Interactive comment on “ Trends of road dust emissions contributions on ambient PM levels at rural , urban and industrial sites in Southern Spain ”

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Trends of road dust emissions contributions on ambient PM levels at rural, urban and industrial sites in Southern Spain
PM 10 concentrations in large European cities over the last decade are not decreasing as expected (EEA, 2012;Harrison et al., 2008).This might be due to the underestimation (or absence) of important sources of primary PM in emission inventories (e.g.road dust) or to secondary aerosol precursors whose emissions reduction have not been substantial (e.g.NOx, VOC and NH 3 ).Kousoulidou et al., (2008) showed clear evidence that non-exhaust sources (road dust and wear emissions) become increas-Introduction

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Full ingly important as no emission control strategies are taken by member states.Road dust emissions are also pointed as the source responsible for the mismatch between modeled and observed PM 10 concentrations in cities (Schaap et al., 2009 among others).
The most echoing impact of road dust emissions is the contribution to PM mass (parameter regulated by the EU Directive 2008/50/EC), due to their relatively coarser size distribution (typically between 1 and 10 µm), causing a high number of the exceedances of air quality limit values at urban and traffic sites.However, road dust is also of concern due to the high content of specific harmful components such as heavy metals and metalloids (i.e.Cu, Sb, Sn, Fe, Zn, Mo, Amato et al., 2009a), sulphides and carbonaceous aerosols such as elemental and organic carbon (EC and OC) and Polycyclic Aromatic Hydrocarbons (PAHs, Pengchai et al., 2004;Majumdar et al., 2012) among others.Heavy metals and sulphides originate from the erosion of brake and tire materials and induce oxidative stress (Yanosky et al., 2012).In California, a correlation between atmospheric concentrations of heavy metals (Fe, Cu, Zn, and Ni) and the mortality rate due to ischemic heart disease was recently found (Cahill et al., 2011).In Stockholm, Meister et al., (2011) estimated a 1.7 % increase in daily mortality per 10 µg m −3 increase in PM 2.5-10 concentrations that include road dust and other coarse-size particles.The association with PM 2.5-10 was stronger for the November-May period when road dust was found to be most important.Exposure to an increase equivalent to the interquartile range of road dust contributions (below 2.5 microns) was associated with a 7 % increment of cardiovascular mortality in Barcelona (Ostro et al., 2011).Gustafsson et al., (2008) found that particles from road wear caused by studded tires are at least as inflammatory as particles from diesel exhaust.Given these evidences, the actual pollution scenario is not encouraging.An overview of atmospheric concentrations of heavy metals in Spain (more than 20 monitoring sites) revealed that the highest concentrations of Fe, Cu, Sr, Sb, Ti and Ba (and partly also Zn and Zr) are measured inside the cities (rather than at industrial hotspots), where most of population live and work (Querol et al., 2007).Concentrations increase further at road-Introduction

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Full side locations where also a significant part of population is exposed.Consequently, for these metals, population exposure is much higher than for common industrial tracers such as As and Cd.Investigating the role of non-exhaust emissions in air quality impairment and their impact on health is therefore a non-regret policy and a must for local authorities, mostly considering that such particles are emitted locally, and are therefore easier to control/mitigate, improving public health.The identification of individual source contributions is crucial for the understanding of health effects since low-contributing sources may be more relevant for health.Differentiating the contribution of road dust from other traffic sources is however problematic: the complexity of the urban environment does not always allow for a clear separation of road traffic sources, consequently most of source apportionment studies presented so far, show results only for total contributions from road traffic emissions (Viana et al., 2008).It is also common to find studies where the road dust component of traffic emissions is mixed with other mineral/soil sources.PM contributions from vehicular traffic should be differentiated between exhaust and non-exhaust fraction.Ideally nonexhaust contributions should be further separated between road dust, brake, tire and road wear.
The relative importance of these categories changes widely in space and in time.Spatially, road dust emissions increase largely in Southern Europe (due to drier climate) and Scandinavian countries (due to the road sanding and the use of studded tires) (Querol et al., 2004) but also within a city environment e.g. next to construction sites and in heavy traffic roads (Amato et al., 2009).Timely, road dust emissions are severely influenced by meteorology (precipitation, insulation, road humidity and droughts, Amato et al., 2012).In addition, it is important to monitor the relative increase of non-exhaust emissions (currently uncontrolled) against the motor exhaust emissions, which have been progressively reduced in last two decades by means of the EURO (1 to 5) standards.Introduction

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Full To date, research on non-exhaust emissions has been rather limited due to the difficulties encountered by experimentalists and modelers to characterize and describe the complex phenomenon of road dust resuspension and wear emissions.
In this study we aim to contribute to the improvement on current knowledge on road dust emissions by estimating their impact on PM 10 and PM 2.5 levels measured at 11 receptors distributed at traffic, urban, industrial and rural location across Andalucía, the most arid and populated region of Spain, which suffers also of frequent Saharan dust deposition events.

Study area
Andalucía is the most populated region in Spain with 8 provinces and 8.4 million inhabitants.The local economy is basically based on tourism, being the primary (agriculture, fishing and mining) and industrial sectors only a small percentage of the gross value added.Urban road traffic is very dense due to the commonly insufficient public transport infrastructure (metro, tram, buses) and to the high density of urban architecture.
Climate is typically Mediterranean, with dry and hot summers and mild winters, favoring the build-up and mobilization of road dust particles and their entrainment into the atmosphere due to the wheel and vehicle induced turbulence.
Due to the evident impact of road dust emissions and their increasing concern (Harrison et al., 2008;Denier van der Gon et al., 2013) on urban air quality the Regional Government of Andalucía had recently promoted research studies aimed at evaluating the impact of road dust emissions on air quality measured at large cities and industrial areas of Andalucía.The five cities under study (Seville, Malaga, Cordoba, Granada and the Algeciras Bay, Fig. 1) are briefly described below: -Seville, the capital of Andalucía, is the fourth largest city of Spain, counting 700 000 inhabitants, and 1.5 million in the Metropolitan region.The city is built on Introduction

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Full -Malaga is the second most populous city of Andalucía with a population of 600 000 (metropolitan area).It lies on the Mediterranean coast, 100 km east of the Gibraltar Strait, and it is bordered to the North by a high mountain range.Malaga is a city of commerce and tourism, therefore the local anthropogenic pollutant source is mainly traffic.
-Cordoba (330 000 inhabitants) is one of main touristic destination in Spain.The city is located on the banks of the Guadalquivir river and has the highest summer average daily temperature of Europe (36,2 • in July).The climate is Mediterranean-Continental. Precipitations are concentrated in winter-autumn and summer is often characterized by droughts.
-Granada (738 m a.s.l.), is a non-industrialized and medium sized city with 250 000 inhabitants.The city is located in a natural valley surrounded by mountains with elevations between 1000 and 3350 m a.s.l.Traffic is the most important source of anthropogenic pollutants in Granada.The topography of Granada favors the development of thermal inversions in winter, with a significant accumulation of pollutants in the study area (Lyamani et al., 2008).
-  (2010).Sampling periods and frequency varied among sites; details are shown in Table 1.Eleven stations were selected among rural, urban background, traffic and urban-industrial environments: -In the Seville province, one traffic (Principes) and one urban background site (Alcalá de Guadaira), the latter being located in the suburb of the city were used (refs).Several studies on air quality have been already performed in metropolitan area of Seville (Adame et al., 2012;Notario et al., 2012).
-In the Malaga province, one traffic (Carranque) and one rural site (Campillo), located 60 km northwest of the city were chosen.
-In the province of Cordoba, one urban background (Lepanto) and one rural site (Poblado) were selected.(García Lorenzo, 2011).Details of the monitoring stations can be found in Lozano et al. (2009).
-In the city of Granada, the traffic monitoring site Granada Norte was used, located in between the two carriages of the Davalos avenue, counting 15 000 vehicles per day totally.
-In the Algeciras Bay four urban-industrial monitoring sites were used (Los Barrios, La Línea, Algeciras and Puente Mayorga).Details can be found in Pandolfi et al.  -Half filter (or 150 cm 2 in case of rectangular filters) was acid digested (5 mL HF, 2.5 mL HNO 3 , 2.5 mL HClO 4 ) for the determination of major and trace elements and analyzed respectively by inductively coupled plasma mass spectrometry and atomic emission spectrometry (ICP-MS and ICP-AES) (Querol et al., 2001).
-A quarter of filter (or 75 cm 2 in case of rectangular filters) was leached in 20 mL of bi-distilled water for the extraction of water-soluble ions and subsequent analysis by ion chromatography (IC) for sulfate, nitrate and chloride and by specific electrode for ammonium.
-A section of 1.5 cm 2 of the filter was used for the determination of TC by means of elemental analysis.
In every case blank concentrations were subtracted for determining final concentrations in samples.

Road dust samplings
Road dust samples were collected, in each city, at four selected roads in the vicinities of the urban monitoring site used for ambient air PM .Road dust particles were collected on 47 mm diameter quartz fiber filters (Pallflex) by means of a dry vacuum sampler coupled with a 10 µm-inlet able to separate only the mobile particles with aerodynamic Introduction

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Full diameter < 10 µm from a delimitated area of active road surface.Details of the device and sampling protocol can be found in our previous publication where the mass loadings of road dust were investigated (Amato et al. 2013).Details of sampling sites are summarized in Table S1.At each road, three different samples were collected in order to improve representativeness and to collect enough sample for a complete chemical characterization: -The first filter was acid digested (following the above protocol) to determine the concentration of major (Na, Mg, Al, Fe, P, S, Cl, K, Ca, Ti and Mn) and trace elements (Li, Sc, V, Cr, Co, Ni, Cu, Zn, Ga, Ge, As, Se, Rb, Sr, Zr, Nb, Mo, Cd, Sn, Sb, Cs, Ba, La, Ce, Hf, W, Tl, Pb, Bi, Th and U among others) by means of ICP-AES and ICP-MS respectively.
-One half of the second filter was used for a leachate in Milli-Q water (20 mL) for the extraction of soluble ions and subsequent Ion Cromatography analysis to determine the concentration of sulphate, nitrate, chloride and specific electrode for NH + 4 .
-A fraction of 1.5 cm 2 of the second filter was used for the determination of Organic carbon (OC) and Elemental carbon (EC) by means of the Sunset thermal-optical analysis (Birch and Cary, 1996).
-A fraction of 1.5 cm 2 of the second filter was used for the determination of particulate Hg by means of the atomic absorption spectrometer LECO AMA 254.
The third filter was stored for further analysis.For the source apportionment study, the average of the four chemical profiles obtained in each city was used.

Source apportionment
Positive Matrix Factorization (PMF, Paatero and Tapper, 1994) is a widely used model for atmospheric aerosol source apportionment, as well as for other types of samples Introduction

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Full such as ashes, soils etc. PMF is based on the mass conservation principle: where x i j is the i th concentration of the species j , g i k is the i th contribution of the source k and f j k is the concentration of the species j in source k.
In this study two types of source apportionment analysis were carried out: a road dust source apportionment, in order to identify the main sources of road dust and their contribution to observed mass loadings.The road dust source apportionment, aimed at identifying the main sources of road dust was performed merging the 20 road dust samples obtained in this study with road dust samples from other Spanish cities (Barcelona and Girona, Amato et al., 2011) collected in previous studies from our group, in order to improve the statistical basis.Source contribution results are however presented only for the sites in Andalucía.
a PM source apportionment, merging PM 10 and PM 2.5 data for each area in order to estimate the contribution of main source of PM including road dust.
In both cases a PMF model was used.For the PM source apportionment a constrained PMF was carried out, divided in six different analyses due to the considerable distance among monitoring sites (i.e. the assumption of same sources at all sites may be not valid).The constraints consist of auxiliary equations (added to the main equations by means of the Multilinear Engine 2 programming, Paatero, 1999) in order to: 1. pull one factor profile f j k towards the target profile of local road dust, obtained experimentally; Introduction

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Full This approach has been already followed by Amato et al. (2009b) and Amato and Hopke (2012) showing a satisfactory theoretical basis.The six analyses were divided as follows: 1. PM 10 and PM 4. PM 10 and PM 2.5 analysis at Granada Norte (traffic site in Granada).A total of 217 PM samples were used (183 PM 10 and 34 PM 2.5 samples) against 31 components of PM.
5. PM 10 and PM 2.5 analysis at Carranque (traffic) (Málaga).A total of 222 PM samples were used (175 PM 10 and 47 PM 2.5 samples) against 29 components of PM.
6. PM 10 and PM 2.5 analysis at Campillo (rural site in the province of Málaga).A total of 95 PM samples were used (54 PM 10 and 41 PM 2.5 samples) against 26 components of PM.Introduction

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Full For each PMF analysis, the selection of species was based on the two-fold criterion of S/N ratio and % of data above detection limit (Amato et al., 2009b).Details are shown in Table S2.
Moreover, temporal trends of source contributions were analyzed at those monitoring sites where at least four years of data were available.The Theil-Sen method (Theil, 1950;Sen, 1968), available in the Openair software (Carslaw, 2012;Carslaw and Ropkins, 2012), was applied to the monthly averages to calculate the regression parameters of the trends including slope, uncertainty in the slope and the p value.The applied method yields accurate confidence intervals even with non-normal data and it is less sensitive to outliers and missing values (Hollander and Wolfe, 1999).Data were deseasonalized and all the regression parameters were estimated through bootstrap resampling.The slopes indicate how road dust contributions have changed through time and are expressed in units (µg m −3 ) per year.The p values show whether the calculated trends are statistically significant.A statistically significant trend was assumed at the 90th percentile significance level (p < 0.1 or +), meaning that there was a 90 % chance that the slope was not due to random chance.p values > 0.1 indicate insignificant trends, whilst p values = 0.01 and 0.001 (or ** and ***) indicate high and very high significant trends, respectively.

Road dust composition and sources
As mentioned previously, the chemical composition of road dust at each city was investigated with two main objectives: -Identifying the main sources of road dust and estimate their contribution to road dust loadings (mgm −2 ) measured on active traffic lanes (this section).Introduction

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Full -Estimating the contribution of road dust to the levels of ambient PM 10 and PM 2.5 (µg m −3 ) measured at the PM monitoring sites under study (Sect.3.2).
Road dust loadings have been already discussed in Amato et al. (2013).Briefly, typical urban roads showed emission factors within 77-480 mg veh −1 km −1 the averages 158 ± 90 mg veh −1 km −1 in Córdoba, 180 ± 113 mg veh −1 km −1 in Málaga, 189 ± 27 mg veh −1 km −1 in Seville and 347 ± 144 mg veh −1 km −1 in Granada.These values are in the upper edge of the range observed in Europe and US.An increasing trend of emission factors was observed from freeway, urban, urban-construction up to industrial sites.After averaging the elemental concentrations at the four roads under study at each city, results show that the main components of respirable (< 10 µm) road dust particles are OC, Ca, EC, Al 2 O 3 , Fe and Mg (silica was not analyzed) (Fig. 2).Concerning trace elements strong enrichments in Ti, Zn, Cu, Ba, Mn, Sn, Sb, Zr and Sr were found (Fig. 2).The relative proportion of these components may vary depending on the importance of the different sources involved: road wear, tire wear, brake wear, other minerals (unpaved areas, works) and motor exhaust.This results in a varying composition depending on the type of road (Table 2): -Typically urban roads showed higher relative concentrations of OC, EC, Cu, Ba, Sn, Sb, Bi and W (usually produced by abrasion of brakes, road and tires) and Cl − .
Interestingly, a correlation was found between the loadings of Fe-Cu-Zn (mg m −2 ) and the distance between sampling point and braking areas such as traffic lights and roundabouts (Fig. S1), regardless of roads category.This suggests that emissions of brake particles (both the airborne and deposited fraction) vary spatially within a city environment.This information is important for urban scale modeling and exposure studies.
-Industrial roads were enriched in Cr, Co, Ni, Pb, Mn and Cd (linked to PM deposition from stationary sources) and Ca (likely due to higher wear rate of road pavement by heavy duty vehicles).Introduction

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Full -Poor state of the pavement shows enrichment in Al, Ti, Rb and K, typical tracers of phyllosilicates.
The PMF identified three main sources responsible for the production and build-up of respirable road dust particles on road pavement: (i) a carbonaceous source, mainly related to tire wear, although a contribution of motor exhaust and brake wear may be present; (ii) road wear, which, in specific samples (Fig. 3) includes mineral dust from unpaved areas and works; (iii) brake wear.Factor profiles are shown in Figure S2.The sum of these three sources explains in average 96 % of the observed road dust mass loadings.
-The carbonaceous source is composed mainly by OC, and, in a minor proportion by EC and Ca, suggesting the presence of tire particles possibly attached to particles of calcite and bitumen from pavement.In average this is the main source of road dust particles (50 %).The highest contributions of this source were found in the Algeciras Bay area and in Granada.The typically urban contribution can be estimated in 3-4 mg m −2 (Fig. 3).
-The road wear factor is responsible for the production of the mineral particles deposited on pavement, even though a contribution from unpaved areas and urban works cannot be discarded.The chemical profile is traced by typically crustal species such as Al, Ca, K, Ti, Fe and Mg, but this source is also responsible for a large variance of Pb and Hg.In typically urban roads, without nearby works, the contribution varies within 0.3-5.8mg m −2 with an average of 1.9 mg m −2 (20 %, Fig. 3).In roads with nearby works, and/or unpaved areas, or with a poor state of the pavement, the contribution can reach up to 10 mg m −2 (Fig. 3).
-The Brake wear factor is clearly identified for the high content in Fe (brake pads contain 13-45 % of metallic iron, Amato et al., 2012), Al and Ca.Aluminum is Introduction

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Full used as abrasive in pads (as metallic Al or corindon), while calcium is used in form of calcite as a filler.This factor also is responsible for most of the variance of Cu, Sn, Sb, Cr and Ba.All these elements are used in brake pads manufacture as lubricants (Sn and Sb sulphides), fillers (barite) and friction materials (metallic Cu, CuO and Cr 2 O 3 ).Brake wear contributes in average 12 % of road dust particles, varying within 0.2-3.0mg m −2 (Fig. 3).Compared to previous studies, road wear/mineral contribution are generally similar (in %) to other Spanish cities as Barcelona and Girona, while carbonaceous materials are higher as opposed to brake particles.Central European cities as Zurich and Utrecht showed much lower contributions from mineral matter (Amato et al., 2011 and2013b).

PM source apportionment
For each PMF analysis the distribution of residuals, G-space plots, F peak values and Q values were explored for solutions with number of factors varying between 3 and 10.The most reliable solution identified six sources at all sites, with the exception of the Algeciras Bay area where eight sources were found (Fig. S3 and Table 3).Four sources were common at all sites, namely Road Dust (RD), Mineral (MI), Vehicle Exhaust (VE) and Secondary Sulfate (SS).Sea salt (SE) was found at all sites with the exception of the traffic station in Granada.Secondary nitrate (SN), Metallurgy (ME) and Heavy oil (HO) were identified at six of the eleven sites (Fig. S3 and Table 3).Tire wear (TW) contributions could be separated only at the traffic site of Granada Norte, where also a Traffic/Secondary (TS) factor, linked to atmospheric stagnation conditions, was found (Fig. S3 and Table 3).The yearly average road dust contribution was found to increase from rural (9-22 % of PM 10 ), urban-industrial (17-22 %), urban (29-34 %) to traffic (21-35 %) PM 10 levels (Fig. 4 and Table 3).Concerning PM 2.5 , road dust contributions were lower but the same pattern is shown: 7 %, 6-16 %, 11-31 % and 21-31 % respectively (Fig. 5 and Table 3).However it has to be noticed that road dust contributions show a marked Introduction

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Full seasonality with maxima in summer and minima in winter, likely due to the rainfall frequency (Fig. 6).
The time trend analysis shows statistically significant decreasing trends for the road dust source at two traffic sites (in Granada and Seville, with p values of 0.5 and 0.01 respectively) and at the urban background site in Córdoba (p value 0.05) in most cases accompanied by stronger and more significant trends also for vehicle exhaust emissions (Fig. S4 and S5).Overall, the downward trend of road dust contribution at the traffic sites can be estimated in −1.5-2.0 µg m −3 yr −1 which can be related to the decrease in construction/demolition activities from 2008 on, due to the financial crisis.As road dust sampling showed, particles generated by urban works increase significantly the road dust mass loadings on road surface and consequently also road dust emissions.The downward trend is in fact also found for the mineral source found at Granada Norte, Príncipes, Lepanto, Carranque, Los Barrios and La Línea.
No trend was observed at the traffic site in Málaga and at the urban background site in Seville (p value > 0.1), although in Seville a clear decrease can be observed after

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Full Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | the flat depression of Guadalquivir river and hosts the only inland port of Spain.Road traffic emissions have been partially reduced by the recent construction of tram and underground lines.
The Algeciras Bay hosts the largest port of Spain (70 millions of tonnes), oil refinery and stainless steel plants.It is around 10 km long by 8 km wide.It opens to the south into the Strait of Gibraltar, where around 80 000 ships per year leave the Mediterranean into the Atlantic.Due to all these activities along the shoreline, air pollution is a severe problem in the area.Heavy trucks visibly dominate road transport.This area is also characterized by a high population density, with more than 300 000 inhabitants.PM 2.5 samples were collected at the five provinces under study from 2003 to 2010.Details of most of the monitoring stations considered in this work can be found in de la Rosa et al.
rectangular filters) and MCV (30 m 3 h −1 onto circular filters) samplers with a frequency of 1-2 samples per week at all sites.A total of 2696 filters were collected on quartz fiber filters (Schleicher & Schuell, Munktell and Pallflex).Before sampling, quartz Discussion Paper | Discussion Paper | Discussion Paper | fiber filters were dried at 205 Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | 3. limit the sum of factor profile by the maximum of 1.
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Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Roads nearby works were enriched in Ca, Ti and Mg (due to the handling of constructing materials and hearths movements).
Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | −3 yr −1 (p = 0.001) and possibly due to local peculiarities such as the construction of new parking lot and urbanization in the vicinity of the monitoring site and the proximity to the national border between Spain and Gibraltar.Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper | Screen / Esc Printer-friendly Version Interactive Discussion Discussion Paper | Discussion Paper | Discussion Paper | Discussion Paper |

Fig. 1 .
Fig. 1.Map of the 11 monitoring sites (divided in six zones) used for the PM source apportionment study.
Querol et al. (2001)onditioned for 48 h at 20 • C and 50 % of relative humidity.Weights of blank filters were measured three times every 24 h (or five times in case of rectangular filters) by means of a Sartorius LA 130 S-F microbalance (1 µg sensitivity).After weighing filters were kept in aluminum foils and brought back to laboratory to be weighted two more times every 24 h.Once the weights of samples were determined, filters were destined to several analytical (destructive) treatments.These procedure are briefly listed below, more details are available inQuerol et al. (2001): 2.5 analysis at Los Barrios, Algecíras, La Línea and PM 10 analysis at

Table 1 .
Details of PM monitoring sites and sampling periods.

Table 2 .
Road dust composition averaged per road category. 1