in smoking and nonsmoking sections. METHODS: We measured active-smoker and total-patron counts during Friday or Saturday night visits (two per casino) to smoking and nonsmoking gaming areas inside 11 southern California casinos. We counted slot machines and table games in each section, deriving theoretical maximum capacities and occupancy rates. We also measured PM(2.5) concentrations (or used published levels) in both nonsmoking and smoking areas. RESULTS: Excluding one casino visit with extremely high occupancy, we counted 24,970 patrons during 21 casino visits of whom 1,737 were actively smoking, for an overall active- smoker proportion of 7.0% and a small range of ~5% across casino visits (minimum of 5% and maximum of 10%). The differences in mean inter-casino active-smoker proportions were not statistically significant. Derived occupancy rates were 24% to 215% in the main (low-stakes) smoking-allowed slot or table areas. No relationship was found between observed active-smoker proportions and occupancy rate. The derived maximum capacities of nonsmoking areas were 1% to 29% of the overall casino capacity (most under 10%) and their observed occupancies were 0.1 to over 3 times that of the main smoking-allowed casino areas. Seven of twelve visits to nonsmoking areas with no separation had occupancy rates greater than main smoking areas. Unenclosed nonsmoking areas don't substantially protect occupants from PM2.5 exposure. Nonsmoking areas encapsulated inside smoking areas or in a separate, but unenclosed, area had PM(2.5) levels that were 10 to 60 µg/m(3) and 6 to 23 µg/m(3) higher than outdoor levels, respectively, indicating contamination from smoking. CONCLUSIONS: Although fewer than roughly 10% of casino patrons are actively smoking on average, these individuals substantially increase PM(2.5) exposure for all patrons in smoking and unenclosed nonsmoking areas. Nonsmoking areas may be too inconvenient, small, or undesirable to serve a substantial number of nonsmoking patrons. Imposing indoor smoking bans, or contained smoking areas with a maximum capacity of up to 10% of the total patronage, would offer protection from PM2.5 exposures for nonsmoking patrons and reduce employee exposures.

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Personal exposure to air pollutants can be substantially higher in close proximity to an active source due to non-instantaneous mixing of emissions. The research presented in this paper quantifies this proximity effect for a non-buoyant source in 2 naturally ventilated homes in Northern California (CA), assessing its spatial and temporal variation and the influence of factors such as ventilation rate on its magnitude. To quantify how proximity to residential sources of indoor air pollutants affects human exposure, we performed 16 separate monitoring experiments in the living rooms of two detached single-family homes. CO (as a tracer gas) was released from a point source in the center of the room at a controlled emission rate for 5-12 h per experiment, while an array of 30-37 real-time monitors simultaneously measured CO concentrations with 15 s time resolution at radial distances ranging from 0.25-5 m under a range of ventilation conditions. Concentrations measured in close proximity (within 1 m) to the source were highly variable, with 5 min averages that typically varied by >100-fold. This variability was due to short-duration (<1 min) pollutant concentration peaks ("microplumes") that were frequently recorded in close proximity to the source. We decomposed the random microplume component from the total concentrations by subtracting predicted concentrations that assumed uniform, instantaneous mixing within the room and found that these microplumes can be modeled using a 3-parameter lognormal distribution. Average concentrations measured within 0.25 m of the source were 6-20 times as high as the predicted well-mixed concentrations.

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BACKGROUND: Tobacco smoke exposure (TSE) is a serious threat to child health. Roughly 40% of children worldwide are exposed to tobacco smoke, and the very young are often "captive smokers" in homes in which others smoke.The goal of this research project is to develop and evaluate an intervention to reduce young child tobacco smoke exposure. The objective of this paper is to document our approach to building the intervention, to describe the planned intervention, and to explore the conceptual issues regarding the intervention and its evaluation. METHODS/DESIGN: This project is being developed using an iterative approach. We are currently in the middle of Stage 1. In this first stage, Intervention Development, we have already conducted a comprehensive search of the professional literature and internet resources, consulted with experts in the field, and conducted several Design Workshops. The planned intervention consists of parental group support therapy, a website to allow use of an "online/offline" approach, involvement of pediatricians, use of a video simulation game ("Dr. Cruz") to teach parents about child TSE, and personalized biochemical feedback on exposure levels. As part of this stage we will draw on a social marketing approach. We plan to use in-depth interviews and focus groups in order to identify barriers for behavior change, and to test the acceptability of program components.In Stage II, we plan to pilot the planned intervention with 5-10 groups of 10 parents each.In Stage III, we plan to implement and evaluate the intervention using a cluster randomized controlled trial with an estimated 540 participants. DISCUSSION: The major challenges in this research are twofold: building an effective intervention and measuring the effects of the intervention. Creation of an effective intervention to protect children from TSE is a challenging but sorely needed public health endeavor. We hope that our approach will contribute to building a stronger evidence base for control of child exposure to tobacco smoke.

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