Comprehensive Characterization of Aerosols

Comprehensive characterization of PM2.5 aerosols in Singapore

R. Balasubramanian and W.-B. QianDepartment of Chemical and Environmental Engineering, National University of Singapore, Singapore

S. Decesari, M. C. Facchini, and S. FuzziIstituto di Scienze dell’Atmosfera e del Clima-Consiglio Nazionale delle Ricerche, CNR, Bologna, Italy

Received 8 May 2002; revised 10 March 2003; accepted 30 May 2003; published 29 August 2003.

[1] A comprehensive characterization of PM2.5 aerosols collected in Singapore fromJanuary through December 2000 is presented. The annual average mass concentrationof PM2.5 was 27.2 mg/m3. The atmospheric loading of PM2.5 was elevated sporadicallyfrom March through May, mainly due to advection of biomass burning (deliberate fires toclear plantation areas) impacted air masses from Sumatra, Indonesia. Satellite images ofthe area, trajectory calculations, and surface wind direction data are in support of thetransport of pyrogenic products from Sumatra toward Singapore. Aerosol samplescollected during the dry season were analyzed for water-soluble ions, water-solubleorganic compounds (WSOC), elemental carbon (EC), organic carbon, and trace elementsusing a number of analytical techniques. The major components were sulfate, EC, water-soluble carbonaceous materials, and water-insoluble carbonaceous materials. AerosolWSOC were characterized based on a combination of chromatographic separations by ionexchange chromatography, functional group investigation by proton nuclear magneticresonance, and total organic carbon determination. The comprehensive chemicalcharacterization of PM2.5 particles revealed that both non-sea-salt sufate (nss-SO4

2�) andcarbonaceous aerosols mainly contributed to the increase in the mass concentration ofaerosols during the smoke haze period. Using a mass closure test (a mass balance), wedetermined whether the physical measurement of gravimetric fine PM concentration of asample is equal to the summed concentrations of the individually identified chemicalconstituents (measured or inferred) in the sample. The sum of the determined groups ofaerosol components and the gravimetrically determined mass agreed reasonably well.Principal component analysis was performed from the combined data set, and five factorswere observed: a soil dust component, a metallurgical industry factor, a factor representingemissions from biomass burning and automobiles, a sea-salt component, and an oilcombustion factor. INDEX TERMS: 0305 Atmospheric Composition and Structure: Aerosols and

particles (0345, 4801); 0320 Atmospheric Composition and Structure: Cloud physics and chemistry; 0345

Atmospheric Composition and Structure: Pollution—urban and regional (0305); 0365 Atmospheric

Composition and Structure: Troposphere—composition and chemistry; 0394 Atmospheric Composition and

Structure: Instruments and techniques; KEYWORDS: aerosols, biomass burning, atmospheric particulate matter

Citation: Balasubramanian, R., W.-B. Qian, S. Decesari, M. C. Facchini, and S. Fuzzi, Comprehensive characterization of PM2.5

aerosols in Singapore, J. Geophys. Res., 108(D16), 4523, doi:10.1029/2002JD002517, 2003.

1. Introduction

[2] Air pollution in Southeast Asia is a subject of interestfrom both regulatory and scientific perspectives sinceregional emissions are growing rapidly as a result of increas-ing population, expanding economies, and urbanization.Regional air pollution problems such as reduced visibilityand acid deposition are already apparent in the region. Forexample, results from comprehensive field studies and air-borne measurements have clearly indicated the impacts of thegaseous and particulate emissions from the forest fires inIndonesia on the regional air quality of Southeast Asia during

1997–1998 [Tsutsumi et al., 1999; Fujiwara et al., 1999;Hoyningen-Huene et al., 1999; Balasubramanian et al.,1999; Balasubramanian, 2001; Radojevic and Hassan,1999; Muraleedharan et al., 2000]. Satellite images showedthat the regional haze was spread over Borneo and Sumatra,Malaysia, Singapore, Brunei, the Philippines, and Thailand[Wooster et al., 1998; Fang and Huang, 1998]. Partially dueto the recurring regional haze episodes resulting from bio-mass fires, there has been an increase in the number of airquality monitoring stations in the region.[3] The existing routine analyses, for example, those that

support current air quality standards in the region, requireonly the determination of gaseous criteria pollutants and themass concentration of suspended particles less than 10 mm

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 108, NO. D16, 4523, doi:10.1029/2002JD002517, 2003

Copyright 2003 by the American Geophysical Union.0148-0227/03/2002JD002517

AAC 7 - 1

in aerodynamic diameter (PM10). Airborne particulate mat-ter is unique among air contaminants because of its potentialcomplexity in terms of both chemical composition andphysical properties. In order to understand the effects ofatmospheric aerosols on human health and climate, it isimportant to know their detailed chemical composition. Anumber of studies on atmospheric aerosol compositions inSoutheast Asia have been reported, but most of these studieswere focused on measuring specific aerosol components inbiomass burning impacted air masses over a limited periodof time [Gras et al., 1999; Okada et al., 2001; Ikegami etal., 2001; Muraleedharan et al., 2000; Nakajima et al.,1999; Jensen et al., 1999; Takeuchi et al., 1998]. Compre-hensive characterization of atmospheric aerosols has notbeen conducted yet despite concerns over human health andregional climate change.[4] Atmospheric aerosols are an aerodispersed system of

solid and liquid particles with different sizes, shapes, andchemical composition and are released from several emissionsources [Raes et al., 2000]. In addition, they are alsoproduced directly in the atmosphere by several physico-chemical mechanisms, and during their residency there, theyundergo several further physical, physiochemical, and chem-ical processes. The resulting product is a polydispersedsystem of chemically heterogeneous particles with complextoxic and carcinogenic potential. Therefore more complex,extended, and improved particulate analyses are required toget better and more precise information about the chemistryof atmospheric aerosols, especially those of anthropogenicorigin. The most important particle size fraction fromhuman health and climate change standpoints is the PM2.5

mode. The trend demonstrating the importance of the finefraction of atmospheric aerosol particles is continuing inseveral recently published epidemiological [e.g., Pope et al.,1995; Reichhardt, 1995; Schwartz et al., 1996] as well asmeasurement studies [e.g., Heintzenberg, 1989; Chow et al.,1996; Gray and Cass, 1998; Hameed et al., 2000]. Thedetermination of the chemical composition of PM2.5 helpsto estimate the impact of various pollution sources on theambient air quality.[5] To improve our knowledge on the particulate air

pollution in Southeast Asia, to address the needs for acomprehensive characterization of airborne particulate matterand their effects, and to assess human exposure to potentiallytoxic air pollutants, we carried out field-based researchstudies in Singapore and in Kalimantan (Indonesia). Theprogram involved chemical characterization of elemental,main ionic and organic composition of urban, semiurban, andrural aerosols, and source apportionment modeling calcula-tions. The main objectives of the present paper are to reportthe mass concentration of PM2.5 aerosols collected in Singa-pore on a daily basis in 2000 under a variety ofmeteorologicalconditions, the detailed chemical composition determinedusing a number of analytical techniques, and the likelysources of different chemical components in aerosols throughthe application of principal component analysis (PCA).

2. Experimental

2.1. Sampling Location and Period

[6] Aerosol sampling was conducted on a daily basis for ayear (from 1 January through 31 December 2000) at the

Atmospheric Research Station, with a 24-hour samplingtime; this site is located on the roof of one of the tallestbuildings at the National University of Singapore campus.Singapore is located at the southern tip of the MalayanPeninsula, between latitudes 1�090N and 1�290N and longi-tudes 103�360E and 104�250E, and measures 42 km fromeast to west and 23 km from north to south. The samplingsite is 67 m above the sea level and is approximately 800–1000 m away from the open sea. The air quality at thesampling site is influenced by local emissions from chem-ical industries, major power plants, and petroleum refinerieslocated in the southwest direction and also by urbanvehicular traffic. There are two main seasons, the northeastmonsoon from November through February and the south-west monsoon from July through October. These twoseasons are separated by two relatively short intermonsoonperiods with winds blowing in no fixed direction. Themonths of February and March are relatively drier.

2.2. Aerosol Collection and Gravimetric Analysis

[7] The annular denuder system (ADS, URG, Inc., USA)was used to collect the PM2.5 samples (particulate matterwith a diameter less than or equal to 2.5 mm) at 25�C. Thissampler is designed to collect pollutants in both the gas andparticulate phase simultaneously. However, only particulatesamples were collected and analyzed in the project. Theparticulate sampling device consists of a Teflon-coatedaluminum cyclone, three annular denuder tubes, and atwo-stage filter assembly. The denuders, coated with anappropriate chemical sink, were used in series to prevent theformation of positive artifacts from both acidic and basicgases in ambient air. The first denuder was coated withNaCl-methanol solution to remove HNO3, the second onewas coated with Na2CO3 to remove SO2 and HONO, andthe last one was coated with citric acid to remove NH3. TheTeflon-coated aluminum cyclone is designed to removecoarse particles (d > 2.5 mm) from the air stream andallow the passage of fine particles (PM2.5) at an airflow rateof 10 L/min. The filter pack at the downstream end of thedenuder tubes consists of a Teflon filter or a precombustedquartz filter with 47 mm diameter for the collection ofPM2.5. At the downstream end of the filter pack, a nylasorbfilter was used to capture HNO3 resulting from the disso-ciation of NH4NO3 particles on the Teflon filter. The NO3

�

mass measured on the nylon back-up filter was thereforeused to correct NH4

+ and NO3� measured on the Teflon filter.

Fifty-four quartz filter samples were collected in this studyfrom March through May using an additional ADS, togetherwith routine PM2.5 sampling on Teflon filters.[8] Sampling of carbonaceous particulate matter is sub-

ject to various artifacts. Positive sampling artifacts canarise from the trapping of gas phase carbonaceous mole-cules on quartz filters, while negative sampling artifactscan result from the volatilization of semivolatile particulatespecies from the filters. The significance of both positiveand negative artifacts depends on the amount of semi-volatile components and is therefore also dependent onseason and location. No attempt was made to correct forthese artifacts, however, since the information to do so wasnot available.[9] The total air volume through the sampling system was

measured during each 24-hour sampling period using a dry

AAC 7 - 2 BALASUBRAMANIAN ET AL.: CHARACTERIZATION OF PM2.5 IN SINGAPORE

gas meter (URG, Inc.). All filters used in this study wereinspected for defects under bright illumination. The filterswere weighed before and after the sampling using a micro-balance (Sartorius, Model MC 3, maintained at a relativehumidity of 42.0 ± 3.0%) with 1-mg sensitivity to obtain theparticulate mass. The microbalance was calibrated with aprimary standard traceable to NIST mass standards at thebeginning of each weighing session. The filters werepreequilibrated in a temperature (22.0� ± 0.5�C) and relativehumidity (45.0 ± 3.0%) controlled environment for at least24 hours before the actual weighing. Field blanks andlaboratory blanks were also weighed for quality assurancepurposes. Mass concentrations of PM2.5 were calculated bysubtracting the precollection weight from postcollectionweight and dividing by the volume of air that was pulledthrough the filter over the sampling period. After gravimet-ric analysis was made, the sample was transferred to anindividual sample container (petrislides) and stored at 4�Cuntil extraction and subsequent analysis to prevent the lossof semivolatile species, particularly ammonium nitrate andorganic carbon (OC). Unexposed blank filters were treatedidentically.

2.3. Chemical Analysis

2.3.1. Analysis of Water-Soluble Ions andTrace Elements[10] The Teflon filter samples were cut into two halves.

One half of the filter was wetted by approximately 0.25 mLof isopropanol and then extracted with 25 mL of deionizedwater (resistivity > 18.2 M��cm) in ultrasonic bath (Ultra-sonik, ITS Science & Medical Pte Ltd) maintained at 60�Cfor 2 hours. The pH of the extraction solution was measuredwith a pH meter (Model 25, Denver Instrument). Thesolution was then filtered through special Whatman Auto-vial filter with 0.45 mm polytetrafluoroethylene (PTFE)membrane filter. Anions were separated and quantified witha Metrohm AG ion chromatograph (IC), equipped with a733 IC analytical separation system (and the correspondingguard column), a 732 IC detector, and a 750 auto sampler. Acombination of two eluents (1.3 mM Na2CO3 and 2.0 mMNaHCO3) was used with a flow rate of 0.8 ml/min. In orderto analyze organic acids in aerosols, a special analyticalcolumn (Shodex IC IJ-424L column) from Metrohm Singa-pore Pte Ltd was employed. This column is speciallydesigned for the separation of inorganic anions such aschloride, nitrite, bromide, nitrate, phosphate, and sulfate,and also organic anions such as formate, malonate, andoxalate by suppressed IC. The analysis procedure was thesame as above, except that the separation column and theeluent were different (2.5 mM Na2CO3, 0.8 ml/min flowrate).[11] Cations were separated and quantified on the same

IC isocratically with Metrosep 1–2, 6.1010.000 separationand guard column, and a combination of two eluents (4 mMtartaric acid and 1 mM dipicolinic acid, 1.0 ml/min flowrate). Sodium, potassium, ammonium, magnesium, andcalcium were determined.[12] The other half of the Teflon filter was treated in a

closed Teflon (PTFE) vessel with 3 mL of concentratedultrapure HNO3 at 130�C on a hot plate until the finalvolume was roughly 1 mL and was further treated byadding 2 mL HNO3. The sample was then heated to

complete dryness by evaporating the acid. This digestionprocedure was repeated twice. The dry residue was dis-solved in 20 mL of 10% ultrapure HNO3. The clearsolution was filtered through a 0.45 mm PTFE autovialand was subjected to elemental analysis of 18 elements(Al, Ag, Ba, Cd, Cr, Co, Cu, Fe, Ga, Li, Mn, Ni, Pb, Sr,Zn, V, Si, and Ti) with an inductively coupled plasma-mass spectrometer (ICP-MS, Model ELAN 6100, PerkinElmer, USA), equipped with a standard pneumatic nebu-lizer and an automatic sampler AS 90. The instrumentalsettings used for the analysis were similar to thoserecommended by the manufacturer.2.3.2. Analysis of Elemental and Organic Carbon[13] The total carbon (TC) present in atmospheric par-

ticles can be expressed as the sum of OC, elemental carbon(EC), and ionic carbon (IC):

TC ¼ OCþ ECþ IC:

The terms ‘‘elemental carbon,’’ ‘‘soot,’’ ‘‘black carbon,’’and ‘‘light-absorbing carbon’’ in suspended particles areused loosely and often interchangeably by air quality,atmospheric, health, and industrial researchers. AtmosphericEC particles are commonly considered to be the product ofincomplete combustion of carbon-containing fuels in anoxygen-starved environment.[14] The contribution of IC to atmospheric aerosol mass

is usually <5%, at least for samples collected in urban areas[Mueller et al., 1972; Appel et al., 1983]. TC analyzersfrequently include instrumentation and techniques for de-termining IC by sample acidification and subsequent quan-tification of the evolved CO2.[15] For carbon analysis in this project, PM2.5 sam-

ples collected on precombusted quartz filters (500�C for4 hours) were used. All the carbonaceous filter sampleswere cut into two equal halves, one for carbon analysisand another one for water-soluble carbon analysis. Differ-ent forms of carbon (TC, EC, IC, and OC) were analyzedwith the elemental CHN 2400 analyzer on two or morecircular spots of the filter of 0.2–0.5 cm2, according to theprocedure detailed by Zappoli et al. [1999]. Briefly, theamount of TC was determined following the multipointcalibration of the elemental analyzer with acetanilide as areference standard. Each calibration curve had at least sixpoints, and the instrument background value was measuredafter analyzing each standard. After removal of inorganiccarbon (IC) with acidification of the filter spots with 1 MHCl, the amount of carbon was determined using the sametechnique as before and then subtracted from that of TC.The resultant mass of carbon is due to both EC and OC(TC � total inorganic carbon (TIC)). To determine theamount of EC, the filter spots were placed in a Carboliteoven at 350�C for 24 hours after acidification to removeboth IC and organic compounds (OC) and were subse-quently processed in the CHN analyzer to determine theamount of low volatile carbon (EC). The amount oforganic carbon (OC) was determined by the difference[TC � TIC � EC].[16] Although there was no absolute standard available to

assess the accuracy of carbon measurement, the resultsobtained were highly reproducible. The detection limits ofTC, EC, and OC were 0.03, 0.03, and 0.06 mg/m3. It is

BALASUBRAMANIAN ET AL.: CHARACTERIZATION OF PM2.5 IN SINGAPORE AAC 7 - 3

important to note that since analytical standards for atmo-spheric elemental carbon particles do not presently exist, thedistinction between EC and OC on the basis of thermalanalysis is rather arbitrary. This distinction should beconsidered more an operational definition (low-temperaturecarbon versus high-temperature carbon) than a real chemicalseparation [Tanner et al., 1982; Cachier et al., 1989].2.3.3. Analysis of Water-Soluble Organic Carbon[17] The other half of the quartz filters was extracted with

approximately 20 mL of ultrapure deionized water bysonication. The extract was filtered through a special What-man membrane filter, and the filtrate was subsequentlyanalyzed for water-soluble organic carbon (WSOC) usingthe TOC 5000 (Shimadzu) analyzer. The TC and inor-ganic carbon (IC) standards were prepared with reagentgrade potassium hydrogen phthalate and reagent gradesodium hydrogen carbonate, respectively, in differentconcentrations (0.5, 1, 2.5, and 5 mg/L). The turbidityof the extract measured with a turbidimeter (Model 2100 P,Hach Company, USA) was almost zero, indicating thatthere was no suspended particulate carbon in the extract.This validates the current technique for measurement ofWSOC in PM2.5.

2.4. WSOC Characterization Techniques

[18] Four aerosol samples collected on quartz filtersduring March 2000 were extracted for WSOC characteriza-tion according to the procedure proposed by Decesari etal. [2000], which is a combination of chromatographicseparations by ion exchange chromatography, functionalgroup investigation by proton nuclear magnetic resonance(HNMR), and total organic carbon (TOC) determination.Filter spots of 1.33 cm2 of the four samples were extractedin 5-ml Milli-Q water and the extracts were filtered through0.45-mm PTFE filters. The extracts were then analyzed fortheir total WSOC content by a TOC analyzer and were thenseparated by high performance liquid chromatography(HPLC) into three fractions: (1) neutral compounds,(2) mono- and di-carboxylic acids, and (3) polycarboxylicacids. About 8 cm2 of one filter (14 March sample) wasextracted following the same procedure described aboveand provided a sufficient amount of dissolved carbon forchromatographic separation at a preparative scale. The threeseparated fractions were then analyzed by both HPLC andTOC to determine the HPLC-specific response factors foreach fraction. This calibration was then applied to thechromatograms of the four samples to convert peak areasof the three fractions into the corresponding carbon con-centrations [Decesari et al., 2001]. The remaining portions(ca. 8 cm2) of filters sampled on 15, 19, and 20 March wereextracted with deuterated water and analyzed by HNMRspectroscopy. Spectra of the extracts were obtained in a5 mm probe using a Varian Mercury 400 spectrometer.Details on the experimental conditions for HNMR analysisare given by Decesari et al. [2000].

2.5. nss-SO42��, nss-K+++, and nss-Ca2+++

[19] The concentrations of non-sea-salt sulfate (nss-SO4

2�), non-sea-salt K+ (nss-K+), and non-sea-salt Ca2+

(nss-Ca2+) were calculated by the following equations andby assuming that the chemical composition of sea-saltparticles is the same as that of seawater, and that the soluble

Na+ in particulate samples comes solely from sea salts[Kennish, 1994]:

nss� SO2�4 ¼ SO2�

4

� �� NAþ½ �0:2516;

nss� Kþ ¼ Kþ½ � � Naþ½ �0:037;nss� Ca2þ ¼ Ca2þ

� �� Naþ½ �0:0385:

2.6. Quality Assurance Measurements

[20] For all chemical measurements, five standard solu-tions and three blank samples were used for calibration.While analyzing a large number of samples, for every10 aerosol samples, two standards (high and low concen-trations) and one blank sample were measured for checkingthe validity of calibration results. For the water-soluble ionsmeasured, the ionic balance, �+/��, was calculated to be0.96 ± 0.11, suggesting that most of the ionic species weremeasured. As a check on the quality of the IC data, S in25 filter samples was measured by particle-induced X-rayemission (PIXE) and compared to the SO4

2� from IC. Theaverage ratio of measured S to SO4

2� was 0.29 (the ratio ofmolecular weight is 0.33) with a correlation coefficient of0.94. Thus the agreement between the two techniques isvery good. For the carbon analysis with the CHN analyzer, astandard (acetanilide) was combusted for every five samplesto check accuracy of the analysis. In the case of traceelement analysis, both graphite furnace atomic absorptionspectrometry (GF-AAS) and ICP-MS were used for analyz-ing selected trace elements in some randomly selectedaerosol samples; the results were in good agreement(slope = 0.95; correlation coefficient = 0.96).

2.7. Uncertainty Analysis

[21] Gravimetric mass concentrations of PM2.5 weredetermined during intensive aerosol sampling using twoparallel URG (ADS) samplers. The difference in massbetween the two samplers (sampling and weighing uncer-tainties) was between +6 and �5%. Uncertainties in theairflow rate are ±3% and would affect the cyclone 50%cutoff diameter by ±0.05 mm. Field blanks were taken, andthe blank variability was ±5%. It was assumed that all theseerrors were random (and normally distributed) so thatuncertainties were propagated as a quadratic sum of allerrors involved. Including the (1) weighing precision, (2) theblank variability, and (3) the uncertainty in the sampled airvolume, the overall relative uncertainty of the aerosolgravimetric mass concentration (mGM) for the averagesample was ±8%. There are possible sources of systematicerrors that have not been quantified. These include positiveorganic aerosol artifacts due to vapor adsorption and/ornegative organic aerosol artifacts due to volatilization oforganics. Whenever uncertainties are presented throughoutthis paper, they reflect ±1s confidence intervals.[22] The chemical analysis of ions and trace elements was

both precise and accurate within a few percent based onintercomparisons of analytical methods. Furthermore, theion balance is one measure of the uncertainty of the ionanalysis. The mean of the absolute value of the ion balancewas 4%, which should be the magnitude in the uncertaintyof the chemical analysis, independent of the absolute massloading. Neither anions nor cations were systematicallymore abundant; this suggests that no significant ionic


components were missed. The uncertainty in the determi-nation of the trace elements is estimated to be comparable tothe value for the ionic species, i.e., ±4%.[23] For organic carbon (OC) and EC the average precision

of themeasurements based on repeated analysis of calibrationstandards were ±6 and ±5%, respectively. The divisionbetween volatile (organic) and nonvolatile (elemental) car-bon seems to depend strongly on the method used. However,this has no influence on the TC amount and only slightinfluence on the mass of carbonaceous material. The amountsof organic matter and soil dust were estimated based onappropriate conversion factors (discussed in a later section).The uncertainty in the molecular-to-carbon ratio cannot beaccurately determined without comprehensive speciation ofthe organic carbon component. The range we have used islarge and encompasses the values recently used in literature.Assuming that uncertainties were propagated as a quadraticsum of all errors involved, the overall relative uncertainty inthe determination of aerosol mass concentration based onchemical analysis (mCA) for the average sample was ±10%.

2.8. Additional Measurements

[24] Meteorological parameters such as temperature, solarradiation, relative humidity, rainfall intensity, wind speed,and wind direction were measured at the sampling site usingthe Solus2 meteorological system (Texas Electronics) in-stalled on the roof of the research station. Three dimensional(3-D) air mass back trajectories were calculated using theHybrid Single-Particle Lagrangian Integrated Trajectory(HY-SPLIT 4) model, 1997 (http://www.arl.noaa.gov/ready/hysplit4.html) which is based on the National Centersfor Environmental Prediction (NCEP) wind fields.

3. Results and Discussion

3.1. General Results

[25] Figure 1 presents mass concentrations of PM2.5

determined daily from January through December 2000 in

the form of a frequency distribution. The detection limit forgravimetric measurements was �15.0 mg (1.0 mg/m3),expressed as 3 times the standard deviation of the fieldblank. About 30% of the PM2.5 samples had mass concen-trations exceeding 30 mg/m3. The highest 24-hour averagemass concentration was 69.0 mg/m3, which occurred duringMay 2000. As can be seen from Figure 2, elevated massconcentrations of PM2.5 were observed during March, May,and November, which exceeded the proposed 24-hourUSEPA PM2.5 standard (65 mg/m3). Overall, the PM2.5 massconcentration ranged from 10 to 69.0 mg/m3 with the annualaverage of 27.2 mg/m3. Thus the annual average valueexceeds the proposed USEPA standard of 15 mg/m3, asituation in which many major cities around the world findthemselves currently.[26] There are several factors, which should be consid-

ered to account for such a high mass concentration of PM2.5

in Singapore. For example, local emissions of combustion-generated particles and/or their precursors from powerplants, oil refineries, petrochemical industry, and thoseindustrial sources involving fossil fuel combustion couldmake an important contribution to the atmospheric loadingof fine particles. In addition, the high population of motorvehicles in the island, particularly diesel vehicles, can alsocontribute significantly to the mass concentration of PM2.5.The sporadic forest fires in the neighboring provinces ofIndonesia (Sumatra and Kalimantan), especially during dryseasons, have a large impact on the regional air quality, asdemonstrated by a number of studies in recent years[Balasubramanian et al., 1999; Radojevic and Hassan,1999; Muraleedharan et al., 2000]. Furthermore, the lowwind speed within the tropical cell is not in favor ofeffectively dispersing particulate air pollution.

3.2. Impact of Biomass Burning on PM2.5 MassConcentration

[27] During the course of this project, a number ofsporadic haze episodes, characterized by elevated PM2.5

Figure 1. Frequency distribution of PM2.5 mass concentration in Singapore.


mass concentration and atmospheric visibility reduction,were experienced in Singapore due to deliberate forest firesto clear plantation areas in Indonesia (Sumatra). Following aperiod of dry weather over Sumatra toward the last week ofFebruary 2000, an increasing number of forest fires wereobserved in the Riau province in central Sumatra, which ledto smoke haze in the region in early March. Daily hot spots

monitoring showed a significant increase in hot spot countssince the beginning of March. This reached a peak of 781on 5 March over Sumatra (see Figure 3). Rainfall in mostparts of Sumatra was below average in February 2000.Conditions turned drier over central Sumatra toward the endof February and extended further into the first week ofMarch and resulted in a significant increase in forest fires

Figure 2. Time series of PM2.5 mass concentration in 2000. The arrows indicate the biomass burningperiods in Sumatra (Indonesia).

Figure 3. Fire counts derived from the global 1-km advanced very high resolution radiometer(AVHRR).


over the area. Backward air trajectory calculations using theHY-SPLIT 4 model and surface wind directions measured atthe sampling site provided further evidence for the transportof biomass burning emissions from Sumatra toward Singa-pore and Peninsular Malaysia, and the resultant haze.Backward air trajectories are shown in Figure 4 for threespecific haze episodes.[28] As we write this article, it is reported that some parts

of Sumatra are covered with thick smoke haze due to forestand ground fires, and at least 222 hot spots had been foundin the central part of Sumatra (http://www.gov.sg/metsin).As a consequence of these fires, the visibility in the affectedareas of Sumatra was reduced to as low as 30 m. However,the air quality in Singapore has not been affected this timebecause of the prevailing northeast wind direction.[29] In Singapore, the intermittent haze, caused by

biomass burning emissions, lasted from March throughMay 2000. In fact, the highest mass concentration ofPM2.5 for the year 2000 was obtained on 6 May. Satelliteimages recorded on this day clearly indicated several‘‘hot spots’’ in Sumatra (http://www.crisp.nus.edu.sg). Inaddition, the backward air trajectory calculation using theHY-SPLIT 4 revealed that the air masses sampled during thefirst week of May originated from Sumatra (see Figure 4).It should be noted that biomass burning can cause a buildup of fine particles in the atmosphere in two ways:(1) direct emission of particles into the atmosphere and(2) emission of a large amount of gaseous pollutants suchas oxides of sulfur and nitrogen and hydrocarbons, fol-lowed by production of secondary ambient aerosols byphotochemical reactions in the atmosphere. It is quitelikely that a combination of both direct emissions and in

situ secondary formation was responsible for the elevatedconcentrations of fine particles in Singapore during thehaze episodes.[30] With the onset of the southwest monsoon, the haze

ended in June 2000 and the normal air quality was restored inSingapore with the mass concentration of PM2.5 beingin range of 17–30 mg/m3 during July and August (seeFigure 2). In November, slight to moderate haze conditionsexisted occasionally in Singapore due to the recurrence offorest fires in Sumatra. The impact of haze episodes on theambient air quality in Singapore depends to a great extenton the location of hot spots and the prevailing winddirection. For example, isolated hot spots were detectedin northern part of Sumatra in July according to thesatellite images available from the Center for RemoteImaging, Sensing, and Processing (CRISP), NUS (http://www.crisp.nus.edu.sg). During this time, the air quality inMalaysia, particularly Kuala Lumpur, was seriously af-fected. However, no obvious increase in the mass con-centration was found in Singapore. Thus the massconcentrations of PM2.5 in Singapore are largely depen-dent on the quality of air masses (contaminated versusclean air masses) being received on a daily basis.

3.3. Chemical Characterization of AtmosphericAerosols

[31] One of the key questions relating to atmosphericaerosols, particularly PM2.5, is how its mass concentration isbuilt up. This information is important from both scientificand regulatory perspectives. We analyzed the PM2.5 aerosolsamples collected in Singapore during the intermittent hazeperiod (March through May 2000) with a variety of analyt-

Figure 4. Map of Southeast Asia showing the location of the hot spots (fires) in Sumatra andbackward air trajectories for three specific cases (solid triangle, 9 March; solid square, 15 March; and opencircle, 6 May).


ical equipment to provide information on chemically re-solved, or speciated, data pertaining to the PM2.5 massconcentration. Altogether, 54 PM2.5 samples were collectedand subjected to detailed chemical analyses to quantify therelative mass concentrations of water-soluble species, car-bonaceous materials, trace elements in them; 32 sampleswere collected on consecutive days, and the remaining oneswere collected for every 2 or 3 days. The recently developedmethodology for the analysis of WSOC by Decesari et al.[2000] was employed to identify different classes of organiccompounds in selected aerosol samples and functionalgroups in selected aerosol samples. The sum of the massconcentrations of the determined components was com-pared with the gravimetrically derived mass concentrations.The detailed information obtained on the chemical compo-sition of PM2.5 is presented in the following sections.Finally, possible sources of various chemical componentsin PM2.5 were identified based on PCA.[32] Table 1 presents the concentrations of all the chem-

ical components analyzed in aerosol samples collectedusing two collocated PM2.5 samplers for 32 consecutivedays to show the temporal variability in the concentration ofvarious chemical components. While the Teflon filters wereanalyzed for water-soluble ions and trace elements, precom-busted quartz filters were processed to quantify differentforms of carbonaceous materials. The mass concentration ofPM2.5 measured on a daily basis and the corresponding winddirection are also included in the table. Relatively high massconcentrations were observed when winds blew predomi-nantly from the southwest direction. This observation is

consistent with the backward air trajectories shown inFigure 4 for specific cases.

3.4. Water-Soluble Ions

[33] Changes in the concentration of individual ions(anions (nss-SO4

2�, NO3�, NO2

�, C1�) and cations (Na+, K+,Ca2+, Mg2+, NH4

+)) during the May haze episode (13 Aprilthrough 14 May) are shown in Figure 5. One of theimportant features to be noted in this figure is that whenbiomass burning impacted air masses from Sumatra werereceived, the concentrations of secondary aerosol compo-nents, particularly nss-sulfate (non-sea-salt sulfate) andammonium, increased significantly (samples 20 through27). This observation suggests that forest and peat fires inSumatra are an important source of sulfate and ammoniumin the region.[34] We made a similar observation during the 1997 haze

in the region [Balasubramanian et al., 1999]. Peat bogs inSumatra are reportedly rich in sulfur and therefore thesmoldering combustion of these materials (low-temperaturecombustion) releases both SO2 and gaseous ammonia intothe atmosphere [Gras et al., 1999]. Controlled combustionstudies in our laboratory with samples of peat collectedfrom Indonesia showed strong SO2 and NH3 emissionsunder smoldering conditions. In addition to the majorwater-soluble inorganic ions, a number of organic acids(formate, acetate, malonate, and oxalate) were also presentin the 32 aerosol samples. Among the organic acids mea-sured in this study, both oxalate and malonate were partic-ularly enriched in biomass burning air masses by a factor

Table 1. Relative Concentrations of Chemical Components in PM2.5 Aerosols (mm3)a

Sample Date PM2.5 Mass TIC WSOC WINOC EC TI TE pH Wind Direction

1 12 April 37.9 1.3 2.7 8.3 1.6 15.5 2.0 5.34 east2 13 April 55.6 1.4 3.4 7.5 2.2 22.0 1.8 5.23 south3 14 April 19.8 0.3 1.7 4.2 1.1 9.3 1.7 5.4 SW4 15 April 21.3 0.3 1.5 5.2 0.8 7.6 1.3 5.5 SW6 16 April 33.9 0.9 2.9 9.2 1.1 12.2 1.5 5.46 SE7 17 April 41.1 1.3 3.9 9.3 0.9 13.8 1.7 5.4 east8 19 April 39.6 1.2 3.9 10.9 1.1 13.4 1.5 5.38 east9 20 April 37.5 0.8 2.9 10.5 1.1 13.4 1.7 5.46 SE10 21 April 44.9 1.7 3.2 9.2 4.1 18.4 1.4 5.41 SE11 22 April 25.7 1.9 2.4 3.6 1.5 9.7 1.1 5.31 SE12 23 April 25.7 1.9 2.4 3.6 1.5 9.7 1.1 5.31 SE13 24 April 31.5 1.9 2.5 7.1 1.7 10.7 1.6 5.58 SE14 26 April 36.1 2.0 3.5 8.9 3.5 14.2 1.7 5.53 SE15 27 April 29.1 1.1 3.4 10.3 1.9 9.9 1.6 5.56 east16 28 April 28.7 0.9 2.3 9.1 3.7 10.9 1.6 5.51 SE17 29 April 16.7 0.2 1.2 5.7 1.3 7.8 0.7 5.53 south18 30 April 16.7 0.2 1.2 5.7 1.3 7.8 0.7 5.53 SW19 1 May 37.6 1.5 2.5 6.1 1.7 23.7 1.3 5.3 SW20 2 May 28.7 0.3 2.7 8.9 1.4 12.8 1.2 5.43 SW21 3 May 46.2 2.3 3.8 14.1 2.3 20.3 1.9 5.35 south22 4 May 40.3 0.2 3.3 13.0 2.9 16.1 2.2 5.28 SW23 5 May 46.1 2.2 3.3 13.2 3.3 17.6 1.6 5.25 SW24 6 May 68.9 0.8 4.8 7.9 2.8 33.8 4.0 5.05 SW25 7 May 62.4 1.5 5.1 9.2 3.6 34.0 1.6 4.98 SW26 8 May 59.1 0.3 4.9 9.5 3.9 27.7 2.8 5.09 west27 9 May 47.9 0.8 4.2 3.7 2.2 25.7 3.2 5.15 south28 10 May 32.9 1.5 4.1 5.5 1.7 11.9 1.8 5.35 south29 11 May 28.7 1.1 3.9 3.1 1.3 7.6 1.4 5.49 south30 12 May 24.2 0.6 3.5 7.1 2.8 7.2 1.3 5.47 south31 13 May 18.9 0.8 2.7 4.1 1.9 5.7 1.1 5.57 SE32 14 May 21.9 0.6 3.1 4.1 2.3 7.5 1.8 5.53 SEaTIC, total inorganic carbon; WSOC, water-soluble organic carbon; WINSOC, water-insoluble organic carbon; EC, elemental carbon; TI, total ions; TE:

total trace elements.


of 4–6, as compared to their background concentrationsin Singapore (100–150 ng/m3). This observation is consis-tent with a recent report in the literature that showedenrichment in the concentration of dicarboxylic acids inbiomass burning impacted air masses of Indonesian origin[Narakawa et al., 1999].[35] The neutralization ratio (N.R.), the ratio of the

concentration of NH4+ (in neq/m3) to the sum of the

concentrations of nss-SO42� and NO3

� (in neq/m3), wascalculated to assess the acidity of atmospheric aerosolsand is shown in Figure 6. A neutralization ratio of unitysuggests the presence of nss-sulfate and nitrate as theirammonium salts. The mass of NH4

+ in the aerosols is takento be the amount needed to neutralize the acidity, whileN.R. values lower than unity imply the likely presence ofacidic aerosols [Larson and Cass, 1989]. Neutralizationratios greater than unity probably arise from the presenceof NH4Cl [Harrison and Pio, 1983]. According to Figure 6,the average N.R. obtained in this study is 0.96, indicatingthat a substantial fraction of the acidity of aerosols wasneutralized by the ammonium. However, during the hazeepisodes, the relative increase in the sulfate (and nitrate)concentration was more than that of ammonium, as can beseen from Figure 5. As a result, the N.R. of the PM2.5

particles was typically less than 1.0, indicating the acidicnature of haze aerosols. On the other hand, when oceanic air

masses (nonhaze (maritime) aerosols) were received at thesampling site, the N.R. tended to be more than 1.0.

3.5. Carbonaceous Aerosols

[36] On an average, the different forms of carbonaceousaerosols, namely, WSOC, water-insoluble organic carbon(WINSOC), EC, and TIC accounted for about 45% of themass concentration of the fine particles in Singapore. Themost significant fraction of carbonaceous aerosols wasWINSOC, which contributed to about 60% of the totalmass of carbon. The contributions of WSOC, EC, and TICto the total mass of carbon were 25, 12, and 3%, respec-tively. The dominant contribution of carbonaceous aerosolsto the total mass of fine particles observed in this study isparticularly noteworthy.

3.6. Water-Soluble Organic Carbon

[37] HPLC analysis showed the occurrence of neutralcompounds, mono-/di-acids and polyacids in the samplescollected on 14, 15, 19, and 20 March, during the periodinfluenced by haze episodes (Figure 7). Table 2 summarizesthe measured air concentrations for the three chromato-graphic classes of WSOC, together with the total WSOCdetermined by TOC analysis. The sum of the three classesvirtually recovers 100% of the total WSOC concentrationfor the first three samples and about 78% for the last one.

Figure 5. Time series of water-soluble ions in PM2.5 during the May haze episode.


Figure 6. Concentration equivalent ratio of NH4+ to the sum of nss-SO4

2� and NO3� in PM2.5 particles.

Figure 7. HPLC chromatogram of the water extract of the sample collected on 14 March. FR1, neutral/basic compounds; FR2, mono- and di-carboxylic acids; and FR3, polyacidic organic compounds. Detailson the experimental conditions are given by Decesari et al. [2000].


Recoveries slightly higher than 100% are not significantwith respect to the accuracy of the analytical methods. Thesamples exhibit a fairly constant composition; the relativeproportions of neutral compounds, mono-/di-acids andpolyacids are 0.26 ± 0.03, 0.44 ± 0.01, and 0.30 ± 0.03,respectively. The same three classes of compounds alsooccurred in samples from other continental polluted areas,in particular at a midlatitude rural site in Europe [Decesariet al., 2001] and in a tropical area of Brazil affected bybiomass burning [Mayol-Bracero et al., 2002].[38] Figure 8 shows the WSOC HNMR spectrum of the

sample collected on 15 March. Some sharp signals are

attributable to a few individual compounds present inrelatively high concentrations. On the basis of the chem-ical shifts (dH) reported by Suzuki et al. [2001] andDecesari et al. [2001], they were identified as: trimethyl-amine (dH 2.91), methanesulfonate (dH 2.82), dimethyl-amine (dH 2.73), succinate (dH 2.42), and acetate (dH 1.92).On the other hand, the most evident feature of the spectrumis that these sharp signals account only for a minor portion ofthe total integrated area. Most of the signals remain unre-solved, appearing as a continuous distribution and suggestingthe occurrence of complex mixtures of structures. The broadunresolved bands in the HNMR spectrum could be attributedto four main categories of functional groups: H-Ar, aromaticrings; H-C-O, aliphatic alcohols and ethers; H-C-C=,aliphatic groups bound to unsaturated structures; and H-C,purely aliphatic groups. These main functional groups werealready identified in aerosol samples from polluted conti-nental sites in Europe [Decesari et al., 2001], SouthAmerica [Graham et al., 2002], and Asia [Suzuki et al.,2001]. The occurrence of these functionalities is relativelyconstant for the three analyzed samples collected in Singa-pore on 15, 19, and 20 March (Figure 9); more than 50% ofthe organic hydrogen content is carried by nonsubstituted

Table 2. Air Concentrations of Neutral Compounds, Mono-/Di-

Acids and Polyacids and Total WSOC of the Samples Analyzed by

the Liquid Chromatographya

Sampling DatesNeutral

Compounds Mono-/Di-Acids Polyacids WSOC

14 March 1.65 2.76 1.92 5.8815 March 1.72 2.98 2.27 6.8319 March 0.98 1.36 0.82 2.9920 March 1.07 2.00 1.36 5.68aAir concentrations are measured in mg C m�3.

Figure 8. HNMR spectrum of the D2O extract of sample collected on 15 March. The horizontal scale isthe chemical shift (dH) referred to the peak of the internal standard (Tspd4). Four specific spectral regionsare identified at the bottom of the spectra. H-C, purely alkylic protons; H-C-C=, protons bound toaliphatic carbon atoms adjacent to unsaturated groups, like C=C double bonds and carbonyls; H-C-O,protons bound to oxygenated aliphatic carbon atoms; and Ar-H, aromatic protons. The spectrum wasrecorded at 400 MHz by a Varian Mercury 400. Details on the experimental conditions are given byDecesari et al. [2000].


aliphatic moieties (H-C groups), the rest being accounted byhydroxylated (H-C-O) or unsaturated (H-C-C=) aliphaticgroups, whereas aromatic protons could hardly be detected.[39] This distribution of functionalities in the samples

examined differs from those reported by the above studiesat other locations. In particular, the samples from Singaporeare enriched in H-C moieties and contain less H-C-C=groups than the European samples, and also less H-C-Ounits than the South American samples. Levoglucosan wasfound to be the major single compound in the Braziliansamples [Graham et al., 2002], which were collected in anarea directly impacted by biomass burning smoke. On thecontrary, levoglucosan could hardly be detected in thesamples from Singapore. It should be pointed out thatHNMR spectroscopy is inherently less sensitive to specificcompounds compared to other analytical methods, such asGC-MS. In the case of the HNMR method, the detectionlimit for levoglucosan is estimated to be around 0.6 mg/m3.The overall differences in WSOC chemical compositionobserved between the samples from Brazil [Graham et al.,2002] and those of the present study can be attributed to localemission sources in Singapore, and possibly, gas-to-particleconversion processes occurring in the biomass plume duringits transport from Sumatra to the sampling site.[40] To summarize the WSOC composition determined

by HNMR, a carbon budget of the functional groups wasprovided following the approach suggested by Fuzzi et al.[2001]. This approach allows to convert the hydrogen molar

concentrations of the different functional groups into theircarbon content on the basis of specific derived C/H molarratios. Table 3 summarizes the H (measured) and C (de-rived) content of the functional groups present in differentsamples. Molar hydrogen concentrations were derived fromthe integrals of the spectral bands, whereas carbon concen-tration was calculated assuming C/H ratios specific for eachcategory [Fuzzi et al., 2001]. The C content of the aromaticmoieties was calculated by the difference from the TOCcontent of the samples. It is noticeable that the aromaticmoieties account for only a negligible fraction of the totalhydrogen content but up to 40% of TOC, indicating thataromatic rings are highly condensed and/or substituted.

3.7. Trace Elements

[41] All the 54 aerosol samples collected from Marchthrough May 2000 were analyzed for 18 trace elements(Al, Ag, Ba, Cd, Cr, Co, Cu, Fe, Ga, Li, Mn, Ni, Pb, Sr,Zn, V, Si, and Ti). The mean concentration for Li was foundto be the lowest at a value of 0.2 ng/m3, while that for Znshowed the highest value of 279.1 ng/m3. Based on a simplecomparison of the magnitude, the data sets can be groupedinto four categories: (1) <1 ng/m3: Ag, Ga, and Li; (2) <1–10ng/m3: Ba, Cd, Co, Sr, V, and Ti; (3) <10–100 ng/m3: Cr, Cu,Mn, Ni, and Pb; and (4) >100 ng/m3: Al, Fe, Zn, and Si.Overall, the measured trace elements typically constituteabout 5% of themass concentration of PM2.5 in the Singaporeatmosphere. The four major elements (Al, Zn, Fe, and Si)account for about 88% of the total trace element concentra-tion measured in this study. The remaining 14 trace elementsalso play an important role in atmospheric processes eventhough they constitute only about 12% of the total concen-tration. More detailed information on trace elements will bepublished elsewhere (W.-B. Qian and R. Balasubramanian,Multi-elemental characterization of fine particles in urbanair using ICP-MS, submitted to The Journal of Environ-mental Monitoring, 2002, hereinafter referred to as Qian andBalasubramanian, submitted manuscript, 2002).

3.8. Aerosol Mass Balance

[42] A fundamental and important issue in characterizingthe atmospheric aerosol is the determination of the aerosolmass concentration. In this section, we compare gravimetricmass with the sum of the concentrations of the variouscomponents inferred from chemical measurements. Thisexercise, referred to as a test for mass closure, serves astest of the mutual consistency of various observations. Massclosure, if achieved, does not necessarily imply that allcomponents of the aerosol have been identified and quan-tified. However, if closure is not achieved, the instruments,methods, and assumptions used need to be evaluated toidentify areas, which need further study. For this purpose,the relative contributions of each major class of aerosol

Figure 9. Normalized abundance of organic functionalgroups in the D2O extracts of samples analyzed by HNMR.For nomenclature see Figure 8.

Table 3. Functional Groups Air Concentrations of WSOC for the Three Samples Analyzed by HNMR

Sample

Ar H-C-O H-C-C=O H-C

mmol H m�3 mg C m�3 mmol H m�3 mg C m�3 mmol H m�3 mg C m�3 mmol H m�3 mg C m�3

15 March 0.017 0.21 (0.09–0.31)a 0.067 0.06 (0.03–0.07) 0.169 0.15 (0.10–0.26) 0.306 0.15 (0.12–0.16)19 March <d.l. 0.05 (0.00–0.11) 0.044 0.04 (0.02–0.04) 0.082 0.07 (0.05–0.13) 0.174 0.09 (0.07–0.09)20 March 0.014 0.19 (0.12–0.27) 0.061 0.06 (0.03–0.06) 0.101 0.09 (0.06–0.15) 0.271 0.14 (0.11–0.14)

aThe range of variation of carbon concentrations was estimated according to the uncertainties on the C/H values.


components was considered according to the followingequation:

Calculated mass of fine particles ¼ inorganic mass½ � þ soil½ �þ sea salt½ � þ carbonaceous matter½ �;

where

[soil] = 2.20A1 + 2.49[Si] + 1.63[Ca] +1 . 5 8 [ F e ] + 1 . 9 4 [ T i ] +1.41[K][Malm et al., 1994],

[sea salt] = 3.27[Na][Ohta and Okita, 1984],[carbonaceous matter] = OM + EC [This study; Countess

et al., 1980],where

OM = 1.8[WSOC] + 1.2[WINOC],[inorganic mass] = [SO4] + [NO3] + [NH4] + 1.79 [V] +

1.24 [Zn] + [Pb] + [Br]. (The equationgiven by Brook et al. [1997] has beenmodified.)

[43] The mass concentration of individual class of com-ponents is based on the chemical species associated with therespective sources. For example, the soil mass concentrationwas estimated by summing up the elements predominantlyassociated with soil in the form of their corresponding oxides(Al2O3, SiO2, CaO, K2O, FeO, Fe2O3, and TiO2). For theinorganic mass, the elements considered (V and Zn) werebasically from combustion sources, as evident from enrich-ment factor calculations (Qian and Balasubramanian, sub-mitted manuscript, 2002). Since the use of leaded gasolinehas been phased out in Singapore several years ago, it musthave been emitted from other combustion-related sourcessuch as waste incinerators. The concentration of Br is

utilized as an indicator of the vehicular emissions [Ali-Mohamed and Jaffar, 1999; Chueinta et al., 1999].[44] In order to convert the amount of OC into the mass

of organic matter, we have used a conversion factor of1.8 for the derivation of WSOC and 1.2 for that ofWINSOC concentrations from the corresponding carbonconcentrations. The use of the conversion factor 1.8 forWSOC is based on our HPLC and HNMR results showingthe presence of organic constituents with oxygenated,multifunctional groups. The conversion factor of 1.2 forWINSOC is realistic since such organic compounds aresaturated and contain only few oxygenated functionalgroups [Zappoli et al., 1999]. As indicated earlier, on anaverage, the WINOC and WSOC accounted for 60 and 40%of the TOC, respectively. Thus the overall conversion factorfor deriving organic matter concentrations from the mea-sured organic carbon is about 1.44.[45] Fine mass (as measured gravimetrically at relative

humidity between 42 and 48%) contains an unknowncontribution from water. According to Quinn and Coffman[1998], the fine particle water content would depend uponthe fine PM composition and relative humidity at whichfilters were weighed. These authors have shown that even at33% RH, significant amount of water can be associated withaerosol particles. However, we have not measured the totalwater content of fine particles in this study due to a lack ofreliable technology.[46] We tested for the closure between chemical and

gravimetric measurements for the PM2.5 for the 32 samplescollected on consecutive days. In general, the agreementbetween the gravimetric mass concentration and the chem-ical mass concentration is reasonably good, and a quantita-tive comparison is presented in Figure 10. High correlation

Figure 10. Comparison of the reconstructed mass concentration and the measured mass concentrationof PM2.5 in Singapore.


between fine mass and the sum of concentrations ofmeasured and inferred components (R2 = 0.9) indicates astrong consistency between chemical and gravimetric meas-urements. The slope of the regression fit is 0.88, i.e., thesum of the chemical components is less than the gravimet-rically measured fine mass.[47] We explore the factors that could be responsible for

the lack of mass closure: the fraction of the total fine particleconcentration not identified by chemical measurements(‘‘unexplained mass’’). However, as explained in section 2,the measurements of individual chemical components andthe fine mass have some errors associated with them.Therefore these errors can be used to calculate the overalluncertainty in the estimated concentration of the unidentifiedcomponent (or unexplained mass). We assume that the errorsin the measurements of the individual components and in thefine mass are independent. Using propagation of erroranalysis, the relative uncertainty of the difference betweenthe total fine PM concentration and sum of chemical com-ponents (i.e., the unidentified component) is estimated to be10%. However, the unexplained mass concentration (12%deficiency) is positive and is larger than its uncertainty(10%). Hence measurement errors alone do not explain ourobserved difference between the gravimetric mass concen-tration and the one derived from chemical measurements.Our chemical measurements did not include water, which isincluded in the gravimetric fine PM concentration measure-ment. Although water content can contribute to differencesbetween chemically and gravimetrically measured concen-tration, there may be other explanations, such as the assump-tions required to calculate the concentration of organicmatter, that contribute to a lack of closure.

3.9. Overall Chemical Composition of PM2.5

in Singapore

[48] Figure 11 gives the average contributions of all themajor chemical components in haze as well as in nonhazeaerosols in the form of a pie diagram. Over the measurementperiod (March through May), PM2.5 mass concentrationsaveraged 47.5 ± 10.2 and 20.7 ± 4.4 mg/m3 for haze andnonhaze aerosols, respectively. The major components ofaerosols in Singapore are water-insoluble carbonaceousmaterials, sulfate, water-soluble carbonaceous materials,and EC. The increase in the gravimeteric mass concentra-tion during the haze period appears to have been contributedmainly by carbonaceous aerosols and sulfate. Since nss-K+

was also enhanced during the same time period, the enrich-ment in the atmospheric loading of fine particles is attrib-uted to the transport of the biomass burning emissions.Based on this comparative speciation study, one can con-clude that the Indonesian forest fires released a lot of soot,organic materials, and sulfate into the air, which farexceeded the normal proportion created by other sourcessuch as traffic and industrial emissions in Singapore. Thefraction reported as ‘‘others’’ refers to the deficit in the sumof component concentrations.

3.10. Principal Component Analysis

[49] PCA is a technique that attempts to explain thestatistical variance in a given data set in terms of a minimumnumber of significant components. It has been widely usedfor the source apportionment of air pollutants measured at a

receptor point [e.g., Thurston and Spengler, 1985; Harrisonet al., 1997]. PCA was carried out on the PM2.5 chemicallyresolved data, collected from March through May 2000,using SPSS for Windows statistical software. The numberof samples (54) is not ideal for PCA calculations, but thedata set was checked by statistical tests provided by thesoftware package. Two tests were performed on the dataset: Kaiser-Meyer-Olkin test that measured the samplingadequacy by calculating the partial correlations amongvariables and Bartlett’s test of sphericity to find out whetherthe correlation matrix is an identity matrix, which wouldindicate the PCA model is inappropriate. The data set haspassed these statistical criteria.[50] Five factors were identified with eigen values greater

than one, which are shown in Table 4; loadings greater than0.5 are deemed to be statistically significant. The five factorstogether accounted for about 80% of the total variance in the

Figure 11. Average contribution of chemical species tothe gravimetric mass concentrations of (a) haze particles(PM2.5 = 47.5 mg/m3) and (b) nonhaze particles (PM2.5 =20.7 mg/m3).


data set. The first factor, with a high loading for crustalelements (Al, Ba, Fe,Mg, nss-Ca, Sr, Ti, Si, and), is attributedto a number of reclamation and construction activities ofinfrastructural developments in Singapore. The second factorwith a high loading for Ag, Cd. Cr, and Mn appeared to berelated to local metallurgical industry (electroplating) and/orpaint industries, painting operations associated with ship-yards, hangars, and automobiles. The third factor representedcombustion sources, as shown by the high loadings for Cu,Pb, Zn, nitrate, nss-sulfate, nss-K, ammonium, and carbona-ceous aerosols. Nss-K is a well-known tracer of biomassburning. Zn is known to be emitted from automobiles. Thusthe combustion factor includes biomass burning (forest fires),and possibly, vehicular emissions. The fourth factor wascharacteristic of sea-salt components, shown by high load-ings for Na and Cl. The last factor consisted of fuel-oilcombustion-related pollutants such as V, Ni, Co, and non-sea-salt sulfate and was related to local fuel oil fired powerplants, oil refineries, petrochemical industries, diesel-drivenvehicles, and other industrial sources involving fossil fuelcombustion. The contribution of the above pollution sourcesto the observed mass concentration of aerosols in Singaporeappears to be reasonable, considering the geographical loca-tion of Singapore and the type of human-induced activitiestaking place in and around the island.

4. Conclusions

[51] We measured the concentration of PM2.5 aerosols inSingapore from January through December 2000 and inves-

tigated their chemical composition during the dry seasonusing a number of analytical techniques. The annual averagemass concentration of fine aerosols was 27.2 mg/m3, and thetemporal variability in their concentration seemed to beinfluenced by a number of factors including changes inemission strength, wind direction, and other meteorologicalparameters. Elevated concentrations were observed duringsporadic smoke haze episodes originating from forest fires inSumatra, Indonesia, as revealed by satellite images, back-ward air trajectory calculations, and surface wind directions.This increase was mainly due to emissions/production andsubsequent transport of biomass combustion products, par-ticularly carbonaceous and sulfate-containing aerosols asevident from the comprehensive chemical characterizationand principal component analysis.[52] The main results of the investigation on the chemical

composition are:[53] (1) The major components in PM2.5 particles in

Singapore were sulfate, water-soluble carbonaceousmaterials, EC, and water-insoluble carbonaceous materials.The minor components included potassium, sodium, am-monium, nitrate, chloride, total inorganic carbon, and traceelements.[54] (2) The average neutralization ratio obtained in this

study was 0.96, indicating that a substantial fraction of theacidity of aerosols was neutralized by the ammonium.However, during the haze episodes, the relative increasein the sulfate (and nitrate) concentration was more than thatof ammonium, indicating the acidic nature of haze aerosols.[55] (3) Both nss-SO4

2� and carbonaceous aerosolsaccounted for a larger proportion of the aerosol massconcentrations determined during the smoke haze episodes,suggesting that these species and/or their precursors wereemitted in larger quantities from biomass fires compared tolocal combustion emission sources in Singapore.[56] (4) WSOC composition, determined by HPLC and

HNMR in the samples collected during the March pollutionevent, is characterized by a complex mixture of unsaturatedoxygenated compounds, including both neutral and acidicspecies. These main functional groups and chemical classeswere already identified in aerosol samples from pollutedcontinental sites in Europe, South America, and easternAsia. Compared to other areas impacted by biomass burning(Brazil), the aerosol in Singapore contained less sugarderivatives, which appear in the neutral polyhydroxylatedfraction of WSOC. The sources of WSOC determined in theSingapore aerosols can be tentatively attributed to a com-bination of local emissions and gas-to-particle conversionprocesses in biomass burning plumes originating fromSumatra.[57] In terms of aerosol mass balance, the mass of the

individual aerosol samples, constructed from the aerosoltypes (components) agreed reasonably well with the gravi-metric mass. The chemical species mass concentrationaccounted for about 88% of the gravimetrically determinedmass concentration, and this deficit is attributed to acombination of the particles water content and measurementerrors. PCAwas performed from the combined data set, andsix major sources of fine aerosols in Singapore wereidentified: soil dust, metallurgical industry, emissions frombiomass fires and local traffic, sea spray, and fuel oil-combustion processes.

Table 4. PCA of PM2.5 Speciation Dataa

Species

Components

1 2 3 4 5

Ag 0.13 0.65 0.04 0.09 �0.14Al 0.87 0.21 �0.08 �0.08 0.09Ba 0.64 0.46 �0.15 0.16 0.27Cd 0.06 0.86 �0.09 �0.10 �0.09Cl �0.08 0.01 �0.10 0.95 0.05Co 0.24 0.16 �0.03 �0.05 0.86Cr 0.11 0.87 �0.07 �0.06 �0.12Cu �0.26 0.03 0.84 �0.15 0.00EC �0.17 �0.12 0.68 0.14 0.39Fe 0.72 0.21 �0.13 �0.18 0.19Li 0.42 0.43 �0.07 �0.13 0.36Mg 0.71 0.30 0.40 0.18 0.08Mn 0.29 0.61 �0.02 �0.14 0.17Na �0.07 �0.04 0.01 0.97 0.04NH4

+ 0.35 �0.16 0.78 0.26 �0.02Ni 0.08 �0.03 �0.05 0.02 0.85NO3

� 0.30 �0.03 0.62 0.32 �0.24nss-Ca 0.63 �0.13 0.08 0.30 �0.18nss-K 0.03 0.01 0.77 0.24 0.13nss-SO4

2� 0.46 �0.05 0.76 0.19 0.61OC 0.28 �0.03 0.79 �0.06 0.44Pb �0.30 �0.09 0.86 �0.07 �0.04Si 0.93 0.21 �0.07 �0.10 0.05Sr 0.64 �0.08 0.12 �0.07 0.45Ti 0.88 0.28 �0.09 �0.09 0.10V �0.01 �0.02 �0.03 0.08 0.95Zn �0.21 �0.06 0.91 �0.05 �0.02Eigen value 7.71 4.19 3.30 2.86 1.93Percent of variance 31.5 16.1 13.7 11.0 7.4Cumulative variance 31.5 47.6 61.3 72.3 79.7

aBold values represent the elements that are grouped together under eachfactor or principal component.


[58] The results obtained from this comprehensive char-acterization of PM2.5 aerosols call for further investigationand speciation studies of aerosols of both anthropogenic andpyrogenic origins in Southeast Asia since it has a largepopulation density and sensitive ecosystems as well. Sincethe smoke haze can exacerbate the regional air quality, morecomprehensive field and speciation studies are warranted sothat effective environmental policies can be formulatedbased on the scientific knowledge of the detailed composi-tion and sources of fine aerosols.

[59] Acknowledgments. The authors are grateful to the Departmentof Chemical and Environmental Engineering, NUS for financial support ofthis research.

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��R. Balasubramanian, Department of Chemical and Environmental

Engineering, National University of Singapore, 10 Kent Ridge Crescent,119 260 Singapore. ([email protected])S. Decesari, M. C. Facchini, and S. Fuzzi, Istituto di Scienze

dell’Atmosfera e del Clima-Consiglio Nazionale delle Ricerche, CNR,Via Gobetti 101, 40129 Bologna, Italy.W.-B. Qian, Department of Chemical and Environmental Engineering,

Block E5, 4 Engineering Drive 4, National University of Singapore, 117576 Singapore.


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Comprehensive Characterization of Aerosols