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.     

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.     

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.     

Estimation and validation of PM2.5/PM10 exhaust and non-exhaust emission factors for practical street pollution modelling

In order to carry out efficient traffic and air quality management, validated models and PM emission estimates are needed. This paper compares current available emission factor estimates for PM₁₀ and PM_2.5 from emission databases and different emission models, and validates these against eight high quality street pollution measurements in Denmark, Sweden, Germany, Finland and Austria.The data sets show large variation of the PM concentration and emission factors with season and with location. Consistently at all roads the PM₁₀ and PM_2.5 emission factors are lower in the summer month than the rest of the year. For example, PM₁₀ emission factors are in average 5–45% lower during the month 6–10 compared to the annual average.The range of observed total emission factors (including non-exhaust emissions) for the different sites during summer conditions are 80–130 mg km⁻¹ for PM₁₀, 30–60 mg km⁻¹ for PM_2.5 and 20–50 mg km⁻¹ for the exhaust emissions.We present two different strategies regarding modelling of PM emissions: (1) For Nordic conditions with strong seasonal variations due to studded tyres and the use of sand/salt as anti-skid treatment a time varying emission model is needed. An empirical model accounting for these Nordic conditions was previously developed in Sweden. (2) For other roads with a less pronounced seasonal variation (e.g. in Denmark, Germany, Austria) methods using a constant emission factor maybe appropriate. Two models are presented here.Further, we apply the different emission models to data sets outside the original countries. For example, we apply the “Swedish” model for two streets without studded tyre usage and the “German” model for Nordic data sets. The “Swedish” empirical model performs best for streets with studded tyre use, but was not able to improve the correlation versus measurements in comparison to using constant emission factors for the Danish side. The “German” method performed well for the streets without clear seasonal variation and reproduces the summer conditions for streets with pronounced seasonal variation. However, the seasonal variation of PM emission factors can be important even for countries not using studded tyres, e.g. in areas with cold weather and snow events using sand and de-icing materials. Here a constant emission factor probably will under-estimate the 90-percentiles and therefore a time varying emission model need to be used or developed for such areas.All emission factor models consistently indicate that a large part (about 50–85% depending on the location) of the total PM₁₀ emissions originates from non-exhaust emissions. This implies that reduction measures for the exhaust part of the vehicle emissions will only have a limited effect on ambient PM₁₀ levels.     

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.     

Definition of yearly emission factor of dust and greenhouse gases through continuous measurements in swine husbandry

The object of this study was to develop an accurate estimation method to evaluate the contribution of the various compartments of swine husbandry to dust and GHG (greenhouse gases, CO₂, CH₄ and N₂O) emission into the atmosphere during one year of observation.A weaning, a gestation, a farrowing and a fattening room in an intensive pig house were observed in three different periods (Autumn–Winter, Springtime and Summer, monitoring at least 60% of each period (20% at the beginning, in the middle and at the end) of each cycle).During monitoring, live weight, average live weight gain, number of animals and its variation, type of feed and feeding time were taken into account to evaluate their influence on PM₁₀, or the fraction of suspended particulate matter with an aerodynamic diameter less than or equal to 10 μm [Emission Inventory Guidebook, 2007. B1100 Particle Emissions from Animal Husbandry Activities. Available from: <http://reports.eea.europa.eu/EMEPCORINAIR5/en/B1100vs1.pdf> (accessed October 2008)] and to define GHG emission.The selected piggery had a ventilation control system using a free running impeller to monitor continuously real-time environmental and management parameters with an accuracy of 5%.PM₁₀ concentration was monitored by a sampler (Haz Dust EPAM 5000), either continuously or through traditional gravimetric technique, and the mean value of dust amount collected on the membranes was utilized as a correction factor to be applied to continuously collected data.PM₁₀ concentration amount incoming from inlets was removed from PM₁₀ emission calculation, to estimate the real contribution of pig house dust pollution into atmosphere.Mean yearly emission factor of PM₁₀ was measured in 2 g d^?1 LU^?1 for the weaning room, 0.09 g d^?1 LU^?1 for the farrowing room, 2.59 g d^?1 LU^?1 for the fattening room and 1.23 g d^?1 LU^?1 for the gestation room. The highest PM₁₀ concentration and emission per LU was recorded in the fattening compartment while the lowest value was recorded in the farrowing room.CO₂, CH₄ and N₂O concentrations were continuously measured in the exhaust ducts using an infrared photoacoustic detector IPD (Brüel & Kjaer, Multi-gas Monitor Type 1302, Multipoint Sampler and Doser Type 1303) sampling data every 15 min, for the 60% of the cycles.Yearly emission factor for CO₂ was measured in 5997 g d^?1 LU^?1 for the weaning room, 1278 g d^?1 LU^?1 for the farrowing room, 13,636 g d^?1 LU^?1 for the fattening room and 8851 g d^?1 LU^?1 for the gestation room.Yearly emission factor for CH₄ was measured in 24.57 g d^?1 LU^?1 for the weaning room, 4.68 g d^?1 LU^?1 for the farrowing room, 189.82 g d^?1 LU^?1 for the fattening room and 132.12 g d^?1 LU^?1 for the gestation room.Yearly emission factor for N₂O was measured in 3.62 g d^?1 LU^?1 for the weaning room, 0.66 g d^?1 LU^?1 for the farrowing room, 3.26 g d^?1 LU^?1 for the fattening room and 2.72 g d^?1 LU^?1 for the gestation room.     

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.     

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.     

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.     

Dispersion modelling of a wintertime particulate pollution episode in Christchurch,New Zealand

This paper examines the inter-suburb dispersion of particulate air pollution in Christchurch, New Zealand, during a wintertime particulate pollution episode. The dispersion is simulated using the RAMS/CALMET/CALPUFF modelling system, with data from a detailed emissions inventory of home heating, motor vehicles and industry. During the period 27 July–1 August 1995, peak 1 h and 24 h PM₁₀ concentrations of 368 and 107 μg m⁻³, respectively, were observed. Peak concentrations occurred at night, when particulate emissions from wood- and coal-burning domestic heating appliances were at a maximum and emitted into a stable boundary layer. The model is generally able to reproduce the observed PM₁₀ time series recorded at surface monitors located throughout the urban area. For this simulation, the fractional gross error ranges between 0.69 and 0.99, and the fractional bias ranges between −0.17 and 0.30. Strong horizontal concentration gradients of 100 μg m⁻³ km⁻¹, both in the observational record and model predictions, are apparent. Three emission reduction options, designed to reduce the severity of particulate pollution episodes in Christchurch, are simulated. When both domestic open-hearth fires and all coal burning are removed, the 24 h average peak concentration is reduced by 55%. The number of guideline exceedences of PM₁₀ in the modelled period is reduced from five to one. Removing open-hearth fires results in 42% reduction in PM₁₀ concentration, resulting in three exceedences of the guideline, and removing coal-burning fires yields a 32% reduction in PM₁₀, resulting in four exceedences of the guideline.     

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 emissions of primary biological aerosol particle mass in Europe

Atmospheric concentration measurements of tracers for primary biological aerosol particles (PBAPs) have been used to obtain estimates of their release into the atmosphere. Emission flux data of surrogate compounds, for which concurrent concentration measurements were available, were used to quantify the release of PBAPs as PM₁₀ mass. Results indicate fungal spores to be the most important contributors. One other main source is plant debris. Area-based emission rates of 24 kg km^?2 and year (range 6–90) have been assessed. Results scaled for Europe indicate a contribution of PBAPs to PM₁₀ concentrations in the low percentage range, with a maximum in summer when concentration levels are small. This is consistent with the range of measurements. Despite of the large uncertainties, results contribute to clarify the potential contribution of biological particles to global load of particle mass.     

Estimation and characterization of children’s ambient generated exposure to PM2.5 using sulphate and elemental carbon as tracers

Children’s exposures to ambient and non-ambient fine particulate matter (PM_2.5) were determined using the sulphate and elemental carbon components of the PM_2.5 mixture as tracers of the ambient contribution during a 6-week winter period in Prince George, British Columbia, Canada. Personal exposures to PM_2.5 were measured in children at 5 elementary schools located throughout the city and ambient samples were collected on school rooftops. Average ambient levels and personal exposures during this time period were 13.8 μg m^?3 and 16.4 μg m^?3 respectively. From the data pooled across individuals, use of the two different tracers indicated identical estimates of median exposure to ambient PM_2.5 (7.5 μg m^?3) and similar estimates of non-ambient generated exposure (6.4 and 5.0 μg m^?3) and infiltration (0.49 and 0.52) for the sulphate and elemental carbon approach, respectively. The median fraction of the ambient concentration resulting in exposure or exposure factors were 0.54 and 0.55 respectively, however lower values of 0.46 and 0.42 were determined from regression analysis. A strong association was found between exposure to ambient PM_2.5 and measured ambient concentrations at both the closest school monitor (median r = 0.92) and a central site (median r = 0.88) demonstrating that the central site monitor was suitable for assessing longitudinal ambient generated exposure throughout the city. These results support the use of elemental carbon as a tracer of ambient generated exposure and the use of ambient data as estimates of longitudinal changes in children’s exposure in this setting. The importance of both ambient and non-ambient sources of PM_2.5 is emphasized by their almost equal contribution to total personal exposures. Comparison with other studies suggests a limited influence of climate and the cold season in Prince George on exposure levels and found similar mean non-ambient generated exposures despite large variability across and within subjects in any given location.     

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.     

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.     

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.     

Physical characterization of aerosol particles during the Chinese New Year’s firework events

Measurements for particles 10 nm to 10 μm were taken using a Wide-range Particle Spectrometer during the Chinese New Year (CNY) celebrations in 2009 in Shanghai, China. These celebrations provided an opportunity to study the number concentration and size distribution of particles in an especial atmospheric pollution situation due to firework displays. The firework activities had a clear contribution to the number concentration of small accumulation mode particles (100–500 nm) and PM₁ mass concentration, with a maximum total number concentration of 3.8 × 10⁴ cm^?3. A clear shift of particles from nucleation and Aitken mode to small accumulation mode was observed at the peak of the CNY firework event, which can be explained by reduced atmospheric lifetimes of smaller particles via the concept of the coagulation sink. High particle density (2.7 g cm^?3) was identified as being particularly characteristic of the firework aerosols. Recalculated fine particles PM₁ exhibited on average above 150 μg m^?3 for more than 12 hours, which was a health risk to susceptible individuals. Integral physical parameters of firework aerosols were calculated for understanding their physical properties and further model simulation.     

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.     

Evaluating urban PM10 pollution benefit induced by street cleaning activities

Despite their burden in urban particulate air pollution, road traffic non-exhaust emissions are often uncontrolled and information about the effectiveness of mitigation measures on paved roads is still scarce. The present study is aimed to evaluate the effectiveness of mechanical sweeping/water flushing treatments in mitigating urban road dust resuspension and to quantify the real benefit in terms of ambient PM₁₀ concentrations. To this aim a specific campaign was carried out in a heavily trafficked central road of Barcelona (Spain), a Mediterranean city suffering from a traffic-related pollution, both for a high car density and a frequent lack of precipitation. Several street washings were performed by means of mechanical sweepers and pressure water during night in all traffic lanes and sidewalks. PM₁₀ levels were simultaneously compared with four reference urban background air quality stations to interpret any meteorological variability. At the downwind measurement site, PM₁₀ concentrations registered a mean daily decrease of 8.8 μg m^?3 during the 24 h after street washing treatments. However 3.7–4.9 μg m^?3 of such decrease were due to the meteorological variability detected at the upwind site, as well as at two of the reference sites. This reveals that an effective decrease of 4–5 μg m^?3 (7–10%) can be related to street washing efficiency. Mitigation of road dust resuspension was confirmed by investigating the chemical composition of airborne-PM₁₀ filters. Concentrations of Cu, Sb, Fe and mineral matter decrease significantly with respect to concentrations of elemental carbon, used as tracer for exhaust diesel emissions. High efficiency of street washing in reducing road dust loads was found by performing periodic samplings both on the treated and the untreated areas.     

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.