Comparison between XRF and IBA techniques in analysis of fine aerosols collected in Rijeka, Croatia

Nuclear Instruments and Methods in Physics Research B 337 (2014) 83–89

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Comparison between XRF and IBA techniques in analysis of fine aerosols collected in Rijeka, Croatia Tatjana Ivoševic´ a, Luka Mandic´ b,⇑, Ivica Orlic´ b, Eduard Stelcer c, David D. Cohen c a

Faculty of Engineering, University of Rijeka, Vukovarska 58, HR-51000 Rijeka, Croatia Department of Physics, University of Rijeka, Radmile Matejcˇic´ 2, HR-51000 Rijeka, Croatia c Institute for Environmental Research, Australian Nuclear Science and Technology Organisation, Kirrawee DC, NSW 2232, Australia b

a r t i c l e

i n f o

Article history: Received 27 March 2014 Received in revised form 16 July 2014 Accepted 19 July 2014

Keywords: IBA XRF PM2.5 Aerosol Rijeka

a b s t r a c t The new system for energy dispersive X-ray fluorescence (EDXRF) analysis has been installed at the Laboratory for Elemental Micro-Analysis (LEMA) at the University of Rijeka. Currently the key application of this new XRF system is in the field of environmental science, i.e. in the analysis of fine airborne particles. In this work, results of initial multi-elemental analysis of PM2.5 fraction is reported for the first time in the region of Rijeka, Croatia. Sampling was performed at the Rijeka City center, during a continuous 9-day period in February/March 2012. All samples were collected on stretched Teflon filters in 12 h periods. To check the reliability of the new XRF system, results of XRF analysis are compared with the results obtained by the well-established Ion Beam Analysis (IBA) laboratory at Australian Nuclear Science and Technology Organisation (ANSTO). The concentrations of H, Na, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Br and Pb were determined. In addition, black carbon was determined by Laser Integrating Plate Method (LIPM). Very good agreement between XRF and IBA techniques is obtained for all elements detected by both techniques. Elemental concentrations were correlated with the traffic volume and wind speed and direction. The summary of our findings is presented and discussed in this paper. Ó 2014 Elsevier B.V. All rights reserved.

1. Introduction The European Union Council Directive 2008/50/EC [1] has attributed great importance to the monitoring of fine particulate matter (PM2.5) in Europe. This fraction has significant implications for human health as fine particles freely enter lungs and soft tissues [2–4]. Long-term exposure to fine aerosol fractions leads to a chronic cough, bronchitis, atherosclerosis, inflammation of the blood vessels, increased risk of lung and heart disease and ultimately to an increase in mortality [5–7]. The conclusion of a number of studies [8] is that the fine aerosol fraction is a key factor causing pollution related deaths in Europe today. This influenced the revision of PM2.5 annual limit value (LV) to 25 lg/m3 by year 2015 and it will become progressively more restrictive by 2020 [1]. Regarding single elements, only limit and/or target values for Pb, Ni, As, and Cd in PM10 fraction are defined. There are no limit or target values for elements in PM2.5 fraction. However, many studies on elemental composition of PM2.5 indicate the importance of such analysis as a basis for source apportionment [9–13].

⇑ Corresponding author. Tel.: +385 51 584 617. E-mail address: [email protected] (L. Mandic´). http://dx.doi.org/10.1016/j.nimb.2014.07.020 0168-583X/Ó 2014 Elsevier B.V. All rights reserved.

In this work, results of initial multi-elemental analysis of PM2.5 fraction collected in Rijeka, Croatia are presented. This is the first time that such data are reported for this urban area. Part of analysis was performed at recently established Laboratory for Elemental Micro-Analysis (LEMA) at the Department of Physics, University of Rijeka. The main objective of this study was to calibrate new XRF spectrometer and to test its reliability. For that purpose, the same fine-aerosol samples were independently analyzed by XRF in Rijeka and by the well-established Ion Beam Analysis (IBA) laboratory at Australian Nuclear Science and Technology Organisation (ANSTO). This is the laboratory with a good track record and with over twenty years of experience in this field [14,15]. For the simultaneous analysis of over twenty elements typically found in aerosol samples, the IBA laboratory is typically using three complementary IBA techniques such as Proton Induced X-ray Emission (PIXE), Proton Induced Gamma-Ray Emission (PIGE) and Proton Elastic Scattering Analysis (PESA). PIXE is generally used for quantification of elements from Al to U, and it is therefore often selected as comparative method for XRF in many studies [16–20]. Those studies show a generally good agreement between PIXE and XRF results, which can be contributed to the fact that the same samples can be used for both analysis without any pre-treatment. Additional concentration data obtainable by PIGE (Na, Mg, and F) and PESA (H) are out

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of the scope of XRF, but they are very important for the total mass reconstruction [13,21].

2. Experimental 2.1. Sample collection Rijeka is the largest Croatian port, and the third city by size in the Republic of Croatia. It has about 130; 000 inhabitants. The sampling site was located next to the busy street (Trpimir Str, TS in Fig. 1) in the city center with the intention to measure air pollution produced by traffic. The sampler was positioned 6 m above the sea level and 5 m above the road level. Another source which may significantly contribute to the air pollution in Rijeka is the industrial complex which is located 9 km eastward from the city center and comprising of 320 MW oil powered thermal plant (TPP) and the oil refinery (Fig. 1). Samples were collected during daytime (6AM–6PM) and nighttime (6PM–6AM) separately, with intention to easily identify traffic fingerprint. Sampling was started on February 24th 2012 (6PM) and ended on March 4th 2012 (6AM). In total, 18 samples were collected. Traffic volumes as counted by the Road authority of Rijeka varied between 800 and 1200 cars/h during daytime, and between 400 and 600 cars/h during nighttime periods. Collaboration with ANSTO was not only confined to laboratory analysis: ANSTO also provided LEMA with aerosol sampling unit designed for their Aerosol sampling project (ASP Unit). PM2.5 air particulate samples have been collected on a stretched Teflon filters (PALL Corporation R2P1025, diameter of 25 mm, 3 lm pore size) with the flow rate of 15–17 l/min. We are aware of the fact that filter diameter is smaller than the one prescribed by the Eu regulation (25 mm instead of 47 mm). However, the airflow rate was chosen to ensure that the cycling cut-off size is 2.5 lm and at the same time the areal density of collected material is very similar to the one that would be obtained with prescribed Eu standard conditions. Beside our sampling location (TS PM2.5), Fig. 1 also shows sampling locations of government institutions whose data were used in this work for comparison with our data. Government sampling sites are managed by the Teaching Institute of Public Health of the Primorsko-goranska county (TIPH) and National network for continuous air quality monitoring (NN). TIPH is measuring PM10

and PM2.5 fractions (by gravimetric method) and elemental concentration of Pb, Fe, Ni, Cu, and Zn in PM10 fraction by atomic absorption spectrometry (AAS). At NN sampling site, only PM10 is measured. As it can be seen from Fig. 1 TIPH-1 and NN locations are close (600–700 m) to our sampling site, while TIPH-2 and TIPH-3 are located near the industrial complex. 2.2. Analysis All aerosol samples were first analyzed by XRF technique at LEMA laboratory followed by IBA techniques at ANSTO. XRF analysis was performed in the air. A low-power rhodium X-ray tube (by X-ray Optical Systems, model X-Beam) was used (50 kV, 1 mA) for excitation. Collimated beam with a diameter of 2 mm and perpendicular to the sample surface was used to scan the sample area of 8  8 mm2. Characteristic X-rays were measured with thermoelectrically cooled silicon drift detector Amptek X-123SDD (energy resolution of 145 eV for Fe-Ka line) positioned at 45 relative to sample surface normal (see Fig. 2). A detector collimation was arranged to confine the field-of-view of detector to the sample area which is slightly larger than irradiated sample area. This has reduced Ar signal from the air and blocked Pb signal from shielding. Samples were irradiated for 3600 s. XRF spectra were fitted using AXIL software package [22]. At ANSTO, aerosol samples were analyzed using acceleratorbased IBA techniques: PIXE, PIGE and PESA. They were applied simultaneously using an 8 mm diameter, 12 nA beam of 2.6 MeV protons and collection charge of 3 lC. These techniques can measure the following most commonly occurring elements in fine particles: H, Na, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Br and Pb and have been described in details elsewhere [9–12]. Additionally, the black carbon (BC) was determined using the Laser Integrating Plate Method (LIPM) assuming a mass absorption coefficient of 7 m2/g [23]. 3. Results and discussion 3.1. Calibration of XRF system XRF system was calibrated with two sets of thin foil standards supplied by the Micromatter Co; one set with Mylar and the other with Nuclepore as support. Nominal area densities of certified

Fig. 1. Locations of sampling site (TS - Trpimir Street) and other relevant air monitoring stations of interest (TIPH - Teaching Institute of Public Health, NN - National network, MHS - Meteorological and Hydrological Service) in Rijeka, Croatia. Locations of major pollutants are also shown (Refinery and Thermal Power Plant (TPP)).

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3.2. Comparison of XRF and PIXE results In this section minimum detection limits (MDL) and concentration ratios obtained by PIXE and XRF techniques are compared. For XRF technique, the minimum detection limit ðMDLS Þ of surface concentration was calculated by using the following equation:

MDLS ¼

pffiffiffiffiffi 3 AB ItK

ð2Þ

where AB stands for background counts in 3r region below the K a X-ray line, K is the sensitivity, I is the X-ray tube current and t is the irradiation time. The minimum detection limit of the volume concentration (MDL) was obtained as

MDL ¼ MDLS  Fig. 2. Diagram of the XRF setup at LEMA.

materials were in the range between 15 and 50 lg/cm2 with uncertainties quoted as 5%. The following materials were used for calibration: Al, SiO, KCl, CaF2, ScF3, Ti, V, Cr, Mn, Fe, Ni, Cu, ZnTe, GaP, Ge, SrF2, and MoO3. The sensitivity K i for an element i was calculated as

Ki ¼

Pi Itci

ð1Þ

where P i stands for peak intensity of corresponding K a line obtained from irradiation of standard material, ci is the certified area density of element i in standard material, I is the X-ray tube current, and t is a measuring time. Obtained sensitivities for XRF are shown in Fig. 3. Squares and rhomboids indicate sensitivities obtained by reference materials on Mylar and Nuclepore supports, respectively. Measured data are fitted by a smooth polynomial function. Accepted values for further calculation are represented with dots. For elements where no reference materials were available (S, Co), respective sensitivities were obtained by interpolation. Sensitivity rapidly decreases for Z < 18 due to attenuation of X-rays in the air and detector window. In Z > 40 region, sensitivity by means of K a rays decreases as well due to relatively thin active layer of detector. Among elements with L lines typically measured, only Pb was detected in our samples. The corresponding sensitivity of 3300 cts lg1 cm2 A1 s1 for Pb L lines was approximated from measured multielemental standards containing Pd, Ag, Sb, Pt, Au, and Bi, also provided by Micromatter Co.

Fig. 3. Sensitivity of XRF LEMA system for excitation and detection of K a rays.

S V

ð3Þ

where S is the filtration surface area, and V is the sampled air volume. Averaged MDL values for PIXE (ANSTO) and XRF (LEMA) are shown in Fig. 4. Left hand-side scale corresponds to mass concentration in air, while right hand-side scale corresponds to areal density on the filter. It is obvious that PIXE technique has much better detection limits for low-Z elements. This result is expected as PIXE cross sections are higher for low-Z elements, and in addition measurements are performed in a vacuum. Due to this XRF limitation, no reliable concentrations of Al, Si, and P are reported in this work. In the low-middle-Z range, PIXE has only slightly better detection limits than XRF. There is a peak in MDL at Cl and Co for XRF technique as the K a line of Cl overlaps with Rh L lines present in XRF excitation spectrum, while K a line of Co interferes with Kb of Fe. Fig. 4 also shows MDLs of two other ED-XRF spectrometers, found in literature. Data labelled as XRF (Cal) were reported by Calzolai et al. [16]. Their measurements were performed in vacuum and in two different configurations. The first configuration was optimized for low-Z elements (Al to P) and it provided detection limits that are lower than PIXE. The second configuration was optimized for the low-middle-Z range and resulting MDL values were similar to those obtained with our set-up. Among the commercial ED-XRF spectrometers, we have selected PANalytical Epsilon 5 XRF analyzer for comparison. Corresponding data were extracted from Zhang et al. [24] and are labelled with XRF (Zha). Epsilon 5 uses three-dimensional polarizing geometry with 11 secondary targets. Here, MDL for specific element is optimized by secondary target selection. Although such system provides better signal to background ratio, measurements cannot be performed simultaneously for all elements. Finally, MDLs for some elements (Mn, Fe, Cu) are identical to ours, and up to 4 times better for other elements in the low-middle-Z range.

Fig. 4. Minimum detection limits of XRF and PIXE techniques for measured elements.

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The summary of measured elemental concentrations is presented in Table 1 in the form of medians, quartiles and maxima. For each element, number of samples ðNÞ with corresponding concentration above MDL is given. Within IBA analysis, 18 elements were found in at least one sample by PIXE and H by PESA. PIGE did not provide any significant data for presence of Na and Mg. In XRF measurements, 17 elements were found by means of N P 1. Statistical data are also provided for elements where N ¼ 0. To compare XRF and PIXE results, concentration ratios for each sample were calculated. Ratios for Al, Si, P, Cl and Co were not included in this analysis as the majority of XRF concentrations were below one half of MDL. Box and whisker plot of obtained data set is presented in Fig. 5. Two groups of elements can be distinguished according to quartiles. Elements with smaller inter-quartile ranges (S, K, Ca, Fe and Zn) correspond to major elements, i.e. elements with concentration significantly above the MDL for XRF. Larger inter-quartile ranges are typical for minor elements, in this case, Ti, Cr, Mn, Ni, Cu, and Br. Most of the medians are very close to the unity, indicating that obtained PIXE and XRF concentrations are nearly identical. Measured elemental concentrations obtained by PIXE and XRF techniques are shown in Fig. 6(a–f) and (i–l) as a function of sampling periods. Only elements with concentrations close to MDL (Ti, V, Mn, Ni) or above MDL (S, K, Ca, Fe, Cu, Zn) for XRF technique are shown. Analyzed samples are numbered starting from #1 (24 February 2012/ nighttime) to #18 (4 March 2012/ daytime), according to aerosols collecting chronology. Odd numbers with black background represent samples collected during nighttime (from 6PM to 6AM), while even numbers with white background represent daytime periods (from 6AM to 6PM). In addition, in Fig. 6 other related data are shown: total hydrogen obtained from PESA spectra (H in Fig. 6(m)); black carbon (BC in Fig. 6(n); wind speed and direction records (Fig. 6(g); traffic volumes (Fig. 6(h)); and PM10 data (Fig. 6(o)) as measured independently by the National network for continuous air quality monitoring (NN in Fig. 1) [25]. Results of PIXE and XRF are in very good agreement especially for elements with concentrations above MDL for XRF. Total errors for PIXE derived concentrations are in the range from 5% to 10% for all major elements [26]. On the other hand, errors for XRF concentrations are somewhat higher (7–30%) especially for elements (Ti, V, Ni) that are close to detection limits. Still, as it can be seen from Fig. 6 data trends for all measured elements are nearly identical for both techniques.

Fig. 5. XRF to PIXE ratios of the measured elemental concentrations.

3.3. General observations The high level of air pollution within the Rijeka basin was visually observable as a gray haze during #1, #2, and #3 sampling periods. This was confirmed by our measurements as nearly all elemental concentrations were higher. Time series in Fig. 6 shows that initially higher concentration dropped to a very low level on the second day of sampling (at #4). Fig. 6(g) shows averaged wind speed and direction for the same periods of aerosol sampling, calculated from hourly records of the local weather station which is managed by the Meteorological and Hydrological Service (MHS). Vertical line plotted at sample #4 through all the graphs suggests that sudden drop of concentrations could be due to increased wind speed. In #4 to #6 sampling periods average wind speed increased from 0:52 m/s to 3:0 m/s. Starting from sampling #7 wind speed decreased and elemental concentrations increased again. Indeed, for all measured elements high negative correlations with wind speed throughout the whole sampling period were calculated (0:85 < r < 0:7). We are certain that changes in concentration were not caused by the activity from a local industry as the thermal power plant was not operational during the sampling period and the oil refinery worked steadily with a typical load. As it can be seen from the Fig. 1, City of Rijeka is a coastal town situated at NE coast of the Kvarner Bay (Adriatic Sea). It is open to the sea on the south and surrounded by high mountains on N, E and W

Table 1 Median, quartile range and maximum of concentrations (in ng/m3) for elements in PM2.5 fraction collected in Rijeka. N stands for the number of samples with concentration above MDL. Element

H (PESA) Al Si P S Cl K Ca Ti V Cr Mn Fe Ni Cu Zn Br Sr Pb

PIXE

XRF

N

Median

Q1–Q3

Max

N

Median

Q1–Q3

Max

18 17 18 17 18 2 18 18 14 14 4 17 18 9 18 18 12 0 8

1226 23.7 88.7 10.6 1262 1.7 314 118 4.4 8.3 1.4 13.0 426 2.7 15.6 41.8 6.1 0.0 9.4

753–2024 18.6–30.4 60.1–105.5 7.7–14.0 725–1641 0.7–3.2 179–534 101–162 3.3–6.2 3.8–13.0 1.0–2.1 4.8–16.8 241–504 1.5–4.2 7.5–19.9 22.8–60.5 4.8–9.6 0.0–1.4 4.6–17.0

3151 66.6 167 94.7 2195 11.7 957 239 9.5 25.9 5.4 23.8 785 10.6 81.7 104 20.3 12.5 57.1

2 1 18 0 18 18 11 13 1 15 18 8 18 18 15 2 12

78.6 13.5 1282 1.5 285 134 4.7 8.6 1.7 13.2 409 2.7 14.1 42.0 5.3 0.0 10.2

49.5–93.4 9.7–16.2 705–1596 0.0–3.4 201–504 84–175 3.0–6.3 4.0–12.1 1.2–2.3 5.1–17.9 232–515 2.0–5.2 8.3–24.8 21.2–62.5 4.1–7.3 0.0–1.0 3.8–18.0

149 55.7 2348 11.3 960 258 9.6 26.3 3.8 23.9 814 10.7 74.7 106 13.2 10.1 55.4

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Fig. 6. Time series of measured PIXE and XRF concentrations of nine elements (S, K, Ca, Ti, V, Mn, Fe, Cu, Zn), black carbon (BC), and selected PM2.5 and PM10 data from other sources. Additionally, the corresponding traffic volumes, and wind speed and direction are given to indicate possible influence on concentrations.

sides. This configuration of the terrain probably contributes to the accumulation of aerosol during calm periods and efficient air clearing when northerly breezes are present, which was demonstrated in our sampling period (#4 to #6).

In this work, we performed aerosols collection in daytime and nighttime regimes to investigate the correlation between traffic volume and pollution. The total number of vehicles during the sampling periods is shown in Fig. 6(h). Positive correlation was

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Table 2 Comparison of selected metal concentrations from this work (in PM2.5 fraction) with available TIPH data for metals in PM10 fraction. Concentrations are given in ng/m3.

Pba Nib Fe Cu Zn a b c

This work

TIPH-1

TIPH-2 & 3

14  14 4.0  3.0 390  190 19  17 44  26

6.0 540c 58c 53c

12 15 -

Limit value = 500 ng/m3. Target value = 20 ng/m3. Average value for 2009–2010 (no data for 2012).

elements between S and Zn. Accelerator-based techniques used by ANSTO are clearly superior to our XRF system as there are often three complementary techniques used, i.e. PIXE, PIGE and PESA. Still, it is encouraging that relatively simple and inexpensive XRF system provides satisfactory detection limits. To improve detection limits for low Z elements (Al, Si, P, Cl, K) we intend to upgrade our XRF experimental setup by introducing helium atmosphere. A very strong dependence of local air pollution on wind speed and direction within the Rijeka basin was confirmed. No significant correlation between PM2.5 elemental composition and traffic intensity was found. Acknowledgements

expected between BC (Fig. 6(n)) and traffic volume [27]. However, statistical analysis has shown that traffic volume was not correlated with any of measured elements. Within measured elements, only potassium shows significant variations between nighttime and daytime concentrations (Fig. 6(b)). Concentration ratios between night and day periods for potassium are ranging from 1:4 to 7:7 with the mean value of 2:9  1:9. This phenomena is often reported by a number of authors and is attributed to a wood burning process used for residential heating that is more frequent at nighttime periods [13,27,28]. Vanadium and nickel were highly positively correlated with each other (r ¼ 0:88). Our average V/Ni ratio of 2:2  0:7 lies within typical range 1–3 for heavy oil combustion [29]. 3.4. Comparison with other published data In Fig. 6(o) time variations of PM10 concentrations at NN site are shown. The NN location was chosen as it was the only sampling site with available hourly concentrations. For this study, NN hourly PM10 values are averaged over 12 h periods to correspond to sampling time. Those data confirm trend found for elemental concentrations. As expected, average PM10 concentrations at the industrial site (TIPH-2&3 as average of TIPH-2 and TIPH-3) are higher than the corresponding concentrations measured at the city center location (NN). In the insert that follows (Fig. 6(p)), PM10 and PM2.5 concentrations obtained at the same site (TIPH-2) and with the same method are shown. As expected, PM10 values are approximately 10% higher than PM2.5 values. In Table 2, selected metal concentrations reported in this work are compared with available average concentrations for metals in PM10 fraction as reported in TIPH Annual reports [30–32]. There are no available hourly concentrations for these metals. When compared to TIPH-1 data, our values are very similar or within standard deviation for Pb, Fe and Zn. The only exception is Cu, which is approximately three times higher at TIPH-1 location. It must be noted here that TIPH-1 PM10 data shown in Table 2 for Pb, Fe, Cu and Zn are estimated as average concentrations for 2009 and 2010 as corresponding values for 2012 were not available. It is also interesting to note that concentrations of Ni at TIPH-2 industrial site is approximately 4 times higher then our value. 4. Conclusion In this work, detailed multi-elemental analysis of fine aerosols pollution in the region of Rijeka is reported for the first time. Samples were analyzed independently by means of new experimental XRF setup at LEMA and accelerator-based techniques at ANSTO. A very good agreement between XRF and PIXE results is obtained demonstrating that our XRF system provides reliable data for all

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