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.     

Using a dispersion model to estimate emission rates of particulate matter from paved roads

From January 1996 to June 1997, we carried out a series of measurements to estimate emissions of PM₁₀ from paved roads in Riverside County, California. The program involved the measurement of upwind and downwind vertical profiles of PM₁₀, in addition to meteorological variables such as wind speed and vertical turbulent intensity. This information was analyzed using a new dispersion model that incorporates current understanding of micrometeorology and dispersion. The emission rate was inferred by fitting model predictions to measurements. The inferred emission factors ranged from 0.2 g VKT^-1 for freeways to about 3 g VKT^-1 for city roads. The uncertainty in these factors is estimated to be approximately a factor of two since the contributions of paved road PM₁₀ emissions to ambient concentrations were comparable to the uncertainty in the mean value of the measurement. At this stage, our best estimate of emission factor lies between 0.1 and 10 g VKT^-1; there is some indication that it is about 0.1 g VKT^-1 for heavily traveled freeways, and is an order of magnitude higher for older city roads. We found that measured silt loadings were poor predictors of emission factors.The measured emission factors imply that paved road emissions may contribute about 30% to the total PM₁₀ emissions from a high traffic area such as Los Angeles. This suggests that it is necessary to develop methods that are more reliable than the upwind–downwind concentration difference technique.     

Factors influencing PM10 emissions from road pavement wear

Accelerated pavement wear is one of the major environmental disadvantages of studded tyres in northern regions and results in increased levels of PM₁₀. Measurements of PM₁₀ in a road simulator hall have been used to study the influence of pavement properties, tyre type and vehicle speed on pavement wear. The test set-up included three different pavements (one granite and two quartzite with different aggregate sizes), three different tyre types (studded, non-studded, and summer tyres) and different speeds (30–70 km h^?1). The results show that the granite pavement was more prone to PM₁₀ production compared to the quartzite pavements. Studded winter tyres yield tens of times higher PM₁₀ concentrations compared to non-studded winter tyres. Wear from summer tyres was negligible in comparison. It was also shown that wear is strongly dependent on speed; every 10 km h^?1 increase yielded an increase of the PM₁₀ concentration of 680 μg m^?3 in one of the simulator experiments.     

Modelling base cations in Europe—sources,transport and deposition of calcium

The deposition of the base cations calcium, magnesium and potassium from the atmosphere needs to be quantified in the calculation of the total deposited acidity in the critical loads approach. Of these base cations, calcium has been found to be the most important in terms of mass deposited. However, the sources of calcium to the atmosphere are not well understood. Recently, the first spatially disaggregated inventory of industrial calcium emissions for Europe was presented by Lee and Pacyna (1998) who estimated a total European emission of 0.7–0.8 Mt yr^-1. However, it is thought that wind blown dust from soils contributes a substantial fraction to the deposition of calcium. In this work, the source strength of calcium from arid regions within the EMEP modelling domain was estimated using the global mineral dust emission data base of Tegen and Fung (1994) and an estimation of the calcium content of soils. This results in a “natural” calcium emission of 6 Mt yr^-1. A long-range transport model, TRACK, was used to calculate the wet and dry deposition of calcium arising from these industrial and natural sources to the UK which resulted in a total deposition of 29–30 kt yr^-1. Of this annual deposition, 0.6–0.7 kt arises from cement manufacturing, 0.02–0.03 kt from iron and steel manufacturing, 0.8–0.83 kt from a large point source power generation, and 28 kt from power generation from a small boiler plant. The natural emissions of calcium from arid regions result in a deposition of calcium to the UK of 0.5 kt yr^-1. The measured wet deposition of calcium to the UK is 89 kt yr^-1 and the estimated dry deposition 14 kt yr^-1. The short-fall in the modelled deposition of calcium is thus of the order of 70 kt yr^-1, which is suggested to arise from wind-blown dust from agricultural land in the UK and mainland Europe. The estimated emissions, and thus modelled deposition are rather uncertain, such that estimating deposition of calcium attributable to agricultural soil emissions by differencing has a large uncertainty. However, this is the first such study of its kind for Europe and represents a first step towards understanding the sources of calcium and their contribution to mitigating deposited acidity from acidifying pollutants such as sulphur dioxide, nitrogen oxides and ammonia.     

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.     

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.     

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.     

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.     

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).     

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.     

Lidar-assisted measurement of PM10 emissions from agricultural tilling in California's San Joaquin Valley – Part II: emission factors

Emission factors for agricultural operations are needed in order to develop reliable PM₁₀ emissions inventories and air quality models for air basins with significant agricultural land use. A framework was developed to analyze the PM₁₀ vertical profiles collected downwind of tilling operations in the San Joaquin Valley. The methods calculate emission factors on the basis of profile shape and assign quality ratings to each land preparation test. Uncertainties in the calculated emission factors and plume heights were used as one criterion for evaluating the relative quality of the reported emission factor. Other quality ratings were based on the magnitude of the difference in measured up- and downwind concentrations, wind direction, whether the tests were conducted near the edges of the field, and how well the proposed model fit the profile data. The emission factors from different operations were compared taking the quality of the emission factor into account. Plume heights and emission factors for 24 valid test profiles ranged from 2 to 20 m (mean=9.8; SD=3.6; median=9.8) and zero to 800 mg m⁻² (mean=152; SD=240; median=43), respectively. Key environmental properties governing PM₁₀ emission from these operations include relative humidity, soil moisture and vertical temperature gradient. Surprisingly, no discernable relationships were found between implement type or wind speed and the measured emission factors.     

Establishment of a database of emission factors for atmospheric pollutants from Chinese coal-fired power plants

Field measurements and data investigations were conducted for developing an emission factor database for inventories of atmospheric pollutants from Chinese coal-fired power plants. Gaseous pollutants and particulate matter (PM) of different size fractions were measured using a gas analyzer and an electric low-pressure impactor (ELPI), respectively, for ten units in eight coal-fired power plants across the country. Combining results of field tests and literature surveys, emission factors with 95% confidence intervals (CIs) were calculated by boiler type, fuel quality, and emission control devices using bootstrap and Monte Carlo simulations. The emission factor of uncontrolled SO₂ from pulverized combustion (PC) boilers burning bituminous or anthracite coal was estimated to be 18.0S kg t^?1 (i.e., 18.0 × the percentage sulfur content of coal, S) with a 95% CI of 17.2S–18.5S. NO_X emission factors for pulverized-coal boilers ranged from 4.0 to 11.2 kg t^?1, with uncertainties of 14–45% for different unit types. The emission factors of uncontrolled PM_2.5, PM₁₀, and total PM emitted by PC boilers were estimated to be 0.4A (where A is the percentage ash content of coal), 1.5A and 6.9A kg t^?1, respectively, with 95% CIs of 0.3A–0.5A, 1.1A–1.9A and 5.8A–7.9A. The analogous PM values for emissions with electrostatic precipitator (ESP) controls were 0.032A (95% CI: 0.021A–0.046A), 0.065A (0.039A–0.092A) and 0.094A (0.0656A–0.132A) kg t^?1, and 0.0147A (0.0092–0.0225A), 0.0210A (0.0129A–0.0317A), and 0.0231A (0.0142A–0.0348A) for those with both ESP and wet flue-gas desulfurization (wet-FGD). SO₂ and NO_X emission factors for Chinese power plants were smaller than those of U.S. EPA AP-42 database, due mainly to lower heating values of coals in China. PM emission factors for units with ESP, however, were generally larger than AP-42 values, because of poorer removal efficiencies of Chinese dust collectors. For units with advanced emission control technologies, more field measurements are needed to reduce emission factor uncertainties.     

Modelling long-range transport of primary particulate material over Europe

This paper uses a simple model of atmospheric transport and an emissions inventory prepared by TNO to estimate the contribution of primary particulate material to PM₁₀ and PM_2.5 concentration across Europe. The resulting population exposure is compared with that of secondary particulates, and it is noted that both primary and secondary contributions will be significantly reduced with the implementation of new protocols under the Convention on Long-Range Transboundary Air Pollution (CLRTAP). Since concentrations of primary PM₁₀ can become elevated in episodic situations, when long-range transport of particulate could, on its own, exceed 24 h average targets of 50 μg m⁻³ over large areas of Europe, such reduction is important for achievement of current air quality standards to control exposure to atmospheric particulate PM₁₀.     

Estimating PM10 air concentrations from dust storms in Iraq,Kuwait and Saudi Arabia

A model for the emission of PM₁₀ dust has been constructed using the concept of a threshold friction velocity which is dependent on surface roughness. Surface roughness in turn was correlated with geomorphology or soil properties for Kuwait, Iraq, part of Syria, Saudi Arabia, the United Arab Emirates and Oman. The PM₁₀ emission algorithm was incorporated into a Lagrangian transport and dispersion model. PM₁₀ air concentrations were computed from August 1990 through August 1991. The model predicted about the right number of dust events over Kuwait (events occur 18% of the time). The model results agreed quantitatively with measurements at four locations in Saudi Arabia and one in Kuwait for one major dust event (>1000 μg/m³). However, for smaller scale dust events (200–1000 μg/m³), especially at the coastal sampling locations, the model substantially over-predicted the air concentrations. Part of the over-prediction was attributed to the entrainment of dust-free air by the sea breeze, a flow feature not represented by the large-scale gridded meteorological data fields used in the model computation. Another part of the over-prediction was the model's strong sensitivity to threshold friction velocity and the surface soil texture coefficient (the soil emission factor), and the difficulty in accurately representing these parameters in the model. A comparison of the model predicted PM₁₀ spatial pattern with the TOMS satellite aerosol index (AI) yielded a spatial pattern covering a major portion of Saudi Arabia that was quite similar to the observed AI pattern.     

Comparison of measured and model-calculated real-world traffic emissions

The quality of an emission calculation model based on emission factors measured on roller test stands and statistical traffic data was evaluated using source strengths and emission factors calculated from real-world exhaust gas concentration differences measured upwind and downwind of a motorway in southwest Germany. Gaseous and particulate emissions were taken into account. Detailed traffic census data were taken during the measurements. The results were compared with findings of similar studies.The main conclusion is the underestimation of CO and NO_x source strengths by the model. On the average, it amounts to 23% in case of CO and 17% for NO_x. The latter underestimation results from an undervaluation by 22% of NO_x emission factors of heavy-duty vehicles (HDVs). There are significant differences between source strengths on working days and weekends because of the different traffic split between light-duty vehicles (LDVs) and HDVs. The mean emission factors of all vehicles from measurements are 1.08 g km⁻¹ veh⁻¹ for NO_x and 2.62 g km⁻¹ veh⁻¹ for CO. The model calculations give 0.92 g km⁻¹ veh⁻¹ for NO_x and 2.14 g km⁻¹ veh⁻¹ for CO.The source strengths of 21 non-methane hydrocarbon (NMHC) compounds quantified are underestimated by the model. The ratio between the measured and model-calculated emissions ranges from 1.3 to 2.1 for BTX and up to 21 for 16 other NMHCs. The reason for the differences is the insufficient knowledge of NMHC emissions of road traffic.Particulate matter emissions are dominated by ultra-fine particles in the 10–40 nm range. As far as aerosols larger than 29 nm are concerned, 1.80×10¹⁴ particles km⁻¹ veh⁻¹ are determined for all vehicles, 1.22×10¹⁴ particles km⁻¹ veh⁻¹ and an aerosol volume of 0.03 cm³ km⁻¹ veh⁻¹ are measured for LDVs, and for HDVs 7.79×10¹⁴ particles km⁻¹ veh⁻¹ and 0.41 cm³ km⁻¹ veh⁻¹ are calculated. Traffic-induced turbulence has been identified to have a decisive influence on exhaust gas dispersion near the source.     

Asian dust events observed by a 20-m monitoring tower in Mongolia during 2009

A 20-m Asian dust monitoring tower was installed at Erdene in Dornogobi, Mongolia in later 2008, which is one of the high Asian dust source regions in the Asian domain, to investigate meteorological conditions for the dust events. The tower was equipped with meteorological sensors (temperature, humidity and wind speed at four levels, precipitation and pressure near the surface), radiation sensors (solar radiation, net radiation) and soil measurement sensors (soil moisture and soil temperature at three levels and soil heat flux at one level) and turbulent measurement (sonic anemometer) at the 8 m height and PM₁₀ concentration measurement (beta guage) at the 3 m height. Measurement was made for a full year of 2009. The observed data indicated that dust events occur all year round with the maximum hourly mean maximum concentration of 4107 μg m^?3 in the early May to a minimum of 92 μg m^?3 in later August. It was found that the dust concentration at this site is directly related to the wind speed exceeding the threshold wind speed (likewise the corresponding friction velocity) during the winter to early spring. However, the observed dust concentration is not only related to the wind speed exceeding the threshold wind speed but also to the Normalized Difference Vegetation Index (NDVI) during the late spring to the late autumn due to the growth of vegetation. It was also found that the surface soil moisture content does not affect the dust concentration due to the relatively short residence time of the soil moisture in the surface soil. The presently monitored data can be used to verify parameters used in the Asian Dust Aerosol Model (ADAM) that is the operational forecasting dust model in the Korea Meteorological Administration (KMA).     

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.     

Decadal reductions of traffic emissions on a transit route in Austria – results of the Tauerntunnel experiment 1997

Real-world emissions of a traffic fleet on a transit route in Austria were determined in the Tauerntunnel experiment in October 1997. The total number of vehicles and the average speed was nearly the same on both measuring days (465 vehicles 30 min⁻¹ and 76 km h⁻¹ on the workday, 477 and 78 km h⁻¹ on Sunday). The average workday fleet contained 17.6% heavy-duty vehicles (HDV) and the average Sunday fleet 2.8% HDV resulting in up to four times higher emission rates per vehicle per km on the workday than on Sunday for most of the regulated components (CO₂, CO, NO_x, SO₂, and particulate matter-PM10). Emission rates of NMVOC accounted for 200 mg vehicle⁻¹ km⁻¹ on both days. The relative contributions of light-duty vehicles (LDV) and HDV to the total emissions indicated that aldehydes, BTEX (benzene, toluene, ethylbenzene, xylenes), and alkanes are mainly produced by LDV, while HDV dominated emissions of CO, NO_x, SO₂, and PM10. Emissions of NO_x caused by HDV were 16,100 mg vehicle⁻¹ km⁻¹ (as NO₂). Produced by LDV they were much lower at 360 mg vehicle⁻¹ km⁻¹. Comparing the emission rates to the results that were obtained by the 1988 experiment at the same place significant changes in the emission levels of hydrocarbons and CO, which accounted 1997 to only 10% of the levels in 1988, were noticed. However, the decrease of PM has been modest leading to values of 80 and 60% of the levels in 1988 on the workday and on Sunday, respectively. Emission rates of NO_x determined on the workday in 1997 were 3130 mg vehicle⁻¹ km⁻¹ and even higher than in 1988 (2630 mg vehicle⁻¹ km⁻¹), presumable due to the increase of the HD-traffic.     

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.