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Atmospheric Environment 91 (2014) 85e94

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Atmospheric Environment

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Chemical characteristics and source apportionment of PM10 duringAsian dust storm and non-dust storm days in Beijing

Qingyang Liu a,b,*, Yanju Liu a,c,*, Jianxin Yin d, Meigen Zhang e, Tingting Zhang a

aBeijing Center for Physical and Chemical Analysis, Beijing 100089, ChinabCollege of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, ChinacBeijing Milu Ecological Research Center, Beijing 100076, ChinadDivision of Environmental Health and Risk Management, School of Geography, Earth and Environmental Sciences, The University of Birmingham,Edgbaston, Birmingham B15 2TT, United Kingdome State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences,Beijing 100029, China

h i g h l i g h t s

� Two dust storm events were monitored on March 28th and April 28th, 2012.� The PMF model was used to calculate soil contribution to PM10.� Higher lead isotopic ratios in PM10 were observed in the DS days.� The dry lakebed region may serve as a dust transport pathway for the two DS events.

a r t i c l e i n f o

Article history:Received 29 November 2013Received in revised form25 March 2014Accepted 27 March 2014Available online 27 March 2014

Keywords:Chemical characteristicsDust stormPM10

Source apportionmentLead isotopePMF model

* Corresponding authors. Beijing Center for PhysBeijing 100089, China.

E-mail addresses: liuqingyang0807@yahoo.com.cncom (Y. Liu).

http://dx.doi.org/10.1016/j.atmosenv.2014.03.0571352-2310/� 2014 Elsevier Ltd. All rights reserved.

a b s t r a c t

To study the chemical characteristics of Asian dust storm, airborne particulate matter PM10 (particleswith aerodynamic diameter smaller than 10 mm) was collected at two sites in Beijing from March to May2012. Water soluble ions, metals, organic carbon and elemental carbon were analyzed. Two dust storm(DS) samples were also collected during the sampling period on March 28th (DS1) and April 28th (DS2).Backward trajectory results showed that both events were originated from Inner Mongolia and Mongolia.A receptor model, positive matrix factorization (PMF) was applied to calculate the soil emission differ-ences between DS and non-DS days. Five emission sources were identified that contribute to PM10,including soil dust, vehicular emission, industrial emission, metal processing and secondary ions. ThePMF estimated contributions of dust aerosols to PM10 were in the range of 31%e40% during DS days,which were far greater than that contribution (10%e20%) from local soil dust only during non-DS days.Furthermore, lead isotopic composition analyses in PM10 in Beijing and the soil samples from InnerMongolia Plateau and Zhangbei Plateau were conducted. Higher lead isotopic ratios (206Pb/207Pb,206Pb/208Pb) in PM10 were observed in DS days than non-DS days, and those ratio compositions werefound to be similar to those observed in the dry lakebed soil samples collected from Inner MongoliaPlateau and Zhangbei Plateau, which indicate that the dry lakebed region served as a dust transportpathway of those two DS events.

� 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Asian dust (Yellow sand) storms commonly originate from aridareas in China and Mongolia, where strong surface winds uplift

ical and Chemical Analysis,

(Q. Liu), liuyanju@hotmail.

mineral particles into the middle troposphere (Jayaratne et al.,2011; Shen et al., 2009). Springtime winds carry a portion of thisdust across the Chinese mainland to East Asia and North America,which increase the ambient PM10 concentrations during March,April and May (Tan et al., 2012; Wang et al., 2005, 2011). Simulatedspringtime dust emission results for the period 1960e2002 indi-cated that Asian dust mainly originated from 10 source areas in thedeserts of Mongolia, northern China, and Kazakhstan (Zhang et al.,2010b; Gallon et al., 2011; Hoffmann et al., 2008; Ho et al., 2003).

Q. Liu et al. / Atmospheric Environment 91 (2014) 85e9486

Both observations and simulations showed that the Inner MongoliaAutonomous Region (Inner Mongolia) in China is one of the mostimportant source regions for Asian dust and is responsible forapproximately 31% of the total dust production (Jayaratne et al.,2011; Li et al., 2009; Kim et al., 2008; Onishi et al., 2012; Tanet al., 2012). Observational studies have explored dust source areaof Inner Mongolia, including deserts, sandy lands of grass lands,agricultural soil, etc (Tan et al., 2012; Zhang et al., 2010a, 2010b; Xieet al., 2005).

To date, source regions responsible for long-range transporteddust have only been qualitatively identified using concentrationratios of selected major elements (e.g. Al, Fe, Ti), backward airtrajectories, satellite data and isotopes (Hoffmann et al., 2008;Ashbaugh et al., 2003; Bozlaker et al., 2013; Shen et al., 2009;Song et al., 2007). Chen et al. (2008) found that Songnen Plain,located at the eastern extension of Inner Mongolia, was a potentialsource region for Asian dust storms using carbon isotopic compo-sition in atmospheric dust carbonates. Yang et al. (2009) exploredthe northeastern Tibetan Plateau, which may serve as one of thesource regions for the atmospheric dust in Beijing in April 2006,based on SreNd isotopic results. In addition, transported dustcontributions have been calculated by comparisons of the compo-sition of samples from remote locations not impacted by localemission sources and that of locally generated materials (Zhanget al., 2010a; Cao et al., 2011). Recently, Bozlaker et al. (2013)have quantified the contribution of long range transported dustto particulate matter using the chemical mass balance receptormodel.

Lead isotopes can serve as powerful source-area fingerprints (Biet al., 2013), as they have distinct 206Pb/207Pb and 206Pb/208Pb ra-tios, depending on their geological origins (Cheng and Hu, 2010).Cheng et al. (2010) have summarized the regional characteristics oflead isotope ratios at several urban sites in Asia. Coal combustioncan be a lead source and its contribution can alter the lead isotoperatios in the atmosphere, whereas industrial emissions wereidentified asmajor sources of lead in the atmosphere in Asia (Chenget al., 2010; Mukai et al., 2001). In addition, Erel et al. (2006) hasnoticed an increasing trend of 206Pb/207Pb isotopic composition inPM during the dust storm days.

In this study, particulate matter (PM10) samples during DS andnon-DS days were collected in two urban sites in Beijing to inves-tigate their chemical characteristics, including water soluble ions,metals, lead isotopic compositions, organic carbon (OC) andelement carbon (EC). To clarify the differences of the dust contri-butions between the dust storm and non-dust storm days, positivematrix factorization (PMF) receptor model was applied to calculatethe source contribution. Based on the backward air trajectory re-sults, soil samples were collected from possible source regions,including Inner Mongolia Plateau and Zhangbei Plateau. Lead iso-topic data were also discussed in order to aid the source appor-tionment results in the sampling areas.

2. Method

2.1. Aerosol and soil sampling

The sampling site S1 (N 39�97091000, E 116�21030000) was selectedas an urban background site on the roof of an office building with aheight of 20m above groundwithin Institute of Botany, the ChineseAcademy of Sciences. The site was located at about 30 km north-west of Tian’anmen Square surrounded by unused land withnearest (about 500 m) anthropogenic pollution arising from a lighttrafficked road. The sampling site S2 was located near a busy trafficline (latitude of N 39�56050007, longitude of E 116�18010008), with thesampling equipment set up on the roof of an office building at a

height of 30 m above ground and a distance about 30 m from theheavy trafficked west 3rd ring road (Fig. S1). 24-h PM10 aerosolsamples were collected onto 90 mm diameter quartz microfiberfilters (QMA, Whatman) at sites S1 and S2 in spring 2012 (March10theMay 10th), using medium volume sampling equipment at aflow 100 L min�1. Filters were replaced daily at 10:00 a.m. Beijingtime through the whole sampling period.

Twenty-three soil samples were collected from possible sourceregions, including Inner Mongolia Plateau and Zhangbei Plateauusing stainless steel shovels. In addition, three soil sub-samplesfrom each sampling site were collected as duplicate samples. Allsoil samples were stored in airtight polyethylene bags and trans-ferred back to the laboratory. Before analysis, they were air-driedand passed through a 75 mm sieve.

2.2. PM mass concentration

PM10 mass concentration was calculated as the filter mass dif-ference before and after sampling at unit sampling volume. Filterswere heated for 4 h at 550 �C and preserved in desiccators for 24 hbefore pre-sampling weighing using a balance (CP225D, with ac-curacy of 0.01 mg, made in Sartorius, Germany), located in aweighing room controlled at a relative humidity of around 35% anda temperature of 20 � 2 �C. After sampling, all filters were equili-brated in the weighing room for at least 24 h before post weighing,and then theywere divided into quarters using stainless steel cutterfor further chemical component analysis.

2.3. Chemical analysis

A 15 cm2 cut piece of the quartz fiber filter samplewas extractedwith 20 mL de-ionized water, filtered and analyzed for major ionschloride, sulfate, nitrate, sodium, potassium, magnesium, calciumand ammonium using a Dionex model ICS-2000 ion chromatog-raphy system (Yin and Harrison, 2008; Yin et al., 2010). The sampleconcentrations were calibrated with a series of mixed standards ofknown concentration (0.01e10 mg mL�1).

One quarter of the filter samples and the soil samples weredigested with HNO3 þ H2O2 (2:0.5) by microwave assisted diges-tion (CEM Co., MARS), and diluted with Mill-Q water (18.2 MU cm,Millipore). A suite of 8 tracer elements (Al, Cu, Fe, Pb, Ni, V, Zn andMn) in the filter samples were quantified using Inductively-Coupled Plasma Mass Spectrometry (Agilent 7500a). Multiple in-ternal standard isotopes of many of the target elements wereanalyzed as part of the overall data quality assessment. Mixedmetal calibration standard solutions used for the analysis wereobtained from the National Center for Standard Materials (China),with a series of known concentrations (0.1e100 ng mL�1). Non-filter/filter and reagent blanks were also used to ensure a goodanalytical precision.

Lead isotope ratios in both filter and soil sample digests weremeasured by quadruple ICP-MS (Agilent 7500a) operated in stan-dard mode, at a dwell time of 2.5 cms and quadruple settle time of1000 ms to minimize the plasma effects. Solution of the Pb wireisotope standard NIST-981 was used to determine correction fac-tors for the detector ‘dead time’ and for mass bias (K-factors) duringanalysis. Only data measured in true pulse-counting mode wereused to determine isotopic abundances; data were rejected if thedetector ‘tripped’ to an analog signal (Cheng and Hu, 2010).

OC and ECweremeasured by DRI-2001AOC/EC Analyzer (Model2001 A, Desert Research Institute) with a detection limit of0.2 mg cm�2. A small piece of the filter (0.518 cm2) was analyzedusing the IMPROVE heating procedure (Cheng et al., 2010), with OCfractions released at the first stage under carrier gas He at tem-peratures 140e580 �C and EC fractions at the second stage in a

Q. Liu et al. / Atmospheric Environment 91 (2014) 85e94 87

helium and oxygen atmosphere at temperatures 580e840 �C. Atthe end of each sample analysis, quantitative internal standard gas(CH4) was injected into the system to calibrate the FID signals, andthe final results. The OC/EC split was determined using a lasersignal based on that the amount of carbon pyrolyzed in the firststage equals to the amount of carbon burnt off the filter in thesecond stage, which brings the laser reflectance value to its initiallevel. A repeat sample run was carried out for every 9 samples tocheck the instrument precision, for which a 10% or less is accepted;otherwise all 9 samples must be re-run. External standards, sucroseand potassium hydrogenphthalate (KHP)were used to calibrate thesystem regularly. The response deviation of the standard solutionless than 5% indicates that the instrument is stable for analyzingsamples.

Fig. 1. a) Trends in PM10 mass concentration at sites S1 and S2 in Beijing from March to Masampling period, the time interval is 24 h. Dust storm samples were highlighted by ellipse

2.4. The PMF model

PMF assumes that concentrations at receptor sites are impactedby linear combinations of source emissions, which are derived asfactors in the model. In this study, PMF was applied to PM10 massconcentration that were collected at sampling sites to identifyemission sources and quantify the contributions of these sources.We used a PMF 3.0 for the current analysis, as shown in Eq. (1):

Xij ¼Xp

k¼1

gik,fkj þ eij (1)

The data set can be expressed as a matrix X of i by j dimensions,where i is the number of samples and j is the species measured.

y 2012; b) The temporal variation of meteorological variables at the site S2 during thecircle.

Fig. 2. The variation of water soluble ions in PM10 at the sites S1 and S2 during sam-pling time in Beijing. Dust storm samples were highlighted by ellipse circle.

Q. Liu et al. / Atmospheric Environment 91 (2014) 85e9488

Additionally, gik is the concentration of chemical species, fkj is themass fraction, eij is the residual of the jth species concentrationmeasured in the ith sample, and p is the total number of the in-dependent factors. The objective of a PMF analysis is to determinethe number of factors p, the chemical composition profile fk, thefactor contributions gk, and residuals e. Concentrations (Xij) andtheir associated uncertainties were prepared according to themethod suggested by Zhang et al. (2010a). The PMF 3.0 determinessignal-to-noise ratio (S/N) statistics for each input species and al-lows the user to downgrade the importance or remove species withsmall S/N values (Liu et al., 2014). Among the species calculated, allspecies were found to have S/N levels more than 3, and wereconsidered “strong”.

2.5. Air mass back trajectories and data analysis

Air mass back trajectories were calculated using the NationalOceanic and Atmospheric Administration (NOAA)’s ARL HYSPLIT4.0 model (with meteorological data from the Global Data Assim-ilation System, GDAS). 24 h backward trajectories, starting at Bei-jing (39.97oN, 116.21oE) were calculated at 200 and 500 m levels.The statistical data analyses were carried out using the SPSS soft-ware version 13.0.

3. Results

3.1. Description of dust storm

Two dust storm (DS) events occurred during the samplingperiod on March 28th (DS1) and April 28th (DS2), which spreadover the two sampling sites S1 and S2, where we collected samples.Fig. 1a shows the total mass variations of PM10 at the two samplingsites during the entire two months interval. The total mass con-centration of PM10 on March 28th was 460 mg m�3 for S2 (PM10sample for S1 was missing), which was 1.64 and 2.16 times of thoseon March 27th before DS1 (212 mg m�3 for S2) and April 3rd afterDS1 (282 mg m�3 for S2) respectively. In contrast, DS2 was muchstronger than DS1, as the total mass concentrations of PM10 reachedas high as 755 mgm�3 for S1 and 767 mgm�3 for S2, whichwere 2.3e2.4 times of those on April 26th before DS2 (305 mg m�3 for S1,312 mg m�3 for S2) and May 4th (314 mg m�3 for S1, 324 mg m�3 forS2) after DS2. Dust events were generally characterized of coldfronts with relatively dry conditions, low relative humidity andhigh wind speed (Wang et al., 2005; Jayaratne et al., 2011). Distinctweather conditions were observed for the two DS days and non-DSdays shown in Fig. 1b. Relative humidity (RH) and temperaturedecreased abruptly when the dust storm came and then increasedagain after it passed, whilst wind speed showed an inverse trend.

To investigate atmospheric dynamics differences for the two DSevents, we examined 24-h backward trajectories for both DS eventsfor several days over the periods (Figs. S2 and S3). In case of DS1,trajectory released on March 26th, 2012 at 00:00 indicated that airmasses over the Beijing region were come from the south region ofHebei Province, with relatively slow moving motion. However, onMarch 27th and 28th, thewind shifted to northewesterly direction,with air masses traveled from Inner Mongolia to the sampling sites,influenced by cold front from Inner Mongolia cyclone and relativelyhigh wind speed and low temperature (Fig. 1b). As shown in Fig. S2,air parcels at 200m and 500m in the Beijing region originated fromhigher altitude of semi-arid region and desert areas, which led tothe occurrence of dust storms over the North China Plain, such asHebei Province, Beijing and Tianjin, following the anticycloneoutflow. Therefore, the increase of PM10 mass concentration inBeijing on 28th March 2012 is clearly associated with air massescoming from Inner Mongolia, suggesting that occasional Inner

Mongolia dust intrusions could affect the air quality of Beijing,which is in accordance with the results obtained from relatedstudies (Hoffmann et al., 2008; Wang et al., 2005; Xie et al., 2005).

Similar trajectory patterns were found for DS2 on days of 27thand 28th April, 2012 (Fig. S3), except with faster moving air masses,which traveled from both Inner Mongolia and Mongolia and thenpassed over the North China Plain before reaching the samplingsites. Moreover, almost the same trajectories were found at all twoaltitudes, indicating that the dust was driven by strong synopticwinds, as is typical for DS1. Mongolia is also a major source of PM10for Beijing, which is consistent with the results of Zhang et al.(2010b), who found that the PM10 levels in Beijing have beenfrequently affected by air masses traveled from the MongoliaPlateau. In comparison with the DS2 event, lower mass concen-trations of PM10 were observed during DS1. The differences in thePM10 levels between the two DS events might be caused mainly byweather conditions.

3.2. Chemical characteristics in PM10

3.2.1. Water soluble ionsAn increasing trend in concentrations of the chemical species in

PM10 were observed for both dust storm events, but this increasewas more marked in the case of DS2 at sites S1 and S2 (Figs. 2e4).Concentrations of Cl�, SO4

2�, NO3� and NH4

þ had similar trendsand the highest concentrations were observed on 28th March for

Fig. 3. The variation of metal species in PM10 at the sites S1 and S2 during samplingtime in Beijing. Dust storm samples were highlighted by ellipse circle.

Q. Liu et al. / Atmospheric Environment 91 (2014) 85e94 89

DS1 and 28th April for DS2, which were 2e3 times of those over thenon-DS days. There were no significant differences observed in theaverage concentration of Cl�, SO4

2�, NO3� and NH4

þ between twoDS episodes. Average concentration of Cl�, SO4

2�, NO3� and NH4

þ

showed a slight elevation at S2 site in comparison of those at S1 site,suggesting diverse emission sources between two sites. Cao et al.(2003) found that dust storm could be accompanied by anthropo-genic sources during the transport process, which results in higherconcentrations of secondary aerosol nitrate and sulfate within the

Fig. 4. The variation of OC and EC in PM10 at the sites S1 and S2 during sampling timein Beijing. Dust storm samples were highlighted by ellipse circle.

dust aerosol samples. Backward trajectory analyses in Figs. S2 andS3 revealed that air mass containing dust particles had passedover the northwest of Beijing-Hebei Province where many largeindustrial factories located. Therefore, both materials emitted fromlocal/regional anthropogenic sources and long range transportedsources fromMongolia/Inner Mongolia can contribute to the higherconcentrations of Cl�, SO4

2�, NO3� and NH4

þ during DS days.These results also concurred with many previous studies relative todust storms in Beijing (Zhuang et al., 2001; Zhang et al., 2005).

3.2.2. ElementsElements like Ca, Al, Fewhich are mainly originated from crustal

sources were found to be present in higher concentrations duringthe dust storm events, due to both long range transported dustfromMongolia/InnerMongolia and re-suspension of local road dustby higher wind speeds or moving traffic. Moreover, it has beenreported in several studies that vehicular exhaust also containssignificant amount of Ca and Fe (Schroeder et al., 1987; Schaueret al., 1996). The average concentrations of Al, Ca, Fe over DS dayswere 6.85, 17.31, 12.15 mg m�3 for S1, and 3.47, 20.68, 10.06 mg m�3

for S2, which were 1e6 times higher than the averages of 1.72,10.28, 6.70 mg m�3 for S1 and 1.32, 11.90, 10.35 mg m�3 for S2 duringnon-DS days, respectively. Unlike water soluble ions, Ca, Al, Feshowed a greater abundance at S1 site and primary associated withregional transport of soil aerosol from unused land. Ca, Al, Feshowed elevated relative concentrations during DS2 episode,consistent with mass concentration, reflecting stronger emissionsfrom dust storm. Furthermore, almost all crustal elements reachedtheir peak concentration values on 28th March for DS1 and 28thApril for DS2, which might due to re-suspension of local road dustand mixing materials containing long range transported crustalelements and other pollution species (Zhang et al., 2010b;Ashbaugh et al., 2003; Ho et al., 2003).

In Fig. 3, it is obvious that the concentrations of these crustalelements in PM10 were higher during DS2 than those during DS1,presumably due to larger contributions of the transported crustalmaterials from Mongolia/Inner Mongolia for DS2 than DS1. It hasbeen reported that the dust storm not only delivers large amountsof crustal aerosols but also carries significant quantities of tracemetal pollutants (Hoffmann et al., 2008; Shen et al., 2009; Tan et al.,2012). The highest concentrations of those pollution elements, Zn,Cu, Pb and Mn in PM10 were 3.61, 2.31, 0.43 and 0.47 mg m�3 at S1,and 3.47, 2.33, 0.18 and 0.46 mg m�3 at S2, respectively, whichoccurred on April 28th (DS2)and were 1e3 times higher than theiraverages of 1.24, 0.81, 0.10 and 0.41 mg m�3 at S1 and 2.18, 1.49, 0.15and 0.46 mg m�3 at S2 for non-DS days, respectively. Similarly, DS1(March 28th) exhibited lower levels of 2.08, 2.16, 0.08 and0.32 mgm�3 at S2 than those on April 28th (DS2), indicating that themixing between crustal and pollution aerosols were stronger overDS2 than that over DS1. In addition, previous studies have identi-fied these elements could also be elevated due to physical andchemical modification of PM10 during long transport process fromsource area (Hoffmann et al., 2008; Mukai et al., 2001).

3.2.3. Carbonaceous aerosolEC is a product of incomplete combustion of residential coal,

motor vehicle fuel and biomass, whilst OC originates from primaryanthropogenic sources and secondary formation (secondary OC) bychemical reaction in the atmosphere (Dan et al., 2004). OC levelswere considerably higher (Fig. 4) (around 3e7 times on average)than EC over the whole sampling period. Similar average concen-trations of OC (34.82 mg m�3 for S1 and 24.80 mg m�3 for S2) and EC(5.53 mg m�3 for S1 and 7.99 mg m�3 for S2) over DS days wereobserved in comparison with the averages of OC (21.72 mg m�3 forS1 and 24.39 mg m�3 for S2) and EC (6.41 mg m�3 for S1 and

Q. Liu et al. / Atmospheric Environment 91 (2014) 85e9490

7.06 mg m�3 for S2) over non-DS days, except obvious higher OClevel for the DS samples than for non-DS samples at site S1 (DS:34.82 mg m�3, non-DS: 21.72 mg m�3). Also, there are no significantdifferences observed in the average concentrations of OC and ECbetween the urban and urban background sites S2 and S1, indicatingthe importance of regional rather than local pollution source con-tributions, such as vehicular emissions in the Capital of Beijing. Inaddition, it should be noted that OC and EC concentrationsincreased rapidly during DS2 comparing with those prior and postDS days, indicating that dust storm could bring a large amount ofcarbonaceous aerosols during the long range transport process(Dan et al., 2004; Hoffmann et al., 2008). The observed concen-trations of OC and EC in Beijing were much higher than thoseobserved in other megacities in developed countries such asBelgium (OC: 4.12 mg m�3 and EC: 1.80 mg m�3), Italy (OC:5.91 mg m�3 and EC: 1.44 mg m�3) (Viana et al., 2007) and Paris (OC:5.9 mg m�3 and EC: 1.7 mg m�3) (Favez et al., 2008).

3.2.4. Lead isotopic compositionLead is unique among the toxic metals because its isotopic ratios

can be used to trace source regions and its atmospheric transportpattern in the atmosphere (Gallon et al., 2011). Stable Pb isotopesprovide a powerful tool that can be used to separate anthropogenicPb from natural Pb. Pb present in the environment has four stableisotopes: 204Pb, 206Pb, 207Pb and 208Pb. While 204Pb is non-radiogenic with a constant abundance on earth in time, 206Pb,207Pb and 208Pb were often used as fingerprint to trace sources(Cheng and Hu, 2010). Normally, natural Pb isotope signature is1.198 and 0.482 for 206Pb/207Pb and 206Pb/208Pb respectively(Sangster et al., 2000). If isotope ratios for 206Pb/207Pb and206Pb/208Pb are lower than 1.198 and 0.482 (Sangster et al., 2000), asignificant input of pollution sources, such as industrial lead fromsmelters and metal industries should be considered (Sun et al.,2011). On the other hand, higher ratios for 206Pb/207Pb and206Pb/208Pb were observed in the unpolluted natural soil (Chengand Hu, 2010).

Fig. 5 shows 206Pb/207Pb and 206Pb/208Pb ratios of our PM10aerosol samples over DS and some non-DS days, which ranged1.142e1.175 and 0.462e0.484 respectively. The 206Pb/207Pb ratiosvaried from 1.142 to 1.172 over non-DS days. Increased ratios of206Pb/207Pb and 206Pb/208Pb were observed in the PM10 samplesover DS days. Although atmospheric lead in Beijing were consid-ered to mainly originate from fuel combustion and industrialemissions, there seemed to be some other sources due to thetemporal variations of Pb isotope ratios observed, i.e. larger duringDS than non-DS days.

Fig. 5. Lead isotopic characteristics of PM10 at the sites S1 and S2 during DS and Non-DS days. All analyses were undertaken in triplicate.

4. Discussion

4.1. Source apportionment of PM10

Figs. 6 and 7 illustrate the average source profiles for the PM10mass concentration at sites S1 and S2 respectively, with daily vari-ations of the PM10 source contribution estimates presented inFigs. S4 and S5. At this stage, the tentative identification of thefactors is largely based on the distribution of element markersamong the source profile and the temporal characteristics of thesource contributions to PM10. The factors contributingmost to PM10mass concentration were interpreted as five different sources orcombinations of sources based on a qualitative comparison toemissions or source profiles reported in the literature (Huang,2010; Song et al., 2007, 2006b). Detailed discussions were shownin Supplementary Information. In the current study, the five sour-ces identified for PM10 in Beijing included dust soil, vehicle emis-sion, industrial emission, metal processing and secondary aerosol.Our results showed that vehicle emissions (25.5%), secondary ions(34.7%) and soil dust (20.3%) were themajor sources for PM10 at siteS1. In contrast, the major sources contributing to PM10 at site S2were vehicle emissions (33.8%) and secondary ions (45.7%). This isbecause that sampling site S1 is located further away from thecenter of Beijing with less immediate pollution sources and sur-rounded by uncultivated land, which is likely to generate moreemissions of soil dust, whilst sampling site S2 is located close to theurban center with heavier trafficked roads, which generate morevehicular emissions.

Vehicle emission source: The first factor with high values of EC,OC and NO3

� was thought to be associated with traffic emissions(Zhang et al., 2009; Yin et al., 2010; Song et al., 2006b). In addition,some representative markers such as Cu and Cl were also includedin this source (Lough et al., 2005). Furusjo et al. (2007) suggestedthat vehicular emissions were associated with high concentrationsof Cu, Zn and Sb. Cl is used as a chemical fingerprint for exhaust gas,whilst Cu is used for break wear. These elements suggest sourcecontributions from motor vehicles. The results of PMF analysisshowed that vehicular emissions contributed about 25.5% and33.8% to the aerosol mass PM10 on average for sites S1 and S2respectively.

Industrial emission source: Metal elements, such as Cu, Fe, Pband V were presented in high concentrations and attributed toindustrial source. Lim et al. (2010) estimated this source as an in-dustrial waste incinerator (made up of several small-sized in-cinerators) or Pb-related industries due to high percentage of Pband positive contributions of Cl, K Sb, SO4

2� and EC. Our resultsshowed that industrial emissions accounted for about 11.6% and7.3% of the PM10 at sites S1 and S2 respectively.

Secondary aerosol source: Secondary aerosols of particulatematter include nitrates and sulfates which are formed in the at-mosphere (Zhang et al., 2009; Song et al., 2006a). Source 3 in thecurrent study was observed to be composed of higher mass frac-tions of secondary nitrates (NO3

�), sulfate (SO42�) and NH4

þ asshown in Figs. 6 and 7. Source apportionment studies conducted byKim et al. (2007) in Ohio, Raman and Hopke (2007) in New Yorkand Tsai and Chen (2006) in southern Taiwan, classified source richin NO3

�, SO42� and NH4

þ as secondary aerosols. Thus, source 3herewas defined as “secondary aerosol source” and it accounted for34.7% and 45.7% of the PM10 mass for sites S1 and S2 respectively.

Metal processing source: The metal processing factor was re-ported in source apportionment results in Beijing by Wang et al.(2009) and Yu et al. (2013). This factor was rich in Fe, V and Zn,that mainly comes from local metal processing. There are manysmall courtyard and curbside metal workshops where metal pro-cessing was carried out in open space in the juncture belt between

Fig. 6. PMF factorization results for PM10 at the site S1.

Q. Liu et al. / Atmospheric Environment 91 (2014) 85e94 91

urban and rural areas of Beijing and emissions from these smallfactories might have transported to the urban areas. In addition,there were many construction plants in the central area of Beijing,where metal cutting and welding were carried out, which will alsocontribute. However, relatively low contributions were observedfrom this source representing 7.9% and 9.3% of the PM10 mass atsites S1 and S2 respectively.

Dust soil source: High compositions of crustal elementsincluding Al, Ca and Fe were observed in source 5 as shown inFigs. 6 and 7. Sources with similar chemical composition resolvedby other source apportionment studies were classified as re-suspended road dust, crystal dust or dust from construction(Lough et al., 2005). We defined source 5 as “dust soil source”,which accounted for 20.3% of the PM mass for site S1 and 3.8% forsite S2. As shown in Figs. S4 and S5, higher dust soil contributionswere observed during the DS days particularly over the DS2 period.Such temporal variations in the source contributionwere attributedto the possible influence of local dust as well as long range trans-ported dust from Inner Mongolia, representing around 31%e40% ofthe PM10 during the dust storm days, which far exceeded thecontributions (10%e20%) from local soil dust only in the non-duststorm days.

4.2. Comparison of lead isotopic composition between PM10 andsoil samples

From the PMF source apportionment results of PM10, lead wasoriginated from mixing sources, including dust soil, vehicle emis-sion, industrial emission, metal processing and secondary aerosol.In general, there were no differences in the average Pb isotope

ratios for industrial and vehicular emissions between DS days andnon-DS days, however regional differences of those ratios in soilsamples are seen in Table 1. These differences are basically attrib-utable to regional geochemical characteristics of the soil. Based onthe back trajectory data in Figs. S2 and S3, emission sources fromthe north direction, i.e. Inner Mongolia/Mongolia, seemed to havecontributed to the relatively high lead concentrations over DS days.In order to further explore the source region of dust storm in ourstudy, lead isotope ratios in the soil samples were measured andcompared with the isotopic lead results in the PM10 aerosolsamples.

Twenty-three surface soil samples were collected from InnerMongolia Plateau and Zhangbei Plateau, with locations shown inFig. S9. The 206Pb/207Pb and 206Pb/208Pb isotope ratios in sample 2collected from Zhangbei Plateau (Table S1) was much lower thanthe natural values for lead isotopes, due to possibly industrialpollution contributed to this soil sample (Mukai et al., 2001). Exceptfrom sample 2, the ratios of 206Pb/207Pb in the surface soil samplesconsiderably varied from 1.172 to 1.307, indicating distinct regionalcharacteristics of Pb sources. But they were close to the values ofsoil lead isotopes in the Indochina geochemical region (unpollutedregion) (Zhu et al., 2003), and to the Al-silicate end member sig-natures (206Pb/207Pb ¼ 1.206e1.219, 206Pb/208Pb ¼ 0.484e0.487)(Cheng and Hu, 2010), suggesting that they are not affected by coaland petrol-derived Pb sources. It is possible to distinguish long-range transported dust source contributions from Inner MongoliaPlateau and Zhangbei Plateau with the atmospheric aerosols inurban cities (from 1.135 to 1.189 for 206Pb/207Pb), based on theisotopic content differences. Fig. S10 compared Pb isotopecomposition between the soil and aerosol samples, and the DS and

Fig. 7. PMF factorization results for PM10 at the site S2.

Q. Liu et al. / Atmospheric Environment 91 (2014) 85e9492

non-DS days. The isotope ratios of 206Pb/207Pb are much lower inthe PM10 samples than that in the soil samples for non-DS days, butcloser ratios were found for DS days shown in the ellipse circle(Fig. S10). This confirmed that during the DS days some sorts of soil(samples 1, 3 and 4 in Table S1, dry lakebed soil) from Zhangbei orInner Mongolia Plateau (Fig. S1b) have been transported to ourBeijing sampling site and contributed to the higher ratios of Pbisotope, which is consistent with the backward trajectory results. In

Table 1Pb isotopic compositions of coals, aerosol samples and soils.

Pb isotopic ratios 206Pb/207Pb

Chinese coalCoal used in Shanghai 1.140e1.208Northern China coal 1.178 � 0.0218China soilNorthern geochemical region 1.153e1.175Yangtze geochemical region 1.152e1.170North China geochemical region 1.040e1.160Cathaysia geochemical region 1.180e1.203Indochina geochemical region 1.189e1.208Zhangbei Plateau and Inner Mongolia Plateau 1.145e1.244Aerosol sampleTianjing 1.160e1.170Shanghai 1.150e1.160DS samples, Beijing 1.160e1.175Non-DS samples, Beijing 1.142e1.172

a N/A: not available.

comparison, the ratios of 206Pb/208Pb are rather similar betweenthe PM10 and soil samples, although they are slightly raised duringthe DS days comparing with the non-DS days.

Pullen et al. (2011) determined and compared UePb ages onzircon crystals from Loess Plateau and those on Qaidam Basin andnorthern Tibetan Plateau, and indicated northern Tibetan Plateaucould be served as dust sources for the Chinese Loess Plateau.Simonetti et al. (2004) also found that the aerosols emitted from

206Pb/208Pb Reference

N/Aa Zheng et al., 20042.100 � 0.0298 Mukai et al., 2001

N/Aa Zhu et al., 2003N/Aa Zhu et al., 2003N/Aa Zhu et al., 2003N/Aa Zhu et al., 2003N/Aa Zhu et al., 20030.445e0.485 This study

N/Aa Cheng and Hu, 2010N/Aa Cheng and Hu, 20100.475e0.484 This study0.462e0.475 This study

Q. Liu et al. / Atmospheric Environment 91 (2014) 85e94 93

the Horne smelter (Rouyn, Québec) were dispersed onto north-eastern North America using Pb isotopic fingerprinting technology.These results from the literature and our current study suggest thatPb isotopic ratios can be used to identify sources from local emis-sions and long-range transported pollutants.

5. Conclusions

Two dust storms on March 28th and April 28th 2012 wereobserved at two Beijing sites S1 and S2, during a spring samplingperiod. PM10 concentrations were elevated during both dust stormdays but the elevation was more marked on April 28th, when thePM10 values reached 755 mg m�3 for S1 and 767 mg m�3 for S2respectively. PMF results over the entire sampling period identifiedfive factors, or sources relating to soil dust, vehicle emissions, in-dustrial emission, metal processing and secondary ions sources.Among these factors, secondary ions sources had the greatestcontribution at both sites S1 and S2, accounting for 34.7% and 45.7%of the PM10 mass respectively on average, followed by vehicularemissions (25.5% and 33.8%), industrial emissions (11.6% and 7.3%),metal processing (7.9% and 9.3%) and dust soil (20.3% and 3.8%).Remarkable impact of the Inner Mongolia dust on Beijing aerosolwas seen during DS days, with soil dust contributions to the PM10mass as high as 31%e40%, comparing with the contributions of 10e20% over non-DS days when only local sources exist. Lead isotopicratios (206Pb/207Pb, 206Pb/208Pb) in the PM10 samples increasedduring the DS days, due to long-range transported soil dust fromInner Mongolia Plateau and Zhangbei Plateau, which was demon-strated by the similar lead isotope ratios found between the PM10samples and the dry lakebed soil samples. We believe that this isthe first report to identify sandy land of dry lakebed in InnerMongolia Plateau and Zhangbei Plateau as a pathway of Asian dusttransportation, which is also supported by the air mass back tra-jectory results.

Acknowledgments

Financial supports for this work have been provided by theNational Natural Science Foundation of China (No. 41175104,41305110), Beijing Natural Science Foundation (No. 8142017,8144044), the Earmaked Fund of State Key Laboratory of Atmo-spheric Boundary Layer Physics and Atmospheric Chemistry, CAS(LAPC-KF-2013-01) and “Young Talent Program of Beijing Academyof Sciences and Technology (201301)”. We would like to thank tworeviewers for their valuable comments and suggestions.

Appendix A. Supplementary data

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.atmosenv.2014.03.057.

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