Spatial and chemical patterns of PM10 in road dust deposited in urban environment

Recent research interest has been focused on road dust resuspension as one of the major sources of atmospheric particulate matter in an urban environment. Given the dearth of studies on the variability of the PM₁₀ fraction of road deposited sediments, our understanding of the main factors controlling this pollutant is incomplete. In the present study a new sampling methodology was devised and applied to collect PM₁₀ deposited mass from 1 m² of road pavement. PM₁₀ road dust fraction was sampled directly from active traffic lanes at 23 sampling sites during a campaign in Barcelona (Spain) in June 2007. The aim of the study was to gain more insight into the variability of mass and chemistry of road dust in different urban environments, such as the city centre, ring roads, and locations nearby demolition/construction sites. The city centre showed values of PM₁₀ road dust within a range of 3–23 mg m^?2, whereas levels reached 24–80 mg m^?2 in locations affected by transport of uncovered heavy trucks. The largest dust loads were measured in the proximity of demolition/construction sites and the harbor entry with values up to 328 mg m^?2.The city centre road dust profiles (%) were enriched in OC, EC, Fe, S, Cu, Zn, Mn, Cr, Sb, Sn, Mo, Zr, Hf, Ge, Ba, Pb, Bi, SO₄^2?, NO₃^?, Cl^? and NH₄⁺, but several crustal components such as Ca, Ti, Na, and Mg were also considerably concentrated. Locations affected by construction and demolition activities had high levels of crustal components such as Ca, Li, Sc, Sr, Rb and also As whereas ring roads, characterized by a higher load of uncovered heavy trucks showed an intermediate composition.Levels of PM₁₀ components per area were also evaluated to quantify the resuspendable amount of each element from 1 m². In the inner city environment mean values of 1363 μg Ca m^?2, 816 μg OC m^?2, 239 μg EC m^?2, 13 μg Cu m^?2, 12 μg Zn m^?2, 1.9 μg Sb m^?2 and 2.0 μg Pb m^?2, in PM₁₀ in all cases, were registered.Moreover the deposited PM load at demolition/construction sites acts as a reservoir or trap for traffic-related particles, which gives rise to large amounts of hazardous pollutants, available for resuspension.     

Estimating the impact of Saharan dust on the year 2001 PM10 record of Rome,Italy

This paper evaluates the role of Saharan dust advection in the exceeding of the PM₁₀ thresholds in the city of Rome, Italy. To this purpose, a series of observations and model forecasts recorded in the year 2001 are analysed and discussed. Lidar profiles collected over 168 days of the year are employed to both assess the presence and magnitude of Saharan dust layers over the city and to evaluate the depth of the planetary boundary layer. Backtrajectories are used to verify the Saharan origin of the lidar-sounded air masses. Model predictions of the presence of Saharan dust over the area are employed to fill the time gaps between lidar observations. PM₁₀ and carbon monoxide records of both a city background (Villa Ada) and a heavy traffic station (Magna Grecia) are cross-analysed with the dust events record and meteorological data. The analysis shows that: (1) Saharan dust was advected over Rome on about 30% of the days of 2001; (2) mean contribution of Saharan dust transport events to daily PM₁₀ levels was of the order of 20 μg m⁻³; (3) at the urban background station of Villa Ada, the Saharan contribution caused the surpassing of the maximum number of days in excess of 50 μg m⁻³ fixed by the current legislation (35 per year). Conversely, at the heavy traffic station of Magna Grecia the Saharan contribution was not determinant at causing the observed large exceeding of that limit, as well as of the maximum yearly average of 40 μg m⁻³; (4) 25% of the Saharan advection days (of the order of 100/year at Rome) led to a PM₁₀ increase >30 μg m⁻³, 4% caused an increase >50 μg m⁻³, thus leading on their own to surpassing the 50 μg m⁻³ daily limit.     

Quantification of Saharan dust contribution to PM10 concentrations over Italy during 2003–2005

Italy is frequently affected by Saharan dust intrusions, which result in high PM₁₀ concentrations in the atmosphere and can cause the exceedances of the PM₁₀ daily limits (50 μg m^?3) set by the European Union (EU/2008/50). The estimate of African dust contribution to PM₁₀ concentrations is therefore a key issue in air quality assessment and policy formulation. This study presents a first identification of Saharan dust outbreaks as well as an estimate of the African dust contribution to PM₁₀ concentrations during the period 2003–2005 over Italy. The identification of dust events has been carried out by looking at different sources of information such as monitoring network observations, satellite images, ground measurements of aerosol optical properties, dust model simulations and air mass backward trajectory analysis. The contribution of Saharan dust to PM₁₀ monthly concentrations has been estimated at seven Italian locations. The results are both spatially (with station) and temporally (with month and year) variable, as a consequence of the variability of the meteorological conditions. However, excluding the contribution of severe dust events (21st February 2004, 25th–28th September 2003, 23rd–27th March 2005), the monthly contribution of dust varies approximately between 1 μg m^?3 and 10 μg m^?3 throughout year 2005 and between 1 μg m^?3 and 8 μg m^?3 throughout year 2003. In 2004 the dust concentration is lower than 2003 and 2005 (<5 μg m^?3 at all sites). The reduction in the number of daily exceedances of the limit value (50 μg m^?3) after subtraction of the dust contribution is also calculated at each station: it varies with station between 20% and 50% in 2005 and between 5% and 25% in 2003 and 2004.     

Spatial variation of mass concentration of roadside suspended particulate matter in metropolitan Hong Kong

This study conducted roadside particulate sampling to measure the total suspended particulate (TSP), PM₁₀ (particles <10 μm in aerodynamic diameter) and PM_2.5 (particles <2.5 μm in aerodynamic diameter) mass concentration in 11 urbanized and densely populated districts in Hong Kong. One hundred and thirty-three samples were obtained to measure the mass concentrations of TSP, PM₁₀ and PM_2.5. According to these results, the TSP, PM₁₀ and PM_2.5 mass concentrations varied from 94.85 to 301.63 μg m⁻³, 67.67 to 142.68 μg m⁻³ and 50.01 to 125.12 μg m⁻³, respectively. The PM_2.5/PM₁₀ ratio of all samples was 0.82 which ranged from 0.62 to 0.95. The PM levels and PM ratios in metropolitan Hong Kong significantly fluctuated from site-to-site and over time. The PM_2.5 mass concentration in different districts corresponding to urban industrial, new town, urban residential and urban commercial were 77.64, 87.50, 106.96 and 88.54 μg m⁻³, respectively. The PM_2.5 level is high in Hong Kong, and for individual sampling, more than 60% daily measurements exceeded the NAAQS. The mass fraction of PM_2.5 in PM₁₀ and TSP is relatively high when compared with overseas studies.     

Characteristics of vertical profiles and sources of PM2.5, PM10 and carbonaceous species in Beijing

In August 2003 during the anticipated month of the 2008 Beijing Summer Olympic Games, we simultaneously collected PM₁₀ and PM_2.5 samples at 8, 100, 200 and 325 m heights up a meteorological tower and in an urban and a suburban site in Beijing. The samples were analysed for organic carbon (OC) and elemental carbon (EC) contents. Particulate matter (PM) and carbonaceous species pollution in the Beijing region were serious and widespread with 86% of PM_2.5 samples exceeding the daily National Ambient Air Quality Standard of the USA (65 μg m⁻³) and the overall daily average PM₁₀ concentrations of the three surface sites exceeding the Class II National Air Quality Standard of China (150 μg m⁻³). The maximum daily PM_2.5 and PM₁₀ concentrations reached 178.7 and 368.1 μg m⁻³, respectively, while those of OC and EC reached 22.2 and 9.1 μg m⁻³ in PM_2.5 and 30.0 and 13.0 μg m⁻³ in PM₁₀, respectively. PM, especially PM_2.5, OC and EC showed complex vertical distributions and distinct layered structures up the meteorological tower with elevated levels extending to the 100, 200 and 300 m heights. Meteorological evidence suggested that there exist fine atmospheric layers over urban Beijing. These layers were featured by strong temperature inversions close to the surface (<50 m) and more stable conditions aloft. They enhanced the accumulation of pollutants and probably caused the complex vertical distributions of PM and carbonaceous species over urban Beijing. The built-up of PM was accompanied by transport of industrial emissions from the southwest direction of the city. Emissions from road traffic and construction activities as well as secondary organic carbon (SOC) are important sources of PM. High OC/EC ratios (range of 1.8–5.1 for PM_2.5 and 2.0–4.3 for PM₁₀) were found, especially in the higher levels of the meteorological tower suggesting there were substantial productions of SOC in summer Beijing. SOC is estimated to account for at least 33.8% and 28.1% of OC in PM_2.5 and PM₁₀, respectively, with higher percentages at the higher levels of the tower.     

PM10 and PM2.5 concentrations in Central and Eastern Europe:: results from the Cesar study

Between November 1995 and October 1996, particulate matter concentrations (PM₁₀ and PM_2.5) were measured in 25 study areas in six Central and Eastern European countries: Bulgaria, Czech Republic, Hungary, Poland, Romania and Slovak Republic. To assess annual mean concentration levels, 24-h averaged concentrations were measured every sixth day on a fixed urban background site using Harvard impactors with a 2.5 and 10 μm cut-point. The concentration of the coarse fraction of PM₁₀ (PM_10−2.5) was calculated as the difference between the PM₁₀ and the PM_2.5 concentration. Spatial variation within study areas was assessed by additional sampling on one or two urban background sites within each study area for two periods of 1 month. QA/QC procedures were implemented to ensure comparability of results between study areas. A two to threefold concentration range was found between study areas, ranging from an annual mean of 41 to 98 μg m⁻³ for PM₁₀, from 29 to 68 μg m⁻³ for PM_2.5 and from 12 to 40 μg m⁻³ for PM_10−2.5. The lowest concentrations were found in the Slovak Republic, the highest concentrations in Bulgaria and Poland. The variation in PM₁₀ and PM_2.5 concentrations between study areas was about 4 times greater than the spatial variation within study areas suggesting that measurements at a single sampling site sufficiently characterise the exposure of the population in the study areas. PM₁₀ concentrations increased considerably during the heating season, ranging from an average increase of 18 μg m⁻³ in the Slovak Republic to 45 μg m⁻³ in Poland. The increase of PM₁₀ was mainly driven by increases in PM_2.5; PM_10−2.5 concentrations changed only marginally or even decreased. Overall, the results indicate high levels of particulate air pollution in Central and Eastern Europe with large changes between seasons, likely caused by local heating.     

Particulate matter in the indoor air of classrooms—exploratory results from Munich and surrounding area

Numerous epidemiological studies have demonstrated the association between particle mass (PM) concentration in outside air and the occurrence of health related problems and/or diseases. However, much less is known about indoor PM concentrations and associated health risks. In particular, data are needed on air quality in schools, since children are assumed to be more vulnerable to health hazards and spend a large part of their time in classrooms.On this background, we evaluated indoor air quality in 64 schools in the city of Munich and a neighbouring district outside the city boundary. In winter 2004–2005 in 92 classrooms, and in summer 2005 in 75 classrooms, data on indoor air climate parameters (temperature, relative humidity), carbon dioxide (CO₂) and various dust particle fractions (PM₁₀, PM_2.5) were collected; for the latter both gravimetrical and continuous measurements by laser aerosol spectrometer (LAS) were implemented. In the summer period, the particle number concentration (PNC), was determined using a scanning mobility particle sizer (SMPS). Additionally, data on room and building characteristics were collected by use of a standardized form. Only data collected during teaching hours were considered in analysis. For continuously measured parameters the daily median was used to describe the exposure level in a classroom.The median indoor CO₂ concentration in a classroom was 1603 ppm in winter and 405 ppm in summer. With LAS in winter, median PM concentrations of 19.8 μg m⁻³ (PM_2.5) and 91.5 μg m⁻³ (PM₁₀) were observed, in summer PM concentrations were significantly reduced (median PM_2.5=12.7 μg m⁻³, median PM₁₀=64.9 μg m⁻³). PM_2.5 concentrations determined by the gravimetric method were in general higher (median in winter: 36.7 μg m⁻³, median in summer: 20.2 μg m⁻³) but correlated strongly with the LAS-measured results. In explorative analysis, we identified a significant increase of LAS-measured PM_2.5 by 1.7 μg m⁻³ per increase in humidity by 10%, by 0.5 μg m⁻³ per increase in CO₂ indoor concentration by 100 ppm, and a decrease by 2.8 μg m⁻³ in 5–7th grade classes and by 7.3 μg m⁻³ in class 8–11 compared to 1–4th class. During the winter period, the associations were stronger regarding class level, reverse regarding humidity (a decrease by 6.4 μg m⁻³ per increase in 10% humidity) and absent regarding CO₂ indoor concentration. The median PNC measured in 36 classrooms ranged between 2622 and 12,145 particles cm⁻³ (median: 5660 particles cm⁻³).The results clearly show that exposure to particulate matter in school is high. The increased PM concentrations in winter and their correlation with high CO₂ concentrations indicate that inadequate ventilation plays a major role in the establishment of poor indoor air quality. Additionally, the increased PM concentration in low level classes and in rooms with high number of pupils suggest that the physical activity of pupils, which is assumed to be more pronounced in younger children, contributes to a constant process of resuspension of sedimented particles. Further investigations are necessary to increase knowledge on predictors of PM concentration, to assess the toxic potential of indoor particles and to develop and test strategies how to ensure improved indoor air quality in schools.     

Studies of the coarse particle (2.5–10 μm) component in UK urban atmospheres

An analysis is presented of continuous simultaneous measurement data for PM₁₀ and PM_2.5 using TEOM instruments from five sites in the United Kingdom. The results are analysed specifically in relation to the sources and processes influencing the coarse particle fraction (2.5–10 μm). The data show a generally strong correlation between fine and coarse particle concentrations at all sites, with a generally higher proportion of coarse particles in the dryer months of the year. The one rural site shows a notably lower proportion of coarse particles than the urban and suburban sites. Whilst it is possible to disaggregate the coarse particle concentrations into a component which is diluted by increasing windspeed and a component which increases with windspeed and is hence possibly attributable to wind-induced resuspension processes, the latter is only a minor proportion of the total coarse particle concentration. There are appreciable weekday-to-weekend and day-to-night differences between coarse particle concentrations which are most marked at the urban sites indicative of anthropogenic activities being a source of coarse particles. The clearest indication of the likely predominant source of coarse particles arises from an analysis of a data set derived from an urban street canyon site after subtraction of measurements from a nearby urban background location. The data indicate strong relationships of both fine and coarse incremental particle concentrations in the street canyon with incremental NO_x. If incremental fine particles and coarse particles are attributed to exhaust emissions and vehicle-induced resuspension, respectively, then it may be concluded that vehicle-induced resuspension provides a source strength approximately equal to that of exhaust emissions. An analysis of the coarse particle concentration data suggest that episodes of elevated coarse particle concentrations alone very rarely lead to exceedence of the UK air quality standard for PM₁₀ of 50 μg m⁻³ measured as a 24-h running mean.     

The use of receptor modelling and emission inventory data to explain the downward trend in UK PM10 concentrations

Statistically significant downward trends in measured UK annual mean PM₁₀ concentrations have been observed at eight out of the nine urban background monitoring sites between the start of monitoring in 1992 or 1993 and 2000.Site-specific projections of the individual components of measured PM₁₀ concentrations have been derived for the period 1992–2000 at three monitoring sites from receptor modelling results for 1999 monitoring data. Measured annual average PM₁₀ concentrations declined to between 71% and 66% of the 1992 values during this period at the sites studied. The largest contributions to the decline in total PM₁₀ are from secondary particles at London Bloomsbury (40%, 3.4 μg m⁻³, tapered element oscillating microbalance (TEOM)), stationary sources at Belfast Centre (53%, 4.6 μg m⁻³, TEOM) and roadside traffic emissions at Bury Roadside (49%, 5.0 μg m⁻³, TEOM). The good agreement between the projected total PM₁₀ concentrations and measured values for the years 1992–2000 indicate that the combination of the receptor model and the site-specific projections provide a suitably robust method for predicting future PM₁₀ concentrations and the quantification of the impact of possible future policy measures to reduce PM₁₀ concentrations. The good agreement between the projections and measured concentration also provides a useful verification of the trends in emissions inventory estimates for the 1990s.Projections of estimated PM₁₀ concentrations have also been calculated for the London Bloomsbury site for the period from 1970 to 1991. Annual mean concentrations are predicted to have been in the range from 30 to 35 μg m⁻³, TEOM from 1977 to 1991 but much higher at values between 39 and 46 μg m⁻³, TEOM in the early 1970s.     

Mass levels,crustal component and trace elements in PM10 in Palermo,Italy

Results concerning the levels and elemental compositions of daily PM₁₀ samples collected at four air quality monitoring sites in Palermo (Italy) are presented. The highest mean value of PM₁₀ concentrations (46 μg m⁻³, with a peak value of 158 μg m⁻³) was recorded at the Di Blasi urban station, and the lowest at Boccadifalco station (25 μg m⁻³), considered as a sub-urban background station. Seventeen elements (Al, As, Ba, Co, Cr, Cu, Fe, Li, Mn, Mo, Ni, Pb, Sb, Sr, U, V, Zn) were measured by ICP-MS. Al and Fe showed the highest concentrations, indicating the significant contribution of soil and resuspended mineral particles to atmospheric PM₁₀. Ba, Cr, Cu, Mn, Mo, Ni, Pb, Sb, V and Zn had higher concentrations at the three urban sampling sites than at the sub-urban background station. Besides soil-derived particles, an R-mode cluster analysis revealed a group of elements, Mo, Cu, Cr, Sb and Zn, probably related to non-exhaust vehicle emission, and another group, consisting of Ba, As and Ni, which seemed to be associated both with exhaust emissions from road traffic, and other combustion processes such as incinerators or domestic heating plants. The results also suggest that Sb, or the association Sb–Cu–Mo, offers a way of tracing road traffic emissions.     

Source apportionment of ambient PM2.5 at five spanish centres of the european community respiratory health survey (ECRHS II)

Fine particulate matter (PM_2.5) was sampled at 5 Spanish locations during the European Community Respiratory Health Survey II (ECRHS II). In an attempt to identify and quantify PM_2.5 sources, source contribution analysis by principal component analysis (PCA) was performed on five datasets containing elemental composition of PM_2.5 analysed by ED-XRF. A total of 4–5 factors were identified at each site, three of them being common to all sites (interpreted as traffic, mineral and secondary aerosols) whereas industrial sources were site-specific. Sea-salt was identified as independent source at all coastal locations except for Barcelona (where it was clustered with secondary aerosols). Despite their typically dominant coarse grain-size distribution, mineral and marine aerosols were clearly observed in PM_2.5. Multi-linear regression analysis (MLRA) was applied to the data, showing that traffic was the main source of PM_2.5 at the five sites (39–53% of PM_2.5, 5.1–12.0 μg m⁻³), while regional-scale secondary aerosols accounted for 14–34% of PM_2.5 (2.6–4.5 μg m⁻³), mineral matter for 13–31% (2.4–4.6 μg m⁻³) and sea-salt made up 3–7% of the PM_2.5 mass (0.4–1.3 μg m⁻³). Consequently, despite regional and climatic variability throughout Spain, the same four main PM_2.5 emission sources were identified at all the study sites and the differences between the relative contributions of each of these sources varied at most 20%. This would corroborate PM_2.5 as a useful parameter for health studies and environmental policy-making, owing to the fact that it is not as subject to the influence of micro-sitting as other parameters such as PM₁₀. African dust inputs were observed in the mineral source, adding on average 4–11 μg m⁻³ to the PM_2.5 daily mean during dust outbreaks. On average, levels of Al, Si, Ti and Fe during African episodes were higher by a factor of 2–8 with respect to non-African days, whereas levels of local pollutants (absorption coefficient, S, Pb, Cl) showed smaller variations (factor of 0.5–2).     

An analysis of seasonal surface dust aerosol concentrations in the western US (2001–2004): Observations and model predictions

Long-term surface observations indicate that soil dust represents over 30% of the annual fine (particle diameter less than 2.5 μm) particulate mass in many areas of the western US; in spring and summer, it represents an even larger fraction. There are numerous dust-producing playas in the western US, but surface dust aerosol concentrations in this region are also influenced by dust of Asian origin. This study examines the seasonality of surface soil dust concentrations at 15 western US sites using observations from the Interagency Monitoring of PROtected Visual Environments (IMPROVE) network from 2001 to 2004. Average soil concentrations in particulate matter less than 10 μm in diameter (PM₁₀) were lowest in winter and peaked during the summer months at these sites; however, episodic higher-concentration events (>10 μg m⁻³) occurred in the spring, the time of maximum Asian dust transport to the western US. Simulated surface dust concentrations from the Navy Aerosol Analysis and Prediction System (NAAPS) suggested that long-range transport from Asia dominates surface dust concentrations in the western US in the spring, and that, although some long-range transport does occur throughout the year (1–2 μg m⁻³), locally generated dust plays a larger role in the region in summer and fall. However, NAAPS simulated some anomalously high concentrations (>50 μg m⁻³) of local dust in the fall and winter months over portions of the western US. Differences between modeled and observed dust concentrations were attributed to overestimation of total observed soil dust concentrations by the assumptions used to convert IMPROVE measurements into PM₁₀ soil concentrations, lack of inhibition of model dust production in snow-covered regions, and lack of seasonal agricultural sources in the model.     

Commuter exposure to particulate matter in public transportation modes in Hong Kong

This study examined commuter’s exposure to respirable suspended particulate matters while commuting in public transportation modes. The survey was conducted between October 1999 and January 2000 in Hong Kong. A total of eight public transportation modes, that are bus, tram, public light bus, taxi, ferry, Kowloon–Canton Railway, Mass Transit Railway and Light Rail Transit, were selected in the study. They were grouped into four categories: (T1) railway transport; (T2) non-air-conditioned roadway transport; (T3) air-conditioned roadway transport and (T4) marine transport. Both PM₁₀ and PM_2.5 levels were investigated. The results indicate that the particulate level is greatly affected by the mode of transport as well as the ventilation system of the transport. The overall average PM₁₀ concentration level in T2 (147 μg m⁻³) is the highest and is followed by T4 (81 μg m⁻³) and T3 (65 μg m⁻³). The PM₁₀ level in T1 (50 μg m⁻³) is the lowest. Notably, the commuter exposure in tram (175 μg m⁻³) is the highest among all the monitored commuting modes. Commuting modes such as railway and air-conditioned vehicle are recommended as a substitute for non-air-conditioned vehicle. The PM_2.5 to PM₁₀ ratio in transports ranged from 63% to 78%. Higher PM_2.5 to PM₁₀ ratio is found in vehicles with air-conditioning system. For the double deck vehicle, higher PM₁₀ level has resulted in the lower deck. The average upper-deck to lower-deck PM₁₀ ratio is 0.836, 0.751 and 0.738 in air-conditioned bus, non-air-conditioned bus and non-air-conditioned tram, respectively. Typical concentration profiles in different transports are also presented.     

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.     

Field performance of dichotomous sequential PM air samplers

For over one year, the Environmental Protection Commission of Hillsborough County (EPCHC) in Tampa, Florida, operated two dichotomous sequential particulate matter air samplers collocated with a manual Federal Reference Method (FRM) air sampler at a waterfront site on Tampa Bay. The FRM was alternately configured as a PM_2.5, then as a PM₁₀ sampler. For the dichotomous sampler measurements, daily 24-h integrated PM_2.5 and PM_10–2.5 ambient air samples were collected at a total flow rate of 16.7 l min⁻¹. A virtual impactor split the air into flow rates of 1.67 and 15.0 l min⁻¹ onto PM_10–2.5 and PM_2.5 47-mm diameter PTFE^® filters, respectively. Between the two dichotomous air samplers, the average concentration, relative bias and relative precision were 13.3 μg m⁻³, 0.02% and 5.2% for PM_2.5 concentrations (n=282), and 12.3 μg m⁻³, 3.9% and 7.7% for PM_10–2.5 concentrations (n=282). FRM measurements were alternate day 24-h integrated PM_2.5 or PM₁₀ ambient air samples collected onto 47-mm diameter PTFE^® filters at a flow rate of 16.7 l min⁻¹. Between a dichotomous and a PM_2.5 FRM air sampler, the average concentration, relative bias and relative precision were 12.4 μg m⁻³, −5.6% and 8.2% (n=43); and between a dichotomous and a PM₁₀ FRM air sampler, the average concentration, relative bias and relative precision were 25.7 μg m⁻³, −4.0% and 5.8% (n=102). The PM_2.5 concentration measurement standard errors were 0.95, 0.79 and 1.02 μg m⁻³; for PM₁₀ the standard errors were 1.06, 1.59, and 1.70 μg m⁻³ for two dichotomous and one FRM samplers, respectively, which indicate the dichotomous samplers have superior technical merit. These results reveal the potential for the dichotomous sequential air sampler to replace the combination of the PM_2.5 and PM₁₀ FRM air samplers, offering the capability of making simultaneous, self-consistent determinations of these particulate matter fractions in a routine ambient monitoring mode.     

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.     

Aerosol scattering properties in northern China

The aerosol scattering properties were investigated at two continental sites in northern China in 2004. Aerosol light scattering coefficient (σ_sp) at 525 nm, PM₁₀, and aerosol mass scattering efficiencies (α) at Dunhuang had a mean value of 165.1±148.8 M m⁻¹, 157.6±270.0 μg m⁻³, and 2.30±3.41 m² g⁻¹, respectively, while these values at Dongsheng were, respectively, 180.2±151.9 M m⁻¹, 119.0±112.9 μg m⁻³, and 1.87±1.41 m² g⁻¹. There existed a seasonal variability of aerosol scattering properties. In spring, at Dunhuang PM₁₀, σ_sp, and α were 184.1±211.548 μg m⁻³, 126.3±89.6 M m⁻¹, and 1.05±0.97 m² g⁻¹, respectively, and these values at Dongsheng were 146.4±142.1 μg m⁻³, 183.4±81.7 M m⁻¹, and 1.98±1.52 m² g⁻¹, respectively. However, in winter at Dunhuang PM₁₀, σ_sp, and α were 158.1±261.4 μg m⁻³, 303.3±165.2 M m⁻¹, and 3.17±1.93 m² g⁻¹, respectively, and these values at Dongsheng were 155.7±170.1 μg m⁻³, 304.4±158.1 M m⁻¹, and 2.90±1.72 m² g⁻¹, respectively. σ_sp and α in winter were higher than that in spring at both the sites, which coincides with the characteristics of dust aerosol and pollution aerosol. Overall, the dominant aerosol types in spring and winter at both sites in northern China are dust aerosol and pollution aerosol, respectively.     

Characterisation of PM10 atmospheric aerosols for the wet season 2005 at two sites in East Africa

Ambient daily PM₁₀ aerosol samples were collected at two sites in Tanzania in May and June 2005 (during the wet season), and their chemical characteristics were studied. The sites were a rural site in Morogoro and an urban kerbside site in Dar es Salaam. A Gent PM₁₀ stacked filter unit sampler with sequential Nuclepore polycarbonate filters, providing fine and coarse size fractions, and a PM₁₀ sampler with quartz fibre filters were deployed. Parallel collections of 24 h were made with the two samplers and the number of these collections was 13 in Morogoro and 16 in Dar es Salaam. The average mass concentration of PM₁₀ was 27 ± 11 μg/m³ in Morogoro and 51 ± 21 μg/m³ in Dar es Salaam. In Morogoro, the mean concentrations of organic carbon (OC), elemental carbon (EC), and water-soluble organic carbon (WSOC) were 6.8, 0.51, and 2.8 μg/m³, respectively. In contrast, higher mean concentrations (11.9, 4.6, and 3.3 μg/m³, respectively) were obtained for Dar es Salaam. At both sites, species and elements, such as black carbon, NH₄⁺, non-sea-salt SO₄^2?, K, and Ni (and at Dar es Salaam also V, As, Br, and Pb) were mainly present in the fine size fraction. The common crustal and sea-salt elements, including Na, Mg, Al, Si, Cl, Ca, Ti, Mn, Fe, and Sr, and also NO₃^? and P (and to a lesser extent Cu and Zn) were concentrated in the coarse particles. Aerosol chemical mass closure indicated that the PM₁₀ mass in Morogoro consisted, on average, of 48% organic matter (OM), 44% crustal matter, 4% sea salt, and 2% EC, while in Dar es Salaam OM, crustal matter, sea salt, and EC represented 37%, 32%, 9%, and 9% of the PM₁₀ mass. The contributions of the secondary inorganic aerosol (non-sea-salt sulphate, nitrate, and ammonium) were small, i.e., only 5% in total at each site. Carbonaceous materials and crustal matter were thus the most important components of the PM₁₀ mass. It is suggested that biomass burning is a major contributor to the OM; at Dar es Salaam there is also a very substantial contribution from traffic. A source apportionment calculation indicated that 68% of the OC at this site originated from traffic exhaust versus 32% from charcoal burning. The crustal matter at Morogoro is likely mainly attributable to soil dust resuspension, whereas in Dar es Salaam it is likely mostly resuspended road dust.     

PM2.5 particles and size-segregated ionic species measured during fall season in three urban sites in Korea

Twelve hours integrated fine particles (PM_2.5) and 24-h average size-segregated particles were collected to investigate the chemical characteristics and to determine the size distribution of ionic species during October–December 1999 in three cities of different urban scale; Chongju, Kwangju, and Seoul, Korea. Concentrations of 5-min PM_2.5 black carbon (BC) and hourly criteria air pollutants (PM₁₀, CO, NO_x, SO₂, and O₃) were also measured using the Aethalometer and ambient air monitoring system, respectively.Highest PM_2.5 mass concentrations at Chongju, Kwangju, and Seoul sites were 63.0, 77.9, and 143.7 μg m⁻³, respectively. For the time period when highest PM_2.5 mass occurred, BC level out of PM_2.5 chemical species was highest at both Chongju and Kwangju, and highest NO₃⁻ (23.6 μg m⁻³) followed by BC (23.1 μg m⁻³) were observed at Seoul site, indicating that highest PM_2.5 pollution is closely associated with the traffic emissions. Strong relationships of Fe with BC and Zn at both Kwangju and Seoul sites support that the Fe and Zn measured there are originated partly from same source as BC, i.e. diesel traffics. However, it is suggested that the Fe measured at Chongju is most likely derived from dispersion of soil dust.The size distributions of SO₄²⁻, NO₃⁻, and NH₄⁺ ionic species indicated similar unimodal distributions at all sampling sites. However, different unimodal patterns in the accumulation mode size range with a peak in the smaller size (0.28–0.53 μm, condensation mode) in both Kwangju and Seoul, and in the relatively larger size (0.53–1.0 μm, droplet mode) in Chongju, were found. The potassium ion under the study sites dominates in the fine mode, and its size distribution showed unimodal character with a maximum in the size range 0.56–1.0 μm.     

Chemical composition of aerosols during a major biomass burning episode over northern Europe in spring 2006: Experimental and modelling assessments

The long-range transported smokes emitted by biomass burning had a strong impact on the PM_2.5 mass concentrations in Helsinki over the 12 days period in April and May 2006. To characterize aerosols during this period, the real-time measurements were done for PM_2.5, PM_2.5–10, common ions and black carbon. Moreover, the 24-h PM₁ filter samples were analysed for organic and elemental carbon (OC and EC), water-soluble organic carbon (WSOC), ions and levoglucosan. The Finnish emergency and air quality modelling system SILAM was used for the forecast of the PM_2.5 concentration generated by biomass burning. According to the real-time PM_2.5 data, the investigated period was divided into four types of PM situations: episode 1 (EPI-1; 25–29 April), episode 2 (EPI-2; 1–5 May), episode 3 (EPI-3; 5–6 May) and a reference period (REF; 24 March–24 April). EPI-3 included a local warehouse fire and therefore it is discussed separately. The PM₁ mass concentrations of biomass burning tracers—levoglucosan, potassium and oxalate—increased during the two long-range transport episodes (EPI-1 and EPI-2). The most substantial difference between the episodes was exhibited by the sulphate concentration, which was 4.9 (±1.4) μg m⁻³ in EPI-2 but only 2.4 (±0.31) μg m⁻³ in EPI-1 being close to that of REF (1.8±0.54 μg m⁻³). The concentration of particulate organic matter in PM₁ was clearly higher during EPI-1 (11±3.3 μg m⁻³) and EPI-2 (9.7±4.0 μg m⁻³) than REF (1.3±0.45 μg m⁻³). The long-range transported smoke had only a minor impact on the WSOC-to-OC ratio. According to the model simulations, MODIS detected the fires that caused the first set of concentration peaks (EPI-1) and the local warehouse fire (EPI-3), but missed the second one (EPI-2) probably due to dense frontal clouds.