Sources of personal exposure to fine particles in Toronto, Ontario, Canada

Individuals are exposed to particulate matter from both indoor and outdoor sources. The aim of this study was to compare the relative contributions of three sources of personal exposure to fine particles (PM2.5) by using chemical tracers. The study design incorporated repeated 24-hr personal exposure measurements of air pollution from 28 cardiac-compromised residents of Toronto, Ontario, Canada. Each study participant wore the Rupprecht & Patashnick ChemPass Personal Sampling System 1 day a week for a maximum of 10 weeks. During their individual exposure measurement days the subjects reported to have spent an average of 89% of their time indoors. Particle phase elemental carbon, sulfate, and calcium personal exposure data were used in a mixed-effects model as tracers for outdoor PM2.5 from traffic-related combustion, regional, and local crustal materials, respectively. These three sources were found to contribute 13% +/- 10%, 17% +/- 16%, and 7% +/- 6% of PM2.5 exposures. The remaining fraction of the personal PM2.5 is hypothesized to be predominantly related to indoor sources. For comparison, central site outdoor PM2.5 measurements for the same dates as personal measurements were used to construct a receptor model using the same three tracers. In this case, traffic-related combustion, regional, and local crustal materials were found to contribute 19% +/- 17%, 52% +/- 22%, and 10% +/- 7%, respectively. Our results indicate that the three outdoor PM2.5 sources considered are statistically significant contributors to personal exposure to PM2.5. Our results also suggest that among the Toronto subjects, who spent a considerable amount of time indoors, exposure to outdoor PM2.5 includes a greater relative contribution from combustion sources compared with outdoor PM2.5 measurements where regional sources are the dominant contributor.     

Modeling exposure to particulate matter

Exposure assessment, a component of risk assessment, links sources of pollution with health effects. Exposure models are scientific tools used to gain insights into the processes affecting exposure assessment. The purpose of this paper is to review the process and methodology of estimating inhalation exposure to particulate matter (PM) using various types of models. Three types of models are discussed in the paper. Indirect type of models are physical models that employ inventories of outdoor and indoor sources and their emission rates to identify major sources contributing to exposure to PM, and use fate and transport and indoor air quality models to estimate PM concentrations at receptor sites. PM concentrations and time spent by a subject at each receptor site are input variables to the conventional exposure model that estimates the desired exposure levels. Direct type models use measured exposure or exposure concentrations in conjunction with information obtained from questionnaires to formulate exposure regression models. Stochastic models use exposure measurements, estimates can also be used, to formulate exposure population distributions and investigate associated uncertainty and variability. Since models developed using databases from western countries are not necessarily applicable in developing countries, the difference in requirements among western and developing countries is highlighted in the paper. Employment of exposure modeling methods in developing countries requires development of local information. Such information includes local outdoor and indoor source inventories, local or regional meteorological conditions, adjustment of indoor models to reflect local building construction conditions, and use of questionnaires to obtain local time budget and activity patterns of the subject population.     

Comparison of short-term variations (15-minute averages) in outdoor and indoor PM2.5 concentrations

Measurements of 15-min average PM2.5 concentrations were made with a real-time light-scattering instrument at both outdoor (central monitoring sites in three communities) and indoor (residential) locations over two seasons in the Minneapolis-St. Paul metropolitan area. These data are used to examine within-day variability of PM2.5 concentrations indoors and outdoors, as well as matched indoor-to-outdoor (I/O) ratios. Concurrent gravimetric measurements of 24-hr average PM2.5 concentrations were also obtained as a way to compare real-time measures with this more traditional metric. Results indicate that (1) within-day variability for both indoor and outdoor 15-min average PM2.5 concentrations was substantial and comparable in magnitude to day-to-day variability for 24-hr average concentrations; (2) some residences exhibited substantial variability in indoor aerosol characteristics from one day to the next; (3) peak values for indoor short-term (15-min) average PM2.5 concentrations routinely exceeded 24-hr average outdoor values by factors of 3-4; and (4) relatively strong correlations existed between indoor and outdoor PM2.5 concentrations for both 24-hr and 15-min averages.     

The influence of human activity patterns on personal PM exposure: a comparative analysis of filter-based and continuous particle measurements

Particulate matter (PM) exposure data from the U.S. Environmental Protection Agency (EPA)-sponsored 1998 Baltimore and 1999 Fresno PM exposure studies were analyzed to identify important microenvironments and activities that may lead to increased particle exposure for select elderly (>65 years old) subjects. Integrated 24-hr filter-based PM2.5 or PM10 mass measurements [using Personal Environmental Monitors (PEMs)] included personal measurements, indoor and outdoor residential measurements, and measurements at a central indoor site and a community monitoring site. A subset of the participants in each study wore passive nephelometers that continuously measured (1-min averaging time) particles ranging in size from 0.1 to approximately 10 microm. Significant activities and locations were identified by a statistical mixed model (p < 0.01) for each study population based on the measured PM2.5 or PM10 mass and time activity data. Elevated PM concentrations were associated with traveling (car or bus), commercial locations (store, office, mall, etc.), restaurants, and working. The modeled results were compared to continuous PM concentrations determined by the nephelometers while participants were in these locations. Overall, the nephelometer data agreed within 6% of the modeled PM2.5 results for the Baltimore participants and within approximately 20% for the Fresno participants (variability was due to zero drift associated with the nephelometer). The nephelometer did not agree as well with the PM10 mass measurements, most likely because the nephelometer optimally responds to fine particles (0.3-2 microm). Approximately one-half (54 +/- 31%; mean +/- standard deviation from both studies) of the average daily PM2.5 exposure occurred inside residences, where the participants spent an average of 83 +/- 10% of their time. These data also showed that a significant portion of PM2.5 exposure occurred in locations where participants spent only 4-13% of their time.     

Chapter one: exposure measurements

Determining human exposure to suspended particulate concentrations requires measurements that quantify different particle properties in microenvironments where people live, work, and play. Particle mass, size, and chemical composition are important exposure variables, and these are typically measured with time-integrated samples on filters that are later submitted to laboratory analyses. This requires substantial sample handling, quality assurance, and data reduction. Newer technologies are being developed that allow in-situ, time-resolved measurements for mass, carbon, sulfate, nitrate, particle size, and other variables. These are large measurement systems that are more suitable for fixed monitoring sites than for personal applications. Human exposure studies need to be designed to accomplish specific objectives rather than to serve too many purposes. Resources need to be divided among study design, field sampling, laboratory analysis, quality assurance, data management, and data analysis phases. Many exposure projects allocated too little to the non-measurement activities.     

Personal exposure to fine particulate matter in elderly subjects: relation between personal, indoor, and outdoor concentrations

The time-series correlation between ambient levels, indoor levels, and personal exposure to PM2.5 was assessed in panels of elderly subjects with cardiovascular disease in Amsterdam, the Netherlands, and Helsinki, Finland. Subjects were followed for 6 months with biweekly clinical visits. Each subject's indoor and personal exposure to PM2.5 was measured biweekly, during the 24-hr period preceding the clinical visits. Outdoor PM2.5 concentrations were measured at fixed sites. The absorption coefficients of all PM2.5 filters were measured as a marker for elemental carbon (EC). Regression analyses were conducted for each subject separately, and the distribution of the individual regression and correlation coefficients was investigated. Personal, indoor, and ambient concentrations were highly correlated within subjects over time. Median Pearson's R between personal and outdoor PM2.5 was 0.79 in Amsterdam and 0.76 in Helsinki. For absorption, these values were 0.93 and 0.81 for Amsterdam and Helsinki, respectively. The findings of this study provide further support for using fixed-site measurements as a measure of exposure to PM2.5 in epidemiological time-series studies.     

Workplace exposure to bioaerosols in pet shops, pet clinics, and flower gardens

The present study evaluated exposure to bioaerosols at three different types of facilities (pet shops, pet clinics, and flower gardens) by measuring the bacterial, fungal and/or PM(10) concentrations in indoor and outdoor air. Regardless of the season, the total bacteria and total fungi were detected for all samples, whereas the fungal genera were not. The bioaerosol concentrations measured in the flower gardens were significantly higher than those of the pet shops and pet clinics. The mean microbial concentrations at the three types of facilities were close to or exceeded the Korean indoor bioaerosol guidelines (800 CFU m(-3)), thus suggesting the need for remedial action regarding indoor microorganisms, in order to reduce the exposure at the surveyed facilities. Another suggestion was that contrary to the airborne microbes, flower gardens are not an important microenvironment for PM(10) (particulate matter 10 microm in aerodynamic diameter) exposure. Two temporal characteristics (seasonal variation and the summer survey period) were important regarding exposure to airborne microbes, depending upon the type of facility surveyed, microbial or sample types, whereas the sampling time of the day was not. The microbial concentration ratio of indoor air to outdoor air depended upon the facility and season.     

Spatial characteristics of fine particulate matter: identifying representative monitoring locations in Seattle, Washington

This study investigates how PM2.5 varies spatially and how these spatial characteristics can be used to identify potential monitoring sites that are most representative of the overall ambient exposures to PM2.5 among susceptible populations in the Seattle, WA, area. Data collected at outdoor sites at the homes of participants of a large exposure assessment study were used in this study. Harvard impactors (HIs) were used at 40 outdoor sites throughout the Seattle metropolitan area. Up to six sites at a time were monitored for 10 consecutive 24-hr average periods. A fixed-effect analysis of variance (ANOVA) model that included date and location effects was used to analyze the spatial variability of outdoor PM2.5 concentrations. Both date and location effects were shown to be highly significant, explaining 92% of the variability in outdoor PM2.5 measurements. The day-to-day variability was 10 times higher than the spatial variability between sites. The site mean square was more than twice the error mean square, showing that differences between sites, while modest, are potentially an important contribution to measurement error. Variances of the model residuals and site effects were examined against spatial characteristics of the monitoring sites. The spatial characteristics included elevation, distance from arterials, and distance from major PM2.5 point sources. Results showed that the most representative PM2.5 sites were located at elevations of 80-120 m above sea level, and at distances of 100-300 m from the nearest arterial road. Location relative to industrial PM2.5 sources is not a significant predictor of residential outdoor PM2.5 measurements. Additionally, for sites to be representative of the average population exposures to PM2.5 among those highly susceptible to the health effects of PM2.5, areas of high elderly population density were considered. These representative spatial characteristics were used as multiple, overlapping criteria in a Geographic Information System (GIS) analysis to determine where the most representative sites are located.     

Development of a microscale emission factor model for particulate matter for predicting real-time motor vehicle emissions

The U.S. Environmental Protection Agency's National Exposure Research Laboratory is pursuing a project to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop improved methods for modeling the source through the air pathway to human exposure in significant exposure microenvironments. Current particulate matter (PM) emission models, particle emission factor model (used in the United States, except California) and motor vehicle emission factor model (used in California only), are suitable only for county-scale modeling and emission inventories. There is a need to develop a site-specific real-time emission factor model for PM emissions to support human exposure studies near roadways. A microscale emission factor model for predicting site-specific real-time motor vehicle PM (MicroFacPM) emissions for total suspended PM, PM less than 10 microm aerodynamic diameter, and PM less than 2.5 microm aerodynamic diameter has been developed. The algorithm used to calculate emission factors in MicroFacPM is disaggregated, and emission factors are calculated from a real-time fleet, rather than from a fleet-wide average estimated by a vehicle-miles-traveled weighting of the emission factors for different vehicle classes. MicroFacPM requires input information necessary to characterize the site-specific real-time fleet being modeled. Other variables required include average vehicle speed, time and day of the year, ambient temperature, and relative humidity.     

Seasonal and diurnal variability in airborne mold from an indoor residential environment in northern New York

It is well known that characterization of airborne bioaerosols in indoor environments is a challenge because of inherent irregularity in concentrations, which are influenced by many environmental factors. The primary aim of this study was to quantify the day-to-day variability of airborne fungal levels in a single residential environment over multiple seasons. Indoor air quality practitioners must recognize the inherent variability in airborne bio-aerosol measurements during data analysis of mold investigations. Changes in airborne fungi due to varying season and day is important to recognize when considering health impacts of these contaminants and when establishing effective controls. Using an Andersen N6 impactor, indoor and outdoor bioaerosol samples were collected on malt extract agar plates for 18 weekdays and 19 weekdays in winter and summer, respectively. Interday and intraday variability for the bioaerosols were determined for each sampler. Average fungal concentrations were 26 times higher during the summer months. Day-to-day fungal samples showed a relatively high inconsistency suggesting airborne fungal levels are very episodic and are influenced by several environmental factors. Summer bio-aerosol variability ranged from 7 to 36% and winter variability from 24 to 212%; these should be incorporated into results of indoor mold investigations. The second objective was to observe the relationship between biological and nonbiological particulate matter (PM). No correlation was observed between biological and nonbiological PM. Six side-by-side particulate samplers collected coarse PM (PM10) and fine PM (PM2.5) levels in both seasons. PM2.5 particulate concentrations were found to be statistically higher during summer months. Interday variability observed during this study suggests that indoor air quality practitioners must adjust their exposure assessment strategies to reflect the temporal variability in bioaerosol concentrations.     

Measurements of personal exposure to nitrogen dioxide in four Mexican cities in 1996

Nitrogen dioxide is a ubiquitous pollutant in urban areas. Indoor NO2 concentrations are influenced by penetration of outdoor concentrations and by indoor sources. The objectives of this study were to evaluate personal exposure to NO2, taking into account human time-activity patterns in four Mexican cities. Passive filter badges were used for indoor, outdoor, and personal NO2 measurements over 48 hr and indoor workplace measurements over 16 hr. Volunteers completed a questionnaire on exposure factors and a time-activity diary during the sample period. An unpaired t test, an analysis of variance (ANOVA), and a linear regression were performed to compare differences among cities and mean personal NO2 concentrations involving housing characteristics, as well as to determine which variables predicted the personal NO2 concentration. Sampling periods were in April, May, and June 1996 in Mexico City, Guadalajara, Cuernavaca, and Monterrey. All 122 volunteers in the study were working adults, with a mean age of 34 (SD +/- 7.38); 64% were female, and the majority worked in public offices and universities. The highest NO2 concentrations were found in Mexico City (36 ppb for outdoor, 57 ppb for indoor, and 39 ppb for personal concentration) and the lowest in Monterrey (19 ppb for outdoor, 24 ppb for indoor, and 24 ppb for personal concentration). Significant differences in NO2 concentrations were found among the cities in different microenvironments. During the sampling period, volunteers spent 85% of their time indoors. The highest personal NO2 concentration was found when volunteers kept their windows closed (p = 0.03). In the regression model adjusted by city and gender, the best predictors of personal NO2 concentration were outdoor levels and time spent outdoors (R2 = 0.68). These findings suggest that outdoor NO2 concentrations were an important influence on the personal exposure to NO2, due to the specific characteristics and personal behavior of the people in these Mexican cities.     

Retrospective prediction of intraurban spatiotemporal distribution of PM2.5 in Taipei

Numerous studies have shown that fine airborne particulate matter particles (PM2.5) are more dangerous to human health than coarse particles, e.g. PM10. The assessment of the impacts to human health or ecological effects by long-term PM2.5 exposure is often limited by lack of PM2.5 measurements. In Taipei, PM2.5 was not systematically observed until August, 2005. Taipei is the largest metropolitan area in Taiwan, where a variety of industrial and traffic emissions are continuously generated and distributed across space and time. PM-related data, i.e., PM10 and Total Suspended Particles (TSP) are independently systematically collected by different central and local government institutes. In this study, the retrospective prediction of spatiotemporal distribution of monthly PM2.5 over Taipei will be performed by using Bayesian Maximum Entropy method (BME) to integrate (a) the spatiotemporal dependence among PM measurements (i.e. PM10, TSP, and PM2.5), (b) the site-specific information of PM measurements which can be certain or uncertain information, and (c) empirical evidence about the PM2.5/PM10 and PM10/TSP ratios. The performance assessment of the retrospective prediction for the spatiotemporal distribution of PM2.5 was performed over space and time during 2003–2004 by comparing the posterior pdf of PM2.5 with the observations. Results show that the incorporation of PM10 and TSP observations by BME method can effectively improve the spatiotemporal PM2.5 estimation in the sense of lower mean and standard deviation of estimation errors. Moreover, the spatiotemporal retrospective prediction with PM2.5/PM10 and PM2.5/TSP ratios can provide good estimations of the range of PM2.5 levels over space and time during 2003–2004 in Taipei.     

A review of the impact of fireworks on particulate matter in ambient air

To determine the impact of fireworks (FW) and firecrackers (FC) on particulate matter (PM) in ambient air, we reviewed evidence related to ambient PM during FW/FC periods; specifically, PM concentration, size, morphology, chemical components, including water-soluble ions and trace metals, and associated human health risks caused by exposure to FW/FC PM were reviewed. A large body of research suggests that outdoor ambient PM levels increase significantly during FW/FC displays. Furthermore, FW/FC PM remains suspended in the air, contributing to high PM concentrations for a long period. Increased PM from burning FW and FC mainly comprises fine and ultrafine spherical particles. Elevated levels of various trace metals, ions, elemental carbon (EC), organic carbon (OC), and organics in PM are present during FW/FC periods.Implications: Unique physical and chemical properties of ambient PM during short-term FW/FC burning can lead to a substantial increase in adverse health effects compared with during non-FW/FC periods. Further epidemiological and toxicological research into the potential health effects resulting from exposure to various pollutants from FW/FC is vital. Geographical distributions of PM concentrations during FW displays highlight the importance of implementing PM controls at the regional level and formulating stricter protective environmental legislation, particularly in Asian (e.g., India, China, or Taiwan) where festivals are not the only periods celebrated with FW/FC.     

Individual particle analysis of indoor,outdoor, and community samples from the 1998 Baltimore particulate matter study

The United States Environmental Protection Agency (US EPA) recently conducted the 1998 Baltimore Particulate Matter (PM) Epidemiology-Exposure Study of the Elderly. The primary goal of that study was to establish the relationship between outdoor PM concentrations and actual human PM exposures within a susceptible (elderly) sub-population. Personal, indoor, and outdoor sampling of particulate matter was conducted at a retirement center in the Towson area of northern Baltimore County. Concurrent sampling was conducted at a central community site. The main objective of this work was to use computer-controlled scanning electron microscopy (CCSEM) with individual-particle X-ray analysis to measure the chemical and physical characteristics of geological and trace element particles collected at the various sampling locations in and around the retirement facility.The CCSEM results show that the relative abundances of some geological and trace element particle classes identified at the outdoor and community locations differ from each other and from the indoor location. Particle images acquired during the computer-controlled analyses played a key role in the identification of certain particle types. Review of these images was particularly useful in distinguishing spherical particles (usually indicative of combustion) from non-spherical particles of similar chemical composition. Pollens and spores were also identified through a manual review of the particle images.     

Exposure of chronic obstructive pulmonary disease patients to particulate matter: relationships between personal and ambient air concentrations

Mot time-series studies of particulate air pollution and acute health outcomes assess exposure of the study population using fixed-site outdoor measurements. To address the issue of exposure misclassification, we evaluate the relationship between ambient particle concentrations and personal exposures of a population expected to be at risk of particle health effects. Sampling was conducted within the Vancouver metropolitan area during April-September 1998. Sixteen subjects (non-smoking, ages 54-86) with physician-diagnosed chronic obstructive pulmonary disease (COPD) wore personal PM2.5 monitors for seven 24-hr periods, randomly spaced approximately 1.5 weeks apart. Time-activity logs and dwelling characteristics data were also obtained for each subject. Daily 24-hr ambient PM10 and PM2.5 concentrations were measured at five fixed sites spaced throughout the study region. SO4(2-), which is found almost exclusively in the fine particle fraction and which does not have major indoor sources, was measured in all PM2.5 samples as an indicator of accumulation mode particulate matter of ambient origin. The mean personal and ambient PM2.5 concentrations were 18 micrograms/m3 and 11 micrograms/m3, respectively. In analyses relating personal and ambient measurements, ambient concentrations were expressed either as an average of the values obtained from five ambient monitoring sites for each day of personal sampling, or as the concentration obtained at the ambient site closest to each subject's home. The mean personal to ambient concentration ratio of all samples was 1.75 (range = 0.24 to 10.60) for PM2.5, and 0.75 (range = 0.09 to 1.42) for SO4(2-). Regression analyses were conducted for each subject separately and on pooled data. The median correlation (Pearson's r) between personal and average ambient PM2.5 concentrations was 0.48 (range = -0.68 to 0.83). Using SO4(2-) as the exposure metric, the median r between personal and average ambient concentrations was 0.96 (range = 0.66 to 1.0). Use of the closest ambient site did not improve the median correlation of the group for either PM2.5 or SO4(2-). All pooled analyses resulted in lower correlation coefficients than the median correlation coefficient of individual regressions. Personal SO4(2-) was more highly correlated with all ambient measures than PM2.5. Inclusion of time-activity and dwelling characteristics data did not result in a useful predictive regression model for PM2.5 personal exposure, but improved the model fit from simply regressing against ambient concentration (R2 = 0.27). The model for SO4(2-) was predictive (R2 = 0.82), as personal exposures were largely explained by ambient levels. These results indicate a relatively low correlation between personal exposure and ambient PM2.5 that is not improved by assigning exposure to the closest ambient monitor. The correlation between personal exposure and ambient concentration is high, however, when using SO4(2-), an indicator of accumulation mode particulate matter of ambient origin.     

Worshippers' exposure to particulate matter in two temples in Taiwan

Worshippers in temples may be exposed to high concentrations of pollutants emitted from incense burning. This work assessed the PM2.5 and PM10 exposures of temple worshippers in Taiwan and explored the important exposure determinants such as numbers of passing visitors and joss sticks in censers, worshipping dates, and temple characteristics. Sampling was conducted on the 1st, 2nd, 15th, and 16th of the lunar month in two temples in Taichung, Taiwan. Research staff took samples by wearing one PM2.5 and one PM10 sampler and imitating worshipping activity. Personal environmental monitors connected to personal pumps with 2-L/min flow rates were used for sampling. PM10 samples were also simultaneously taken outside the temples. The results suggested that burning joss sticks in temples is a significant PM exposure source. The geometric mean of personal exposure was 444 microg/m3 PM2.5 [geometric standard deviation (GSD) = 1.8] and 583 microg/m3 PM10 (GSD = 1.4). The latter was approximately 4-6 times that of roadside concentrations. Exposures on the 1st and 15th (with more visitors and more joss sticks) were about 130 microg/m3 PM2.5 and 249 microg/m3 PM10 higher than those on the 2nd and the 16th. Furthermore, each joss stick in the censer contributed about 0.40 microg/m3 of particles to the worshippers' exposure. In the worst case, PM exposure during one temple visit would account for 11% of the personal exposure in one day.     

Personal exposures to particles and their relationships with personal activities for chronic obstructive pulmonary disease patients living in Boston

An exposure study of 18 subjects with chronic obstructive pulmonary disease (COPD) living in the Boston, MA, area was conducted. The objective was to examine determinants of personal exposures to particulate matter (PM) with aerodynamic diameters of less than 2.5 microm (PM2.5), less than 10 microm (PM10), and between 2.5 and 10 microm (PM2.5-10). In a previous publication, the analyses of the longitudinal individual-specific relationships among indoor, outdoor, and personal levels showed that the relationships varied by subject and by particle size fraction. In the present paper, statistical and physical models were used to examine personal PM2.5, PM10, and PM2.5-10 exposure covariates. Results indicated that time-weighted indoor concentrations were significant predictors of personal PM2.5, PM10, and PM2.5-10 exposures. Also, time-weighted outdoor concentrations, time spent near smokers, and time spent during transportation were important predictors for PM2.5 but not for personal PM2.5-10 exposures. In turn, time spent cleaning contributed to all size-fraction personal exposures, whereas cooking affected only personal PM2.5-10 exposures. The findings showed that the relationship between personal PM2.5 exposures and the corresponding ambient concentrations was influenced by home air exchange rates (or by ventilation status). Because the particle properties or components causing the health effects are unknown, it is not certain to what extent the risk posed by ambient particles can be reduced by controlling any one of these factors.     

Time-resolved measurements of aerosol elemental concentrations in indoor working environments

We have measured the elemental concentrations in aerosols with a 2-h time resolution in two different types of working environment: a chemistry laboratory dealing with the processing of advanced nanoparticulate materials and a medium-sized machine workshop. Non-stop 10-day and 12-day samplings were performed at each location in order to determine the concentration trends during the non-working/working and weekday/weekend periods. Supplementary measurements of PM10 aerosols with a 2-day sample collection time were performed with a standard Gent PM10 sampler to compare the elemental concentrations with the time-averaged concentrations detected by the 2D step-sampler. The concentrations were determined a posteriori by analyzing the x-ray spectra of aerosol samples emitted after 3-MeV proton bombardment. The PM10 samples collected in the chemistry laboratory were additionally inspected by scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX) to determine the chemical compositions of the individual particles. In the workshop, a total PM10 mass sampling was performed simultaneously with a minute resolution to compare the signal with typical outdoor PM10 concentration levels. A factor analysis of the time-resolved dataset points to six and eight factors in the chemistry laboratory and the machine workshop, respectively. These factors describe most of the data variance, and their composition in terms of different elements can be related to specific indoor activities and conditions. We were able to demonstrate that the elemental concentration sampling with hourly resolution is an excellent tool for studying the indoor air pollution. While sampling the total PM10 mass concentration with a minute resolution may lack the potential to identify the emission sources in a “noisy” environment, the time averaging on a day time scale is too coarse to cope with the working dynamics, even if elemental sensitivity is an option.     

Outdoor versus indoor contributions to indoor particulate matter (PM) determined by mass balance methods

This study compares an indoor-outdoor air-exchange mass balance model (IO model) with a chemical mass balance (CMB) model. The models were used to determine the contribution of outdoor sources and indoor resuspension activities to indoor particulate matter (PM) concentrations. Simultaneous indoor and outdoor measurements of PM concentration, chemical composition, and air-exchange rate were made for five consecutive days at a single-family residence using particle counters, nephelometers, and filter samples of integrated PM with an aerodynamic diameter of less than or equal to 2.5 microm (PM2.5) and PM with an aerodynamic diameter of less than or equal to 5 microm (PM5). Chemical compositions were determined by inductively coupled plasma mass-spectrometry. During three high-activity days, prescribed activities, such as cleaning and walking, were conducted over a period of 4-6 hr. For the remaining two days, indoor activities were minimal. Indoor sources accounted for 60-89% of the PM2.5 and more than 90% of the PM5 for the high-activity days. For the minimal-activity days, indoor sources accounted for 27-47% of PM2.5 and 44-60% of the PM5. Good agreement was found between the two mass balance methods. Indoor PM2.5 originating outdoors averaged 53% of outdoor concentrations.     

An alternative way to determine the size distribution of airborne particulate matter

We developed and tested a methodology to extract both the size-segregated source apportionment of atmospheric aerosol and the size distribution of each detected element. The experiment is based on the parallel use of a standard low-volume sampler to collect Particulate Matter (PM) and an Optical Particle Counter (OPC). The approach is complementary to size-segregated PM sampling, and it was tested versus a 12-stage cascade impactor. Samples were collected inside the urban area of Genoa (Italy) and their elemental composition was measured by Energy Dispersive-X Ray Fluorescence (ED-XRF). Positive Matrix Factorization (PMF) was applied to time series of elemental concentrations to identify major PM sources, and both PM mass concentration and size-segregated particle number concentration were apportioned. Source profiles and temporal trends extracted by PMF were analyzed together with the OPC data to obtain the size distribution for several elements. The new methodology proved to be reliable for the PM apportionment as well as in providing the elemental concentrations in PM10, PM2.5, and PM1 (PM with aerodynamic diameter, D_ae < 10, 2.5, and 1 μm, respectively). The elemental size distributions are in good agreement with those obtained by the cascade impactor for several elements but some discrepancies, in particular for traffic emissions, are stressed and discussed in the text. The new methodology has two main advantages: it only requires standard semi-automatic sampling equipment and compositional analysis and it provides size-segregated information averaged over quite long periods (typically several months). This is particularly important since campaigns with cascade impactors are generally laborious and thus limited to short periods.