Temporal size distribution and concentration of ...

Atmospheric Environment 43 (2009) 1100–1105

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Temporal size distribution and concentration of particles near a major highway G. Buonanno a, *, A.A. Lall b, L. Stabile a a b

Dipartimento di Meccanica, Strutture, Ambiente e Territorio, University of Cassino, Italy Department of Mechanical Engineering, University of Maryland, College Park, USA

a r t i c l e i n f o

a b s t r a c t

Article history: Received 3 July 2008 Received in revised form 4 November 2008 Accepted 5 November 2008

Ultrafine particles (UFP, diameter < 100 nm), as reported in recent findings of toxicological and epidemiological studies, could represent health and environmental risks. Motor vehicle emissions usually constitute the most significant source of UFP in an urban environment. Number, surface and mass concentration of particles were determined at increasing distances from the most important Italian road: the ‘‘Autostrada del Sole’’ A1 highway. Particles in the size range from 0.0059 to 20 mm were measured with a Scanning Mobility Particle Sizer (SMPS) and an Aerodynamic Particle Sizer (APS) spectrometers. The A1 highway was selected because it is characterized by two different traffic conditions: a daily and a weekly traffic. During the weekdays the average traffic flow was about 50 vehicles min1 with more than 30% of vehicles being heavy-duty (HD) diesel trucks. The weekly traffic component is characterized by an increased traffic up to approximately 100 vehicles min1 during Monday mornings and Friday afternoons because of light-duty vehicles, with substantial reduction of the percentage of HD diesel trucks (typically only 10%). The purpose of this study is the characterization of the A1 highway in terms of evolution of particle size distribution (PSD) and total number concentration at different distances from the highway. This analysis is interesting because Italian traffic presents a higher i) percentage of diesel light-duty vehicles and ii) mean traffic speed in respect to US and Australian traffics. Particle number, surface and mass, exponentially decreases as one moves away from the freeway, whereas UFP number concentration measured at 400 m downwind from the freeway is indistinguishable from upwind background concentration. Ó 2008 Elsevier Ltd. All rights reserved.

Keywords: Ultrafine particles Number, surface and mass concentration Highway emissions Aggregates

1. Introduction Particulate pollution and its effects on public health in urban areas, the global climate and local visibility have been longstanding concerns of the air quality management community and regulatory authorities. Epidemiological data from air pollution studies correlate particulate matter to the negative effects on human breathing, cardiovascular problems and increase of mortality and morbidity (Schwartz, 1991; Vedal, 1997; Cheng et al., 1999; Cheng, 2003; Kreyling et al., 2006), even if it is not clear what particle sizes have the worst effects on human health. A number of epidemiological studies correlate these effects to the particle mass concentration PM2.5 (Dockery et al., 1993; Pope et al., 1995a; Brunekreef, 2000; Pope, 2000; Oberdo¨rster et al., 2000) and PM10 (Pope et al., 1995b; Pekkanen et al., 1997; Brunekreef, 2000; Loomis, 2000), otherwise, other studies correlate these negative effects to the UFP number concentration (Agarwal and Remiarz, 1981; Peters et al., 1997; Hauser et al., 2001) or to the assumption rate (Siegmann and Siegmann, 1998). These results

* Corresponding author. Tel.: þ39 0776 2993669; fax: þ39 0776 2994002. E-mail address: [email protected] (G. Buonanno). 1352-2310/$ – see front matter Ó 2008 Elsevier Ltd. All rights reserved. doi:10.1016/j.atmosenv.2008.11.011

suggest that health effects from particles are strongly tied with coexposure to other pollutants (Samet, 2000; Oberdo¨rster, 2001; Anastasio and Martin, 2001). Current air quality standards only regulate the particle concentration in terms of mass: PM10 and PM2.5 (EPA 40 CFR, 1997; EN 12341, 1999; EN 14907, 2005). These mass-based concentrations are mainly dominated by particles greater than 100 nm. Otherwise, in an urban environment, UFP represent over 80% of particles in terms of number concentration (Morawska et al., 1998; Zhu et al., 2004; Holmes et al., 2005; Buonanno et al., 2008).

1.1. Emission sources Emission inventories suggest that the highest contribution to the fine and ultrafine particles comes from anthropogenic activities, namely from emissions of industrial combustion processes and traffic-related emissions (Schauer et al., 1996; Shi et al., 1999; Airborne Particles Expert Group, 1999; EPA, 2000; Cass et al., 2000; Harrison et al., 2000; Hitchins et al., 2000). In the traffic-related emission issue, the greater part of particle number from vehicle exhausts is in the 20–130 nm size range for diesel engines (Morawska et al., 1998; Kittelson, 1998) and 20–60 nm for gasoline

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engines (Ristovski et al., 1998; Kittelson, 1998). It is important and necessary to quantify UFP emission levels and to determine UFP behavior after emission as they are transported away from the emission sources, such as busy roads and highways. Hitchins et al. (2000) determined the PSD and concentration at increasing distances from a road in two sites in Australia finding decays of fine and ultrafine particles up to half of their maximum at a distance of 100–150 m from the road. Shi et al. (1999) observed a faster decline of particle number than mass concentration between a busy roadside and a nearby urban background site in Birmingham, United Kingdom. Zhu et al. (2002a,b) conducted systematic measurements of the concentration and size distribution of UFP in the vicinity of a highway dominated by gasoline vehicles (freeway 405) and of the Interstate 710 freeway in Los Angeles: a very interesting study because more than 25% of the vehicles along this freeway are HD diesel trucks. Kittelson et al. (2004) characterized on-road aerosol on highways surrounding the Minneapolis area. They determined on-road nanoparticle concentrations and estimated fuel-specific particle emissions finding onroad aerosol number concentrations ranged from 104 to 106 part. cm3 and that the highest nanoparticle concentrations were associated with high-speed traffic. 1.2. On-line measurements On-line UFP measurement, in terms of number concentration and PSD, can be obtained through the Scanning Mobility Particle Sizer (SMPS). These measurements are strictly influenced by the presence of aggregates as reported in Lall and Friedlander (2006) and Lall et al. (2006). Furthermore, urban ultrafine atmospheric aerosol and particle emissions from combustion sources such as diesel engines are typically low fractal dimension aggregates (Df 2) composed of spherical primary particles with a diameter of 5–50 nm (Xiong and Friedlander, 2001). These agglomerates are not rigid structures and are typically flexible nanoparticle chain (Friedlander, 2000). Thus, the dynamics of agglomerate significantly differs from that of spherical particle and it could lead to errors in the mobility size data interpretation for aerosol carrying a high aggregates percentage and subsequent calculations of its surface area and volume (and hence mass) distributions. Lall and Friedlander (2006) and Lall et al. (2006) have developed a method to analyze mobility of nanoparticle aggregates for a limiting case of idealized aggregates (Df 2): the Idealized Aggregate (IA) theory, also tested in Lall et al. (2008) by using an Aerosol Particle Mass analyzer (APM). The basic assumption of this theory is that aggregates are composed of primary particles all of which have the same (known) diameter. In the present paper the authors have used this theory in order to correct the data and to calculate the surface area and the mass concentration. The primary particle diameter has been evaluated in some scientific studies demonstrating an average size of approximately 30 nm (Lee et al., 2001; Park et al., 2004; Barone et al., 2006). Authors also collected particles in College Park, MD, along a crowded avenue in the proximity of the University of Maryland. Particles were collected by a Nanometer Aerosol Sampler (Model 3089 TSI Inc.) and examined using a ZEISS EM10CA TEM. In Fig. 1 one of the sampled atmospheric aggregates is reported (photomicrograph taken at 64800 magnification). It presents typical branched chain-like structures with fractal dimension lower than 2 and primary particle diameter equal to about 30 nm as it can be qualitatively estimated by comparing these images with literature aggregates shapes (Dye et al., 2000; Xiong and Friedlander, 2001). In the present work, besides the above mentioned qualitative TEM analysis, the authors determined number, surface and mass concentration of particles at increasing distances from the most important Italian road: the ‘‘Autostrada del Sole’’ A1 highway. The

Fig. 1. Typical atmospheric aggregate particle sampled at University of Maryland, College Park.

analysis of Italian traffic is very interesting because it presents very different characteristics in respect to the US and Australian traffics reported in Zhu et al. (2002a,b) and Hitchins et al. (2000): a) the percentage of diesel vehicles is very relevant in respect to the gasoline ones and b) the Italian mean traffic speed is mostly higher than speed values reported in Zhu et al. (2002a,b), Hitchins et al. (2000), and Kittelson et al. (2004). 2. Experimental 2.1. Site description The site selected for the present study, located in the centre of Italy, Cassino (41260 5400 N–13 500 4000 E), is adjacent the Italian most important highway: the A1 ‘‘Autostrada del Sole’’, that presents a W–E direction (actual orientation 170 ). The A1 highway has six lines (plus two emergency lines), three west bound and three east bound. It is approximately 26 m wide (not considering the emergency lines). The location selected is ideal both for the absence of residential areas (a nearby residential area is approximately 800 m downwind from the highway) and of local traffic (the sampling road is a perpendicular rural road at the same elevation of the highway with no local traffic during the sampling periods). In Table 1 sampling dates and times are summarized. In Fig. 2 wind velocities and directions measured during the sampling period are reported through a weather station (Davis Vantage Pro). These parameters were measured every 5-min interval during each Table 1 Sampling dates, times and weather conditions during the sampling period. Date

Time

Traffic conditions

Temperature and relative humidity during the sampling period

02/04/08 15/04/08 18/04/08 24/04/08 05/05/08 09/05/08

14:15–18:30 14:30–19:30 14:00–19:30 14:00–16:30 14:30–19:00 15:30–18:30

Daily traffic Daily traffic Weekly traffic Weekly traffic Daily traffic Weekly traffic

17.8 1.3 C; 42.2 3.3% R.H. 16.4 1.4 C; 75.2 8.3% R.H. 18.1 1.6 C; 71.2 7.7% R.H. 17.8 2.3 C; 70.9 11.7% R.H. 21.4 1.2 C; 50.2 6.9% R.H. 20.1 1.9 C; 55.2 7.3% R.H.

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Fig. 2. Wind direction and speed at the sampling site.

sampling period at a fixed site 5 m above the ground level 200 m downwind of the A1 highway. The orientations of the highway and the sampling road are also reported in Fig. 2. More than 90% of the wind data collected (the other 10% was not included in the sampling) present an orientation varying from SW to S–SE (however from the emission source to the sampling points). In Fig. 2 the percentage of sampling time that the wind came from each 22.5 segment and the corresponding mean values (continuous line) and standard deviations of the wind velocity are also indicated. The consistency of the wind is important in order to average data collected in different days. In fact, Hitchins et al. (2000) found a completely different decay of total number concentration with increasing distances from a major road when the wind was blowing directly from, parallel to or away in respect to the sampling location. During every measurement period, the number of vehicles passing per minute in all six lines of the highway was monitored and recorded by a video camera. Three 1-min samples were randomly selected from every 10-min interval in order to estimate two different traffic conditions: a) the daily traffic presents a traffic density of 53 15 vehicles min1 (23% of HD vehicles) and b) the weekly traffic presents a traffic density of 95 12 vehicles min1 (12% of HD vehicles). The authors want to point out that emission related to diesel vehicles represent in Italy the dominant emissions even because the gasoline light-duty vehicles represent a roughly 50% of the total vehicles. As regard vehicle speed, it is in Italy higher in respect to other Western countries such as US and Australia: the average vehicle speed along the analyzed highway ranged from 25 to 40 m s1 (90–140 km h1). 2.2. Instrumentation and methodology Particle number concentration and size distribution were measured by a Scanning Mobility Particle Sizer (SMPS 3936, TSI Inc.) and an Aerodynamic Particle Sizer (APS 3321, TSI Inc.) spectrometers. Flexible, conductive tubing was used for sampling to minimise the losses due to electrostatic forces. In addition we have corrected the measurement data both for the diffusion losses (Chen et al., 1998; Birmili et al., 1997; Reineking and Porstendo¨rfer, 1986) and for the presence of aggregates using IA theory (Lall and Friedlander, 2006) assuming the primary particle diameter equal to 30 nm. These corrections are absolutely necessary to avoid an uncorrected estimation of the PSD. In particular, diffusion is the primary transport mechanism for particles smaller than 100 nm and the corresponding has to be applied in order to avoid an underestimation of smaller particles. Corrections for the presence

of aggregate are also important because the data based on spherical particles can lead errors in the mobility size data interpretation, by underestimating surface area and overestimating volume (and hence mass) distributions. The accuracy of the CPC was verified in the TSI laboratory in High Wycombe, UK few days before the starting of the experimental campaign, by means of monodisperse polystyrene latex spheres. The postprocessing analysis was performed through the Aerosol Instrument ManagerÒ and Data MergeÒ (TSI Inc.) software, together with authors’ self-made subroutines. Measurements were made at distances of 20, 30, 100, 150, 400 m (downwind in respect to the highway) and 300 m upwind as background values (these distances are referred to the centre of the highway). To check the effect of variations of the source with time, the closest point to the source was used as reference point. Samples were taken alternatively from this point and from each of the more distant points.

3. Results and discussion 3.1. PSD spatial evolution near the highway Fig. 3 shows the ultrafine size distribution at different distances from the A1 highway in the case of a) weekly traffic and b) daily traffic. The reported data represent the average values of the tests carried out. Only one dominant particle mode was observed for all sampling locations in the case of weekly traffic. At 30 m downwind this mode occurred around 7 nm with a modal number concentration of 6.0 105 part. cm3. This mode persisted at distances up to 400 m without shifting to a larger size. The UFP concentrations measured at 400 m downwind the A1 highway were still different from the background concentrations. The obtained results agree very well the ones reported in Zhu et al. (2004) and referred to the 405 freeway (with a dominant gasoline vehicle emission, in winter with a mean temperature of 23.2 C). The differences between the UFP concentrations measured at 400 m downwind the A1 highway in respect to the background concentrations (in Zhu et al., 2004 they were compared at 300 m) can be roughly explained with the higher mean wind speed (3.1 m s1 in this study in respect to 1.3 m s1 in Zhu et al., 2004). The higher the wind speed from the highway towards the sampling points, the greater the distance from the highway influenced by traffic emissions (Hitchins et al., 2000). The most relevant difference with Zhu et al. (2004) regards the mode number concentration (1.8 105 part. cm3 in Zhu et al., 2004). This is, probably, due to the diffusion correction that was


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distance from the highway to approximately half of its value at 30 m somewhere between 100 and 150 m. This decay agrees very well the trends reported in Hitchins et al. (2000) and Zhu et al. (2002a,b, 2004). The maximum total number concentration measured at 20 m downwind the highway during weekly traffic conditions was equal to 1.9 105 0.5 105 part. cm3, about 27 times greater than that at the background sampling site. In the same Fig. 4, the solid line represents the best fitting exponential decay curve, determined using Origin 6.0 software non-linear curve fitting procedure. The best fitting exponential decay equations and R2 values are also given in the figure. Fig. 4b compares the decay of particle number concentrations near the A1 highway in five size ranges during weekly traffic conditions: 6–12 nm, 12–25 nm, 25–50 nm, 50–100 nm and 100– 220 nm. Total particle number concentration in the 6–25 nm size range accounted for more than 60% of the total particle number concentration. It sharply decays (around 60% before 100 m) and the trend is similar to the other size ranges analyzed. 3.3. Surface area concentration decay Fig. 5a shows the decay curves of particle surface area concentration during weekly traffic conditions evaluated using the SMPS/

Fig. 3. Ultrafine particle size distribution at different sampling locations near the A1 highway during a) weekly and b) daily traffic. Measurements are made on April 18th, 2008 by means of a SMPS/APS tandem correcting measurements data for diffusion losses and presence of aggregates.

performed only by the authors (the mode number concentration without the diffusion correction decreases to 1.4 105 part. cm3). As regards daily traffic emissions with a higher percentage of diesel vehicles, Fig. 3b reports the UFP size distribution at different sampling locations. The predominant mode presents similar trends in respect to the ones observed during weekly traffic conditions. By the way, a second mode at about 20 nm is clearly shown at 20 m downwind the A1 highway, as found also in Zhu et al. (2004) during the wintertime along the 710 freeway. In both these cases, the percentage of HD diesel trucks is higher, ranging from 25 to 35%. The higher decay of the second mode in this study in respect to Zhu et al. (2004) can be related to the higher wind speed and, consequently, a stronger atmospheric dilution. 3.2. Daily and weekly concentration decays Fig. 4a shows the total particle number concentration decays at increasing downwind distance from the A1 highway for weekly and daily traffic conditions. Because of atmospheric dilution, the number concentration dramatically dropped with increased

Fig. 4. Decay of a) total particle number concentrations during weekly and daily traffic conditions and b) in several size ranges during weekly traffic emissions.

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Fig. 6. Relative decay of mass, surface area and number concentrations versus downwind distances from the A1 highway during weekly traffic conditions.

used hypothisizing, on the basis of an algorithm well described in Fine et al. (2004) and Sioutas et al. (1999), a constant value of the particle density equal to 1.7 g cm3. As reported in other studies (Zhu et al., 2002b; Hitchins et al., 2000) the mass concentrations decrease by only a few percent in respect to the maximum value measured at the downwind edge of the highway. The PM2.5/PM10 determined ratio is 0.63 (varying from 0.64 at 30 m downwind to 0.63 at 400 m downwind the A1 highway), typical of traffic exposed site not separated by topographic obstacles (Gehrig and Buchmann, 2003). 4. Conclusions

Fig. 5. Decay of a) total surface area concentrations during weekly traffic conditions and b) total surface area concentrations in the 6–220 size range during daily traffic emissions at several downwind distances from A1 highway.

APS tandem and considering a 30 nm primary particles aggregates diameter. The solid line in Fig. 5a represents the best fitting exponential decay curve, determined using Origin 6.0 software non-linear curve fitting procedure. The best fitting exponential decay equations and R2 values are also given in the figure. In the same figure, the surface area concentration decay in the 6–220 nm, 220–723 nm and 0.723– 20 mm size ranges is also reported. It is clear that, in order to estimate the decay of the surface area concentration, it is necessary to extend the monitor to the 200–723 nm size range. Because of atmospheric dilution, the total surface area concentration dropped with increased distance from the highway to approximately half of its value at 30 m around 150 m. In Fig. 5b a comparison between the surface area concentration evaluated by the authors in the 6–220 nm size range during daily traffic conditions (with a high percentage of high-duty vehicles) and the results obtained by Zhu et al. (2004) near the 710 freeway is reported, showing a very good agreement. Fig. 6 shows the relative decay curves for total number, surface area, PM2.5 and PM10 concentrations at increasing downwind distances from the A1 highway during weekly traffic conditions. For the evaluation of the mass concentration, the SMPS/APS tandem was

In this study we have measured the decay of the number, surface area and mass concentrations near the ‘‘Autostrada del Sole’’ A1 highway in the centre of Italy, Cassino. The A1 highway traffic was monitored showing two conditions: a) a daily traffic characterized by 53 15 vehicles min1 passing the sampling site in both directions (23% of HD vehicles) and b) a weekly traffic, with a traffic density of 95 12 vehicles min1 (12% of HD vehicles). The following observations are made: - during weekly traffic conditions a total number concentration of 1.9 105 0.5 105 part. cm3, about 27 times greater than that at the background sampling site, was measured at the downwind edge of the highway; - in the typical weather condition analyzed (wind blowing directly from the highway to the sampling sites with a mean speed equal to 3.1 m s1) the number concentration decays to about half of the maximum occurring at the edge of the highway, at a distance of approximately 100 m from the highway. The dilution seems to be predominant in the conditions analyzed; - the decay of the total surface area concentration (determined in the 6 nm–20 mm size range) shows a maximum value of 8.0 108 nm2 cm3 (around 3 times greater than that at the background sampling site) and with half of this value occurring at a distance of approximately 150 m from the highway; - the trends of PM2.5 and PM10 levels show a slight decay. The authors conclude that it was very significant to analyze an Italian highway particle emission by comparing the results with similar studies carried out in US and Australia characterized by


different mean speed velocity and diesel vehicle percentage. In particular, the evolution of size distribution and the particle number concentration decay are similar to the experimental data referred to US and Australian studies, even if in these studies the traffic density was much higher in respect to our study. Although, the emissions from a highway depend on several aspects (for example vehicle type, emission control equipment, fuel type, condition of the vehicles, fraction of cold/hot starts, atmospheric temperature and humidity), in our opinion the very high average speed along Italian highways represents the most important influencing parameter. On this basis, also near Italian highway, personnel living and working in close proximity to a main road will likely be exposed to levels of UFP higher than background levels. Acknowledgements The authors would like to thank Prof. Michael R. Zachariah (University of Maryland, College Park, USA) for TEM analysis support and valuable discussions in writing this paper. References Agarwal, J.K., Remiarz, R.J., 1981. Development of an Aerodynamic Particle Size Analyzer. National Institute for Occupational Safety and Health (NIOSH). Airborne Particles Expert Group, 1999. Source Apportionment of Airborne Particulate Matter in the United Kingdom. Report for the Department of the Environment, Transport and the Regions, the Welsh Office, the Scottish Office and the Department of the Environment, Northern Ireland. Anastasio, C., Martin, S.T., 2001. Atmospheric Nanoparticles, vol. 44. Mineralogical Society of America, Washington, DC, pp. 293–349. Barone, T., Lall, A.A., Zhu, Y., Yu, R., Friedlander, S.K., 2006. Inertial deposition of nanoparticle chain aggregates: theory and comparison with impactor data for ultrafine atmospheric aerosols. J. Nanopart. Res. 8, 669–680. Birmili, W., Stratmann, F., Wiedensohler, A., Covert, D., Russell, L.M., Berg, O., 1997. Determination of differential mobility analyzer transfer functions using identical instruments in series. Aerosol Sci. Technol. 27, 215–223. Brunekreef, B., 2000. What properties of particulate matter are responsible for health effects? Inhal. Toxicol. 12 (Suppl. 1), 15–18. Buonanno, G., Ficco, G., Stabile, L., 2008. Size distribution of ultrafine particles and trends of concentration near a linear (major highway) and point source (waste incinerator). In: Proceedings of the Advanced Atmospheric Aerosol Symposium, 9–12 November, Naples, Italy. Cass, G.R., Hughes, L.A., Bhave, P., Kleeman, M.J., Allen, J.O., Salmon, L.G., 2000. The chemical composition of atmospheric ultrafine particles. Philos. Trans. R. Soc. Lond. A 358, 2581–2592. Chen, D.R., Pui, D.Y.H., Hummes, D., Fissan, H., Quant, F.R., Sem, G.J., 1998. Design and evaluation of a nanometer aerosol differential mobility analyzer (nanoDMA). J. Aerosol Sci. 29, 497–509. Cheng, Y.S., 2003. Aerosol deposition in the extrathoracic region. Aerosol Sci. Technol. 37, 659–671. Cheng, Y.S., Zhou, Y., Chen, B.T., 1999. Particle deposition in a cast of human oral airways. Aerosol Sci. Technol. 31, 286–300. Dockery, D.W., Pope III, A., Xu, X., Spengler, J.D., Ware, J.H., Fay, M.E., Ferris Jr., B.G., Speizer, F.E., 1993. An association between air pollution and mortality in six US cities. J. Med. 329, 1753–1759. Dye, A.L., Rhead, M.M., Trier, C.J., 2000. The quantitative morphology of roadside and background urban aerosol in Plymouth, UK. Atmos. Environ. 34, 3139–3148. EN 12341, 1999. Determination of the PM10 Fraction of Suspended Particulate Matter. Reference Method Field Test Procedure to Demonstrate Reference Equivalence Measurement Methods. EN 14907, 2005. Ambient Air Quality – Standard Gravimetric Measurement Method for the Determination of the PM2.5 Mass Fraction of Suspended Particulate Matter. EPA 40 CFR, 1997. Protection of Environment Part 50–51. EPA, 2000. National Air Pollution Emission Trends 1900–1998, 1998 Emissions. United States Environmental Protection Agency. Fine, P.M., Shen, S., Sioutas, C., 2004. Inferring the sources of fine and ultrafine particulate matter at downwind receptor sites in the Los Angeles Basin using multiple continuous measurements. Aerosol Sci. Technol. 38 (12), 182–195. Friedlander, S.K., 2000. Smoke, Dust and Haze: Fundamentals of Aerosol Dynamics. Oxford University Press, New York. Gehrig, R., Buchmann, B., 2003. Characterising seasonal variations and spatial distribution of ambient PM10 and PM2.5 concentrations based on long-term Swiss monitoring data. Atmos. Environ. 37 (19), 2571–2580. Harrison, R.M., Shi, J.P., Xi, S.H., Khan, A., Mark, D., Kinnersley, R., Yin, J.X., 2000. Measurement of number, mass and size distribution of particles in the atmosphere. Philos. Trans. R. Soc. Lond. A 358, 2567–2579.

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