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Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil
Environmental Pollution xxx (2017) 1e8
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Invited paper
Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil* Tarcísio S. Almeida a, b, c, Mirna O. SantAna a, Jersica M. Cruz a, Luciano Tormen b, d, ~ an b, e, Pericles A. Azevedo a, Carlos Alexandre B. Garcia a, Vera Lúcia A. Frescura Bascun a do Patrocínio H. Alves , Rennan G.O. Araujo a, c, e, * Jose ~o Cristova ~o, Sa ~o Cristova ~o, SE, Brazil rio de Química Analítica Ambiental, Departamento de Química, Universidade Federal de Sergipe, Campus Sa Laborato rio de Espectrometria Ato ^mica, Departamento de Química, Universidade Federal de Santa Catarina, Campus Trindade, Floriano polis, SC, Brazil Laborato c Universidade Federal da Bahia, Instituto de Química, Departamento de Química Analítica, Salvador, BA, Brazil d Universidade Federal da Fronteira Sul, Campus Laranjeira do Sul, Laranjeiras do Sul, PR, Brazil e Instituto Nacional de Ci^ encia e Tecnologia do CNPq e INCT de Energia e Ambiente, Universidade Federal da Bahia, Salvador, BA, Brazil a
b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 October 2016 Received in revised form 7 January 2017 Accepted 7 April 2017 Available online xxx
In this work, studies using samples collected in an urban area of Aracaju city, Sergipe State, Northeast, Brazil revealed that soil dust in suspension was the main source of total airborne particulate matter (TAPM), followed by vehicular pollution. The concentration profiles for Cu, Fe, Mn, Ni, V and Ti were established for the collected TAPM samples. The concentrations of SO2 and smoke were also measured all along the 42 sampling days. Through multivariate data analysis of the results a correlation between Fe, Mn, Ni and Ti in the mineral composition of the particles was established, indicating soil dust in suspension as the main source of TAPM. The concentrations of Cu and smoke were found to be related to vehicular traffic, and the second largest source of TAPM. Enrichment factors (EF) were calculated for the studied elements, and only Cu was found to be enriched. The concentrations of the elements in TAPM were evaluated using the geoaccumulation index (Igeo), and Fe, Mn, Ni, V and Ti were found to derive from natural sources, in TAPM. However, approximately 55% of the samples did not presented Cu contamination (Igeo0), and the remaining 45% presented Cu concentrations levels that indicated between low to moderate (0
Keywords: Total airborne particulate matter Atmospheric pollution PCA and HCA Enrichment factor Geoaccumulation index
1. Introduction Airborne particulate matter (APM) is a complex mixture of organic and inorganic substances of varying particle size, chemical composition and source, which can be present as solid or liquid (WHO, 2003). APM has been source of concern because of its adverse health effects, especially for urban populations (Valavanidis et al., 2006). The characteristics of this atmospheric pollutant are affected by
*
This paper has been recommended for acceptance by David Carpenter. * Corresponding author. Departamento de Química Analítica, Instituto de Química, Universidade Federal da Bahia (UFBA), 40170-115, Salvador, BA, Brazil. E-mail addresses: [email protected], [email protected] (R.G.O. Araujo).
topographic and meteorological characteristics, and by the presence of human activity. These factors have significant influences on the emission, transport and dispersion of APM (Carvalho et al., 2000; Bogo et al., 2003; Beceiro-Gonz alez et al., 1997; Pateraki et al., 2014; Taiwo et al., 2014). Epidemiological studies show that in urban areas continuous exposure to particles with a diameter smaller than 10 mm has the potential to affect human health, causing several respiratory diseases such as allergies, asthma, pulmonary emphysema and cardiopulmonary mortality (Brunekreef and Holgate, 2002; Donalson et al., 2007). et al., 2002; Dongarra The trace element concentrations in APM are related to their physicochemical characteristics, their solubility in biological fluids, their toxicity, the reactions catalysed by ions present and other effects particular to the exposure area (Voutsa and Samara, 2002).
http://dx.doi.org/10.1016/j.envpol.2017.04.018 0269-7491/© 2017 Elsevier Ltd. All rights reserved.
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018
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T.S. Almeida et al. / Environmental Pollution xxx (2017) 1e8
The elemental composition of APM is widely used to characterize lez et al., 1997). atmospheric air conditions (Beceiro-Gonza Several studies have dealt with trace metals, such as Al, Cu, Cr, Fe, K, Mn, Mg, Na, Ni, Pb, Sm, Ti and V, in APM composition collected lez et al., 1997; in urban areas (Carvalho et al., 2000; Beceiro-Gonza Balasubramanian and Qian, 2002; Queiroz et al., 2007). According to this studies the suspended material can be related to siderurgy and thermoelectric plants (Fe, Cu, Cr, Mn, Mg, Pb and Ni) (Carvalho et al., 2000); solid waste incineration and vehicular traffic (Fe, Cu, Pb, Zn) (Balasubramanian and Qian, 2002; Queiroz et al., 2007); extraction and/or limestone processing, concrete and ceramic production, as well as other types of industrial processes (Sm, Cu, As and Na) (Queiroz et al., 2007); soil dust, crustal erosion, proximity to forest, oil plants, refineries and fuel burning of oils in lez et al., 1997; boilers (Al, Fe, K, Mn, Ni, Ti and V) (Beceiro-Gonza Balasubramanian and Qian, 2002; Queiroz et al., 2007) and other matrices. Therefore, identification of the different APM emission sources is worthwhile, since airborne particles characterisation has been an advantageous method in evaluating anthropic emission levels in urban areas and assessing possible consequences of emissions on public health, flora, fauna and materials. However, reliable results for trace elements in the range of ng m3 or lower are required, which is difficult due to the extremely low concentrations in fractions of milligrams of powder collected from the air (Balasubramanian and Qian, 2002; Wu et al., 2008; Habil et al., 2013). Spectrometric techniques based on atomic absorption spectrometry (AAS) and inductively coupled plasma sources (ICP), such as optical emission spectrometry (ICP OES) and mass spectrometry (ICP-MS) are widely used for trace element determination in APM (Balasubramanian and Qian, 2002; Wu et al., 2008; Quiterio et al., 2004; Wilson et al., 2002; Carneiro et al., 1993; Ferreira et al., 2011; Araujo et al., 2011). Environmental samples are evaluated through the use of chemometric tools for multivariate data analysis, such as principal component analysis (PCA) and hierarchical cluster analysis (HCA) in order to establish relationships between the chemicals and their probable sources of emission (Hair et al., 2006). A study performed in Herceg Novi, Montenegro, PCA indicated that groups of emission sources such as soil resuspension, iron and steel processing, and ship maintenance contributed to the content of trace elements in the total APM (TAPM) (Mihajlidi-zelic and Relic, 2005). BeceiroGonz alez et al. determined Pb, Cd, Mn, V, Zn and Fe concentrations ~, Spain. PCA in TAPM collected in two different places in La Coruna was applied using the metal concentrations, and it suggested two main sources d soil resuspension and anthropic activity d but the TAPM concentration depended on the atmospheric conditions lez et al., 1997). Loyola et al. used PCA and HCA to (Beceiro-Gonza study an urban area highly impacted by vehicular traffic. The analysis suggested that the APM collected in the area was related to natural sources, soil resuspension as well as vehicular traffic (Loyola et al., 2012). To evaluate the degree of atmospheric pollution, the determined concentration of an element in TAPM can be compared with its natural concentration (background) through factors such as the geoaccumulation index (Igeo) (Müller, 1969) and the enrichment factor (EF) (Chester et al., 2000). These two factors combine information about the likely source of emission, indicating whether the element is derived from natural or non-natural sources. Loyola et al. calculated the EF for Al, Ca, Cr, Cu, Fe, Mg, Mn, V and Zn in TAPM collected in an urban area of Rio de Janeiro city. According to their study, the Zn and Cu concentrations were considered anomalous in all samples, and were likely derived from anthropic sources (Loyola et al., 2012). Yaquin et al. investigated the influence of soil dust on TAPM and PM10 (airborne particulate matter with diameter particles smaller than 10 mm) formation in 15
China's cities, where the Igeo for 17 trace elements was evaluated. The results indicated that in some of the cities TAPM and PM10 are affected by the soil dust (Ji et al., 2008). Observing the problems caused by TAPM and air pollution in general, the purpose of the present work was to study the likely sources of pollutants in an urban area located in Aracaju city, Sergipe State, Brazil. The study aimed to associate the probable natural or anthropic sources of emission via the concentrations of Cu, Fe, Mn, Ni, Ti and V present in TAPM, as well as the concentrations of SO2 and smoke measured on 42 different days. PCA, HCA, enrichment factor and geoaccumulation index were used to evaluate the obtained results. 2. Experimental 2.1. Study area Aracaju is the capital of Sergipe State, Brazil, and it covers an area of 181.8 km2 with a population of about 641,523 inhabitant (Igbe). The city is located on the coast, bathed by Atlantic Ocean, and divided by the Poxim and Sergipe rivers. Among the climatic characteristics, the city exhibits an average annual temperature of 26 C and annual rainfall of 1590 mm, the rainy season being from March to August (Aracaju). The city of Aracaju has a fleet of more than 290 thousand motor vehicles according to data from the Traffic Department of the State of Sergipe (Departamento Estadual ^nsito de Sergipe - DETRAN/SE) (Detran). de Tra Samples were collected using large and small volume samplers installed at a point located in an urban area belonging to the Environment and Water Resource Department of Sergipe (SEMARH) under the responsibility of the Environment State Adminis~o Estadual de Meio Ambiente - ADEMA), near tration (Administraça the Viaduct Carvalho Deda (Viaduto Deda Carvalho) and the Integration bus station in the Industrial District of Aracaju (Distrito Industrial de Aracaju e D.I.A.), with the geographical coordinates 24 710458E 87 89116N (UTM) (Adema). 2.2. Sampling of airborne particulate matter Forty-two TAPM samples were collected on ash-free glass fibre tica, Rio de Janeiro, Brazil) in Aracaju filters (E55, 8 10 inch, Energe city, Sergipe State, Northeast, Brazil, using a high-volume air tica, Rio de Janeiro, RJ, Brazil). The sampling period sampler (Energe was from August 2009 to October 2010. The sampling flow rate used was 1000 L min1, and the total sampling time was around 24 h (approximately from noon to noon on consecutive days) (ABNT, 1997). The sampled air volume was about 1440 m3. Each filter was placed in a clean polyethylene bag for transport and storage. The glass fibre filters were heated in a vacuum drying oven at 110e120 C for 2 h prior the use. The filters were weighed (after moisture equilibration) before and after sampling to determine the net mass of the particles collected. During the 24-hour equilibration period, the filters were conditioned at a controlled temperature with variation of less than ±3.0 C, and constant relative humidity within a variation of less than ±5.0%. After the final weighing, the exposed and blank filters were dried in desiccator during 24 h. The filters were divided in ten parts and three of them were used for analysis. Previously the analysis, the samples were ground for 15 min in a ball mill of agate (Retsch, Düsseldorf, Germany) to particle size lower than 63 mm. After grinding, the powdered samples were stored in polyethylene tubes. An unused filter was used to check the decontamination procedure (de Almeida et al., 2013). Standard reference materials (SRM) Fly Ash 176R, acquired from the Bureau of Reference, Brussels, Belgium (BCR) and Urban
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018
T.S. Almeida et al. / Environmental Pollution xxx (2017) 1e8
Particulate Matter (SRM NIST 1648) from the National Institute of Standards and Technology (NIST, United State American) were used to check the accuracy of the procedure. 2.3. Sampling and determination of SO2 and smoke concentrations tica, model OPSMS) was used to A small volume sampler (Energe collect smoke and SO2. The collection procedures followed the Brazilian Standards NBR 12979 and NBR 10736 for the determination of the concentrations of SO2 and smoke, respectively (ABNT, 1989; ABNT, 1993), and were carried out by the Laboratory of Assessment and Environmental Monitoring of the ADEMA in Aracaju, Sergipe, Brazil. For determination of the smoke concentration, a filter paper was inserted into a filter holder and air was sucked through for 24 h. Upon removal the reflectance was measured using a reflectometer (model M43D EEL; Diffusion Systems Ltd., London, UK), and from this value and the volume of air sampled (average volume of 2.5 m3) the smoke concentration in the air was calculated. To determine the SO2 concentration, a volume of approximately 2.5 m3 of air was sucked and bubbled for 24 h in a hydrogen peroxide solution 0.3% (v v1), with a volume of 70 mL, contained in a Dreschsel bottle. Another closed bottle containing an identical solution was kept in the equipment to be used as a sample blank solution. After 24 h, the solution was made up to 100 mL with distilled water, and titrated with sodium tetraborate 4.0 103 mol L1, using a mixed indicator of bromocresol green and methyl red in methanol solution. The concentration was calculated using the stoichiometry of sodium tetraborate and the sulphuric acid present in the solution resulting from the oxidation of SO2 by H2O2. 2.4. Microwave-assisted acid extraction The efficiency of the sample preparation procedure proposed in this work was checked comparing the results with the obtained data using microwave-assisted acid extraction. An approximately 80.0 ± 0.1 mg portion of the filter containing the collected APM was weighed directly into a polytetrafluoroethylene (PTFE) flask, to which 4.0 mL of HNO3, 1.5 mL of HCl and 3.0 mL of H2O were added. The samples were submitted to microwave-assisted acid extraction using a model MLS 1200 MEGA digester (Milestone, Sorisole, Italy), with a program consisting of three steps: (Step 1) hold time 5 min, temperature 25 to 85 C; (Step 2) hold time 15 min, temperature 85 to 210 C and (Step 3) hold time 25 min, temperature 210 C (de Almeida et al., 2013). After the extraction procedure, the solution still containing nondecomposed particles was filtered through a cellulose acetate filter (Millipore, USA). The clear filtered solution was diluted to 30 mL with ultrapure water. A further dilution (3:10, v v1) was necessary prior the analysis by inductively coupled plasma-mass spectrometry (ICP-MS). An unused filter was used to check the decontamination procedure. All samples were analysed in triplicate. 2.5. Chemical analysis The concentrations of Cu, Fe, Mn, Ni and V in APM extracts were determined considering the stables isotopes 63Cu, 57Fe, 55Mn, 60Ni and 51V, by inductively coupled plasma mass spectrometry (ICPMS, Perkin-Elmer SCIEX, model ELAN 6000, Thornhill, Canada) using 103Rh as internal standard (10 mg L1). Argon gas with a ~o minimum purity of 99.996% was obtained from White Martins (Sa Paulo, Brazil). The sample introduction system equipped with a cross flow nebuliser and a Scott spray chamber was used. The instrument
3
conditions used were: flow rate of 1.15 L min1, radiofrequency power of 1.2 kW, autolens mode on, peak hopping measurement mode, dwell time of 25 ms, 50 sweeps by reading, one reading per replicate, three replicates. A platinum cone and skimmer and an alumina injector of 1.5 mm i.d. were used. All samples were analysed in triplicate. For titanium determination (atomic line at 334.188 nm) an inductively coupled plasma-optical emission spectrometer (ICP OES) with an axial view configuration (VISTA PRO, Varian, Mulgrave, Australia) was used. The instrumental parameters were as following: radio frequency 40 MHz; applied power 1300 W; plasma gas flow rate 15.0 L min1; auxiliary gas flow rate 1.5 L min1; nebuliser gas flow rate 0.8 mL min1; sample uptake rate 0.8 mL min1; signal integration time 1 s. The sample introduction system is composed of a concentric Sea spray nebuliser and a cyclonic spray chamber. All analyses were also performed in triplicate. 2.6. Statistical analysis The software Statistica 6.0 was used to apply PCA and HCA to the results of the metal, smoke and SO2 concentration determinations. 2.7. Evaluation of the pollution The enrichment factor (EF) was used to analyse geochemical processes, identifying changes in the natural concentration profile of a chemical element. The EF can be calculated according Equation (1):
FEcrust ¼
½Ci ½Z
½Ci ½Z Crust TAPM
(1)
where [Ci] is the concentration of the element i in the samples of TAPM originating from the Earth's crust, and [Z] is the element concentration used as standard, for both the TAPM and the crust. A given element X in the sample and crust are normalised using element Z, which is considered constant, such as Ti, Al, Fe and Mn, or other elements not likely to arise from anthropic sources in the case of atmospheric pollution. In this study Fe and Ti were used for guen et al., 2012). normalisation (Gue By convention, an arbitrary value of EF < 10 is considered as an indication that a significant proportion of the element does originate not from the crust. On the other hand, EF > 10 is considered as an indication that the trace element may have the Earth's crust as a significant source. An “anomalously enriched element” (AEE) may be considered as originating from anthropic source (Pereira et al., 2007; Chester et al., 2000). Similar information to the one given by the EF can be obtained from the geoaccumulation index (Igeo) that has been applied to classify contamination in APM. Igeo can be calculated using equation (2).
Igeo ¼ Log2
Ci 1:5:CBkgi
! (2)
where Ci is the concentration of the element i in the samples; CBkgi is the background concentration of element i, which is the concentration in the Earth's crust (Rudnick and Gao, 2004). A constant value of 1.5 represents background scattering due to lithogenic variations. Six different pollution classes can be distinguished using guen et al., 2012), as shown in Table 1. This index this model (Gue was also used to evaluate the pollution classes estimated for the TAPM samples collected.
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018
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T.S. Almeida et al. / Environmental Pollution xxx (2017) 1e8
Table 1 Pollution classes estimated for the geoaccumulation index model. Geoaccumulation index (Igeo)
Classes
Pollution intensity
Igeo<0 0< Igeo1 1< Igeo 2 2< Igeo 3 3< Igeo 4 4< Igeo 5 Igeo >5
0 1 2 3 4 5 6
Almost unpolluted Low to moderately polluted Moderately polluted Moderate to heavily polluted Heavily polluted Strong to very heavily polluted Very heavily polluted
Table 2 Limits of detection and quantification calculated for Cu, Fe, Mn, Ni, V and Ti in the air.
3
LoD (ng m ) LoQ (ng m3) a
Cu
Fe
Ni
Mn
V
Tia
0.2 0.7
14 46
0.1 0.3
0.4 1.3
3.6 12
0.1 0.3
Determination by ICP OES.
3. Results and discussion 3.1. Determination of trace metals in TAPM by ICP-MS The trace metal concentrations in TAPM were determined by ICP-MS. The stables isotopes measured in the determination were 63 Cu, 57Fe, 55Mn, 60Ni and 51V. For these isotopes, the limit of detection (LoD) was calculated as three times the standard deviation value of a set of measured intensities (ten times) of the blank solutions divided by the slope of the calibration curve (using Rh as internal standard). The limit of quantification (LoQ) was calculated as 3.3 times the LoD value (International Union of Pure and Applied Chemistry, 1978). The calculation was based in a value corresponding to the average volume of air sampled of 1600 m3 and a mass of filter of 2.2 g. The LoQs ranged from 0.3 (Ni) to 46 ng m3 (Fe) of the air as specified by the results of the atmospheric chemistry measurements. For determination of titanium by ICP OES, the LoD and LoQ were calculated using the background equivalent concentration (BEC) and the signal noise ratio (SBR), according to the recommendations of the International Union of Pure and Applied Chemistry (IUPAC) (International Union of Pure and Applied Chemistry, 1978): BEC ¼ CRS/SBR, SBR ¼ (IRS e Iblank)/Iblank. LoD ¼ (3 BEC x RSD)/100 and LoQ ¼ 3.3 times LoD value, where CSR is the reference metal concentration in the solution, and ISR and Iblank are the intensities of emission for the concentration of the reference element and the sample blank, respectively. The RSD is the relative standard deviation calculated from the standard deviation of ten consecutive measurements of a control blank solution. The LoQ calculated for Ti was 0.5 ng m3. A summary of the LoDs and LoQs obtained is
presented in Table 2. To confirm the accuracy of the results of analyses of TAPM collected on glass fibre filters certificate reference materials (CRM) Urban particulate matter (NIST 1648) and Fly ash (BCR 176R) - were used. The results obtained for the CRMs analysed by ICP-MS and ICP OES are shown in Table 3. %Agreement ¼ [(found value/certified value) x 100]
3.2. Statistical summaries of air pollutants and trace metals The concentration of trace metals, SO2 and smoke were determined in 42 samples from an urban area in Aracaju, Sergipe, Brazil. The concentrations determined are presented in Table 4 (or Table S1 in Appendix A. Supplementary data). The range of TAPM concentrations was between 11.62 and 124.31 mg m3, with an average concentration of 72.13 mg m3. In Rio de Janeiro City, Loloya et al. found TAPM (or total suspended particulate - TSP) levels between 35.04 and 95.6 mg m3, with an average concentration (n ¼ 31) of 53.7 mg m3 (Loyola et al., 2012). The average value was lower than in Aracaju city. In Sete Lagoas (Southeast, Brazil), Queiroz et al. registered an average of 349 mg m3 for TAPM concentration (or TSP), a value 4.8 times higher than in Aracaju, with values between 143 and 647 mg m3 (n ¼ 29) (Queiroz et al., 2007). In urban areas of Charqueadas and Sapucaia do Sul (South, Brazil), higher concentrations of TAPM (or TSP) were also found, in an average of 235.72 mg m3 (153.34e302.95 mg m3, n ¼ 9) and 311.92 mg m3 (159.56e692.62 mg m3, n ¼ 14), being 3.2 times and 4.3 times higher than in Aracaju city, respectively (Carvalho et al., 2000). In both urban areas in Brazilian South, there was an indication of emission sources such as steel industry, thermoelectric power plant, vehicular traffic, concrete and ceramic production as contributing to TAPM found near the sample site. The concentrations of SO2 varied between 2.53 and 24.2 mg m3, with an average concentration of 6.8 mg m3. Smoke concentrations ranged from 7.73 to 43.5 mg m3, with an average of 13.4 mg m3. The zero values of concentration for SO2 and smoke were recorded on days when there was rainfall. For concentrations of TAPM, SO2 and smoke (period of 24 h), the values found in the urban area of Aracaju were below than the maximum value allowed for primary standard and secondary required by National Council of the Environment (Conselho Nacional de Meio Ambiente) through Resolution N. 03/90 (Carvalho et al., 2000). Regarding the metals present in TAPM, high concentrations were observed for Fe, with a range between <46 and 1620 ng m3. Data from literature indicate that the main sources of this metal are related to the soil resuspension (Queiroz et al., 2007; Loyola et al., 2012; Das et al., 2000), and in some cases, it is associated with
Table 3 Comparison of results for certificate reference materials of urban particulate matter (NIST 1648) and fly ash (BCR 176R) with their certificate concentrations (in mg g1). CRM Element
Urban particulate matter (NIST 1648) Certified value
Found valuea
Agreement (%)
Certified value
Found valuea
Agreement (%)
Cu Fe Mn Ni V Ti
609 ± 27 3.91 ± 0.10b 786 ± 17 82 ± 3 127 ± 7 ***
546 ± 55 4.03 ± 0.56 816 ± 54 78 ± 6 136 ± 6 0.19 ± 0.01b
90 ± 9 103 ± 14 104 ± 7 95 ± 7 107 ± 5 91 ± 5c
1050 ± 70 13100 ± 500 730 ± 50 117 ± 6 35 ± 6 ***
865 ± 80 14701 ± 1853 850 ± 61 105 ± 6 33 ± 6 7021 ± 318
82 ± 3 112 ± 6 116 ± 3 90 ± 2 94 ± 7 92 ± 4d
a b c d
Fly ash (BCR 176R)
Results expressed as average ± standard deviation (n ¼ 3). Concentration expressed as % m m1. Value calculated considering a reference concentration determined by ICP-MS of 0.21 ± 0.06% (n ¼ 3). Value calculated considering a reference concentration determined by ICP-MS of 7622 ± 183 mg g1 (n ¼ 3).
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018
T.S. Almeida et al. / Environmental Pollution xxx (2017) 1e8 Table 4 Statistical summary of the concentrations of TAPM, smoke, SO2 and the trace elements in TAPM, determined in 42 samples collected in an urban area from Aracaju, Sergipe, Brazil. Parameters 3
TAPM/mg m Smoke/mg m3 SO2/mg m3 Cu/ng m3 Fe/ng m3 Mn/ng m3 Ni/ng m3 Ti/ng m3 V/ng m3
Average
Median
Minimum
Maximum
SD
72.13 14.44 9.85 67.8 849 4.54 4.96 55.76 16.31
73.3 13.36 6.45 32.7 851 4.24 4.25 54.32 16.64
11.6 7.72 2.53 0.7 <46 <1.3 1.13 4.58 <12
124.3 43.46 24.12 321.9 1620 12.69 15.96 129.00 49.28
19.1 7.75 7.04 64.3 332 2.89 2.98 24.93 8.75
Table 5 Loading values for the variables in the three first PCs obtained applying the PCA. Variable
PC1
PC2
PC3
Fe Cu Mn Ni V Ti SO2 Smoke Total variance (%) Variance accumulated (%)
0.85 0.06 0.74 0.70 0.30 0.73 0.44 0.10 32.2 32.2
0.04 0.55 0.22 0.23 0.64 0.34 0.45 0.64 19.4 51.6
0.28 0.76 0.23 0.31 0.11 0.10 0.42 0.18 13.0 64.6
manganese, which also has soil as natural source (Valavanidis et al., 2006; Dongarr a et al., 2007; Queiroz et al., 2007). Manganese presented an average concentration of 4.54 ng m3, with a range from <1.3 to 12.69 ng m3. Another metal that may be related to soil is Ti, which presented a range of concentrations from 4.58 to 129.00 ng m3. Some authors have attributed its presence in APM to soil resuspension (Lara et al., 2005; Castanho and Artaxo, 2001; Marcazzan et al., 2001). However, Apeagyei et al. (2011).
5
associated the Ti presence in APM with vehicular traffic, showing that this was also a likely source of Ti. The concentration of Cu presented considerable values, as the metal with the second highest concentration in TAPM, with a range from 0.7 to 321.9 ng m3 and a average concentration of 67.8 ng m3. According some studies, Cu is mainly derived from vehicle emissions (Chester et al., 2000; Rudnick and Gao, 2004; Manalis et al., 2005; Allen et al., 2001; Swaine, 2000). In the present study, Cu may also be derived mainly from the same source, since the location has a large amount of vehicular traffic, near to a bus station in Aracaju city. Nickel and V showed average concentrations of 4.96 and 16.31 ng m3 ranging from 1.13 to 15.96 ng m3 and <12e49.28 ng m3, respectively. These elements are commonly emitted by the burning of fossil fuels (Allen et al., 2001; Swaine, 2000). 3.3. Multivariate data analysis A data matrix composed of 42 samples and eight analytes (42 8) was constructed, wherein the samples are organized as rows and the concentrations of trace metals (Cu, Fe, Mn, Ni, Ti and V), smoke and SO2 are in columns. The data were analysed using principal component analysis (PCA) and hierarchical cluster analysis (HCA). The data were autoscaled, in order to avoid misclassifications due to the different orders of magnitude and range of the variables. For PCA application, the choice of the number of principal components (PC) was made based on an explained fraction of the total variance of 64.6%, with a model adjusted to the first three PCs, which was sufficient to describe the system. PC1, PC2 and PC3 explained 32.2, 19.4 and 13.0% of the total variance, respectively. Table 5 shows the weight values, the total variance and the accumulated variance for the three PCs. For PC1 strong correlations were obtained for the concentrations of Fe, Mn, Ni and Ti. For Fe and Mn these correlations are very common due to soil resuspension, as reported by other works (Taiwo et al., 2014; Balasubramanian and Qian, 2002). Thus, these
Fig. 1. Dendrogram with calculation of Euclidean distance and Ward's method of connection to the variables.
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018
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four metals probably originate from the same source, which is soil resuspension or city dust. For PC2, there was an inverse correlation between V and smoke concentration. V is usually emitted by vehicular traffic and burning fossil fuels (Sturini et al., 2010), as well as by some industries that use vanadium compounds in their products (especially V2O5 as dye for inks) (Mihajlidi-zelic and Relic, 2005; Loyola et al., 2012). However, smoke is emitted through the burning of several materials such as biomass and fossil fuels. Thus, as these two components are inversely correlated, probably one of them has not been emitted by vehicular traffic. The most likely explanation is that the dispersed vanadium in the air may be emitted by a different source than vehicular emission. PC3 was mainly influenced by Cu concentrations which presented a high weight with positive signal. The presence of Cu is highly influenced by vehicular traffic, but may be also emitted by industries (Kothai et al., 2011). As the sample location is near to areas with intense vehicular traffic, Cu concentration found in TAPM is likely derived from burning fossil fuels and vehicular emissions in general (Carvalho et al., 2000; Loyola et al., 2012). In addition to PCA, HCA was applied to the matrix of data. HCA also demonstrated a situation with three diverse conditions, wherein there was a correlation between Fe, Mn, Ni and Ti and also two other correlations, one for V and SO2 and the second for Cu and smoke. The dissimilarity between the clusters in this case was
approximately 68%. Fig. 1 shows the dendrogram generated for the related variables. The correlation for Cu and smoke indicates that they come from the same source, likely vehicular traffic. The correlation for V and SO2 suggests that they are emitted by burning fuel, which is the main source of SO2 in the atmosphere (Loyola et al., 2012; Watson et al., 2001). However, the presence of vanadium also may be derived from the burning of fuel or the emissions of industries located near to the sampling area. Using these exploratory data analysis techniques it is possible to infer that the two main contributions to the formation of TAPM collected in an urban area of Aracaju city are soil resuspension or urban dust and vehicular traffic. 3.4. Enrichment factor To calculate the enrichment factor (EF), iron was used as the reference element due to its low variability related to the concentration found in the earth's crust (Rudnick and Gao, 2004). Iron concentrations, and the concentrations of the other metals are presented in Table 6. To evaluate the EF for Fe, titanium was used as the reference element based on the concentration of TiO2 in the crust. The results indicate that the only anomalously enriched element was Cu, which may be enriched by anthropic sources. PCA and HCA
Table 6 Values of EF founded, based on the average concentration of the elements in TAPM collected in Aracaju, Sergipe.
Concentration in the Earth's crust (mg g1) Enrichment factor
Cu
Fe
Mn
Ni
Ti
V
28 109
39200 1.5
775 0.3
47 4.8
3837 0.7
97 8.1
Values of concentration in the Earth's crust (Chester et al., 2000).
Fig. 2. Values of Igeo over the sample period from August 2009 to October 2010. Legend: Almost unpolluted (Igeo0); Low to moderately polluted (0 < Igeo1); Moderately polluted (1 < Igeo2); Moderate to heavily polluted (2 < Igeo3); heavily contaminated (3 < Igeo4); Strong to very heavily polluted (4 < Igeo5); Very heavily polluted (Igeo5).
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018
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7
suggested that the emission of this element was caused by vehicular traffic. Therefore EF calculation confirmed vehicular traffic as a significant source of Cu in TAPM. With intense vehicular traffic in the sampling area, the Cu concentration found in TAPM is likely derived from burning fossil fuels and vehicular emissions, being considered an enriched element (Carvalho et al., 2000; Loyola et al., 2012). Although V presented an EF lower than 10, the value found (8.1) in this work indicates a worrisome of future enrichment of this element in the urban area.
gico (CNPq, process nº 476589/2011-8, 482416/ Científico e Tecnolo 2013-0, 312058/2012-8, 308917/2015-4 and 437267/2016-4), for providing scholarship, financial support and infrastructure.
3.5. Geoaccumulation index
References
For the matrix of dates, samples and metal concentrations the geoaccumulation index was calculated. Among the six metals, only Cu presented significant values through the evaluation by Igeo guen et al., 2012). The other elements presented values of Igeo (Gue less or equal to zero, which are considered as almost unpolluted (class 0), according to Table 1. For concentration of Cu in TAPM, 23 samples presented values of Igeo0, indicating almost unpolluted. Five samples presented values of 0
Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.envpol.2017.04.018.
ABNT, 1989. Particulate Matter in Suspension in the Atmosphere e Determination of Smoke Concentration by Light Reflectance Method. NBR 10736. Brazilian Association of Technique Standards. ABNT, 1993. Atmosphere e Determination of Sulfur Dioxide by the Hidrogen Peroxide Method. NBR 12979. Brazilian Association of Technique Standards. ABNT, 1997. Particulate Matter in Suspension in the Ambient Air e Determination of Total Concentration by High Volume Sampler Method. NBR 9547. Brazilian Association of Technique Standards. Allen, A.G., Nemitz, E., Shi, J.P., Harrison, R.M., Greenwood, J.C., 2001. Size distributions of trace metals in atmospheric aerosols in the United Kingdom. Atmos. Environ. 35, 4581e4591. Apeagyei, E., Banck, M.S., Spengler, J.D., 2011. Distribution of heavy metals in road dust along an urban-rural gradient in Massachusetts. Atmos. Environ. 45, 2310e2323. Araujo, R.G.O., Vignola, F., Castilho, I.N.B., Borges, D.L.G., Welz, B., Vale, M.G.R., Smichowski, P., Ferreira, S.L.C., Becker-Ross, H., 2011. Determination of Mercury in airbone particulate matter collected on glass fiber filters using highresolution continuum source graphite furnace atomic absorption spectrometry and direct solid sampling. Spectrochim. Acta Part B 66 (5), 378e382. Balasubramanian, R., Qian, W.-B., 2002. Characterization and source identification of airborne trace metals in Singapore. J. Environ. Monit. 6, 813e818. lez, E., Andrade-Garda, J.M., Serrano-Velasco, E., Lo pez-Mahia, P., Beceiro-Gonza ~ a (NW Spain). Sci. Total 1997. Metals in airborne particulate matter in La Corun Environ. 196 (2), 131e139. Bogo, H., Otero, M., Castro, P., Ozafran, M.J., Kreiner, A., Calvo, E.J., Negri, R.M., 2003. Study of atmospheric particulate matter in Buenos Aires city. Atmos. Environ. 37, 1135e1147. Brunekreef, B., Holgate, S.T., 2002. Air pollution and health. Lancet 360, 1233e1242. Carneiro, M.C., Campos, R.C., Curtius, A.J., 1993. Determination of Sb, Ni and V in slurry from airborne particulate material collected on filter by graphite-furnace atomic-absorption spectrometry. Talanta 40, 1815e1822. Carvalho, F.G., Jablonski, A., Teixeira, E.C., 2000. Estudo das partículas totais em ~o e metais associados em suspensa areas urbanas. Quím. Nova 23, 614e617. Castanho, A.D.A., Artaxo, P., 2001. Wintertime and summertime S~ ao Paulo aerosol source apportionment study. Atmos. Environv 35, 4889e4902. Chester, R., Nimmo, M., Fontes, G.R., Keyse, S., Zhang, Z., 2000. Trace metal chemistry of particulate aerosols from the UK mainland coastal rim of the NE Irish sea. Atmos. Environ. 34, 949e958. ~o, E.M., Associados, E.M., Areas, Das, E., Totais, P., Suspensa E.M., 2000. Study of total suspended particles and the associated metals in urban. Quimica Nova 23, 614e617. de Almeida, T.S., Sant’Ana, M.O., Cruz, J.M., Tormen, L., Curtius, A.J., Alves, J.P.H., Garcia, C.A.B., Santos, P.A., Araujo, R.G.O., 2013. Optimization method for sequential determination of copper and iron in airborne particulate matter collected on glass fiber filters by slurry sampling flame atomic absorption spectrometry. J. Braz. Chem. Soc. 24 (4), 700e706. Donalson, K., Brown, D., Clouter, A., Duffin, R., MacNee, W., Renwick, L., Tran, L., Stone, V., 2002. The pulmonary toxicology of ultrafine particles. J. Aerosol Med 15, 213e220. Dongarr a, G., Manno, E., Varrica, D., Vultaggio, M., 2007. Mass levels, crustal component and trace elements in PM10, in Palermo, Italy. Atmos. Environ. 41, 7977e7986. Ferreira, S.L.C., Macedo, S.M., dos Santos, D.C., de Jesus, R.M., dos Santos, W.N.L., Queiroz, A.F.D., de Andrade, J.B., 2011. Speciation analysis of inorganic antimony in airborne particulate matter employing slurry sampling and HG QT AAS. J. Anal. At. Spectrom. 26, 1887e1891. guen, F., Stille, P., Lahd Geagea, M., Boutin, R., 2012. Atmospheric pollution in an Gue urban environment by tree bark biomonitoring - Part I: trace element analysis. Chemosphere 86 (10), 1013e1019. Habil, M., Massey, D.D., Taneja, A., 2013. Exposure of children studying in schools of India to PM levels and metal contamination: sources and their identification. Air Qual. Atmos. Health 6 (3), 575e587. lise multivariada de Hair Jr., J.F., Anderson, R.E., Tatham, R.L., Black, W.C., 2006. Ana dados, Bookman, 5a ed. Porto Alegre, Brazil, 593 pp. Ademahttp://www.adema.se.gov.br Accessed 8 February 2016. Aracajuhttp://www.aracaju.se.gov.br/aracaju/Accessed 8 February 2016. Detranhttp://www.detran.se.gov.br Accessed 8 February 2016. Semarhhttp://www.semarh.se.gov.br/meteorologia Accessed in 30 de maio de 2011. International Union of Pure and Applied Chemistry. Analytical Chemistry Division, 1978. Nomenclature, symbols, units and their usage in spectrochemical
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018
8
T.S. Almeida et al. / Environmental Pollution xxx (2017) 1e8
analysis-III. analytical flame spectroscopy and associated non-flame procedures. Spectrochim. Acta B 33 (6), 247e269. Ji, Y., Feng, Y., Wu, J., Zhu, T., Bai, Z., Duan, C., 2008. Using geoaccumulation index to study source profiles of soil dust in China. J. Environ. Sci. 20 (5), 571e578. Kothai, P., Saradhi, I.V., Pandit, G.G., Markwitz, A., Puranik, V.D., 2011. Chemical characterization and source identification of particulate matter at an urban city of Navi Mumbai, India. Aerosol Air Qual. Res. 11, 560e569. Lara, L.L., Artaxo, P., Martinelli, L.A., Camargo, P.B., Victoria, R.L., Ferraz, E.S.B., 2005. Properties of aerosols from sugar-cane burning emissions in Southeastern Brazil. Atmos. Environ. 39, 4627e4637. Loyola, J., Arbilla, G., Quiterio, S.L., Escaleira, V., Minho, A.S., 2012. Trace metals in the urban aerosols of Rio de Janeiro city. J. Braz. Chem. Soc. 23 (4), 628e638. Manalis, M., Grivas, G., Protonotarios, V., Moutsatsou, A., Samara, C., Chaloulakou, A., 2005. Toxic metal content of particulate matter (PM10), within the Greater Area of Athens. Chemosphere 60, 557e566. Marcazzan, G.M., Vaccaro, S., Valli, G., Vecchi, R., 2001. Characterization of PM10 and PM2.5 particulate matter in the ambient air of Milan (Italy). Atmos. Environ. 35, 4639e4650. Mihajlidi-zelic, A., Relic, D., 2005. Differentiation of the contribution of local resuspension from that of regional and remote sources on trace elements content in the atmospheric aerosol in the Mediterranean area. Atmos. Environ. 39, 6271e6281. Müller, G., 1969. Index of geoaccumulation in sediments of the Rhine river. Geojournal 2, 108e118. Pateraki, S., Asimakopoulos, D.N., Bougiatioti, A., Maggos, T., Vasilakos, C., Mihalopoulos, N., 2014. Assessment of PM2.5 and PM1 chemical profile in a multiple-impacted Mediterranean urban area: origin, sources and meteorological dependence. Sci. Total Environ. 479e480 (1), 210e220. Pereira, P.A.P., Lopes, W.A., Carvalho, L.S., Rocha, G.O., Bahia, N.C., Loyola, J., Quiterio, S.L., Escaleira, V., Arbilla, G., Andrade, J.B., 2007. Atmospheric concentrations and dry deposition fluxes of particulate trace metals in salvador, Bahia, Brazil. Atmos. Environ. 41, 7837e7850. ~o elementar Queiroz, P.G.M., Jacomino, V.M.F., Menezes, M.A.D.B.C., 2007. Composiça rico do município de Sete do material particulado presente no aerossol atmosfe Lagoas, Minas Gerais. Quimica Nova 30 (5), 1233e1239.
Quiterio, S.L., Silva, C.R.S., Arbilla, G., Escaleira, V., 2004. Metals in Airborne Particulate Matter in the Industrial District of Santa Cruz, Rio de Janeiro, in an Annual Period. Atmos. Environ. 38, 321e331. Rudnick, R.L., Gao, S., 2004. Composition of the continental crust. Treatise Geochem. 3, 1e64. Sturini, M., Maraschi, F., Cucca, L., Spini, G., Talamini, G., Profumi, A., 2010. Determination of vanadium (V) in the particulate matter of emissions and working areas by sequential dissolution and solid-phase extraction. Anal. Byoanal. Chem. 397, 395e399. Swaine, D.J., 2000. Why trace elements are important. Fuel Process. Technol. 65e66, 21e33. Taiwo, A.M., Beddows, D.C.S., Shi, Z., Harrison, R.M., 2014. Mass and number size distributions of particulate matter components: Comparison of an industrial site and an urban background site. Sci. Total Environ. 475, 29e38. Thorpe, A., Harrison, R.M., 2008. Sources and properties of non-exhaust particulate matter from road traffic: a review. Sci. Total Environ. 400 (1e3), 270e282. Valavanidis, A., Fiotakis, K., Vlahogianni, T., Bakeas, E.B., Triantafillaki, S., Paraskevopoulou, V., Dassenakis, M., 2006. Characterization of atmospheric particulates, particle-bound transition metals and polycyclic aromatic hydrocarbons of urban air in the centre of Athens (Greece). Chemosphere 65, 760e768. Voutsa, D., Samara, C., 2002. Labile and bioaccessible fractions of heavy metals in the airborne particulate matter from urban and industrial areas. Atmos. Environ. 36, 3583e3590. Watson, J.G., Chow, J.C., Houck, J.E., 2001. PM2.5 chemical source profiles for vehicle exhaust, vegetative burning, geological material, and coal burning in Northwestern Colorado during 1995. Chemosphere 43 (8), 1141e1151. WHO, 2003. Health Aspects of Air Pollution with Particulate Matter, Ozone and Nitrogen Dioxide. World Health Organization. Wilson, W.E., Chow, J.C., Claiborn, C., Fusheng, W., Engelbrecht, J., Watson, J.G., 2002. Monitoring of particulate matter outdoors. Chemosphere 49, 1009e1043. Wu, Z., Hua, M., Lin, P., Liu, S., Wehner, B., Wiedensohler, A., 2008. Particle number size distribution in the urban atmosphere of Beijing, China. Atmos. Environ. 42, 7967e7980. Igbewww.igbe.com.br Accessed 27 December 2016.
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Invited paper
Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil* Tarcísio S. Almeida a, b, c, Mirna O. SantAna a, Jersica M. Cruz a, Luciano Tormen b, d, ~ an b, e, Pericles A. Azevedo a, Carlos Alexandre B. Garcia a, Vera Lúcia A. Frescura Bascun a do Patrocínio H. Alves , Rennan G.O. Araujo a, c, e, * Jose ~o Cristova ~o, Sa ~o Cristova ~o, SE, Brazil rio de Química Analítica Ambiental, Departamento de Química, Universidade Federal de Sergipe, Campus Sa Laborato rio de Espectrometria Ato ^mica, Departamento de Química, Universidade Federal de Santa Catarina, Campus Trindade, Floriano polis, SC, Brazil Laborato c Universidade Federal da Bahia, Instituto de Química, Departamento de Química Analítica, Salvador, BA, Brazil d Universidade Federal da Fronteira Sul, Campus Laranjeira do Sul, Laranjeiras do Sul, PR, Brazil e Instituto Nacional de Ci^ encia e Tecnologia do CNPq e INCT de Energia e Ambiente, Universidade Federal da Bahia, Salvador, BA, Brazil a
b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 October 2016 Received in revised form 7 January 2017 Accepted 7 April 2017 Available online xxx
In this work, studies using samples collected in an urban area of Aracaju city, Sergipe State, Northeast, Brazil revealed that soil dust in suspension was the main source of total airborne particulate matter (TAPM), followed by vehicular pollution. The concentration profiles for Cu, Fe, Mn, Ni, V and Ti were established for the collected TAPM samples. The concentrations of SO2 and smoke were also measured all along the 42 sampling days. Through multivariate data analysis of the results a correlation between Fe, Mn, Ni and Ti in the mineral composition of the particles was established, indicating soil dust in suspension as the main source of TAPM. The concentrations of Cu and smoke were found to be related to vehicular traffic, and the second largest source of TAPM. Enrichment factors (EF) were calculated for the studied elements, and only Cu was found to be enriched. The concentrations of the elements in TAPM were evaluated using the geoaccumulation index (Igeo), and Fe, Mn, Ni, V and Ti were found to derive from natural sources, in TAPM. However, approximately 55% of the samples did not presented Cu contamination (Igeo0), and the remaining 45% presented Cu concentrations levels that indicated between low to moderate (0
Keywords: Total airborne particulate matter Atmospheric pollution PCA and HCA Enrichment factor Geoaccumulation index
1. Introduction Airborne particulate matter (APM) is a complex mixture of organic and inorganic substances of varying particle size, chemical composition and source, which can be present as solid or liquid (WHO, 2003). APM has been source of concern because of its adverse health effects, especially for urban populations (Valavanidis et al., 2006). The characteristics of this atmospheric pollutant are affected by
*
This paper has been recommended for acceptance by David Carpenter. * Corresponding author. Departamento de Química Analítica, Instituto de Química, Universidade Federal da Bahia (UFBA), 40170-115, Salvador, BA, Brazil. E-mail addresses: [email protected], [email protected] (R.G.O. Araujo).
topographic and meteorological characteristics, and by the presence of human activity. These factors have significant influences on the emission, transport and dispersion of APM (Carvalho et al., 2000; Bogo et al., 2003; Beceiro-Gonz alez et al., 1997; Pateraki et al., 2014; Taiwo et al., 2014). Epidemiological studies show that in urban areas continuous exposure to particles with a diameter smaller than 10 mm has the potential to affect human health, causing several respiratory diseases such as allergies, asthma, pulmonary emphysema and cardiopulmonary mortality (Brunekreef and Holgate, 2002; Donalson et al., 2007). et al., 2002; Dongarra The trace element concentrations in APM are related to their physicochemical characteristics, their solubility in biological fluids, their toxicity, the reactions catalysed by ions present and other effects particular to the exposure area (Voutsa and Samara, 2002).
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The elemental composition of APM is widely used to characterize lez et al., 1997). atmospheric air conditions (Beceiro-Gonza Several studies have dealt with trace metals, such as Al, Cu, Cr, Fe, K, Mn, Mg, Na, Ni, Pb, Sm, Ti and V, in APM composition collected lez et al., 1997; in urban areas (Carvalho et al., 2000; Beceiro-Gonza Balasubramanian and Qian, 2002; Queiroz et al., 2007). According to this studies the suspended material can be related to siderurgy and thermoelectric plants (Fe, Cu, Cr, Mn, Mg, Pb and Ni) (Carvalho et al., 2000); solid waste incineration and vehicular traffic (Fe, Cu, Pb, Zn) (Balasubramanian and Qian, 2002; Queiroz et al., 2007); extraction and/or limestone processing, concrete and ceramic production, as well as other types of industrial processes (Sm, Cu, As and Na) (Queiroz et al., 2007); soil dust, crustal erosion, proximity to forest, oil plants, refineries and fuel burning of oils in lez et al., 1997; boilers (Al, Fe, K, Mn, Ni, Ti and V) (Beceiro-Gonza Balasubramanian and Qian, 2002; Queiroz et al., 2007) and other matrices. Therefore, identification of the different APM emission sources is worthwhile, since airborne particles characterisation has been an advantageous method in evaluating anthropic emission levels in urban areas and assessing possible consequences of emissions on public health, flora, fauna and materials. However, reliable results for trace elements in the range of ng m3 or lower are required, which is difficult due to the extremely low concentrations in fractions of milligrams of powder collected from the air (Balasubramanian and Qian, 2002; Wu et al., 2008; Habil et al., 2013). Spectrometric techniques based on atomic absorption spectrometry (AAS) and inductively coupled plasma sources (ICP), such as optical emission spectrometry (ICP OES) and mass spectrometry (ICP-MS) are widely used for trace element determination in APM (Balasubramanian and Qian, 2002; Wu et al., 2008; Quiterio et al., 2004; Wilson et al., 2002; Carneiro et al., 1993; Ferreira et al., 2011; Araujo et al., 2011). Environmental samples are evaluated through the use of chemometric tools for multivariate data analysis, such as principal component analysis (PCA) and hierarchical cluster analysis (HCA) in order to establish relationships between the chemicals and their probable sources of emission (Hair et al., 2006). A study performed in Herceg Novi, Montenegro, PCA indicated that groups of emission sources such as soil resuspension, iron and steel processing, and ship maintenance contributed to the content of trace elements in the total APM (TAPM) (Mihajlidi-zelic and Relic, 2005). BeceiroGonz alez et al. determined Pb, Cd, Mn, V, Zn and Fe concentrations ~, Spain. PCA in TAPM collected in two different places in La Coruna was applied using the metal concentrations, and it suggested two main sources d soil resuspension and anthropic activity d but the TAPM concentration depended on the atmospheric conditions lez et al., 1997). Loyola et al. used PCA and HCA to (Beceiro-Gonza study an urban area highly impacted by vehicular traffic. The analysis suggested that the APM collected in the area was related to natural sources, soil resuspension as well as vehicular traffic (Loyola et al., 2012). To evaluate the degree of atmospheric pollution, the determined concentration of an element in TAPM can be compared with its natural concentration (background) through factors such as the geoaccumulation index (Igeo) (Müller, 1969) and the enrichment factor (EF) (Chester et al., 2000). These two factors combine information about the likely source of emission, indicating whether the element is derived from natural or non-natural sources. Loyola et al. calculated the EF for Al, Ca, Cr, Cu, Fe, Mg, Mn, V and Zn in TAPM collected in an urban area of Rio de Janeiro city. According to their study, the Zn and Cu concentrations were considered anomalous in all samples, and were likely derived from anthropic sources (Loyola et al., 2012). Yaquin et al. investigated the influence of soil dust on TAPM and PM10 (airborne particulate matter with diameter particles smaller than 10 mm) formation in 15
China's cities, where the Igeo for 17 trace elements was evaluated. The results indicated that in some of the cities TAPM and PM10 are affected by the soil dust (Ji et al., 2008). Observing the problems caused by TAPM and air pollution in general, the purpose of the present work was to study the likely sources of pollutants in an urban area located in Aracaju city, Sergipe State, Brazil. The study aimed to associate the probable natural or anthropic sources of emission via the concentrations of Cu, Fe, Mn, Ni, Ti and V present in TAPM, as well as the concentrations of SO2 and smoke measured on 42 different days. PCA, HCA, enrichment factor and geoaccumulation index were used to evaluate the obtained results. 2. Experimental 2.1. Study area Aracaju is the capital of Sergipe State, Brazil, and it covers an area of 181.8 km2 with a population of about 641,523 inhabitant (Igbe). The city is located on the coast, bathed by Atlantic Ocean, and divided by the Poxim and Sergipe rivers. Among the climatic characteristics, the city exhibits an average annual temperature of 26 C and annual rainfall of 1590 mm, the rainy season being from March to August (Aracaju). The city of Aracaju has a fleet of more than 290 thousand motor vehicles according to data from the Traffic Department of the State of Sergipe (Departamento Estadual ^nsito de Sergipe - DETRAN/SE) (Detran). de Tra Samples were collected using large and small volume samplers installed at a point located in an urban area belonging to the Environment and Water Resource Department of Sergipe (SEMARH) under the responsibility of the Environment State Adminis~o Estadual de Meio Ambiente - ADEMA), near tration (Administraça the Viaduct Carvalho Deda (Viaduto Deda Carvalho) and the Integration bus station in the Industrial District of Aracaju (Distrito Industrial de Aracaju e D.I.A.), with the geographical coordinates 24 710458E 87 89116N (UTM) (Adema). 2.2. Sampling of airborne particulate matter Forty-two TAPM samples were collected on ash-free glass fibre tica, Rio de Janeiro, Brazil) in Aracaju filters (E55, 8 10 inch, Energe city, Sergipe State, Northeast, Brazil, using a high-volume air tica, Rio de Janeiro, RJ, Brazil). The sampling period sampler (Energe was from August 2009 to October 2010. The sampling flow rate used was 1000 L min1, and the total sampling time was around 24 h (approximately from noon to noon on consecutive days) (ABNT, 1997). The sampled air volume was about 1440 m3. Each filter was placed in a clean polyethylene bag for transport and storage. The glass fibre filters were heated in a vacuum drying oven at 110e120 C for 2 h prior the use. The filters were weighed (after moisture equilibration) before and after sampling to determine the net mass of the particles collected. During the 24-hour equilibration period, the filters were conditioned at a controlled temperature with variation of less than ±3.0 C, and constant relative humidity within a variation of less than ±5.0%. After the final weighing, the exposed and blank filters were dried in desiccator during 24 h. The filters were divided in ten parts and three of them were used for analysis. Previously the analysis, the samples were ground for 15 min in a ball mill of agate (Retsch, Düsseldorf, Germany) to particle size lower than 63 mm. After grinding, the powdered samples were stored in polyethylene tubes. An unused filter was used to check the decontamination procedure (de Almeida et al., 2013). Standard reference materials (SRM) Fly Ash 176R, acquired from the Bureau of Reference, Brussels, Belgium (BCR) and Urban
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018
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Particulate Matter (SRM NIST 1648) from the National Institute of Standards and Technology (NIST, United State American) were used to check the accuracy of the procedure. 2.3. Sampling and determination of SO2 and smoke concentrations tica, model OPSMS) was used to A small volume sampler (Energe collect smoke and SO2. The collection procedures followed the Brazilian Standards NBR 12979 and NBR 10736 for the determination of the concentrations of SO2 and smoke, respectively (ABNT, 1989; ABNT, 1993), and were carried out by the Laboratory of Assessment and Environmental Monitoring of the ADEMA in Aracaju, Sergipe, Brazil. For determination of the smoke concentration, a filter paper was inserted into a filter holder and air was sucked through for 24 h. Upon removal the reflectance was measured using a reflectometer (model M43D EEL; Diffusion Systems Ltd., London, UK), and from this value and the volume of air sampled (average volume of 2.5 m3) the smoke concentration in the air was calculated. To determine the SO2 concentration, a volume of approximately 2.5 m3 of air was sucked and bubbled for 24 h in a hydrogen peroxide solution 0.3% (v v1), with a volume of 70 mL, contained in a Dreschsel bottle. Another closed bottle containing an identical solution was kept in the equipment to be used as a sample blank solution. After 24 h, the solution was made up to 100 mL with distilled water, and titrated with sodium tetraborate 4.0 103 mol L1, using a mixed indicator of bromocresol green and methyl red in methanol solution. The concentration was calculated using the stoichiometry of sodium tetraborate and the sulphuric acid present in the solution resulting from the oxidation of SO2 by H2O2. 2.4. Microwave-assisted acid extraction The efficiency of the sample preparation procedure proposed in this work was checked comparing the results with the obtained data using microwave-assisted acid extraction. An approximately 80.0 ± 0.1 mg portion of the filter containing the collected APM was weighed directly into a polytetrafluoroethylene (PTFE) flask, to which 4.0 mL of HNO3, 1.5 mL of HCl and 3.0 mL of H2O were added. The samples were submitted to microwave-assisted acid extraction using a model MLS 1200 MEGA digester (Milestone, Sorisole, Italy), with a program consisting of three steps: (Step 1) hold time 5 min, temperature 25 to 85 C; (Step 2) hold time 15 min, temperature 85 to 210 C and (Step 3) hold time 25 min, temperature 210 C (de Almeida et al., 2013). After the extraction procedure, the solution still containing nondecomposed particles was filtered through a cellulose acetate filter (Millipore, USA). The clear filtered solution was diluted to 30 mL with ultrapure water. A further dilution (3:10, v v1) was necessary prior the analysis by inductively coupled plasma-mass spectrometry (ICP-MS). An unused filter was used to check the decontamination procedure. All samples were analysed in triplicate. 2.5. Chemical analysis The concentrations of Cu, Fe, Mn, Ni and V in APM extracts were determined considering the stables isotopes 63Cu, 57Fe, 55Mn, 60Ni and 51V, by inductively coupled plasma mass spectrometry (ICPMS, Perkin-Elmer SCIEX, model ELAN 6000, Thornhill, Canada) using 103Rh as internal standard (10 mg L1). Argon gas with a ~o minimum purity of 99.996% was obtained from White Martins (Sa Paulo, Brazil). The sample introduction system equipped with a cross flow nebuliser and a Scott spray chamber was used. The instrument
3
conditions used were: flow rate of 1.15 L min1, radiofrequency power of 1.2 kW, autolens mode on, peak hopping measurement mode, dwell time of 25 ms, 50 sweeps by reading, one reading per replicate, three replicates. A platinum cone and skimmer and an alumina injector of 1.5 mm i.d. were used. All samples were analysed in triplicate. For titanium determination (atomic line at 334.188 nm) an inductively coupled plasma-optical emission spectrometer (ICP OES) with an axial view configuration (VISTA PRO, Varian, Mulgrave, Australia) was used. The instrumental parameters were as following: radio frequency 40 MHz; applied power 1300 W; plasma gas flow rate 15.0 L min1; auxiliary gas flow rate 1.5 L min1; nebuliser gas flow rate 0.8 mL min1; sample uptake rate 0.8 mL min1; signal integration time 1 s. The sample introduction system is composed of a concentric Sea spray nebuliser and a cyclonic spray chamber. All analyses were also performed in triplicate. 2.6. Statistical analysis The software Statistica 6.0 was used to apply PCA and HCA to the results of the metal, smoke and SO2 concentration determinations. 2.7. Evaluation of the pollution The enrichment factor (EF) was used to analyse geochemical processes, identifying changes in the natural concentration profile of a chemical element. The EF can be calculated according Equation (1):
FEcrust ¼
½Ci ½Z
½Ci ½Z Crust TAPM
(1)
where [Ci] is the concentration of the element i in the samples of TAPM originating from the Earth's crust, and [Z] is the element concentration used as standard, for both the TAPM and the crust. A given element X in the sample and crust are normalised using element Z, which is considered constant, such as Ti, Al, Fe and Mn, or other elements not likely to arise from anthropic sources in the case of atmospheric pollution. In this study Fe and Ti were used for guen et al., 2012). normalisation (Gue By convention, an arbitrary value of EF < 10 is considered as an indication that a significant proportion of the element does originate not from the crust. On the other hand, EF > 10 is considered as an indication that the trace element may have the Earth's crust as a significant source. An “anomalously enriched element” (AEE) may be considered as originating from anthropic source (Pereira et al., 2007; Chester et al., 2000). Similar information to the one given by the EF can be obtained from the geoaccumulation index (Igeo) that has been applied to classify contamination in APM. Igeo can be calculated using equation (2).
Igeo ¼ Log2
Ci 1:5:CBkgi
! (2)
where Ci is the concentration of the element i in the samples; CBkgi is the background concentration of element i, which is the concentration in the Earth's crust (Rudnick and Gao, 2004). A constant value of 1.5 represents background scattering due to lithogenic variations. Six different pollution classes can be distinguished using guen et al., 2012), as shown in Table 1. This index this model (Gue was also used to evaluate the pollution classes estimated for the TAPM samples collected.
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018
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T.S. Almeida et al. / Environmental Pollution xxx (2017) 1e8
Table 1 Pollution classes estimated for the geoaccumulation index model. Geoaccumulation index (Igeo)
Classes
Pollution intensity
Igeo<0 0< Igeo1 1< Igeo 2 2< Igeo 3 3< Igeo 4 4< Igeo 5 Igeo >5
0 1 2 3 4 5 6
Almost unpolluted Low to moderately polluted Moderately polluted Moderate to heavily polluted Heavily polluted Strong to very heavily polluted Very heavily polluted
Table 2 Limits of detection and quantification calculated for Cu, Fe, Mn, Ni, V and Ti in the air.
3
LoD (ng m ) LoQ (ng m3) a
Cu
Fe
Ni
Mn
V
Tia
0.2 0.7
14 46
0.1 0.3
0.4 1.3
3.6 12
0.1 0.3
Determination by ICP OES.
3. Results and discussion 3.1. Determination of trace metals in TAPM by ICP-MS The trace metal concentrations in TAPM were determined by ICP-MS. The stables isotopes measured in the determination were 63 Cu, 57Fe, 55Mn, 60Ni and 51V. For these isotopes, the limit of detection (LoD) was calculated as three times the standard deviation value of a set of measured intensities (ten times) of the blank solutions divided by the slope of the calibration curve (using Rh as internal standard). The limit of quantification (LoQ) was calculated as 3.3 times the LoD value (International Union of Pure and Applied Chemistry, 1978). The calculation was based in a value corresponding to the average volume of air sampled of 1600 m3 and a mass of filter of 2.2 g. The LoQs ranged from 0.3 (Ni) to 46 ng m3 (Fe) of the air as specified by the results of the atmospheric chemistry measurements. For determination of titanium by ICP OES, the LoD and LoQ were calculated using the background equivalent concentration (BEC) and the signal noise ratio (SBR), according to the recommendations of the International Union of Pure and Applied Chemistry (IUPAC) (International Union of Pure and Applied Chemistry, 1978): BEC ¼ CRS/SBR, SBR ¼ (IRS e Iblank)/Iblank. LoD ¼ (3 BEC x RSD)/100 and LoQ ¼ 3.3 times LoD value, where CSR is the reference metal concentration in the solution, and ISR and Iblank are the intensities of emission for the concentration of the reference element and the sample blank, respectively. The RSD is the relative standard deviation calculated from the standard deviation of ten consecutive measurements of a control blank solution. The LoQ calculated for Ti was 0.5 ng m3. A summary of the LoDs and LoQs obtained is
presented in Table 2. To confirm the accuracy of the results of analyses of TAPM collected on glass fibre filters certificate reference materials (CRM) Urban particulate matter (NIST 1648) and Fly ash (BCR 176R) - were used. The results obtained for the CRMs analysed by ICP-MS and ICP OES are shown in Table 3. %Agreement ¼ [(found value/certified value) x 100]
3.2. Statistical summaries of air pollutants and trace metals The concentration of trace metals, SO2 and smoke were determined in 42 samples from an urban area in Aracaju, Sergipe, Brazil. The concentrations determined are presented in Table 4 (or Table S1 in Appendix A. Supplementary data). The range of TAPM concentrations was between 11.62 and 124.31 mg m3, with an average concentration of 72.13 mg m3. In Rio de Janeiro City, Loloya et al. found TAPM (or total suspended particulate - TSP) levels between 35.04 and 95.6 mg m3, with an average concentration (n ¼ 31) of 53.7 mg m3 (Loyola et al., 2012). The average value was lower than in Aracaju city. In Sete Lagoas (Southeast, Brazil), Queiroz et al. registered an average of 349 mg m3 for TAPM concentration (or TSP), a value 4.8 times higher than in Aracaju, with values between 143 and 647 mg m3 (n ¼ 29) (Queiroz et al., 2007). In urban areas of Charqueadas and Sapucaia do Sul (South, Brazil), higher concentrations of TAPM (or TSP) were also found, in an average of 235.72 mg m3 (153.34e302.95 mg m3, n ¼ 9) and 311.92 mg m3 (159.56e692.62 mg m3, n ¼ 14), being 3.2 times and 4.3 times higher than in Aracaju city, respectively (Carvalho et al., 2000). In both urban areas in Brazilian South, there was an indication of emission sources such as steel industry, thermoelectric power plant, vehicular traffic, concrete and ceramic production as contributing to TAPM found near the sample site. The concentrations of SO2 varied between 2.53 and 24.2 mg m3, with an average concentration of 6.8 mg m3. Smoke concentrations ranged from 7.73 to 43.5 mg m3, with an average of 13.4 mg m3. The zero values of concentration for SO2 and smoke were recorded on days when there was rainfall. For concentrations of TAPM, SO2 and smoke (period of 24 h), the values found in the urban area of Aracaju were below than the maximum value allowed for primary standard and secondary required by National Council of the Environment (Conselho Nacional de Meio Ambiente) through Resolution N. 03/90 (Carvalho et al., 2000). Regarding the metals present in TAPM, high concentrations were observed for Fe, with a range between <46 and 1620 ng m3. Data from literature indicate that the main sources of this metal are related to the soil resuspension (Queiroz et al., 2007; Loyola et al., 2012; Das et al., 2000), and in some cases, it is associated with
Table 3 Comparison of results for certificate reference materials of urban particulate matter (NIST 1648) and fly ash (BCR 176R) with their certificate concentrations (in mg g1). CRM Element
Urban particulate matter (NIST 1648) Certified value
Found valuea
Agreement (%)
Certified value
Found valuea
Agreement (%)
Cu Fe Mn Ni V Ti
609 ± 27 3.91 ± 0.10b 786 ± 17 82 ± 3 127 ± 7 ***
546 ± 55 4.03 ± 0.56 816 ± 54 78 ± 6 136 ± 6 0.19 ± 0.01b
90 ± 9 103 ± 14 104 ± 7 95 ± 7 107 ± 5 91 ± 5c
1050 ± 70 13100 ± 500 730 ± 50 117 ± 6 35 ± 6 ***
865 ± 80 14701 ± 1853 850 ± 61 105 ± 6 33 ± 6 7021 ± 318
82 ± 3 112 ± 6 116 ± 3 90 ± 2 94 ± 7 92 ± 4d
a b c d
Fly ash (BCR 176R)
Results expressed as average ± standard deviation (n ¼ 3). Concentration expressed as % m m1. Value calculated considering a reference concentration determined by ICP-MS of 0.21 ± 0.06% (n ¼ 3). Value calculated considering a reference concentration determined by ICP-MS of 7622 ± 183 mg g1 (n ¼ 3).
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018
T.S. Almeida et al. / Environmental Pollution xxx (2017) 1e8 Table 4 Statistical summary of the concentrations of TAPM, smoke, SO2 and the trace elements in TAPM, determined in 42 samples collected in an urban area from Aracaju, Sergipe, Brazil. Parameters 3
TAPM/mg m Smoke/mg m3 SO2/mg m3 Cu/ng m3 Fe/ng m3 Mn/ng m3 Ni/ng m3 Ti/ng m3 V/ng m3
Average
Median
Minimum
Maximum
SD
72.13 14.44 9.85 67.8 849 4.54 4.96 55.76 16.31
73.3 13.36 6.45 32.7 851 4.24 4.25 54.32 16.64
11.6 7.72 2.53 0.7 <46 <1.3 1.13 4.58 <12
124.3 43.46 24.12 321.9 1620 12.69 15.96 129.00 49.28
19.1 7.75 7.04 64.3 332 2.89 2.98 24.93 8.75
Table 5 Loading values for the variables in the three first PCs obtained applying the PCA. Variable
PC1
PC2
PC3
Fe Cu Mn Ni V Ti SO2 Smoke Total variance (%) Variance accumulated (%)
0.85 0.06 0.74 0.70 0.30 0.73 0.44 0.10 32.2 32.2
0.04 0.55 0.22 0.23 0.64 0.34 0.45 0.64 19.4 51.6
0.28 0.76 0.23 0.31 0.11 0.10 0.42 0.18 13.0 64.6
manganese, which also has soil as natural source (Valavanidis et al., 2006; Dongarr a et al., 2007; Queiroz et al., 2007). Manganese presented an average concentration of 4.54 ng m3, with a range from <1.3 to 12.69 ng m3. Another metal that may be related to soil is Ti, which presented a range of concentrations from 4.58 to 129.00 ng m3. Some authors have attributed its presence in APM to soil resuspension (Lara et al., 2005; Castanho and Artaxo, 2001; Marcazzan et al., 2001). However, Apeagyei et al. (2011).
5
associated the Ti presence in APM with vehicular traffic, showing that this was also a likely source of Ti. The concentration of Cu presented considerable values, as the metal with the second highest concentration in TAPM, with a range from 0.7 to 321.9 ng m3 and a average concentration of 67.8 ng m3. According some studies, Cu is mainly derived from vehicle emissions (Chester et al., 2000; Rudnick and Gao, 2004; Manalis et al., 2005; Allen et al., 2001; Swaine, 2000). In the present study, Cu may also be derived mainly from the same source, since the location has a large amount of vehicular traffic, near to a bus station in Aracaju city. Nickel and V showed average concentrations of 4.96 and 16.31 ng m3 ranging from 1.13 to 15.96 ng m3 and <12e49.28 ng m3, respectively. These elements are commonly emitted by the burning of fossil fuels (Allen et al., 2001; Swaine, 2000). 3.3. Multivariate data analysis A data matrix composed of 42 samples and eight analytes (42 8) was constructed, wherein the samples are organized as rows and the concentrations of trace metals (Cu, Fe, Mn, Ni, Ti and V), smoke and SO2 are in columns. The data were analysed using principal component analysis (PCA) and hierarchical cluster analysis (HCA). The data were autoscaled, in order to avoid misclassifications due to the different orders of magnitude and range of the variables. For PCA application, the choice of the number of principal components (PC) was made based on an explained fraction of the total variance of 64.6%, with a model adjusted to the first three PCs, which was sufficient to describe the system. PC1, PC2 and PC3 explained 32.2, 19.4 and 13.0% of the total variance, respectively. Table 5 shows the weight values, the total variance and the accumulated variance for the three PCs. For PC1 strong correlations were obtained for the concentrations of Fe, Mn, Ni and Ti. For Fe and Mn these correlations are very common due to soil resuspension, as reported by other works (Taiwo et al., 2014; Balasubramanian and Qian, 2002). Thus, these
Fig. 1. Dendrogram with calculation of Euclidean distance and Ward's method of connection to the variables.
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T.S. Almeida et al. / Environmental Pollution xxx (2017) 1e8
four metals probably originate from the same source, which is soil resuspension or city dust. For PC2, there was an inverse correlation between V and smoke concentration. V is usually emitted by vehicular traffic and burning fossil fuels (Sturini et al., 2010), as well as by some industries that use vanadium compounds in their products (especially V2O5 as dye for inks) (Mihajlidi-zelic and Relic, 2005; Loyola et al., 2012). However, smoke is emitted through the burning of several materials such as biomass and fossil fuels. Thus, as these two components are inversely correlated, probably one of them has not been emitted by vehicular traffic. The most likely explanation is that the dispersed vanadium in the air may be emitted by a different source than vehicular emission. PC3 was mainly influenced by Cu concentrations which presented a high weight with positive signal. The presence of Cu is highly influenced by vehicular traffic, but may be also emitted by industries (Kothai et al., 2011). As the sample location is near to areas with intense vehicular traffic, Cu concentration found in TAPM is likely derived from burning fossil fuels and vehicular emissions in general (Carvalho et al., 2000; Loyola et al., 2012). In addition to PCA, HCA was applied to the matrix of data. HCA also demonstrated a situation with three diverse conditions, wherein there was a correlation between Fe, Mn, Ni and Ti and also two other correlations, one for V and SO2 and the second for Cu and smoke. The dissimilarity between the clusters in this case was
approximately 68%. Fig. 1 shows the dendrogram generated for the related variables. The correlation for Cu and smoke indicates that they come from the same source, likely vehicular traffic. The correlation for V and SO2 suggests that they are emitted by burning fuel, which is the main source of SO2 in the atmosphere (Loyola et al., 2012; Watson et al., 2001). However, the presence of vanadium also may be derived from the burning of fuel or the emissions of industries located near to the sampling area. Using these exploratory data analysis techniques it is possible to infer that the two main contributions to the formation of TAPM collected in an urban area of Aracaju city are soil resuspension or urban dust and vehicular traffic. 3.4. Enrichment factor To calculate the enrichment factor (EF), iron was used as the reference element due to its low variability related to the concentration found in the earth's crust (Rudnick and Gao, 2004). Iron concentrations, and the concentrations of the other metals are presented in Table 6. To evaluate the EF for Fe, titanium was used as the reference element based on the concentration of TiO2 in the crust. The results indicate that the only anomalously enriched element was Cu, which may be enriched by anthropic sources. PCA and HCA
Table 6 Values of EF founded, based on the average concentration of the elements in TAPM collected in Aracaju, Sergipe.
Concentration in the Earth's crust (mg g1) Enrichment factor
Cu
Fe
Mn
Ni
Ti
V
28 109
39200 1.5
775 0.3
47 4.8
3837 0.7
97 8.1
Values of concentration in the Earth's crust (Chester et al., 2000).
Fig. 2. Values of Igeo over the sample period from August 2009 to October 2010. Legend: Almost unpolluted (Igeo0); Low to moderately polluted (0 < Igeo1); Moderately polluted (1 < Igeo2); Moderate to heavily polluted (2 < Igeo3); heavily contaminated (3 < Igeo4); Strong to very heavily polluted (4 < Igeo5); Very heavily polluted (Igeo5).
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018
T.S. Almeida et al. / Environmental Pollution xxx (2017) 1e8
7
suggested that the emission of this element was caused by vehicular traffic. Therefore EF calculation confirmed vehicular traffic as a significant source of Cu in TAPM. With intense vehicular traffic in the sampling area, the Cu concentration found in TAPM is likely derived from burning fossil fuels and vehicular emissions, being considered an enriched element (Carvalho et al., 2000; Loyola et al., 2012). Although V presented an EF lower than 10, the value found (8.1) in this work indicates a worrisome of future enrichment of this element in the urban area.
gico (CNPq, process nº 476589/2011-8, 482416/ Científico e Tecnolo 2013-0, 312058/2012-8, 308917/2015-4 and 437267/2016-4), for providing scholarship, financial support and infrastructure.
3.5. Geoaccumulation index
References
For the matrix of dates, samples and metal concentrations the geoaccumulation index was calculated. Among the six metals, only Cu presented significant values through the evaluation by Igeo guen et al., 2012). The other elements presented values of Igeo (Gue less or equal to zero, which are considered as almost unpolluted (class 0), according to Table 1. For concentration of Cu in TAPM, 23 samples presented values of Igeo0, indicating almost unpolluted. Five samples presented values of 0
Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.envpol.2017.04.018.
ABNT, 1989. Particulate Matter in Suspension in the Atmosphere e Determination of Smoke Concentration by Light Reflectance Method. NBR 10736. Brazilian Association of Technique Standards. ABNT, 1993. Atmosphere e Determination of Sulfur Dioxide by the Hidrogen Peroxide Method. NBR 12979. Brazilian Association of Technique Standards. ABNT, 1997. Particulate Matter in Suspension in the Ambient Air e Determination of Total Concentration by High Volume Sampler Method. NBR 9547. Brazilian Association of Technique Standards. Allen, A.G., Nemitz, E., Shi, J.P., Harrison, R.M., Greenwood, J.C., 2001. Size distributions of trace metals in atmospheric aerosols in the United Kingdom. Atmos. Environ. 35, 4581e4591. Apeagyei, E., Banck, M.S., Spengler, J.D., 2011. Distribution of heavy metals in road dust along an urban-rural gradient in Massachusetts. Atmos. Environ. 45, 2310e2323. Araujo, R.G.O., Vignola, F., Castilho, I.N.B., Borges, D.L.G., Welz, B., Vale, M.G.R., Smichowski, P., Ferreira, S.L.C., Becker-Ross, H., 2011. Determination of Mercury in airbone particulate matter collected on glass fiber filters using highresolution continuum source graphite furnace atomic absorption spectrometry and direct solid sampling. Spectrochim. Acta Part B 66 (5), 378e382. Balasubramanian, R., Qian, W.-B., 2002. Characterization and source identification of airborne trace metals in Singapore. J. Environ. Monit. 6, 813e818. lez, E., Andrade-Garda, J.M., Serrano-Velasco, E., Lo pez-Mahia, P., Beceiro-Gonza ~ a (NW Spain). Sci. Total 1997. Metals in airborne particulate matter in La Corun Environ. 196 (2), 131e139. Bogo, H., Otero, M., Castro, P., Ozafran, M.J., Kreiner, A., Calvo, E.J., Negri, R.M., 2003. Study of atmospheric particulate matter in Buenos Aires city. Atmos. Environ. 37, 1135e1147. Brunekreef, B., Holgate, S.T., 2002. Air pollution and health. Lancet 360, 1233e1242. Carneiro, M.C., Campos, R.C., Curtius, A.J., 1993. Determination of Sb, Ni and V in slurry from airborne particulate material collected on filter by graphite-furnace atomic-absorption spectrometry. Talanta 40, 1815e1822. Carvalho, F.G., Jablonski, A., Teixeira, E.C., 2000. Estudo das partículas totais em ~o e metais associados em suspensa areas urbanas. Quím. Nova 23, 614e617. Castanho, A.D.A., Artaxo, P., 2001. Wintertime and summertime S~ ao Paulo aerosol source apportionment study. Atmos. Environv 35, 4889e4902. Chester, R., Nimmo, M., Fontes, G.R., Keyse, S., Zhang, Z., 2000. Trace metal chemistry of particulate aerosols from the UK mainland coastal rim of the NE Irish sea. Atmos. Environ. 34, 949e958. ~o, E.M., Associados, E.M., Areas, Das, E., Totais, P., Suspensa E.M., 2000. Study of total suspended particles and the associated metals in urban. Quimica Nova 23, 614e617. de Almeida, T.S., Sant’Ana, M.O., Cruz, J.M., Tormen, L., Curtius, A.J., Alves, J.P.H., Garcia, C.A.B., Santos, P.A., Araujo, R.G.O., 2013. Optimization method for sequential determination of copper and iron in airborne particulate matter collected on glass fiber filters by slurry sampling flame atomic absorption spectrometry. J. Braz. Chem. Soc. 24 (4), 700e706. Donalson, K., Brown, D., Clouter, A., Duffin, R., MacNee, W., Renwick, L., Tran, L., Stone, V., 2002. The pulmonary toxicology of ultrafine particles. J. Aerosol Med 15, 213e220. Dongarr a, G., Manno, E., Varrica, D., Vultaggio, M., 2007. Mass levels, crustal component and trace elements in PM10, in Palermo, Italy. Atmos. Environ. 41, 7977e7986. Ferreira, S.L.C., Macedo, S.M., dos Santos, D.C., de Jesus, R.M., dos Santos, W.N.L., Queiroz, A.F.D., de Andrade, J.B., 2011. Speciation analysis of inorganic antimony in airborne particulate matter employing slurry sampling and HG QT AAS. J. Anal. At. Spectrom. 26, 1887e1891. guen, F., Stille, P., Lahd Geagea, M., Boutin, R., 2012. Atmospheric pollution in an Gue urban environment by tree bark biomonitoring - Part I: trace element analysis. Chemosphere 86 (10), 1013e1019. Habil, M., Massey, D.D., Taneja, A., 2013. Exposure of children studying in schools of India to PM levels and metal contamination: sources and their identification. Air Qual. Atmos. Health 6 (3), 575e587. lise multivariada de Hair Jr., J.F., Anderson, R.E., Tatham, R.L., Black, W.C., 2006. Ana dados, Bookman, 5a ed. Porto Alegre, Brazil, 593 pp. Ademahttp://www.adema.se.gov.br Accessed 8 February 2016. Aracajuhttp://www.aracaju.se.gov.br/aracaju/Accessed 8 February 2016. Detranhttp://www.detran.se.gov.br Accessed 8 February 2016. Semarhhttp://www.semarh.se.gov.br/meteorologia Accessed in 30 de maio de 2011. International Union of Pure and Applied Chemistry. Analytical Chemistry Division, 1978. Nomenclature, symbols, units and their usage in spectrochemical
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analysis-III. analytical flame spectroscopy and associated non-flame procedures. Spectrochim. Acta B 33 (6), 247e269. Ji, Y., Feng, Y., Wu, J., Zhu, T., Bai, Z., Duan, C., 2008. Using geoaccumulation index to study source profiles of soil dust in China. J. Environ. Sci. 20 (5), 571e578. Kothai, P., Saradhi, I.V., Pandit, G.G., Markwitz, A., Puranik, V.D., 2011. Chemical characterization and source identification of particulate matter at an urban city of Navi Mumbai, India. Aerosol Air Qual. Res. 11, 560e569. Lara, L.L., Artaxo, P., Martinelli, L.A., Camargo, P.B., Victoria, R.L., Ferraz, E.S.B., 2005. Properties of aerosols from sugar-cane burning emissions in Southeastern Brazil. Atmos. Environ. 39, 4627e4637. Loyola, J., Arbilla, G., Quiterio, S.L., Escaleira, V., Minho, A.S., 2012. Trace metals in the urban aerosols of Rio de Janeiro city. J. Braz. Chem. Soc. 23 (4), 628e638. Manalis, M., Grivas, G., Protonotarios, V., Moutsatsou, A., Samara, C., Chaloulakou, A., 2005. Toxic metal content of particulate matter (PM10), within the Greater Area of Athens. Chemosphere 60, 557e566. Marcazzan, G.M., Vaccaro, S., Valli, G., Vecchi, R., 2001. Characterization of PM10 and PM2.5 particulate matter in the ambient air of Milan (Italy). Atmos. Environ. 35, 4639e4650. Mihajlidi-zelic, A., Relic, D., 2005. Differentiation of the contribution of local resuspension from that of regional and remote sources on trace elements content in the atmospheric aerosol in the Mediterranean area. Atmos. Environ. 39, 6271e6281. Müller, G., 1969. Index of geoaccumulation in sediments of the Rhine river. Geojournal 2, 108e118. Pateraki, S., Asimakopoulos, D.N., Bougiatioti, A., Maggos, T., Vasilakos, C., Mihalopoulos, N., 2014. Assessment of PM2.5 and PM1 chemical profile in a multiple-impacted Mediterranean urban area: origin, sources and meteorological dependence. Sci. Total Environ. 479e480 (1), 210e220. Pereira, P.A.P., Lopes, W.A., Carvalho, L.S., Rocha, G.O., Bahia, N.C., Loyola, J., Quiterio, S.L., Escaleira, V., Arbilla, G., Andrade, J.B., 2007. Atmospheric concentrations and dry deposition fluxes of particulate trace metals in salvador, Bahia, Brazil. Atmos. Environ. 41, 7837e7850. ~o elementar Queiroz, P.G.M., Jacomino, V.M.F., Menezes, M.A.D.B.C., 2007. Composiça rico do município de Sete do material particulado presente no aerossol atmosfe Lagoas, Minas Gerais. Quimica Nova 30 (5), 1233e1239.
Quiterio, S.L., Silva, C.R.S., Arbilla, G., Escaleira, V., 2004. Metals in Airborne Particulate Matter in the Industrial District of Santa Cruz, Rio de Janeiro, in an Annual Period. Atmos. Environ. 38, 321e331. Rudnick, R.L., Gao, S., 2004. Composition of the continental crust. Treatise Geochem. 3, 1e64. Sturini, M., Maraschi, F., Cucca, L., Spini, G., Talamini, G., Profumi, A., 2010. Determination of vanadium (V) in the particulate matter of emissions and working areas by sequential dissolution and solid-phase extraction. Anal. Byoanal. Chem. 397, 395e399. Swaine, D.J., 2000. Why trace elements are important. Fuel Process. Technol. 65e66, 21e33. Taiwo, A.M., Beddows, D.C.S., Shi, Z., Harrison, R.M., 2014. Mass and number size distributions of particulate matter components: Comparison of an industrial site and an urban background site. Sci. Total Environ. 475, 29e38. Thorpe, A., Harrison, R.M., 2008. Sources and properties of non-exhaust particulate matter from road traffic: a review. Sci. Total Environ. 400 (1e3), 270e282. Valavanidis, A., Fiotakis, K., Vlahogianni, T., Bakeas, E.B., Triantafillaki, S., Paraskevopoulou, V., Dassenakis, M., 2006. Characterization of atmospheric particulates, particle-bound transition metals and polycyclic aromatic hydrocarbons of urban air in the centre of Athens (Greece). Chemosphere 65, 760e768. Voutsa, D., Samara, C., 2002. Labile and bioaccessible fractions of heavy metals in the airborne particulate matter from urban and industrial areas. Atmos. Environ. 36, 3583e3590. Watson, J.G., Chow, J.C., Houck, J.E., 2001. PM2.5 chemical source profiles for vehicle exhaust, vegetative burning, geological material, and coal burning in Northwestern Colorado during 1995. Chemosphere 43 (8), 1141e1151. WHO, 2003. Health Aspects of Air Pollution with Particulate Matter, Ozone and Nitrogen Dioxide. World Health Organization. Wilson, W.E., Chow, J.C., Claiborn, C., Fusheng, W., Engelbrecht, J., Watson, J.G., 2002. Monitoring of particulate matter outdoors. Chemosphere 49, 1009e1043. Wu, Z., Hua, M., Lin, P., Liu, S., Wehner, B., Wiedensohler, A., 2008. Particle number size distribution in the urban atmosphere of Beijing, China. Atmos. Environ. 42, 7967e7980. Igbewww.igbe.com.br Accessed 27 December 2016.
Please cite this article in press as: Almeida, T.S., et al., Characterisation and source identification of the total airborne particulate matter collected in an urban area of Aracaju, Northeast, Brazil, Environmental Pollution (2017), http://dx.doi.org/10.1016/j.envpol.2017.04.018