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.     

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.     

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.     

Airborne particle PM2.5/PM10 mass distribution and particle-bound PAH concentrations near a medical waste incinerator

This study attempts to determine the influence of air quality in a residential area near a medical waste incineration plant. Ambient air concentrations of polycyclic aromatic hydrocarbons (PAHs), PM₁₀ and PM_2.5 (PM—particulate matter) were determined by collecting air samples in areas both upwind and downwind of the plant. The differences in air pollutant levels between the study area and a reference area 11 km away from the plant were evaluated.Dichotomous samplers were used for sampling PM_2.5 and PM₁₀ from ambient air. Two hundred and twenty samples were obtained from the study area, and 100 samples were taken from a reference area. Samples were weighed by an electronic microbalance and concentrations of PM_2.5 and PM₁₀ were determined. A HPLC equipped with a fluorescence detector was employed to analyze the concentrations of 15 PAHs compounds adsorbed into PM_2.5 and PM₁₀.The experimental results indicated that the average concentrations of PM_2.5 and PM₁₀ were 30.34±17.95 and 36.81±20.45 μg m⁻³, respectively, in the study area, while the average ratio of PM_2.5/PM₁₀ was 0.82±0.01. The concentrations of PM_2.5 and PM₁₀ of the study area located downwind of the incinerator were significantly higher than the study area upwind of the incinerator (P<0.05).The concentration of PAHs in PM_2.5 in the study area was 2.2 times higher than in the reference area (P<0.05). Furthermore, the benzo(a)pyrene concentrations in PM_2.5 and PM₁₀ were 0.11±0.05 ng m⁻³ and 0.12±0.06 ng m⁻³ in the study area, respectively. The benzo(a)pyrene concentrations of PM_2.5 and PM₁₀ in the study area were 7 and 5.3 times higher than in the reference area (P<0.05), respectively.The study indicated that the air quality of PM_2.5, PM₁₀ and PAHs had significant contamination by air pollutants emitted from a medical waste incineration factory, representing a public health problem for nearby residences, despite the factory being equipped with a modern air pollution control system.     

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.     

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.     

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).     

PM2.5–10, PM2.5 and associated water-soluble inorganic species at a coastal urban site in the metropolitan region of Rio de Janeiro

The concentrations of PM_2.5−10, PM_2.5 and associated water-soluble inorganic species (WSIS) were determined in a coastal site of the metropolitan region of Rio de Janeiro, Southeastern Brazil, from October 1998 to September 1999 (n=50). Samples were dissolved in water and analyzed for major inorganic ions. The mean (± standard deviation; median) concentrations of PM_2.5−10 and PM_2.5 were, respectively, 26 (± 16; 21) μg m⁻³ and 17 (± 13; 14) μg m⁻³. Their mean concentrations were 1.7–1.8 times higher in dry season (May–October) than in rainy season (November–April). The WSIS comprised, respectively, 34% and 28% of the PM_2.5−10 and PM_2.5 masses. Chloride, Na⁺ and Mg²⁺ were the predominant ions in PM_2.5−10, indicating a significant influence of sea-salt aerosols. In PM_2.5, SO₄²⁻ (∼97% nss-SO₄²⁻) and NH₄⁺ were the most abundant ions and their equivalent concentration ratio (SO₄²⁻/NH₄⁺ ∼1.0) suggests that they were present as (NH₄)₂SO₄ particles. The mean concentration of (NH₄)₂SO₄ was 3.4 μg m⁻³. The mean equivalent PM_2.5 NO₃⁻ concentration was eight times smaller than those of SO₄²⁻ and NH₄⁺. The PM_2.5 NO₃⁻ concentration in dry season was three times higher than in rainy season, probably due to reaction of NaCl (sea salt) with HNO₃ as a result of higher levels of NO_y during the dry season and/or reduced volatilization of NH₄NO₃ due to lower wintertime temperature. Chloride depletion was observed in both size ranges, although more pronouncely in PM_2.5.     

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.     

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.     

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.     

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.     

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.     

Receptor modeling of source apportionment of Hong Kong aerosols and the implication of urban and regional contribution

Understanding the spatial–temporal variations of source apportionment of PM_2.5 is critical to the effective control of particulate pollution. In this study, two one-year studies of PM_2.5 composition were conducted at three contrasting sites in Hong Kong from November 2000 to October 2001, and from November 2004 to October 2005, respectively. A receptor model, principal component analysis (PCA) with absolute principal component scores (APCS) technique, was applied to the PM_2.5 data for the identification and quantification of pollution sources at the rural, urban and roadside sites. The receptor modeling results identified that the major sources of PM_2.5 in Hong Kong were vehicular emissions/road erosion, secondary sulfate, residual oil combustion, soil suspension and sea salt regardless of sampling sites and sampling periods. The secondary sulfate aerosols made the most significant contribution to the PM_2.5 composition at the rural (HT) (44 ± 3%, mean ± 1σ standard error) and urban (TW) (28 ± 2%) sites, followed by vehicular emission (20 ± 3% for HT and 23 ± 4% for TW) and residual oil combustion (17 ± 2% for HT and 19 ± 1% for TW). However, at the roadside site (MK), vehicular emissions especially diesel vehicle emissions were the major source of PM_2.5 composition (33 ± 1% for diesel vehicle plus 18 ± 2% for other vehicles), followed by secondary sulfate aerosols (24 ± 1%). We found that the contribution of residual oil combustion at both urban and rural sites was much higher than that at the roadside site (2 ± 0.4%), perhaps due to the marine vessel activities of the container terminal near the urban site and close distance of pathway for the marine vessels to the rural site. The large contribution of secondary sulfate aerosols at all the three sites reflected the wide influence of regional pollution. With regard to the temporal trend, the contributions of vehicular emission and secondary sulfate to PM_2.5 showed higher autumn and winter values and lower summer levels at all the sites, particularly for the background site, suggesting that the seasonal variation of source apportionment in Hong Kong was mainly affected by the synoptic meteorological conditions and the long-range transport. Analysis of annual patterns indicated that the contribution of vehicular emission at the roadside was significantly reduced from 2000/01 to 2004/05 (p < 0.05, two-tail), especially the diesel vehicular emission (p < 0.001, two-tail). This is likely attributed to the implementation of the vehicular emission control programs with the tightening of diesel fuel contents and vehicular emission standards over these years by the Hong Kong government. In contrast, the contribution of secondary sulfate was remarkably increased from 2001 to 2005 (p < 0.001, two-tail), indicating a significant growth in regional sulfate pollution over the years.     

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.     

Characterization of fine primary biogenic organic aerosol in an urban area in the northeastern United States

Scanning electron microscopy coupled to energy-dispersive x-ray spectroscopy (SEM/EDX) was used to quantify individual bioparticles in PM_2.5 samples collected during the Pittsburgh Air Quality Study. Microscopy-based estimates of primary biogenic organic aerosol (PBOA) mass were compared to carbohydrate mass associated with PM_2.5. Carbohydrates show substantial seasonal variations, with higher concentrations in the spring and the fall. During the summer, carbohydrates were about 30% of the estimated PBOA concentrations, but in the winter carbohydrate concentrations often greatly exceeded the PBOA mass estimate. Spores and insect detritus were the most abundant PBOA types in the summer samples, while winter samples were comprised predominantly of a mixture of microorganisms, insect and vegetative detritus. During the summer PBOA contributed on average 6.9 ± 5.4% by mass of the PM_2.5 versus 3.3 ± 1.4% of the PM_2.5 mass during the winter.     

Seasonal and shorter-term variations in particulate atmospheric nitrate in Baltimore

Fine particle nitrate concentrations were measured at 10-min intervals for approximately 9.5 months beginning on 14 February 2002, at the Baltimore Supersite Ponca St. location using an R&P 8400N semi-continuous monitor. The measurement results were used to characterize seasonal and shorter-term excursions in nitrate concentrations and determine their influence on PM_2.5 concentrations. Over the 9.5-month study period, nitrate levels of 1.7±1.6 μg m⁻³ accounted for 11.4% of the PM_2.5 mass. Monthly averages ranged from 0.8 μg m⁻³ in August to 2.9 μg m⁻³ in November, and accounted for 4.7–17.3% of monthly PM_2.5 mass. Hourly averages, however, were often larger, especially in the colder months, owing to numerous relatively short-term transients, where hourly nitrate concentrations exceeded 5.0 μg m⁻³. These often occurred along with NO_x and ultrafine particle transients during the morning commute hours.A total of 275 short-term transients (31.7% of the total) exceeding 1.0 μg m⁻³ were identified. These were associated with one of three sets of conditions. The first, most typical (177, i.e. 64.4% of the 275 incidences), is characterized by high NO_x typically between 0500 and 0800EST and is attributed to early morning commute traffic activity. The second type occurred during the afternoon due to photochemical activity. The excursions in the afternoon occurred infrequently (only 9.5% of all the observed transients) during the study period and were characterized by less elevated nitrate concentrations than morning and nighttime transients. The third (72, i.e. 26.2% of the 275 transients) occurred at night, typically between 2000EST and 0200EST.Multiple linear regression analysis between nitrate excursions and volume size distributions indicates that particulate nitrate observed is closely related to the near accumulation (0.1–0.2 μm) and droplet modes (0.5–1.0 μm) in the morning hours, and associated with the droplet (0.5–1.0 μm) and coarse modes (1.0–2.5 μm) for nighttime transients, suggesting that processes governing particulate nitrate formation depend on time-of-day.     

Concentrations of ultrafine,fine and PM2.5 particles in three European cities

Total number concentrations, number concentrations of ultrafine (0.01–0.1 μm) and accumulation (0.1–0.5 μm) particles, as well as mass concentration of PM_2.5 particles and blackness of PM_2.5 filters, which is related to Black Smoke were simultaneously monitored in three European cities during the winter period for three and a half months. The purpose of the study was to describe the differences in concentration levels and daily and diurnal variations in particle number and mass concentrations between European cities. The results show statistically significant differences in the concentrations of PM_2.5 and the blackness of the PM_2.5 filters between the cities, but not in the concentrations of ultrafine particles. Daily PM_2.5 levels were found to be poorly correlated with the daily total and ultrafine number concentrations but better correlated with the number concentration of accumulation particles. According to the principal component analysis airborne particulate pollutants seem to be divided into two major source categories, one identified with particle number concentrations and the other related to mass-based information. The present results underline the importance of using both particle number and mass concentrations to evaluate urban air quality.     

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.     

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.