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.     

Characterisation of fresh particulate vehicular exhausts near a Paris high flow road

Simultaneous continuous measurements of PM_2.5, PM₁₀, black carbon mass (BCae), Black smoke (BS) and particle number density (N) were conducted in the close vicinity of a high traffic road around Paris during a three-month period beginning in August 1997. In parallel some aerosol collection was performed on filters in order to assess the black carbon (BC), organic carbon (OC) and water soluble organic fractions (WSOC) of the freshly emitted traffic aerosols. The high hourly concentrations of PM_2.5 (39±20 μg m⁻³), BCae (14±7 μg m⁻³), and N (220,000±115,000 cm⁻³), were found to be well correlated with each other. On average PM_2.5 represented 66±13% of PM₁₀ and appears to be composed primarily of BC (43±20%). On the contrary no correlation was found between PM_2.5 and the coarse (PM₁₀–PM_2.5) mass fractions which was attributed to resuspension processes by vehicles. Black carbon mass concentrations obtained from both filter analyses (BC) and Aethalometre data (BCae) show a good agreement suggesting that the Aethalometre calibration based on a black carbon specific attenuation coefficient (σ) of 19 m² g⁻¹ is well adapted to nearby roadside measurements. Daily BC (used as a surrogate for fine particles) concentrations and wind speed were found to be anti-correlated. Average daily variations of BC could be related to traffic intensity and regime as well as to the boundary layer height. As expected for freshly emitted traffic aerosols, filter analyses indicated a high BC/TC ratio (29±5%) and a low mean WSOC/OC ratio (12.5±5%) for the bulk aerosol. For these two ratios no day/night differences were observed, the sampling station being probably too close to traffic to evidence photochemical modification of the aerosol phase. Finally, a linear relationship was found between BC and BS hourly concentrations (BC=0.10×BS+1.18; r²=0.93) which offers interesting perspectives to retrieve BC concentrations from existing BS archives.     

Assessment of air quality benefits from national air pollution control policies in China. Part II: Evaluation of air quality predictions and air quality benefits assessment

Following the meteorological evaluation in Part I, this Part II paper presents the statistical evaluation of air quality predictions by the U.S. Environmental Protection Agency (U.S. EPA)’s Community Multi-Scale Air Quality (Models-3/CMAQ) model for the four simulated months in the base year 2005. The surface predictions were evaluated using the Air Pollution Index (API) data published by the China Ministry of Environmental Protection (MEP) for 31 capital cities and daily fine particulate matter (PM_2.5, particles with aerodiameter less than or equal to 2.5 μm) observations of an individual site in Tsinghua University (THU). To overcome the shortage in surface observations, satellite data are used to assess the column predictions including tropospheric nitrogen dioxide (NO₂) column abundance and aerosol optical depth (AOD). The result shows that CMAQ gives reasonably good predictions for the air quality.The air quality improvement that would result from the targeted sulfur dioxide (SO₂) and nitrogen oxides (NO_x) emission controls in China were assessed for the objective year 2010. The results show that the emission controls can lead to significant air quality benefits. SO₂ concentrations in highly polluted areas of East China in 2010 are estimated to be decreased by 30–60% compared to the levels in the 2010 Business-As-Usual (BAU) case. The annual PM_2.5 can also decline by 3–15 μg m^?3 (4–25%) due to the lower SO₂ and sulfate concentrations. If similar controls are implemented for NO_x emissions, NO_x concentrations are estimated to decrease by 30–60% as compared with the 2010 BAU scenario. The annual mean PM_2.5 concentrations will also decline by 2–14 μg m^?3 (3–12%). In addition, the number of ozone (O₃) non-attainment areas in the northern China is projected to be much lower, with the maximum 1-h average O₃ concentrations in the summer reduced by 8–30 ppb.     

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.     

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.     

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.     

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.     

Study of aluminium distribution and speciation in atmospheric particles of different diameters in Nanjing,China

Aluminium (Al) is one of the trace inorganic metals present in atmospheric particles. Al speciation study is essential to better evaluate the mobility, availability, and persistence of trace Al and Al species in the atmosphere. This paper reports Al distribution and speciation in atmospheric particles with aerodynamic diameters >10.0, 10.0–2.5 and <2.5 μm in the urban area of Nanjing, China. Urban particles were collected with a high-volume sampling system equipped with a cascade impactor, which effectively separates the particulate matter into three size ranges. Particulate Al was fractionated into five different forms (insoluble, oxide, organic, carbonate, and exchangeable species) by the modified five-step Tessier's sequential extraction procedure. The main points are as follows: (1) The average levels of Al in PM_2.5, PM_2.5–10 and PM_>10 are 2.02±0.35, 3.04±0.43 and 6.32±0.76 μg m⁻³, respectively, with PM_2.5, PM_2.5–10 and PM_>10 constituting respectively, 17.8±3.1%, 26.7±3.8% and 55.5±6.7% of suspended particulate matter (SPM) mass (11.38 μg m⁻³). (2) The vertical profile of airborne Al in the above three size fractions has been estimated. A significant increase in airborne Al concentrations was found for PM_2.5, PM_2.5–10 and PM_>10 as the sampling height above the ground increased from 2.5 to 17.5 m; however, there was an obvious decrease in airborne Al concentrations between 17.5 and 40.0 m. The maximum mean of total Al in PM_2.5, PM_2.5–10 and PM_>10 occurred between 12.5 and 20.0 m above the ground. (3) The distribution of Al speciation was studied. It was found that the size distribution of airborne Al species followed the order: insoluble species>oxide species>organic species>carbonate species>exchangeable species.     

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.     

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.     

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).     

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.     

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.     

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.     

Estimation of wind blown dust emissions in Europe and its vicinity

The assessment of the wind blown dust emission for Europe and selected regions of North Africa and Southwest Asia was carried out using a mesoscale model. The mesoscale model was parameterized based on the current literature review. The model provides data on PM₁₀ emission from several dust reservoirs (anthropogenic, agriculture, semi- and natural) with spatial resolution of 10 × 10 km and temporal resolution of 1 h. The spatial variability of PM₁₀ emission depends on soil texture, land cover/land use as well as meteorological conditions. Lands covered with water or permanently wet were excluded from the model. The land covered with vegetation is treated as dust reservoir whose dust emission capacity depends on the type of vegetation and cover. The dust reservoirs are divided into reservoirs with stable and unstable surface. The changes of emission in time depend on meteorological parameters.The wind blown dust emission should be treated as a non-continuous spatio-temporal process. The emissions are estimated with high uncertainty. The estimated PM₁₀ yearly total load emitted by wind from the European territory is highly differentiated in space and time and is equal to 0.74 Tg. The total load of PM₁₀ emitted by wind from North African and Southwest Asian land surface located in the vicinity of European boundaries is assessed as nearly 50% (0.43 Tg) of the total load estimated for the whole Europe.The average yearly PM₁₀ emission factor for Europe was estimated at 0.139 Mg km^?2.The PM₁₀ emission from agricultural areas is estimated at 52% of the total wind blown emission from the domain of the European Union project “Improving and applying methods for the calculation of natural and biogenic emissions and assessment of impacts to the air quality” - NatAir.PM₁₀ emission factor for natural areas of Europe is estimated at 0.021 Mg km^?2. Appropriate factors for agricultural areas and anthropogenic areas are 0.157 Mg km^?2 and 0.118 Mg km^?2, respectively. The latter two factors are probably underestimated due to omitting in the model of other dust emission mechanisms than aeolian erosion.     

Quantifying the effect of urban tree planting on concentrations and depositions of PM10 in two UK conurbations

Trees are efficient scavengers of particulate matter and are characterised by higher rates of dry deposition than other land types. To estimate the potential of urban tree planting for the mitigation of urban PM₁₀ concentrations, an atmospheric transport model was used to simulate the transport and deposition of PM₁₀ across two UK conurbations (the West Midlands and Glasgow). Tree planting was simulated by modifying the land cover database, using GIS techniques and field surveys to estimate reasonable planting potentials. The model predicts that increasing total tree cover in West Midlands from 3.7% to 16.5% reduces average primary PM₁₀ concentrations by 10% from 2.3 to 2.1 μg m⁻³ removing 110 ton per year of primary PM₁₀ from the atmosphere. Increasing tree cover of the West Midlands to a theoretical maximum of 54% by planting all available green space would reduce the average PM₁₀ concentration by 26%, removing 200 ton of primary PM₁₀ per year. Similarly, for Glasgow, increasing tree cover from 3.6% to 8% reduces primary PM₁₀ concentrations by 2%, removing 4 ton of primary PM₁₀ per year. Increasing tree cover to 21% would reduce primary PM₁₀ air concentrations by 7%, removing 13 ton of primary PM₁₀ per year.     

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.     

Water-soluble organic nitrogen (WSON) in size-segregated atmospheric particles over the Eastern Mediterranean

Atmospheric water-soluble organic nitrogen (WSON) was determined on size-segregated aerosol particles collected during a two years period (2005–2006) in a remote marine location in the Eastern Mediterranean (Finokalia, Crete island). Average concentration of WSON was 5.5 ± 3.9 nmol m^?3 and 11.6 ± 14.0 nmol m^?3 for coarse (PM_1.3-10) and fine (PM_1.3) mode respectively, corresponding to 13% of Total Dissolved Nitrogen (TDN) in both modes. Air masses origin and correlation with tracers of natural and anthropogenic sources indicate that combustion process (biomass burning and fossil fuel) and African dust play an important role in regulating levels of WSON in both coarse and fine aerosol fractions. Chemical speciation of organic nitrogen pool was attempted by analyzing 47 fine aerosol samples (PM₁) for 17 free amino acids (N-FAA), dimethylamine (DMA) and trimethylamine (TMA). The average concentration of N-FAA was 0.5 ± 0.5 nmol m^?3, while the average concentration of DMA was 0.2 ± 0.8 nmol m^?3, TMA was below detection limit. The percentage contribution of N-FAA and DMA to WSON was 2.1 ± 2.3% and 0.9 ± 3.4%, respectively.     

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.