Measurements of the physical properties of particles in the urban atmosphere

Measurements of the physical properties of particles in the atmosphere of a UK urban area have been made, including particle number count by condensation nucleus counters with different lower particle size cut-offs; particle size distributions using a Scanning Mobility Particle Sizer; total particle Fuchs surface area using an epiphaniometer and particle mass using Tapered Element Oscillating Micro-balance (TEOM) instruments with size selective (PM₁₀ and PM_2.5) inlets. Mean particle number counts at three sites range from 2.86×10⁴ to 9.60×10⁴ cm^-3. A traffic-influenced location showed a substantially higher ratio of particle number to PM₁₀ mass than a nearby background location despite being some 70 m from the roadway. Operating two condensation nucleus counters in tandem to determine particles in the 3–7 nm size range by difference showed signficant numbers of particles in this range, apparently related to homogeneous nucleation processes. Measurements with the Scanning Mobility Particle Sizer showed a clear difference between roadside size distributions and those at a nearby background location with an additional mode in the roadside samples below 10 nm diameter. Particle number counts were found to show a significant linear correlation with PM₁₀ mass (r²=0.44; n=44 for 24 h data at an urban background location), although during one period of high pollution a curvilinear relationship was found. Measurements of the diurnal variation in PM₁₀ mass, particle number count and Fuchs surface area show the same general pattern of behaviour of the three variables, explicable in terms of vehicle emission source strength and atmospheric dispersion, although the surface area growth was out of phase with the particle number and mass. It appears that particle number gives the clearest indication of recent road traffic emissions.     

Estimation of particle resuspension source strength on a major London Road

Non-exhaust particles from road traffic arise from both abrasion sources and the resuspension of particles from the road surface. This paper reports a new combination of existing methods for indirect estimation of resuspension emission factors for Marylebone Road, London, a busy multi-lane highway in a street canyon. The method involves firstly estimating the total source strength of coarse particles (PM_2.5–10) arising from the road by calculating the roadside incremental concentration of coarse particles above the urban background. This is converted to a source strength by its ratio to NO_x whose source strength is estimated from the knowledge of the traffic mix and mean speed. This coarse particle source strength is assumed to represent the sum of resuspension emissions and the coarse particle component of abrasion emissions. Using information on the traffic mix and speed, the abrasion emissions have been calculated from the EMEP/CORINAIR emissions factor database, the result subtracted from the total coarse particle emissions in order to yield resuspension emissions, and combined with traffic count data to derive fleet-average emission factors. Using the fact that the traffic mix differs substantially between weekdays and weekends, separate average emission factors for light- and heavy-duty vehicles have been estimated. In addition to traffic mix, the influence of wind speed and the time elapsed since the last rainfall upon resuspension have been estimated. Wind speed was found to have by far the larger influence, although this was still secondary to the number of heavy-duty vehicles. Uncertainties arising from the choice of urban background site and poor data quality are discussed.     

Improved Version of Anion-exchange Resin-based Desulfurization Process for Alkali Metal Sulfates

Abstract

Vehicle gaseous emissions (NO, CO, CO₂, and hydrocarbon [HC]) and driver’s particle exposures (particulate matter <1 μm [PM₁], <2.5 μm [PM_2.5], and<10 μm [PM₁₀]) were measured using a mobile laboratory to follow a wide variety of vehicles during very heavy traffic congestion in Macao, Special Administrative Region, People’s Republic of China, an urban area having one of the highest population densities in the world. The measurements were taken with high time resolution so that fluctuations in the emissions can be seen readily during vehicle acceleration, cruising, deceleration, and idling. The tests were conducted in close proximity to the vehicles, with the inlet of a five-gas analyzer mounted on the front bumper of the mobile laboratory, and the distance between the vehicles was usually within several meters. To measure the driver’s particle exposures, the inlets of the particle analyzers were mounted at the height of the driver’s breathing position in the mobile laboratory, with the driver’s window open. A total of 178 and 113 vehicles were followed individually to determine the gaseous emission factor and the driver’s particle exposures, respectively, for motorcycle, passenger car, taxi, truck, and bus. The gaseous emission factors were used to model the roadside air quality, and good correlations between the modeled and monitored CO, NO₂, and nitrogen oxide (NO_x) verified the reliability of the experiments. Compared with petrol passenger cars and petrol trucks, diesel taxies and diesel trucks emitted less CO but more NO_x. The impact of urban canyons is shown to cause a significant increase in the PM₁ peak. The background concentrations contributed a significant amount of the driver’s particle exposures.     

Roadside measurements of fine and ultrafine particles at a major road north of Gothenburg

Particle measurements were conducted at a road site 15 km north of the city of Gothenburg for 3 weeks in June 2000. The size distribution between 10 and 368 nm was measured continuously by using a differential mobility particle sizer (DMPS) system. PM_2.5 was sampled on a daily basis with subsequent elemental analysis using EDXRF-spectroscopy. The road is a straight four-lane road with a speed limit of 90 kph. The road passing the site is flat with no elevations where the vehicles run on a steady workload and with constant speed. The traffic intensity is about 20,000 cars per workday and 13,000 vehicles per day during weekends. The diesel fuel used in Sweden is low in sulphur content (<10 ppm) and therefore the diesel vehicles passing the site contribute less to particle emissions in comparison with other studies. A correlation between PM_2.5 and accumulation mode particles (100–368 nm) was observed. However, no significant correlation was found between number concentrations of ultrafine particles (10–100 nm) and PM_2.5 or the accumulation mode number concentration. The particle distribution between 10 and 368 nm showed great dependency on wind speed and wind direction, where the wind speed was the dominant factor for ultrafine (10–100 nm) particle concentrations. The difference in traffic intensity between workday and weekend together with wind data made it possible to single out the traffic contribution to particle emissions and measure the size distribution. The results presented in combination with previous studies show that both PM_2.5 and the mass of accumulation mode particles are bad estimates for ultrafine particles.     

Development and Preliminary Evaluation of a Particulate Matter Emission Factor Model for European Motor Vehicles

ABSTRACT

Although modeling of gaseous emissions from motor vehicles is now quite advanced, prediction of particulate emissions is still at an unsophisticated stage. Emission factors for gasoline vehicles are not reliably available, since gasoline vehicles are not included in the European Union (EU) emission test procedure. Regarding diesel vehicles, emission factors are available for different driving cycles but give little information about change of emissions with speed or engine load. We have developed size-specific speed-dependent emission factors for gasoline and diesel vehicles. Other vehicle-generated emission factors are also considered and the empirical equation for re-entrained road dust is modified to include humidity effects. A methodology is proposed to calculate modal (accelerating, cruising, or idling) emission factors. The emission factors cover particle size ranges up to 10 um, either from published data or from user-defined size distributions.

A particulate matter emission factor model (PMFAC), which incorporates virtually all the available information on particulate emissions for European motor vehicles, has been developed. PMFAC calculates the emission factors for five particle size ranges [i.e., total suspended particulates (TSP), PM₁₀, PM₅, PM₂₅, and PM₁] from both vehicle exhaust and nonexhaust emissions, such as tire wear, brake wear, and re-entrained road dust. The model can be used for an unlimited number of roads and lanes, and to calculate emission factors near an intersection in user-defined elements of the lane. PMFAC can be used for a variety of fleet structures. Hot emission factors at the user-defined speed can be calculated for individual vehicles, along with relative cold-to-hot emission factors. The model accounts for the proportions of distance driven with cold engines as a function of ambient temperature and road type (i.e., urban, rural, or motorway).

A preliminary evaluation of PMFAC with an available dispersion model to predict the airborne concentration in the urban environment is presented. The trial was on the A6 trunk road where it passes through Loughborough, a medium-size town in the English East Midlands. This evaluation for TSP and PM₁₀ was carried out for a range of traffic fleet compositions, speeds, and meteorological conditions. Given the limited basis of the evaluation, encouraging agreement was shown between predicted and measured concentrations.     

Interpretation of air quality in relation to monitoring station's surroundings

This study explores the appropriateness of the locality of air monitoring stations which are meant to indicate air quality in the area. Daily variations in NO₂ and PM₁₀ concentrations at 14 monitoring stations in Hong Kong are examined. The daily variations in NO₂ at a number of background monitoring stations exhibit patterns similar to variations in traffic volume while variations in PM₁₀ concentration exhibit less discernible pattern. Principal component analysis (PCA) and cluster analysis (CA) are applied to analyse NO₂ and PM₁₀ measurements between January 2001 and December 2005. The results show that NO₂ concentrations at background stations within the urban area are highly influenced by vehicle emissions. The effect vehicle emission has on NO₂ at stations within new towns is smaller. CA results also show that variations in PM₁₀ concentrations are distinguished by the area the station is located in. PCA results show that there are two principal components (PC's) associated with variations in roadside concentration of PM₁₀. The strong influence of roadside emissions towards concentrations of NO₂ and PM₁₀ at a number of urban background stations may be due to their close proximity to busy roadways and the high density of surrounding tall buildings, which creates an enclosure that hinders dispersion of roadside emissions and results in air pollution behaviour that reflects variation in traffic.     

Temporal variations of atmospheric aerosol in four European urban areas

Purpose

The concentrations of PM₁₀ mass, PM_2.5 mass and particle number were continuously measured for 18 months in urban background locations across Europe to determine the spatial and temporal variability of particulate matter.

Methods

Daily PM₁₀ and PM_2.5 samples were continuously collected from October 2002 to April 2004 in background areas in Helsinki, Athens, Amsterdam and Birmingham. Particle mass was determined using analytical microbalances with precision of 1 ??g. Pre- and post-reflectance measurements were taken using smoke-stain reflectometers. One-minute measurements of particle number were obtained using condensation particle counters.

Results

The 18-month mean PM₁₀ and PM_2.5 mass concentrations ranged from 15.4 ??g/m³ in Helsinki to 56.7 ??g/m³ in Athens and from 9.0 ??g/m³ in Helsinki to 25.0 ??g/m³ in Athens, respectively. Particle number concentrations ranged from 10,091 part/cm³ in Helsinki to 24,180 part/cm³ in Athens with highest levels being measured in winter. Fine particles accounted for more than 60% of PM₁₀ with the exception of Athens where PM_2.5 comprised 43% of PM₁₀. Higher PM mass and number concentrations were measured in winter as compared to summer in all urban areas at a significance level p?Conclusions Significant quantitative and qualitative differences for particle mass across the four urban areas in Europe were observed. These were due to strong local and regional characteristics of particulate pollution sources which contribute to the heterogeneity of health responses. In addition, these findings also bear on the ability of different countries to comply with existing directives and the effectiveness of mitigation policies.     

Spatial variation of particle number and mass over four European cities

The number of ultrafine particles may be a more health relevant characteristic of ambient particulate matter than the conventionally measured mass. Epidemiological time series studies typically use a central site to characterize human exposure to outdoor air pollution. There is currently very limited information how well measurements at a central site reflect temporal and spatial variation across an urban area for particle number concentrations (PNC).The main objective of the study was to assess the spatial variation of PNC compared to the mass concentration of particles with diameter less than 10 or 2.5 μm (PM₁₀ and PM_2.5).Continuous measurements of PM₁₀, PM_2.5, PNC and soot concentrations were conducted at a central site during October 2002–March 2004 in four cities spread over Europe (Amsterdam, Athens, Birmingham and Helsinki). The same measurements were conducted directly outside 152 homes spread over the metropolitan areas. Each home was monitored during 1 week. We assessed the temporal correlation and the variability of absolute concentrations.For all particle indices, including particle number, temporal correlation of 24-h average concentrations was high. The median correlation for PNC per city ranged between 0.67 and 0.76. For PM_2.5 median correlation ranged between 0.79 and 0.98. The median correlation for hourly average PNC was lower (range 0.56–0.66). Absolute concentration levels varied substantially more within cities for PNC and coarse particles than for PM_2.5. Measurements at the central site reflected the temporal variation of 24-h average concentrations for all particle indices at the selected homes across the urban area. A central site could not assess absolute concentrations across the urban areas for particle number.     

Air Quality Measurements from the Fresno Supersite

ABSTRACT

The Fresno Supersite intends to 1) evaluate non-routine monitoring methods, establishing their comparability with existing methods and their applicability to air quality planning, exposure assessment, and health effects studies; 2) provide a better understanding of aerosol characteristics, behavior, and sources to assist regulatory agencies in developing standards and strategies that protect public health; and 3) support studies that evaluate relationships between aerosol properties, co-factors, and observed health end-points. Supersite observables include in-situ, continuous, short-duration measurements of 1) PM_2.5, PM₁₀, and coarse (PM₁₀ minus PM_2.5) mass; 2) PM_2.5 SO₄ ^-2, NO₃ ^-, carbon, light absorption, and light extinction; 3) numbers of particles in discrete size bins ranging from 0.01 to ~10μm; 4) criteria pollutant gases (O₃, CO, NO_x); 5) reactive gases (NO₂, NO_y, HNO₃, peroxyacetyl nitrate [PAN], NH₃); and 6) single particle characterization by time-of-flight mass spectrometry. Field sampling and laboratory analysis are applied for gaseous and particulate organic compounds (light hydrocarbons, heavy hydrocarbons, carbonyls, polycyclic aromatic hydrocarbons [PAH], and other semi-volatiles), and PM_2.5 mass, elements, ions, and carbon. Observables common to other Supersites are 1) daily PM_2.5 24-hr average mass with Federal Reference Method (FRM) samplers; 2) continuous hourly and 5-min average PM_2.5 and PM₁₀ mass with beta attenuation monitors (BAM) and tapered element oscillating microbalances (TEOM); 3) PM_2.5 chemical specia-tion with a U.S. Environmental Protection Agency (EPA) speciation monitor and protocol; 4) coarse particle mass by dichotomous sampler and difference between PM₁₀ and PM_2.5 BAM and TEOM measurements; 5) coarse particle chemical composition; and 6) high sensitivity and time resolution scalar and vector wind speed, wind direction, temperature, relative humidity, barometric pressure, and solar radiation. The Fresno Supersite is coordinated with health and toxicological studies that will use these data in establishing relationships with asthma, other respiratory disease, and cardiovascular changes in human and animal subjects.     

Evaluation and application of biomagnetic monitoring of traffic-derived particulate pollution

Inhalation of particulate pollutants below 10 μm in size (PM₁₀) is associated with adverse health effects. Here we use magnetic remanence measurements of roadside tree leaves to examine levels of vehicle-derived PM around Lancaster, UK. Leaf saturation remanence (SIRM) values exhibit strong correlation with both the SIRM and particulate mass of co-located, pumped-air samples, indicating that these leaf magnetic values are an effective proxy for ambient PM₁₀ concentrations. Biomagnetic monitoring using tree leaves can thus provide high spatial resolution data sets for assessment of particulate pollution levels at pedestrian-relevant heights. Leaf SIRM values not only increase with proximity to roads with higher traffic volumes, but are also ～100% higher at 0.3 m than at ～1.5–2 m height. Magnetic and SEM data indicate that the particle populations are dominated by spherical, iron-rich particles ～0.1–1 μm in diameter, with fewer larger, more angular, silica-rich particles. Comparison of the roadside leaf-calculated PM₁₀ concentrations with PM₁₀ concentrations predicted by a widely-used atmospheric dispersion model indicates some agreement between them. However, the model under-predicts PM₁₀ concentrations at ‘urban hotspots’ such as major–minor road junctions and traffic lights. Conversely, the model over-predicts PM₁₀ concentrations with distance from the road wherever one tree is screened by another, indicating the filtering/protective effect of roadside trees in leaf.     

A European aerosol phenomenology – 3: Physical and chemical characteristics of particulate matter from 60 rural,urban, and kerbside sites across Europe

This paper synthesizes data on aerosol (particulate matter, PM) physical and chemical characteristics, which were obtained over the past decade in aerosol research and monitoring activities at more than 60 natural background, rural, near-city, urban, and kerbside sites across Europe. The data include simultaneously measured PM₁₀ and/or PM_2.5 mass on the one hand, and aerosol particle number concentrations or PM chemistry on the other hand. The aerosol data presented in our previous works (Van Dingenen et al., 2004, Putaud et al., 2004) were updated and merged to those collected in the framework of the EU supported European Cooperation in the field of Scientific and Technical action COST633 (Particulate matter: Properties related to health effects). A number of conclusions from our previous studies were confirmed. There is no single ratio between PM_2.5 and PM₁₀ mass concentrations valid for all sites, although fairly constant ratios ranging from 0.5 to 0.9 are observed at most individual sites. There is no general correlation between PM mass and particle number concentrations, although particle number concentrations increase with PM_2.5 levels at most sites. The main constituents of both PM₁₀ and PM_2.5 are generally organic matter, sulfate and nitrate. Mineral dust can also be a major constituent of PM₁₀ at kerbside sites and in Southern Europe. There is a clear decreasing gradient in SO₄^2? and NO₃^? contribution to PM₁₀ when moving from rural to urban to kerbside sites. In contrast, the total carbon/PM₁₀ ratio increases from rural to kerbside sites. Some new conclusions were also drawn from this work: the ratio between ultrafine particle and total particle number concentration decreases with PM_2.5 concentration at all sites but one, and significant gradients in PM chemistry are observed when moving from Northwestern, to Southern to Central Europe. Compiling an even larger number of data sets would have further increased the significance of our conclusions, but collecting all the aerosol data sets obtained also through research projects remains a tedious task.     

Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2

Atmospheric PM pollution from traffic comprises not only direct emissions but also non-exhaust emissions because resuspension of road dust that can produce high human exposure to heavy metals, metalloids, and mineral matter. A key task for establishing mitigation or preventive measures is estimating the contribution of road dust resuspension to the atmospheric PM mixture. Several source apportionment studies, applying receptor modeling at urban background sites, have shown the difficulty in identifying a road dust source separately from other mineral sources or vehicular exhausts. The Multilinear Engine (ME-2) is a computer program that can solve the Positive Matrix Factorization (PMF) problem. ME-2 uses a programming language permitting the solution to be guided toward some possible targets that can be derived from a priori knowledge of sources (chemical profile, ratios, etc.). This feature makes it especially suitable for source apportionment studies where partial knowledge of the sources is available.In the present study ME-2 was applied to data from an urban background site of Barcelona (Spain) to quantify the contribution of road dust resuspension to PM₁₀ and PM_2.5 concentrations. Given that recently the emission profile of local resuspended road dust was obtained (Amato, F., Pandolfi, M., Viana, M., Querol, X., Alastuey, A., Moreno, T., 2009. Spatial and chemical patterns of PM₁₀ in road dust deposited in urban environment. Atmospheric Environment 43 (9), 1650–1659), such a priori information was introduced in the model as auxiliary terms of the object function to be minimized by the implementation of the so-called “pulling equations”.ME-2 permitted to enhance the basic PMF solution (obtained by PMF2) identifying, beside the seven sources of PMF2, the road dust source which accounted for 6.9 μg m^?3 (17%) in PM₁₀, 2.2 μg m^?3 (8%) of PM_2.5 and 0.3 μg m^?3 (2%) of PM₁. This reveals that resuspension was responsible of the 37%, 15% and 3% of total traffic emissions respectively in PM₁₀, PM_2.5 and PM₁. Therefore the overall traffic contribution resulted in 18 μg m^?3 (46%) in PM₁₀, 14 μg m^?3 (51%) in PM_2.5 and 8 μg m^?3 (48%) in PM₁. In PMF2 this mass explained by road dust resuspension was redistributed among the rest of sources, increasing mostly the mineral, secondary nitrate and aged sea salt contributions.     

Sources and processes affecting concentrations of PM10 and PM2.5 particulate matter in Birmingham (U.K.)

Hourly average concentrations of PM₁₀ and PM_2.5 have been measured simultaneously at a site within Birmingham U.K. between October 1994 and October 1995. Comparison of PM₁₀ and NO_x data with two other sites in the same city shows comparable summer and winter mean concentrations and highly significant inter-site correlations for both hourly and daily mean data. Over a four-month period samples were also collected for chemical analysis of sulphate, nitrate, chloride, ammonium and elemental and organic carbon. Analysis of the data indicates a marked difference between summer and winter periods. In the winter months PM_2.5 comprises about 80% of PM₁₀ and is strongly correlated with NO_x indicating the importance of road traffic as a source. In the summer months, coarse particles (PM₁₀−PM_2.5) account for almost 50% of PM₁₀ and the influence of resuspended surface dusts and soils and of secondary particulate matter is evident. The chemical analysis data are also consistent with three sources dominating the PM₁₀ composition: vehicle exhaust emissions, secondary ammonium salts and resuspended surface dusts. Coarse particles from resuspension showed a positive dependence on windspeed, whilst elemental carbon derived from road traffic exhibited a negative dependence.     

Exposure to ultrafine and fine particles and noise during cycling and driving in 11 Dutch cities

Recent studies have suggested that exposures during traffic participation may be associated with adverse health effects. Traffic participation involves relatively short but high exposures. Potentially relevant exposures include ultrafine particles, fine particles (PM_2.5) and noise.Simultaneously, detailed real time exposure of particle number concentration (PNC), PM_2.5 and noise has been measured while driving and cycling 12 predefined routes of approximately 10–20 min duration. Sampling took place in eleven medium-sized Dutch cities on eleven weekdays in August till October 2006. To investigate variability in cyclists exposure, we systematically collected information on meteorology, GPS coordinates, type of road, traffic intensity, passing vehicles and mopeds while cycling.The overall mean PNC of car drivers was 5% higher than the mean PNC of cyclists. The overall mean concentration of PM_2.5 in the car was 11% higher than during cycling. Slightly higher 1-min peak concentrations were measured in the car (PNC 14%; PM_2.5 29% for 95-percentiles). Shorter duration peaks of PNC were higher during cycling (43% for 99-percentile of 1-s averages). Peaks in PNC typically last for less than 10 s. A large variability of exposure was found within and between routes. Factors that significantly predicted PNC variability during cycling were: passing vehicles (mopeds, cars), waiting for traffic lights, passing different types of (large) intersections and bicycle lanes and bike paths close to motorized traffic. No relation was found between PM_2.5 and those predictor variables. The correlation between PNC and noise was moderate (median 0.34). PM_2.5 had very low correlations with PNC and noise.PNC and PM_2.5 exposure of car drivers was slightly higher than that of cyclists. PNC was largely uncorrelated with PM_2.5 and reflected local traffic variables more than PM_2.5. Different factors were associated with high PNC and high noise exposures.     

PM10 concentration levels at an urban and background site in Cyprus: The impact of urban sources and dust storms

Air quality in Cyprus is influenced by both local and transported pollution, including desert dust storms. We examined PM₁₀ concentration data collected in Nicosia (urban representative) from April 1, 1993, through December 11, 2008, and in Ayia Marina (rural background representative) from January 1, 1999, through December 31, 2008. Measurements were conducted using a Tapered Element Oscillating Micro-balance (TEOM). PM₁₀ concentrations, meteorological records, and satellite data were used to identify dust storm days. We investigated long-term trends using a Generalized Additive Model (GAM) after controlling for day of week, month, temperature, wind speed, and relative humidity. In Nicosia, annual PM₁₀ concentrations ranged from 50.4 to 63.8 μg/m³ and exceeded the EU annual standard limit enacted in 2005 of 40 μg/m³ every year. A large, statistically significant impact of urban sources (defined as the difference between urban and background levels) was seen in Nicosia over the period 2000–2008, and was highest during traffic hours, weekdays, cold months, and low wind conditions. Our estimate of the mean (standard error) contribution of urban sources to the daily ambient PM₁₀ was 24.0 (0.4) μg/m³. The study of yearly trends showed that PM₁₀ levels in Nicosia decreased from 59.4 μg/m³ in 1993 to 49.0 μg/m³ in 2008, probably in part as a result of traffic emission control policies in Cyprus. In Ayia Marina, annual concentrations ranged from 27.3 to 35.6 μg/m³, and no obvious time trends were observed. The levels measured at the Cyprus background site are comparable to background concentrations reported in other Eastern Mediterranean countries. Average daily PM₁₀ concentrations during desert dust storms were around 100 μg/m³ since 2000 and much higher in earlier years. Despite the large impact of dust storms and their increasing frequency over time, dust storms were responsible for a small fraction of the exceedances of the daily PM₁₀ limit.

ImplicationsThis paper examines PM₁₀ concentrations in Nicosia, Cyprus, from 1993 to 2008. The decrease in PM₁₀ levels in Nicosia suggests that the implementation of traffic emission control policies in Cyprus has been effective. However, particle levels still exceeded the European Union annual standard, and dust storms were responsible for a small fraction of the daily PM₁₀ limit exceedances. Other natural particles that are not assessed in this study, such as resuspended soil and sea salt, may be responsible in part for the high particle levels.     

Dust build-up on surfaces in the indoor environment

The concentration and the composition of dust in the indoor environment has been associated with reported symptoms of the sick building syndrome. Levels of airborne concentrations of dust particles are well known. However, the relation to dust on surfaces for office environments are not well described. In this study, 662 measurements were performed of surface dust concentrations on hard surfaces in 19 buildings within Harvard University based on a sticking gelatine foil method. The measure is the dust covered area of the surface as a percentage. In three offices, the build-up of dust on surfaces was measured for a period of five days. Close to these surfaces the airborne PM_2.5 and PM₁₀ particle mass concentrations were measured simultanously. A significant correlation between the dust build-up and the difference between the PM₁₀ and the PM_2.5 was established. The particle size distribution was measured by means of an Aerodynamic Particle Sizer. The mean dust build-up normalized with the measured PM₁₀ was approximately four times higher than the equivalent calculated by a deposition model. This may in part be due to the effect of preferred orientation when particles settle to a surface. Different data for dust on surfaces and airborne particles in offices were compared. The levels of airborne particles in offices in Europe seem to be higher than the levels in the US.     

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.     

Evaluating the dynamical characteristics of particle matter emissions in an open ore yard with industrial operation activities

A study to investigate the dynamical characteristics of particle matter emissions in a working open yard is conducted in Caofeidian Port of Hebei Province, China. The average diurnal concentrations of the total suspended particulate (TSP) matter and respirable particulate matter (PM₁₀ and PM₅) are monitored during the field measurement campaign. Sampling is performed at a regular interval at 8 monitoring stations in the yard with normal industrial activities. The average TSP, PM₁₀ and PM₅ concentrations range from 285 to 568, 198 to 423 and 189 to 330 μg.m-3 in the yard, respectively. The linear regression correlation coefficient of TSP/PM₁₀ and TSP/PM₅ is 0.95±0.01 and 0.88±0.02, respectively.By using the Spearman correlation method, the wind speed and relative humidity are both weakly correlated with the PM₁₀ and PM₅ concentrations according to the measurements. In addition, industrial operation activities, such as vehicular traffic in the yard and the loading time of stackers, are significantly positively correlated with the PM concentration. Using the multivariate regression method, the main parameters influencing the TSP concentration variations are integratedly analysed. The traffic volume is found to be a significant predictor of TSP concentration variation, with the smallest P value (P<0.05).To understand the dynamical characteristics of particle emissions in the yard, the emissions from the truck transports, that is, from unpaved haul roads and from the loading process, are established. Then, the dynamical emission factor (EF_D) based on the industrial activities in the yard is proposed. The dynamical emissions average 5.25x10⁵ kg.year^-1 and EF_D is evaluated to be 0.29 kg.(ton.day)^-1 during the measurement period. These outcomes have meaningful implications not only for understanding the dynamical characteristics of particle emissions in the working stockyard but also for implementing effective control measures at appropriate sites in the harbour area.     

Spatial and temporal variability of outdoor coarse particulate matter mass concentrations measured with a new coarse particle sampler during the Detroit Exposure and Aerosol Research Study

The Detroit Exposure and Aerosol Research Study (DEARS) provided data to compare outdoor residential coarse particulate matter (PM_10–2.5) concentrations in six different areas of Detroit with data from a central monitoring site. Daily and seasonal influences on the spatial distribution of PM_10–2.5 during Summer 2006 and Winter 2007 were investigated using data collected with the newly developed coarse particle exposure monitor (CPEM). These data allowed the representativeness of the community monitoring site to be assessed for the greater Detroit metro area. Multiple CPEMs collocated with a dichotomous sampler determined the precision and accuracy of the CPEM PM_10–2.5 and PM_2.5 data.CPEM PM_2.5 concentrations agreed well with the dichotomous sampler data. The slope was 0.97 and the R² was 0.91. CPEM concentrations had an average 23% negative bias and R² of 0.81. The directional nature of the CPEM sampling efficiency due to bluff body effects probably caused the negative CPEM concentration bias.PM_10–2.5 was observed to vary spatially and temporally across Detroit, reflecting the seasonal impact of local sources. Summer PM_10–2.5 was 5 μg m^?3 higher in the two industrial areas near downtown than the average concentrations in other areas of Detroit. An area impacted by vehicular traffic had concentrations 8 μg m^?3 higher than the average concentrations in other parts of Detroit in the winter due to the suspected suspension of road salt. PM_10–2.5 Pearson Correlation Coefficients between monitoring locations varied from 0.03 to 0.76. All summer PM_10–2.5 correlations were greater than 0.28 and statistically significant (p-value < 0.05). Winter PM_10–2.5 correlations greater than 0.33 were statistically significant (p-value < 0.05). The PM_10–2.5 correlations found to be insignificant were associated with the area impacted by mobile sources during the winter. The suspected suspension of road salt from the Southfield Freeway, combined with a very stable atmosphere, caused concentrations to be greater in this area compared to other areas of Detroit. These findings indicated that PM_10–2.5, although correlated in some instances, varies sufficiently across a complex urban airshed that that a central monitoring site may not adequately represent the population's exposure to PM_10–2.5.     

Feasibility of using low-cost portable particle monitors for measurement of fine and coarse particulate matter in urban ambient air

Exposure to ambient particulate matter (PM) is known as a significant risk factor for mortality and morbidity due to cardiorespiratory causes. Owing to increased interest in assessing personal and community exposures to PM, we evaluated the feasibility of employing a low-cost portable direct-reading instrument for measurement of ambient air PM exposure. A Dylos DC 1700 PM sensor was collocated with a Grimm 11-R in an urban residential area of Houston Texas. The 1-min averages of particle number concentrations for sizes between 0.5 and 2.5 µm (small size) and sizes larger than 2.5 µm (large size) from a DC 1700 were compared with the 1-min averages of PM_2.5 (aerodynamic size less than 2.5 µm) and coarse PM (aerodynamic size between 2.5 and 10 µm) concentrations from a Grimm 11-R. We used a linear regression equation to convert DC 1700 number concentrations to mass concentrations, utilizing measurements from the Grimm 11-R. The estimated average DC 1700 PM_2.5 concentration (13.2 ± 13.7 µg/m³) was similar to the average measured Grimm 11-R PM_2.5 concentration (11.3 ± 15.1 µg/m³). The overall correlation (r²) for PM_2.5 between the DC 1700 and Grimm 11-R was 0.778. The estimated average coarse PM concentration from the DC 1700 (5.6 ± 12.1 µg/m³) was also similar to that measured with the Grimm 11-R (4.8 ± 16.5 µg/m³) with an r² of 0.481. The effects of relative humidity and particle size on the association between the DC 1700 and the Grimm 11-R results were also examined. The calculated PM mass concentrations from the DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.

Implications: The performance of a low-cost particulate matter (PM) sensor was evaluated in an urban residential area. Both PM_2.5 and coarse PM (PM_10-2.5) mass concentrations were estimated using a DC1700 PM sensor. The calculated PM mass concentrations from the number concentrations of DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.