Mass concentration and elemental composition of PM10 in classrooms

Trace elements in outdoor and indoor PM2.5 in urban schools in Xi'an, Western China: characteristics, sources identification and health risk assessment

The PM_2.5-bounded elements were measured in outdoor and indoor from two urban middle schools in Xi'an. The PM_2.5 mass was from 42.4 to 283.7 µg/m³ with bounded element from 3.4 to 41.7 µg/m³. Both the particle mass and the bounded elements displayed higher levels compared with previous studies in school environments. The most abundant elements were Ca, K, Fe, S, Zn and Cl both indoor and outdoor in two schools, which accounted for about 90% of the total elements. Strong correlations between indoor and outdoor were obtained along with relative effect from students' and teachers' activities on the indoor distributions between workdays and weekends. There had different indoor/outdoor (I/O) distributions for the two schools. It revealed the main outdoor sources for elements in JT and predominance of indoor sources in HT. The principal component analysis investigated main sources of elements in this study were coal combustion, geogenic dust and industrial emission, even though there displayed differences in the two school classrooms. The health risk assessment showed that the cancer risk for Ni and Pb was below the safe value while As and Cr might pose acceptable potential threat to both students' and teachers' health. The total non-cancer risks of accumulative multi-metals in JT exhibited to be higher than 1, indicating that there existed the potential non-carcinogenic health risks of exposure metals.

Indoor carbon dioxide concentrations in Croatian elementary school classrooms during the heating season

Aware that exposure to stuffy indoor air with high levels of carbon dioxide (CO2) is associated with higher absenteeism and reduced academic performance in school pupils, the World Health Organization (WHO) Regional Office for Europe initiated indoor air quality surveys in schools, including CO2 monitoring, to assess ventilation and exposure to stuffy air. Here we report the findings of the first such survey in Croatia. It was conducted in 60 classrooms of 20 urban and rural elementary schools throughout the country during the heating season. Measurements of CO2 levels showed that all 60 classrooms exceeded the international guidelines of 1938 mg/m3. Mean CO2 concentrations ranged from 2771 to 7763 mg/m3. The highest concentration measured in urban schools was 7763 mg/m3 and in rural schools 4771 mg/m3. Average CO2 levels were higher in continental schools (3683 mg/m3) than the coastal ones (3134 mg/m3), but all demonstrate poor ventilation during the heating season all over Croatia.

Air quality of an urban school in São Paulo city

A major campaign was carried out in indoor and outdoor environments in a school located in the university campus of the city of São Paulo. Elements, PAH, oxy-PAH, water-soluble ions and black carbon were determined and compared with preliminary campaigns. The results indicated that the concentrations of particles and organic compounds were higher indoors. Some high molecular weight compounds, attributed to vehicular emissions, were more abundant outdoors. The associated health risk was found to be low. 2-Methylanthraquinone and benzo(a)anthracene-7,12-dione were detected in the indoor samples, denoting the infiltration of vehicle exhaust. The observation of black carbon also corroborates the contribution of traffic emissions. For most of the elements, except for chromium, iron and manganese, the concentrations obtained in indoors were higher than outdoors, mainly due to soil resuspension. Chromium and manganese likely derived from emissions of the vehicle powered by mixtures of ethanol and gasoline. Water-soluble inorganic ions species denoted the influence of soil resuspension and human activities.

Indoor Air Quality: A Bibliometric Study

What are the actual trends in Indoor Air Quality (IAQ), and in which direction is academic interest moving? Much progress has been made in identifying and mitigating indoor pollutants, due to both prevention campaigns (e.g., smoking bans) and greater control of product emissions. However, IAQ is still of interest and the future trends are unknown. In this study, a thorough bibliometric analysis was conducted on the scientific literature available on the Web of Science database with CiteSpace from 1990 until today. It was possible to identify past trends and current advances, both with the aim of introducing the IAQ topic to those encountering it for the first time and to examine the issues that are expected to be pertinent in the future.

Key Factors Determining Indoor Air PM10 Concentrations in Naturally Ventilated Primary Schools in Belgrade, Serbia

Introduction

Indoor air quality (IAQ) is rated as a serious public health issue. Knowing children are accounted as more vulnerable to environmental health hazards, data are needed on air quality in schools.

Methods

A project was conducted from 2007 until 2009 (SEARCH, School Environment and Respiratory Health of Children), aiming to verify links between IAQ and children’s respiratory health. Study was conducted in ten primary schools on 735 children, in 44 classrooms. Children were randomly selected. Research tools and indicators used for children’s exposure to school environment were indoor and outdoor pollutants, two standardized questionnaires for school and classroom characteristics. In both classroom air and ambient air in front of them we measured, during a 5-day exposure period for continuous 24h measuring: carbon monoxide, carbon dioxide, indoor air temperature, relative humidity, and PM₁₀ during classes.

Results

PM₁₀ concentrations were significantly most frequent in an interval of ≥80.1μg/m³, that is, in the interval above 50μg/m³. Mean PM₁₀ value was 82.24±42.43 μg/m³, ranging from 32.00μg/m³ to of 197.00μg/m³.

Conclusion

The increase of outdoor PM₁₀ concentration significantly affects the increase of indoor PM₁₀. A statistically significant difference exists for average IAQ PM₁₀ concentrations vs. indicators of indoor thermal comfort zone (p<0.0001); they are lower in the classrooms with indicators within the comfort zone. Moreover, dominant factors for the increase of PM₁₀ are: high occupancy rate in the classroom (<2m² of space per child), high relative humidity (>75%), and indoor temperature beyond 23°C, as well as bad ventilation habits (keeping windows shut most of the time).

The impact of particle filtration on indoor air quality in a classroom near a highway

A pilot study was performed to investigate whether the application of a new mechanical ventilation system with a fine F8 (MERV14) filter could improve indoor air quality in a high school near the Amsterdam ring road. PM10, PM2.5, and black carbon (BC) concentrations were measured continuously inside an occupied intervention classroom and outside the school during three sampling periods in the winter of 2013/2014. Initially, 3 weeks of baseline measurements were performed, with the existing ventilation system and normal ventilation habits. Next, an intervention study was performed. A new ventilation system was installed in the classroom, and measurements were performed during 8 school weeks, in alternating 2-week periods with and without the filter in the ventilation system under otherwise identical ventilation conditions. Indoor/outdoor ratios measured during the weeks with filter were compared with those measured without filter to evaluate the ability of the F8 filter to improve indoor air quality. During teaching hours, the filter reduced BC exposure by, on average, 36%. For PM10 and PM2.5, a reduction of 34% and 30% was found, respectively. This implies that application of a fine filter can reduce the exposure of schoolchildren to traffic exhaust at hot spot locations by about one-third.

Effect of indoor air quality of day care centers in children with different predisposition for asthma

BACKGROUND

Scarce information is available about the relationships between indoor air quality (IAQ) at day care centers (DCC), the estimated predisposition for asthma, and the actual wheezing susceptibility.

METHODS

In the Phase II of ENVIRH study, 19 DCC were recruited after cluster analysis. Children were evaluated firstly using the ISAAC questionnaire and later by a follow-up questionnaire about recent wheezing. A positive asthma predictive index (API) was considered as predisposition for asthma. Every DCC was audited for IAQ and monitored for chemical and biologic contaminants.

RESULTS

We included 1191 children, with a median age of 43 (P25 -P75 : 25-58) months. Considering the overall sample, in the first questionnaire, associations were found between CO2 concentration (increments of 200 ppm) and diagnosis of asthma (OR: 1.10; 95% CI: 1.00-1.20). Each increment of 100 μg/m(3) of total volatile organic compounds (TVOC) and 1 μg of Der p1/g of dust were associated with wheezing in the previous 12 months (OR: 1.06; 95% CI: 1.01-1.11 and OR: 1.06; 95% CI: 0.99-1.12, respectively). In the follow-up questionnaire, TVOC were again associated with wheezing (OR: 1.05; 95% CI: 1.00-1.11). Children exposed to fungal concentration above the 75th percentile had also higher odds of wheezing at follow-up. TVOC were associated with wheezing in children with either negative or positive API.

CONCLUSIONS

IAQ in DCC seems to be associated with wheezing, in children with and without predisposition for asthma.

Modeling and estimating manganese concentrations in rural households in the mining district of Molango, Mexico

Airborne manganese (Mn) is considered the most hazardous route of exposure since Mn particles can enter into the body through the lung and may access the brain directly through olfactory uptake, thereby bypassing homeostatic excretory mechanisms. Environmental indoor and outdoor manganese concentrations in PM2.5 were monitored in ten rural households from two communities of Hidalgo, Mexico, from 2006 to 2007. Indoor and outdoor air samples of PM2.5 were collected using MiniVol samplers, and Mn concentrations in the filters were measured using proton-induced X-ray emission (PIXE). An adjusted generalized linear mixed model was applied and then used for estimating indoor concentrations in non-monitored households. Our monitoring results showed a higher daily average concentration of indoor PM2.5 vs. outdoor PM2.5 (46.4 vs. 36.2 μg/m(3), respectively); however, manganese concentration in PM2.5 indoor and outdoor was 0.09 μg/m(3) in both sceneries. Predictor variables of indoor Mn concentration were outdoor Mn concentration (64.5% increase per 0.1 μg/m(3) change in Mn) and keeping the windows open (4.2% increase). Using these predictors, the average estimated indoor Mn concentration in PM2.5 was 0.07 μg/m(3) (SD = 0.05). Our results confirm the direct effect of outdoor Mn levels, opening house windows, and the distance to the mining chimney in indoor Mn levels in houses.

Characterizing and predicting coarse and fine particulates in classrooms located close to an urban roadway

The PM10, PM2.5, and PM1 (particulate matter with aerodynamic diameters < 10, < 2.5, and < 1 microm, respectively) concentrations were monitored over a 90-day period in a naturally ventilated school building located at roadside in Chennai City. The 24-hr average PM10, PM2.5, and PM1 concentrations at indoor and outdoor environments were found to be 136 +/- 60, 36 +/- 15, and 20 +/- 12 and 76 +/- 42, 33 +/- 16, and 23 +/- 14 microg/m3, respectively. The size distribution of PM in the classroom indicated that coarse mode was dominant during working hours (08:00 a.m. to 04:00 p.m.), whereas fine mode was dominant during nonworking hours (04:00 p.m. to 08:00 a.m.). The increase in coarser particles coincided with occupant activities in the classrooms and finer particles were correlated with outdoor traffic. Analysis of indoor PM10, PM2.5, and PM1 concentrations monitored at another school, which is located at urban reserved forest area (background site) indicated 3-4 times lower PM10 concentration than the school located at roadside. Also, the indoor PM1 and PM2.5 concentrations were 1.3-1.5 times lower at background site. Further, a mass balance indoor air quality (IAQ) model was modified to predict the indoor PM concentration in the classroom. Results indicated good agreement between the predicted and measured indoor PM2.5 (R2 = 0.72-0.81) and PM1 (R2 = 0.81-0.87) concentrations. But, the measured and predicted PM10 concentrations showed poor correlation (R2 = 0.17-0.23), which may be because the IAQ model could not take into account the sudden increase in PM10 concentration (resuspension of large size particles) due to human activities. Implications: The present study discusses characteristics of the indoor coarse and fine PM concentrations of a naturally ventilated school building located close to an urban roadway and at a background site in Chennai City, India. The study results will be useful to engineers and policymakers to prepare strategies for improving the IAQ inside classrooms. Further, this study may help in the development of IAQ standards and guidelines in India.

Respirable antimony and other trace-elements inside and outside an elementary school in Flagstaff, AZ, USA

Because people spend almost 90% of their time indoors, ambient air monitors may severely underestimate actual exposure to atmospheric particulate matter (PM). Therefore, it becomes increasingly important to better understand the microenvironments where people are spending their time. For preadolescent children, the best estimates of exposure may be inside of their school. In this study, 11 size fractions of PM were collected inside and outside of an elementary school in Flagstaff, AZ, USA. In particles<1 μm (PM1), the total mass indoors was similar to the mass outdoors (indoor:outdoor, I:O, ratio=0.92 ± 0.16). In the PM1-10 fraction, however, the mass concentration inside the school was highly elevated relative to outside the school (I:O ratios=13 ± 3). Mass concentrations of 27 elements were analyzed by ICP-MS. For all metals except for antimony (Sb), the PM1 and PM1-10 I:O ratios are found to be similar to the overall PM mass (near 1 and 13, respectively). In addition, indoor and outdoor particle size distributions reveal a crustal character for every element except Cu, Zn, Pb, and Sb. Therefore, we hypothesize that most of the PM mass inside the school is a result of transport from outside the school followed by resuspension from floors and clothing. In the PM1 fraction, the indoor mass of Sb was 86 times greater than the outdoor mass and had an air concentration of 17 ngm(-3) - greater than many urban areas around the world. Cu:Sb ratios and size distribution functions suggest that the excess source of PM1 indoor Sb results from the suspension of embedded Sb (used as a flame retardant) in the carpeting. This is the first study to observe elevated submicron Sb in schools and further studies are required to determine if this is a widespread health risk.

Toxicity and elemental composition of particulate matter from outdoor and indoor air of elementary schools in Munich, Germany

Outdoor particulate matter (PM(10)) is associated with detrimental health effects. However, individual PM(10) exposure occurs mostly indoors. We therefore compared the toxic effects of classroom, outdoor, and residential PM(10). Indoor and outdoor PM(10) was collected from six schools in Munich during teaching hours and in six homes. Particles were analyzed by scanning electron microscopy and X-ray spectroscopy (EDX). Toxicity was evaluated in human primary keratinocytes, lung epithelial cells and after metabolic activation by several human cytochromes P450. We found that PM(10) concentrations during teaching hours were 5.6-times higher than outdoors (117 ± 48 μg/m(3) vs. 21 ± 15 μg/m(3), P < 0.001). Compared to outdoors, indoor PM contained more silicate (36% of particle number), organic (29%, probably originating from human skin), and Ca-carbonate particles (12%, probably originating from paper). Outdoor PM contained more Ca-sulfate particles (38%). Indoor PM at 6 μg/cm(2) (10 μg/ml) caused toxicity in keratinocytes and in cells expressing CYP2B6 and CYP3A4. Toxicity by CYP2B6 was abolished with the reactive oxygen species scavenger N-acetylcysteine. We concluded that outdoor PM(10) and indoor PM(10) from homes were devoid of toxicity. Indoor PM(10) was elevated, chemically different and toxicologically more active than outdoor PM(10). Whether the effects translate into a significant health risk needs to be determined. Until then, we suggest better ventilation as a sensible option.

PRACTICAL IMPLICATIONS

Indoor air PM(10) on an equal weight base is toxicologically more active than outdoor PM(10). In addition, indoor PM(10) concentrations are about six times higher than outdoor air. Thus, ventilation of classrooms with outdoor air will improve air quality and is likely to provide a health benefit. It is also easier than cleaning PM(10) from indoor air, which has proven to be tedious.

Composition of heavy metals and airborne fibers in the indoor environment of a building during renovation

The renovation of a building will certainly affect the quality of air in the vicinity of where associated activities were undertaken, this includes the quality of air inside the building. Indoor air pollutants such as particulate matter, heavy metals, and fine fibers are likely to be emitted during renovation work. This study was conducted to determine the concentration of heavy metals, asbestos and suspended particulates in the Biology Building, at the Universiti Kebangsaan, Malaysia (UKM). Renovation activities were carried out widely in the laboratories which were located in this building. A low-volume sampler was used to collect suspended particulate matter of a diameter size less than 10 μm (PM₁₀) and an air sampling pump, fitted with a cellulose ester membrane filter, were used for asbestos sampling. Dust was collected using a small brush and scope. The concentration of heavy metals was determined through the use of inductively coupled plasma-mass spectroscopy and the fibers were counted through a phase contrast microscope. The concentrations of PM₁₀ recorded in the building during renovation action (ranging from 166 to 542 μg m⁻³) were higher than the value set by the Department of Safety and Health for respirable dust (150 μg m⁻³). Additionally, they were higher than the value of PM₁₀ recorded in indoor environments from other studies. The composition of heavy metals in PM₁₀ and indoor dust were found to be dominated by Zn and results also showed that the concentration of heavy metals in indoor dust and PM₁₀ in this study was higher than levels recorded in other similar studies. The asbestos concentration was 0.0038 ± 0.0011 fibers/cc. This was lower than the value set by the Malaysian Department of Occupational, Safety and Health (DOSH) regulations of 0.1 fibers/cc, but higher than the background value usually recorded in indoor environments. This study strongly suggests that renovation issues need to be considered seriously by relevant stakeholders within the university in order to ensure that the associated risks toward humans and indoor environment are eliminated, or where this is not feasible, minimized as far as possible.

Variability of environmental exposure to fine particles, black smoke, and trace elements among a Swedish population

Mixed-effects models were used to estimate within-person and between-person variance components, and some determinants of environmental exposure to particulate matter (PM(2.5)), black smoke (BS) and trace elements (Cl, K, Ca, Ti, Fe, Ni, Cu, Zn, and Pb) for personal measurements from 30 adult subjects in Gothenburg, Sweden. The within-person variance component dominated the total variability for all investigated compounds except for PM(2.5) and Zn (in which the variance components were about equal). Expressed as fold ranges containing 95% of the underlying distributions, the within-person variance component ranged between 5-fold and 39-fold (median: sixfold), whereas the between-person variance component was always <sixfold (median: threefold). The relatively large within-person variance components can lead to attenuation bias in exposure-response relationships and point to the importance of obtaining repeated samples of PM exposure from study subjects in epidemiological investigations of urban air pollution. On the basis of the variance components estimated for the various particulate species, between 3 and 39 repeated measurements per subject would be required to limit attenuation bias to 20%. Significant determinants for personal exposure levels were urban background air concentrations (PM(2.5), BS, Cl, Zn, and Pb), cigarette smoking (PM(2.5), BS, K, and Ti), season (PM(2.5), Fe, and Pb), and the time spent outdoors or in traffic (Fe).

Characterization of coarse particulate matter in school gyms

We investigated the mass concentration, mineral composition and morphology of particles resuspended by children during scheduled physical education in urban, suburban and rural elementary school gyms in Prague (Czech Republic). Cascade impactors were deployed to sample the particulate matter. Two fractions of coarse particulate matter (PM(10-2.5) and PM(2.5-1.0)) were characterized by gravimetry, energy dispersive X-ray spectrometry and scanning electron microscopy. Two indicators of human activity, the number of exercising children and the number of physical education hours, were also recorded. Lower mass concentrations of coarse particulate matter were recorded outdoors (average PM(10-2.5) 4.1-7.4 μg m(-3) and PM(2.5-1.0) 2.0-3.3 μg m(-3)) than indoors (average PM(10-2.5) 13.6-26.7 μg m(-3) and PM(2.5-1.0) 3.7-7.4 μg m(-3)). The indoor concentrations of coarse aerosol were elevated during days with scheduled physical education with an average indoor-outdoor (I/O) ratio of 2.5-16.3 for the PM(10-2.5) and 1.4-4.8 for the PM(2.5-1.0) values. Under extreme conditions, the I/O ratios reached 180 (PM(10-2.5)) and 19.1 (PM(2.5-1.0)). The multiple regression analysis based on the number of students and outdoor coarse PM as independent variables showed that the main predictor of the indoor coarse PM concentrations is the number of students in the gym. The effect of outdoor coarse PM was weak and inconsistent. The regression models for the three schools explained 60-70% of the particular dataset variability. X-ray spectrometry revealed 6 main groups of minerals contributing to resuspended indoor dust. The most abundant particles were those of crustal origin composed of Si, Al, O and Ca. Scanning electron microscopy showed that, in addition to numerous inorganic particles, various types of fibers and particularly skin scales make up the main part of the resuspended dust in the gyms. In conclusion, school gyms were found to be indoor microenvironments with high concentrations of coarse particulate matter, which can contribute to increased short-term inhalation exposure of exercising children.

Characterizing and predicting ultrafine particle counts in Canadian classrooms during the winter months: model development and evaluation

School classrooms are potentially important micro-environments for childhood exposures owing to the large amount of time children spend in these locations. While a number of airborne contaminants may be present in schools, to date few studies have examined ultrafine particle (0.02-1 microm) (UFP) levels in classrooms. In this study, our objective was to characterize UFP counts (cm(-3)) in classrooms during the winter months and to develop a model to predict such exposures based on ambient weather conditions and outdoor UFPs, as well as classroom characteristics such as size, temperature, relative humidity, and carbon dioxide levels. In total, UFP count data were collected on 60 occasions in 37 occupied classrooms at one elementary school and one secondary school in Pembroke, Ontario. On average, outdoor UFP levels exceeded indoor measures by 8989 cm(-3) (95% confidence interval (CI): 6382, 11596), and classroom UFP counts were similar at both schools with a combined average of 5017 cm(-3) (95% CI: 4300, 5734). Of the variables examined only wind speed and outdoor UFPs were important determinants of classrooms UFP levels. Specifically, each 10 km/h increase in wind speed corresponded to an 1873 cm(-3) (95% CI: 825, 2920) decrease in classroom UFP counts, and each 10000 cm(-3) increase in outdoor UFPs corresponded to a 1550 cm(-3) (95% CI: 930, 2171) increase in classroom UFP levels. However, high correlations between these two predictors meant that the independent effects of wind speed and outdoor UFPs could not be separated in multivariable models, and only outdoor UFP counts were included in the final predictive model. To evaluate model performance, classroom UFP counts were collected for 8 days at two new schools and compared to predicted values based on outdoor UFP measures. A moderate correlation was observed between measured and predicted classroom UFP counts (r=0.63) for both schools combined, but this relationship was not valid on days in which a strong indoor UFP source (electric kitchen stove) was active in schools. In general, our findings suggest that reasonable estimates of classroom UFP counts may be obtained from outdoor UFP data but that the accuracy of such estimates are limited in the presence of indoor UFP sources.

Indoor and outdoor concentrations of PM2.5 trace elements at homes, preschools and schools in Stockholm, Sweden

Fine particles (PM2.5) were sampled indoors and outdoors at 40 sampling sites; in ten classrooms in five schools, at ten preschools and 20 non-smoking homes, in three communities in Stockholm, Sweden, during nine 2-week periods. Each sampling site was sampled twice, once during winter and once during spring. The samples were analysed for elemental concentrations using X-ray fluorescence (XRF) spectroscopy. In all locations significantly higher outdoor concentrations were found for elements that are related to long-range transported air masses (S, Ni, Br and Pb), while only Ti was higher indoors in all locations. Similar differences for S, Br and Pb were found in both seasons for homes and schools. In preschools different seasonal patterns were seen for the long-range transported elements S, Br and Pb and the crustal elements Ti, Mn and Fe. The indoor/outdoor ratios for S and Pb suggest an outdoor PM2.5 particle net infiltration of about 0.6 in these buildings. The community located 25 km from the city centre had significantly lower outdoor concentrations of elements of crustal or traffic origin compared with the two central communities, but had similar levels of long-range transported elements. Significant correlations were found between PM2.5 and most elements outdoors (rs = 0.45-0.90). Copper levels were found to correlate well (rs = 0.64-0.91) to the traffic marker NO2 during both winter and spring in all locations. Copper may be a suitable elemental marker for traffic-related aerosols in health studies in areas without other significant outdoor Cu sources.

The effect of outdoor air and indoor human activity on mass concentrations of PM(10), PM(2.5), and PM(1) in a classroom

The 12-h mass concentration of PM(10), PM(2.5), and PM(1) was measured in a lecturing room by means of three co-located Harvard impactors. The filters were changed at 8 AM and at 8 PM to cover the periods of presence and absence of students. Concentrations were assessed by gravimetry. Ambient PM(10) data were available for corresponding 12-h intervals from the nearest state air-quality-monitoring network station. The data were pooled into four periods according to the presence and absence of students-Monday-Thursday day (workday daytime), Monday-Thursday night (workday night), Friday-Sunday day (weekend daytime), and Friday-Sunday night (weekend night). Average indoor workday daytime concentrations were 42.3, 21.9 and 13.7 microgm(-3), workday night were 20.9, 19.1 and 15.2 microgm(-3), weekend daytime were 21.9, 18.1 and 11.4 microgm(-3), and weekend night were 24.5, 21.3, and 15.6 microgm(-3) for PM(10), PM(2.5), and PM(1), respectively. The highest 12-h mean, median, and maximum (42.3, 43.0, and 76.2 microgm(-3), respectively) indoor concentrations were recorded on workdays during the daytime for PM(10). The statistically significant (r=0.68,P<0.0009) correlation between the number of students per hour per day and the indoor coarse fraction calculated as PM(10--2.5) during daytime on workdays indicates that the presence of people is an important source of coarse particles indoor. On workdays, the daytime PM(10) indoor/outdoor ratio was positively associated (r=0.93) with an increasing indoor coarse fraction (PM(10--2.5)), also indicating that an important portion of indoor PM(10) had its source inside the classroom. With the exception of the calculated coarse fraction (PM(10--2.5)), all of the measured indoor particulate matter fractions were significantly highly correlated with outdoor PM(10) and negatively correlated with wind velocity, showing that outdoor levels of particles influence their indoor concentrations.

Using sulfur as a tracer of outdoor fine particulate matter

Six homes in the metropolitan Boston area were sampled between 6 and 12 consecutive days for indoor and outdoor particle volume and mass concentrations, particle elemental concentrations, and air exchange rates (AERs). Indoor/outdoor (I/O) ratios of nighttime (i.e., particle nonindoor source periods) sulfur, PM2.5 and the specific particle size intervals were used to provide estimates of the effective penetration efficiency. Mixed models and graphical displays were used to assess the ability of the I/O ratios for sulfur to estimate corresponding I/O ratios for PM2.5 and the various particle sizes. Results from this analysis showed that particulate sulfur compounds were primarily of outdoor origin and behaved in a manner that was representative of total PM2.5 in Boston, MA. These findings support the conclusion that sulfur can be used as a suitable tracer of outdoor PM2.5 for the homes sampled in this study. Sulfur was more representative of particles of similar size (0.06-0.5 microm), providing evidence that the size composition of total PM2.5 is an important characteristic affecting the robustness of sulfur-based estimation methods.

Can one use ambient air concentration data to estimate personal and population exposures to particles? An approach within the European EXPOLIS study

The objective of this paper is to devise a way to facilitate the use of fixed air monitors data in order to assess population exposure. A weighting scheme that uses the data from different monitoring sites and takes into account the time-activity patterns of the study population is proposed. PM2.5 personal monitoring data were obtained within the European EXPOLIS study, in Grenoble, France (40 adult non-smoking volunteers, winter 1997). Volunteers carried PM2.5 personal monitors during 48 h and filled in time-activity diaries. Workplaces and places of residence were classified into two categories using a Geographic Information System (GIS): some volunteers' life environments are seen as best represented by PM10 ambient air monitors located in urban background sites; others by monitors situated close to high traffic density sites (proximity sites). Measurements from the Grenoble fixed monitoring network using a TEOM PM10 sampler were available across the same period for these two types of sites (PM10block and PM10prox). These data were used to compute a translator parameter deltai that forces the measured PM2.5 personal exposures (PM2.5persoi) to equate the average PM10 urban ambient air concentrations ([PM10back + PM10prox]/2) measured the same days. Average deltai was 4.2 microg/m3 (CI95%[-3.4; 11.9]), with true average PM2.5 personal exposure being 36.2 microg/m3 (28.2; 44.1). PM10 ambient levels at the proximity site and at the background site were respectively PM10prox = 43.8 microg/m3 (37.1; 50.6) and PM10back = 37.0 microg/m3 (31.8; 42.3). In order to assess the consistency of this approach, six scenarios of 'proximity' and 'background' environments were accommodated, according to traffic intensity and road distance. Deltai was estimated for the entire EXPOLIS population and for subgroups, using terciles based on the percentage of time spent in proximity by each subject. Other similar studies need to be conducted in different urban settings, and with other pollutants, in order to assess the generalizability of this simple approach to estimate population exposures from air quality surveillance data.