- Email: [email protected]
Influence of meteorological variability upon aerosol mass size distribution
Atmospheric Research 94 (2009) 330–337
Contents lists available at ScienceDirect
Atmospheric Research j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / a t m o s
Influence of meteorological variability upon aerosol mass size distribution J.F. Nicolás a,⁎, E. Yubero a, C. Pastor a, J. Crespo a, A. Carratalá b a b
Laboratory of Atmospheric Pollution (LCA), Miguel Hernández University, Av. de la Universidad s/n, Edif. Alcudia, 03202, Elche, Spain Department of Chemical Engineering, University of Alicante, P. O. Box 99, 03080, Alicante, Spain
a r t i c l e
i n f o
Article history: Received 13 March 2009 Received in revised form 27 May 2009 Accepted 15 June 2009 Keywords: Size distribution Precipitation Wind Stagnant episodes Coarse and accumulation modes
a b s t r a c t Aerosol mass size distribution has been measured by using an optical particle counter. The measurements were done in an urban background location in the western Mediterranean during winter 2006. The study has been focused in determining the mass size distribution under special meteorological conditions like moderate rain, considerable winds and high atmospheric stability. The results obtained showed a mass predominance of accumulation mode during rain and high stability periods although for different reasons. In the case of rain, it is due to greater atmospheric cleansing effectiveness that rain has upon coarse mode particles. However, during stagnant periods, the meteorological situation favored coagulation processes among nucleation mode particles giving like result a mass increase in the accumulation mode. Finally, strong winds favor the resuspension of the largest particles and the dispersion of particles with sizes inferior to 7.5 μm. Similar results have been reproduced using principal component analysis (PCA). In this way, three components were identified. The first (PC1) represents particles in the accumulation mode. The second component (PC2) is constituted by coarse particles to 7.5 μm, and the third (PC3) corresponds to coarser particles. The contribution of each group to the overall average concentration was determined: 27.2% corresponds to particles with sizes belonging within the first component, 35.4% to PC2 and 37.3% to PC3. Important percentage variability for each component under meteorological episodes has been obtained. Results obtained showed an important increase of PC1 during Rainy Days (53.8%) and High Pollution Days (40.2%). Contrary to this on Windy Days this component decreases to 7.4%. However, during this kind of day PC3 increases to 64.6%. © 2009 Elsevier B.V. All rights reserved.
1. Introduction The interest in the determination of the atmospheric aerosol size distribution in a definite environment is because this allows evaluating aerosol properties, like residence time and origin. Different modes are identified within distributions that are generally related to the formation mechanisms of the particles comprising them (Morawska et al.,1999). The nucleation mode, particles smaller than 0.1 μm, mostly originates from condensation of hot vapors during combustion processes (Seinfeld and Pandis,1998). Accumulation mode particles, extending from 0.1 to 1 μm (Whitby and Sverdrup, 1980), are formed from the ⁎ Corresponding author. Tel.: +34 966658325; fax: +34 966658397. E-mail address: [email protected] (J.F. Nicolás). 0169-8095/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.atmosres.2009.06.007
coagulation of nucleation mode particles, as well as from heterogeneous nucleation of secondary sulfate, nitrate, ammonium and organics generated by atmospheric reactions. Coarse mode particle sources (N1 μm) are mechanical processes, both natural and anthropogenic. The relative importance of each of these modes varies depending upon the environment sampled and which type of size distribution is addressed, either mass or number. In this way, it is possible to find that 80% of the total number of particles in urban areas belong to nucleation mode (Morawska et al., 1998; Wichmann et al., 2000; Rodríguez et al., 2007), while the aerosol mass is predominantly concentrated in the coarse mode (Salma et al., 2002). It is rare to find the three modes cited, observing instead only bimodal distributions. Therefore, even in environments influenced by traffic, the mass distribution might only feature the accumulation and coarse
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337
modes (Morawska et al., 1999). Traffic sources in urban areas are capable of modulating size distributions. In such a way, motor vehicle emissions constitute the most significant source of particles present in the nucleation mode (Zhu et al., 2002). Non-emission traffic also contributes to aerosol mass, like coarse mode resuspension (Chen et al., 2006; Nicolás et al., 2009a) or vehicular brake abrasion dusts in accumulation and coarse modes (Thorpe and Harrison, 2008). Different physicochemical processes related to atmospheric aerosols are those which provoke changes in the size distribution profile. Processes like nucleation increase the number of particles, whereas coagulation or dry and wet deposition reduce them. Condensation does not affect the number of particles but does affect their mass (Tunved et al., 2004). The influence of inter- and intra-modal effects has also been determined, thus when the number concentration of coarse mode increases, like for example during dust events, it may reduce the number concentration of accumulation mode due to the coagulation from this mode to coarse mode (Jung et al., 2002). However, it is difficult to quantify this effect since accumulation mode particles are strongly influenced by local emissions and the growth of nucleation mode particles (Kim et al., 2007). Meteorological variability can generate processes that, as has been indicated, modify the size distributions. Relative humidity values above 50% affect particle masses (Hänel, 1976). However, with high humidities the relative mass increase in the fine mode (d b 1 µm) differs from the coarse one, due to fine mode aerosols consisting predominantly of soluble material while the coarse mode has a strong crustal component (Hitzenberger et al., 1997). Wet removal stands out as the main process capable of removing aerosol mass (Tunved et al., 2004). Precipitation scavenging mechanisms vary depending upon the distribution mode analyzed. The nucleation mode material scavenged is mainly due to Brownian diffusion, in the accumulation mode this is due to interception, and in the coarse mode this is from inertial impaction (Seinfeld and Pandis, 1998). The scavenging effectiveness from precipitation depends on the collection efficiency. This parameter is elevated in the nucleation and coarse modes, but not so in the accumulation (Radke et al., 1980; Andronache, 2003), and this is because the accumulation mode dominates the size distribution after moderate rains (Andronache, 2003). Other meteorological situations capable of influencing the particle distribution are those characterized by stagnant air masses coinciding with high surface atmospheric pressure and an absence of strong winds. These situations favor the accumulation of pollutants within cities and the progressive displacement of aerosol size distribution towards the accumulation mode due to either coagulation between particles or between particles and semi-volatile compounds (Pey et al., 2008). The primary objective of this investigation consists in acquiring mass size distributions within urban surroundings during periods characterized by special meteorological conditions like periods of precipitation, considerable winds and high atmospheric stability. The degree of influence that each meteorological event has on the mass distribution of particles can then be determined. In order to be able to discriminate the resulting effect strictly from each meteorological event,
331
the urban contribution, mainly due to traffic, must be removed from the mass size distribution obtained during these episodes. 2. Study area and data collection 2.1. Features of the study zone The sampling campaign was conducted in Elche, a city of 228,000 inhabitants in southeastern Spain. Elche is 12 km from the Mediterranean coast (38°16′N; 0°41. 5′W), and lies 86 m above sea level. The monitoring station, classified as urban background, was placed on the roof of a 15 m high building located in the city center. The urban area is situated in a semi-arid Mediterranean region surrounded by barren soil due to scarce annual precipitation (less than 250 l m− 2). Most rain occurs during autumn (~ 43%) and winter (~ 31%). Mediterranean cyclogenesis is the primary atmospheric condition causing this, and to a lesser extent Atlantic advection, although other convective situations during the summer can be sources for rain. The study area can be classified as having a semi-arid Mediterranean climate. Average temperatures oscillate between 12 °C in January and 26 °C in July. The wind, as well as its speed, presents clear seasonal variation. Northwest (NW) winds with averages of about 2 m s− 1 are common during winter. Predominant in the summer period are southeast (SE) winds whose average speeds are inferior to those of winter. With the suitable wind, soil particles can reach the city of Elche on dry days because eroded topsoils are found northwest of Elche. Due to the proximity of the Mediterranean Sea, the effects of marine breezes (SE winds) are noticed at the sampling point on approximately 40% of the days of the year. They are, however, mainly concentrated during the months of spring and summer, making up 75% of the total. One feature of Elche is its high density of motor vehicles. In the study period there were more than 140,000 licensed. Motor vehicles constitute the main source of anthropogenic pollution in the urban area. 2.2. Data collection Size distributions were measured with a Grimm 1108 optical particle counter. This instrument determines the particle number concentration in 16 particle size channels from 0.23–0.3 µm to N20 μm. Conversions to the mass size distributions are carried out using an internal algorithm. The uncertainty in the determination of the total mass concentration is between 10 and 20%. The measurements were made in winter, from January to March 2006 (60 days) at 10 min intervals. Twenty-four hour averaged size distributions were subsequently calculated based on the counter data. Local meteorological data and gaseous pollutant concentrations were obtained from the Environmental Surveillance Network of the regional Government of Valencia. Atmospheric soundings came from the Department of Atmospheric Science at the University of Wyoming (http://weather.uwyo. edu/upperair/sounding.html). NCEP meteorological maps (Kalnay et al., 1996) were also used.
332
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337
3. Methodology applied In order to determine how the variability of certain meteorological parameters influences in both the mass distribution of atmospheric particles as well as in the different groups in which these can be included based on their origin, four different types of days within the campaign were chosen. They were characterized as such when the magnitude of one or a number of meteorological variables stood out above the corresponding average values obtained for the complete set of days that the campaign lasted. In this way, four groups of days were obtained in which: a) Precipitation occurred (Rainy Days—RD) caused by Atlantic advection. The dominant low pressure had an average value of 1000 mb at sea level during the episode. This was located north of the Canary Islands, a synoptic situation usually causing torrential rains in the study area (Millán et al.,1995), although in this occasion they were only of moderate intensity. b) Very low mixing layer heights coupled with very low ground-level wind speeds favored the accumulation of polluting agents in the urban atmosphere (High Pollution Days—HPD). The Holtworth method was used to determine the mixing layer thickness (Seibert et al., 2000). During the days the episode lasted, the mixing layer thickness measured at 12:00 UTC, had an average value inferior to 500 m. There was even a thermal inversion on one day of the episode, causing greater confinement of the suspended particulate matter in the urban atmosphere of Elche due to the elevated atmospheric stability. c) Consecutive days characterized solely by rather elevated average wind speeds, v N 3 m s− 1 (Windy Days—WD). d) A fourth group of days was considered where no meteorological variable stood out with either an elevated or reduced value (Normal Days—ND). The meteorological characteristics defining these groups of days appear in Table 1. The number of days making up each group is four. Furthermore, they fulfill the particularity of being consecutive. Once the days corresponding to each type of meteorological event are defined and characterized, comparisons of their respective mass size distributions can be achieved. In order to be able to discriminate the effect that these meteorological episodes present upon the mass size distribution, urban and background contributions must be subtracted from these distributions. To do this, the differences between the distributions presented on the days with meteorological events and those obtained on Normal Days will be determined. The urban Table 1 Summary of meteorological parameters on different types of days in Elche during winter 2006.
Fig. 1. a) Average particle mass size distribution in Elche during winter; b) mass size distribution components.
contribution, mainly due to traffic, and the background aerosol are similar for each of the four groups of analyzed days. Concentration differences among average mass size distributions of the types of meteorological episodes were checked using Tukey's test. This test constitutes a post hoc comparison, as it must be applied once the Anova (analysis of the variance) general hypothesis, that all the averages are equal, is rejected. It is useful to find out which specific averages are those differing among themselves, from which it provides greater information. A multivariate statistical technique, principal component analysis (PCA), was employed to identify particle source groups at the monitoring site (using the SPSS software package, version 16). PCA reduces the original variables of a large dataset to a smaller number of uncorrelated principal components (PC) that explain a large fraction of the total variance (Statheropoulos et al., 1998). In the present study, PCA with Varimax rotation was applied.
Periods
Duration
PA
WV
WD
T
RH
Rain (RD) High Pollution (HPD) Wind (WD) Normal (ND) Total
27–30 January 7–10 February 6–9 March 23–26 March 27 January–27 March
28.7 0.2 0 0 40.8
2.6 0.9 3.9 2.1 2.5
NW – NW SW –
7.1 11.6 17.5 18.0 13.2
71 65 37 46 57
4.1. Global results of the campaign. Particle grouping by size according to its origin
PA: precipitation (mm); WV: average wind speed (m s− 1); WD: average wind direction; T: temperature (°C); RH: relatively humidity (%).
The average concentration value for the whole study period was 63.5 µg m- 3, with a standard deviation of 25.7 µg m- 3. The
4. Results and discussion
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337 Table 2 r/p-values between PCs and NOx, wind velocity and relative humidity.
PC1 (µg/m3) PC2 (µg/m3) PC3 (µg/m3) a
NOx (µg m− 3)
Wind velocity (m s− 1)
Relative humidity a (%)
0.41/0.002 0.69/0.000 0.04/0.772
− 0.55/0.001 − 0.36/0.043 0.56/0.000
0.78/0.000 0.03/0.761 − 0.67/0.000
Potential correlation (y = axb).
particle mass size distribution averaged for the whole study period is plotted in Fig. 1a. Coarse mode particles (d N 1 µm) account for about 70% of the total mass. The spectrum contains an important mass contribution of particles N20.0 μm. These results suggest that some or all of the following processes, like resuspended road, soil dust or construction activities are relevant in the study area. To confirm the relationship among the different sizes of particles, a principal component analysis (PCA) with Varimax rotation was performed. Ten-minute mass concentrations for each particle size range were selected as variables for the analysis, whose results are presented in Fig. 1b. The analysis gives three components with eigenvalues higher than 1, explaining 91% of the total variance. The first component (PC1) shows an elevated correlation with particles smaller than 0.90 μm and can be associated with the processes responsible for the generation of particles in the accumulation mode. This component explains almost 50% of the total variance.
333
PC2 presents the highest factor loadings for particles at the end of the accumulation mode and beginning of the coarse mode, to 7.5 µm. This component, based on the sizes it includes, could be related to particles introduced into the atmosphere by vehicle-induced resuspension (Chen et al., 2006). To a lesser extent it can also be related to marine aerosol (Mazzei et al., 2006). In fact, marine aerosol was recorded at the sampling point during the winter, although in far lesser concentrations than those obtained during the summer period (Nicolás et al., 2009b). Finally, the variables correlated to PC3 are the coarser particles. This component could be interpreted as wind resuspension of soil particles from the semi-arid areas surrounding Elche. PC3 is favored by low relative humidities and high wind speeds (Nicolás et al., 2009a). In order to reaffirm the relations shown between the diverse particle sources and obtained components, they were correlated with the NOx levels, a variable representative of the traffic levels in the city, with the wind speed and with the relative humidity (RH). Table 2 shows Pearson's correlation coefficients (r) and the obtained p-values. All the correlations are linear, with the exception of those carried out with the RH, because they adjust quite better to a potential function. All the correlation coefficients shown in Table 2 are statistically significant at the 95% confidence level, excluding the relation between PC3–NOx and PC2–RH. The coefficients between PC2 and NOx, (see correlation graph in Fig. 2a), and
Fig. 2. Correlations between: a) PC2 and NOx; b) PC1 and wind velocity; c) PC3 and RH; and d) PC1 and RH.
334
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337
between PC3 and the wind speed (0.56), confirm that, to a certain extent, vehicle-induced resuspension and wind resuspension of soil particles from the semi-arid areas surrounding Elche are possible particle sources related to components PC2 and PC3. The negative correlation coefficient between PC1 and the wind indicates that the wind speed increase produces a reducing effect in the mass concentration registered by this component. Nevertheless, the inverse relation between both variables adjusts better to exponential decay, shown in Fig. 2b. On the other hand, the three components indicate a different behavior with the humidity. Component PC2 does not present any correlation, whereas PC1 and PC3 do, however differently. In both cases the correlation, as previously indicated, adjusts better to a potential than to a linear function. In the case of component PC3, the equation (Fig. 2c) shows an inverse and practically quadratic dependency, whereas component PC1 (Fig. 2d) displays a cubical dependency. This increase in mass along with the humidity of accumulation mode particles, included in PC1, has already been proven in other studies (Hitzenberger et al., 1997). Based on the three groups of particles, the contribution of each one to the total mass recorded was determined for the total number of days of the campaign. Determined as the sum of the average concentrations recorded during the entire period for each size interval, (63.5 µg m- 3), 27.2% of the average mass concentration corresponds to particles with sizes belonging within the first component (PC1), 35.4% to PC2, and 37.3% to PC3. With the correlation equation shown in Fig. 2a and the mass percentage attributable to PC2, the mass concentration of this component related to traffic (road resuspension) can be quantitatively estimated. The method of assigning the value of the ordinate at the origin (6.3 ± 2.0 μg m- 3) to the mass
unrelated to traffic was used for this. This method has been used in several studies (Harrison et al.,1997; Harrison et al., 2001). In this sense, if the average mass contribution of the component is 22.5 µg m- 3 (35.4% of the total), then 16.2 µg m- 3 in this component can be considered attributable to road resuspension from traffic. 4.2. Variation of the mass contribution of each component per meteorological event The average percentages that each component contributes to the overall average concentration value vary according to the meteorological episode. The component distribution, in percentages, for each meteorological event can be observed in Fig. 3. Also the average mass concentration on these days is shown. Important particle concentration reductions occur on Rainy Days (RD), specifically some 60% with respect to the average concentrations for the total period. Particulate matter levels generally reduce considerably in all regions of Spain during Atlantic advection episodes, showing minimum values in their annual temporal evolution, independent of the type of environment sampled (Rodríguez et al., 2003; Querol et al., 2004; Pey et al., 2008). High Pollution Days (HPD) undergo large concentration increases, with increases approaching 40%. This mass concentration increase under these atmospheric conditions has been widely shown (Artíñano et al., 2003; Rodríguez et al., 2003). Windy Days (WD) and Normal Days (ND) do not present remarkable variations in the mass concentrations. Fig. 3 shows important percentage variability for each component depending on the meteorological event. It shows the important contribution of PC1 during the HPD, and above all the RD. Relative humidity levels were high on both types of days
Fig. 3. Percentage contribution to mass concentration for: a) Rainy Days; b) High Pollution Days; c) Windy Days; and d) Normal Days.
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337
335
(see Table 1), confirming the positive dependency between this component and the RH (see Fig. 2d). It is noteworthy that more than one-half of the concentration during Rainy Days is due to the mass contribution within the accumulation mode. Contrary to this, during ND this component presents a meager percentage, and on WD, comprises only 7.4% in its contribution. Components two and three present similar percentages on all types of days, except for WD, when PC3 (particles with d N 7.5 µm) show a contribution considerably superior to PC2, with 64.6%. This indicates the great importance of the very coarse particulate matter during these types of days. 4.3. Meteorological episode characteristic size distribution profiles Fig. 4 shows the mass size distribution for each type of day analyzed. The mass concentration value for each size is the result of averaging the recorded values of each size obtained during the four days making up a certain episode. It is important to point out the stability of the mass size distribution during each day of each episode. In this way, for example, all four days characterized as High Pollution present their maximums and minimums in the same particle sizes and their daily mass concentrations by sizes are very similar as well. As is possible to verify, depending on the particle size the four distributions present either similar or different tendencies. Each distribution presents minimums at the division between the accumulation and coarse modes. There are only two clear maximums within the accumulation mode; the first occurring on RD (the only clear maximum this distribution showed), and another maximum on HPD. There is trimodal distribution on HPD days since there are two more maximums in the coarse mode: the first at 2–3 µm and a greater second one between 5 and 7.5 µm. For the distribution on Windy Days, one relative maximum appears at 7.5–10.0 μm, but above all a far more significant maximum clearly stands out for particles N20 μm. Tukey's test was conducted in order to determine if the concentration differences for each particle size in the four distributions from Fig. 4 are statistically significant to a 95% confidence level. The test results have shown that the differences are statistically significant (p-value b0.05) for
Fig. 4. Average mass size distribution for: Windy, High Pollution, Rainy and Normal Days.
Fig. 5. Difference between the mass size distribution for Windy, High Pollution and Rainy Days versus Normal Days.
the four distributions among the sizes 0.23–0.4 µm, 0.9–5. 0 μm and N15 µm. The differences are not significant (p-value N0.05) for: WD and ND for sizes 0.4–0.65 µm and 5.0–10. 0 μm. RD and WD for sizes 0.65–0.9 µm. HPD–WD for sizes 7.5–10. 0 μm. HPD–ND for sizes 10.0–15.0 µm. Fig. 5 shows the concentration differences in sizes for HPD, RD and WD plotted versus ND. This was done to highlight the repercussions each meteorological event has upon each particle size with respect to a day in which no differential meteorological episodes occur. Fig. 5 shows how Rainy Days contribute to a slight mass increase in the accumulation mode and an important reduction in the coarse mode concentration when compared to days without remarkable meteorological events. This confirms that coarse mode atmospheric particle cleansing is effective with moderate precipitation, but not so in the accumulation mode. One consequence of this is that the resulting mass size distribution during precipitation is dominated by accumulation mode particles, as Fig. 4 shows. High Pollution Days are characterized by increasing particle concentrations when compared to Normal Days. This increase occurs primarily in the accumulation mode, being some 98% of the total. Accumulation mode predominates on HPD, like during RD, but for different reasons. On HPD the meteorological situation provokes the settlement of larger particles, and favors coagulation among particles in the nucleation mode. A mass increase in the accumulation mode is one effect of this situation. On the other hand, Windy Days distinguish themselves by producing a significant mass increase in the largest particles (N20.0 µm) versus Normal Days; the average concentration increase for these on WD was 12.5 µg m− 3 greater than what occurred on ND. The mass size distribution on these days shows a negative profile from the accumulation mode up to particles having diameters of 7.5 µm, which could indicate that the wind neither transports nor resuspends this type of particle and possibly favors their dispersion into the urban environment. Over the course of the day the evolution of the mass size distribution for all episodes is different and somewhat associated with the temporal evolution of the meteorological parameters characterizing them. Thus on Rainy Days the
336
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337
minimum values of coarse mode particles occurred precisely during the hours of the precipitation. On High Pollution Days the greatest mass concentrations of particles corresponding to the accumulation mode coincided with the highest registered hourly values of the relative humidity. For their part, Windy Days showed a considerable increase in the heaviest particles during the middle hours of the day, which coincided with the hours having the highest wind speeds. 5. Conclusions Coarse mode particle concentrations accounted for about 70% of the total mass for the entire study period. This reflects the importance of sources that emit coarse particles in the study area, like resuspended road, soil dust and construction activities. Nevertheless, this high percentage can be substantially reduced under certain meteorological situations, be they either periods of rain or high atmospheric stability. Significant linear correlation was noticed between traffic and a portion of coarse mode particles (d b 7.5 µm), confirming vehicle-induced resuspension as their possible origin. Good correlation was also considered, in this case of an exponential type, between the wind speed and mass concentrations of accumulation mode particles. The influence of the humidity resulted in being different depending upon the size ranges. Accumulation mode particles showed positive potential correlation, whereas the largest particles (d N 7.5 µm) did so negatively. No significant correlation was observed for coarse mode particles with diameters inferior to 7.5 µm. The most relevant conclusions of the analysis of the influence that the three types of meteorological episodes studied (precipitation, wind and high atmospheric stability) have upon the mass particle distribution reflect that particle masses during episodes of rain and elevated stability were concentrated mainly in the accumulation mode, although due to diverse causes. In the case of rain, this is due to greater atmospheric cleansing effectiveness that rain has upon coarse mode particles when compared to those in the accumulation mode. Contrary to this, the meteorological situation on High Pollution Days favored coagulation processes among nucleation mode particles, and bringing about mass increases in the accumulation mode. Situations characterized by high wind speeds favor the dispersion of particles with sizes inferior to 7.5 µm in the urban environment, which in turn bring about a significant increase in the mass attributable to the largest particles (N20 µm). Acknowledgements We thank the Elche City hall for allowing access to their facilities for the placement of the instruments, the Air Quality Surveillance Network of the Valencian Community Regional Government for supplying data, and Paul Nordstrom and Guillermo Escribano for their assistance in this work. References Andronache, C., 2003. Estimated variability of below-cloud aerosol removal by rainfall for observed aerosol size distributions. Atmospheric Chemistry and Physics 3, 131–143.
Artíñano, B., Salvador, P., Alonso, D.G., Querol, X., Alastuey, A., 2003. Anthropogenic and natural influence on the PM10 and PM2.5 aerosol in Madrid (Spain). Analysis of high concentrations episodes. Environmental Pollution 125, 453–465. Chen, J., Zheng, H., Wang, W., Liu, H., Lu, L., Bao, L., Ren, L., 2006. Resuspension method for road surface dust collection and aerodynamic size distribution characterization. China Particuology 4, 300–303. Jung, C.H., Kim, Y.P., Lee, K.W., 2002. Simulation of the influence of coarse mode particles on the properties of fine mode particles. Journal of Aerosol Science 33, 753–767. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A., Reynolds, B., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.C., Ropelewski, C., Wang, J., Jenne, R., Joseph, D., 1996. The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society 77, 437–471. Hänel, G., 1976. The properties of atmospheric aerosol particles as functions of the relative humidity at thermodynamic equilibrium with the surrounding moist air. Advances Geophysics 19, 74–188. Harrison, R.M., Deacon, A.R., Jones, M.R., Appleby, R.S., 1997. Sources and processes affecting concentrations of PM10 and PM2.5 particulate matter in Birmingham (U.K.). Atmospheric Environment 31, 4103–4117. Harrison, R.M., Yin, J., Mark, D., Stedman, J., Appleby, R.S., Booker, J., Moorcroft, S., 2001. Studies of the coarse particle (2.5–10 µm) component in UK urban atmospheres. Atmospheric Environment 35, 3667–3679. Hitzenberger, R., Berner, A., Dusek, U., Alabashi, R., 1997. Humidity-dependent growth of size-segregated aerosol samples. Aerosol Science and Technology 27, 116–130. Kim, J., Jung, C.H., Choi, B.-C., Oh, S.-N., Brechtel, F., Yoon, S.-C., Kim, S.-W., 2007. Number size distribution of atmospheric aerosol during ACE-Asia dust and precipitation events. Atmospheric Environment 41, 4841–4855. Mazzei, F., D'Alessandro, A., Lucarelli, F., Marenco, F., Nava, S., Prati, P., Valli, G., Vecchi, R., 2006. Elemental composition and source apportionment of particulate matter near a steel plant in Genoa (Italy). Nuclear instruments and methods in physics. Research Section B: Beam Interactions with Materials and Atoms 249, 548–551. Millán, M., Estrela, M.J., Caselles, V., 1995. Torrential precipitations on the Spanish east coast: the role of the Mediterranean Sea surface temperature. Atmospheric Research 36, 1–16. Morawska, L., Thomas, S., Bofinger, N., Wainwright, D., Neale, D., 1998. Comprehensive characterization of aerosol in a subtropical urban atmosphere: particle size distribution and correlation with gaseous pollutants. Atmospheric Environment 41, 2145–2155. Morawska, L., Thomas, S., Jamriska, M., Johnson, G., 1999. The modality of particle size distributions of environmental aerosols. Atmospheric Environment 33, 4401–4411. Nicolás, J., Yubero, E., Galindo, N., Giménez, J., Castañer, R., Carratalá, A., Crespo, J., Pastor, C., 2009a. Characterization of events by aerosol mass size distribution. Journal of Environmental Monitoring 11, 394–399. Nicolás, J., Galindo, N., Yubero, E., Pastor, C., Esclapez, R., Crespo, J., 2009b. Aerosol Inorganic Ions in a Semiarid Region on the Southeastern Spanish Mediterranean Coast. Water air and soil pollution 201, 149–159. Pey, J., Rodríguez, S., Querol, X., Alastuey, A., Moreno, T., Putaud, J.P., Dingenen, R.V., 2008. Variations of urban aerosols in the western Mediterranean. Atmospheric Environment 42, 9052–9062. Querol, X., Alastuey, A., Rodríguez, S., Viana, M.M., Artıñano, B., Salvador, P., Mantilla, E., Santos, S.G.D., Patier, R.F., Rosa, J.D.L., Campa, A.S.D.L., Menéndez, M., 2004. Levels of PM in rural, urban and industrial sites in Spain. The Science of the Total Environment 334–335, 359–376. Radke, L.F., Hobbs, P.V., Eltgroth, M.W., 1980. Scavenging of aerosol particles by precipitation. Journal of Applied Meteorology 19, 715–722. Rodríguez, S., Querol, X., Alastuey, A., Viana, M.M., 2003. Events affecting levels and seasonal evolution of airborne particulate matter concentrations in the western Mediterranean. Environmental Science and Technology 37, 216–222. Rodríguez, S., Van Dingenen, R., Putaud, J.P., Dell'Acqua, A., Pey, J., Querol, X., Alastuey, A., Chenery, S., Ho, K.F., Harrison, R., Tardivo, R., Scarnato, B., Gemelli, V., 2007. A study on the relationship between mass concentrations, chemistry and number size distribution of urban fine aerosols in Milan, Barcelona and London. Atmospheric Chemistry and Physics 7, 2217–2232. Salma, I., Dal Maso, M., Kulmala, M., Záray, G., 2002. Modal characteristics of particulate matter in urban atmospheric aerosols. Microchemical Journal 73, 19–26. Seibert, P., Beyrich, F., Gryning, S.-E., Joffre, S., Rasmussen, A., Tercier, P., 2000. Review and intercomparison of operational methods for the determination of the mixing height. Atmospheric Environment 34, 1001–1027. Seinfeld, J.H., Pandis, S.N., 1998. Atmospheric Chemistry and Physics. Wiley, New York, USA.
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337 Statheropoulos, N., Vassiliadis, N., Pappa, A., 1998. Principal component and canonical correlation analysis for examining air pollution and meteorological data. Atmospheric Environment 32, 1087–1095. Thorpe, A., Harrison, R.M., 2008. Sources and properties of non-exhaust particulate matter from road traffic: a review. Science of the Total Environment 400, 270–282. Tunved, P., Ström, J., Hansson, H.C., 2004. An investigation of processes controlling the evolution of the boundary layer aerosol size distribution properties at the Swedish background station Aspvreten. Atmospheric Chemistry and Physics 4, 2581–2592.
337
Wichmann, H.E., Spix, C., Tuch, T., Wölke, G., Peters, A., Heinrich, J., Kreyling, W.G., Heyder, J., 2000. Daily mortality and fine and ultrafine particles in Erfurt, Germany. Part I: Role of Particle Number and Particle Mass, vol. 98. Health Effects Institute. Whitby, K.T., Sverdrup, G.M., 1980. California aerosols: their physicals and chemical characteristics. In: Hidy, G.M. (Ed.), The Character and Origins of Smog Aerosol. InWiley, New York, p. 495. Zhu, Y., Hinds, W.C., Kim, S., Shen, S., Sioutas, C., 2002. Study of ultrafine particles near a major highway with heavy-duty diesel traffic. Atmospheric Environment 36, 4323–4335.
Contents lists available at ScienceDirect
Atmospheric Research j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / a t m o s
Influence of meteorological variability upon aerosol mass size distribution J.F. Nicolás a,⁎, E. Yubero a, C. Pastor a, J. Crespo a, A. Carratalá b a b
Laboratory of Atmospheric Pollution (LCA), Miguel Hernández University, Av. de la Universidad s/n, Edif. Alcudia, 03202, Elche, Spain Department of Chemical Engineering, University of Alicante, P. O. Box 99, 03080, Alicante, Spain
a r t i c l e
i n f o
Article history: Received 13 March 2009 Received in revised form 27 May 2009 Accepted 15 June 2009 Keywords: Size distribution Precipitation Wind Stagnant episodes Coarse and accumulation modes
a b s t r a c t Aerosol mass size distribution has been measured by using an optical particle counter. The measurements were done in an urban background location in the western Mediterranean during winter 2006. The study has been focused in determining the mass size distribution under special meteorological conditions like moderate rain, considerable winds and high atmospheric stability. The results obtained showed a mass predominance of accumulation mode during rain and high stability periods although for different reasons. In the case of rain, it is due to greater atmospheric cleansing effectiveness that rain has upon coarse mode particles. However, during stagnant periods, the meteorological situation favored coagulation processes among nucleation mode particles giving like result a mass increase in the accumulation mode. Finally, strong winds favor the resuspension of the largest particles and the dispersion of particles with sizes inferior to 7.5 μm. Similar results have been reproduced using principal component analysis (PCA). In this way, three components were identified. The first (PC1) represents particles in the accumulation mode. The second component (PC2) is constituted by coarse particles to 7.5 μm, and the third (PC3) corresponds to coarser particles. The contribution of each group to the overall average concentration was determined: 27.2% corresponds to particles with sizes belonging within the first component, 35.4% to PC2 and 37.3% to PC3. Important percentage variability for each component under meteorological episodes has been obtained. Results obtained showed an important increase of PC1 during Rainy Days (53.8%) and High Pollution Days (40.2%). Contrary to this on Windy Days this component decreases to 7.4%. However, during this kind of day PC3 increases to 64.6%. © 2009 Elsevier B.V. All rights reserved.
1. Introduction The interest in the determination of the atmospheric aerosol size distribution in a definite environment is because this allows evaluating aerosol properties, like residence time and origin. Different modes are identified within distributions that are generally related to the formation mechanisms of the particles comprising them (Morawska et al.,1999). The nucleation mode, particles smaller than 0.1 μm, mostly originates from condensation of hot vapors during combustion processes (Seinfeld and Pandis,1998). Accumulation mode particles, extending from 0.1 to 1 μm (Whitby and Sverdrup, 1980), are formed from the ⁎ Corresponding author. Tel.: +34 966658325; fax: +34 966658397. E-mail address: [email protected] (J.F. Nicolás). 0169-8095/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.atmosres.2009.06.007
coagulation of nucleation mode particles, as well as from heterogeneous nucleation of secondary sulfate, nitrate, ammonium and organics generated by atmospheric reactions. Coarse mode particle sources (N1 μm) are mechanical processes, both natural and anthropogenic. The relative importance of each of these modes varies depending upon the environment sampled and which type of size distribution is addressed, either mass or number. In this way, it is possible to find that 80% of the total number of particles in urban areas belong to nucleation mode (Morawska et al., 1998; Wichmann et al., 2000; Rodríguez et al., 2007), while the aerosol mass is predominantly concentrated in the coarse mode (Salma et al., 2002). It is rare to find the three modes cited, observing instead only bimodal distributions. Therefore, even in environments influenced by traffic, the mass distribution might only feature the accumulation and coarse
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337
modes (Morawska et al., 1999). Traffic sources in urban areas are capable of modulating size distributions. In such a way, motor vehicle emissions constitute the most significant source of particles present in the nucleation mode (Zhu et al., 2002). Non-emission traffic also contributes to aerosol mass, like coarse mode resuspension (Chen et al., 2006; Nicolás et al., 2009a) or vehicular brake abrasion dusts in accumulation and coarse modes (Thorpe and Harrison, 2008). Different physicochemical processes related to atmospheric aerosols are those which provoke changes in the size distribution profile. Processes like nucleation increase the number of particles, whereas coagulation or dry and wet deposition reduce them. Condensation does not affect the number of particles but does affect their mass (Tunved et al., 2004). The influence of inter- and intra-modal effects has also been determined, thus when the number concentration of coarse mode increases, like for example during dust events, it may reduce the number concentration of accumulation mode due to the coagulation from this mode to coarse mode (Jung et al., 2002). However, it is difficult to quantify this effect since accumulation mode particles are strongly influenced by local emissions and the growth of nucleation mode particles (Kim et al., 2007). Meteorological variability can generate processes that, as has been indicated, modify the size distributions. Relative humidity values above 50% affect particle masses (Hänel, 1976). However, with high humidities the relative mass increase in the fine mode (d b 1 µm) differs from the coarse one, due to fine mode aerosols consisting predominantly of soluble material while the coarse mode has a strong crustal component (Hitzenberger et al., 1997). Wet removal stands out as the main process capable of removing aerosol mass (Tunved et al., 2004). Precipitation scavenging mechanisms vary depending upon the distribution mode analyzed. The nucleation mode material scavenged is mainly due to Brownian diffusion, in the accumulation mode this is due to interception, and in the coarse mode this is from inertial impaction (Seinfeld and Pandis, 1998). The scavenging effectiveness from precipitation depends on the collection efficiency. This parameter is elevated in the nucleation and coarse modes, but not so in the accumulation (Radke et al., 1980; Andronache, 2003), and this is because the accumulation mode dominates the size distribution after moderate rains (Andronache, 2003). Other meteorological situations capable of influencing the particle distribution are those characterized by stagnant air masses coinciding with high surface atmospheric pressure and an absence of strong winds. These situations favor the accumulation of pollutants within cities and the progressive displacement of aerosol size distribution towards the accumulation mode due to either coagulation between particles or between particles and semi-volatile compounds (Pey et al., 2008). The primary objective of this investigation consists in acquiring mass size distributions within urban surroundings during periods characterized by special meteorological conditions like periods of precipitation, considerable winds and high atmospheric stability. The degree of influence that each meteorological event has on the mass distribution of particles can then be determined. In order to be able to discriminate the resulting effect strictly from each meteorological event,
331
the urban contribution, mainly due to traffic, must be removed from the mass size distribution obtained during these episodes. 2. Study area and data collection 2.1. Features of the study zone The sampling campaign was conducted in Elche, a city of 228,000 inhabitants in southeastern Spain. Elche is 12 km from the Mediterranean coast (38°16′N; 0°41. 5′W), and lies 86 m above sea level. The monitoring station, classified as urban background, was placed on the roof of a 15 m high building located in the city center. The urban area is situated in a semi-arid Mediterranean region surrounded by barren soil due to scarce annual precipitation (less than 250 l m− 2). Most rain occurs during autumn (~ 43%) and winter (~ 31%). Mediterranean cyclogenesis is the primary atmospheric condition causing this, and to a lesser extent Atlantic advection, although other convective situations during the summer can be sources for rain. The study area can be classified as having a semi-arid Mediterranean climate. Average temperatures oscillate between 12 °C in January and 26 °C in July. The wind, as well as its speed, presents clear seasonal variation. Northwest (NW) winds with averages of about 2 m s− 1 are common during winter. Predominant in the summer period are southeast (SE) winds whose average speeds are inferior to those of winter. With the suitable wind, soil particles can reach the city of Elche on dry days because eroded topsoils are found northwest of Elche. Due to the proximity of the Mediterranean Sea, the effects of marine breezes (SE winds) are noticed at the sampling point on approximately 40% of the days of the year. They are, however, mainly concentrated during the months of spring and summer, making up 75% of the total. One feature of Elche is its high density of motor vehicles. In the study period there were more than 140,000 licensed. Motor vehicles constitute the main source of anthropogenic pollution in the urban area. 2.2. Data collection Size distributions were measured with a Grimm 1108 optical particle counter. This instrument determines the particle number concentration in 16 particle size channels from 0.23–0.3 µm to N20 μm. Conversions to the mass size distributions are carried out using an internal algorithm. The uncertainty in the determination of the total mass concentration is between 10 and 20%. The measurements were made in winter, from January to March 2006 (60 days) at 10 min intervals. Twenty-four hour averaged size distributions were subsequently calculated based on the counter data. Local meteorological data and gaseous pollutant concentrations were obtained from the Environmental Surveillance Network of the regional Government of Valencia. Atmospheric soundings came from the Department of Atmospheric Science at the University of Wyoming (http://weather.uwyo. edu/upperair/sounding.html). NCEP meteorological maps (Kalnay et al., 1996) were also used.
332
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337
3. Methodology applied In order to determine how the variability of certain meteorological parameters influences in both the mass distribution of atmospheric particles as well as in the different groups in which these can be included based on their origin, four different types of days within the campaign were chosen. They were characterized as such when the magnitude of one or a number of meteorological variables stood out above the corresponding average values obtained for the complete set of days that the campaign lasted. In this way, four groups of days were obtained in which: a) Precipitation occurred (Rainy Days—RD) caused by Atlantic advection. The dominant low pressure had an average value of 1000 mb at sea level during the episode. This was located north of the Canary Islands, a synoptic situation usually causing torrential rains in the study area (Millán et al.,1995), although in this occasion they were only of moderate intensity. b) Very low mixing layer heights coupled with very low ground-level wind speeds favored the accumulation of polluting agents in the urban atmosphere (High Pollution Days—HPD). The Holtworth method was used to determine the mixing layer thickness (Seibert et al., 2000). During the days the episode lasted, the mixing layer thickness measured at 12:00 UTC, had an average value inferior to 500 m. There was even a thermal inversion on one day of the episode, causing greater confinement of the suspended particulate matter in the urban atmosphere of Elche due to the elevated atmospheric stability. c) Consecutive days characterized solely by rather elevated average wind speeds, v N 3 m s− 1 (Windy Days—WD). d) A fourth group of days was considered where no meteorological variable stood out with either an elevated or reduced value (Normal Days—ND). The meteorological characteristics defining these groups of days appear in Table 1. The number of days making up each group is four. Furthermore, they fulfill the particularity of being consecutive. Once the days corresponding to each type of meteorological event are defined and characterized, comparisons of their respective mass size distributions can be achieved. In order to be able to discriminate the effect that these meteorological episodes present upon the mass size distribution, urban and background contributions must be subtracted from these distributions. To do this, the differences between the distributions presented on the days with meteorological events and those obtained on Normal Days will be determined. The urban Table 1 Summary of meteorological parameters on different types of days in Elche during winter 2006.
Fig. 1. a) Average particle mass size distribution in Elche during winter; b) mass size distribution components.
contribution, mainly due to traffic, and the background aerosol are similar for each of the four groups of analyzed days. Concentration differences among average mass size distributions of the types of meteorological episodes were checked using Tukey's test. This test constitutes a post hoc comparison, as it must be applied once the Anova (analysis of the variance) general hypothesis, that all the averages are equal, is rejected. It is useful to find out which specific averages are those differing among themselves, from which it provides greater information. A multivariate statistical technique, principal component analysis (PCA), was employed to identify particle source groups at the monitoring site (using the SPSS software package, version 16). PCA reduces the original variables of a large dataset to a smaller number of uncorrelated principal components (PC) that explain a large fraction of the total variance (Statheropoulos et al., 1998). In the present study, PCA with Varimax rotation was applied.
Periods
Duration
PA
WV
WD
T
RH
Rain (RD) High Pollution (HPD) Wind (WD) Normal (ND) Total
27–30 January 7–10 February 6–9 March 23–26 March 27 January–27 March
28.7 0.2 0 0 40.8
2.6 0.9 3.9 2.1 2.5
NW – NW SW –
7.1 11.6 17.5 18.0 13.2
71 65 37 46 57
4.1. Global results of the campaign. Particle grouping by size according to its origin
PA: precipitation (mm); WV: average wind speed (m s− 1); WD: average wind direction; T: temperature (°C); RH: relatively humidity (%).
The average concentration value for the whole study period was 63.5 µg m- 3, with a standard deviation of 25.7 µg m- 3. The
4. Results and discussion
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337 Table 2 r/p-values between PCs and NOx, wind velocity and relative humidity.
PC1 (µg/m3) PC2 (µg/m3) PC3 (µg/m3) a
NOx (µg m− 3)
Wind velocity (m s− 1)
Relative humidity a (%)
0.41/0.002 0.69/0.000 0.04/0.772
− 0.55/0.001 − 0.36/0.043 0.56/0.000
0.78/0.000 0.03/0.761 − 0.67/0.000
Potential correlation (y = axb).
particle mass size distribution averaged for the whole study period is plotted in Fig. 1a. Coarse mode particles (d N 1 µm) account for about 70% of the total mass. The spectrum contains an important mass contribution of particles N20.0 μm. These results suggest that some or all of the following processes, like resuspended road, soil dust or construction activities are relevant in the study area. To confirm the relationship among the different sizes of particles, a principal component analysis (PCA) with Varimax rotation was performed. Ten-minute mass concentrations for each particle size range were selected as variables for the analysis, whose results are presented in Fig. 1b. The analysis gives three components with eigenvalues higher than 1, explaining 91% of the total variance. The first component (PC1) shows an elevated correlation with particles smaller than 0.90 μm and can be associated with the processes responsible for the generation of particles in the accumulation mode. This component explains almost 50% of the total variance.
333
PC2 presents the highest factor loadings for particles at the end of the accumulation mode and beginning of the coarse mode, to 7.5 µm. This component, based on the sizes it includes, could be related to particles introduced into the atmosphere by vehicle-induced resuspension (Chen et al., 2006). To a lesser extent it can also be related to marine aerosol (Mazzei et al., 2006). In fact, marine aerosol was recorded at the sampling point during the winter, although in far lesser concentrations than those obtained during the summer period (Nicolás et al., 2009b). Finally, the variables correlated to PC3 are the coarser particles. This component could be interpreted as wind resuspension of soil particles from the semi-arid areas surrounding Elche. PC3 is favored by low relative humidities and high wind speeds (Nicolás et al., 2009a). In order to reaffirm the relations shown between the diverse particle sources and obtained components, they were correlated with the NOx levels, a variable representative of the traffic levels in the city, with the wind speed and with the relative humidity (RH). Table 2 shows Pearson's correlation coefficients (r) and the obtained p-values. All the correlations are linear, with the exception of those carried out with the RH, because they adjust quite better to a potential function. All the correlation coefficients shown in Table 2 are statistically significant at the 95% confidence level, excluding the relation between PC3–NOx and PC2–RH. The coefficients between PC2 and NOx, (see correlation graph in Fig. 2a), and
Fig. 2. Correlations between: a) PC2 and NOx; b) PC1 and wind velocity; c) PC3 and RH; and d) PC1 and RH.
334
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337
between PC3 and the wind speed (0.56), confirm that, to a certain extent, vehicle-induced resuspension and wind resuspension of soil particles from the semi-arid areas surrounding Elche are possible particle sources related to components PC2 and PC3. The negative correlation coefficient between PC1 and the wind indicates that the wind speed increase produces a reducing effect in the mass concentration registered by this component. Nevertheless, the inverse relation between both variables adjusts better to exponential decay, shown in Fig. 2b. On the other hand, the three components indicate a different behavior with the humidity. Component PC2 does not present any correlation, whereas PC1 and PC3 do, however differently. In both cases the correlation, as previously indicated, adjusts better to a potential than to a linear function. In the case of component PC3, the equation (Fig. 2c) shows an inverse and practically quadratic dependency, whereas component PC1 (Fig. 2d) displays a cubical dependency. This increase in mass along with the humidity of accumulation mode particles, included in PC1, has already been proven in other studies (Hitzenberger et al., 1997). Based on the three groups of particles, the contribution of each one to the total mass recorded was determined for the total number of days of the campaign. Determined as the sum of the average concentrations recorded during the entire period for each size interval, (63.5 µg m- 3), 27.2% of the average mass concentration corresponds to particles with sizes belonging within the first component (PC1), 35.4% to PC2, and 37.3% to PC3. With the correlation equation shown in Fig. 2a and the mass percentage attributable to PC2, the mass concentration of this component related to traffic (road resuspension) can be quantitatively estimated. The method of assigning the value of the ordinate at the origin (6.3 ± 2.0 μg m- 3) to the mass
unrelated to traffic was used for this. This method has been used in several studies (Harrison et al.,1997; Harrison et al., 2001). In this sense, if the average mass contribution of the component is 22.5 µg m- 3 (35.4% of the total), then 16.2 µg m- 3 in this component can be considered attributable to road resuspension from traffic. 4.2. Variation of the mass contribution of each component per meteorological event The average percentages that each component contributes to the overall average concentration value vary according to the meteorological episode. The component distribution, in percentages, for each meteorological event can be observed in Fig. 3. Also the average mass concentration on these days is shown. Important particle concentration reductions occur on Rainy Days (RD), specifically some 60% with respect to the average concentrations for the total period. Particulate matter levels generally reduce considerably in all regions of Spain during Atlantic advection episodes, showing minimum values in their annual temporal evolution, independent of the type of environment sampled (Rodríguez et al., 2003; Querol et al., 2004; Pey et al., 2008). High Pollution Days (HPD) undergo large concentration increases, with increases approaching 40%. This mass concentration increase under these atmospheric conditions has been widely shown (Artíñano et al., 2003; Rodríguez et al., 2003). Windy Days (WD) and Normal Days (ND) do not present remarkable variations in the mass concentrations. Fig. 3 shows important percentage variability for each component depending on the meteorological event. It shows the important contribution of PC1 during the HPD, and above all the RD. Relative humidity levels were high on both types of days
Fig. 3. Percentage contribution to mass concentration for: a) Rainy Days; b) High Pollution Days; c) Windy Days; and d) Normal Days.
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337
335
(see Table 1), confirming the positive dependency between this component and the RH (see Fig. 2d). It is noteworthy that more than one-half of the concentration during Rainy Days is due to the mass contribution within the accumulation mode. Contrary to this, during ND this component presents a meager percentage, and on WD, comprises only 7.4% in its contribution. Components two and three present similar percentages on all types of days, except for WD, when PC3 (particles with d N 7.5 µm) show a contribution considerably superior to PC2, with 64.6%. This indicates the great importance of the very coarse particulate matter during these types of days. 4.3. Meteorological episode characteristic size distribution profiles Fig. 4 shows the mass size distribution for each type of day analyzed. The mass concentration value for each size is the result of averaging the recorded values of each size obtained during the four days making up a certain episode. It is important to point out the stability of the mass size distribution during each day of each episode. In this way, for example, all four days characterized as High Pollution present their maximums and minimums in the same particle sizes and their daily mass concentrations by sizes are very similar as well. As is possible to verify, depending on the particle size the four distributions present either similar or different tendencies. Each distribution presents minimums at the division between the accumulation and coarse modes. There are only two clear maximums within the accumulation mode; the first occurring on RD (the only clear maximum this distribution showed), and another maximum on HPD. There is trimodal distribution on HPD days since there are two more maximums in the coarse mode: the first at 2–3 µm and a greater second one between 5 and 7.5 µm. For the distribution on Windy Days, one relative maximum appears at 7.5–10.0 μm, but above all a far more significant maximum clearly stands out for particles N20 μm. Tukey's test was conducted in order to determine if the concentration differences for each particle size in the four distributions from Fig. 4 are statistically significant to a 95% confidence level. The test results have shown that the differences are statistically significant (p-value b0.05) for
Fig. 4. Average mass size distribution for: Windy, High Pollution, Rainy and Normal Days.
Fig. 5. Difference between the mass size distribution for Windy, High Pollution and Rainy Days versus Normal Days.
the four distributions among the sizes 0.23–0.4 µm, 0.9–5. 0 μm and N15 µm. The differences are not significant (p-value N0.05) for: WD and ND for sizes 0.4–0.65 µm and 5.0–10. 0 μm. RD and WD for sizes 0.65–0.9 µm. HPD–WD for sizes 7.5–10. 0 μm. HPD–ND for sizes 10.0–15.0 µm. Fig. 5 shows the concentration differences in sizes for HPD, RD and WD plotted versus ND. This was done to highlight the repercussions each meteorological event has upon each particle size with respect to a day in which no differential meteorological episodes occur. Fig. 5 shows how Rainy Days contribute to a slight mass increase in the accumulation mode and an important reduction in the coarse mode concentration when compared to days without remarkable meteorological events. This confirms that coarse mode atmospheric particle cleansing is effective with moderate precipitation, but not so in the accumulation mode. One consequence of this is that the resulting mass size distribution during precipitation is dominated by accumulation mode particles, as Fig. 4 shows. High Pollution Days are characterized by increasing particle concentrations when compared to Normal Days. This increase occurs primarily in the accumulation mode, being some 98% of the total. Accumulation mode predominates on HPD, like during RD, but for different reasons. On HPD the meteorological situation provokes the settlement of larger particles, and favors coagulation among particles in the nucleation mode. A mass increase in the accumulation mode is one effect of this situation. On the other hand, Windy Days distinguish themselves by producing a significant mass increase in the largest particles (N20.0 µm) versus Normal Days; the average concentration increase for these on WD was 12.5 µg m− 3 greater than what occurred on ND. The mass size distribution on these days shows a negative profile from the accumulation mode up to particles having diameters of 7.5 µm, which could indicate that the wind neither transports nor resuspends this type of particle and possibly favors their dispersion into the urban environment. Over the course of the day the evolution of the mass size distribution for all episodes is different and somewhat associated with the temporal evolution of the meteorological parameters characterizing them. Thus on Rainy Days the
336
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337
minimum values of coarse mode particles occurred precisely during the hours of the precipitation. On High Pollution Days the greatest mass concentrations of particles corresponding to the accumulation mode coincided with the highest registered hourly values of the relative humidity. For their part, Windy Days showed a considerable increase in the heaviest particles during the middle hours of the day, which coincided with the hours having the highest wind speeds. 5. Conclusions Coarse mode particle concentrations accounted for about 70% of the total mass for the entire study period. This reflects the importance of sources that emit coarse particles in the study area, like resuspended road, soil dust and construction activities. Nevertheless, this high percentage can be substantially reduced under certain meteorological situations, be they either periods of rain or high atmospheric stability. Significant linear correlation was noticed between traffic and a portion of coarse mode particles (d b 7.5 µm), confirming vehicle-induced resuspension as their possible origin. Good correlation was also considered, in this case of an exponential type, between the wind speed and mass concentrations of accumulation mode particles. The influence of the humidity resulted in being different depending upon the size ranges. Accumulation mode particles showed positive potential correlation, whereas the largest particles (d N 7.5 µm) did so negatively. No significant correlation was observed for coarse mode particles with diameters inferior to 7.5 µm. The most relevant conclusions of the analysis of the influence that the three types of meteorological episodes studied (precipitation, wind and high atmospheric stability) have upon the mass particle distribution reflect that particle masses during episodes of rain and elevated stability were concentrated mainly in the accumulation mode, although due to diverse causes. In the case of rain, this is due to greater atmospheric cleansing effectiveness that rain has upon coarse mode particles when compared to those in the accumulation mode. Contrary to this, the meteorological situation on High Pollution Days favored coagulation processes among nucleation mode particles, and bringing about mass increases in the accumulation mode. Situations characterized by high wind speeds favor the dispersion of particles with sizes inferior to 7.5 µm in the urban environment, which in turn bring about a significant increase in the mass attributable to the largest particles (N20 µm). Acknowledgements We thank the Elche City hall for allowing access to their facilities for the placement of the instruments, the Air Quality Surveillance Network of the Valencian Community Regional Government for supplying data, and Paul Nordstrom and Guillermo Escribano for their assistance in this work. References Andronache, C., 2003. Estimated variability of below-cloud aerosol removal by rainfall for observed aerosol size distributions. Atmospheric Chemistry and Physics 3, 131–143.
Artíñano, B., Salvador, P., Alonso, D.G., Querol, X., Alastuey, A., 2003. Anthropogenic and natural influence on the PM10 and PM2.5 aerosol in Madrid (Spain). Analysis of high concentrations episodes. Environmental Pollution 125, 453–465. Chen, J., Zheng, H., Wang, W., Liu, H., Lu, L., Bao, L., Ren, L., 2006. Resuspension method for road surface dust collection and aerodynamic size distribution characterization. China Particuology 4, 300–303. Jung, C.H., Kim, Y.P., Lee, K.W., 2002. Simulation of the influence of coarse mode particles on the properties of fine mode particles. Journal of Aerosol Science 33, 753–767. Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A., Reynolds, B., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.C., Ropelewski, C., Wang, J., Jenne, R., Joseph, D., 1996. The NCEP/NCAR 40-year reanalysis project. Bulletin of the American Meteorological Society 77, 437–471. Hänel, G., 1976. The properties of atmospheric aerosol particles as functions of the relative humidity at thermodynamic equilibrium with the surrounding moist air. Advances Geophysics 19, 74–188. Harrison, R.M., Deacon, A.R., Jones, M.R., Appleby, R.S., 1997. Sources and processes affecting concentrations of PM10 and PM2.5 particulate matter in Birmingham (U.K.). Atmospheric Environment 31, 4103–4117. Harrison, R.M., Yin, J., Mark, D., Stedman, J., Appleby, R.S., Booker, J., Moorcroft, S., 2001. Studies of the coarse particle (2.5–10 µm) component in UK urban atmospheres. Atmospheric Environment 35, 3667–3679. Hitzenberger, R., Berner, A., Dusek, U., Alabashi, R., 1997. Humidity-dependent growth of size-segregated aerosol samples. Aerosol Science and Technology 27, 116–130. Kim, J., Jung, C.H., Choi, B.-C., Oh, S.-N., Brechtel, F., Yoon, S.-C., Kim, S.-W., 2007. Number size distribution of atmospheric aerosol during ACE-Asia dust and precipitation events. Atmospheric Environment 41, 4841–4855. Mazzei, F., D'Alessandro, A., Lucarelli, F., Marenco, F., Nava, S., Prati, P., Valli, G., Vecchi, R., 2006. Elemental composition and source apportionment of particulate matter near a steel plant in Genoa (Italy). Nuclear instruments and methods in physics. Research Section B: Beam Interactions with Materials and Atoms 249, 548–551. Millán, M., Estrela, M.J., Caselles, V., 1995. Torrential precipitations on the Spanish east coast: the role of the Mediterranean Sea surface temperature. Atmospheric Research 36, 1–16. Morawska, L., Thomas, S., Bofinger, N., Wainwright, D., Neale, D., 1998. Comprehensive characterization of aerosol in a subtropical urban atmosphere: particle size distribution and correlation with gaseous pollutants. Atmospheric Environment 41, 2145–2155. Morawska, L., Thomas, S., Jamriska, M., Johnson, G., 1999. The modality of particle size distributions of environmental aerosols. Atmospheric Environment 33, 4401–4411. Nicolás, J., Yubero, E., Galindo, N., Giménez, J., Castañer, R., Carratalá, A., Crespo, J., Pastor, C., 2009a. Characterization of events by aerosol mass size distribution. Journal of Environmental Monitoring 11, 394–399. Nicolás, J., Galindo, N., Yubero, E., Pastor, C., Esclapez, R., Crespo, J., 2009b. Aerosol Inorganic Ions in a Semiarid Region on the Southeastern Spanish Mediterranean Coast. Water air and soil pollution 201, 149–159. Pey, J., Rodríguez, S., Querol, X., Alastuey, A., Moreno, T., Putaud, J.P., Dingenen, R.V., 2008. Variations of urban aerosols in the western Mediterranean. Atmospheric Environment 42, 9052–9062. Querol, X., Alastuey, A., Rodríguez, S., Viana, M.M., Artıñano, B., Salvador, P., Mantilla, E., Santos, S.G.D., Patier, R.F., Rosa, J.D.L., Campa, A.S.D.L., Menéndez, M., 2004. Levels of PM in rural, urban and industrial sites in Spain. The Science of the Total Environment 334–335, 359–376. Radke, L.F., Hobbs, P.V., Eltgroth, M.W., 1980. Scavenging of aerosol particles by precipitation. Journal of Applied Meteorology 19, 715–722. Rodríguez, S., Querol, X., Alastuey, A., Viana, M.M., 2003. Events affecting levels and seasonal evolution of airborne particulate matter concentrations in the western Mediterranean. Environmental Science and Technology 37, 216–222. Rodríguez, S., Van Dingenen, R., Putaud, J.P., Dell'Acqua, A., Pey, J., Querol, X., Alastuey, A., Chenery, S., Ho, K.F., Harrison, R., Tardivo, R., Scarnato, B., Gemelli, V., 2007. A study on the relationship between mass concentrations, chemistry and number size distribution of urban fine aerosols in Milan, Barcelona and London. Atmospheric Chemistry and Physics 7, 2217–2232. Salma, I., Dal Maso, M., Kulmala, M., Záray, G., 2002. Modal characteristics of particulate matter in urban atmospheric aerosols. Microchemical Journal 73, 19–26. Seibert, P., Beyrich, F., Gryning, S.-E., Joffre, S., Rasmussen, A., Tercier, P., 2000. Review and intercomparison of operational methods for the determination of the mixing height. Atmospheric Environment 34, 1001–1027. Seinfeld, J.H., Pandis, S.N., 1998. Atmospheric Chemistry and Physics. Wiley, New York, USA.
J.F. Nicolás et al. / Atmospheric Research 94 (2009) 330–337 Statheropoulos, N., Vassiliadis, N., Pappa, A., 1998. Principal component and canonical correlation analysis for examining air pollution and meteorological data. Atmospheric Environment 32, 1087–1095. Thorpe, A., Harrison, R.M., 2008. Sources and properties of non-exhaust particulate matter from road traffic: a review. Science of the Total Environment 400, 270–282. Tunved, P., Ström, J., Hansson, H.C., 2004. An investigation of processes controlling the evolution of the boundary layer aerosol size distribution properties at the Swedish background station Aspvreten. Atmospheric Chemistry and Physics 4, 2581–2592.
337
Wichmann, H.E., Spix, C., Tuch, T., Wölke, G., Peters, A., Heinrich, J., Kreyling, W.G., Heyder, J., 2000. Daily mortality and fine and ultrafine particles in Erfurt, Germany. Part I: Role of Particle Number and Particle Mass, vol. 98. Health Effects Institute. Whitby, K.T., Sverdrup, G.M., 1980. California aerosols: their physicals and chemical characteristics. In: Hidy, G.M. (Ed.), The Character and Origins of Smog Aerosol. InWiley, New York, p. 495. Zhu, Y., Hinds, W.C., Kim, S., Shen, S., Sioutas, C., 2002. Study of ultrafine particles near a major highway with heavy-duty diesel traffic. Atmospheric Environment 36, 4323–4335.