Source apportionment using reconstructed mass calculations

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Source apportionment using reconstructed masscalculationsNaila Siddique a & Shahida Waheed aa Chemistry Division, Directorate of Science , Pakistan Institute of Nuclear Science andTechnology , Islamabad , PakistanPublished online: 17 Dec 2013.

To cite this article: Naila Siddique & Shahida Waheed (2014) Source apportionment using reconstructed mass calculations,Journal of Environmental Science and Health, Part A: Toxic/Hazardous Substances and Environmental Engineering, 49:4,463-477, DOI: 10.1080/10934529.2014.854687

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Journal of Environmental Science and Health, Part A (2014) 49, 463–477Copyright C© Taylor & Francis Group, LLCISSN: 1093-4529 (Print); 1532-4117 (Online)DOI: 10.1080/10934529.2014.854687

Source apportionment using reconstructed mass calculations

NAILA SIDDIQUE and SHAHIDA WAHEED

Chemistry Division, Directorate of Science, Pakistan Institute of Nuclear Science and Technology, Islamabad, Pakistan

A long-term study was undertaken to investigate the air quality of the Islamabad/Rawalpindi area. In this regard fine and coarseparticulate matter were collected from 4 sites in the Islamabad/Rawalpindi region from 1998 to 2010 using Gent samplers andpolycarbonate filters and analyzed for their elemental composition using the techniques of Neutron Activation Analysis (NAA),Proton Induced X-ray Emission/Proton Induced Gamma-ray Emission (PIXE/PIGE) and X-ray Fluorescence (XRF) Spectroscopy.The elemental data along with the gravimetric measurements and black carbon (BC) results obtained by reflectance measurement wereused to approximate or reconstruct the particulate mass (RCM) by estimation of pseudo sources such as soil, smoke, sea salt, sulfateand black carbon or soot. This simple analysis shows that if the analytical technique used does not measure important major elementsthen the data will not be representative of the sample composition and cannot be further utilized for source apportionment studiesor to perform transboundary analysis. In this regard PIXE/PIGE and XRF techniques that can provide elemental compositionaldata for most of the major environmentally important elements appear to be more useful as compared to NAA. Therefore %RCMcalculations for such datasets can be used as a quality assurance (QA) measure to treat data prior to application of chemometricaltools such as factor analysis (FA) or cluster analysis (CA).

Keywords: Reconstructed mass (RCM), pollution sources, soil, crustal material, sulfate, black carbon (BC), Islamabad.

Introduction

Awareness of environmental pollution issues and degrada-tion has resulted in air monitoring and air quality studiesbecoming a routine part of our lives. Environmental regu-latory agencies throughout the world monitor and reportcoarse and fine particulate masses (PM10 and PM2.5, respec-tively) along with the amounts of various criteria pollutantssuch as CO, CO2, CH4, O3, NOx, SOx, etc. To evaluate theair quality status, the data obtained can be directly com-pared with the local national standards or it can be furthertreated and analyzed to obtain more detailed informationregarding the pollution sources and their origin. This is es-pecially useful if the concentrations of a large number ofspecies are available over a long time period.

Multiple techniques can be used to obtain a more com-plete picture of particulate composition. A database, named“A-PAD,” is being compiled using the data obtained dur-ing the Joint UNDP/RCA/IAEA Project RAS/7/015“Characterization and Source Identification of Particu-late Air Pollution in the Asian Region” (1998 to 2012).This database will be available from the IAEA websiteand will contain the data for all 16 countries that par-ticipated in this project. The data for Pakistan has been

Address correspondence to Naila Siddique, Chemistry Division,Directorate of Science, PINSTECH, P. O. Nilore, Islamabad,45650 Pakistan; E-mail: [email protected] June 10, 2013.

used in this work to show how some simple data anal-ysis procedures may be used to obtain useful results orto initially sort the data. The A-PAD database containssample collection details along with the gravimetric data,black carbon (BC) values obtained using reflectance mea-surements and elemental composition of fine (with aerody-namic diameter <2.5 µm PM2.5) and coarse (aerodynamicdiameter between 2.5 µm and 10 µm PM2.5–10) particulatematter (PM) obtained using nuclear analytical techniques(NATs), such as Neutron Activation Analysis (NAA), Pro-ton Induced X-ray Emission/ Proton Induced Gamma-rayEmission (PIXE/PIGE) and X-ray Fluorescence (XRF)Spectroscopy.

Fine and coarse PM samples were collected from 4 sitesin the Islamabad/ Rawalpindi region from 1998 to 2012.Details of sampling sites, sample collection and analysis aregiven in our earlier work and summarized in Table 1.[1] Hereonly the data obtained till 2010 is presented and discussedhere. As mentioned earlier, air quality studies are carriedout to identify sources of pollution and their origin. One ofthe simplest ways to carry out source apportionment anal-ysis is by the calculation of reconstructed mass as discussedbelow.

Reconstructed mass (RCM)

The reconstructed mass or RCM is calculated by assumingthat six composite variables or pseudo sources, as given in

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464 Siddique and Waheed

Table 1. Air filter samples collected from Islamabad/Rawalpindi area (1998–2010).

Site name Coordinates

No. of filterpairs

collected Sample collection dates

Techniqueused foranalysis

G-9/3 (Residential/commercial)

33◦ 41′ 3′′N 73◦ 2′ 1′′E 16 05/08/1999 to 18/12/1999 INAA

I-9 (Industrial; Steel re-rollingplants, marble factories, etc.)

33◦ 39′ 41′′N 73◦ 3′ 47′′E 115 04/10/1998 to 01/10/1999 (73)13/01/2001 to 25/04/2002 (42)

INAA

Nilore (Rural; farms, residences,shops, brick kilns, etc.)

33◦ 39′ 7′′N 73◦ 15′ 41′′E 874 17/04/2002 to 09/07/200312/11/2003 to 20/05/200923/5/2009 to 25/11/2010

INAA (163)IBA (560)XRF (147)

Airport Housing Society (AHS)(Residential/heavy traffic)

33◦ 36′ 3′′N 73◦ 7′ 34′′E 103 14/02/2004 to 07/08/2004 IBA (103)

the following equation, are the major contributors to fineand coarse particle mass.[2,3]

RCM = [Soil

] + [OC

] + [BC

] + [Smoke

] + [Sulfate

]

+[Seasalt

](1)

where the 6 pseudo-sources are calculated using the elemen-tal concentrations of their constituent elements as givenhere:

[Soil

] = 2.20 ∗ [Al

] + 2.49 ∗ [Si

] + 1.63 ∗ [Ca

]

+2.42 ∗ [Fe

] + 1.94 ∗ [Ti

](2)

[OC] =∑

[Organics] (3)

[BC] = [Soot] (4)[Smoke] = [K ] − 0.6 ∗ [Fe] (5)

[Seasalt] = 2.54 ∗ [Na] = [Na] + [Cl] (6)[Sulfate] = 4.125 ∗ [S] (7)

The [Soil] factor contains elements predominantly foundin the earth’s crust (Al, Si, Ca, Fe, Ti) as oxides and includesa multiplier to correct for the oxygen content and an ad-ditional multiplier of 1.16 to correct for the fact that threemajor oxide contributors (MgO, K2O, Na2O), carbonateand bound water are excluded from Eq. (2).

In the case of [OC] determination, total hydrogen onthe filter is assumed to comprise mainly of H from organicmaterial and ammonium sulfate. Therefore organic contentis calculated from the total amount of H by the followingequation:

[OMH] = 11 ∗(

[H] − 0.25 ∗ [S])

(8)

In Eq. (8), it is assumed that average particulate organicmatter is composed of 11% H, 71% C, and 20% O by weight.As H was not measured in our study therefore, this factoris not included in the formula for RCM in our calculations.[BC] is simply the soot or concentration of black carbon,measured in this case by light reflectance. [Smoke] repre-sents K not included as part of crustal matter. This factoris used as an indicator of biomass burning. [Seasalt] repre-

sents the marine aerosol contribution and assumes that theNaCl weight is 2.54 times the Na concentration. Approxi-mate values of sea salt can also be determined by summingthe measured amounts of Na and Cl. However, Na is morecommonly used as Cl can be volatilized from aerosol orfrom filters in the presence of acidic aerosol, particularly inthe fine fraction via the reactions.

NaCl (s) + HNO3 (aq) → NaNO3 (s) + HCl (g) (9)NaCl (s) + H2SO4 (aq) → 1/2Na2SO4 (s) + 2HCl (g)

(10)

Most fine sulfates are the result of oxidation of SO2 gas toform sulfate particles in the atmosphere. It is assumed thatsulfate is present in fully neutralized form as ammoniumsulfate. Sulfate therefore represents the ammonium sulfatecontribution to aerosol mass with the multiplicative factorof 4.125∗[S] to account for ammonium ion and oxygenmass. The amounts of sulfate have also been estimated usingother formulae such as:[4,5]

[(NH4)2 SO4

] = 0.29 ∗ [NO−

3

](11)

or[(NH4)2 SO4

] = 3 ∗ [S] (12)

Other authors have also included other pseudo-sourcesto make the RCM expression more complete. For exampleMurillo et al. have used the following formulae:[4]

RCM = [Soil

] + [OM

] + [EC

] + [TEO

]

+[(NH4

)2SO4

] + [NH4 NO3

] + [NaCl

]

+[PBW

](13)

where

Ammonium Nitrate [NH4 NO3] = 1.29 ∗ [NO−

3

](14)

Organic Matter [OM] = 1.4 ∗ [OC] (15)Elemental Carbon [EC] = [EC] = [BC] (16)

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Source apportionment using mass calculations 465

OC is the organic carbon. OC and EC can be determinedusing thermo-optical methods. [6]

Soil[Soil

] = 3.48 ∗ [Si

] + 1.63 ∗ [Ca

] + 2.42 ∗ [Fe

]

+1.41 ∗ [K

] + 1.94 ∗ [Ti

](17)

Total Elemental Oxides[TEO

] = 1.47 ∗ [V

] + 1.29 ∗ [Mn

] + 1.27 ∗ [Ni

]

+1.25 ∗ [Cu

] + 1.24 ∗ [Zn

] + 1.08 ∗ [Pb

]

+3.07 ∗ [P

] + 1.31 ∗ [Cr

](18)

Particle Bound Water [PBW ] = 0.32 ∗ ([SO2−

4

] + [NH+

4

])(19)

In the present study ammonium nitrate, organic car-bon and elemental carbon were not measured. There-fore these sources were not included when Eq. (13) wasused.

Minerals in decreasing importance in average sedimentare: SiO2, Al2O3, CaO, CO2, Fe2O3, H2O, K2O, MgO, FeO,C, Na2O, TiO2, SO2, P2O5 and Ba. Potassium can alsocome from smoke, Fe from industrial sources, Al from alu-minum smelters and Ca from concrete. As Al is difficult tomeasure using X-ray analysis (PIXE or XRF) due to theinterference with the Si peak it is suggested that where Alis measured Eq. (2) should be used. If it is missing then theformula using Si (Eq. (17)) should be used. Si can also beused instead of Fe to find the soil component of K; i.e., Sifactor changes to 2.66 and Fe factor to 1.58.

Frank [5] states that due to high detection limits for Alobtained using XRF the equation for soil becomes:

[Crustal Material

] = 3.73 ∗ [Si

] + 1.63 ∗ [Ca

]

+2.42 ∗ [Fe

] + 1.94 ∗ [Ti

](20)

This expression differs slightly from Eq. (17). Frank alsoobserved that most filter analysis methods do not cap-ture all ambient particles. Losses of ammonium nitrate(NH4NO3) and other semi-volatile organic compounds(SVOCs) produce negative artifacts while particle boundwater (PBW) associated with hygroscopic species producespositive artifacts.

The RCM and mass closure calculations using thepseudo-source and pseudo-element approach have beenfound to be a useful way to examine initial relationshipsin the data and to see how the measured mass of speciesin samples compare to gravimetric mass. As a quality as-surance (QA) mechanism, those samples for which RCMgreatly exceeds gravimetric mass are excluded from fur-ther analysis. From the above and numerous other pub-lications,[3,7] it can be seen that various expressions areused to obtain measures of different species. Therefore careshould be taken when making comparison or reaching anyconclusions.

Materials and methods

Sampling sites

As summarized in Table 1, fine and coarse PM sampleswere collected using Gent samplers from 4 sites in theIslamabad/Rawalpindi region from 1998 to 2010.[1] Sam-pling sites were selected to ensure that different environ-ments were studied and elemental analysis was carried outusing NAA, PIXE/PIGE and XRF at the Pakistan Insti-tute of Nuclear Science and Technology (PINSTECH) inPakistan, at the Institute of Geological and Nuclear Sci-ences Limited (GNS) in New Zealand and at ClarksonUniversity (Potsdam, NY, USA), respectively. Thereforethe merits and de-merits of each technique can be assessedfor such studies having access to such a database.

Due to practical issues such as availability of continuouspower supply, trained personnel for filter loading and un-loading, security etc the samples were collected at 3 sitesin Islamabad and 1 site in Rawalpindi. The Gent samplerwas initially tested at 2 sites in Islamabad; 1) the small in-dustrial area in I-9 and 2) the busy commercial/ residentialG-9 site. NAA methodology was developed for the analysisof the samples collected. The sampler was kept at the I-9site for a longer period to observe the impact of the smallindustrial units operational in the industrial area of Islam-abad. Samples were collected continuously at the Niloresite from April 2002 onwards. A sampler was also locatedat the Airport Housing Society (AHS) site in Rawalpindiduring 2004. This is a busy residential area close to Islam-abad International Airport in the busy neighbouring city ofRawalpindi. Details of the sampling sites and the numberof samples collected are given in Table 1.

Sample collection

Coarse and fine air particulate samples were collected usingGent samplers and Nucleopore polycarbonate filters.[8] Thesampler contains 2 filters; the top filter collects particulatematter of size between 2.5–10 µm aerodynamic diameterwhile the bottom filter collects particulate matter of size2.5 µm and less aerodynamic diameter. Samples were col-lected from the roofs of buildings at a height of around4–6 m. Around 2–3 samples were collected weekly witheach sample being collected for around 24 hours. Furtherdetails are available in Table 1.

Gravimetric analysis

The polycarbonate filters were weighed before and aftersampling using a Sartorius BP 210D semi-microbalance(Goettingen, Germany). Prior to weighing the filters werestored for 24 h at controlled environmental conditions of20◦C and 50% humidity. The gravimetric mass was ob-tained from the particulate loading and the volume of airpassed through the sampler.

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Tab

le2.

RC

Mca

lcul

atio

nsfo

rP

M2.

5sa

mpl

esco

llect

edat

the

4sa

mpl

ing

site

sin

the

Isla

mab

ad/R

awal

pind

iare

a.

AH

SG

-9I-

9N

ilore

Para

met

erA

ve.

Ran

ge#

Ave

.R

ange

#A

ve.

Ran

ge#

Ave

.R

ange

#

Soil

5797

±33

3213

48–1

5890

9013

65±

647

892–

2493

512

86±

917

163–

3570

3924

77±2

646

53–1

9748

530

Smok

e11

2±

119

12–1

086

9040

6±

341

97–1

310

1213

3±17

52–

1735

474

BC

3618

±18

9610

59–7

988

9090

35±

3105

4480

–136

749

4665

±28

6912

78–1

4949

3622

93±1

670

65–1

2900

530

SS(N

a)22

0±

170

15–1

125

9066

4±

247

378–

808

313

42±

1067

257–

5075

3930

9±31

64–

3175

498

SS(N

aCl)

257±

401

87–3

885

9026

1±

9714

9–31

83

529

±42

010

1–19

9839

181±

209

2–25

7952

9(N

H4) 2

SO4

2236

±16

9882

1–15

680

9014

61±1

186

19–9

075

430

RC

M11

983±

5663

4878

–273

9290

1001

5±

3958

4480

–153

229

7059

±36

8016

27–1

7967

3963

05±4

372

433–

2503

253

5�

RC

M45

78±

5040

−252

4–30

532

9017

787

±92

7833

15–3

5071

919

064

±17

481

2225

–932

3439

5827

±755

8−1

0884

–766

3953

5So

il(S

i)62

11±

3556

1457

–168

6890

390

±32

359–

419

367

9±

614

7–24

5638

2582

±291

647

–211

6352

0T

EO

339±

738

51–7

002

9016

±3

13–1

93

481

±96

21–

4079

3817

6±20

92–

1873

523

PB

W61

8±

469

227–

4333

9040

4±32

85–

2508

430

RC

M12

941±

6397

5244

–385

2390

1002

0±

3964

4480

–153

419

7527

±40

0916

27–1

8304

3968

57±5

013

259–

2771

353

5�

RC

M36

20±

5106

−670

4–30

044

9017

782

±92

7633

15–3

5071

918

596

±17

187

2212

–927

5839

5275

±760

6−1

3097

–750

5153

5C

rust

alM

ater

ial

6076

±35

3113

83–1

6826

9039

0±

3235

6–41

93

451±

410

7–18

5937

2521

±29

342–

2118

849

7

Not

e:A

irpo

rtH

ousi

ngSo

ciet

y(A

HS)

site

isin

Raw

alpi

ndiw

hile

G-9

,I-9

and

Nilo

rear

ere

side

ntia

l,in

dust

rial

and

rura

lsit

esin

Isla

mab

ad.

466

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Tab

le3.

RC

Mca

lcul

atio

nsfo

rP

M2.

5–10

sam

ples

colle

cted

atth

e4

sam

plin

gsi

tes

inth

eIs

lam

abad

/Raw

alpi

ndia

rea.

AH

SG

-9I-

9N

ilore

Para

met

erA

veR

ange

#A

veR

ange

#A

veR

ange

#A

veR

ange

#

Soil

5292

3±

1604

820

019–

8983

690

5706

±30

4420

28–9

566

632

705

±21

134

4139

–102

761

3916

282±

1177

751

9–11

8408

533

Smok

e11

3±

888–

358

3220

00±

1472

64–5

957

2333

7±

794

0.5–

6297

311

BC

6010

±19

4421

41–1

0259

9025

00±

996

1087

–359

79

8779

±49

7817

25–2

2516

3614

43±

812

87–5

288

531

SS(N

a)14

46±

730

392–

4474

9069

3±

7961

0–76

73

3792

±17

8971

1–86

1133

782

±92

23–

1062

751

3SS

(NaC

l)11

22±

563

283–

2898

9027

3±

3124

0–30

23

1522

±72

829

8–34

3833

441

±32

635

–418

452

5(N

H4) 2

SO4

7351

±26

5527

55–1

5667

9015

65±

1274

84–1

0381

431

RC

M67

770

±19

591

2878

2–10

8520

9065

35±

4685

1568

–137

729

4519

7±

2588

474

83–1

2014

739

1982

7±

1350

590

0–12

3904

536

�R

CM

7423

3±

3767

820

217–

2108

0490

5273

4±

1556

721

353–

7334

39

2050

28±

1366

7544

926–

5433

5039

2606

0±

3193

3−3

4261

–341

477

536

Soil

(Si)

5702

9±

1748

021

510–

9716

190

3436

±80

527

81–4

334

318

135

±17

076

898–

8893

439

1552

4±

1149

336

5–85

338

530

TE

O13

19±

642

453–

4547

9056

±5

52–6

13

525

±11

6921

–744

339

416

±43

37–

5322

532

PB

W20

31±

734

761–

4330

9043

3±

352

23–2

869

431

RC

M71

120

±20

361

3194

7–11

3429

9065

54±

4712

1568

–138

289

4572

2±

2597

075

18–1

2041

139

1974

3±

1355

890

0–10

8921

536

�R

CM

7088

3±

3704

118

535–

2063

0590

5271

5±

1554

621

353–

7328

29

2045

03±

1364

2844

861–

5429

1039

2613

9±

3475

0−3

0270

–345

073

536

Cru

stal

Mat

eria

l56

952

±17

444

2141

7–97

094

9034

36±

805

2781

–433

43

1474

9±

1536

689

8–81

137

3915

860±

1155

21–

8594

750

5

Not

e:A

irpo

rtH

ousi

ngSo

ciet

y(A

HS)

site

isin

Raw

alpi

ndiw

hile

G-9

,I-9

and

Nilo

rear

ere

side

ntia

l,in

dust

rial

and

rura

lsit

esin

Isla

mab

ad.

467

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38.37

23.82

0.75 1.56

14.76

38.72

4.42

0.09 1.01

5.52

0

5

10

15

20

25

30

35

40

45

%Soil %BC %Smoke %Sea Salt %Sulfate

% C

ontr

ibut

ion

to P

M

Fine Coarse

(a) Airport Housing Society (AHS), Rawalpindi

3.92

35.77

2.12

9.27

4.16

0.870

5

10

15

20

25

30

35

40


% C

ontr

ibut

ion

to P

M

Fine Coarse

(b) G-9, Islamabad

5.65

23.64

1.96

6.16

13.97

3.58

0.941.92

0

5

10

15

20

25


% C

ontr

ibut

ion

to P

M

Fine Coarse

(c) I-9, Islamabad

23.54 22.46

1.263.35

15.33

46.27

4.32

0.571.93

5.58

0

5

10

15

20

25

30

35

40

45

50


% C

ontr

ibut

ion

to P

M

Fine Coarse

(d) Nilore, Islamabad

Fig. 1. Comparison plots of percentage contribution of different sources at the 4 sampling sites in the Islamabad/Rawalpindi area.

Black carbon (BC) measurement

An Evans Electro Selenium Limited (London, UK), EEL43D smoke stain reflectometer was used for black carbon(BC) measurements. Standard filters were used to calibratethe reflectometer and were also used for QA/QC purposes.BC was determined by comparing the reflectance from anexposed filter and a blank filter. A fixed value of 5.27 m2/gwas used as mass attenuation coefficient for all sites andseasons.[9]

Elemental analysis

Three analytical techniques NAA, PIXE/PIGE and XRFwere used to determine the elemental composition of thecollected samples. Brief details of these techniques and theconditions, equipment and procedures employed are givennext.

Neutron activation analysis (NAA)

Numerous publications are available in which NAA hasbeen used to study air particulate matter in the past.[10–17]

Experimental procedures employed depend on the reactorused as well as the size of the sample being analyzed. In thiswork the samples were irradiated twice first at the 27 kWPakistan Atomic Research Reactor-II (PARR-II) facility todetermine the shorter lived isotopes, cooled for 2–4 weeksand then the 9 MW Pakistan Atomic Research Reactor-I (PARR-I) was used to determine longer lived elements.Reference materials IAEA-S7 (soil), IAEA-SL1 (lake sed-iment) and IAEA-SD-M-2/TM (marine sediment) wereused for QA purposes. Further details are available in ourearlier publications.[1,18,19]

Ion beam analysis (IBA)

IBA has also been extensively used for the study of airparticulate samples.[20–23] Important elements from an en-vironmental point of view such as Cd, P, Pb, S and Sicannot be determined using conventional NAA but can beeasily determined using IBA methods. Therefore, IBA tech-niques such as proton induced X-ray emission (PIXE) and

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38.37

40.95

40.09

38.72

41.67

41.63

0 20 40 60 80 100

%Soil

%Soil (Si)

%Crustal Material

% Soil/ Crustal Contribution

Coarse Fine

(a) AHS, Rawalpindi

3.92

1.19

1.19

9.27

4.32

4.32

0 20 40 60 80 100

%Soil

%Soil (Si)

%Crustal Material


Coarse Fine

(b) G-9, Islamabad

5.65

3.51

2.29

13.97

7.72

6.23

0 20 40 60 80 100

%Soil

%Soil (Si)

%Crustal Material


Coarse Fine

(c) I-9, Islamabad

23.54

24.66

24.05

46.27

46.80

48.54

0 20 40 60 80 100

%Soil

%Soil (Si)

%Crustal Material


Coarse Fine

(d) Nilore, Islamabad

Fig. 2. Comparison plots of % Soil related species at the 4 sampling sites in the Islamabad/Rawalpindi area.

proton induced gamma-ray emission (PIGE) were used toanalyze elements heavier than Ne. A SiLi detector was usedto obtain X-ray spectra, while a HPGe detector was used toobtain the gamma-ray spectra. Gupix software was used toperform the de-convolution of the X-ray spectra obtained.A total of 29 elements, namely Al, As, Br, Ca, Cl, Co, Cr,Cu, F, Fe, Ga, Ge, Hg, I, K, Mg, Mn, Na, Ni, P, Pb, Rb, S,Sc, Se, Sr, Ti, V, Zn were determined in the fine and coarsesamples. The analysis was carried out at the Institute ofGeological and Nuclear Sciences Limited (GNS) in NewZealand.[1]

X-ray fluorescence spectrometry

X-ray fluorescence (XRF) spectrometry is used extensivelyby the United States Environmental Protection Agency(US EPA) to carry out elemental analysis in its Intera-gency Monitoring of the Protected Visual Environments(IMPROVE) network due to it suitability for the analysisof filters containing few hundred micrograms of particulate

air pollutant.[24] First, 147 pairs of coarse and fine filterssamples were analyzed using XRF at Clarkson University,USA, using the Spectro XLAB-2000 XRF spectrometer(Westborough, MA, USA). Single element MicroMatterStandards were used to develop the calibration parametersand samples of NIST SRM 2783 were analyzed with eachbatch of samples for QA purposes. XRF can be used todetermine the concentrations of Cd, P, Pb, S, Si as well asother elements but has a lower sensitivity than NAA.

Results and discussion

In the current study a large amount of data were obtained.The fact that sampling was carried out at multiple sitesenables us to compare the variations in the elemental com-position of these sites which can be attributed to the dif-ferences in the land uses at these sites. Moreover as at theNilore site 3 analytical techniques were used for the de-termination of the elemental composition of particulate

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79.26

38.6634.24

62.16

49.72

10.63

19.45

56.96

0

10

20

30

40

50

60

70

80

90

AHS G-9 I-9 Nilore

RC

M (

%)

Fine Coarse

(a)

85.26

38.6735.76

67.91

52.22

10.66

19.66

59.85

0

10

20

30

40

50

60

70

80

90

AHS G-9 I-9 Nilore

RC

M (

%)

Fine Coarse

(b)

Fig. 3. % RCM calculated using (a) Eq. (1) and (b) Eq. (13) at the4 sampling sites in the Islamabad/ Rawalpindi area.

samples comparison of techniques can also be carried out.Furthermore as sampling was carried simultaneously at 2sites in 2004 (Nilore and AHS) direct comparison of sitescan be made which is not possible for the other 2 sites (G-9and I-9) where the sampling periods do not overlap.

Comparison of RCM data for sampling sites

The results obtained for the fine and coarse samples col-lected at the 4 sampling sites were used in Eqs. (1), (2), and(4)–(7) to obtain the data presented in Tables 2a and 2b. The[Soil], [TEO] and [PBW] components were also calculatedusing Eqs. (17)–(19), respectively, while RCM was obtainedusing both Eqs. (1) and (13). This was done to observe theeffect of inclusion of [TEO] and [PBW] on the [RCM] aswell as to see how using [Si] instead of both [Al] and [Si]effect the magnitude of the [Soil] component. [Seasalt] wascalculated using both the amounts of Na and Cl and justNa as shown in Eq. 6. The RCM was subtracted from thePM mass to obtain �RCM for each mass fraction.

This quantity can be positive when the RCM is lessthan the PM mass and negative when it exceeds it. Dueto the presence of numerous sources of particulate matterwhich cannot be all identified or measured �RCM shouldhave a positive magnitude. However, the lower the valuesof �RCM the better the sources used to approximate thePM mass and the better the technique or combination oftechniques used to obtain the data. The crustal componentsof fine and coarse PM masses, PM2.5 and PM2.5–10 respec-tively, were also estimated using Eq. (20) and are given inthe last row of these tables.

In Tables 2a and 2b the average overall values of thespecies discussed along with their standard deviation, rangeand the number of values used for calculations are given.Looking at these tables a few points to note are that as onlyNAA was used to obtain the data for the samples collectedat the G-9 and I-9 sites therefore elements such a Cd, P, Pb,S and Si were not determined at these sites. Consequently[Sulfate] cannot be estimated for these sites. Generally seasalt estimated using just [Na] provided a higher value of[Seasalt] as compared to when both the concentrations ofNa and Cl are summed. This shows the volatile nature ofCl as discussed earlier. The only exception is for the finedata at the AHS site. However the average concentrationdifference is very slight.

In order to better understand this data Figs. 1a–d areplotted in which the data presented in Tables 2a and 2bhave been converted into percentages of PM2.5 and PM2.5–10respectively. These plots clearly show the absence of thesulfate source for the G-9 and I-9 sites. The smoke sourceis also missing at the G-9 site even though both K and Fecan be measured using NAA. Therefore the absence of thissource is probably due to the fact that very few samples werecollected at this site. Moreover as Si was not measured atG-9 and I-9 sites the soil component of PM2.5–10 is onlyaround 10% with the component for PM2.5 even lower ataround 5%. At the G-9 and I-9 sites the major sources ofPM are BC, soil and sea salt. As BC is determined usingreflectance measurement it appears that the data obtainedusing NAA does not apportion a significant amount of thePM mass for both size fractions. It can also be seen that %BC is much higher in PM2.5 than in the PM2.5–10 for all sites.This is not surprising as soot, which is the major constituentof BC, is produced directly and emitted as primary particlesfrom combustion processes.[7]

PIXE/PIGE was used for the speciation of air particulatematter collected at the AHS site while all 3 techniques wereutilized at the Nilore site. At both these sites soil is the majorsource followed by BC and sulfate. However % Soil is higherin PM2.5–10 while % BC and % Sulfate are higher in thePM2.5. This is to be expected as soil particles are producedby physical processes such as abrasion and erosion of largersoil particles, while soot and sulfate particles are createdfrom combustion processes and the reaction of SO2 gaswith moisture in the air respectively.[25] Of the 5 sourcesestimated the % BC, % Smoke, % Seasalt and % Sulfate

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Tab

le4.

RC

Mca

lcul

atio

nsfo

rP

M2.

5sa

mpl

esco

llect

edat

the

Nilo

resi

teus

ing

diff

eren

tan

alyt

ical

tech

niqu

es.

Nilo

reN

AA

PIX

E/P

IGE

XR

F

Para

met

erA

ve.

Ran

ge#

Ave

.R

ange

#A

ve.

Ran

ge#

Ave

.R

ange

#

Soil

2477

±26

4653

–197

4853

011

19±

704

143–

4474

100

3316

±30

0915

2–19

748

315

1360

±15

1653

–142

0411

5Sm

oke

133

±17

52–

1735

474

326±

371

18–1

735

4811

9±

101

2–73

831

189

±15

89–

1382

115

BC

2293

±16

7065

–129

0053

026

60±

1800

389–

1290

010

125

83±

1720

65–1

2473

315

1166

±57

928

5–30

9411

4SS

(Na)

309

±31

64–

3175

498

327±

373

4–31

7510

132

3±

305

20–1

851

288

256±

282

8–22

3410

9SS

(NaC

l)18

1±

209

2–25

7952

912

9±

147

2–12

5010

120

8±

184

33–1

961

315

155±

294

6–25

7911

3(N

H4) 2

SO4

1461

±11

8619

–907

543

017

44±

1214

91–9

075

315

685±

642

19–3

518

115

RC

M63

08±

4372

433–

2503

253

540

88±

2093

756–

1603

210

580

56±

4641

433–

2503

231

535

33±

2339

447–

1828

111

5�

RC

M58

27±

7558

−108

84–7

6639

535

1415

7±

1341

7−1

747–

7518

110

553

07±

8140

−108

84–7

6639

315

4056

±62

94−2

140–

4707

111

5So

il(S

i)25

82±

2916

47–2

1163

520

597

±70

247

–352

590

3525

±32

3817

6–21

163

315

1554

±16

7776

–152

5111

5T

EO

176

±20

92–

1873

523

57±

992–

545

9324

4±

227

3–18

7331

582

±12

910

–117

911

5P

BW

404

±32

85–

2508

430

482±

335

25–2

508

315

189±

177

5–97

211

5R

CM

6804

±47

4246

2–26

683

535

4139

±21

2475

6–16

032

105

8787

±49

7946

2–26

683

315

3804

±25

3946

9–18

834

115

�R

CM

5328

±75

26−1

1726

–755

1253

514

107

±13

432

−174

7–75

181

105

4576

±80

63−1

1726

–755

1231

537

85±

6127

−243

0–45

745

115

Cru

stal

Mat

eria

l25

21±

2934

2–21

188

497

417

±51

72–

3418

6733

76±

3238

165–

2118

831

514

04±

1593

53–1

4946

115

471

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Tab

le5.

RC

Mca

lcul

atio

nsfo

rP

M2.

5–10

sam

ples

colle

cted

atth

eN

ilore

site

usin

gdi

ffer

ent

anal

ytic

alte

chni

ques

.

Nilo

reN

AA

PIX

E/P

IGE

XR

F

Para

met

erA

ve.

Ran

ge#

Ave

.R

ange

#A

ve.

Ran

ge#

Ave

.R

ange

#

Soil

1628

2±

1177

751

9–11

8408

533

1504

3±

1562

951

9–11

8408

102

1708

0±

1182

369

7–79

584

315

1520

1±

6414

3324

–379

5711

6Sm

oke

337

±79

40–

6297

311

1347

±13

319–

6297

6474

±85

0–52

217

678

±76

1–36

871

BC

1443

±81

287

–528

853

120

24±

945

294–

5288

101

1295

±76

287

–413

731

513

38±

559

304–

3426

115

SS(N

a)78

2±

922

3–10

627

513

1584

±14

9619

6–10

627

9958

8±

654

3–58

0029

859

8±

299

46–1

659

116

SS(N

aCl)

441

±32

635

–418

452

558

4±

497

77–4

184

9441

5±

292

35–2

459

315

397

±17

511

2–11

4611

6(N

H4) 2

SO4

1565

±12

7484

–103

8143

117

53±

1374

84–1

0381

315

1056

±74

689

–514

111

6R

CM

1982

2±

1350

490

0–12

3904

536

1887

5±

1708

590

0–12

3904

105

2072

5±

1384

192

2–98

798

315

1822

8±

7462

3834

–415

9711

6�

RC

M26

060±

3193

3−3

4261

–341

477

536

6504

9±

5039

3−3

4261

–341

477

105

1635

7±

1532

3−2

5942

–940

5931

517

113

±89

27−1

5610

–470

0811

6So

il(S

i)15

524±

1149

336

5–85

338

530

6481

±71

6036

5–45

615

9918

008±

1250

575

4–85

338

315

1649

5±

6977

3558

–408

1611

6T

EO

416

±43

37–

5322

532

288

±69

47–

5322

101

528±

353

12–2

113

315

224

±13

828

–750

116

PB

W43

3±

352

23–2

869

431

484±

380

23–2

869

315

292

±20

625

–142

111

6R

CM

2058

8±

1387

790

0–12

3966

536

1915

3±

1711

990

0–12

3966

105

2174

6±

1436

095

7–10

2867

315

1874

5±

7673

3887

–422

3311

6�

RC

M25

294±

3195

9−3

4323

–341

452

536

6477

2±

5037

9−3

4323

–341

452

105

1533

6±

1493

6−2

8436

–899

9031

516

597

±87

39−1

6048

–460

8211

6C

rust

alM

ater

ial

1586

0±

1155

21–

8594

750

560

94±

7003

1–43

510

7418

041±

1258

875

6–85

947

315

1616

9±

6824

3507

–400

7511

6

472

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23.54 22.46

1.263.35

15.33

46.27

4.32

0.57 1.93

5.58

0

5

10

15

20

25

30

35

40

45

50


% C

ontr

ibut

ion

to P

M

Fine Coarse

(a) All Techniques

7.60

20.01

2.69 2.66

18.85

2.741.66 2.11

0

5

10

15

20

25


% C

ontr

ibut

ion

to P

M

Fine Coarse

(b) NAA

28.98

23.29

1.053.35

17.16

56.28

4.98

0.331.95

6.55

0

10

20

30

40

50

60


% C

ontr

ibut

ion

to P

M

Fine Coarse

(c) PIXE/PIGE

21.12 20.68

1.203.86

10.26

43.17

3.92

0.211.71

2.93

0

5

10

15

20

25

30

35

40

45

50


% C

ontr

ibut

ion

to P

M

Fine Coarse

(d) XRF

Fig. 4. Comparison plots of percentage contribution of different sources at the Nilore site for different analytical techniques.

are comparable at the AHS and Nilore sites while % Soildiffers significantly with much higher amounts of fine soilat the AHS site. The Nilore site is a rural site with cultivatedfarmland and some commercial and residential buildingsso the % Soil in the coarse fraction is almost twice as muchas in the fine fraction. The AHS site is mostly residentialwith busy roads and heavy traffic. The remaining area isnot fully covered with vegetation or paved. Therefore the %Soil in both PM2.5 and PM2.5–10 is comparable as significantcontribution is also from road dust to the fine fraction.[1,26]

In Figs. 2a–d the percent contribution from soil relatedelements has been calculated and plotted using Eqs. (2),(17) and (20), respectively. For the G-9 and I-9 sites % Soilobtained from Eq. (2) has the highest magnitude for bothmass fractions due to the fact that Si was not measured atthese sites as NAA was the analytical technique used. Atthe other 2 sites the soil component for both mass frac-tions obtained using all three expression are close to eachother with the % Crustal Material component being slightlygreater in magnitude.

RCM was calculated using Eqs. (1) and (13), respectively,for all 4 sites and both size fractions. The results obtainedare plotted in Figures 3a and 3b. These show that as moresources are included in Eq. (13), therefore, the RCM cal-culated using this equation is greater than when Eq. (1) isused. Moreover at sites where only NAA is used as an ana-lytical technique the fine and coarse % RCM do not exceed20 and 40% of their respective PM masses. Therefore, morethan 80 and 60%, respectively, of the fine and coarse massremains un-apportioned when these calculations are per-formed. In the case of the Nilore and AHS site the fine andcoarse % RCM do not exceed 90 and 60% of their respectivePM masses with the missing or mass un-apportioned beingaround 10 and 40%, respectively. Therefore the elementalanalysis using these techniques is providing a more com-plete picture of the particulate matter. The missing massmay be organics or nitrates which were not measured inthis study. It should be noted that before any conclusionsabout the differences in the 4 sampling sites may be reachedit is required that sampling be carried out simultaneously

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23.54

24.66

24.05

46.27

46.80

48.54

0 10 20 30 40 50 60 70 80 90 100

%Soil

%Soil (Si)

%Crustal Material


Coarse Fine

(a) All Techniques

7.60

4.40

2.74

18.85

8.61

8.36

0 10 20 30 40 50 60 70 80 90 100

%Soil

%Soil (Si)

%Crustal Material


Coarse Fine

(b) NAA

28.98

30.59

29.28

56.28

58.80

58.81

0 10 20 30 40 50 60 70 80 90 100

%Soil

%Soil (Si)

%Crustal Material


Coarse Fine

(c) PIXE/PIGE

21.12

23.76

21.69

43.17

46.81

45.92

0 10 20 30 40 50 60 70 80 90 100

%Soil

%Soil (Si)

%Crustal Material


Coarse Fine

(d) XRF

Fig. 5. Comparison plots of % Soil related species at the Nilore site for different analytical technique.

for at least a year at these 4 sites and the samples analyzedusing the same analytical technique.

Comparison of RCM data for analytical techniques

At the Nilore site sampling was carried out non-stop from2002 to 2010 and the samples were analyzed using NAA,PIXE/PIGE and XRF techniques. The results obtained forthe fine and coarse samples were again used in Eqs. (1), (2),(4)–(7), (13), (17), (18) and (20) to obtain the data presentedin Tables 3a and 3b. The data were also converted into per-centages and are plotted in Figs. 4a–d. These plots clearlyshow that the magnitude of % BC, % Smoke and % Seasaltare comparable for all techniques, while the % Sulfate com-ponent and % Soil component are technique dependent.Moreover the sulfate source is not estimated and the % BCcomponent is the major source when NAA is used. The %Soil component of fine and coarse soil is 28.98%, 56.28%using PIXE/PIGE while it is 21.12%, 43.17% using XRF

respectively. Similarly the % Sulfate component of fineand coarse samples are 17.16%, 10.26% using PIXE/PIGEwhile it is 6.55%, 2.93% using XRF, respectively. The% Soil and % Sulfate estimated using PIXE/PIGE andXRF may differ due to the lower sensitivity of the XRFtechnique.

Another reason may be due to the fact that the samplesanalyzed using PIXE/PIGE and XRF were collected andhence analyzed at different times. In the time period whensamples analyzed using PIXE/PIGE were collected roadscloser to the sampling site were being paved and widened.Moreover more residences and commercial areas were con-structed so lesser exposed soil was present. Furthermore inthis time period compressed natural gas vehicles were intro-duced and their use encouraged. Therefore fewer vehicleson the road were using diesel or gasoline even though thenumber of vehicles increased over time.[1,27] These measuresmay be responsible for the differences in the % Soil and %Sulfate measured at this site at different time periods.

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62.16

30.28

73.53

56.9156.96

23.95

69.83

51.85

0

10

20

30

40

50

60

70

80

All Techs NAA PIXE XRF

RC

M (

%)

Fine Coarse

(a)

67.91

30.67

82.19

60.9259.85

24.32

76.16

53.30

0

10

20

30

40

50

60

70

80

90

All Techs NAA PIXE XRF

RC

M (

%)

Fine Coarse

(b)

Fig. 6. % RCM calculated using (a) Eq. (1) and (b) Eq. (13) at theNilore site for different analytical techniques.

32.98

20.18

0.86

5.92

17.72

48.61

2.820.19

2.624.42

0

10

20

30

40

50

60


% C

ontr

ibut

ion

to P

M

Fine Coarse

Fig. 7. Plot of percentage contribution of different sources at theNilore site for samples collected in 2004.

32.98

20.18

0.86

5.92

17.72

48.61

2.820.19

2.624.42

0

10

20

30

40

50

60


% C

ontr

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M

Fine Coarse

Fig. 8. Plot of % Soil related species at the Nilore site for samplescollected in 2004.

In Figures 5a–d the % contribution from soil relatedelements has been calculated and plotted using Eqs. (2),(17) and (20), respectively. As Si is not determined whenNAA is used the magnitudes of all three soil componentsare below 10% and 20% for the respective fine and coarsefractions. The % Crustal or Soil components calculatedusing Eqs. (2), (17) and (20) provides very similar estimatesfor samples analyzed using PIXE/PIGE and XRF; i.e.,below 25% for the fine fraction and below 50% for thecoarse fraction.

RCM was again calculated using Eqs. (1) and (13), re-spectively, for all 3 analytical techniques and both size frac-tions at the Nilore site. The results obtained are plotted inFigs. 6a and 6b. Once again RCM calculated using Eq. 13is greater than when Eq. (1) is used. Moreover when NAAis used as an analytical technique the fine and coarse %RCM do not exceed 25 and 31% of their respective PMmasses. Therefore more than 75 and 69% of the respectivePM2.5 and PM2.5–10 masses remain un-apportioned whenthese calculations are performed. In the case of the sam-ples analyzed using PIXE/PIGE and XRF the fine andcoarse % RCM do not exceed 83 and 77% of their respectivePM masses with the missing or mass un-apportioned beingaround 17 and 23%, respectively. Once again the missingmass may be organics or nitrates which are not measuredby any of the techniques used.

Comparison of Nilore and AHS sites

Samples were simultaneously collected at the Nilore andAHS sites in 2004. These samples were all analyzed usingPIXE/PIGE. The sources for the overlapping time periodwere also estimated and RCM calculated. The results ob-tained at the Nilore site are plotted in Figure 7 while thesame plot for AHS has been presented earlier in Fig. 1a. The% Smoke component at both sites has comparable magni-tudes while the % BC differs slightly with the amounts of

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Table 6. Comparison of % RCM obtained using Eqs. 1 and 13for the Nilore samples collected in 2004 and for the AHS site.

Nilore AHS

Parameter Fine Coarse Fine Coarse

% RCM (Eq. (1)) 77.66 58.51 79.26 49.72% RCM (Eq. (13)) 87.11 64.34 85.26 52.22

this source higher at the AHS site due to the higher volumeof traffic in this area. % Soil and % Sulfate componentsdiffer at both sites.

There is more coarse soil at Nilore as compared to theAHS sites where the fine and coarse % Soil componentsare similar in magnitude due to road dust. The % Sulfatecomponent of coarse particles at both sites is comparable,while in the fine component it is slightly higher at the Niloresite. This may be due to the existence of numerous brickkilns utilizing coal with high sulfur content in the vicinityof this site.[1] The % Seasalt is higher at the Nilore sitewhich may be due to prevalent wind conditions or due tothe smaller PM masses collected at this site which are givinghigher percentages of this component.

The crustal components of particulate matter samplescollected at Nilore in 2004 are plotted in Fig. 8, while thesame species have been presented earlier for the AHS sitein Fig. 2a. These plots are similar to plots obtained forFigs. 2a–d and 5a–d as the % Crustal Material and % Soilcomponents estimated using the amount of Si instead of Al,i.e., using Eq. (20) instead of Eq. (2), gives slightly highervalues of % Crustal Material and % Soil. Moreover it canbe seen that the amounts of all three soil components incoarse soil are almost 20% higher than the amounts in finesoil at the Nilore site, while at the AHS site their amountsare comparable and the fine components are slightly lessthan the coarse components.

The RCM obtained using Eqs. (1) and (13) are given inTable 4 for the fine and coarse samples collected in 2004at the Nilore and the AHS sites. From this table it can beseen that use of Eq. (13) gives higher values of % RCM.Moreover the use of 5–6 pseudo-sources can be used toapportion more than 75% and around 50% of the respectivefine and coarse particulate masses.

Conclusions

From the preceding simple analysis, it can be seen that theselection of analytical technique is vital in any air moni-toring study. If the analytical technique does not measureimportant major elements then the data will not be repre-sentative of the sample composition. This data then cannotbe used in models to carry out further source apportion-ment studies or perform transboundary analysis.[28]

Therefore even though NAA is a very sensitive technique,it should not be used on its own for the speciation of air

particulate matter. PIXE/PIGE and XRF techniques canprovide elemental compositional data, especially for fineparticulate samples, for most of the major environmen-tally important elements. Hence the data obtained eitherby PIXE/PIGE or XRF can be directly used along withthe gravimetric and BC results to carry out source appor-tionment studies. This study also shows that RCM shouldbe calculated as a quality assurance measure before anysoftware such as Positive Matrix Factorization (PMF) orchemometrical tools such as Factors Analysis (FA) andCluster Analysis (CA) are applied and those samples forwhich RCM greatly exceeds or underestimates the gravi-metric mass are excluded from further analysis.

Acknowledgments

The lead author would like to thank the IAEA for pro-viding analytical services for the analysis of air particulatesamples and a 2-month Fellowship at the Institute of Ge-ological and Nuclear Sciences Limited, Lower Hutt, NewZealand. The lead author would also like to thank theHigher Education Commission of Pakistan for the awardof postdoctoral fellowship at Clarkson University, Pots-dam, NY, USA, where the XRF analysis was performedunder the supervision of Professor P.K. Hopke. The au-thors are grateful for the technical assistance provided byMr. Lal Habib and acknowledge the Reactor OperationGroup at PINSTECH for the neutron irradiation of thesamples.

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Source apportionment using reconstructed mass calculations

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