Indoor Concentrations Of PM2 Research Articles

Development of a probabilistic multi-zone multi-source computational model and demonstration of its applications in predicting PM concentrations indoors

This paper highlights the development and application of the probabilistic model (IAPPEM), which predicts PM10 and PM2.5 concentrations in the indoor environments. A number of features are detailed and justified through simulated comparison, which are shown to be necessary when modelling indoor PM concentrations. A one minute resolution predicts up to 20% higher peak concentrations compared with a 15min resolution. A modified PM10 deposition method, devised to independently analyse the PM2.5 fraction of PM10, predicts up to 56% higher mean concentrations. The application of the model is demonstrated by a number of simulations. The total PM contribution, from different indoor emission sources, was analysed in terms of both emission strength and duration. In addition, PM concentrations were examined by varying the location of the emission source. A 24-hour sample profile is simulated based on sample data, designed to demonstrate the combined functionality of the model, predicting PM10 and PM2.5 peak concentrations up to 1107±175 and 596±102μgm−3 respectively, whilst predicting PM10 and PM2.5 mean concentrations up to 259±21 and 166±11μgm−3 respectively.

Multivariate methods for indoor PM10 and PM2.5 modelling in naturally ventilated schools buildings

In this study the concentrations of PM10, PM2.5, CO and CO2 concentrations and meteorological variables (wind speed, air temperature, and relative humidity) were employed to predict the annual and seasonal indoor concentration of PM10 and PM2.5 using multivariate statistical methods. The data have been collected in twelve naturally ventilated schools in Gaza Strip (Palestine) from October 2011 to May 2012 (academic year). The bivariate correlation analysis showed that the indoor PM10 and PM2.5 were highly positive correlated with outdoor concentration of PM10 and PM2.5. Further, Multiple linear regression (MLR) was used for modelling and R2 values for indoor PM10 were determined as 0.62 and 0.84 for PM10 and PM2.5 respectively. The Performance indicators of MLR models indicated that the prediction for PM10 and PM2.5 annual models were better than seasonal models. In order to reduce the number of input variables, principal component analysis (PCA) and principal component regression (PCR) were applied by using annual data. The predicted R2 were 0.40 and 0.73 for PM10 and PM2.5, respectively. PM10 models (MLR and PCR) show the tendency to underestimate indoor PM10 concentrations as it does not take into account the occupant’s activities which highly affect the indoor concentrations during the class hours.

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 μm, 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 μg/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.

Spatial and temporal variations of particulate matter concentrations in multifamily apartment buildings

We report a comprehensive assessment of PM concentrations and its variations in multifamily apartment buildings. Fifty apartments in ten multifamily buildings were investigated during heating seasons of 2011 and 2012 in Kaunas city, Lithuania. PM concentration and size distribution measurements were performed using the optical particle counters indoors and outdoors. Usually mean 24-h indoor PM concentrations were lower (median 7.8 μg/m3 for PM2.5) than outdoor concentrations (median 16.9 μg/m3 for PM2.5) of corresponding location, and I/O ratios of PM2.5 were lower (0.70) than that of PM10 (0.98). Night time levels, representing background indoor exposure to PM, were equal to 5.0 (PM2.5) and 6.7 μg/m3 (PM10), respectively. Particle deposition rates were determined by regression fitting of the measured PM2.5 concentration decay curves, with the median equal to 0.32 h−1. The data have been discussed aiming to characterize indoor PM sources and select the most representative indicator(s) for an assessment of the effects of energy saving refurbishment on indoor air quality. We found that a combination of several indicators allowed an adequate characterization of indoor PM sources and can be used in the subsequent assessment.

Building removal of particulate pollutant plume during outdoor resuspension event

The capacity of buildings to reduce the outdoor pollutant level during particle transport has not been thoroughly investigated. This study demonstrates that CFD modeling combined with multizone modeling can provide a complete picture on the fate and transport of PM pollutant plume passing a building. A plume intersecting a 6 m × 6 m × 6.3 m building with concentrations of 56, 93, 93, and 74 μg/m3 for 0.85 μm, 2.63 μm, 3.94 μm, and 8.77 μm particles, respectively, is simulated. The building removal rates are 79 ± 4 mg/h, 182 ± 10 mg/h, 209 ± 12 mg/h, 280 ± 26 mg/h, which are 0.1%, 0.13%, 0.15%, and 0.25% of the plume source emission rates, respectively. The building removal is mainly contributed by the deposition to the building envelope and deposition in the building cracks. The building removal rate varies with particle size, and is more affected by wind direction than the air intake location for the building air handling system. The resulting indoor PM concentration, estimated via multizone modeling, varies with particle size and zone, and is affected by the alignment of building crack openings and wind direction. The demonstrated simulation method can be used to investigate the reduction of a pollutant plume by high-density building clusters in the urban environment as well as the human exposure to the plume indoors. As compared to well-mixed models, the CFD generated spatially-resolved pollutant concentration around the building improves the accuracy of the prediction of indoor exposure to outdoor PM plumes.

Indoor Air Quality in the United Arab Emirates

Air quality was measured inside 628 United Arab Emirates (UAE) personal residences. Weekly average concentrations of carbon monoxide (CO), formaldehyde (HCHO), hydrogen sulfide (H2S), nitrogen dioxide (NO2), sulfur dioxide (SO2), and three size fractions of particulate matter (PM2.5, PMc, and PM10) were determined in each home. In a subset of the homes, measurements of outdoor air quality, ultrafine PM concentrations, and elemental PM concentrations were also made. Questionnaires were administered to obtain information on housing demographics and lifestyle habits. Air measurements were performed using simple and cost effective passive samplers. The 90th percentiles of indoor CO, HCHO, H2S, NO2, and SO2 were 1.55 ppm, 0.05 ppm, 0.12 ppm, 0.01 ppm, and 0.05 ppm, respectively. Median indoor PM2.5, PMc, and PM10, concentrations were 5.73 μg/m3, 29.4 μg/m3, and 35.2 μg/m3, respectively. The median indoor concentration of ultrafine PM was 3.62 × 1010 particles/m3. Indoor/outdoor ratios for PM were 0.44, 0.41, and 0.38 for ultrafine PM, PM2.5, and PM10, respectively. These values fall within the range of other indoor air studies findings conducted in developing countries. Air conditioning, smoking, and attached kitchens were significantly correlated with indoor levels of carbon monoxide. In addition, indoor concentrations of PM2.5 and PM10 were significantly correlated with vehicles parked within five meters of the home, central air conditioning, and having attached kitchens. This is the first robust indoor air quality data set developed for the UAE. This study demonstrates that screening level tools are a good initial step for assessing air quality when logistical issues (distance, language, cultural, training) and intrusion into personal lives need to be minimized.

Indoor and outdoor suspended particulate matter and associated carbonaceous species at residential homes in northwestern Portugal

Particulate matter with an aerodynamic diameter equal to or less than 10μm (PM10), organic carbon (OC) and elemental carbon (EC) concentrations were measured simultaneously in the indoor and outdoor air of 4 residences located in urban and sub-urban areas in northwestern Portugal. The residences were studied with occupants. One residence was also studied without any indoor activity, taking advantage of the fact that the occupants had moved into a new home. First, 48-h aerosol samples were collected on quartz fiber filters with low-volume samplers equipped with size selective inlets. The filters were weighed and then analyzed for OC and EC using a thermal–optical transmittance method. The average indoor and outdoor PM10 concentrations in the occupied residences were 71.9±38.3μg/m3 and 54.0±13.3μg/m3, respectively. Despite the higher concentration of PM10 indoors, outdoor sources were found to be a significant contributor to indoor concentrations. An estimate based on data from the residence studied under different occupancy conditions indicated that outdoor sources can account for 68% of the indoor PM10 mass concentration. Average indoor to outdoor (I/O) ratios for OC ranged from 1.7 to 5.6 in occupied residences, showing that indoor sources, such as cooking, smoking, biomass burning and movement of people, strongly influenced indoor OC concentrations. In contrast, I/O ratios for EC were close to 1, except for a smokers' residence, suggesting that indoor concentrations were mainly controlled by outdoor sources, most likely from vehicular emissions and biomass burning.

Indoor concentrations and emissions factors of particulate matter, ammonia and greenhouse gases for pig fattening facilities

The objective of the study was to investigate indoor concentrations (IC) of particulate matter (PM1, PM2.5 and PM10), NH3, N2O, CH4 and CO2 in different conventional pig fattening facilities and one low-emission fattening facility. Concentration data were used to calculate respective emission factors (EF), which were assessed and evaluated with regard to similar studies. In total, six pig fattening stables were sampled during two fattening periods. The average indoor PM concentrations were 15.0, 38.9 and 719 μg m−3 for PM1, PM2.5 and PM10 respectively for conventional pig fattening stables, while for the low emission stable, these were 14.2, 41.2 and 595 μg m−3 respectively. The average indoor gas concentrations for the conventional stables were 18.7, 817, 128 and 2034 ppm for NH3, N2O, CH4, and CO2 respectively and for the low emission stable 16.3, 0.731, 164 and 2156 ppm. The emission factors of the conventional fattening facilities were 3.4, 7.8 and 99.9 g a−1 yr−1 for PM1, PM2.5 and PM10 respectively, while the EF was 2.2 kg a−1 yr−1 for NH3, 154 g a−1 yr−1 for N2O, 10.4 kg a−1 yr−1 for CH4, and 420 kg a−1 yr−1 for CO2. For the low emission stable the EF were 2.3, 7.3 and 85.3 g a−1 yr−1 for PM1, PM2.5 and PM10 respectively, while the EF was 1.6 kg a−1 yr−1 for NH3, 136 g a−1 yr−1 for N2O, 19.5 kg a−1 yr−1 for CH4, and 545 kg a−1 yr−1 for CO2. Furthermore, the particle size distribution and the correlations between EF, IC and different operational conditions were investigated.

Indoor–outdoor concentrations of particulate matter in nine microenvironments of a mix-use commercial building in megacity Delhi

Three naturally and six mechanically ventilated microenvironments (MEs) of a mix-use commercial building in Delhi are used to study indoor–outdoor (I/O) relationships of particulate matter ≤10 μm (PM10), ≤2.5 μm (PM2.5), and ≤1 μm (PM1). Effect of environmental and occupancy parameters on the concentrations of PM during working and non-working hours (i.e., activity and non-activity periods, respectively) are also investigated. Average outdoor concentration of PM10 and PM2.5 were found to exceed the 24-h averaged national standard values, showing a polluted environment surrounding the studied building. During working hours, indoor PM10 concentration was found 6–10 times, both PM2.5 and PM1 were 1.5–2 times, higher than the non-working hours in the selected MEs. The variations of indoor concentrations were highest (17.1–601.2 μg/m3) for PM10 compared with PM2.5 (16.9–102.6 μg/m3) and PM1.0 (10.6–63.6 μg/m3). The I/O for PM10, PM2.5, and PM1.0 varied from 0.37–3.1, 0.2–3.2, and 0.17–2.9, respectively. The results suggest highest I/O for PM10, PM2.5, and PM1 as 3.1, 2.15, and 1.76, respectively, in all the three natural-ventilated MEs (canteen, kitchen, reception). Irrespective of PM types, the average I/O was 1 for naturally ventilated MEs. As opposed to PM1, better correlation (r > 0.6) was noted between indoor PM10, PM2.5, and CO2 concentrations in most of the airtight MEs.

Airborne Allergens, Endotoxins, and Particulate Matter in Elementary Schools, Results from Germany (LUPE 2)

Allergic disorders are the most common childhood-related chronic diseases in developed countries. It is essential to assess the exposure, especially in schools, where children spend a large portion of their time. We aimed to investigate allergen and endotoxin levels in the air of schools and to observe seasonal variations of these factors. We evaluated airborne concentrations of house dust mites allergens (Der p 1, Der f 1), cat allergen (Fel d 1), and endotoxin in PM10 in 14 classrooms during the school days in the region of Munich, each over 20 consecutive days and in 1 classroom over the course of a year (at 83 days); we also tested outdoor air close to the schools. Endotoxin levels were quantified using two different analytical methods. In addition, indoor air climate parameters were measured. The median daily indoor CO2 and PM10 concentrations in the classrooms ranged from 423 to 3,135 ppm (median: 1,211 ppm) and 9 to 390 μg/m3 (median: 127 μg/m3), respectively. Fel d 1 in the PM10 samples was the most frequently detected allergen, with levels from 0.02 to 1.15 ng/m3 in a total of 301 samples (median: 0.19 ng/m3, 95th percentile: 0.57 ng/m3). Der p 1 and Der f 1 were detected in only 51% and 19% of the samples, with 95th percentiles at 0.5 and 0.3 ng/m3. Endotoxin levels in the PM10 and inhalable dust samples ranged from 0.5 to 84.1 EU/m3 (median: 15.3 EU/m3; 95th percentile: 58.2 EU/m3) and from 0.03 to 115 EU/m3 (median: 8.4 EU/m3; 95th percentile: 27.9 EU/m3). Fel d 1 and endotoxin were found in higher levels in the winter months. The results of the two different indoor sampling techniques for endotoxin were statistically significantly correlated. The results of airborne allergens indicate a generally low exposure level in classrooms. With regard to endotoxin, our study showed higher levels in schools compared with residences.

Exposure assessment on the relationship between daily activity patterns and indoor air quality in university buildings

This study analyzed the impact of the spatial-temporal distribution of occupants on indoor air quality. To observe daily building usage by students, Dongnam Health University with about 5,000 students and staffs was selected as the survey site, and the survey was conducted on 500 students (10%) as a sample to represent the activities all students. The students’ activities were surveyed and classified into seven categories (work, study, exercise, circle, recreation, others, and trip) to know how long they stayed in the space between 6 a.m. to 24 p.m. Based on the survey results, an hourly activity behavior profile of students in each building was obtained in the statistical model. While the survey was conducted, PM10 concentration and CO2 concentration were measured using a dust spectrometer (Grimm Inc., model 1.108) and IAQ monitor (Senscube Inc.), respectively, inside eight buildings on the campus. The indoor PM10 concentration was found to be more affected by outdoor concentration rather than the number of occupants while indoor CO2 concentration was found to be affected more by the number of occupants. This study was the first attempt to apply the spatial-temporal distribution of occupants for managing indoor air quality using a statistical model and is intended to propose a new method for managing indoor air quality.

PM LEVELS IN SELECTED URBAN MICROENVIRONMENTS NEAR THE COPER SMELTER COMPLEX, BOR, SERBIA

Background: Numerous epidemiological studies have associated exposure to PM in the outdoor environment to adverse health effects. Nowadays, the attention is paid to indoor air pollution, since people spend most of time in the indoor for which there is gap of PM data. Aims: The Municipality of Bor has been the major centre for mining and processing of copper and other precious metals, assumed as hot spot with the main source of air pollution of SO2 and toxic metals and metalloids in PM. However, annual values of outdoor PM in Bor town have been reported for several years as one of the lowest in Serbia. Our study is aimed to determine the level PM in selected indoor microenvironments as hospital, kindergarten, etc. Methods: In the real-time PM10 and PM2.5 were monitored in the outdoor air with the GRIMM EDM180 while in the indoor with Turnkey OSIRIS Model 2315. For calculation calibration factors at each location during the first week of campaign a 24-h samples were collected concurrently with reference gravimetric samplers for both PM fractions. Campaigns for microenvironments were conducted in duration of 240 days covering heating and non-heating period during work-shifts days in period of 2009-2012. Results:Mean PM10 levels at Hospital and Kindergarten surpassing the EU yearly air quality standard of 40 µg/m3. The number of days that exceed the daily limit value for ambient PM10 level was calculated equal to 52% and 63% respectively. Furthermore, the measured indoor PM10 concentrations were higher than the outdoor ones at both sites. At the both microenvironment during heating period, mean daily concentrations of PM2.5 were greater than 25 µg/m3. Conclusions: Correlation coefficient between 0.33 and 0.62 show influence of outdoor to indoor PM. Mean I/O ratios were found to vary depending on the indoor activities and the outdoor concentration levels. Further research should be carried out in order to fully confirm these findings and identify sources of indoor PM.

Associations of particulate air pollution and daily mortality in 16 Chinese cities: An improved effect estimate after accounting for the indoor exposure to particles of outdoor origin

People typically spend most of their time indoors. We modeled the daily indoor PM10 concentrations of outdoor origin using a set of exposure parameters, including the fraction of residences with air conditionings (AC), the fraction of time that windows are closed when cooling occurs for buildings with AC, the fractions of time that windows are open or closed for buildings with or without AC, the particle penetration factors, air change rates, and surface removal rate constant of PM10. We calculated the time-weighted average of the simulated indoor PM10 concentration of outdoor origin and the original recorded outdoor PM10 concentration. We then evaluated the acute effects of PM10 using traditional and amended exposure metrics in 16 Chinese cities. Compared with the original estimates, the new effect estimates almost doubled, with improved model fit and attenuated between-city heterogeneity. Conclusively, this proposed exposure assessment approach could improve the effect estimates of ambient particles.

Characteristics of Indoor Aerosols in College Laboratories

This study was conducted in National Pingtung University of Science and Technology (NPUST), in Taiwan. The main objective was to provide quantitative information on concentrations of the indoor and outdoor PMs, as well as watersoluble ions, at seven selected locations and the spatial variations in four different types of typical laboratories. They include Type I: General Chemistry Laboratories (GCL); Type II: WCLTP during a semester and a summer vacation in college; Type III: Environmental Research Laboratories; and Type IV: Soil Research Laboratories and Field in NPUST. In addition, this paper also investigates the characteristics of indoor aerosols in college laboratories. Indoor and outdoor particulate matters with aerodynamic diameters of less than 2.5 μm (PM2.5) and 10 μm (PM10) were sampled from June to September in 2002. The acid and base gases in outdoor samples and the amount of eight particle-bound water-soluble ions (NO3 – , SO4 2– , Cl – , NH4 + , Na + , K + , Ca 2+ , and Mg 2+ ) were also determined. The results for laboratories Types I and II revealed that the mean PM2.5 concentrations indoors in GCL (during a semester) and WCLTP (during a summer vacation) exceeded the air quality guidelines of the World Health Organization (WHO) of 20 μg/m 3 for PM2.5. The results also showed that the indoor concentrations of PM2.5 and PM10 in GCL increased by 4.9 and 1.7 times, respectively, during a semester as compared to the indoor measured data during a summer vacation. Students’ laboratory activities in colleges thus deserve more attention, because these cause significant increases in the PM emissions.

Environmental and occupational respiratory diseases – 1057. Correlation between air pollution and respiratory health of school children in Delhi

Background Urban air pollution (indoor and outdoor) poses a major health hazard for city dwellers. Exposure to ambient air pollution may result in respiratory health disorders. The aim of this study was to correlate air pollutant levels to the respiratory health of school children in Delhi. Methods The questionnaire was designed based on the internationally valid questionnaires for respiratory illness. The respiratory health survey was approved by the Directorate of Education – Delhi and schools were selected based on land usage pattern i.e. commercial (Chandni Chowk), industrial (Mayapuri) and residential (Sarojini Nagar) areas. Approximately 1800 students (600 / zone) of age 10 – 14 years participated in the survey which included spirometry tests also. Indoor and outdoor levels of SO2 ,N O2 and PM were also measured in the school premises. Results The questionnaire data showed that the students having respiratory disorder symptoms was maximum in Chandni Chowk (66%) followed by Mayapuri (59%) and Sarojini Nagar (46%). Spirometry test results demonstrated that a significant population of subjects in Chandni Chowk (19%) had mild to severe pulmonary obstruction. However the percentage of subjects with such conditions was comparatively less in Maypuri (17%) and Sarojini Nagar (14%) area. Indoor and outdoor PM10 concentration at schools located in Chandni Chowk, a commercial zone, was observed to be 815±354.45 µg/m 3 & 337±85 µg/m 3 respectively, which is ten times above the permissible limits. The PM10 concentration was lower in Mayapuri (694.6±322.9 µg/m 3 & 274±78 µg/m 3 ), an industrial zone, and was least in Sarojini Nagar (534.3±94.22µg/m 3 & 197±48 µg/m 3 ) which is a residential zone. However, levels of SO2 and NO2were under the permissible limits in all three areas. Conclusions

Impact of biomass burning sources on seasonal aerosol air quality

In the Huon Valley, Tasmania, current public perception is that smoke from regeneration burning is the principal cause of pollution events in autumn. These events lead to exceedences of national air quality standards and to significant health impacts on the rural population. To date there is little data on the significance of the impact.The aim of the study was to quantitatively assess the seasonal atmospheric particle loadings in the Huon Valley and determine the impact of smoke pollution. The study monitored fine (PM2.5) and coarse (PM10) particle concentrations and their chemical composition at two locations in the Huon Valley, Geeveston, an urban site and Grove, a rural site, between March 2009 and November 2010.The monitoring program clearly showed that biomass burning was a significant source of PM2.5 in the Huon Valley, leading to exceedences of the 24 h PM2.5 Ambient Air Quality National Environment Protection Measures advisory standard on a number of occasions. Significant increases of PM2.5 concentrations above background occurred during periods of prescribed burning as well as during the winter season. Although the intensity of emissions from prescribed burns (PB) and residential woodheaters (WH) was similar, emissions from WH were the largest source of PM2.5, with a contribution of 77% to the ambient PM2.5 load compared to an 11% contribution from PB. The results have also shown a greater impact on air quality at the urban site than at the rural site, indicating that PM2.5 concentrations are primarily influenced by localised sources rather than by regional pollution.The potential impact on local residents of the high PM concentrations during the PB and WH season was assessed. WH pollution is largely a persistent night-time issue in contrast to PB events which generally occur during the day and are of short duration. Due to the long persistence of high PM concentrations in winter, indoor PM concentrations are unlikely to be substantially lower than outdoor ones. However plume strikes are usually of shorter duration and therefore it may be possible to avoid exposure to PB events by remaining indoors.

Evaluation of the vehicle contributions of metals to indoor environments

A large number of diesel vehicles carrying gravel and sand shuttle back and forth every day on the major thoroughfares (Tai-16 and Tai-21) from Shinyi to Jiji in Nantou, Taiwan. A total of 10 stations along the major thoroughfares were selected as the exposure sites, whereas a small village located ∼9 km from a main traffic route was selected as the control site. Outdoor and indoor aerosol samples were collected using high-volume samplers and Harvard samplers, respectively. The metal concentrations of outdoor and indoor PM(10) at the exposure sites were, respectively, higher than those at the control site. The plots between metal contents in the aerosols and road dust showed that diesel vehicles contributed significant amounts of metals to the outdoor and indoor aerosols at the exposure sites. Household dust samples along the roadside within 30 m of the main road in the small towns were collected using the wipe method. Based on the results of principal component analysis (PCA), three major components for household dust were identified: resuspended from road dust, brake wear and diesel emissions. Enrichment factors were applied to assess the contribution of pollution sources to household dust. These factors were calculated with respect to unpolluted river dust samples (EF(river)) and road dust (EF(road)). The differences between EF(river) and EF(road) could be mainly attributed to the effects of resuspension by passing vehicles. Approximately 72%, 68%, 68%, 73% and 86% of the vehicle-related metals Pb, Zn, Cu, Ni and Mo content, respectively, in household dust were the result of the resuspension of road dust by passing vehicles. The data of daily intakes of five metals (i.e., Fe, Pb, Cu, Ni and Mo) from inhalation and ingestion pathways showed that the doses from the ingestion pathway were much higher than those from the inhalation pathway.

Elemental Characterization Of Indoor Breathable Particles at a Portuguese Urban Hospital

Hospitals are a specific indoor environment with highly susceptible individuals for whom indoor air pollution represents additional health risks. Particulate matter (PM) is one of the most health-relevant indoor pollutants due to its association with respiratory and cardiovascular diseases. Particles can also act as a carrier for various harmful organisms present in the air of hospitals, thus leading to airborne transmission of infectious diseases. Thus, the objective of this study was to characterize indoor PM collected in a hospital in consideration of concentration, size distribution, and elemental composition. Emission sources of indoor PM were indentified and risks associated with indoor PM estimated. Sampling was performed at radiology ward of a Portuguese urban hospital where PM10, PM2.5, and PM1 were collected during a period of 4 wk; PM elemental composition was determined by proton-induced x-ray emission (PIXE) analysis. Data showed that indoor PM10 concentrations ranged from 13 to 58.8 μg/m3 and from 10.5 to 41.9 μg/m3 for PM2.5. Fine particles constituted 77% of PM10, indicating that PM2.5 made a significant contribution to indoor air quality at the hospital. PM1 ranged from 9.9 to 35.6 μg/m3, accounting for 93% of PM2.5. PIXE identified 21 elements in PM, including health-hazardous metals (manganese, iron, copper, and vanadium) and carcinogenic elements (nickel, chromium, arsenic, and lead). However, no significant indoor source of PM emissions was identified, while outdoor air was the major contributor of indoor particles. Further, no significant risks existed through PM10 inhalation for population at the respective hospital.

Comparative assessment of a real-time particle monitor against the reference gravimetric method for PM10 and PM2.5 in indoor air

Accurate monitoring of indoor mass concentrations of particulate matter is very important for health risk assessment as people in developed countries spend approximately 90% of their time indoors. The direct reading, aerosol monitoring device, Turnkey, OSIRIS Particle Monitor (Model 2315) and the European reference low volume sampler, LVS3 (Sven/Leckel LVS3) with size-selective inlets for PM10 and PM2.5 fractions were used to assess the comparability of available optical and gravimetric methods for particulate matter characterization in indoor air. Simultaneous 24-hour samples were collected in an indoor environment for 60 sampling periods in the town of Bor, Serbia. The 24-hour mean PM10 levels from the OSIRIS monitor were well correlated with the LVS3 levels (R2=0.87) and did not show statistically significant bias. The 24-hour mean PM2.5 levels from the OSIRIS monitor were moderately correlated with the LVS3 levels (R2=0.71), but show statistically significant bias. The results suggest that the OSIRIS monitor provides sufficiently accurate measurements for PM10. The OSIRIS monitor underestimated the indoor PM10 concentrations by approximately 12%, relative to the reference LVS3 sampler. The accuracy of PM10 measurements could be further improved through empirical adjustment. For the fine fraction of particulate matter, PM2.5, it was found that the OSIRIS monitor underestimated indoor concentrations by approximately 63%, relative to the reference LVS3 sampler. This could lead to exposure misclassification in health effects studies relying on PM2.5 measurements collected with this instrument in indoor environments.

Indoor air quality investigations in a naturally ventilated school building located close to an urban roadway in Chennai, India

In this study, indoor air quality parameters were investigated in a naturally ventilated school building located near an urban roadway in Chennai. Monitoring was done during the winter (34 days) and summer (26 days) of 2011. The mean value of indoor PM10, PM2.5, PM1 and CO concentrations were found to be 149 ± 69, 61 ± 29, 43 ± 24, 0.10 ± 0.18 and 95 ± 61, 32 ± 16, 18 ± 9 μg/m3, 0.11 ± 0.14 ppm, respectively for winter and summer seasons. PM data analysis indicated that the indoor PM10 (60% of time) and PM2.5 (27% of time) levels were often exceeding the National Ambient Air Quality Standards (NAAQS). The indoor –outdoor (I/O) ratios of PM10, PM2.5 and PM1 and CO were found to be 2.52 ± 2.71, 1.44 ± 0.67, 0.97 ± 0.18 and 0.51 ± 0.38, respectively. The high I/O value of PM10 concentration indicates significant contribution from the activities of occupants inside classroom. The low I/O values for finer PM fractions and CO concentrations confirm the vehicular emission contribution from the adjacent road. The influence of classroom occupancy, comfort parameters, outdoor traffic and meteorological parameters on indoor pollutant concentrations were also investigated. Results showed good correlation between PM with comfort and outdoor meteorological parameters.