Indoor particle size distributions in homes with open fires and improved Patsari cook stoves

Particulate pollution has been clearly linked with adverse health impacts from open fire cookstoves, and indoor air concentrations are frequently used as a proxy for exposures in health studies. Implicit are the assumptions that the size distributions for the open fire and improved stove are not significantly different, and that the relationship between indoor concentrations and personal exposures is the same between stoves. To evaluate the impact of these assumptions size distributions of particulate matter in indoor air were measured with the Sioutas cascade impactor in homes using open fires and improved Patsari stoves in a rural Purepecha community in Michoacan, Mexico. On average indoor concentrations of particles less than 0.25 μm were 72% reduced in homes with improved Patsari stoves, reflecting a reduced contribution of this size fraction to PM_2.5 mass concentrations from 68% to 48%. As a result the mass median diameter of indoor PM_2.5 particulate matter was increased by 29% with the Patsari improved stove compared to the open fire (from 0.42 μm to 0.59 μm, respectively). Personal PM_2.5 exposure concentrations for women in homes using open fires were approximately 61% of indoor concentration levels (156 μg m^?3 and 257 μg m^?3 respectively). In contrast personal exposure concentrations were 77% times indoor air concentration levels for women in homes using improved Patsari stoves (78 μg m^?3and 101 μg m^?3 respectively). Thus, if indoor air concentrations are used in health and epidemiologic studies significant bias may result if the shift in size distribution and the change in relationship between indoor air concentrations and personal exposure concentrations are not accounted for between different stove types.     

Experimental evidence for a significant contribution of cellulose to indoor aerosol mass concentration

An apartment bedroom located in a residential area of Aveiro (Portugal) was selected with the aim of characterizing the cellulose content of indoor aerosol particles. Two sets of samples were taken: (1) PM₁₀ collected simultaneously in indoor and outdoor air; (2) PM₁₀ and PM_2.5 collected simultaneously in indoor air. The aerosol particles were concentrated on quartz fibre filters with low-volume samplers equipped with size selective inlets. The filters were weighed and then extracted for cellulose analysis by an enzymatic method. The average indoor cellulose concentration was 1.01 ± 0.24 μg m^?3, whereas the average outdoor cellulose concentration was 0.078 ± 0.047 μg m^?3, accounting for 4.0% and 0.4%, respectively, of the PM₁₀ mass. The corresponding average ratio between indoor and outdoor cellulose concentrations was 11.1 ± 4.9, indicating that cellulose particles were generated indoors, most likely due to the handling of cotton-made textiles as a result of routine daily activities in the bedroom. Indoor cellulose concentrations averaged 1.22 ± 0.53 μg m^?3 in the aerosol coarse fraction (determined from the difference between PM₁₀ and PM_2.5 concentrations) and averaged 0.38 ± 0.13 μg m^?3 in the aerosol fine fraction. The average ratio between the coarse and fine fractions of cellulose concentrations in the indoor air was 3.6 ± 2.1. This ratio is in line with the primary origin of this biopolymer. Results from this study provide the first experimental evidence in support of a significant contribution of cellulose to the mass of suspended particles in indoor air.     

Experimental and statistical analyses to characterize in-vehicle fine particulate matter behavior inside public transit buses operating on B20-grade biodiesel fuel

This paper presents results from an in-vehicle air quality study of public transit buses in Toledo, Ohio, involving continuous monitoring, and experimental and statistical analyses to understand in-vehicle particulate matter (PM) behavior inside buses operating on B20-grade biodiesel fuel. The study also focused on evaluating the effects of vehicle’s fuel type, operating periods, operation status, passenger counts, traffic conditions, and the seasonal and meteorological variation on particulates with aerodynamic diameter less than 1 micron (PM_1.0). The study found that the average PM_1.0 mass concentrations in B20-grade biodiesel-fueled bus compartments were approximately 15 μg m^?3, while PM_2.5 and PM₁₀ concentration averages were approximately 19 μg m^?3 and 37 μg m^?3, respectively. It was also observed that average hourly concentration trends of PM_1.0 and PM_2.5 followed a “μ-shaped” pattern during transit hours.Experimental analyses revealed that the in-vehicle PM_1.0 mass concentrations were higher inside diesel-fueled buses (10.0–71.0 μg m^?3 with a mean of 31.8 μg m^?3) as compared to biodiesel buses (3.3–33.5 μg m^?3 with a mean of 15.3 μg m^?3) when the windows were kept open. Vehicle idling conditions and open door status were found to facilitate smaller particle concentrations inside the cabin, while closed door facilitated larger particle concentrations suggesting that smaller particles were originating outside the vehicle and larger particles were formed within the cabin, potentially from passenger activity. The study also found that PM_1.0 mass concentrations at the back of bus compartment (5.7–39.1 μg m^?3 with a mean of 28.3 μg m^?3) were higher than the concentrations in the front (5.7–25.9 μg m^?3 with a mean of 21.9 μg m^?3), and the mass concentrations inside the bus compartment were generally 30–70% lower than the just-outside concentrations. Further, bus route, window position, and time of day were found to affect the in-vehicle PM concentrations significantly. Overall, the in-vehicle PM_1.0 concentrations inside the buses operating on B20-grade biodiesel ranged from 0.7 μg m^?3 to 243 μg m^?3, with a median of 11.6 μg m^?3.Statistical models developed to study the effects of vehicle operation and ambient conditions on in-vehicle PM concentrations suggested that while open door status was the most important influencing variable for finer particles and higher passenger activity resulted in higher coarse particles concentrations inside the vehicle compartments, ambient PM concentrations contributed to all PM fractions inside the bus irrespective of particle size.     

A four-year size-segregated characterization study of particles PM10, PM2.5 and PM1 depending on air mass origin at Melpitz

PM₁₀ measurements were started in November 1992 at Melpitz site. The mean PM₁₀ concentration in 1993 was 38 μg m^?3 in the summer season (May until October) and about 44 μg m^?3 in the winter season (November until April). The mean PM₁₀ level decreased until 1999 and varies now in ranges from 20–34 μg m^?3 to 17–24 μg m^?3 (minimum and maximum mean values for 1999–2008) in winter and summer seasons, respectively. High volume filter samples of particles PM₁₀, PM_2.5 and PM₁ were characterized for mass, water-soluble ions, organic and elemental carbon from 2004 until 2008. The percentage of PM_2.5 in PM₁₀ varies between summer (71.6%) and winter seasons (81.9%). Mean concentrations of PM₁₀, PM_2.5 and PM₁ in Melpitz were 20, 15, and 13 μg m^?3 in 2004, 22, 18, and 13 μg m^?3 in 2005, 24, 19, and 12 μg m^?3 in 2006 and 22, 17, and 12 μg m^?3 in 2007, respectively. In the four winters the rural background concentration PM₁₀ at Melpitz exceeded the daily 50 μg m^?3 limit for Europe on 8, 8, 7 and 6 days, respectively.Findings for a simple two-sector-classification of the samples (May 2004 until April 2008) using 96-h backward trajectories for the identification of source regions are: Air masses were transported most of time (60%) from the western sector and secondly (17%) from the eastern sector. The lowest daily mean mass concentration PM₁₀ were found during western inflow in summer (17 μg m^?3) containing low amounts of sulphate (2.4 μg m^?3), nitrate (1.7 μg m^?3), ammonium (1.1 μg m^?3) and TC (3.7 μg m^?3). In opposite the highest mean mass concentration PM₁₀ was found during eastern inflow in winter (35 μg m^?3) with high amounts of sulphate (6.1 μg m^?3), nitrate (5.4 μg m^?3), ammonium (3.8 μg m^?3) and TC (9.4 μg m^?3). An estimation of secondary formed OC (SOA) shows 0.8–0.9 μg m^?3 for air masses from West and 2.1–2.2 μg m^?3 from East. The seasonal difference can be neglected.The half-hourly measurements of the particle mass concentration PM₁₀ evaluated as mean daily courses using a TEOM^® show low values (14–21 μg m^?3) in summer and winter for air masses transported from West and the highest concentrations (31–38 μg m^?3) in winter for air masses from East.The results demonstrate the influence of meteorological parameters on long-range transport, secondary particle mass formation and re-emission which modify mass concentration and composition of PM₁₀, PM_2.5 and PM₁. Melpitz site is located in the East of Germany faraway from strong local anthropogenic emissions (rural background). Therefore, this site is suitable for investigation of the influence of long-range transport of air pollution in continental air masses from the East with source regions inside and outside of the European Union.     

PM2.5, soot and NO2 indoor–outdoor relationships at homes,pre-schools and schools in Stockholm,Sweden

In developed nations people spend about 90% of their time indoors. The relationship between indoor and outdoor air pollution levels is important for the understanding of the health effects of outdoor air pollution. Although other studies describe both the outdoor and indoor atmospheric environment, few excluded a priori major indoor sources, measured the air exchange rate, included more than one micro-environment and included the presence of human activity. PM_2.5, soot, NO₂ and the air exchange rate were measured during winter and summer indoors and outdoors at 18 homes (mostly apartments) of 18 children (6–11-years-old) and also at the six schools and 10 pre-schools that the children attended. The three types of indoor environments were free of environmental tobacco smoke and gas appliances, as the aim was to asses to what extent PM_2.5, soot and NO₂ infiltrate from outdoors to indoors. The median indoor and outdoor PM_2.5 levels were 8.4 μg m^?3 and 9.3 μg m^?3, respectively. The median indoor levels for soot and NO₂ were 0.66 m^?1 × 10^?5 and 10.0 μg m^?3, respectively. The respective outdoor levels were 0.96 m^?1 × 10^?5 and 12.4 μg m^?3. The median indoor/outdoor (I/O) ratios were 0.93, 0.76 and 0.92 for PM_2.5, soot and NO₂, respectively. Their infiltration factors were influenced by the micro-environment, ventilation type and air exchange rate, with aggregated values of 0.25, 0.55 and 0.64, respectively. Indoor and outdoor NO₂ levels were strongly associated (R² = 0.71), followed by soot (R² = 0.50) and PM_2.5 (R² = 0.16). In Stockholm, the three major indoor environments occupied by children offer little protection against combustion-related particles and gases in the outdoor air. Outdoor PM_2.5 seems to infiltrate less, but indoor sources compensate.     

Speciation and diurnal variation of thoracic,fine thoracic and sub-micrometer airborne particulate matter at naturally ventilated office environments

Thoracic (PM₁₀), fine thoracic (PM_2.5) and sub-micrometer (PM₁) airborne particulate matter was sampled during day and night. In total, about 100 indoor and outdoor samples were collected for each fraction at ten different office environments. Energy-dispersive X-ray fluorescence spectrometry and ion chromatography were applied for the quantification of some major and minor elements and ions in the collected aerosols. During daytime, mass concentrations were in the ranges: 11–29, 8.1–24, and 6.6–18 μg m^?3, with averages of 20 ± 1, 15.0 ± 0.9, and 11.0 ± 0.8 μg m^?3, respectively. At night, mass concentrations were found to be significantly lower for all fractions. Indoor PM₁ concentrations exceeded the corresponding outdoor levels during office hours and were thought to be elevated by office printers. Particles with diameters between 1 and 2.5 μm and 2.5 and 10 μm were mainly associated with soil dust elements and were clearly subjected to distinct periods of settling/resuspension. Indoor NO₃^? levels were found to follow specific microclimatic conditions at the office environments, while daytime levels of sub-micrometer Cl^? were possibly elevated by the use of Cl-containing cleaning products. Indoor carbon black concentrations were sometimes as high as 22 μg m^?3 and were strongly correlated with outdoor traffic conditions.     

Particulate matter and manganese exposures in Toronto,Canada

Methylcyclopentadienyl manganese tricarbonyl (MMT) is a manganese-based gasoline additive used to enhance automobile performance. MMT has been used in Canadian gasoline for about 20 yr. Because of the potential for increased levels of Mn in particulate matter resulting from automotive exhausts, a large-scale population-based exposure study (∼1000 participant periods) was conducted in Toronto, Canada, to estimate the distribution of 3-day average personal exposures to particulate matter (PM_2.5 and PM₁₀) and Mn. A stratified, three-stage, two-phase probability, longitudinal sample design of the metropolitan population was employed. Residential indoor and outdoor, and ambient levels (at a fixed site and on a roof) of PM_2.5, PM₁₀, and Mn were also measured. Supplementary data on traffic counts, meteorology, MMT levels in gasoline, personal occupations, and activities (e.g. amount of vehicular usage) were collected. Overall precision (%RSD) for analysis of duplicate co-located samples ranged from 2.5 to 5.0% for particulate matter and 3.1 to 5.5% for Mn. The detection limits were 1.47 and 3.45 μg m^-3 for the PM₁₀ and PM_2.5 fractions, respectively, and 5.50 and 1.83 ng m^-3 for Mn in PM₁₀ and PM_2.5, respectively. These low detection limits permitted the reporting of concentrations for >98% of the samples. For PM₁₀, the personal particulate matter levels (median 48.5 μg m^-3) were much higher than either indoor (23.1 μg m^-3) or outdoor levels (23.6 μg m^-3). The median levels for PM_2.5 for personal, indoor, and outdoor were 28.4, 15.4 and 13.2 μg m^-3, respectively. The correlation between PM_2.5 personal exposures and indoor concentrations was high (0.79), while correlations between personal and the outdoor, fixed site and roof site were low (0.16–0.27). Indoor Mn concentration distributions (in PM_2.5 and PM₁₀), unlike particulate matter, exhibited much lower and less variable levels that the corresponding outdoor data. The median personal exposure was 8.0 ng m^-3, compared with 4.7 and 8.6 ng m^-3, respectively, for the indoor and outdoor distributions. The highest correlations occurred for personal vs indoor data (0.56) and for outdoor vs roof site data (0.66), and vs fixed site data (0.56). The concentration of Mn in particulate matter, expressed in ppm (w/w), revealed that the fixed site was the highest, followed by the roof site, outdoor, indoor, and personal. The personal and indoor data showed a statistically significant correlation (0.68) while all other correlations between personal or indoor data and outdoor or fixed-site data were quite small. The low correlations of personal and indoor levels with outdoor levels suggest that different sources in the indoor and outdoor microenvironments produce particle matter with dissimilar composition. The correlation results indicate that neither the roof- nor fixed-site concentrations can adequately predict personal particulate matter or Mn exposures.     

Impact of smoking on in-vehicle fine particle exposure during driving

Indoor smoking ban in public places can reduce secondhand smoke (SHS) exposure. However, smoking in cars and homes has continued. The purpose of this study was to assess particulate matter less than 2.5 μm (PM_2.5) concentration in moving cars with different window opening conditions. The PM_2.5 level was measured by an aerosol spectrometer inside and outside moving cars simultaneously, along with ultrafine particle (UFP) number concentration, speed, temperature and humidity inside cars. Two sport utility vehicles were used. Three different ventilation conditions were evaluated by up to 20 repeated experiments. In the pre-smoking phase, average in-vehicle PM_2.5 concentrations were 16–17 μg m^?3. Regardless of different window opening conditions, the PM_2.5 levels promptly increased when smoking occurred and decreased after cigarette was extinguished. Although only a single cigarette was smoked, the average PM_2.5 levels were 506–1307 μg m^?3 with different window opening conditions. When smoking was ceased, the average PM_2.5 levels for 15 min were several times higher than the US National Ambient Air Quality Standard of 35 μg m^?3. It took longer than 10 min to reach the level of the pre-smoking phase. Although UFP levels had a similar temporal profile of PM_2.5, the increased levels during the smoking phase were relatively small. This study demonstrated that the SHS exposure in cars with just a single cigarette being smoked could exceed the US EPA NAAQS under realistic window opening conditions. Therefore, the findings support the need for public education against smoking in cars and advocacy for a smoke-free car policy.     

Physicochemical variations in atmospheric aerosols recorded at sea onboard the Atlantic–Mediterranean 2008 Scholar Ship cruise (Part I): Particle mass concentrations,size ratios,and main chemical components

We report on ambient atmospheric aerosols present at sea during the Atlantic–Mediterranean voyage of Oceanic II (The Scholar Ship) in spring 2008. A record was obtained of hourly PM₁₀, PM_2.5, and PM₁ particle size fraction concentrations and 24-h filter samples for chemical analysis which allowed for comparison between levels of crustal particles, sea spray, total carbon, and secondary inorganic aerosols. On-board monitoring was continuous from the equatorial Atlantic to the Straits of Gibraltar, across the Mediterranean to Istanbul, and back via Lisbon to the English Channel. Initially clean air in the open Atlantic registered PM₁₀ levels <10 μg m^?3 but became progressively polluted by increasingly coarse PM as the ship approached land. Away from major port cities, the main sources of atmospheric contamination identified were dust intrusions from North Africa (NAF), smoke plumes from biomass burning in sub-Saharan Africa and Russia, industrial sulphate clouds and other regional pollution sources transported from Europe, sea spray during rough seas, and plumes emanating from islands. Under dry NAF intrusions PM₁₀ daily mean levels averaged 40–60 μg m^?3 (30–40 μg m^?3 PM_2.5; c. 20 μg m^?3 PM₁), peaking briefly to >120 μg m^?3 (hourly mean) when the ship passed through curtains of higher dust concentrations amassed at the frontal edge of the dust cloud. PM₁/PM₁₀ ratios ranged from very low during desert dust intrusions (0.3–0.4) to very high during anthropogenic pollution plume events (0.8–1).     

New approach using lidar measurements to characterize spatiotemporal aerosol mass distribution in an underground railway station in Paris

For the first time eye safe lidar measurements were performed at 355 nm simultaneously to in situ measurements in an underground station so as to test the potential interest of active remote sensing measurements to follow the spatiotemporal evolution of aerosol content inside such a confined microenvironment. The purpose of this paper is to describe different methods enabling the conversion of lidar-derived aerosol extinction coefficient into aerosol mass concentrations (PM_2.5 and PM₁₀). A theoretical method based on a well marked linear regression between mass concentrations simulated from the size distribution and extinction coefficients retrieved from Mie calculations provides averaged mass to optics' relations over the campaign for traffic (6.47 × 10⁵ μg m^?2) or no traffic conditions (3.73 × 10⁵ μg m^?2). Two empirical methods enable to significantly reduce CPU time. The first one is based upon the knowledge of size distribution measurements and scattering coefficients from nephelometer and allows retrieving mass to optics' relations for well determined periods or particular traffic conditions, like week-ends, with a good accuracy. The second method, that is more direct, is simply based on the ratio between TEOM concentrations and extinction coefficients obtained from nephelometer. This method is easy to set up but is not suitable for nocturnal measurements where PM stabilization time is short. Lidar signals thus converted into PM concentrations from those approaches with a fine accuracy (30%) provide a spatiotemporal distribution of concentrations in the station. This highlights aerosol accumulation in one side of the station, which can be explained by air displacement from the tunnel entrance. Those results allow expecting a more general use of lidar measurement to survey indoor air quality.     

Spatial and temporal variability of outdoor coarse particulate matter mass concentrations measured with a new coarse particle sampler during the Detroit Exposure and Aerosol Research Study

The Detroit Exposure and Aerosol Research Study (DEARS) provided data to compare outdoor residential coarse particulate matter (PM_10–2.5) concentrations in six different areas of Detroit with data from a central monitoring site. Daily and seasonal influences on the spatial distribution of PM_10–2.5 during Summer 2006 and Winter 2007 were investigated using data collected with the newly developed coarse particle exposure monitor (CPEM). These data allowed the representativeness of the community monitoring site to be assessed for the greater Detroit metro area. Multiple CPEMs collocated with a dichotomous sampler determined the precision and accuracy of the CPEM PM_10–2.5 and PM_2.5 data.CPEM PM_2.5 concentrations agreed well with the dichotomous sampler data. The slope was 0.97 and the R² was 0.91. CPEM concentrations had an average 23% negative bias and R² of 0.81. The directional nature of the CPEM sampling efficiency due to bluff body effects probably caused the negative CPEM concentration bias.PM_10–2.5 was observed to vary spatially and temporally across Detroit, reflecting the seasonal impact of local sources. Summer PM_10–2.5 was 5 μg m^?3 higher in the two industrial areas near downtown than the average concentrations in other areas of Detroit. An area impacted by vehicular traffic had concentrations 8 μg m^?3 higher than the average concentrations in other parts of Detroit in the winter due to the suspected suspension of road salt. PM_10–2.5 Pearson Correlation Coefficients between monitoring locations varied from 0.03 to 0.76. All summer PM_10–2.5 correlations were greater than 0.28 and statistically significant (p-value < 0.05). Winter PM_10–2.5 correlations greater than 0.33 were statistically significant (p-value < 0.05). The PM_10–2.5 correlations found to be insignificant were associated with the area impacted by mobile sources during the winter. The suspected suspension of road salt from the Southfield Freeway, combined with a very stable atmosphere, caused concentrations to be greater in this area compared to other areas of Detroit. These findings indicated that PM_10–2.5, although correlated in some instances, varies sufficiently across a complex urban airshed that that a central monitoring site may not adequately represent the population's exposure to PM_10–2.5.     

Meteorological variability in NO2 and PM10 concentrations in the Netherlands and its relation with EU limit values

The extent of the exceedance of the EU limit values for nitrogen dioxide (NO₂) and particulate matter (PM₁₀) concentrations within the Netherlands is expected to decrease significantly, in the coming years. Whether limit values will actually be exceeded, in the next decade, depends not only on European, national and local policies, but also on the effects of inevitable interannual meteorological fluctuations. An analysis of model calculations and measurements yields variations (1 sigma) in the annual average concentration of about 5% for NO₂ and 9% for PM₁₀, due to meteorological fluctuations. These deviations from long-term average concentrations affect assessments of future levels, set against limit values. For instance, an NO₂ concentration of 39 μg m^?3, estimated for a given year with long-term average meteorology, indicates that it is likely (chance >66%) that the limit value of 40 μg m^?3 will not be exceeded in that particular year. At the same time, the estimation also indicates, for example, that this situation is unlikely (change <33%) to continue for three years in a row. However, with an estimated concentration of 38 μg m^?3, it is likely that the limit value will not be exceeded for three years in a row. The limit value for the daily average PM₁₀ concentration is equivalent to an annual average of about 32 μg m^?3. This threshold is unlikely to be exceeded for three years in a row, when an annual average concentration of 29 μg m^?3 is estimated. Interannual variations in concentrations of NO₂ and PM₁₀ are linked to large-scale meteorological fluctuations. Therefore, similar results can be expected for other European countries.     

Fine particles and carbon monoxide from wood burning in 17th–19th century Danish kitchens: Measurements at two reconstructed farm houses at the Lejre Historical–Archaeological Experimental Center

Carbon monoxide (CO) and particulate matter (PM_2.5) were measured in two reconstructed Danish farmhouses (17–19th century) during two weeks of summer. During the first week intensive measurements were performed while test cooking fires were burned, during the second week the houses were monitored while occupied by guest families. A masonry hearth was located in the middle of each house for open cooking fires and with heating stoves. One house had a chimney leading to the outside over the hearth; in the other, a brickwork hood led the smoke into an attic and through holes in the roof. During the first week the concentration of PM_2.5 averaged daily between 138 and 1650 μg m^?3 inside the hearths and 21–160 μg m^?3 in adjacent living rooms. CO averaged daily between 0.21 and 1.9 ppm in living areas, and up to 12 ppm in the hearths. Highest concentrations were measured when two fires were lit at the same time, which would cause high personal exposure for someone working in the kitchens. 15 min averages of up to 25 400 μg m^?3 (PM_2.5) and 260 ppm CO were recorded. WHO air quality guidelines were occasionally exceeded for CO and constantly for PM_2.5. However, air exchange and air distribution measurements revealed a large draw in the chimney, which ensured a fast removal of wood smoke from the hearth area. The guest families were in average exposed to no more than 0.21 ppm CO during 48 h. Based on a hypothetical time-activity pattern, however, a woman living in this type of house during the 17–19th century would be exposed to daily averages of 1.1 ppm CO and 196 μg m^?3 PM_2.5, which exceeds WHO guideline for PM_2.5, and is comparable to what is today observed for women in rural areas of developing countries.     

Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2

Atmospheric PM pollution from traffic comprises not only direct emissions but also non-exhaust emissions because resuspension of road dust that can produce high human exposure to heavy metals, metalloids, and mineral matter. A key task for establishing mitigation or preventive measures is estimating the contribution of road dust resuspension to the atmospheric PM mixture. Several source apportionment studies, applying receptor modeling at urban background sites, have shown the difficulty in identifying a road dust source separately from other mineral sources or vehicular exhausts. The Multilinear Engine (ME-2) is a computer program that can solve the Positive Matrix Factorization (PMF) problem. ME-2 uses a programming language permitting the solution to be guided toward some possible targets that can be derived from a priori knowledge of sources (chemical profile, ratios, etc.). This feature makes it especially suitable for source apportionment studies where partial knowledge of the sources is available.In the present study ME-2 was applied to data from an urban background site of Barcelona (Spain) to quantify the contribution of road dust resuspension to PM₁₀ and PM_2.5 concentrations. Given that recently the emission profile of local resuspended road dust was obtained (Amato, F., Pandolfi, M., Viana, M., Querol, X., Alastuey, A., Moreno, T., 2009. Spatial and chemical patterns of PM₁₀ in road dust deposited in urban environment. Atmospheric Environment 43 (9), 1650–1659), such a priori information was introduced in the model as auxiliary terms of the object function to be minimized by the implementation of the so-called “pulling equations”.ME-2 permitted to enhance the basic PMF solution (obtained by PMF2) identifying, beside the seven sources of PMF2, the road dust source which accounted for 6.9 μg m^?3 (17%) in PM₁₀, 2.2 μg m^?3 (8%) of PM_2.5 and 0.3 μg m^?3 (2%) of PM₁. This reveals that resuspension was responsible of the 37%, 15% and 3% of total traffic emissions respectively in PM₁₀, PM_2.5 and PM₁. Therefore the overall traffic contribution resulted in 18 μg m^?3 (46%) in PM₁₀, 14 μg m^?3 (51%) in PM_2.5 and 8 μg m^?3 (48%) in PM₁. In PMF2 this mass explained by road dust resuspension was redistributed among the rest of sources, increasing mostly the mineral, secondary nitrate and aged sea salt contributions.     

Personal exposure to particulate air pollution in transport microenvironments

Personal measurements of exposure to particulate air pollution (PM₁₀, PM_2.5, PM₁) were simultaneously made during walking and in-car journeys on two suburban routes in Northampton, UK, during the winter of 1999/2000. Comparisons were made between concentrations found in each transport mode by particle fraction, between different particle fractions by transport mode, and between transport microenvironments and a fixed-site monitor located within the study area. High levels of correlation were seen between walking and in-car concentrations for each of the particle fractions (PM₁₀: r²=0.82; PM_2.5: r²=0.98; PM₁: r²=0.99). On an average, PM₁₀ concentrations were 16% higher inside the car than for the walker, but there were no difference in average PM_2.5 and PM₁ concentrations between the two modes. High PM_2.5:PM₁₀ ratios (0.6–0.73) were found to be associated with elevated sulphate levels. The PM_2.5:PM₁₀ and PM₁:PM_2.5 ratios were shown to be similar between walking and in-car concentrations. Concentrations of PM₁₀ were found to be more closely related between transport mode than either mode was with concentrations recorded at the fixed-site (roadside) monitor. The fixed-site monitor was shown to be a poor marker for PM₁₀ concentrations recorded during walking and in-car on a route over 1 km away.     

Potential effects of particulate matter from combustion during services on human health and on works of art in medieval churches in Cyprus

Indoor and outdoor particulate matter (PM_0.3-10) number concentrations were established in two medieval churches in Cyprus. In both churches incense was burnt occasionally during Mass. The highest indoor PM_0.5-1 concentrations compared with outdoors (10.7 times higher) were observed in the church that burning of candles indoors was allowed. Peak indoor black carbon concentration was 6.8 μg m⁻³ in the instances that incense was burning and 13.4 μg m⁻³ in the instances that the candles were burning (outdoor levels ranged between 0.6 and 1.3 μg m⁻³). From the water soluble inorganic components determined in PM₁₀, calcium prevailed in all samples indoors or outdoors, whilst high potassium concentration indoors were a clear marker of combustion. Indoor sources of PM were clearly identified and their emission strengths were estimated via modeling of the results. Indoor estimated PM_0.3-10 mass concentrations exceeded air quality standards for human health protection and for the preservation of works of art.     

Particulate matter emissions from on-road vehicles in a freeway tunnel study

Particulate matter, including coarse particles (PM_2.5–10, aerodynamic diameter of particle between 2.5 and 10 μm) and fine particles (PM_2.5, aerodynamic diameter of particle lower than 2.5 μm) and their compositions, including elemental carbon, organic carbon, and 11 water-soluble ionic species, and elements, were measured in a tunnel study. A comparison of the six-hour average of light-duty vehicle (LDV) flow of the two sampling periods showed that the peak hours over the weekend were higher than those on weekdays. However, the flow of heavy-duty vehicles (HDVs) on the weekdays was significant higher than that during the weekend in this study. EC and OC content were 49% for PM_2.5–10 and 47% for PM_2.5 in the tunnel center. EC content was higher than OC content in PM_2.5–10, but EC was about 2.3 times OC for PM_2.5. Sulfate, nitrate, ammonium were the main species for PM_2.5–10 and PM_2.5. The element contents of Na, Al, Ca, Fe and K were over 0.8 μg m^?3 in PM_2.5–10 and PM_2.5. In addition, the concentrations of S, Ba, Pb, and Zn were higher than 0.1 μg m^?3 for PM_2.5–10 and PM_2.5. The emission factors of PM_2.5–10 and PM_2.5 were 18 ± 6.5 and 39 ± 11 mg km^?1-vehicle, respectively. The emission factors of EC/OC were 3.6/2.7 mg km^?1-vehicle for PM_2.5–10 and 15/4.7 mg km^?1-vehicle for PM_2.5 Furthermore, the emission factors of water-soluble ions were 0.028(Mg²⁺)–0.81(SO₄^2?) and 0.027(NO₂^?)–0.97(SO₄^2?) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively. Elemental emission factors were 0.003(V)–1.6(Fe) and 0.001(Cd)–1.05(Na) mg km^?1-vehicle for PM_2.5–10 and PM_2.5, respectively.     

Behavioral and environmental determinants of personal exposures to PM2.5 in EXPOLIS – Helsinki,Finland

Behavioral and environmental determinants of PM_2.5 personal exposures were analyzed for 201 randomly selected adult participants (25–55 years old) of the EXPOLIS study in Helsinki, Finland. Personal exposure concentrations were higher than respective residential outdoor, residential indoor and workplace indoor concentrations for both smokers and non-smokers. Mean personal exposure concentrations of active smokers (31.0±31.4 μg m⁻³) were almost double those of participants exposed to environmental tobacco smoke (ETS) (16.6±11.8 μg m⁻³) and three times those of participants not exposed to tobacco smoke (9.9±6.2 μg m⁻³). Mean indoor concentrations of PM_2.5 when a member of the household smoked indoors (20.8±23.9 μg m⁻³) were approximately 2.5 times the concentrations of PM_2.5 when no smoking was reported (8.2±5.2 μg m⁻³). Interestingly, however, both mean (8.2 μg m⁻³) and median (6.9 μg m⁻³) residential indoor concentrations for non-ETS exposed participants were lower than residential outdoor concentrations (9.5 and 7.3 μg m⁻³, respectively). In simple linear regression models residential indoor concentrations were the best predictors of personal exposure concentrations. Correlations (r²) between PM_2.5 personal exposure concentrations of all participants, both smoking and non-smoking, and residential indoor, workplace indoor, residential outdoor and ambient fixed site concentrations were 0.53, 0.38, 0.17 and 0.16, respectively. Predictors for personal exposure concentrations of non-ETS exposed participants identified in multiple regression were residential indoor concentrations, workplace concentrations and traffic density in the nearest street from home, which accounted for 77% of the variance. Subsequently, step-wise regression not including residential and workplace indoor concentrations as input (as these are frequently not available), identified ambient PM_2.5 concentration and home location, as predictors of personal exposure, accounting for 47% of the variance. Ambient fixed site PM_2.5 concentrations were closely related to residential outdoor concentrations (r²=0.9, p=0.000) and PM_2.5 personal exposure concentrations were higher in summer than during other seasons. Personal exposure concentrations were significantly (p=0.040) higher for individuals living downtown compared with individuals in suburban family homes. Further analysis will focus on comparisons of determinants between Helsinki and other EXPOLIS centers.     

Journey-time exposure to particulate air pollution

Journey-time exposures to particulate air pollution were investigated in Leicester, UK, between January and March 2005. Samples of TSP, PM₁₀, PM_2.5, and PM₁ were simultaneously collected using light scattering devices whilst journeys were made by walking an in-car. Over a period of two months, 33 pairs of walking and in-car measurements were collected along two circular routes. Average exposures while walking were seen to be higher than those found in-car for each of the particle fractions: average walking to in-car ratios were 1.2 (± 0.6), 1.5 (± 0.6), 1.3 (± 0.6), and 1.4 (± 0.6) μg m⁻³ for coarse (TSP–PM₁₀), intermediate (PM₁₀–PM_2.5), fine (PM_2.5–PM₁), and very fine particles (PM₁), respectively. Correlations between walking and in-car exposures were seen to be weak for coarse particles (r=0.10, p=0.58), moderate for the intermediate particles (r=0.49, p<0.01) but strong for fine (r=0.89, p<0.01) and very fine (r=0.90, P<0.01) particles. PM₁₀ exposures while walking were on average 70% higher than a nearby roadside fixed-site monitor whilst in-car exposures were 25% higher than the same fixed-site monitor. Particles with an aerodynamic diameter of less than 2.5 μm were seen to be highly correlated between walking and in-car particle exposures and a rural fixed-site monitor about 30 km south of Leicester.     

Air pollutants in rural homes in Guizhou,China – Concentrations,speciation, and size distribution

Several types of fuels, including coal, fuel wood, and biogas, are commonly used for cooking and heating in Chinese rural households, resulting in indoor air pollution and causing severe health impacts. In this paper, we report a study monitoring multiple pollutants including PM₁₀, PM_2.5, CO, CO₂, and volatile organic compounds (VOCs) from fuel combustion at households in Guizhou province of China. The results showed that most pollutants exhibited large variability for different type of fuels except for CO₂. Among these fuels, wood combustion caused the most serious indoor air pollution, with the highest concentrations of particulate matters (218～417 μg m^?3 for PM₁₀ and 201～304 μg m^?3 for PM_2.5), and higher concentrations of CO (10.8 ± 0.8 mg m^?3) and TVOC (about 466.7 ± 337.9 μg m^?3). Coal combustion also resulted in higher concentrations of particulate matters (220～250 μg m^?3 for PM₁₀ and 170～200 μg m^?3 for PM_2.5), but different levels for CO (respectively 14.5 ± 3.7 mg m^?3 for combustion in brick stove and 5.5 ± 0.7 mg m^?3 for combustion in metal stove) and TVOC (170 mg m^?3 for combustion in brick stove and 700 mg m^?3 for combustion in metal stove). Biogas was the cleanest fuel, which brought about the similar levels of various pollutants with the indoor case of non-combustion, and worth being promoted in more areas. Analysis of the chemical profiles of PM_2.5 indicated that OC and EC were dominant components for all fuels, with the proportions of 30～48%. A high fraction of SO₄^2? (31～34%) was detected for coal combustion. The cumulative percentages of these chemical species were within the range of 0.7～1.3, which was acceptable for the assessment of mass balance.