aerosol characterization study in santiago de chile ... · aerosol characterization study in...

Report Prepared for

CONAMA - RM - Comission Nacional del Medio Ambiente - Santiago de Chile

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Part of the study:

“Caracterización Físicoquimica del Material Particulado Inorgánico Primario.Distribución por Tamaño y Modelo Receptor”

Prof. Paulo ArtaxoApplied Physics Department, Institute of Physics, University of São Paulo, Rua do

Matão, Travessa R, 187, CEP 05008-900, São Paulo, Brazil. Phone:[55](11)8187016, FAX:[55](11)8186749, e-mail: [email protected]

IIInnndddeeexxx1 – Introduction Pg. 22 - Aerosol sampling and analysis Pg. 2

2.1- Elemental analysis of aerosol samples by PIXE Pg. 32.2- Aerosol source apportionment and receptor modeling Pg. 6

3 - Results and discussion for the wintertime 1998 sampling campaign Pg. 73.1 – Aerosol mass concentrations Pg. 73.2 - Quality assurance of mass concentration measurements Pg. 133.3 – Black carbon aerosol concentration Pg. 163.4 – Aerosol elemental concentrations Pg. 183.5 – Aerosol source apportionment Pg. 283.6 – Aerosol source apportionment O’Higgins fine mode Pg. 283.7 – Aerosol source apportionment O’Higgins coarse mode Pg. 323.8 – Aerosol source apportionment Las Condes fine mode Pg. 353.9 – Aerosol source apportionment Las Condes coarse mode Pg. 383.10 – Aerosol source apportionment Pudahuel fine mode Pg. 403.11 – Aerosol source apportionment Pudahuel coarse mode Pg. 433.12 – Aerosol source apportionment Peldehue fine mode Pg. 453.13 – Aerosol source apportionment Peldehue coarse mode Pg. 473.14 – Aerosol source apportionment Talagante fine mode Pg. 493.15 – Aerosol source apportionment Talagante coarse mode Pg. 513.16 – Comparison of elemental sources profiles Pg. 53

4 – Aerosol size distributions Pg. 564.2 – Black carbon aerosol size distributions Pg. 58

5 – Conclusions Pg. 596 – References and bibliography Pg. 60

Aerosols in Santiago de Chile Wintertime 1998 – Pg. 2

111 --- IIInnntttrrroooddduuuccctttiiiooonnnSantiago de Chile suffers from heavy air pollution episodes during wintertime.

Aerosol particles are one of the most important air pollutants in the Santiago airbasin. In

order to study the aerosol sources in Santiago area, an aerosol source apportionment study

was designed to measures ambient aerosol composition and size distribution for five sites

in the winter of 1998. The study was a cooperation between the Institute of Physics,

University of São Paulo and CONAMA-RM.

222 --- AAAeeerrrooosssooolll sssaaammmpppllliiinnnggg aaannnddd aaannnaaalllyyysssiiisssSampling was performed during wintertime 1998, with a 12 or 24 hour sampling

time. The sampler was the “Gent” Stacked Filter Unit [Hopke et al., 1997, Parker et al.,

1977, Cahill et al., 1979], fitted with a specially designed inlet that provided a 50 % cutoff

diameter of 10 µm. Fine and coarse aerosol particles were sampled with the SFU using

Nuclepore filters. The SFU collects coarse mode particles (2.0 < dp < 10 µm) on a 47-mm-

diameter, 8-µm pore size Nuclepore filter while a 0.4-µm pore size Nuclepore filter

collects the fine mode particles (dp < 2.0 µm) [John et al., 1983]. The flow rate was

typically 17 liters per minute. Particle bounce was minimized by the use of Apiezon coated

coarse mode filters. The volume was obtained with volume integrators, calibrated with

Hastings Precision Mass Flowmeters, to within 1% accuracy. The sampling time was 12

hours, separated for day and night for each of the sites in the urban area of Santiago

(O’Higgins, Las Condes and Pudahuel) and 24 hours for the other more remote sites

(Peldehue and Talagante).

A MOUDI (Multi-Orifice Uniform Deposit Impactor) cascade impactor was used

to collect size-segregated aerosol samples. The 8-stages of the MOUDI cascade impactor

have d50 size cuts at 18, 3.2, 1.8, 1.0, 0.56, 0.33, 0.175, and 0.093µm equivalent

aerodynamic diameter. A Teflon after-filter collected all particles smaller than 0.093 µm.

Gravimetric analysis of fine and coarse mode SFU samples allows the

determination of fine and coarse mode aerosol mass concentration. A Mettler electronic

microbalance with 1µm sensitivity in an environmental controlled room is used to weigh

the filters. Black carbon concentration was measured in the fine aerosol fraction using an

optical absorption technique, with a Diffusion System photometer.

Five sampling sites were operated in O’Higgins, Las Condes, Pudahuel, Talagante,


and Peldehue. The O’Higgins site is at Santiago downtown, and is heavily impacted by

traffic and vehicular emissions. The Las Condes site is also impacted by heavy traffic, and

is impacted by regional emissions. The Pudahuel site is located near the Santiago airport.

The two other sites, Peldehue and Talagante are sites far from downtown Santiago, but still

impacted by regional air pollution sources. These sites represent very different regions in

terms of air pollution loading and impact from the main aerosol sources in Santiago de

Chile. In the wintertime of 1996, a similar but smaller air pollution study have sampled

aerosol samples at the Gotuzo site, near O’Higgins site, and comparisons between 1996

and 1998 aerosol composition for these sites can be done. Also a sampling station in the

Las Condes site was operated in 1996, but in a site farther away from sources than the Las

Condes 1998 site, so concentrations are not directly comparable for these two sites.

Sampling was performed from July 15 to August 22, 1998. Table 2.1 presents the sampling

timing and the number of samples collected in each of the 5 sites. A significant number of

aerosol samples was collected for each sampling site.

Table 3.1 – Sampling data for the Santiago de Chile wintertime 1998 samplingprogram.

Sampling site Starting of aerosolsampling

End of aerosolsampling

Number of aerosolsamples collected

O'Higgins 15/July 20/August 60

Pudahuel 15/July 18/August 60

Las Condes 20/July 19/August 60

Talagante 17/July 17/August 28

Peldehue 23/July 22/August 30

222...111--- EEEllleeemmmeeennntttaaalll aaannnaaalllyyysssiiisss ooofff aaaeeerrrooosssooolll sssaaammmpppllleeesss bbbyyy PPPIIIXXXEEEParticle Induced X-ray Emission – PIXE [Johanson and Campbell, 1985] was used

to measure about 20 trace elements (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu,

Zn, As, Br, Sr, Pb). Irradiation was performed at the LAMFI – Laboratório de Análises de

Materiais por Feixes Iônicos from the Institute of Physics, University of São Paulo. Figure

2.1.1 shows a schematic view of the São Paulo PIXE system.

A 2.4 MeV proton beam irradiates the samples and X-rays are produced and

collected. The system uses an innovative detection system with two Si(Li) detectors with

12µm Be window and 138 eV resolution for the Mn Kα line. A low Z detector has an

80µm Be X-ray absorber, and the high Z detector has a 380µm Mylar X-ray absorber.


Irradiation time is 10 minutes at a count rate of 2500 cps for the low Z detector and 500-

cps for the high Z detector. These count rates and the use of two Si(Li) detectors avoids

problems with pile-up peaks and dead time corrections. Typical detection limits for normal

operational conditions in Santiago de Chile are presented in Figure 2.1.2.

��

CurrentIntegrador

Data acquisitionsystem

Beam Colimator

Aerosolsample

High energyX-ray Si(Li)

detector


Protons Beam 2.4 MeV

Low EnergyX-ray Si(Li)

detector

��

��

Faradaycup

Low energyX-ray Si(Li)

detector

Proton Beam 2.4 MeV

High energyX-ray Si(Li)

detector

Currentintegrator



Aerosolsample

Beamcolimator

Faradaycup

Figure 2.1.1 - Schematic view of the irradiation conditions of the São Paulo PIXEsystem.

0.1

1

10

100

Elem

enta

l con

cent

ratio

n (n

g/m

³)

MgAl

SiP

SCl

KCa

TiV

CrMn

FeNi

CuZn

AsSe

BrRb

SrZr

NbMo

Pb

Elements

São Paulo PIXE System Detection LimitsSFU 20 m³ volume, 80 µC, Nuclepore

Figure 2.1.2 - Typical detection limits for the São Paulo PIXE system obtained forNuclepore filters with a volume of 20 m³, and a proton charge of about 80µC.


1E0

1E1

1E2

1E3

1E4

1E5

Cou

nts

0 100 200 300 400 500 600 700 800 900 1000 Channel

AlSi

P SCl

KCa

Ti

V

Cr Mn

Fe

Fe

NiCu Zn

Pb

BrPb

Rb

ZrSr

Al

Si

P SCl K

Ca

High energy X-ray detector Low energy X-ray detector

São Paulo PIXE system spectra

Figure 2.1.3 - Typical X-ray spectra from the São Paulo PIXE system. Twospectra are shown one for low-energy X-rays, detecting elements from Sodium toCalcium. The second spectra are collected to measure elements with Z higherthan Ca.

For each analyzed aerosol sample, two spectra are recorded, one from the low-Z

detector and a second from a high-Z detector. A typical x-ray spectra from the São Paulo

PIXE system is presented in Figure 2.1.3. The reproducibility of the system irradiating the

same aerosol sample many times is about 7 % for most of the elements. Figure 2.1.4

presents some results from the quality assurance tests performed routinely as part of the

irradiation procedures in the São Paulo PIXE system. A set of standard reference materials

samples from NIST; IAEA and other agencies are routinely analyzed as “unknown”

samples. The average standard deviation for most of the detected elements is 14%. This is

a good result, because many of these samples are not with the thin sample criteria, having

grain sizes larger than 10-50µm, leading to problems in the quantification procedures due

to X-ray self absorption in the particles.


1E1

1E2

1E3

1E4

1E5C

ertif

ied

Valu

es (µ

g/g)

1E1 1E2 1E3 1E4 1E5PIXE (µg/g)

PIXE analysis of certified standartof sediment and soil for:

Al, Si, P, S, K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Rb, Sr, Zr e Pb

a)

-1.0

-0.5

0.0

0.5

1.0

Res

idue

(PIX

E-St

and.

/Cer

t. Va

lue)

Al S K Ca Ti V Cr Mn Fe Ni Cu Zn Br Rb Sr Zr Pb

SL-1 IAEA356 BRS LKSD-3 SOIL-7

Residue for Element in theCertified standart

+/- 14 %

b)

Figure 2.1.4 – Quality assurance of the São Paulo PIXE system. a) Comparison ofPIXE measurements in µg/g with certified values for soil and sediment referencematerials. The average agreement between measured and certified concentrationsis about 8 %; b) Relative residuals for the reference material analysis.

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To separate the different aerosol components, absolute principal factor analysis

(APFA) was used [Thurston and Spengler, 1985; Hopke, 1985]. APFA can provide a


quantitative elemental source profile, instead of just a qualitative factor-loading matrix as

in traditional factor analysis. The absolute elemental source profiles help in the

identification of the factors, and can be used to quantitatively compare the factor

composition with assumed aerosol sources. The APFA provides the elemental mass

contribution of each identified component by calculating the absolute principal factor

scores (APFS) for each sample [Artaxo et al., 1988, 1990]. The elemental concentrations

are subsequently regressed on the APFS to obtain the contribution of each element for each

component. The source profiles thus obtained can be compared with values from the

literature to gain information on enrichment and atmospheric chemistry processes [Hopke,

1985]. The measured aerosol mass concentration can be regressed on the APFS to obtain

the aerosol total mass source apportionment. It is important to notice that the factor model

deals with trace element variability, so if two elements that are emitted by different sources

co-vary together, they could be identified in the same component. This fact must be taken

in account in interpreting the factor analysis results.

Cluster analysis was used to measure the distances in the elemental space between

the samples and the variables. The dendogram express the distances between the variables

taking the samples as a multivariate space and measuring the distances between the aerosol

samples. The result is expressed as a distance chart, the dendogram. Ward’s error sum

strategy was used to classify the samples, and the squared Euclidean distance was used to

measure the distances. It is important to notice that cluster analysis is a completely

independent statistical analysis from factor analysis. Although factor analysis analyzes data

variability, cluster analysis analyzes distances between the samples in the elemental space.

SPSS for Windows version 8.0 was used in the receptor modeling calculations.

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The extensive set of results will be presented and discussed first with the mass and

black carbon concentrations for all the stations, and latter for the composition and aerosol

source apportionment for each sampling station separately. Finally, a comparison of results

and elemental source profiles for all sites will be presented.

333...111 ––– AAAeeerrrooosssooolll mmmaaassssss cccooonnnccceeennntttrrraaatttiiiooonnnsssThe aerosol mass concentration is the most important parameter when it is

necessary to compare air pollution measurements with the legislation, or to assess the


health impact on the affected population. The aerosol mass concentration in urban areas is

generally dominated by organic aerosol that accounts for 40 – 70 % of the aerosol mass in

fine or coarse mode.

Table 3.1.1 shows the average gravimetric and black carbon concentrations for the

wintertime 1998 sampling campaign. High levels of PM10 aerosol were observed in the

three urban sites and also elevated concentrations were observed in the two more remote

sites. The same Table 3.1.1 shows average values measured in sampling campaigns in

1996 for the sites Gotuzo, Las Condes and Buin. For O’Higgins and Pudahuel, coarse

mode aerosol concentrations are higher than the fine fraction, indicating that soil dust

ressuspension has an important air pollution impact in these sites. In the Las Condes,

Talagante and Peldehue sites, each of the two size fractions, fine and coarse mode aerosols

account for approximately 50 % of PM10 aerosol concentration. Also black carbon

concentrations are high in all sites, averaging 12 µg/m³ in O’Higgins, and 15 µg/m³ in Las

Condes. In The O’Higgins sites, black carbon accounts for a high 20.5% of the fine mode

aerosol mass, indicating a strong impact of buses and automobile traffic sources in

downtown Santiago. The variability in the aerosol concentration is high, with peak 12-hour

averages exceeding 200 to 300 µg/m³ several times during the sampling period and for

several of the sampling sites.

Table 3.1.1 – Average aerosol mass concentrations in Santiago wintertime 1998.Also shown for comparison, measurements made in Santiago during wintertime1996 and in São Paulo downtown in 1997 using the same aerosol sampler. (*)

Sampling Site FPM(µg/m³)

CPM(µg/m³)

PM10(µg/m³)

FPM/PM10(%)

CPM/PM10(%)

BC(µg/m³)

BC/FPM(%)

O'Higgins 39.74 92.61 132.35 30.02 69.97 8.46 21.28

Las Condes 40.29 40.43 80.72 49.35 49.52 5.46 13.55

Pudahuel 32.59 83.20 115.79 28.15 71.85 5.79 17.77

Peldehue 37.53 40.43 77.96 48.14 51.86 3.39 9.03

Talagante 31.00 34.38 65.38 47.42 52.58 2.68 8.65

Gotuzo 96 54.40 94.00 148.40 36.66 63.34 10.35 19.0

Las Condes 96 35.70 41.10 76.80 46.48 53.52 3.53 9.89

Buin 96 29.10 23.20 52.30 55.64 44.36 2.31 7.94

São Paulo 97 39.02 57.91 96.93 40.26 59.74 8.58 21.99

(*); FPM - Fine mode aerosol mass concentration, particles with aerodynamicdiameter dp<2 µm. CPM - Coarse mode aerosol mass concentration, particles withaerodynamic diameter 2<dp<10µm. PM10 - Inhalable particle mass concentration


(particles smaller than 10 µm). BC is the black carbon concentration in the finemode.

It is difficult to find in the scientific literature data to compare with our

measurements, because of different aerosol samplers and different sampling period along

the year. Only one work is similar to the one performed by us, and was made in 1990 by

Carlos Rojas (Rojas et al., 1990), with sampling done at the University of Chile campus

during January and February 1987. Rojas et al. reports average fine mode concentrations of

34.0 µg/m³, CPM of 66.0 µg/m³ and PM10 average of 100 µg/m³, values similar to the ones

measured by us in the Pudahuel and Las Condes sampling sites. PM10 values for downtown

São Paulo are in the vicinity of 75 - 100µg/m³, values similar to the ones measured in

Santiago. For both cities, São Paulo and Santiago, traffic is the major source of

atmospheric pollutants.

0 10 20 30 40 50 60 70 80 90

100 110 120 130 140 150 160 170 180

Con

cent

ratio

n (µ

g/m

³)

O'Higgins Las Condes Pudahuel Peldehue Talagante Gotuzo 96 Las Condes 96 Buin 96 São Paulo 97

FPM CPM PM10

Santiago de Chile Aerosol Winter 1998Average Gravimetric Concentrations

Samples from Winter 98 Samples from Winter 96 São Paulo 1997

Figure 3.1.1 - Average fine, coarse and PM10 aerosol concentrations measuredin the Santiago 1998 sampling program for the five sampling sites. Also shown arethe averages for the sampling campaigns of 1996 and 1995, using the samemethodology.

Figure 3.1.1 shows the average fine, coarse and PM10 gravimetric concentrations

measured in the Santiago 1998 sampling program. Also shown in the same figure are

averages for the sampling campaigns of 1996 and São Paulo, using the same methodology.

There was a reduction in PM10 at downtown Santiago, as can be seen comparing

measurements in Gotuzo 1996 and O’Higgins 1998. This reduction occurred for both fine

and coarse aerosol fraction, but the largest reduction was in the fine mode aerosol. This is

the component that has the largest health effects. Comparing to São Paulo, concentrations

in Santiago are higher, mainly due to coarse mode soil dust, because the Chilean climate is


much dryer than São Paulo. Fine mode concentrations in São Paulo is identical to the fine

mode component in O’Higgins and Las Condes, indicating similar traffic impact.

0

1

2

3

4

5

6

7

8

9

10

11

12

13 C

once

ntra

tion

(µg/

m³)

O'HigginsLas Condes

PudahuelPeldehue

Talagante Gotuzo 96Las Condes 96

Buin 96 São Paulo 97

Santiago de Chile Aerosol Winter 1998Average Black Carbon Concentrations


Figure 3.1.2 - Average black carbon concentrations measured in the fine modeaerosol from Santiago 1998 sampling program for the five sampling sites. Alsoshown are the averages for the sampling campaigns of 1996, and measurementsdone in São Paulo, using the same methodology.

0 2 4 6 8

10 12 14 16 18 20 22 24 26

Perc

enta

ge o

f BC

in F

PM (%

)

O'HigginsLas Condes

PudahuelPeldehue

Talagante Gotuzo 96Las Condes 96

Buin 96 São Paulo 97

Santiago de Chile Aerosol Winter 1998Average Ratio Black Carbon to FPM


Figure 3.1.3 - Average ratio of black carbon to fine mode mass concentrationmeasured in the fine mode aerosol from Santiago 1998 sampling program for thefive sampling sites.

The Figure 3.1.2 shows the average black carbon concentrations measured in the

fine mode aerosol from Santiago 1998 sampling program for the five sampling sites. BC is

much higher in O’Higgins than in the other four sites, indicating the impact of diesel

emissions downtown Santiago. Comparing values from 1996, BC concentrations are about

20 % lower, indicating progresses in the control of diesel emissions. Black carbon


concentrations in downtown Santiago and São Paulo are very similar, again indicating

similar impact from traffic. The ratio of black carbon to fine aerosol mass in O’Higgins is

identical to São Paulo. The values are similar to the ones measured in Gotuzo in 1996.

From the concentrations in Peldehue, Talagante and Buin (1996), the background black

carbon concentrations in these sites are about 8 µg/m³, an elevated value.

0 20 40 60 80

100 120 140 160 180 200 220 240 260 280 300 320

O'H

iggi

ns F

PM, C

PM a

nd P

M10

(µg/

m³)

OHI 01 F OHI 03 F

OHI 05 F

OHI 07 F OHI 09 F

OHI 11 F

OHI 13 F OHI 15 F

OHI 17 F

OHI 19 F OHI 21 F

OHI 23 F

OHI 25 F OHI 27 F

OHI 29 F

OHI 31 F OHI 33 F

OHI 35 F

OHI 37 F OHI 39 F

OHI 41 F

OHI 43 F OHI 45 F

OHI 47 F

OHI 49 F OHI 51 F

OHI 53 F

OHI 55 F OHI 57 F

OHI 59 F

Fine Mode Coarse Mode

Santiago Wintertime 1998 AerosolO'Higgins FPM, CPM and PM10

Figure 3.1.4 – Time series of fine, coarse and PM10 aerosol mass concentrationfor the O’Higgins sampling site.

0

20

40

60

80

100

120

140

160

180

Las

Con

des

FPM

, CPM

and

PM

10 (µ

g/m

³)

LCD 01 F LCD 03 F

LCD 05 F

LCD 07 F LCD 09 F

LCD 11 F

LCD 13 F LCD 15 F

LCD 17 F

LCD 19 F LCD 21 F

LCD 23 F

LCD 25 F LCD 27 F

LCD 29 F

LCD 31 F LCD 34 F

LCD 36 F

LCD 38 F LCD 40 F

LCD 42 F

LCD 44 F LCD 46 F

LCD 48 F

LCD 50 F LCD 52 F

LCD 54 F

LCD 56 F LCD 58 F

LCD 60 F


Santiago Wintertime 1998 AerosolLas Condes FPM, CPM and PM10

Figure 3.1.5 - – Time series of fine, coarse and PM10 aerosol mass concentrationfor the Las Condes sampling site.

The Figure 3.1.4 shows the time series of fine, coarse and PM10 aerosol mass

concentration for the O’Higgins sampling site. It is possible to observe that during air

pollution episodes the PM10 concentrations can exceed 200 µg/m³. The interesting point is

that during these air pollution episodes, the coarse mode fractions increase more than the


fine fraction. A strategy to control road dust trough road cleaning can help in this situation.

The figure 3.1.5 shows the time series for Las Condes. In Las Condes only one important

episode with concentrations higher than 150µg/m³ was observed. Proportionally, it is

possible to observe in Las Condes a higher impact of fine particles than O’Higgins. Figure

3.1.6 shows the time series of FPM, CPM and PM10 Pudahuel sampling site. Several air

pollution episodes can be observed, mostly caused by coarse mode particles.

0 20 40 60 80

100 120 140 160 180 200 220 240 260 280 300 320

Puda

huel

FPM

, CPM

and

PM

10 (µ

g/m

³)

PAD 01 F PAD 03 F

PAD 05 F

PAD 07 F PAD 09 F

PAD 11 F

PAD 13 F PAD 15 F

PAD 17 F

PAD 19 F PAD 21 F

PAD 23 F

PAD 25 F PAD 27 F

PAD 29 F

PAD 31 F PAD 33 F

PAD 35 F

PAD 37 F PAD 39 F

PAD 41 F

PAD 43 F PAD 45 F

PAD 47 F

PAD 49 F PAD 51 F

PAD 53 F

PAD 55 F PAD 57 F

PAD 59 F


Santiago Wintertime 98 AerosolPudahuel FPM, CPM and PM10

Figure 3.1.6 - – Time series of fine, coarse and PM10 aerosol mass concentrationfor the Pudahuel sampling site.

0

20

40

60

80

100

120

140

160

180

200

Peld

ehue

FPM

, CPM

and

PM

10 (µ

g/m

³)

PEL 01 F PEL 02 F

PEL 03 F

PEL 04 F PEL 05 F

PEF 06 F

PEL 07 F PEL 08 F

PEL 09 F

PEL 10 F PEL 11 F

PEL 12 F

PEL 13 F PEL 14 F

PEL 15 F

PEL 16 F PEL 17 F

PEL 18 F

PEL 19 F PEL 20 F

PEL 21 F

PEL 22 F PEL 23 F

PEL 24 F

PEL 25 F PEL 26 F

PEL 27 F

PEL 28 F PEL 29 F

PEL 30 F


Santiago Wintertime 1998 AerosolPeldehue FPM, CPM and PM10

Figure 3.1.7 – Time series of fine, coarse and PM10 aerosol mass concentrationfor the Peldehue sampling site.

Figure 3.1.7 shows the Peldehue results, with a strong presence of fine particles for

a type of more remote sampling site. A similar feature happens in Talagante, as can be

observed in Figure 3.1.8. Concentrations in Talagante in the fine mode are much more


constant than the other sites, reflecting a more regional feature, and that it is less impacted

by local air pollution sources.

0 10 20 30 40 50 60 70 80 90

100 110 120 130 140

Tala

gant

e FP

M, C

PM a

nd P

M10

(µg/

m³)

TGT 01 F TGT 02 F

TGT 03 F

TGT 04 F TGT 05 F

TGT 06 F

TGT 07 F TGT 08 F

TGT 10 F

TGT 11 F TGT 12 F

TGT 13 F

TGT 14 F TGT 15 F

TGT 16 F

TGT 17 F TGT 18 F

TGT 19 F

TGT 20 F TGT 21 F

TGT 22 F

TGT 23 F TGT 24 F

TGT 25 F

TGT 26 F TGT 27 F

TGT 28 F

TGT 29 F TGT 30 F


Santiago Wintertime 1998 AerosolTalagante FPM, CPM and PM10

Figure 3.1.8 - – Time series of fine, coarse and PM10 aerosol mass concentrationfor the Talagante sampling site.

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Quality assurance of measured concentrations is an integral part of all air pollution

study. We performed several quality control procedures trough all phases of our

experiment.

0 10 20 30 40 50 60 70 80 90

100 110 120 130 140

Con

cent

ratio

ns (µ

g/m

³)

O'Higgins Las Condes Pudahuel Peldehue Talagante

SFU PM10 TEOM PM10

Comparison PM10 for SFU and TEOMSantiago 1998 Average Concentrations

Figure 3.2.1 – Comparison of PM10 measurements performed by the StackedFilter Unit and the TEOM sampler.


Figure 3.2.1 shows the comparison of co-located Stacked Filter Units (SFU) and

TEOM (Tapered Oscilating Microbalance) aerosol monitors. The agreement between the

two independent measurements is excellent. It is important to notice that the measurement

principle of TEOM and the SFU are completely different. In figure 3.2.2 it can be

observed the largest variability in PM10 that affects both measurements are caused by the

coarse faction. Fine fraction is almost constant along the five sampling sites, with lower

concentrations in Talagante.

0

20

40

60

80

100

120

140

160

Con

cent

ratio

ns (µ

g/m

³)

FPM CPM SFU PM10 TEOM PM10

OHiggins Las Condes Pudahuel Peldehue Talagante

Santiago de Chile Aerosol 1998Average Gravimetric Concentrations

Figure 3.2.2 – Average gravimetric concentrations of FPM, CPM, SFU PM10 andTEOM PM10.

São Paulo Experiment - FMSP 1997 WinterComparison of PM10 Concentration

SFU x TEOM

0

50

100

150

200

250

300

12-A

ug

14-A

ug

15-A

ug

17-A

ug

18-A

ug

20-A

ug

21-A

ug

23-A

ug

24-A

ug

26-A

ug

27-A

ug

29-A

ug

30-A

ug1-S

ep2-S

ep4-S

ep5-S

ep7-S

ep8-S

ep

Conc

entr

atio

n (µ

g/m

³)

SFU TEOM

SFU = 99 µg/m³TEOM = 83 µg/m³

Figure 3.2.3 – Comparison of PM10 measurements performed by the StackedFilter Unit and the TEOM sampler for São Paulo, winter of 1997. The regressionequation between the samplers is TEOM = 0.86*SFU - 2.33, with an R² of 0.96.

Similar comparisons between a TEOM sampler and the SFU were performed in


São Paulo. Figure 3.2.3 shows a time series of such comparison. The SFU in São Paulo

measures higher concentrations than the TEOM. Both instruments agree very well, with

TEOM concentrations lower by about 14% in average. The TEOM sampler heats up the

aerosol to remove humidity that interferes with the measurement procedure. This can cause

some loss of organic components.

0 20 40 60 80

100 120 140 160 180

PM10

Mas

s C

once

ntra

tion

(ug/

m3)

165166

168

169171

172

174176

178

180182

184

187189

192

194196

198

203205

207

209211

213

215217

219

221223

226

228230

236

240

1994 Julian DayPM10 SFU Gent PM10 Beta

São Paulo Aerosol CharacterizationPM10 Mass Concentration 1994

Figure 3.2.3 – São Paulo Inhalable aerosol mass concentration (PM10) providedby the beta gauge aerosol monitoring instrument operated by the state air pollutioncontrol agency (CETESB) nearby SFU equipped with an PM10 inlet.

0 20 40 60 80

100 120 140 160 180

PM10

Bet

a G

auge

(ug/

m3)

0 20 40 60 80 100 120 140 160 180 PM10 Gent SFU (ug/m3)

São Paulo Aerosol Characterization 94PM10 - Beta Gauge versus Gent SFU

PM10 Beta = PM10 SFU*0.992 - 2.214 (R2=0.86)

Figure 3.2.4 – Regression curve between the measurements from the two


instruments (Beta gauge and SFU) for PM10 in São Paulo. Same data series asplotted in figure 3.2.2.

Figure 3.2.3 shows a comparison between SFU and beta gauge sampled in parallel

in São Paulo. The ratio between the two samplers showed in figure 3.2.4 is 0.992,

indicating that the SFU can very reliably express aerosol mass concentrations.

333...333 --- BBBlllaaaccckkk cccaaarrrbbbooonnn aaaeeerrrooosssooolll cccooonnnccceeennntttrrraaatttiiiooonnnBlack carbon is an excellent tracer for the urban impact of diesel and vehicles

emissions. A small fraction of BC could be due to combustion processes in the industrial

sector. The Figure 3.3.1 shows the time series of black carbon aerosol concentrations

measured in the O’Higgins sampling site. According to German air pollution standards, BC

concentrations should not exceed 10 µg/m³. This was the case for several aerosol samples

collected at the O’Higgins site. The average values for BC concentrations in O’Higgins

was 8.46 µg/m³. The Figure 3.3.2 shows similar measurements at the Las Condes

sampling site. Las Condes shows more uniform values, with average at 5.46µg/m³, and

peaks at 7-8 µg/m³. Black carbon time series in Pudahuel, showed in Figure 3.3.3 exhibits

a more episodic nature than in Las Condes, with a baseline concentration of about 3 µg/m³

of black carbon. Peldehue and Talagante show a baseline value of about 2 µg/m³.

0 2 4 6 8

10 12 14 16 18 20 22 24 26 28 30

O'H

iggi

ns B

lack

Car

bon

(µg/

m³)

OHI 01 F OHI 03 F

OHI 05 F

OHI 07 F OHI 09 F

OHI 11 F

OHI 13 F OHI 15 F

OHI 17 F

OHI 19 F OHI 21 F

OHI 23 F

OHI 25 F OHI 27 F

OHI 29 F

OHI 31 F OHI 33 F

OHI 35 F

OHI 37 F OHI 39 F

OHI 41 F

OHI 43 F OHI 45 F

OHI 47 F

OHI 49 F OHI 51 F

OHI 53 F

OHI 55 F OHI 57 F

OHI 59 F

Santiago Wintertime 1998 AerosolO'Higgins Black Carbon

Figure 3.3.1 – Black Carbon concentration in µg/m³ measured in the fine modefraction of aerosols from the O’Higgins sampling station.


0

1

2

3

4

5

6

7

8

9

10

11

12

Las

Con

des

Blac

k C

arbo

n (µ

g/m

³)

LCD 01 F LCD 03 F

LCD 05 F

LCD 07 F LCD 09 F

LCD 11 F

LCD 13 F LCD 15 F

LCD 17 F

LCD 19 F LCD 21 F

LCD 23 F

LCD 25 F LCD 27 F

LCD 29 F

LCD 31 F LCD 34 F

LCD 36 F

LCD 38 F LCD 40 F

LCD 42 F

LCD 44 F LCD 46 F

LCD 48 F

LCD 50 F LCD 52 F

LCD 54 F

LCD 56 F LCD 58 F

LCD 60 F

Santiago Wintertime 1998 AerosolLas Condes Black Carbon

Figure 3.3.2 – Black Carbon concentration in µg/m³ measured in the fine modefraction of aerosols from the Las Condes sampling station.

0 1 2 3 4 5 6 7 8 9

10 11 12 13 14 15 16

Puda

huel

Bla

ck C

arbo

n (µ

g/m

³)

PAD 01 F PAD 03 F

PAD 05 F

PAD 07 F PAD 09 F

PAD 11 F

PAD 13 F PAD 15 F

PAD 17 F

PAD 19 F PAD 21 F

PAD 23 F

PAD 25 F PAD 27 F

PAD 29 F

PAD 31 F PAD 33 F

PAD 35 F

PAD 37 F PAD 39 F

PAD 41 F

PAD 43 F PAD 45 F

PAD 47 F

PAD 49 F PAD 51 F

PAD 53 F

PAD 55 F PAD 57 F

PAD 59 F

Santiago Wintertime 98 AerosolPudahuel Black Carbon

Figure 3.3.3 – Black Carbon concentration in µg/m³ measured in the fine modefraction of aerosols from the Pudahuel sampling station.


0

1

2

3

4

5

6

7

8

Peld

ehue

Bla

ck C

arbo

n (µ

g/m

³)

PEL 01 F PEL 02 F

PEL 03 F

PEL 04 F PEL 05 F

PEF 06 F

PEL 07 F PEL 08 F

PEL 09 F

PEL 10 F PEL 11 F

PEL 12 F

PEL 13 F PEL 14 F

PEL 15 F

PEL 16 F PEL 17 F

PEL 18 F

PEL 19 F PEL 20 F

PEL 21 F

PEL 22 F PEL 23 F

PEL 24 F

PEL 25 F PEL 26 F

PEL 27 F

PEL 28 F PEL 29 F

PEL 30 F

Santiago Wintertime 1998 AerosolPeldehue Black Carbon

Figure 3.3.4 – Black Carbon concentration in µg/m³ measured in the fine modefraction of aerosols from the Peldehue sampling station.

0

1

2

3

4

5

6

7

Tala

gant

e Bl

ack

Car

bon

(µg/

m³)

TGT 01 F TGT 02 F

TGT 03 F

TGT 04 F TGT 05 F

TGT 06 F

TGT 07 F TGT 08 F

TGT 10 F

TGT 11 F TGT 12 F

TGT 13 F

TGT 14 F TGT 15 F

TGT 16 F

TGT 17 F TGT 18 F

TGT 19 F

TGT 20 F TGT 21 F

TGT 22 F

TGT 23 F TGT 24 F

TGT 25 F

TGT 26 F TGT 27 F

TGT 28 F

TGT 29 F TGT 30 F

Santiago Wintertime 1998 AerosolTalagante Black Carbon

Figure 3.3.5 – Black Carbon concentration in µg/m³ measured in the fine modefraction of aerosols from the Talagante sampling station.

333...444 ––– AAAeeerrrooosssooolll eeellleeemmmeeennntttaaalll cccooonnnccceeennntttrrraaatttiiiooonnnsssAverage elemental concentrations and related data for each of the five sampling

stations and fine and coarse mode data are presented in Tables 3.4.1 to 3.4.10. In these

tables the population standard deviation is also presented, as well as minimum and

maximum concentration values. The number of samples where the element was detected

above detection limits is presented in the last column. In calculating averages, only values

above detection limits were considered to avoid problems with estimation of missing

values.


Table 3.4.1 - O’Higgins Fine mode average concentration and other statistics. Std.Dev. is the population standard deviation, Min. and Max. are minimum andmaximum concentration and N is the number of samples where the variable wasmeasured above detection limits. Concentrations of elements are presented inng/m³. Mass (FPM and CPM) and black carbon (BC) is in µg/m³.

O’HigginsFine Average Std. Dev. Min. Max. N

FPM 39.74 19.00 11.64 100.34 60CPM 92.61 49.69 13.17 236.25 60BC 8.46 5.31 1.04 28.24 60Mg 120.60 87.80 17.79 315.91 23Al 776.00 226.70 392.38 1402.24 60Si 657.21 413.17 111.04 2006.95 60 P 15.74 7.42 4.40 35.48 29 S 1841.16 1339.49 408.36 6371.28 60Cl 100.16 58.37 28.62 390.64 60 K 307.24 152.78 104.58 868.02 60Ca 280.24 130.30 77.64 677.02 60Sc 3.37 1.01 2.65 4.09 2Ti 55.14 19.48 24.13 114.59 60V 7.41 4.11 1.51 18.35 60Cr 7.51 4.57 2.87 22.07 22Mn 21.33 12.86 4.78 68.94 60Fe 456.51 172.80 187.42 864.47 60Ni 2.58 1.60 0.42 7.94 60Cu 35.48 18.83 5.33 83.62 60Zn 107.41 72.41 13.74 285.36 60As 49.01 32.31 7.44 130.00 60Br 74.97 57.41 7.86 236.88 60Sr 5.05 1.50 1.96 7.74 60Pb 176.75 120.85 24.48 635.85 60

In general, aerosol mass concentration as well as black carbon and sulfur are high

compared to other urban sites. Concentration of soil dust-related elements are also high,

indicating the importance of ressuspended soil dust in the atmosphere of Santiago. Latter,

in this section, a comparison with São Paulo average concentrations will be presented.


Table 3.4.2 - O’Higgins coarse mode average concentration and other statistics.See legend of Figure 3.4.1.

O’HigginsCoarse Average Std. Dev. Min. Max. N

FPM 39.74 19.00 11.64 100.34 60CPM 92.61 49.69 13.17 236.25 60PM10 131.63 58.34 24.82 260.25 60Mg 530.76 221.84 152.20 1197.35 60Al 3010.43 1437.26 766.23 7113.11 60Si 7235.93 3718.93 1602.58 17708.43 60 P 82.69 47.87 13.41 233.00 60 S 1700.23 1101.61 114.77 4397.81 60Cl 529.10 491.85 53.97 2936.87 60 K 975.10 523.77 186.09 2714.26 60Ca 3103.84 1573.82 541.81 7300.19 60Sc 12.84 5.39 6.67 16.65 3Ti 402.49 201.76 76.87 926.84 60V 18.56 10.40 3.81 49.35 60Cr 21.03 13.71 6.84 60.85 30Mn 95.21 49.66 15.64 239.42 60Fe 3430.05 1736.08 652.20 8457.25 60Ni 3.92 2.39 0.43 9.28 40Cu 90.03 59.22 4.95 226.00 60Zn 202.72 137.16 21.17 560.20 60As 72.23 72.36 3.28 267.15 60Br 101.41 97.23 8.47 359.44 60Sr 25.76 14.15 3.54 65.78 60Pb 219.16 191.79 10.15 774.44 60

Table 3.4.3 – Las Condes fine mode average concentration and other statistics.See legend of Figure 3.4.1.Las Condes

Fine Average Std. Dev. Min. Max. N

FPM 40.29 15.22 20.64 105.92 59CPM 40.43 22.20 12.12 114.10 59PM10 81.64 28.68 33.70 170.21 59BC 5.46 1.59 2.18 10.14 59MgAl 619.53 290.17 128.35 1679.73 59Si 466.21 288.47 36.63 1140.88 59 P 31.00 19.36 5.77 94.50 30 S 1830.45 1177.36 425.99 6258.61 59Cl 40.16 23.45 9.97 167.71 59 K 250.63 127.51 79.62 947.15 59Ca 224.73 114.87 55.28 539.75 59Sc 4.10 2.10 1.30 9.28 19Ti 43.53 18.95 10.22 114.60 59V 4.66 2.29 1.72 12.30 59Cr 9.79 4.38 5.63 18.26 7Mn 14.27 6.46 2.21 41.14 59Fe 384.31 173.07 101.54 1049.89 59Ni 1.72 0.68 0.63 4.43 59Cu 24.53 10.59 7.67 76.00 59Zn 64.29 27.76 18.14 185.34 59As 57.04 57.82 11.67 259.46 59Br 28.74 15.09 6.10 114.40 59Sr 2.20 . 2.20 2.20 1Pb 81.49 34.70 37.73 247.85 59


Table 3.4.4 – Las Condes coarse mode average concentration and otherstatistics. See legend of Figure 3.4.1.Las Condes

Coarse Average Std. Dev. Min. Max. N

FPM 40.29 15.22 20.64 105.92 59CPM 40.41 21.99 12.12 114.10 59PM10 81.62 28.30 33.70 170.21 59MgAl 1557.34 596.94 600.74 3055.53 59Si 3622.97 1532.93 969.85 6993.82 59 P 37.87 17.49 12.42 85.84 49 S 722.31 543.70 200.10 2657.16 59Cl 88.56 33.77 32.73 156.53 35 K 391.11 183.68 69.54 869.85 59Ca 1617.16 803.30 403.34 3615.53 59Sc 4.61 0.77 3.56 5.55 6Ti 187.54 78.67 61.24 374.52 59V 9.02 4.35 2.74 25.41 59Cr 15.89 11.06 6.66 37.37 16Mn 43.22 22.19 10.95 98.92 59Fe 1669.25 781.51 475.49 3585.09 59Ni 2.14 1.80 0.24 8.34 45Cu 37.07 20.65 7.71 87.67 59Zn 78.93 52.17 23.31 278.69 59As 33.12 35.35 5.64 175.00 45Br 18.62 12.79 5.88 56.38 41Sr 7.79 4.10 2.09 21.38 59Pb 46.73 34.41 7.75 189.28 59

Table 3.4.5 – Pudahuel fine mode average concentration and other statistics. Seelegend of Figure 3.4.1.

PudahuelFine Average Std. Dev. Min. Max. N

FPM 32.59 14.60 12.00 80.00 60CPM 83.20 53.46 23.44 219.31 60PM10 115.79 57.74 44.72 277.26 60BC 5.79 3.30 1.75 15.59 60MgAl 468.75 245.81 82.67 1122.52 60Si 691.33 386.86 66.14 1987.48 60 P 15.29 8.10 1.79 37.17 33 S 1552.88 1015.72 234.47 4574.46 60Cl 74.99 51.59 20.37 244.56 60 K 260.62 108.07 118.00 625.00 60Ca 253.73 130.44 66.01 722.63 60Sc 4.02 2.44 0.60 7.25 13Ti 41.65 16.03 13.20 97.94 60V 4.16 2.25 0.83 9.80 45Cr 7.75 6.64 2.52 20.77 6Mn 11.66 5.54 1.48 28.09 60Fe 331.12 135.03 86.77 721.52 60Ni 1.33 0.45 0.63 2.40 38Cu 19.50 12.75 3.32 61.45 60Zn 58.48 39.19 13.86 237.86 60As 44.50 37.03 9.09 172.22 60Br 43.80 34.28 10.77 148.48 60SrPb 99.93 64.61 29.53 289.01 60


Table 3.4.6 – Pudahuel coarse mode average concentration and other statistics.See legend of Figure 3.4.1.

PudahuelCoarse Average Std. Dev. Min. Max. N

FPM 32.59 14.60 12.00 80.00 60CPM 83.20 53.46 23.44 219.31 60PM10 115.79 57.74 44.72 277.26 60MgAl 3016.90 1650.41 1074.16 6983.36 60Si 7815.18 4391.37 2498.39 18197.31 60 P 94.71 60.40 24.94 275.50 60 S 1366.24 942.44 266.80 3599.91 60Cl 413.53 317.45 41.12 1370.17 60 K 882.37 542.47 254.06 2237.06 60Ca 2619.17 1540.58 775.84 6838.26 60Sc 8.56 5.51 4.93 14.91 3Ti 332.13 189.97 111.97 815.68 60V 11.85 7.58 3.67 34.23 60Cr 15.57 8.01 6.18 34.56 16Mn 78.23 47.69 22.22 200.66 60Fe 2772.60 1632.73 833.36 7005.31 60Ni 2.23 1.59 0.36 6.67 33Cu 45.45 33.08 8.55 133.50 60Zn 112.79 74.11 20.68 358.64 60As 55.60 64.67 2.48 308.35 60Br 58.17 72.54 1.50 331.24 60Sr 20.73 13.10 5.89 72.42 60Pb 125.20 136.75 16.17 631.92 60

Table 3.4.7 – Peldehue fine mode average concentration and other statistics. Seelegend of Figure 3.4.1.

PeldehueFine Average Std. Dev. Min. Max. N

FPM 37.53 19.37 11.10 76.70 30CPM 40.43 21.93 14.13 91.74 30PM10 77.96 38.14 25.79 164.35 30BC 3.39 1.74 1.02 7.15 30MgAl 469.89 322.84 91.07 1764.57 30Si 832.35 572.67 50.72 2975.43 30 P 20.85 21.37 3.75 70.36 9 S 1807.55 1066.81 372.24 4419.54 30Cl 41.13 26.32 8.25 93.57 30 K 262.49 137.90 83.60 572.46 30Ca 259.40 178.24 90.64 1010.00 30Sc 4.39 . 4.39 4.39 1Ti 49.82 28.54 11.68 150.00 30V 5.05 3.12 1.25 14.84 30Cr 7.02 4.70 1.96 14.86 10Mn 17.54 10.59 3.73 49.05 30Fe 451.38 265.33 102.55 1300.00 30Ni 2.19 2.03 0.30 8.27 16Cu 22.84 12.86 3.41 58.87 30Zn 97.03 83.86 17.14 440.00 30As 59.02 52.53 5.90 248.50 30Br 16.05 8.97 3.57 36.26 30Sr 3.43 2.45 0.75 11.09 24Pb 56.27 28.66 15.88 128.00 30


Table 3.4.8 – Peldehue coarse mode average concentration and other statistics.See legend of Figure 3.4.1.

PeldehueCoarse Average Std. Dev. Min. Max. N


Table 3.4.9 – Talagante fine mode average concentration and other statistics. Seelegend of Figure 3.4.1.

TalaganteFine Average Std. Dev. Min. Max. N

FPM 31.00 11.73 17.92 59.63 29CPM 34.38 13.67 15.86 87.48 29PM10 65.38 18.59 43.07 123.68 29BC 2.68 1.10 1.32 6.30 29Mg 120.89 95.66 46.10 469.32 20Al 503.11 220.97 205.32 1021.09 29Si 623.37 318.84 34.00 1326.65 29 P 12.14 7.47 5.93 22.92 4 S 1824.61 1193.69 469.70 5320.35 29Cl 48.45 43.02 6.00 165.51 29 K 297.94 116.20 86.06 640.15 29Ca 305.89 223.24 20.00 1020.92 29Sc 3.91 . 3.91 3.91 1Ti 33.48 14.91 3.78 62.05 29V 4.00 1.69 1.53 7.87 29Cr 4.77 0.94 3.45 5.69 4Mn 12.77 8.29 1.00 33.14 29Fe 261.51 115.97 51.00 501.05 29Ni 1.51 1.06 0.41 3.82 12Cu 17.64 13.31 0.38 53.57 29Zn 36.48 23.18 9.42 87.46 29As 71.13 94.98 1.71 482.69 29Br 13.02 6.02 5.00 29.56 29Sr 2.06 0.73 0.93 4.19 29Pb 37.92 18.76 16.49 83.30 29


Table 3.4.10 – Talagante coarse mode average concentration and other statistics.See legend of Figure 3.4.1.

TalaganteCoarse Average Std. Dev. Min. Max. N


Figure 3.4.1 shows the average elemental concentration in the fine mode aerosol

from the 5 sampling sites. Several important issues can be noticed in Figure 3.4.1. First the

average fine mode sulfur concentrations are very similar for the five sites, including the

two more remote (Talagante and Peldehue). Also K and Ca exhibits very similar

concentrations for the five sites. The worthwhile exceptions are: BC, V, Ni, Br and Pb.

O’Higgins clearly shows much higher concentrations for black carbon, a tracer of diesel

and vehicles emissions, as well as V and Ni, indicators of residual oil combustion, and Pb

and Br, indicators of vehicular emissions. Some elements associated with local

ressuspension of soil dust, such as Al, Mn and Cu also shows higher concentration in the

O’Higgins site. Talagante has the highest concentrations for As, indicating regional

transport of this element. Talagante in general has the smallest concentrations for Pb, Br

and BC, indicating small vehicular traffic influences.

Figure 3.4.2 shows the average elemental concentration in the coarse mode aerosol

from the 5 sampling sites. The variability between the sites in the coarse mode is much

higher than in the fine fraction. In general, O’Higgins and Pudahuel show the highest

elemental concentrations. Even in the coarse mode, V and Ni are much higher in

O’Higgins, indicating the higher impact of residual oil combustion in this site. Also Pb, Br,

is elevated in the coarse mode at O’Higgins, and has minimum values in Talagante.


1E0

1E1

1E2

1E3

1E4

Con

cent

ratio

ns (n

g/m

³)

FPMCPM

PM10

BCTEOM

Mg

AlSi

P

SCl

K

CaSc

Ti

VCr

Mn

FeNi

Cu

ZnAs

Br

SrPb


Santiago de Chile - Fine Mode Aerosol1998 Average Elemental Concentration

Figure 3.4.1 – Average elemental concentration in the fine mode aerosols fromthe 5 sampling sites for Santiago de Chile wintertime 1998 sampling campaign.

1E0

1E1

1E2

1E3

1E4

1E5

Con

cent

ratio

ns (n

g/m

³)

FPMCPM

PM10

BCTEOM

Mg

AlSi

P

SCl

K

CaSc

Ti

VCr

Mn

FeNi

Cu

ZnAs

Br

SrPb


Santiago de Chile- Coarse Mode Aerosol1998 Average Elemental Concentration

Figure 3.4.2 – Average elemental concentration in the coarse mode aerosols fromthe 5 sampling sites for Santiago de Chile wintertime 1998 sampling campaign.

Figure 3.4.3 shows a comparison of trace element concentrations in the fine mode

for downtown Santiago, presenting concentrations from Gotuzo measured in 1996 and

O’Higgins measured in 1998. It is remarkable the similarities between the two

measurements, but a very important change occurred in the V and Ni concentrations. They

are reduced in 1998 by 60-80 % compared to measurements in 1996. This clearly indicates

the reduction in the combustion of oil in Santiago between 1996 and 1988. Also there is a

significant reduction in Br and Pb, indicating the change in the fleet, with more cars

equipped with air pollution control equipment, burning unleaded gasoline in 1998. A

reduction in black carbon is observed maybe as a result of air pollution control in diesel


buses. The concentration of fine mode particles is also significantly reduced. The

concentration of some elements are higher in 1998, mostly soil dust related elements, such

as Al, Si, K, Ca, Ti, and Fe, possibly indicating an increase in ressuspended soil dust.

Arsenic and sulfur are also significantly reduced in 1998.

1E0

1E1

1E2

1E3

1E4

Con

cent

ratio

ns (n

g/m

³)

FPMCPM

PM10

BCMg

Al

Si P

S

Cl K

Ca

ScTi

V

CrMn

Fe

NiCu

Zn

AsBr

Sr

Pb

Gotuzo 96 O'Higgins 98

Santiago de Chile Downtown Fine ModeComparison Elemental Concentrations

Figure 3.4.3 – Comparison of average elemental concentrations between finemode aerosol samples from Gotuzo in 1996 and O’Higgins 1998.

1E0

1E1

1E2

1E3

1E4

Con

cent

ratio

ns (n

g/m

³)

FPMCPM

PM10BC

MgAl

Si P

SCl

KCa

ScTi

VCr

MnFe

NiCu

ZnAs

BrSr

Pb

Las Condes 96 Las Condes 98

Santiago de Chile Las Condes Fine ModeAverage Elemental Concentrations (*)

(*) The two sites at Las Condes are not exactly at the same location in 1996 and 1998. The 1998 site is more heavilly impacted by vehicles and traffic.

Figure 3.4.4 – Comparison of average elemental concentrations between finemode aerosol samples from Las Condes in 1996 and 1998. The stations are not inthe same site, but are in a few kilometers from each other. The site in 1998 ismore heavily impacted by transport and ressuspended road dust.

The Figure 3.4.4 shows a comparison of average elemental concentrations between

fine mode aerosol samples from Las Condes in 1996 and 1998. It is important to call the

attention that the two sites are located in different parts of Las Condes, with the site in


1998 much more impacted by vehicular and traffic emissions. Even with this notice, the

reduction in V and Ni is very significant. There is an increase in the concentration of soil

dust related elements for samples collected in 1998, because of the new location of the site.

The PM10 values, as well as FPM and CPM are very similar between 1996 and 1998.

For comparison, table 3.4.11 shows the average elemental concentrations measured

in the fine mode fraction of aerosol from wintertime 1994 in São Paulo. Figure 3.4.5

shows a plot comparing the fine mode average concentration in Santiago at the O‘Higgins

station and São Paulo. FPM and BC values are similar in both sites, with slightly higher

concentrations in Santiago. Soil dust related elements are much more pronounced in

Santiago than in São Paulo, possibly an effect of the much dryer environment in Santiago

de Chile. Pb and Br are much higher in Santiago because of the use of leaded gasoline in

Santiago that is being phased out. In São Paulo, alcohol is added to the gasoline,

eliminating Pb from the fuel additives. Sulfur concentrations are also higher in Santiago.

Vanadium concentration are very similar, but nickel concentrations are higher in São

Paulo, indicating that residual oil combustion impact can be similar, and the increase in

nickel concentration can be attributed to non-ferrous metal smelters and small

metallurgical activities in São Paulo. The higher zinc concentrations in São Paulo

emphasize this point. Copper is much higher in Chile, because the country has the soil very

much enriched in this metal.

Table 3.4.11 – Average elemental concentration for fine mode São Paulo aerosolduring wintertime 1994. Elemental concentrations in ng/m3.

São PauloFine Mode Average Std. Dev. Min. Max. N

Al 115 69.5 4.48 253 67Si 175 50.1 104 236 16S 1527 1039 94.9 5294 82Cl 35.9 27.0 3.26 132 74K 530 268 36.3 1357 82

Ca 91.5 39.4 18.2 217 82Ti 15.1 8.34 0.93 36.8 82V 7.25 4.21 0.73 19.2 82Cr 5.43 3.91 0.25 18.1 68

Mn 21.9 14.7 0.34 68.8 82Fe 346 159 46.9 887 82Ni 6.28 4.04 0.33 16.7 82Cu 15.3 9.96 2.12 52.6 82Zn 127 104 5.24 530 82Br 7.77 4.24 1.25 17.4 82Rb 2.34 1.09 0.76 5.33 34Sr 1.43 0.47 1.06 2.12 6Zr 4.84 2.86 1.98 9.37 8Pb 44.4 35.6 3.16 178 82

FPM (*) 30.9 14.9 3.64 79.8 82BC (*) 7.97 3.49 1.62 19.3 82

(*) FPM is the aerosol fine mode mass concentration in µg/m3. BC is the Black Carbonconcentration in µg/m3. N is the number of samples in which the variable appears abovethe analytical detection limit.


1E0

1E1

1E2

1E3

1E4

Con

cent

ratio

n (n

g/m

³)

FPM BC Al Si S Cl K Ca Ti V Cr Mn Fe Ni Cu Zn Br Sr Pb

O'Higgins 98 São Paulo 94

São Paulo and Santiago Fine ModeAverage Elemental Concentration

Figure 3.4.5 – Comparison of average elemental concentrations between finemode aerosol samples from O’Higgins 1998 in Santiago de Chile and wintertimeSão Paulo aerosol measured in 1994 using the same sampler and techniques.

333...555 ––– AAAeeerrrooosssooolll sssooouuurrrccceee aaappppppooorrrtttiiiooonnnmmmeeennntttWith the large number of aerosol samples collected in each of the five sites and in

each aerosol fraction, fine or coarse mode aerosol, it is possible to perform principal factor

analysis and extract the major sources of trace element variability for each site and each

aerosol fraction. The sections 3.6 to 3.15 discuss in detail the factor analysis results for

each site, as well as the absolute principal factor analysis results that provides absolute

elemental source profiles and quantitative aerosol source apportionment.

333...666 ––– AAAeeerrrooosssooolll sssooouuurrrccceee aaappppppooorrrtttiiiooonnnmmmeeennnttt OOO’’’HHHiiiggggggiiinnnsss fffiiinnneeemmmooodddeee

Table 3.6.1 presents the factor-loading matrix for the fine mode O’Higgins aerosol.

The factor loadings express the relationship between the four factors and each element,

indicating the nature of each source of variability. Four factors were obtained for the fine

mode aerosol from O’Higgins. The first factor has associations with Ca, Si, Ti, Fe, Al and

Sr, indicating that it is associated with soil dust. The second factor is associated with Br,

Pb, BC, K and Sr, as well as with the fine mode mass concentration (FPM) indicating it

represents vehicular emissions. The third factor is loaded with V and Ni, together with Zn,

Mn, and Cl, indicating it represents residual oil combustion mixed with industrial

emissions. The last factor is loaded with As and S, as well as the fine mode mass

concentration, representing the copper smelting industry in Chile. This component is


associated with copper, as observed in the cluster analysis procedure.

Table 3.6.1 – Factor Loading matrix for the fine mode O’Higgins aerosol.Factor 1 Factor 2 Factor 3 Factor 4

O'Higgins Fine Soil Dust Vehicles Oil Combustion +Industry S + As

CA .936 .112 .183 .115SI .932 -.160 - -TI .906 .128 .207 .247FE .809 .193 .473 .182AL .698 .330 .175 .395BR - .953 - .140PB - .908 .218 .244BC - .854 .343 .290K .304 .672 .202 .417

SR .607 .623 - -CU .223 .456 .397 .351NI .106 .127 .908 .230ZN - - .867 .354MN .328 - .852 -V - .362 .795 .194

CL .112 .497 .503 -S .123 .158 .360 .877

AS .308 .397 .148 .664FPM .280 .487 .436 .642

The Figure 3.6.1 shows the dendogram for the cluster analysis of the fine mode

O’Higgins aerosol. The dendogram express the distances between the variables taking the

samples as a multivariate space and measuring the distances between the 60 fine mode

aerosol samples. The result is expressed as a distance chart, the dendogram. The horizontal

axis expresses the similarities between the variables. It can be observed that Pb, Br and

BC are very similar in distances, characterizing the vehicular emissions. This first cluster

group represents factor 2 in the factor analysis expressed in Table 3.6.1. The next group of

elements has similarities for S, As, Cu, FPM, and K, representing copper smelter

emissions, the factor 4 in Table 3.6.1. The third group is associated with Ni, V, Zn, Mn and

Cl representing factor 3 in table 3.6.1. The last group of elements consists of Ti, Fe, Ca, Si,

Al and Sr. These elements are ressuspended soil dust, represented in the factor 1 in Table

3.6.1. The results from the cluster and factor analysis in this case agrees very well,

showing the stability of the solutions.


C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ BC 2 -+ PB 19 -+---------------+ BR 17 -+ I FPM 1 ---+-+ +-----------+ S 5 ---+ +-+ I I K 7 -----+ +-+ I I AS 16 -------+ +-------+ I CU 14 ---------+ +-------------------+ NI 13 -+-+ I I ZN 15 -+ +-+ I I V 10 ---+ +-------+ I I MN 11 -----+ +---------------+ I CL 6 -------------+ I TI 9 -+ I FE 12 -+---+ I CA 8 -+ +-+ I SI 4 -----+ +-----+ I AL 3 -------+ +-----------------------------------+ SR 18 -------------+

Figure 3.6.1 – Dendogram for the cluster analysis of the fine mode O’Higginsaerosol.

The table 3.6.2 shows the Absolute Principal Factor Analysis for the fine mode

O’Higgins aerosol. This table is somewhat similar to the factor loading matrix showed in

Table 3.6.1, but it is expressed in absolute amounts, ng/m³. The four columns show the

amount in ng/m³ apportioned to each element to each factor. The column “Sum Model”

expresses the sum of the concentrations apportioned to each factor for each element. The

“Measured” column expresses the observed concentration and the last column express the

ratio between the factor model and the measured concentrations. Most of the elements have

ratios near unity, expressing the adequacy of the source apportionment. For example, the

apportionment of FPM shows that 12.25 µg/m³ is associated with the soil dust component,

14.02 µg/m³ is originated from the vehicles emissions, 9.09 µg/m³ is associated with the oil

combustion and industry, and 3.78 µg/m³ is associated with the S+As+Cu factor. The total

FPM apportioned by the factor model was within 2 % of the measured value.

The Figure 3.6.2 shows the aerosol mass source apportionment for the fine mode

O’Higgins aerosol. Vehicle emissions account for the largest fraction of FPM, accounting

for 35.8 %. Soil dust is the second largest aerosol component, accounting for 31.3 % of

FPM. Oil combustion and industry accounts for 23.22 %, and the factor associated with

copper emissions, loaded with As and S accounts for 9.67% of the fine aerosol mass at

O’Higgins. The figure 3.6.3 shows the source apportionment for the black carbon at

O’Higgins fine mode aerosol. Vehicles are by far the largest source of black carbon

accounting in O’Higgins for 74.18 % of aerosol mass. Oil combustion and industry

accounts for 20.60 % and the copper smelter accounts for 5.22 % of the black carbon.


Concentrations apportioned (ng/m³) O'Higgins Fine Mode Factor AnalysisVariables Factor 1 Factor 2 Factor 3 Factor 4 Sum Model Measured Ratio

Soil Dust VehiclesOil

Combustion+Industry

S+As

FPM 12.25 14.02 9.09 3.78 39.15 39.74 1.02BC 6.49 1.80 0.46 8.75 8.46 0.97Mg 51.31 78.07 1.98 131.35 120.60 0.92Al 487.90 160.02 66.93 30.98 745.84 776.00 1.04Si 826.59 128.96 41.25 996.80 657.21 0.66 P 8.38 6.11 14.50 15.74 1.09 S 506.54 370.20 550.78 360.15 1787.67 1841.16 1.03Cl 19.24 45.55 33.00 97.79 100.16 1.02 K 99.88 152.66 31.92 19.55 304.00 307.24 1.01Ca 252.47 7.29 18.54 4.06 282.35 280.24 0.99Ti 43.56 4.23 4.75 1.55 54.10 55.14 1.02V 0.89 2.42 3.66 0.25 7.22 7.41 1.03Cr 2.61 2.80 5.41 7.51 1.39Mn 8.25 1.15 11.62 0.25 21.27 21.33 1.00Fe 313.82 42.58 87.27 9.58 453.26 456.51 1.01Ni 0.47 0.34 1.60 0.11 2.53 2.58 1.02Cu 10.78 13.46 8.43 2.06 34.72 35.48 1.02Zn 16.82 10.31 69.51 7.94 104.58 107.41 1.03As 19.85 17.94 4.51 6.50 48.80 49.01 1.00Br 79.17 0.87 2.33 82.37 74.97 0.91Sr 2.98 1.81 4.78 5.05 1.06Pb 156.09 24.06 8.65 188.80 176.75 0.94

Table 3.6.2 – Absolute Principal Factor Analysis for the fine mode O’Higginsaerosol.

Soil Dust (31.30%)

Oil Combustion +Industry (23.22%)

S+As (9.67%)

Vehicles (35.81%)

Santiago Aerosol Source ApportionmentFine Mode Mass O'Higgins Winter 1998

Figure 3.6.2 – Aerosol mass source apportionment for the fine mode O’Higginsaerosol.


Oil Combustion +Industry (20.60%)

S+As (5.22%)

Vehicles (74.18%)

Santiago Aerosol Source ApportionmentBlack Carbon O'Higgins Winter 1998

Figure 3.6.3 – Black carbon source apportionment for the fine mode O’Higginsaerosol.

333...777 ––– AAAeeerrrooosssooolll sssooouuurrrccceee aaappppppooorrrtttiiiooonnnmmmeeennnttt OOO’’’HHHiiiggggggiiinnnsss cccoooaaarrrssseeemmmooodddeee

The coarse mode aerosol generally is loaded with resuspended soil dust in urban

areas, and this is also the case for Santiago. Table 3.7.1 shows the factor-loading matrix

for coarse mode aerosol in O’Higgins. The first factor account for a very large fraction of

data variability is loaded with soil dust related elements and also V, Zn, Cu, As and Cl.

This joint variability between different aerosol sources can be caused by joint variability of

trace elements caused by the meteorology. The second factor is loaded with Br, Pb, and

therefore is associated with vehicle emissions, but the presence of V, Cu and As indicates

some mixing with other sources such as oil combustion and copper smelters. The third

factor is loaded with black carbon sulfur and FPM, indicating the impact of direct diesel

emissions. The last factor has mostly chlorine, and it could represent intrusions of marine

air masses in Santiago downtown, or other unidentified aerosol source.

The Figure 3.7.1 shows the dendogram for the cluster analysis of the coarse mode

O’Higgins aerosol. The first group of elements is associated with soil dust. Chlorine indeed

is separated from most of the other elements, and constitutes the second group. The third

group is As, Cu, S, Zn, and V, consisting of copper smelters with some contribution of oil

combustion. The next group is Br and Pb, very closed together, and mostly separated from

other groups. The black carbon and fine mass is an independent group from the other

coarse mode elements.


Table 3.7.1 – Factor Loading matrix for the coarse mode O’Higgins aerosol.Factor 1 Factor 2 Factor 3 Factor 4

O'Higgins Coarse Soil Dust+Industry Vehicles BC+ Organics Cl

SI .966 .182 .153 -AL .955 .203 .180 -TI .941 .240 .204 -K .931 .329 - -P .921 .281 - -

MN .915 .292 .211 -FE .911 .347 .206 -CA .910 .305 .248 -SR .882 .269 .208 -MG .881 .227 .200 .187

CPM .864 .429 .154 -V .730 .496 .282 -

ZN .682 .377 .343 -.112S .591 .439 .491 -.379

BR .242 .941 - -PB .360 .916 - -CU .507 .662 .317 .157AS .498 .579 - -.568BC .142 .258 .914 -

FPM .257 -.130 .899 -.146CL .525 .366 - .684

C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ AL 6 -+ SI 7 -+ K 11 -+ CA 12 -+ FE 16 -+ TI 13 -+-+ MN 15 -+ +-+ CPM 2 -+ I +---------------+ SR 21 ---+ I I MG 5 ---+-+ +-------------------+ P 8 ---+ I I CL 10 ---------------------+ I V 14 -------+---+ +-------+ CU 17 -------+ +-------+ I I S 9 -----+---+ I I I I ZN 18 -----+ +-+ +---------------------+ I AS 19 ---------+ I I BR 20 -+-----------+ I I PB 22 -+ +-----+ I TEOM 4 -------------+ I FPM 1 -------+-----------------------------------------+ BC 3 -------+

Figure 3.7.1 – Dendogram for the cluster analysis of the coarse mode O’Higginsaerosol.

The table 3.7.2 shows the Absolute Principal Factor Analysis for the coarse mode

O’Higgins aerosol. It is interesting to notice that Pb and Br that are mostly associated with

factor 2, has an strong presence in factor 1 also. This happens because when we have


vehicular emissions in the coarse mode, it is certainly associated with ressuspended soil

dust.

Table 3.7.2 – Absolute Principal Factor Analysis for the coarse mode O’Higginsaerosol.

Concentrations apportioned (ng/m³) - O'Higgins Coarse Mode Factor AnalysisVariables Factor 1 Factor 2 Factor 3 Factor 4 Sum Coarse Measured Ratio

Soil Dust+Industry Vehicles BC +

Organics Cl

CPM 72.25 7.93 11.83 0.42 92.42 92.61 1.00MgAl 2374.97 112.50 442.18 7.39 2937.03 3010.43 1.02Si 6021.77 251.44 859.43 17.44 7150.07 7235.93 1.01 P 73.88 4.98 1.49 0.84 81.20 82.69 1.02 S 978.95 173.05 722.22 15.54 1889.76 1700.23 0.90Cl 406.42 64.79 71.42 126.81 669.44 529.10 0.79 K 822.18 64.21 67.89 2.02 956.30 975.10 1.02Ca 2358.42 176.58 551.09 17.40 3103.49 3103.84 1.00Ti 318.76 18.09 62.07 3.18 402.10 402.49 1.00V 12.25 1.89 4.06 0.20 18.40 18.56 1.01Cr 7.99 12.17 0.49 20.65 21.03 1.02Mn 74.20 5.30 14.18 0.64 94.33 95.21 1.01Fe 2630.02 222.64 520.64 6.50 3379.80 3430.05 1.01Ni 1.41 0.27 1.64 0.05 3.36 3.92 1.17Cu 46.64 14.26 25.37 3.39 89.67 90.03 1.00Zn 137.97 18.16 56.19 0.67 212.99 202.72 0.95As 61.53 15.36 8.69 85.58 72.23 0.84Br 48.96 33.83 10.83 2.33 95.95 101.41 1.06Sr 20.16 1.38 3.87 0.18 25.58 25.76 1.01Pb 122.64 64.52 23.25 1.80 212.21 219.16 1.03

Vehicles (8.58%)

BC+Organics (12.79%)Cl (0.45%)

Soil Dust +Industry (78.18%)

Santiago Aerosol Source ApportionmentCoarse Mode Mass O'Higgins Winter 1998

Figure 3.7.2 – Source apportionment for the coarse mode O’Higgins aerosol.Figure 3.7.2 shows the source apportionment for the coarse mode O’Higgins

aerosol. Soil dust dominates with 78.18 % of the coarse mode mass concentrations. The


BC and organics component is responsible for 13% and vehicles accounts for 8.58 % of

coarse particle mass.

333...888 ––– AAAeeerrrooosssooolll sssooouuurrrccceee aaappppppooorrrtttiiiooonnnmmmeeennnttt LLLaaasss CCCooonnndddeeesss fffiiinnneeemmmooodddeee

Las Condes is a Santiago area that receives significant secondary pollutants emitted

in other parts of the city. Table 3.8.1 shows the factor Loading matrix for the fine mode

Las Condes aerosol. Four components were identified, that are similar than the ones

observed in O’Higgins for the fine mode aerosol. The four factors are well separated and

constitute the sources: Transport, soil dust, oil combustion and the copper smelters.

Table 3.8.1 – Factor Loading matrix for the fine mode Las Condes aerosol.Factor 1 Factor 2 Factor 3 Factor 4

Las Condes Fine Transport Soil Dust Oil Combustion As+S

K .875 .237 .159BC .862 .201 .262BR .843 .126 .265 .253CL .842 .322 .130PB .839 .275 .254 .245

FPM .591 .374 .533CU .553 .348 .500 .335CA .118 .890 .379SI .108 .887 .252FE .272 .791 .491 .140

CPM .780 -.103 .146TI .360 .759 .400 .280AL .247 .568 .499 .456NI .297 .224 .756 .197V .257 .334 .641 .289

MN .346 .586 .628ZN .526 .231 .576 .385S .363 .265 .860

AS .283 .118 .179 .848

The figure 3.8.1 shows the dendogram for the cluster analysis of the fine mode Las

Condes aerosol. The first group in the dendogram is the soil dust group. The second group

is the oil combustion group with V, Ni, coupled with other elements such as Cu, Zn and

Mn. The third group is the Pb and Br dominated vehicle emissions, with black carbon

combined in the group, as expected. The S and As shows a very close relationship, with

association with the fine mode mass concentration.


C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ TI 10 -+-+ FE 13 -+ +-----------+ SI 5 -+-+ +-------+ CA 9 -+ I I CPM 2 ---------------+ I CU 15 ---+-+ +-------------------------+ ZN 16 ---+ I I I MN 12 -----+-----+ I I AL 4 -----+ +-----------+ I V 11 -------+---+ I NI 14 -------+ I CL 7 ---+-+ I K 8 ---+ +---------------+ I BR 18 -+-+ I I I PB 19 -+ +-+ +---------------------------+ BC 3 ---+ I S 6 -+-------+ I AS 17 -+ +-----------+ FPM 1 ---------+

Figure 3.8.1 – Dendogram for the cluster analysis of the fine mode Las Condesaerosol.

The Table 3.8.2 shows the Absolute Principal Factor Analysis for the fine mode

Las Condes aerosol. Most of the elements were modeled within a few percent of the

measured concentrations. The Figure 3.8.2 shows the source apportionment for the fine

mode Las Condes aerosol. Transport and soil dust dominates completely the fine mode

aerosol in Las Condes, accounting for 80 % of the measured mass concentration. The

copper smelter group accounts for about 14% of the mass.

The Figure 3.8.3 shows the source apportionment for the fine mode black carbon

concentration at Las Condes, indicating that transport accounts for 70% of BC and the

factor associated with soil dust accounts for an extra 20.2% of the black carbon.


Table 3.8.2 – Absolute Principal Factor Analysis for the fine mode Las Condesaerosol.

Concentrations apportioned (ng/m³) - Las Condes Fine Mode Factor AnalysisFactor 1 Factor 2 Factor 3 Factor 4 Sum

Model Measured Ratio

Transport Soil Dust OilCombustion As + S

FPM 21.05 11.62 0.91 5.35 38.94 40.29 1.03BC 3.59 1.05 0.21 0.34 5.19 5.46 1.05Mg 0.00 0.00Al 138.10 273.56 117.82 81.22 610.70 619.53 1.01Si 21.82 396.56 52.23 470.60 466.21 0.99 P 9.73 3.22 4.44 7.58 24.97 31.00 1.24 S 829.96 111.18 249.52 612.90 1803.57 1830.45 1.01Cl 35.07 5.44 1.47 41.98 40.16 0.96 K 214.98 23.40 11.72 250.11 250.63 1.00Ca 19.45 165.98 34.32 3.17 222.92 224.73 1.01Ti 11.59 22.81 5.87 3.08 43.36 43.53 1.00V 1.41 1.44 1.24 0.43 4.52 4.66 1.03Cr 0.00 9.79Mn 4.45 6.35 3.33 14.14 14.27 1.01Fe 79.78 220.77 67.51 13.55 381.61 384.31 1.01Ni 0.64 0.42 0.47 0.11 1.64 1.72 1.05Cu 11.59 6.07 4.33 2.18 24.18 24.53 1.01Zn 30.87 11.81 13.42 6.76 62.87 64.29 1.02As 20.81 3.39 6.40 28.35 58.95 57.04 0.97Br 22.73 1.32 2.82 2.09 28.95 28.74 0.99Sr 0.00 2.20Pb 55.49 13.81 6.73 4.97 81.00 81.49 1.01

Oill Combustion (2.34%)

As+S (13.75%)

Transport (54.07%)

Soil Dust (29.85%)

Santiago Aerosol Source ApportionmentFine Mode Mass Las Condes Winter 1998

Figure 3.8.2 – Source apportionment for the fine mode Las Condes aerosol.


Soil Dust (20.24%)

Oill Combustion (4.01%)As+S (6.50%)

Transport (69.25%)

Santiago Aerosol Source ApportionmentBlack Carbon Las Condes Winter 1998

Figure 3.8.3 – Source apportionment for the fine mode black carbon concentrationat Las Condes.

333...999 ––– AAAeeerrrooosssooolll sssooouuurrrccceee aaappppppooorrrtttiiiooonnnmmmeeennntttLLLaaasss CCCooonnndddeeesss cccoooaaarrrssseee mmmooodddeee

The Table 3.9.1 shows the factor loading matrix for the coarse mode Las Condes

aerosol. As expected from the fine mode results for this site and from the heavy traffic,

ressuspended soil dust is responsible for most of the aerosol mass, and this factor cames

together with industrial emissions. The second factor is sulfates mixed with Zn and

transport. The third factor represents oil combustion.

Table 3.9.1 – Factor Loading matrix for the coarse mode Las Condes aerosol.Factor 1 Factor 2 Factor 3

Las Condes Coarse Soil Dust +Industry S+Zn+Transport Oil Combustion

SI .869 .334 .343AL .845 .329 .362K .827 .443 .269

FE .822 .410 .369TI .809 .430 .381CA .777 .430 .419MN .770 .492 .377

CPM .643 .623 .411S .366 .854 .180

ZN .439 .803 .340PB .258 .758 .536CU .638 .716 .145SR .508 .267 .763V .508 .432 .638

The Figure 3.9.1 shows the dendogram for the cluster analysis of the coarse mode

Las Condes aerosol. The very strong associations between the soil dust elements is clear in


this analysis. Vanadium and strontium are clustered similarly to the third factor. Cu, Pb

and Zn are clustered with black carbon, sulfur and the fine mass, representing the second

component.

C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ TI 10 -+ FE 13 -+ CA 9 -+ MN 12 -+ AL 5 -+-------+ SI 6 -+ +-+ K 8 -+ I I V 11 -----+---+ +-----+ SR 16 -----+ I I TEOM 4 -----------+ I CPM 2 -+-+ +-------------------------------+ ZN 15 -+ I I I CU 14 ---+-+ I I PB 17 ---+ +-----------+ I S 7 -----+ I FPM 1 -----+-------------------------------------------+ BC 3 -----+

Figure 3.9.1 – Dendogram for the cluster analysis of the coarse mode Las Condesaerosol.

Table 3.9.2 shows the Absolute Principal Factor Analysis for the coarse mode Las

Condes aerosol. The dominance in mass for the first component is very strong, dominating

the contribution of most of the trace elements. The Figure 3.9.2 shows the source

apportionment for the coarse mode Las Condes aerosol. About 66% of the coarse mass is

associated with soil dust and industry. Oil combustion contributes to 22% and the

remaining mass is associated with the component loaded with sulfur, zinc and transport.

Oil Combustion (21.93%)

Soil Dust +Industry (65.94%)

S+Zn (12.13%)

Santiago Aerosol Source ApportionmentCoarse Mode Mass Las Condes Winter 98

Figure 3.9.2 – Source apportionment for the coarse mode Las Condes aerosol.


Table 3.9.2 – Absolute Principal Factor Analysis for the coarse mode Las Condesaerosol.

Concentrations apportioned (ng/m³)Factor 1 Factor 2 Factor 3 Sum Measured Ratio

Soil Dust+Industry

S + Zn+Transport

OilCombustion

CPM 26.54 4.88 8.83 40.25 40.41 1.00MgAl 1164.36 76.55 261.03 1501.94 1557.34 0.96Si 2791.24 189.66 568.62 3549.52 3622.97 0.98 P 25.98 1.15 8.14 35.27 37.87 0.93 S 427.65 166.43 108.35 702.43 722.31 0.97Cl 61.87 0.51 10.62 73.00 88.56 0.82 K 305.56 29.53 50.59 385.68 391.11 0.99Ca 1168.07 122.13 324.85 1615.05 1617.16 1.00Ti 137.02 12.64 33.24 182.90 187.54 0.98V 5.01 0.70 3.03 8.74 9.02 0.97Cr 15.93 15.93 15.89 1.00Mn 31.53 3.86 7.88 43.27 43.22 1.00Fe 1253.80 114.95 286.67 1655.41 1669.25 0.99Ni 0.92 0.39 0.63 1.95 2.14 0.91Cu 27.51 5.36 3.35 36.22 37.07 0.98Zn 44.90 14.96 17.99 77.84 78.93 0.99As 24.13 8.64 32.76 33.12 0.99Br 7.16 2.31 6.76 16.23 18.62 0.87Sr 4.08 0.39 3.21 7.69 7.79 0.99Pb 17.77 9.30 18.87 45.95 46.73 0.98

333...111000 ––– AAAeeerrrooosssooolll sssooouuurrrccceee aaappppppooorrrtttiiiooonnnmmmeeennnttt PPPuuudddaaahhhuuueeelll fffiiinnneeemmmooodddeee

The Table 3.10.1 shows the factor-loading matrix for the fine mode Pudahuel

aerosol. The three same factor structures were observed, with soil dust, a transport and a

copper smelter component explaining most of the data variability. Fine mass is mostly

associated with the transport and copper smelter components.

The dendogram for the cluster analysis of the fine mode Pudahuel aerosols showed

in Figure 3.10.1. It is worthwhile to note the very close association between BC, Pb, Cl

and Br. Arsenic, copper, sulfur and zinc are also close together. Coarse particle mass is

associated with fine mode soil dust related elements.


Table 3.10.1 – Factor Loading matrix for the fine mode Pudahuel aerosol.Pudahuel Fine Factor 1 Factor 2 Factor 3

Soil Dust Transport As+S+Cu

SI .967 - -CA .952 .214 -FE .941 .155 .245TI .930 .138 .254AL .850 .379 -MN .767 - .459

CPM .613 .521 -.161BR .127 .960 -PB .113 .952 .153BC - .888 .297CL .282 .812 .217K .323 .763 .297

ZN .145 - .911S - .125 .907

CU - .405 .712FPM .184 .540 .691AS .445 .254 .567

C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ TI 10 -+ FE 12 -+-+ SI 5 -+ +-+ CA 9 -+ I +---+ AL 4 ---+ I +---------------------------------------+ MN 11 -----+ I I CPM 2 ---------+ I S 6 ---+---+ I ZN 14 ---+ I I CU 13 -------+-------------------+ I AS 15 -------+ I I FPM 1 ---+-----+ +---------------------+ K 8 ---+ I I BR 16 -+ +-----------------+ PB 17 -+-+ I BC 3 -+ +-----+ CL 7 ---+

Figure 3.10.1 – Dendogram for the cluster analysis of the fine mode Pudahuelaerosol.

The Table 3.10.2 shows the Absolute Factor Analysis results for the fine mode

Pudahuel aerosol. The copper smelter and transport dominates the fine mass, as can be

seen in figure 3.10.2. The soil dust component makes the majority of Si, Fe and other

elements.


Table 3.10.2 – Absolute Factor Analysis results for the fine mode Pudahuelaerosol.

Concentrations apportioned (ng/m³) Pudahuel Fine ModeFactor 1 Factor 2 Factor 3 Sum Measured Ratio

Soil Dust Transport As+S+Cu

FPM 6.28 10.23 15.13 31.64 32.59 0.97BC 0.51 3.62 1.49 5.63 5.79 0.97MgAl 373.26 110.05 4.13 487.44 468.75 1.04Si 677.39 4.75 4.13 686.27 691.33 0.99 P 10.24 3.93 0.62 14.79 15.29 0.97 S 54.56 164.54 1299.42 1518.52 1552.88 0.98Cl 18.47 46.71 10.97 76.15 74.99 1.02 K 83.38 110.02 57.10 250.51 260.62 0.96Ca 227.19 34.24 1.38 262.80 253.73 1.04Ti 29.72 3.60 7.04 40.36 41.65 0.97V 0.80 1.04 2.29 4.13 4.16 0.99Cr 4.92 4.92 7.75 0.63Mn 8.07 0.46 3.48 12.01 11.66 1.03Fe 242.76 29.09 51.62 323.46 331.12 0.98Ni 0.41 0.15 0.66 1.22 1.33 0.91Cu 6.55 13.11 19.66 19.50 1.01Zn 9.42 49.15 58.58 58.48 1.00As 18.43 6.30 22.44 47.18 44.50 1.06Br 5.38 38.17 0.28 43.83 43.80 1.00Sr 0.00Pb 12.12 73.33 13.14 98.60 99.93 0.99

Soil Dust (19.85%)

As+S+Cu (47.80%)

Transport (32.34%)

Santiago Aerosol Source ApportionmentFine Mode Mass Pudahuel Winter 1998

Figure 3.10.2 – Source apportionment for the fine mode Pudahuel aerosol.


Soil Dust (9.09%)

As+S+Cu (26.52%)

Transport (64.39%)

Santiago Aerosol Source ApportionmentBlack Carbon Pudahuel Winter 1998

Figure 3.10.3 – Source apportionment for the black carbon in fine mode Pudahuelaerosol.

333...111111 ––– AAAeeerrrooosssooolll sssooouuurrrccceee aaappppppooorrrtttiiiooonnnmmmeeennnttt PPPuuudddaaahhhuuueeelll cccoooaaarrrssseeemmmooodddeee

Almost the same factor structure as in the Pudahuel fine mode component was

observed in the coarse mode. Table 3.11.1 shows the factor-loading matrix for the coarse

mode Pudahuel aerosol. The transport component with Pb, Cl and Br is very clear. The

Figure 3.11.1 shows the dendogram for the cluster analysis of the coarse mode Pudahuel

aerosol. The very short distance between Br and Pb and between the soil dust elements is

clear. The black carbon and the fine particle mass does not have any association to the

coarse mode components in Pudahuel.

The Table 3.11.2 shows the Absolute Factor Analysis results for the coarse mode

Pudahuel aerosol. Soil dust dominates completely the aerosol mass, accounting for 88% of

the aerosol, as can be seen in Figure 3.11.2. Copper smelters and transport accounts for the

rest.


Table 3.11.1 – Factor Loading matrix for the coarse mode Pudahuel aerosol.Factor 1 Factor 2 Factor 3

Pudahuel Fine Soil Dust S + As + Cu Transport

SI .813 .443 .371AL .804 .464 .366TI .790 .474 .381FE .772 .480 .409K .772 .451 .438

CA .762 .481 .416MN .760 .495 .408P .752 .469 .352

CPM .725 .557 .391V .668 .425 .484

SR .664 .425 .444S .500 .828 .130

AS .359 .827 .334ZN .487 .770 .307CU .583 .672 .365PB .474 .622 .595CL .410 .187 .858BR .451 .562 .650

C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ AL 4 -+ SI 5 -+ TI 11 -+ FE 14 -+ MN 13 -+ K 9 -+-+ CA 10 -+ +-+ CPM 2 -+ I +-----+ P 6 ---+ I I V 12 -----+ +---+ BR 18 -+---+ I I PB 20 -+ +-+ I I SR 19 -----+ +---+ +---------------------------------+ CL 8 -------+ I I CU 15 -+---+ I I ZN 16 -+ +---------+ I S 7 ---+-+ I AS 17 ---+ I FPM 1 -------+-----------------------------------------+ BC 3 -------+

Figure 3.11.1 – Dendogram for the cluster analysis of the coarse mode Pudahuelaerosol.


Table 3.11.2 – Absolute Factor Analysis results for the coarse mode Pudahuelaerosol.

Concentrations apportioned (ng/m³) Pudahuel CoarseFactor 1 Factor 2 Factor 3 Sum Measured Ratio

Soil Dust S+As+Cu Transport

CPM 72.66 7.83 2.21 82.70 83.20 0.99MgAl 2680.47 205.95 64.65 2951.07 3016.90 0.98Si 7004.00 518.53 173.72 7696.25 7815.18 0.98 P 84.64 7.43 2.24 94.31 94.71 1.00 S 1079.28 209.32 13.41 1302.02 1366.24 0.95Cl 338.37 17.24 28.94 384.55 413.53 0.93 K 787.57 64.31 25.11 876.99 882.37 0.99Ca 2310.29 197.31 68.18 2575.77 2619.17 0.98Ti 295.08 23.99 7.70 326.78 332.13 0.98V 10.30 0.86 0.39 11.55 11.85 0.98Cr 11.71 0.69 0.00 12.41 15.57 0.80Mn 69.16 6.24 2.06 77.46 78.23 0.99Fe 2454.58 208.12 71.00 2733.70 2772.60 0.99Ni 1.83 0.33 0.02 2.17 2.23 0.97Cu 37.57 5.87 1.27 44.72 45.45 0.98Zn 88.38 15.45 2.46 106.29 112.79 0.94As 39.86 13.90 2.24 56.01 55.60 1.01Br 46.39 10.35 4.87 61.61 58.17 1.06Sr 18.02 1.49 0.62 20.14 20.73 0.97Pb 99.68 21.79 8.43 129.90 125.20 1.04

S+As+Cu (9.47%)Transport (2.67%)

Soil Dust (87.86%)

Santiago Aerosol Source ApportionmentCoarse Mode Mass Pudahuel Winter 1998

Figure 3.11.2 – Source apportionment for the coarse mode Pudahuel aerosol.

333...111222 ––– AAAeeerrrooosssooolll sssooouuurrrccceee aaappppppooorrrtttiiiooonnnmmmeeennnttt PPPeeellldddeeehhhuuueee fffiiinnneeemmmooodddeee

The Table 3.12.1 shows the factor-loading matrix for the fine mode Peldehue


aerosol. Four components were observed, the first three ones similar to components

observed in O’Higgins and Las Condes, and a fourth factor with Cl and Zn, whose nature

is unknown.

Table 3.12.1 – Factor Loading matrix for the fine mode Peldehue aerosol.Factor 1 Factor 2 Factor 3 Factor 4

Peldehue Fine Soil Dust Transport + OilCombustion As+S Cl+Zn

SI .960 .199 - -CA .952 .268 - -TI .910 .392 - -AL .904 .271 .178 .212FE .895 .415 - -MN .829 .483 - -ZN .742 .349 - .514CU .716 .489 .251 .308BC .365 .873 .108 .163BR .433 .796 .237 -V .294 .771 .120 .305

FPM .571 .762 .192 .149K .627 .742 - -.106

PB .567 .711 .201 .237AS - - .990 -S - .556 .739 .268

CL .117 .542 .480 .572


Peldehue aerosol. The soil dust is the first cluster. Copper smelters with As, Cu, S and Zn

is the second group. Vehicle emissions are the third group, with Pb, BC, Cl and Br. We

have not observed the fourth component observed in the factor analysis in the clusters.

C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ TI 10 -+ FE 12 -+-+ SI 5 -+ +-+ CA 9 -+ I +---+ AL 4 ---+ I +---------------------------------------+ MN 11 -----+ I I CPM 2 ---------+ I S 6 ---+---+ I ZN 14 ---+ I I CU 13 -------+-------------------+ I AS 15 -------+ I I FPM 1 ---+-----+ +---------------------+ K 8 ---+ I I BR 16 -+ +-----------------+ PB 17 -+-+ I BC 3 -+ +-----+ CL 7 ---+

Figure 3.12.1 – Dendogram for the cluster analysis of the fine mode Peldehueaerosol.


Figure 3.12.2 shows the aerosol source apportionment for the fine mode Peldehue

aerosol. The transport and oil combustion component dominates the mass, with a

significant contribution of the fine mode soil dust component. Copper smelter accounts for

9.7% of the fine mode mass. Figure 3.12.3 shows the aerosol source apportionment for the

black carbon in the fine mode Peldehue aerosol, with a similar distribution to the mass.

Soil Dust (31.41%)

As+S (9.74%)Cl+Zn (0.94%)

Transport+Oil Combustion (57.90%)

Santiago Aerosol Source ApportionmentFine Mode Mass Peldehue Winter 1998

Figure 3.12.2 – Aerosol source apportionment for the fine mode Peldehueaerosol.

Soil Dust (21.65%)

As+S (6.82%)Cl+Zn (1.02%)

Transport+Oil Combustion (70.51%)

Santiago Aerosol Source ApportionmentBlack Carbon Peldehue Winter 1998

Figure 3.12.3 – Aerosol source apportionment for the black carbon in the finemode Peldehue aerosol.

333...111333 ––– AAAeeerrrooosssooolll sssooouuurrrccceee aaappppppooorrrtttiiiooonnnmmmeeennntttPPPeeellldddeeehhhuuueee cccoooaaarrrssseee mmmooodddeee

The Table 3.13.1 shows the factor-loading matrix for the coarse mode Peldehue


aerosol. Four components were observed, with a separation of a second factor with Pb, S,

and Zn. The dendogram for the cluster analysis of the coarse mode Peldehue aerosol can be

observed in Figure 3.13.1. The first group is heavily on soil dust elements, with vanadium

and others elements. Arsenic and sulfur are very closely associated. Copper, zinc and

sulfur are also clearly clustered.

Table 3.13.1 – Factor Loading matrix for the coarse mode Peldehue aerosol.Factor 1 Factor 2 Factor 3 Factor 4

PeldehueCoarse Soil Dust Pb + S + Zn Oil

Combustion As + S

MN .871 .397 .251 -K .871 .403 .211 .145SI .860 .330 .375 -AL .858 .378 .312 .102CA .847 .396 .333 -FE .845 .405 .331 -TI .837 .381 .375 -P .792 - .586 -

CPM .792 .420 .377 .188SR .607 .387 .567 .172CU .598 .574 .172 .356PB .421 .780 .129 .307ZN .538 .773 .259 -S .369 .695 .138 .553NI .261 .112 .949 -V .491 .223 .823 -

AS - .217 - .969

C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ AL 4 -+ SI 5 -+ TI 11 -+ FE 14 -+ MN 13 -+ K 9 -+-+ CA 10 -+ +-+ CPM 2 -+ I +-----+ P 6 ---+ I I V 12 -----+ +---+ BR 18 -+---+ I I PB 20 -+ +-+ I I SR 19 -----+ +---+ +---------------------------------+ CL 8 -------+ I I CU 15 -+---+ I I ZN 16 -+ +---------+ I S 7 ---+-+ I AS 17 ---+ I FPM 1 -------+-----------------------------------------+ BC 3 -------+

Figure 3.13.1 – Dendogram for the cluster analysis of the coarse mode Peldehueaerosol.


Figure 3.13.2 shows the aerosol source apportionment for the coarse mode

Peldehue aerosol, with a heavy dominance of soil dust particles. The second factor with

Pb, S and Zn is responsible for about 20 % of the aerosol mass.

Oil Combustion (8.28%)

As+S (7.62%)

Soil Dust (64.16%)

Pb+S+Zn (19.94%)

Santiago Aerosol Source ApportionmentCoarse Mode Mass Peldehue Winter 1998

Figure 3.13.2 – Aerosol source apportionment for the coarse mode Peldehueaerosol.

333...111444 ––– AAAeeerrrooosssooolll sssooouuurrrccceee aaappppppooorrrtttiiiooonnnmmmeeennntttTTTaaalllaaagggaaannnttteee fffiiinnneee mmmooodddeee

Talagante has the lowest aerosol loading from the five sites for both fine and coarse

mode components. Table 3.14.1 shows the factor-loading matrix for the fine mode

Talagante aerosol. A soil dust and a transport component is clearly observed. A third

component with copper smelters and other elements such as V and Zn was observed.


Talagante aerosol. The very close distance of Cl, Br and Pb is clear. Also the As, Cu, S,

Zn, fine mass and V can be observed. In terms of source apportionment, the transpor

components makes the majority of the aerosol mass, while the copper smelter and soil dust

accounts each for 15-20%, as can be observed in figure 3.14.2. Black carbon has a similar

source apportionment, but more heavily loaded in the transport component, as expected.


Table 3.14.1 – Factor Loading matrix for the fine mode Talagante aerosol.Factor 1 Factor 2 Factor 3

Talagante Fine Soil Dust Transport Cu+As+S+V+Zn

SI .927 .215 .195FE .909 .147 .347CA .873 - .119MN .836 -.149 -SR .815 .171 -TI .812 .385 .321AL .598 .567 .521BR - .936 .161CL - .877 .302PB .176 .802 .430K .425 .791 .156

BC .100 .785 .250FPM .175 .721 .569

S .154 .398 .868AS .125 .147 .861CU .399 .229 .812V .159 .257 .659

ZN .214 .403 .635

C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ SI 5 -+ FE 13 -+---+ TI 10 -+ I SR 18 -----+---+ MN 12 -----+ +---------------------------------------+ CPM 2 ---+-----+ I CA 9 ---+ I AL 4 ---+---+ I K 8 ---+ I I CL 7 -+ +---------+ I BR 17 -+---+ I I I PB 19 -+ +-+ I I BC 3 -----+ +-------------------------------+ CU 14 ---+---+ I AS 16 ---+ I I FPM 1 -+-+ I I S 6 -+ +---+---------+ ZN 15 ---+ I V 11 -------+

Figure 3.14.1 – Dendogram for the cluster analysis of the fine mode Talaganteaerosol.


Soil Dust (19.61%)Cu+As+S+V+Zn (15.60%)

Transport (64.79%)

Santiago Aerosol Source ApportionmentFine Mode Mass Talagante Winter 1998

Figure 3.14.2 – Aerosol source apportionment for the fine mode Talaganteaerosol.

Soil Dust (16.11%)Cu+As+S+V+Zn (7.94%)

Transport (75.95%)

Santiago Aerosol Source ApportionmentBlack Carbon Talagante Winter 1998

Figure 3.14.3 – Aerosol source apportionment for the black carbon aerosol in thefine mode Talagante site.

333...111555 ––– AAAeeerrrooosssooolll sssooouuurrrccceee aaappppppooorrrtttiiiooonnnmmmeeennnttt TTTaaalllaaagggaaannnttteee cccoooaaarrrssseeemmmooodddeee

Table 3.15.1 shows the factor-loading matrix for the coarse mode Talagante

aerosol. In addition to the soil dust, copper smelters and oil combustion components, a S

and Zn component was also observed. In Figure 3.15.1, the dendogram for the cluster

analysis of the coarse mode Talagante aerosol can be observed. The close association of S

and Zn is clearly observed, confirming the factor analysis results. This component is close

to the Copper smelter factor.


Table 3.15.1 – Factor Loading matrix for the coarse mode Talagante aerosol.Factor 1 Factor 2 Factor 3 Factor 4

TalaganteCoarse Soil Dust As + Cu + Pb S + Zn Oil

Combustion

K .972 .117 .129 -MN .963 .153 - -FE .952 .203 .135 .149SI .948 .143 .201 .167

CPM .929 .123 .289 -TI .924 .240 .141 .212P .818 - .276 .189

CA .815 - .381 -AL .812 .350 .168 .218AS - .886 - .252PB - .846 .283 -CU .264 .817 .245 .285S .385 .280 .826 .129

ZN .254 .425 .817 .104V .328 .374 .177 .818

C A S E 0 5 10 15 20 25 Label Num +---------+---------+---------+---------+---------+ SI 3 -+ FE 9 -+ TI 15 -+-+ CPM 1 -+ I K 6 -+ +-+ MN 8 -+ I +-+ AL 2 ---+ I +-----------------------------------------+ P 4 -----+ I I CA 7 -+-----+ I SR 14 -+ I S 5 ---+-----------+ I ZN 11 ---+ I I CU 10 -+-----+ +---------------------------------+ AS 12 -+ +---+ I PB 13 -------+ +---+ V 16 -----------+

Figure 3.15.1 – Dendogram for the cluster analysis of the coarse mode Talaganteaerosol.


As+Cu+Pb (7.96%)

S+Zn (14.26%)Oil Combustion (0.71%)

Soil Dust (77.07%)

Santiago Aerosol Source ApportionmentCoarse Mode Mass Talagante Winter 1998

Figure 3.15.2 – Aerosol source apportionment for the coarse mode Talaganteaerosol.

The Figure 3.15.2 shows the aerosol source apportionment for the coarse mode

Talagante aerosol, with a very heavy dominance of soil dust aerosol. The copper smelter

component adds up to 20% of the aerosol mass, and the oil combustion has a negligible

contribution to the aerosol mass.

333...111666 ––– CCCooommmpppaaarrriiisssooonnn ooofff eeellleeemmmeeennntttaaalll sssooouuurrrccceeesss ppprrrooofffiiillleeesssThe obtained absolute elemental source profiles can be compared trough all the

sites in order to learn about the constancy of elemental composition for the sources

impacting the Santiago de Chile atmosphere. The Figure 3.16.1 shows a comparison of the

elemental composition for the soil dust source profile in the coarse mode of the three

sampling stations more impacted by ressuspended soil dust. It is remarkable the similarity

between the source profiles for most of the elements. The stability of the factor analysis

procedure is very strong on the analysis of elemental variability in Santiago de Chile. The

Figure 3.16.2 shows the soil dust elemental profile for the fine mode. In this case a large

variability was observed, because of mixing between the factors. In the fine mode direct

emissions of vehicular traffic is frequently mixed with ressuspended soil dust, because

both factors have similar time variability. Br and Pb were not onserved in the O’Higgins

fine mode soil dust component, possibly because the traffic is a so strng variability that that

factor tried to explain all variability in these two elements.


0.001

0.01

0.1

1

10

100

Perc

enta

ge o

f Coa

rse

Mod

e M

ass

(%)

AlSi

P S

Cl K

CaTi

VCr

MnFe

NiCu

ZnAs

BrSr

Pb

OHiggins Las Condes Pudahuel

Santiago de Chile Coarse Mode AerosolSoil Dust Source Profiles 1998

Figure 3.16.1 – Comparison of the elemental composition for the soil dust sourceprofile in the coarse mode of the three sampling stations.

0.001

0.01

0.1

1

10

100

Perc

enta

ge o

f Fin

e M

ass

(%)

AlSi

P S

Cl K

CaTi

VCr

MnFe

NiCu

ZnAs

BrSr

Pb


Santiago de Chile - Fine Mode AerosolSoil Dust Source Profiles 1998

Figure 3.16.2 – Comparison of the elemental composition for the soil dust sourceprofile in the fine mode of the three sampling stations.

Figure 3.16.3 shows a comparison of the elemental composition for the transport

source profile in the coarse mode of Santiago aerosol, while figure 3.16.4 shows the

transport source profile for the fine mode aerosol. For O’Higgins and Pudahuel sites, the

transport source profiles are similar. It is worthwhile to notice that this factor contain V

and Ni, probably as a result of mixing with oil combustion sources that have similar

variability because of joint meteorological controls. Although the absolute amount of Br

and Pb differs in the fine mode for the three stations, the ratio between Br and Pb is very

constant.


0.0001

0.001

0.01

0.1

1

10

100

Perc

enta

ge o

f Coa

rse

Mas

s (%

)

AlSi

P S

Cl K

CaTi

VCr

MnFe

NiCu

ZnAs

BrSr

Pb

OHiggins Coarse Pudahuel Coarse

Santiago de Chile Coarse Mode AerosolCoarse Transport Source Profiles 1998

Figure 3.16.3 – Comparison of the elemental composition for the transport sourceprofile in the coarse mode of Santiago aerosol.

0.001

0.01

0.1

1

10

Perc

enta

ge o

f Fin

e M

ass

(%)

AlSi

P S

Cl K

CaTi

VCr

MnFe

NiCu

ZnAs

BrSr

Pb


Santiago de Chile - Fine Mode AerosolFine Transport Source Profiles 1998

Figure 3.16.4 – Comparison of the elemental composition for the transport sourceprofile in the fine mode of the three sampling stations.

The Figure 3.16.5 shows a comparison of the elemental composition for the oil

combustion source profile in the fine mode aerosol from Santiago. Las Condes shows

higher absolute values because less fine mode mass was apportioned to this factor than in

O’Higgins. But, in general the ratios between the elements are quite similar. Figure 3.16.6

shows similar plot for the copper smelter component. It is remarkably that fine sulfur in

this component account for a high 10% of the mass and it is quite constant along the three

sites. Arsenic in this factor is about 0.1 to 0.6% in mass.


0.001

0.01

0.1

1

10

100

Perc

enta

ge o

f Fin

e M

ass

(%)

AlSi

P S

Cl K

CaTi

VCr

MnFe

NiCu

ZnAs

BrSr

Pb

OHiggins Fine Las Condes Fine

Santiago de Chile - Fine Mode AerosolOil Combustion Source Profiles 1998

Figure 3.16.5 – Comparison of the elemental composition for the oil combustionsource profile in the fine mode aerosol from Santiago.

0.001

0.01

0.1

1

10

100

Perc

enta

ge o

f Fin

e M

ass

(%)

AlSi

P S

Cl K

CaTi

VCr

MnFe

NiCu

ZnAs

BrSr

Pb

OHiggins Fine Las Condes Fine Pudahuel Fine

Santiago de Chile - Fine Mode AerosolArsenic+Sulfur Source Profiles 1998

Figure 3.16.6 – Comparison of the elemental composition for the Arsenic + Sulfursource profile in the fine mode aerosol from Santiago.

444 ––– AAAeeerrrooosssooolll sssiiizzzeee dddiiissstttrrriiibbbuuutttiiiooonnnsssThe importance to measure aerosol size distribution resides in the fact that there a

large diversity of particle concentrations and composition from 0.1µm to 20µm in size.

Figure 4.1 shows the size distribution measured at the O’Higgins site on August

16, 1998. Note the dominance of particles in the size range of 3µm in size, at the coarse

mode aerosol. These coarse mode particles are resuspended soil dust.


0 2 4 6 8

10 12 14 16 18 20 22 24 26 28 30

Aero

sol M

ass

Con

cent

ratio

n (µ

g/m

³)

0.093 0.175 0.33 0.56 1.0 1.8 3.2 18.0Aerodynamic Diameter (µm)

Aerosol Size Distribution Santiago 98MOUDI 2 Mass Distribution (16/08/98)

Figure 4.1 – Aerosol size distribution measured with the MOUDI cascade impactorin the O’Higgins sampling site. Sampling on August 16, 1998.

. At figures 4.2 and 4.3, it is possible to observe that the fine mode is larger that

the coarse mode, probably due to increase of direct vehicle emissions. We can also notice

the strong presence of ultra fine particles at 0.18µm size, which have high efficiency to be

trapped in the alveolar region in the lungs.

0 2 4 6 8

10 12 14 16 18 20 22 24 26

Aero

sol M

ass

Con

cent

ratio

n (µ

g/m

³)





0

2

4

6

8

10

12

14

Aero

sol M

ass

Con

cent

ratio

n (µ

g/m

³)




444...222 ––– BBBlllaaaccckkk cccaaarrrbbbooonnn aaaeeerrrooosssooolll sssiiizzzeee dddiiissstttrrriiibbbuuutttiiiooonnnsssAs fine mode black carbon particles carries many carcinogenic organic compounds,

it is important to measure with detail the concentration and size distribution of these

particles. Figure 4.2.1 shows the size distribution of black carbon aerosol particles

measured in O’Higgins on August 16, 1998. Significant concentrations were observed in

very fine size ranges, from 0.093 to 0.33µm in size. This is exactly the range expected to

have the highest lung penetration and deposition. The size distribution shows a consistent

picture. The same is true for others cascade impactors collected at different periods at the

O’Higgins sampling site. It is important to notice that black carbon particles have very

strong absorption characteristics for the visible part of the solar spectrum, especially at the

size range 0.2-0.4 µm. The amount of solar radiation absorbed by the high black carbon

concentrations as measured in Santiago de Chile could affect the vertical structure of the

temperature. This temperature changes affects the vertical atmospheric stability. Further

studies in Santiago could be directed to clarify this important phenomena.


0

200

400

600

800

1000

1200

1400

1600

1800

2000

Blac

k C

arbo

n C

once

ntra

tion

(ng/

m³)


Aerosol Size Distribution Santiago 98MOUDI 2 Black Carbon (16/08/98)

Figure 4.2.1 – Black carbon aerosol size distribution measured with the MOUDIcascade impactor in the O’Higgins sampling site. Sampling on August 16, 1998.

555 ––– CCCooonnncccllluuusssiiiooonnnsssAerosol mass concentrations for the fine, coarse and PM10 aerosol components

were measured for 5 sites in Santiago de Chile. Averages aerosol concentrations are high,

and similar to the ones measured in São Paulo. We also observed a significant reduction in

aerosol concentrations between 1996 and 1998. The average concentrations observed at

O’Higgins and Las Condes sites may have an important impact on human health. It was

observed that Santiago de Chile suffers from important air pollution problem, especially in

the aerosol particle component. Black carbon concentrations are high in downtown

Santiago, in levels approaching European black carbon standards.

There was a very significant reduction in 1998 compared to measurements in 1996

in the concentration of elements associated with residual oil combustion (vanadium and

nickel). This reduction is probably an effect of air pollution control strategies in making

more intense use of natural gas instead of oil combustion in industries in the metropolitan

area of Santiago de Chile. Also a reduction in black carbon concentrations was clearly

observed, possibly because of air pollution control strategies and the modernization of the

buses and auto fleet. Also reduction in fine mode mass concentration in Santiago was

pronounced for the Gotuzo and O’Higgins region.

It was identified five main aerosol sources in the urban area of Santiago: 1)

ressuspended soil dust; 2) Vehicular emissions; 3) Residual oil combustion; 4) Industrial


emission; 5) Emissions from copper smelters. For most of the sites, but more importantly

in the O’Higgins and Las Condes sites, ressuspension of soil dust and traffic emissions

dominates the aerosol mass concentrations. The cooper smelter component was observed

in all five sampling sites, including the two more remote ones, Talagante and Peldehue.

Aerosol size distribution was measured showing two size ranges: fine mode

particles centered at 0.33µm aerodynamic diameter, and coarse mode particles centered at

3µm. Back carbon concentration were present exclusively in the fine mode fraction.

AAAccckkknnnooowwwllleeedddgggeeemmmeeennntttsssThanks are due to Pedro Oyola, Roberto Martinez, and Alcides Camargo Ribeiro

for help during the sampling and analysis. We also thank Ana L. Loureiro and Tarsis

Germano for assistance during gravimetric and PIXE analysis. The staff of the LAMFI

laboratory is acknowledged for assistance in accelerator operation. We thank financial

support from CONAMA-RM for this study.

666 ––– RRReeefffeeerrreeennnccceeesss aaannnddd bbbiiibbbllliiiooogggrrraaappphhhyyyAndrade, M. F., C. Orsini, and W. Maenhaut, Relation between aerosol sources and meteorologicalparameters for inhalable atmospheric particles in São Paulo city, Brazil. Atmospheric Environment, Vol. 28,No. 14, pp.2307-2315, 1994.

Andrade, M. F., Orsini, C., Maenhaut, W., Receptor modeling for inhalable atmospheric particles in sãoPaulo, Brazil, Nuclear Instruments and Methods in Physics Research, B75, pp. 308-311, 1993.

Andreae, M. O., T. W. Andreae, R. J. Ferek, and H. Raemdonck, Long-range transport of soot carbon in themarine atmosphere, Sci. Total Environment, 36, 73-80, 1984.

Artaxo, Castro, W. E. de, Freitas, M. de, Longo, K.M., Receptor modeling of atmospheric aerosols in theurban area of São Paulo, in: Applied Research in air pollution using nuclear-related analytical techniques,Report International Atomic Energy Agency, NAHRES-26, IAEA, Vienna, 1995a.

Artaxo, P., and C. Orsini, PIXE and receptor models applied to remote aerosol source apportionment inBrazil, Nucl. Instrum. Methods Phys. Res., B22, 259-263, 1987.

Artaxo, P., and H. C. Hansson, Size distribution and trace element concentration of atmospheric aerosolsfrom the Amazon Basin, in Aerosols: Science, Industry, Health and Environment, edited by S. Masuda andK. Takahashi, pp. 1042-1045, Elsevier, New York, 1990.

Artaxo, P., and H-C Hansson, Size distribution of biogenic aerosol particles from the Amazon basin. Atmos.Environ., 29, 3, 393-402, 1995.

Artaxo, P., F. Gerab, M. A. Yamasoe, J. V. Martins, Fine Mode Aerosol Composition in Three Long TermAtmospheric Monitoring Sampling Stations in the Amazon Basin. Journal of Geophysical Research, Vol. 99,D11, Pages 22857-22868, 1994.

Artaxo, P., H. Storms, F. Bruynseels, R. Van Grieken, and W. Maenhaut, Composition and sources ofaerosols from the Amazon Basin, J. Geophys. Res., 93, 1605-1615, 1988.

Artaxo, P., H-C Hansson, Size distribution of biogenic aerosol particles from the Amazon basin.Atmospheric Environment, Vol. 29, No. 3, pg. 393 - 402, 1995.

Artaxo, P., W. Maenhaut, H. Storms, and R. Van Grieken, Aerosol characteristics and sources for theAmazon Basin during the wet season, J. Geophys. Res., 95, 16971-16985, 1990.


Cahill, T. A., R. A. Eldred, J. Barone, and L. Ashbaugh, Ambient aerosol sampling with stacked filter units,Rep. Fed. Highway Adminis. FHW-RD-78-178, 78 pp., Air Qual. Group, Univ. of Calif., Davis, 1979.

Earthwatch, Urban air pollution in megacities of the world, Global Environment Monitoring System, UNEP,WHO, 1992.

Echalar, F., P. Artaxo, G. D. Thurston, "Source apportionment of aerosols in the industrial area of Cubatão,Brazil". in: "Aerosols: Science, Industry, Health and Environment", ed. S. Masuda e K. Takahashi, pg. 942-945, Elsevier, London, 1990.

Gordon, G., Receptor Models, Environmental Science and Technology, Vol. 22, no. 10, 1988.

Hopke, P. K., Receptor Modeling for Air Quality Management, 2nd. ed., Elsevier Science Publishers,Amsterdam, 1991.

Hopke, P. K., Receptor Modeling in Environmental Chemistry, John Wiley, New York, 1985.

Hopke, P. K., Y. Xie, T. Raunemaa, S. Biegalski, S. Landsberger, W. Maenhaut, P. Artaxo, D. Cohen,Characterization of the Gent Stacked Filter Unit PM10 sampler. Aerosol Science and Technology, 27, 726-735, 1997.

Johansson, S. A. E., and J. L. Campbell, PIXE - A Novel Technique for Elemental Analysis, John Wiley, NewYork, 1988.

John, W., S. Hering, G. Reischl, and G. Sasaki, Characteristics of Nuclepore filters with large pore size, II,Filtration properties, Atmos. Environ., 17, 373-382, 1983.

Orsini, C.; Andrade, F.; Artaxo, P., "Characteristics of inhalable particles of São Paulo", in: Aerosols:Formation and Reactivity, ed. G. Israel, pg. 14-17 Pergamon Press, 1986.

Orsini, C.; Artaxo, P.; Tabacniks, M., "The São Paulo PIXE system and its use on a national monitoring airquality program", Nuclear Instruments & Methods in Physics Research, Vol. 231, pg. 462-465, 1984.

Orsini, C.; Artaxo, P.; Tabacniks, M., "Trace elements in the urban aerosol of São Paulo", Ciência e Cultura,Vol. 36, no. 5, pg. 823-827, 1984.

Orsini, C.; Tabacniks, M.; Artaxo, P.; Andrade, F.; Kerr, A., "Characteristics of fine and coarse particles ofnatural and urban aerosols of Brazil", Atmospheric Environment, Vol. 20, no. 11, pg. 2259-2269, 1986

Ortiz, J.L. N. Apablaza, C. Campos, S. Zolezzi, M. Prendez, Tropospheric aerosols above the thermalinversion layer of Santiago, Chile: size distribution of elemental concentrations. Atmospheric Environment,27, 397-400. 1993.

Rojas, C. M., P. Artaxo, R. Van Grieken, Aerosols in Santiago de Chile: A study using receptor modellingwith X-ray fluorescence and single particle analysis. Atmospheric Environment 24B, 2, pp 227-241, 1990.

Parker, R.D., G.H. Buzzard, T.G. Dzubay, and J.P. Bell, A two stage respirable aerosol sampler usingNuclepore filters in series, Atmos. Environ., 11, 617-621, 1977.

Prendez, M., J. L. Ortiz, E. Cortes, V. Cassorla, Elemental composition of the airborne particulate matterfrom Santiago City, Chile, 1976. J. Air Pollut. Control Ass. 34, 54-56, 1984.

Switlicki, E., S. Puri, H. C. Hansson, Urban air pollution source apportionment using a combination ofaerosol and gas monitoring techniques, Atmospheric Environment, Vol. 30, pp. 2795-2809, 1996.

Thurston, G. C., and J. D. Spengler, A quantitative assessment of source contributions to inhalable particulatematter pollution in metropolitan Boston, Atmos. Environ., 19, 9-25, 1985.

Trier, A., and Silva, C., Inhalable urban atmospheric particulate matter in a semi-arid climate: the case ofSantiago de Chile. Atmospheric Environment, 21, 419-983. 1987.

Trier, A., Observations on inhalable atmospheric particulate in Santiago, Chile, J. Aerosol Science, 15, 419-421, 1984.

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