Proposal of a Methodology for Prediction of Indoor PM2.5 Concentration Using Sensor-Based Residential Environments Monitoring Data and Time-Divided Multiple Linear Regression Model.

This study aims to propose an indoor air quality prediction method that can be easily utilized and reflects temporal characteristics using indoor and outdoor input data measured near the indoor target point as input to calculate indoor PM2.5 concentration through a multiple linear regression model. The atmospheric conditions and air pollution detected in one-minute intervals using sensor-based monitoring equipment (Dust Mon, Sentry Co Ltd., Seoul, Korea) inside and outside houses from May 2019 to April 2021 were used to develop the prediction model. By dividing the multiple linear regression model into one-hour increments, we attempted to overcome the limitation of not representing the multiple linear regression model's characteristics over time and limited input variables. The multiple linear regression (MLR) model classified by time unit showed an improvement in explanatory power by up to 9% compared to the existing model, and some hourly models had an explanatory power of 0.30. These results indicated that the model needs to be subdivided by time period to more accurately predict indoor PM2.5 concentrations.

Personal Exposure to PM2.5 Black Carbon and Aerosol Oxidative Potential using an Automated Microenvironmental Aerosol Sampler (AMAS).

Traditional methods for measuring personal exposure to fine particulate matter (PM2.5) are cumbersome and lack spatiotemporal resolution; methods that are time-resolved are limited to a single species/component of PM. To address these limitations, we developed an automated microenvironmental aerosol sampler (AMAS), capable of resolving personal exposure by microenvironment. The AMAS is a wearable device that uses a GPS sensor algorithm in conjunction with a custom valve manifold to sample PM2.5 onto distinct filter channels to evaluate home, school, and other (e.g., outdoors, in transit, etc.) exposures. Pilot testing was conducted in Fresno, CA where 25 high-school participants ( n = 37 sampling events) wore an AMAS for 48-h periods in November 2016. Data from 20 (54%) of the 48-h samples collected by participants were deemed valid and the filters were analyzed for PM2.5 black carbon (BC) using light transmissometry and aerosol oxidative potential (OP) using the dithiothreitol (DTT) assay. The amount of inhaled PM2.5 was calculated for each microenvironment to evaluate the health risks associated with exposure. On average, the estimated amount of inhaled PM2.5 BC (µg day-1) and OP [(µM min-1) day-1] was greatest at home, owing to the proportion of time spent within that microenvironment. Validation of the AMAS demonstrated good relative precision (8.7% among collocated instruments) and a mean absolute error of 22% for BC and 33% for OP when compared to a traditional personal sampling instrument. This work demonstrates the feasibility of new technology designed to quantify personal exposure to PM2.5 species within distinct microenvironments.

Source proximity and meteorological effects on residential outdoor VOCs in urban areas: Results from the Houston and Los Angeles RIOPA studies.

Concentrations of volatile organic compounds (VOCs) measured outside homes in Houston, TX and Los Angeles, CA were characterized by the effects of source proximity and meteorological factors. Benzene, toluene, ethylbenzene, m,p-xylene, o-xylene (BTEX), methyl tert butyl ether (MTBE), tetrachloroethylene (perchloroethylene, PCE), and carbon tetrachloride (CCl4) were examined. Multiple stepwise regression analysis converged the best-fit models with predictors from meteorological conditions and the proximity to specific point, area, and mobile sources on the residential outdoor VOC concentrations. Negative associations of wind speed with concentrations demonstrated the effect of dilution by high wind speed. Atmospheric stability increase was associated with concentration increase. Petrochemical source proximity was a significant predictor for BTEX and MTBE concentrations in Houston. Ethylbenzene and xylene source proximity was a significant predictor in Los Angeles. Close proximity to area sources such as scrap metal recycling or dry cleaning facilities increased the MTBE, PCE, and CCl4 concentrations in Houston and Los Angeles. Models for ethylbenzene, m,p-xylene, and MTBE in Houston, and benzene in Los Angeles explained that for the median values of the meteorological factors, homes closest to influential highways would have concentrations that were 1.7-2.2 fold higher than those furthest from these mobile emission sources. If the median distance to sources were used in the models, the VOC concentrations varied 1.7 to 6.6 fold as the meteorological conditions varied over the observed range. These results highlight that each urban area is unique and localized sources need to be carefully evaluated to understand potential contributions to VOC air concentrations near residences, which influence baseline indoor air concentrations and personal exposures. Results of this study could assist in the appropriate design of monitoring networks for community-level sampling. They may also improve the accuracy of exposure models linking emission sources with estimated pollutant concentrations at the residential level.

Effects of Air Pollution on Asthma Hospitalization Rates in Different Age Groups in Metropolitan Cities of Korea.

Many studies have shown associations between air pollution and asthma admissions in Korea, but have not reported whether these effects differ by age classification. The purpose of this study was to determine whether air pollution effects on asthmatic hospital admissions are different by three age groups (years): children (less than 15), adults (15-64; reference group), and the elderly (over 65). Daily time-series data from seven metropolitan cities in South Korea were analyzed in two stages. In the first stage, relative asthma morbidity rates associated with air pollution were estimated for each city and age group, using semi-parametric log-linear regression. In the second stage, estimates from all seven cities were combined by age group using Bayesian hierarchical modeling. The effects of exposure to particulate matter <10 micrometers in aerodynamic diameter (PM10), carbon monoxide (CO) and nitrogen dioxide (NO2) varied significantly by age groups. Using adults as the referent, the relative rate (RR) of asthma admissions with 10µg/m3 increase of PM10 is 1.5% (95%CI: 0.1-2.8%) lower for children, and 1.3% (95% CI: 0.7-1.9%) higher for the elderly; RR with 1ppm increase of CO is 1.9% (95% CI: 0.3-3.8%) lower for children; RR with 1ppb increase of NO2(1ppb) is 0.5% (95% CI: 0.3-0.7%) higher for the elderly. No significant age group difference in relative rate was found for ozone or sulfur dioxide.

Personal and ambient exposures to air toxics in Camden, New Jersey.

Personal exposures and ambient concentrations of air toxics were characterized in a pollution "hot spot" and an urban reference site, both in Camden, New Jersey. The hot spot was the city's Waterfront South neighborhood; the reference site was a neighborhood, about 1 km to the east, around the intersection of Copewood and Davis streets. Using personal exposure measurements, residential ambient air measurements, statistical analyses, and exposure modeling, we examined the impact of local industrial and mobile pollution sources, particularly diesel trucks, on personal exposures and ambient concentrations in the two neighborhoods. Presented in the report are details of our study design, sample and data collection methods, data- and model-analysis approaches, and results and key findings of the study. In summary, 107 participants were recruited from nonsmoking households, including 54 from Waterfront South and 53 from the Copewood-Davis area. Personal air samples were collected for 24 hr and measured for 32 target compounds--11 volatile organic compounds (VOCs*), four aldehydes, 16 polycyclic aromatic hydrocarbons (PAHs), and particulate matter (PM) with an aerodynamic diameter < or = 2.5 microm (PM2.5). Simultaneously with the personal monitoring, ambient concentrations of the target compounds were measured at two fixed monitoring sites, one each in the Waterfront South and Copewood-Davis neighborhoods. To understand the potential impact of local sources of air toxics on personal exposures caused by temporal (weekdays versus weekend days) and seasonal (summer versus winter) variations in source intensities of the air toxics, four measurements were made of each subject, two in summer and two in winter. Within each season, one measurement was made on a weekday and the other on a weekend day. A baseline questionnaire and a time diary with an activity questionnaire were administered to each participant in order to obtain information that could be used to understand personal exposure to specific air toxics measured during each sampling period. Given the number of emission sources of air toxics in Waterfront South, a spatial variation study consisting of three saturation-sampling campaigns was conducted to characterize the spatial distribution of VOCs and aldehydes in the two neighborhoods. Passive samplers were used to collect VOC and aldehyde samples for 24- and 48-hr sampling periods simultaneously at 22 and 16 grid-based sampling sites in Waterfront South and Copewood-Davis, respectively. Results showed that measured ambient concentrations of some target pollutants (mean +/- standard deviation [SD]), such as PM2.5 (31.3 +/- 12.5 microg/m3), toluene (4.24 +/- 5.23 microg/m3), and benzo[a]pyrene (0.36 +/- 0.45 ng/m3), were significantly higher (P < 0.05) in Waterfront South than in Copewood-Davis, where the concentrations of PM2.5, toluene, and benzo[a]pyrene were 25.3 +/- 11.9 microg/m3, 2.46 +/- 3.19 microg/m3, and 0.21 +/- 0.26 ng/m3, respectively. High concentrations of specific air toxics, such as 60 microg/m3 for toluene and 159 microg/m3 for methyl tert-butyl ether (MTBE), were also found in areas close to local stationary sources in Waterfront South during the saturation-sampling campaigns. Greater spatial variation in benzene, toluene, ethylbenzene, and xylenes (known collectively as BTEX) as well as of MTBE was observed in Waterfront South than in Copewood-Davis during days with low wind speed. These observations indicated the significant impact of local emission sources of these pollutants and possibly of other pollutants emitted by individual source types on air pollution in Waterfront South. (Waterfront South is a known hot spot for these pollutants.) There were no significant differences between Waterfront South and Copewood-Davis in mean concentrations of benzene or MTBE, although some stationary sources of the two compounds have been reported in Waterfront South. Further, a good correlation (R > 0.6) was found between benzene and MTBE in both locations. These results suggest that automobile exhausts were the main contributors to benzene and MTBE air pollution in both neighborhoods. Formaldehyde and acetaldehyde concentrations were found to be high in both neighborhoods. Mean (+/- SD) concentrations of formaldehyde were 20.2 +/- 19.5 microg/m3 in Waterfront South and 24.8 +/- 20.8 microg/m3 in Copewood-Davis. A similar trend was observed for the two compounds during the saturation-sampling campaigns. The results indicate that mobile sources (i.e., diesel trucks) had a large impact on formaldehyde and acetaldehyde concentrations in both neighborhoods and that both are aldehyde hot spots. The study also showed that PM2.5, aldehydes, BTEX, and MTBE concentrations in both Waterfront South and Copewood-Davis were higher than ambient background concentrations in New Jersey and than national average concentrations, indicating that both neighborhoods are in fact hot spots for these pollutants. Higher concentrations were observed on weekdays than on weekend days for several compounds, including toluene, ethylbenzene, and xylenes (known collectively as TEX) as well as PAHs and PM2.5. These observations showed the impact on ambient air pollution of higher traffic volumes and more active industrial and commercial operations in the study areas on weekdays. Seasonal variations differed by species. Concentrations of TEX, for example, were found to be higher in winter than in summer in both locations, possibly because of higher emission rates from automobiles and reduced photochemical reactivity in winter. In contrast, concentrations of MTBE were found to be significantly higher in summer than in winter in both locations, possibly because of higher evaporation rates from gasoline in summer. Similarly, concentrations of heavier PAHs, such as benzo[a]pyrene, were found to be higher in winter in both locations, possibly because of higher emission rates from mobile sources, the use of home heating, and the reduced photochemical reactivity of benzo[a]pyrene in winter. In contrast, concentrations of lighter PAHs were found to be higher in summer in both locations, possibly because of volatilization of these compounds from various surfaces in summer. In addition, higher concentrations of formaldehyde were observed in summer than in winter, possibly because of significant contributions from photochemical reactions to formaldehyde air pollution in summer. Personal concentrations of toluene (25.4 +/- 13.5 microg/m3) and acrolein (1.78 +/- 3.7 microg/m3) in Waterfront South were found to be higher than those in the Copewood-Davis neighborhood (13.1 +/- 15.3 microg/m3 for toluene and 1.27 +/- 2.36 microg/m3 for acrolein). However, personal concentrations for most of the other compounds measured in Waterfront South were found to be similar to or lower than those than in Copewood-Davis. (For example, mean +/- SD concentrations were 4.58 +/- 17.3 microg/m3 for benzene, 4.06 +/- 5.32 microg/m3 for MTBE, 16.8 +/- 15.5 microg/m3 for formaldehyde, and 0.40 +/- 0.94 ng/m3 for benzo[a]pyrene in Waterfront South and 9.19 +/- 34.0 microg/m3 for benzene, 6.22 +/- 19.0 microg/m3 for MTBE, 16.0 +/- 16.7 microg/m3 for formaldehyde, and 0.42 +/- 1.08 ng/m3 for benzo[a]pyrene in Copewood-Davis.) This was probably because many of the target compounds had both outdoor and indoor sources. The higher personal concentrations of these compounds in Copewood-Davis might have resulted in part from higher exposure to environmental tobacco smoke (ETS) of subjects from Copewood-Davis. The Spearman correlation coefficient (R) was found to be high for pollutants with significant outdoor sources. The R's for MTBE and carbon tetrachloride, for example, were > 0.65 in both Waterfront South and Copewood-Davis. The R's were moderate or low (0.3-0.6) for compounds with both outdoor and indoor sources, such as BTEX and formaldehyde. A weaker association (R < 0.5) was found for compounds with significant indoor sources, such as BTEX, formaldehyde, PAHs, and PM2.5. The correlations between personal and ambient concentrations of MTBE and BTEX were found to be stronger in Waterfront South than in Copewood-Davis, reflecting the significant impact of local air pollution sources on personal exposure to these pollutants in Waterfront South. Emission-based ambient concentrations of benzene, toluene, and formaldehyde and contributions of ambient exposure to personal concentrations of these three compounds were modeled using atmospheric dispersion modeling and Individual Based Exposure Modeling (IBEM) software, respectively, which were coupled for analysis in the Modeling Environment for Total Risk (MENTOR) system. The compounds were associated with the three types of dominant sources in the two neighborhoods: industrial sources (toluene), exhaust from gasoline-powered motor vehicles (benzene), and exhaust from diesel-powered motor vehicles (formaldehyde). Subsequently, both the calculated and measured ambient concentrations of each of the three compounds were separately combined with the time diaries and activity questionnaires completed by the subjects as inputs to IBEM-MENTOR for estimating personal exposures from ambient sources. Modeled ambient concentrations of benzene and toluene were generally in agreement with the measured ambient concentrations within a factor of two, but the values were underestimated at the high-end percentiles. The major local (neighborhood) contributors to ambient benzene concentrations were from mobile sources in the study areas; both mobile and stationary (point and area) sources contributed to the ambient toluene concentrations. This finding can be used as guidance for developing better emission inventories to characterize, through modeling, the ambient concentrations of air toxics in the study areas. (ABSTRACT TRUNCATED)

Concentrations and source characteristics of airborne carbonyl compounds measured outside urban residences.

This paper presents the analysis of ambient air concentrations of 10 carbonyl compounds (aldehydes and ketones) measured in the yards of 87 residences in the city of Elizabeth, NJ, throughout 1999-2001. Most of these residences were measured twice in different seasons; the sampling duration was 48 hr each time. The authors observed higher concentrations for most of the measured carbonyl compounds on warmer days, reflecting larger contributions of photochemical reactions on warmer days. The estimated contributions of photochemical production varied substantially across the measured carbonyl compounds and could be as high as 60%. Photochemical activity, however, resulted in a net loss for formaldehyde. The authors used stepwise multiple linear regression models to evaluate the impact of traffic sources and meteorological conditions on carbonyl concentrations using the data collected on colder days (with lower photochemical activities). They found that the concentrations of formaldehyde, acetaldehyde, acrolein, propionaldehyde, crotonaldehyde, benzaldehyde, glyoxal, and methylglyoxal significantly decreased with increasing distance between a measured residence and one or more major roadways. They also found significant negative associations between concentrations for most of the measured carbonyl compounds and each of the following meteorological parameters: mixing height, wind speed, and precipitation.

Source proximity and outdoor-residential VOC concentrations: results from the RIOPA study.

Ambient volatile organic compound concentrations outside residences were measured in Elizabeth, New Jersey as part of the Relationship of Indoor, Outdoor, and Personal A:r (RIOPA) study to assess the influence of proximity of the residences to known ambient emissions sources. The closest distances between the outdoor samplers and emission sources were determined using Geographic Information Systems (GIS)techniques. Multiple regression models were developed for residential ambient concentrations of aromatic hydrocarbons (BTEX), methyl tert butyl ether (MTBE), and tetrachloroethylene (PCE). The natural log transformed ambient concentrations of BTEX were inversely associated with distances to major roadways with high traffic densities and gasoline stations, atmospheric stability, temperature, and wind speed. Ambient MTBE levels were associated with inverse distance to gas stations and interstate highways. Residential ambient PCE concentration was inversely associated with distance to dry cleaning facilities, atmospheric stability, temperature, wind speed, and relative humidity. The linear regression models that include proximity to emission sources and meteorological variables explained 16-45% of the overall variation of ambient residential VOC concentrations. Meteorological conditions, especially atmospheric stability and temperature, explained 60-90% of the total variation in the regression models. The residential ambient air concentrations were 1.5-4 times higher than the urban background levels outside homes very close (<50 m) to ambient emission sources where approximately 7% of the population live. However, the relative increase of risk for disease is small and variations in air concentration in the background urban atmosphere are greater than those from the proximity to roadways.

Fine organic particulate matter dominates indoor-generated PM2.5 in RIOPA homes.

Residential indoor and outdoor fine particle (PM(2.5)) organic (OC) and elemental carbon (EC) concentrations (48 h) were measured at 173 homes in Houston, TX, Los Angeles County, CA, and Elizabeth, NJ as part of the Relationship of Indoor, Outdoor and Personal Air (RIOPA) study. The adsorption of organic vapors on the quartz fiber sampling filter (a positive artifact) was substantial indoors and out, accounting for 36% and 37% of measured OC at the median indoor (8.2 microg C/m(3)) and outdoor (5.0 microg C/m(3)) OC concentrations, respectively. Uncorrected, adsorption artifacts would lead to substantial overestimation of particulate OC both indoors and outdoors. After artifact correction, the mean particulate organic matter (OM=1.4 OC) concentration indoors (9.8 microg/m(3)) was twice the mean outdoor concentration (4.9 microg/m(3)). The mean EC concentration was 1.1 microg/m(3) both indoors and outdoors. OM accounted for 29%, 30% and 29% of PM(2.5) mass outdoors and 48%, 55% and 61% of indoor PM(2.5) mass in Los Angeles Co., Elizabeth and Houston study homes, respectively. Indirect evidence provided by species mass balance results suggests that PM(2.5) nitrate (not measured) was largely lost during outdoor-to-indoor transport, as reported by Lunden et al. This results in dramatic changes with outdoor-to-indoor transport in the mass and composition of ambient-generated PM(2.5) at California homes. On average, 71% to 76% of indoor OM was emitted or formed indoors, calculated by (1) Random Component Superposition (RCS) model and (2) non-linear fit of OC and air exchange rate data to the mass balance model. Assuming that all particles penetrate indoors (P=1) and there is no particle loss indoors (k=0), a lower bound estimate of 41% of indoor OM was indoor-generated (mean). OM appears to be the predominant species in indoor-generated PM(2.5), based on species mass balance results. Particulate OM emitted or formed indoors is substantial enough to alter the concentration, composition and behavior of indoor PM(2.5). One interesting effect of increased indoor OM concentrations is a shift in the gas-particle partitioning of polycyclic aromatic hydrocarbons (PAHs) from the gas to the particle phase with outdoor-to-indoor transport.

Influence of ambient (outdoor) sources on residential indoor and personal PM2.5 concentrations: analyses of RIOPA data.

The Relationship of Indoor, Outdoor and Personal Air (RIOPA) study was designed to investigate residential indoor, outdoor and personal exposures to several classes of air pollutants, including volatile organic compounds, carbonyls and fine particles (PM2.5). Samples were collected from summer, 1999 to spring, 2001 in Houston (TX), Los Angeles (CA) and Elizabeth (NJ). Indoor, outdoor and personal PM2.5 samples were collected at 212 nonsmoking residences, 162 of which were sampled twice. Some homes were chosen due to close proximity to ambient sources of one or more target analytes, while others were farther from sources. Median indoor, outdoor and personal PM2.5 mass concentrations for these three sites were 14.4, 15.5 and 31.4 microg/m3, respectively. The contributions of ambient (outdoor) and nonambient sources to indoor and personal concentrations were quantified using a single compartment box model with measured air exchange rate and a random component superposition (RCS) statistical model. The median contribution of ambient sources to indoor PM2.5 concentrations using the mass balance approach was estimated to be 56% for all study homes (63%, 52% and 33% for California, New Jersey and Texas study homes, respectively). Reasonable variations in model assumptions alter median ambient contributions by less than 20%. The mean of the distribution of ambient contributions across study homes agreed well for the mass balance and RCS models, but the distribution was somewhat broader when calculated using the mass balance model with measured air exchange rates.

Relationship of Indoor, Outdoor and Personal Air (RIOPA) study: study design, methods and quality assurance/control results.

The Relationship of Indoor, Outdoor and Personal Air (RIOPA) Study was undertaken to evaluate the contribution of outdoor sources of air toxics, as defined in the 1990 Clean Air Act Amendments, to indoor concentrations and personal exposures. The concentrations of 18 volatile organic compounds (VOCs), 17 carbonyl compounds, and fine particulate matter mass (PM(2.5)) were measured using 48-h outdoor, indoor and personal air samples collected simultaneously. PM2.5 mass, as well as several component species (elemental carbon, organic carbon, polyaromatic hydrocarbons and elemental analysis) were also measured; only PM(2.5) mass is reported here. Questionnaires were administered to characterize homes, neighborhoods and personal activities that might affect exposures. The air exchange rate was also measured in each home. Homes in close proximity (<0.5 km) to sources of air toxics were preferentially (2:1) selected for sampling. Approximately 100 non-smoking households in each of Elizabeth, NJ, Houston, TX, and Los Angeles, CA were sampled (100, 105, and 105 respectively) with second visits performed at 84, 93, and 81 homes in each city, respectively. VOC samples were collected at all homes, carbonyls at 90% and PM(2.5) at 60% of the homes. Personal samples were collected from nonsmoking adults and a portion of children living in the target homes. This manuscript provides the RIOPA study design and quality control and assurance data. The results from the RIOPA study can potentially provide information on the influence of ambient sources on indoor air concentrations and exposure for many air toxics and will furnish an opportunity to evaluate exposure models for these compounds.

Relationships of Indoor, Outdoor, and Personal Air (RIOPA). Part I. Collection methods and descriptive analyses.

This study on the relationships of indoor, outdoor, and personal air (RIOPA) was undertaken to collect data for use in evaluating the contribution of outdoor sources of air toxics and particulate matter (PM) to personal exposure. The study was not designed to obtain a population-based sample, but rather to provide matched indoor, outdoor, and personal concentrations in homes that varied in their proximity to outdoor pollution sources and had a wide range of air exchange rates (AERs). This design allowed examination of relations among indoor, outdoor, and personal concentrations of air toxics and PM across a wide range of environmental conditions; the resulting data set obtained for a wide range of environmental pollutants and AERs can be used to evaluate exposure models. Approximately 100 households with residents who do not smoke participated in each of three cities in distinct locations expected to have different climates and housing characteristics: Elizabeth, New Jersey; Houston, Texas; and Los Angeles County, California. Questionnaires were administered to characterize homes, neighborhoods, and personal activities that might affect exposures. The concentrations of a suite of volatile organic compounds (VOCs) and carbonyl compounds, as well as the fraction of airborne particulate matter with a mass median aerodynamic diameter < or = 2.5 microm (PM2.5), were measured during continuous 48-hour sessions in which indoor, outdoor, and personal air samples were collected simultaneously. During the same 48-hour period, the AER (exchanges/hr; x hr(-1)) was determined in each home, and carbonyl compounds were measured inside vehicle cabins driven by a subset of the participants. In most of the homes, measurements were made twice, during two different seasons, to obtain a wide distribution of AERs. This report presents in detail the data collection methods, quality control measures, and initial analyses of data distributions and relations among indoor, outdoor, and personal concentrations. The results show that indoor sources dominated personal and indoor air concentrations of many measured VOCs and carbonyl compounds. For several measured species, personal concentrations were higher than either indoor or outdoor concentrations, indicating the presence of some sources closely related to personal activities. For some species there were no significant indoor sources in the majority of the homes; thus indoor concentrations were mainly determined by outdoor concentrations in these homes. The range of distributions of air concentrations for the measured VOCs, formaldehyde and acetaldehyde, PM2.5, and AERs were generally consistent with values reported previously in the literature. Thus associations derived from or models based on this data set that may link the influence of outdoor sources with indoor air concentrations of air toxics and PM2.5 can be relevant to other urban settings. The simultaneous measurements of indoor concentrations, outdoor concentrations, AERs, and room volumes allowed the use of a mass balance model, under the steady-state approximation, to mechanistically examine the relative contributions of indoor and outdoor sources to measured indoor concentrations on a home-by-home basis. Estimated indoor source strengths for VOCs and carbonyl compounds varied widely from home to home, consistent with the indoor-outdoor concentration patterns, as shown in scatter plots. The indoor source estimations agreed with published values for PM2.5 and with the general understanding of sources of VOCs and carbonyl compounds. The source strengths reported here, derived from hundreds of homes, are an important contribution to the literature on exposure to air toxics. For the first time for many compounds, these estimates present a cohesive set of measurements across a range of air toxics in paired indoor, outdoor, and personal samples along with AER and questionnaire results that can be used for future analyses of indoor air quality. The estimation of outdoor contributions to measured indoor concentrations provides insights about the relative importance of indoor and outdoor sources in determining indoor concentrations, the main determinant of personal exposure for most of the measured compounds. In this report simple statistical tests mainly of the pooled data were used to analyze differences by sampling site, emission source type, season, home type, and home age. Paired adult-child personal concentrations within the same home were also compared using the pooled data set. These analyses generated some intriguing results that warrant more in-depth investigation in the future.

Polycyclic aromatic hydrocarbons in the indoor and outdoor air of three cities in the U.S.

The indoor and outdoor concentrations of 30 polycyclic aromatic hydrocarbons (PAHs) were measured in 55 nonsmoking residences in three urban areas during June 1999-May 2000. The data represent the subset of samples collected within the Relationship of Indoor, Outdoor, and Personal Air study (RIOPA). The study collected samples from homes in Los Angeles, CA, Houston, TX, and Elizabeth, NJ. In the outdoor samples, the total PAH concentrations (sigmaPAH) were 4.2-64 ng m(-3) in Los Angeles, 10-160 ng m(-3) in Houston, and 12-110 ng m(-3) in Elizabeth. In the indoor samples, the concentrations of sigmaPAH were 16-220 ng m(-3) in Los Angeles, 21-310 ng m(-3) in Houston, and 22-350 ng m(-3) in Elizabeth. The PAH profiles of low molecular weight PAHs (3-4 rings) in the outdoor samples from the three cities were not significantly different. In contrast, the profiles of 5-7-ring PAHs in thesethree citieswere significantlydifferent, which suggested different dominant PAH sources. The signatures of 5-7-ring PAHs in the indoor samples in each city were similar to the outdoor profiles, which suggested that indoor concentrations of 5-7-ring PAHs were dominated by outdoor sources. Indoor-to-outdoor ratios of the PAH concentrations showed that indoor sources had a significant effect on indoor concentrations of 3-ring PAHs and a smaller effect on 4-ring PAHs and that outdoor sources dominated the indoor concentrations of 5-7-ring PAHs.