Measuring Indoor Air Quality and Engaging California Indian Stakeholders at the Win-River Resort and Casino: Collaborative Smoke-Free Policy Development.

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.

Determining PM2.5 calibration curves for a low-cost particle monitor: common indoor residential aerosols.

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.

Outdoor fine and ultrafine particle measurements at six bus stops with smoking on two California arterial highways--results of a pilot study.

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.

Stochastic modeling of short-term exposure close to an air pollution source in a naturally ventilated room: an autocorrelated random walk method.

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.

Real-time particle monitor calibration factors and PM2.5 emission factors for multiple indoor sources.

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)).

Measurement of the proximity effect for indoor air pollutant sources in two homes.

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.

Determination of response of real-time SidePak AM510 monitor to secondhand smoke, other common indoor aerosols, and outdoor aerosol.

The amount of light scattered by airborne particles inside an aerosol photometer will vary not only with the mass concentration, but also with particle properties such as size, shape, and composition. This study conducted controlled experiments to compare the measurements of a real-time photometer, the SidePak AM510 monitor (SidePak), with gravimetric mass. PM sources tested were outdoor aerosols, and four indoor combustion sources: cigarettes, incense, wood chips, and toasting bread. The calibration factor for rescaling the SidePak measurements to agree with gravimetric mass was similar for the cigarette and incense sources, but different for burning wood chips and toasting bread. The calibration factors for ambient urban aerosols differed substantially from day to day, due to variations in the sources and composition of outdoor PM. A field evaluation inside a casino with active smokers yielded calibration factors consistent with those obtained in the controlled experiments with cigarette smoke.

Modeling exposure close to air pollution sources in naturally ventilated residences: association of turbulent diffusion coefficient with air change rate.

For modeling exposure close to an indoor air pollution source, an isotropic turbulent diffusion coefficient is used to represent the average spread of emissions. However, its magnitude indoors has been difficult to assess experimentally due to limitations in the number of monitors available. We used 30-37 real-time monitors to simultaneously measure CO at different angles and distances from a continuous indoor point source. For 11 experiments involving two houses, with natural ventilation conditions ranging from <0.2 to >5 air changes per h, an eddy diffusion model was used to estimate the turbulent diffusion coefficients, which ranged from 0.001 to 0.013 m² s⁻¹. The model reproduced observed concentrations with reasonable accuracy over radial distances of 0.25-5.0 m. The air change rate, as measured using a SF6 tracer gas release, showed a significant positive linear correlation with the air mixing rate, defined as the turbulent diffusion coefficient divided by a squared length scale representing the room size. The ability to estimate the indoor turbulent diffusion coefficient using two readily measurable parameters (air change rate and room dimensions) is useful for accurately modeling exposures in close proximity to an indoor pollution source.

Fine particle air pollution and secondhand smoke exposures and risks inside 66 US casinos.

Smoking bans often exempt casinos, exposing occupants to fine particles (PM(2.5)) from secondhand smoke. We quantified the relative contributions to PM(2.5) from both secondhand smoke and infiltrating outdoor sources in US casinos. We measured real-time PM(2.5), particulate polycyclic aromatic hydrocarbons (PPAH), and carbon dioxide (CO(2)) (as an index of ventilation rate) inside and outside 8 casinos in Reno, Nevada. We combined these data with data from previous studies, yielding a total of 66 US casinos with smoking in California, Delaware, Nevada, New Jersey, and Pennsylvania, developing PM(2.5) frequency distributions, with 3 nonsmoking casinos for comparison. Geometric means for PM(2.5) were 53.8 µg/m(3) (range 18.5-205 µg/m(3)) inside smoking casinos, 4.3 µg/m(3) (range 0.26-29.7 µg/m(3)) outside those casinos, and 3.1 µg/m(3) (range 0.6-9 µg/m(3)) inside 3 nonsmoking casinos. In a subset of 21 Reno and Las Vegas smoking casinos, PM(2.5) in gaming areas averaged 45.2 µg/m(3) (95% CI, 37.7-52.7 µg/m(3)); adjacent nonsmoking casino restaurants averaged 27.2 µg/m(3) (95% CI, 17.5-36.9 µg/m(3)), while PM(2.5) outside the casinos averaged 3.9 µg/m(3) (95% CI, 2.5-5.3 µg/m(3)). For a subset of 10 Nevada and Pennsylvania smoking casinos, incremental (indoor-outdoor) PM(2.5) was correlated with incremental PPAH (R(2)=0.79), with ventilation rate-adjusted smoker density (R(2)=0.73), and with smoker density (R(2)=0.60), but not with ventilation rates (R(2)=0.15). PPAH levels in 8 smoking casinos in 3 states averaged 4 times outdoors. The nonsmoking casinos' PM(2.5) (n=3) did not differ from outdoor levels, nor did their PPAH (n=2). Incremental PM(2.5) from secondhand smoke in approximately half the smoking casinos exceeded a level known to produce cardiovascular morbidity in nonsmokers after less than 2h of exposure, posing acute health risks to patrons and workers. Casino ventilation and air cleaning practices failed to control secondhand smoke PM(2.5). Drifting PM(2.5) from secondhand smoke contaminated unseparated nonsmoking areas. Smoke-free casinos reduced PM(2.5) to the same low levels found outdoors.

Measurement of fine particles and smoking activity in a statewide survey of 36 California Indian casinos.

Despite California's 1994 statewide smoking ban, exposure to secondhand smoke (SHS) continues in California's Indian casinos. Few data are available on exposure to airborne fine particles (PM2.5) in casinos, especially on a statewide basis. We sought to measure PM2.5 concentrations in Indian casinos widely distributed across California, exploring differences due to casino size, separation of smoking and non-smoking areas, and area smoker density. A selection of 36 out of the 58 Indian casinos throughout California were each visited for 1-3 h on weekend or holiday evenings, using two or more concealed monitors to measure PM2.5 concentrations every 10 s. For each casino, the physical dimensions and the number of patrons and smokers were estimated. As a preliminary assessment of representativeness, we also measured eight casinos in Reno, NV. The average PM2.5 concentration for the smoking slot machine areas (63 µg/m³) was nine times as high as outdoors (7 µg/m³), whereas casino non-smoking restaurants (29 µg/m³) were four times as high. Levels in non-smoking slot machine areas varied: complete physical separation reduced concentrations almost to outdoor levels, but two other separation types had mean levels that were 13 and 29 µg/m³, respectively, higher than outdoors. Elevated PM2.5 concentrations in casinos can be attributed primarily to SHS. Average PM2.5 concentrations during 0.5-1 h visits to smoking areas exceeded 35 µg/m³ for 90% of the casino visits.

Model-based reconstruction of the time response of electrochemical air pollutant monitors to rapidly varying concentrations.

Electrochemical sensors are commonly used to measure concentrations of gaseous air pollutants in real time, especially for personal exposure investigations. The monitors are small, portable, and have suitable response times for estimating time-averaged concentrations. However, for transient exposures to air pollutants lasting only seconds to minutes, a non-instantaneous time response can cause measured values to diverge from actual input concentrations, especially when the pollutant fluctuations are pronounced and rapid. Using 38 Langan carbon monoxide (CO) monitors, which can be set to log data every 2 s, we found electrochemical sensor response times of 30-50 s. We derived a simple model based on Fick's Law to reconstruct a close to accurate time series from logged data. Starting with experimentally measured data for repetitive step input signals of alternating high and low CO concentrations, we were able to reconstruct a much improved 2-s concentration time series using the model. We also utilized the model to examine errors in monitor measurements for different averaging times. By selecting the averaging time based on the response time of the monitor, the error between actual and measured pollutant levels can be minimized. The methodology presented in this study is useful when aiming to accurately determine a time series of rapidly time-varying concentrations, such as for locations close to an active point source or near moving traffic.

A comparison of particulate matter from biomass-burning rural and non-biomass-burning urban households in northeastern China.

BACKGROUND: Biomass fuel is the primary source of domestic fuel in much of rural China. Previous studies have not characterized particle exposure through time-activity diaries or personal monitoring in mainland China. OBJECTIVES: In this study we characterized indoor and personal particle exposure in six households in northeastern China (three urban, three rural) and explored differences by location, cooking status, activity, and fuel type. Rural homes used biomass. Urban homes used a combination of electricity and natural gas. METHODS: Stationary monitors measured hourly indoor particulate matter (PM) with an aerodynamic diameter < or = 10 microm (PM10) for rural and urban kitchens, urban sitting rooms, and outdoors. Personal monitors for PM with an aerodynamic diameter < or = 2.5 microm (PM2.5) were employed for 10 participants. Time-activity patterns in 30-min intervals were recorded by researchers for each participant. RESULTS: Stationary monitoring results indicate that rural kitchen PM10 levels are three times higher than those in urban kitchens during cooking. PM10 was 6.1 times higher during cooking periods than during noncooking periods for rural kitchens. Personal PM2.5 levels for rural cooks were 2.8-3.6 times higher than for all other participant categories. The highest PM2.5 exposures occurred during cooking periods for urban and rural cooks. However, rural cooks had 5.4 times higher PM2.5 levels during cooking than did urban cooks. Rural cooks spent 2.5 times more hours per day cooking than did their urban counterparts. CONCLUSIONS: These findings indicate that biomass burning for cooking contributes substantially to indoor particulate levels and that this exposure is particularly elevated for cooks. Second-by-second personal PM2.5 exposures revealed differences in exposures by population group and strong temporal heterogeneity that would be obscured by aggregate metrics.