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Determination of trace elements in ambient aerosol samples
Analytica Chimica Acta 540 (2005) 269–277
Determination of trace elements in ambient aerosol samples Natalie J. Pekney a , Cliff I. Davidson a,b,∗ a
Department of Civil and Environmental Engineering, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA b Engineering and Public Policy, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA Received 6 December 2004; received in revised form 19 March 2005; accepted 22 March 2005 Available online 25 April 2005
Abstract A microwave-assisted digestion procedure using HNO3 , HF, and H2 O2 has been developed for analysis of elements in ambient particulate matter (PM). The samples are collected on cellulose filters and analyzed by inductively coupled plasma mass spectrometry (ICP-MS). The ICP-MS is calibrated with external standards, and recovery of analytes is tested with NIST SRM 1648 Urban Dust. This method has been used to quantify the airborne concentrations of a large number of elements, including Ag, As, Ba, Be, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, K, Li, Mg, Mn, Mo, Ni, Pb, Rb, Se, Sb, Sr, Ti, Tl, V, and Zn. For the majority of these elements, recovery of the NIST SRM is within 15% of the certified values. © 2005 Elsevier B.V. All rights reserved. Keywords: Trace elements; Atmospheric aerosols; Inductively coupled plasma-mass spectrometry; Microwave digestion; Cellulose filter
1. Introduction Trace element concentrations in atmospheric aerosols are now widely used in source–receptor modeling studies. However, obtaining such data requires collection of a large number of samples and a cost- and time-effective method of analysis. Sample preparation varies, but one popular method is microwave-assisted digestion of filter-based samples. This method is appealing for analyses that require liquid samples, due to the ease and low contamination levels with which samples can be prepared. Analysis methods also vary; inductively coupled plasma-mass spectrometry (ICP-MS) as used here has low detection limits, large linear dynamic range and simultaneous multi-element output data. However, because ICP-MS requires a liquid sample, accurate measurements are dependent on the sample extraction efficiency. Other analysis techniques include graphite furnace atomic absorption spectrometry (GFAAS), proton-induced X-ray emission spectrometry (PIXE), and X-ray fluorescence (XRF). GFAAS has comparable detection limits to those of ICP-MS, but does not ∗
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have the capability of simultaneous multiple element measurement and therefore is not time-effective. PIXE and XRF are both non-destructive analysis techniques but detection limits are much higher, two orders of magnitude for some elements, as compared to ICP-MS. The choice of digestion reagents is an important consideration for measurement of multiple elements in ambient aerosols. Atmospheric particulate matter (PM) includes primary emissions of carbonaceous and metallic particles from combustion and industrial processes, crustal material from erosion of soil and rock, and secondary pollutants such as sulfates, nitrates and organic aerosols, among other species. The reagents chosen must digest the sample as completely as possible and keep the elements stable in solution. Nitric acid can accomplish this for many elements; however, it cannot completely digest silicon-containing compounds and the elements bonded to siliceous material. Previous groups have used relatively large amounts of hydrofluoric acid (HF) to break the silica bonds despite the fact that HF is extremely hazardous and therefore difficult to work with. Jalkanen and Hasanen [1] used a 3:1 mixture of HNO3 and HF in a total volume of 2.0 mL. Yang et al. [2] used a digestion solution of 5 mL HNO3 , 4 mL H2 O2 , 0.5 mL of HF, and 5 mL of H3 BO3 .
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If the silica content of the samples can be measured or estimated, the use of HF can be minimized. In this paper, we examine the use of trace amounts of HF in digesting aerosol filter samples for trace element analysis. We begin by using a certified NIST standard reference material (SRM) to test the recovery of trace elements using the digestion procedure developed here. Next, we apply the digestion procedure to ambient PM2.5 and PM10 collected in Pittsburgh, PA on cellulose filters with analysis by ICP-MS. We then compare SRM samples digested with and without HF to quantify the influence of using this acid. Finally, we compare the ambient PM analysis by ICP-MS using the new digestion procedure with non-destructive analysis by X-ray fluorescence (XRF) for samples collected at other sites in the Pittsburgh region.
2. Experimental The Pittsburgh Air Quality Study (PAQS) took place during July 2001–September 2002. The study included more than 20 different types of analyses of gas and aerosol samples, including analysis of trace elements in aerosol particles. Most samples were collected at the main monitoring station in Schenley Park, adjacent to the Carnegie Mellon University campus [3]. This location is approximately 6 km east of downtown Pittsburgh in the densely populated neighborhood of Oakland. Ambient air was sampled for concentrations of elements using PM10 and PM2.5 high-volume (hi vol) samplers from Andersen Instruments Inc. (Smyrna, Georgia) using 20 cm × 25 cm filters. The hi vols operated at a flow rate of 1.13 m3 /min, and they were specially equipped with brushless motors to minimize contamination. Many types of Teflon filters are commercially available, and these filters are useful for non-destructive analysis methods such as XRF or proton induced X-ray emission. In the current study, cellulose filters (Whatman 41, Whatman Inc., Clifton, NJ) were used as they completely digest in the acids, leaving a liquid solution for injection into the ICPMS. Retention efficiency of the Whatman 41 filters varies with particle size, with a minimum value at 0.3 m diameter of 92% at a face velocity of 45.2 cm/s. [4]. This is admittedly somewhat lower than the minimum 99.7% retention efficiency for Teflon filters [5]. However, the efficiency is over 99% for particles larger than 1.0 m diameter [4]. 2.1. Reagents All reagents were purchased in the purest form available: redistilled nitric acid (70%) and custom redistilled 70% nitric/0.5% hydrofluoric acid blend from GFS Chemicals (Columbus, OH), as well as semiconductor grade hydrogen peroxide (30–32%) from Sigma Aldrich (St. Louis, MO). Distilled, deionized water from a NANOpure ultrapure water system was used (Barnstead/Thermolyne, Dubuque, IA).
Fig. 1. Temperature-controlled program for the MARS 5 digestion method.
2.2. Microwave description The microwave used was a MARS 5 (CEM Corp., Matthews, NC) equipped with an EST-300 Plus temperature sensor and an ESP-1500 Plus pressure sensor. The microwave digestion vessels, HP500 Plus, had working maximum pressure and temperature of 2.4 × 10 N/m and 195 ◦ C, respectively. The microwave could accommodate digestion of up to 14 samples simultaneously. For sample preparation, Standard EPA Method 3052 was followed with some adaptations [6]. The microwave method developed for sample digestion was controlled by temperature and is illustrated in Fig. 1. The slower ramp time between 105 and 135 ◦ C allowed for slower decomposition of the cellulose filter material without a very large or very rapid increase in pressure. 2.3. ICP-MS description Analyses were performed at Duquesne University using an Agilent 4500 ICP-MS (Agilent Technologies, Palo Alto, CA). The ICP-MS was equipped with a concentric nebulizer and a quartz torch. Operating parameters are listed in Table 1. All other parameters, such as torch position, sample depth, extraction, and ion focusing lenses voltages, Omega lenses voltages, quadrupole settings, and carrier and blend gas flow rates were tuned at the start of each analysis session such that the sensitivity was optimized. Oxides and doubly charged ion ratios were kept below 2%. Table 1 ICP-MS operating parameters RF power (kW) RF matching (V) Plasma gas flow rate (L/min) Auxiliary gas flow rate (L/min) Peristaltic pump flow (rps) Measurement mode Number of measurements per peak Integration time Number of repetitions Time per sample measurement (min) Rinse time (min)
1.4–1.5 1.99 15 1 0.10 Spectrum analysis mode 3 (full quant. mode) 0.10 s/point 3 2–3 1
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2.4. Filter handling Filters were handled in ways to minimize contamination. Blank filters were handled identically to the samples, but were run on the hi vol for only 1 min. For the first two months of the study, field blanks were taken once per filter change. Subsequently, field blanks were taken once weekly. For the majority of the study period, 24-h samples were taken. After collection of the samples, filter cassettes were delivered to the laboratory in clean, sealed bags. Filters were removed from the cassettes under a laminar flow hood and cut into strips using a polypropylene template and disposable stainless steel knife blades. Cutting the filter into smaller sections was necessary to get the sample mass below 0.5 g, which is the working limit of the microwave vessels, and also allowed for comparison of analysis results from multiple strips per filter. For the first two months of the study, the filter-cutting template made seven strips per filter, each sized 2.5 cm × 17.8 cm. Subsequent filters were cut with a larger template, which made six strips per filter, sized 3.2 cm × 17.8 cm. Individual filter strips were transferred to sterilized polypropylene centrifuge tubes (tested to be clean for metals) and labeled, sealed in a clean plastic bag (KNF Clean Room Products Corp., Ronkonkoma, NY) and stored in a freezer to minimize biological activity until digestion and analysis. With the exception of the filter loading and removal at the sampling site, all work was conducted under HEPA-filtered laminar flow hoods. 2.5. Sample preparation We can estimate the amount of HF needed to dissolve all of the silicate material in a typical sample. Based on Rees et al. [7], the crustal component of the samples is estimated to account for about 4% of the PM2.5 mass. For the hi vol samples collected at the main site, the annual average 24-h air volume was 1630 m3 and the annual average PM2.5 mass concentration was 17 g/m3 . If we assume conservatively that all crustal mass was SiO2 , the typical amount of Si in a strip comprising 1/6 of the total filter would be 1.8 × 10−4 g. The amount of HF necessary for complete digestion of the SiO2 can be determined from the following reaction: Heat
SiO2 + 4HF −→ SiF4 (g) + 2H2 O
(1)
Results show that 1.2 × 10−5 moles of HF (2.5 × 10−4 g), or less than 0.1% HF in the digestion solution, completely digests all of the crustal material in an average sample. A concentration of 0.5% HF was therefore chosen to digest the crustal material in all the samples. HF at this low concentration can be purchased already blended with nitric acid, and thus it is not necessary to use the stringent precautions invoked for more concentrated HF. Also, the sample introduction system for the ICP-MS does not have to be replaced with an expensive inert system needed for more concentrated HF. Only one quartz torch was used for the duration of this
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study that involved analysis of over 3200 samples during the course of one year. Hydrogen peroxide can reduce NO fumes as well as pressure in the closed microwave vessel. The pressure-reducing mechanism is described by the following chemical reactions [8]: Heat
2H2 O2 −→ 2H2 O + O2 (g)
(2)
2NO(g) + O2 (g) → 2NO2 (g)
(3)
2NO2 (g) + H2 O → HNO3 + HNO2
(4)
Boric acid is sometimes used to complex the HF at higher concentrations but was not used here. Other reagents sometimes used include perchloric and hydrochloric acid, neither of which was used in this study since ClO, ClOH, and ArCl can cause interference problems in the measurement of As, Se, V, and Cr by ICP-MS [9]. Using Teflon-coated forceps, filter strips were transferred to the digestion vessels, the solution was added, and the vessels were capped. The digestion solution consisted of 9 mL custom redistilled 70% nitric/0.5% hydrofluoric acid blend and 2 mL hydrogen peroxide. After digestion in the microwave, the vessels were transferred to the CEM Microvap assembly, connected to a vacuum pump, and heated in the microwave until the volume of the sample decreased to approximately 0.5 mL. This allowed evaporation of the acid without loss of the analytes [10]. The samples were then removed and poured into sterilized, graduated sample cups already containing the internal standard solution. Deionized water was added to bring the total volume to 10 mL. Each sample contained 50 ppb of the internal standard solution because this concentration level was approximately mid-calibration range for most elements. The final acid concentrations in the samples were approximately 4% nitric acid and 0.02% hydrofluoric acid. 2.6. Analysis Samples were transported to the Duquesne University Laboratory clean room in airtight plastic containers. The ICPMS was tuned and calibrated. A check standard was analyzed after the initial calibration and subsequently after every 10 samples. If the measured check standard concentrations were not within 10% of actual concentrations, the instrument was recalibrated and the previous 10 samples were re-analyzed. If a sample concentration was higher than the highest calibration standard for an element, the sample was diluted and re-analyzed for that element. External ICP-MS calibration standards were custommade from SCP Science (Champlain, NY). Because of the great difference in concentrations of various elements in each sample, a standard stock solution was made to reflect these differences, and five calibration standards were mixed from the stock solution. Maximum standard concentration for elements of lowest concentrations in the samples was 200 ppb,
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while maximum for elements of highest concentrations was 8000 ppb. The multi-element internal standard solution, also from SCP Science, contained Sc, In, Tb, Ho, Y, and Bi. The internal standard solution was added to every external calibration standard and sample. Addition of the internal standard helped to account for matrix effects. Selection of the appropriate internal standard element for each sample element depends on similarities in mass number, ionization potential, and chemical characteristics. Table 2 shows selected internal standard elements for each analyte.
3. Results and discussion 3.1. Recovery of NIST standard reference material Success of the digestion procedure was measured by the recovery of elements in the NIST SRM 1648, Urban Dust, and also the agreement between two different strips per filter. For each batch of samples digested, one microwave vessel contained a measured mass of the SRM, approximately 1.0 mg to represent sample mass, in the same digestion solution. Also, one microwave vessel per digestion batch contained only reagents to examine contamination from the reagents. The reagent blank sample concentrations (RGB) were subtracted from the NIST SRM samples (SRMmeasured ) prior to calculating recovery. Percent recovery, %R, was calculated as: %R =
SRMmeasured − RGB × 100% SRMcertified
(5)
where SRMcertified is the concentration of the element in the SRM as certified by NIST. Minimum detection limits (MDLs) were established as per EPA Method 200.8 [9] and are listed for each element in Table 2. Where concentrations of elements in either the SRM or the RGB samples were below the MDL, they were replaced with the MDL as a conservative upper limit of the concentration, and were listed as an upper limit. For blank correction, typically either the SRM was many times the RGB or both the SRM and RGB were below the MDL; there were not a significant number of cases in which the subtraction of a RGB replaced by the MDL for an element resulted in a substantial decrease from the true concentration that would therefore render the recovery unacceptable. Elements in a sample for which either the measured concentration or the NIST certified concentration were less than two times the reagent blank concentration were flagged as below detection. Also in Table 2 is the number of samples analyzed that were above detection out of a possible total of 139. This total does not include values deleted due to a malfunction of the balance. Note that early tests of this method included a blank filter strip along with the NIST SRM in some samples; the presence of the filter strip did not affect the results and hence further
work with the SRM samples did not incorporate blank filter strips. Recoveries for each element are shown in Table 2. Data for Na and Al are unreliable and therefore are not given. All other elements are within the target recovery of 100 ± 15% with the exception of Cr (59%) and Cs (82%). The precision and accuracy of the results of this study compare well with recoveries of the NIST SRM 1648 reported by others, despite much higher concentrations of HF used in their studies. Jalkanen and Hasanen [1], using a 3:1 mixture of HNO3 and HF, report recoveries in the range of 80–98% for several elements in 10 samples with the exception of a very low recovery of Cr (28%). Yang et al. [2] and Wu et al. [11], both using a digestion solution of HNO3 /H2 O2 /HF/H3 BO3 report recoveries of 90–110% for several elements, with lower recoveries of 70% and 77% for Se and Cr, respectively, reported by Yang et al. Swami et al. [12] find similar recoveries for most elements at varying amounts of HF in a HNO3 /H2 O2 digestion solution. Precision and recovery of Se decreased with increasing amounts of HF, although recovery of Cr improved. The low recovery of chromium in the NIST SRM 1648 is a documented problem [13]. It has been hypothesized that the high soot content of NIST SRM 1648 signifies the presence of organic material that somehow inhibits dissolution of all the chromium [1]. Most of the samples had concentrations below detection for Cs. Therefore, the low recovery of Cs is likely due to detection limit problems. The SRM did not have certified concentrations for several elements analyzed, namely Li, Be, Ca, Ga, Sr, Mo, and Tl. 3.2. Trace elements in ambient PM Data from either two or three filter strips have been averaged for every filter used in this study to report airborne concentrations [14]. However, agreement between filter strips is discussed here only for two typical months, October 2001 (two strips per filter) and January 2002 (three strips per filter). Ambient concentrations were determined by subtracting the average of the field blank filter mass from the filter sample mass, and dividing by the volume of air sampled. For a sample to be considered above detection, concentration must be greater than 3.3 times the standard deviation of the field blank concentrations [9]. Field blank concentrations varied by element, ranging from 0.001 to 4 ng/m3 . Table 3 shows the average difference between concentrations from the two strips divided by the daily average mass concentration for each element for the month of October 2001, termed the percent error. For both PM10 and PM2.5 , the average errors are almost always less than 30%. For the January 2002 filters, the relative standard deviation of the data from three strips was smaller than the values of the average percent error given in Table 3 for nearly all elements. These levels of error are acceptable for using the data with such source–receptor models as positive matrix factorization (PMF) and Unmix [14].
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Table 2 Percent recovery for each element Element
Internal standard element
Minimum detection limit (ppb)
Li Be Mg K Ca Ti V Cr Mn Fe Co Ni Cu Zn Ga As Se Rb Sr Mo Ag Cd Sb Cs Ba Ce Tl Pb
Sc Sc Sc Sc Sc Sc Sc Sc Sc Sc Sc Y Y Y Y Y Y Y Y Y In In In In In In Bi Bi
0.076 0.048 0.439 66.1 5.26 0.506 0.155 0.358 0.372 50.5 0.070 0.268 0.129 0.340 0.031 0.039 0.536 0.039 0.037 0.115 0.060 0.071 0.092 0.083 0.312 0.101 0.025 0.032
Number of samples above detection (139 total samples)
Recovery (%) (S.D., %) of NIST SRM 1648
125 139
96 (18) 96 (18)
139 139 139 139 139 118 137 139 139
86 (12) 103 (21) 59 (17) 95 (22) 102 (17) 91 (33) 96 (34) 93 (17) 97 (19)
139 121 136
89 (15) 88 (48) 85 (21)
86 139 129 28 139 69
85 (35) 95 (14) 87 (22) 82 (33) 105 (15) 97 (32)
130
95 (19)
For Ag, Ce, and Cs, a large fraction of the NIST samples were below detection because of significant reagent blanks. For all other elements, the NIST sample concentrations exceeded the reagent blanks by a factor of six or more except in two instances (Co and Rb). Certified concentrations were not given by NIST for some elements.
3.3. Comparison of recoveries from the SRM with and without HF To show that the addition of a trace amount of HF to the digestion solution improved recovery of the elements in NIST SRM samples, a batch of seven NIST samples, three with trace HF and four without HF, were prepared and analyzed according to the procedure described above. Table 4 presents the results of this comparison. The improved recoveries of the elements in the NIST SRM samples for K, Ti, Cr, Rb, Sb, Cs, and Ba were statistically significant with the addition of trace HF at the P = 0.05 level of significance. The other elements showed recoveries that were not statistically different between the two sets of samples with the exception of Mg. Recovery of Mg in these samples significantly decreased with the addition of HF, but recoveries of Mg as reported in Table 2 are quite good. The reason for the low recovery of Mg in the three samples digested with HF presented in Table 4 as compared to the good recovery of Mg in the samples reported in Table 2 is unknown. 3.4. Comparison of ambient PM analyzed by ICP-MS and XRF During July 2001 and January 2002, daily Teflon filter samples were collected at four satellite sites surrounding the
main Pittsburgh sampling site, and these filters were analyzed by XRF by Research Triangle Institute, Triangle Park, NC. The main Pittsburgh sampling site, the Lawrenceville site, and the Hazelwood site are located within the Pittsburgh city limits. The rural Florence site is located 50 km west of Pittsburgh, which is typically upwind of the city, and the Greensburg site is located 55 km east of Pittsburgh, typically downwind. More information about the locations of the four satellite sites and details of sample collection are given in Tang et al. [15]. Ambient concentrations of many elements analyzed by XRF appear noisy as compared to the ICP-MS results for the main site due to the smaller air volumes sampled for XRF analysis and the higher detection limits of XRF as compared to ICP-MS. Nevertheless, several elements with high concentrations show reasonable agreement, namely K, Ti, V, Mn, Fe, Zn, As, Se, and Pb. The correlation coefficient ρ and the number of valid samples for comparison n are shown in Table 5. Note that sampling at the Pittsburgh main site began on July 11, 2001, while sampling at the four satellite sites was continuous beginning on June 30 until July 31, 2001. Based on a two-tailed t-test with n − 2 degrees of freedom, the correlation coefficients were tested against the hypothesis that they were significantly greater than zero. The level of significance of the correlation is given in Table 5 as well. Figs. 2 and 3
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Table 3 A comparison of the concentrations measured on two different strips for samples collected in October 2001 Element
PM10
Li Be Mg K Ca Ti V Cr Mn Fe Co Ni Cu Zn Ga As Se Rb Sr Mo Ag Cd Sb Cs Ba Ce Pb
PM2.5
Number of samples above detection (31 total samples)
Percent error
Number of samples above detection (31 total samples)
Percent error
22 22 31 31 31 31 31 31 30 31 21 26 28 31 31 30 31 29 31 28 15 30 30 23 31 29 31
7.4 50.2 13.1 23.2 14.7 16.5 25.8 20.2 28.0a 7.1 37.0a 12.6 14.0 15.9 16.5 9.3 26.1 14.2 4.9 11.0 26.1 11.0a 16.6 24.6 9.1 10.8 12.1
20 19 31 31 30 29 29 28 30 31 13 22 14 26 23 30 31 25 26 19 14 28 26 17 31 13 30
6.6 16.5 8.7 9.5 14.1b 19.2 7.9 34.4 21.7b 21.3 21.9 21.8 17.6 9.4 36.8 8.3 9.6 4.6 19.9b 11.9 32.1 6.4b 35.9 6.0 29.0 13.9 5.6
All Tl concentrations were below detection in October 2001. a One outlier pair was removed from the full dataset for each of these elements (total 3 outlier pairs out of 769 pairs). b One outlier pair was removed from the full dataset for each of these elements (total 4 outlier pairs out of 670 pairs).
Table 4 A comparison of samples digested with and without trace HF
Mg K Ca Ti V Cr Mn Fe Co Ni Cu Zn As Se Rb Ag Cd Sb Cs Ba Pb
Samples digested without HF (n = 4)
Samples digested with HF (n = 3)
µ
µ
0.831 0.517 0.845 0.408 0.829 0.421 0.864 0.793 0.754 0.781 0.720 0.689 0.722 0.637 0.411 1.126 1.010 0.463 0.609 0.849 0.867
0.126 0.055 0.138 0.062 0.133 0.018 0.153 0.123 0.131 0.116 0.126 0.108 0.105 0.096 0.052 0.181 0.124 0.042 0.140 0.128 0.139
0.693 0.716 0.717 0.605 0.841 0.626 0.788 0.734 0.751 0.724 0.600 0.903 0.614 0.533 0.590 1.024 0.910 0.939 1.041 1.003 0.806
0.051 0.052 0.06 0.093 0.067 0.038 0.067 0.062 0.136 0.099 0.137 0.610 0.120 0.113 0.118 0.034 0.042 0.053 0.033 0.048 0.071
tobs
P-value
−1.99 4.87 −1.66 3.17 0.16 8.66 −0.89 −0.84 −0.03 −0.69 −1.19 0.60 −1.25 −1.23 2.45 −1.10 −1.50 12.75 5.95 2.20 −0.75
0.05 0.003 0.08 0.012 0.44 0.0002 0.21 0.22 0.49 0.26 0.14 0.29 0.13 0.13 0.029 0.16 0.10 0.00003 0.001 0.04 0.24
Average recovery, µ, is the measured concentration divided by the certified concentration and σ is the standard deviation of the recoveries for each element. The test statistic tobs , based on a student’s t-test, is given for each element and P-values are given for all elements.
Table 5 Comparison of ICP-MS data from the Pittsburgh Supersite and XRF data from the Lawrenceville, Hazelwood, Greensburg, and Florence sites Ti
V
Mn
Fe
Zn
As
Se
Pb
July 2001 Pittsburgh–Lawrenceville Pittsburgh–Hazelwood Pittsburgh–Greensburg Pittsburgh–Florence Lawrenceville–Hazelwood Lawrenceville–Greensburg Lawrenceville–Florence Hazelwood–Greensburg Hazelwood–Florence Greensburg–Florence
0.65/20/1% 0.53/19/2% 0.77/20/1% 0.63/20/1% 0.97/30/1% 0.93/31/1% 0.78/31/1% 0.87/30/1% 0.67/30/1% 0.87/31/1%
0.70/20/1% 0.36/19/NC 0.35/20/NC 0.35/20/NC 0.73/30/1% 0.59/31/1% 0.26/31/NC 0.60/30/1% 0.35/30/10% 0.37/31/5%
0.69/20/1% 0.76/19/1% 0.45/20/5% 0.48/20/5% 0.67/30/1% 0.70/31/1% 0.09/31/NC 0.10/30/NC 0.26/30/NC 0.18/31/NC
0.16/20/NC 0.10/19/NC 0.16/20/NC 0.05/20/NC −0.04/30/NC 0.00/31/NC 0.47/31/1% −0.18/30/NC −0.20/30/NC 0.14/31/NC
0.46/20/5% 0.28/19/NC 0.48/20/5% 0.40/20/10% 0.11/30/NC 0.73/31/1% 0.42/31/2% 0.00/30/NC −0.10/30/NC 0.37/31/5%
0.46/19/5% 0.09/19/NC −0.10/19/NC −0.06/19/NC 0.24/30/NC 0.06/31/NC 0.22/31/NC 0.07/30/NC −0.07/30/NC 0.23/31/NC
−0.14/19/NC −0.22/19/NC −0.04/19/NC 0.32/19/NC −0.32/30/NC 0.23/31/NC −0.35/31/NC 0.09/30/NC −0.06/30/NC 0.01/31/NC
0.65/19/1% 0.49/19/5% 0.47/19/5% 0.05/19/NC 0.70/30/1% 0.47/31/1% −0.08/31/NC 0.08/30/NC −0.04/30/NC −0.13/31/NC
0.65/19/1% 0.73/19/1% 0.35/19/NC 0.64/19/1% 0.42/30/2% 0.51/31/1% 0.44/31/2% −0.12/30/NC 0.27/30/NC 0.44/31/2%
January 2002 Pittsburgh–Lawrenceville Pittsburgh–Hazelwood Pittsburgh–Greensburg Pittsburgh–Florence Lawrenceville–Hazelwood Lawrenceville–Greensburg Lawrenceville–Florence Hazelwood–Greensburg Hazelwood–Florence Greensburg–Florence
0.66/18/1% 0.79/18/1% 0.79/21/1% 0.57/19/2% 0.82/16/1% 0.74/18/1% 0.63/18/1% 0.97/16/1% 0.62/16/1% 0.66/19/1%
0.10/18/NC 0.31/18/NC 0.53/21/2% 0.23/19/NC −0.29/16/NC 0.43/18/10% 0.21/18/NC 0.31/16/NC 0.25/16/NC 0.40/19/10%
0.03/18/NC 0.19/18/NC 0.09/21/NC 0.08/19/NC 0.09/16/NC 0.20/18/NC 0.35/18/10% −0.22/16/NC −0.39/16/NCa 0.39/19/10%
0.91/18/1% 0.55/18/2% 0.73/20/1% −0.31/19/NC 0.72/16/1% 0.70/18/1% −0.22/18/NC 0.36/16/10% −0.21/16/NC −0.06/19/NC
0.92/18/1% 0.89/18/1% 0.83/20/1% 0.10/19/NC 0.90/16/1% 0.88/18/1% 0.02/18/NC 0.86/16/1% 0.02/16/NC 0.09/19/NC
0.86/18/1% 0.95/18/1% 0.89/21/1% 0.16/19/NC 0.91/16/1% 0.92/18/1% 0.22/18/NC 0.93/16/1% 0.18/16/NC 0.32/19/10%
0.73/18/1% 0.30/18/NC 0.11/21/NC 0.60/19/1% 0.32/16/NC 0.32/18/10% 0.67/18/1% 0.47/16/10% 0.66/16/1% 0.60/19/1%
0.86/18/1% 0.93/18/1% −0.10/21/NC −0.07/19/NC 0.87/16/1% 0.00/18/NC 0.01/18/NC −0.03/16/NC −0.23/16/NC −0.08/19/NC
0.47/18/5% 0.60/18/1% 0.81/21/1% 0.52/19/5% 0.43/16/10% 0.46/18/10% 0.48/18/5% 0.66/16/1% 0.25/16/NC 0.34/19/10%
Given in each cell are: correlation coefficient, ρ; number of valid datapoints to compare, n; level of significance of correlation, tested at the 1%, 2%, 5%, and 10% level. Correlations not significant at the 10% level or better are listed as not correlated, NC. a Correlation is negative at the 10% significance level.
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K
275
276
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Fig. 2. Airborne concentrations during June 30–July 31, 2001 for the Pittsburgh Supersite and XRF data for four satellite sites in the Pittsburgh area. Concentrations are shown in g/m3 . () Pittsburgh; (䊉) Florence; ( ) Greensburg; () Lawrenceville; ( ) Hazelwood.
show time series graphs of these elements for the two months. Potassium correlation coefficients are high among all sites for both months. The large peak in early July 2001 is likely due to Fourth of July fireworks, as most fireworks contain potassium salts for ignition. Titanium concentrations are significantly correlated among the sites for July, but there is more scatter in the January XRF data and not as many of the site pairs are correlated. Concentrations of titanium are slightly higher on average during July as compared to January, so poorer correlations in January may be due to decreased detection capability of the XRF. Most site-to-site correlations of vanadium concentrations are insignificant in January. There is more day-to-day variability in the concentration data in July, and correlations are in general higher. Concentrations of manganese, iron, and zinc tend to be higher at the city sites, suggesting that there are significant sources of these elements within the city. Manganese and zinc concentrations show poor correlations between the sties in July. Correlations of iron data for July are significant for many of the site pairs. In January, the rural Florence site data do not correlate well with any other site for manganese, iron, and zinc, but the other sites are significantly correlated.
Fig. 3. Airborne concentrations during January 2–22, 2002 at the same sites as in Fig. 2. Concentrations are shown in g/m. () Pittsburgh; (䊉) Florence; ( ) Greensburg; () Lawrenceville; ( ) Hazelwood.
Arsenic shows reasonable agreement among all sites in January with most site-to-site correlations being significant, but there is more scatter in the XRF data in July where none of the site pairs correlate significantly. Concentrations on average are approximately equal for the two months. Selenium concentrations show some significant correlations but also several poorly correlated site pairs, especially in January. Concentrations of arsenic and selenium are relatively low in PM2.5 , making these elements more difficult to detect by XRF. Lead data show most sites significantly correlated for both months with the concentrations at the Lawrenceville site somewhat elevated on some dates. It is possible that there is a local source of lead near this site. Overall, there are many significant correlations between the Supersite and the satellite site data for July 2001 and January 2002. Instances of uncorrelated data could be due to differences in emissions at the five sites, not just analytical differences. The method developed here for measurement of trace element concentrations in ambient PM and analysis by ICP-MS compares reasonably well with non-destructive XRF analysis using different filter media. 4. Conclusions The method described in this paper for digestion and analysis of trace elements in ambient aerosol samples is suitable
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for routine analysis of the large number of samples commonly generated in air quality monitoring studies. Sample preparation by microwave digestion minimizes contamination and allows for digestion of silicate materials with the use of nitric/hydrofluoric acid blend and hydrogen peroxide solution. Results suggest that only a trace amount of HF is required for essentially complete digestion. Recovery of the NIST SRM 1648 Urban Dust is acceptable using this method, with recoveries within 15% of certified values for all analyzed elements except Na, Al, Cr, and Cs. Comparison of element concentrations measured on two or three different strips from the same filter allows a quantitative examination of uncertainty, which was within 20% for PM10 and PM2.5 for nearly all elements. The method developed here for digestion of cellulose filter samples and analysis by ICP-MS shows results that compare well with non-destructive XRF analysis of Teflon filters exposed simultaneously to ambient PM at other sites in the Pittsburgh area.
Acknowledgments This research was conducted as part of the Pittsburgh Air Quality Study, which was supported by US Environmental Protection Agency under contract R82806101 and the US Department of Energy National Energy Technology Laboratory under contract DE-FC26-01NT41017. Support was also provided by the US National Science Foundation under grant BES-9714162. This paper has not been subject to EPA’s peer and policy review, and therefore does not necessarily reflect the views of the Agency. No official endorsement should be inferred. We would like to thank Dr. H.M. “Skip” Kingston and his group at Duquesne University for guidance in microwave digestion method development and instruction and use of their ICP-MS. The analyses provided by R.K.M. Jayanty at Research Triangle Institute are greatly appreciated. We would also like to thank Carnegie Mellon University students and researchers Dr. Andrey Khlystov, Dr. Wei Tang, Satoshi Taka-
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hama, Lenny Lucas, Sam Byun, Emily Lauffer, Lin Tian, Nick McCullar, Lisa Branden, David Carothers, Meredith Fry, Emma Goodson, Mackenzie Dilts, Serge LiHoiFooGregory, Kseniya Shabanova, Gustavo Fimbres, Mithun Shenoi, Dimitris Vayenas, and Elizabeth Higgins for their assistance in collecting and preparing the samples. References [1] L.M. Jalkanen, E.K. Hasanen, J. Anal. At. Spectrom. 11 (1996) 365–369. [2] K.X. Yang, K. Swami, L. Husain, Spectrochim. Acta Part B 57 (2002) 73–84. [3] E.A. Wittig, N.J. Anderson, A. Khlystov, S.N. Pandis, C.I. Davidson, A.L. Robinson, Atmos. Environ. 38 (2004) 3107–3125. [4] B.Y.H. Liu, K.L. Rubow, in: V.A. Marple, B.Y.H. Liu (Eds.), Aerosols in the Mining and Industrial Work Environments, vol. 3, Ann Arbor Science Publishers, Ann Arbor, Michigan, 1983. [5] Whatman Inc., Whatman PM2.5 Filters Statement of Conformance, http://www.whatman.com, accessed July 2004. [6] U.S. Environmental Protection Agency, Microwave Assisted Acid Digestion of Siliceous and Organically Based Matrices, http://www. epa.gov/epaoswer/hazwaste/test/pdfs/3052.pdf. [7] S. Rees, A.L. Robinson, A. Khlystov, C.O. Stanier, S.N. Pandis, Atmos. Environ. 38 (2004) 3305–3318. [8] H.M. Kingston, S. Haswell (Eds.), Microwave Enhanced Chemistry, ACS Professional Reference Series, ACS, Washington, DC, 1997. [9] U.S. Environmental Protection Agency. Determination of Trace Elements in Waters and Wastes by Inductively Coupled Plasma-Mass Spectrometry, revision 4.4, EPA-600-R-94-111, April 1991. [10] CEM Corp., Technical Note 003, Temperature-Controlled Microwave Concentration Using Vacuum-Assisted Evaporation, CEM Corporation, Matthews, NC, www.cem.com, accessed Fall 2003. [11] S. Wu, Y. Zhao, X. Feng, A. Wittmeier, J. Anal. At. Spectrom. 11 (1996) 287–296. [12] K. Swami, C. Judd, J. Orsini, K. Yang, L. Husain, Fresenius J. Anal. Chem. 369 (2001) 63–70. [13] T. Yamashige, M. Yamamoto, H. Sunahara, Analyst 114 (1989) 1071. [14] N.J. Pekney, C.I. Davidson, A.L. Robinson, L. Zhou, P.K. Hopke, D. Eatough, Aerosol Sci. Technol., submitted for publication. [15] W. Tang, T. Raymond, E.A. Wittig, C.I. Davidson, S.N. Pandis, A.L. Robinson, K. Crist, Aerosol Sci. Technol. 38 (Suppl. 2) (2004) 80–90.
Determination of trace elements in ambient aerosol samples Natalie J. Pekney a , Cliff I. Davidson a,b,∗ a
Department of Civil and Environmental Engineering, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA b Engineering and Public Policy, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA Received 6 December 2004; received in revised form 19 March 2005; accepted 22 March 2005 Available online 25 April 2005
Abstract A microwave-assisted digestion procedure using HNO3 , HF, and H2 O2 has been developed for analysis of elements in ambient particulate matter (PM). The samples are collected on cellulose filters and analyzed by inductively coupled plasma mass spectrometry (ICP-MS). The ICP-MS is calibrated with external standards, and recovery of analytes is tested with NIST SRM 1648 Urban Dust. This method has been used to quantify the airborne concentrations of a large number of elements, including Ag, As, Ba, Be, Ca, Cd, Ce, Co, Cr, Cs, Cu, Fe, Ga, K, Li, Mg, Mn, Mo, Ni, Pb, Rb, Se, Sb, Sr, Ti, Tl, V, and Zn. For the majority of these elements, recovery of the NIST SRM is within 15% of the certified values. © 2005 Elsevier B.V. All rights reserved. Keywords: Trace elements; Atmospheric aerosols; Inductively coupled plasma-mass spectrometry; Microwave digestion; Cellulose filter
1. Introduction Trace element concentrations in atmospheric aerosols are now widely used in source–receptor modeling studies. However, obtaining such data requires collection of a large number of samples and a cost- and time-effective method of analysis. Sample preparation varies, but one popular method is microwave-assisted digestion of filter-based samples. This method is appealing for analyses that require liquid samples, due to the ease and low contamination levels with which samples can be prepared. Analysis methods also vary; inductively coupled plasma-mass spectrometry (ICP-MS) as used here has low detection limits, large linear dynamic range and simultaneous multi-element output data. However, because ICP-MS requires a liquid sample, accurate measurements are dependent on the sample extraction efficiency. Other analysis techniques include graphite furnace atomic absorption spectrometry (GFAAS), proton-induced X-ray emission spectrometry (PIXE), and X-ray fluorescence (XRF). GFAAS has comparable detection limits to those of ICP-MS, but does not ∗
Corresponding author. Tel.: +1 412 268 2951. E-mail address: [email protected] (C.I. Davidson).
0003-2670/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.aca.2005.03.065
have the capability of simultaneous multiple element measurement and therefore is not time-effective. PIXE and XRF are both non-destructive analysis techniques but detection limits are much higher, two orders of magnitude for some elements, as compared to ICP-MS. The choice of digestion reagents is an important consideration for measurement of multiple elements in ambient aerosols. Atmospheric particulate matter (PM) includes primary emissions of carbonaceous and metallic particles from combustion and industrial processes, crustal material from erosion of soil and rock, and secondary pollutants such as sulfates, nitrates and organic aerosols, among other species. The reagents chosen must digest the sample as completely as possible and keep the elements stable in solution. Nitric acid can accomplish this for many elements; however, it cannot completely digest silicon-containing compounds and the elements bonded to siliceous material. Previous groups have used relatively large amounts of hydrofluoric acid (HF) to break the silica bonds despite the fact that HF is extremely hazardous and therefore difficult to work with. Jalkanen and Hasanen [1] used a 3:1 mixture of HNO3 and HF in a total volume of 2.0 mL. Yang et al. [2] used a digestion solution of 5 mL HNO3 , 4 mL H2 O2 , 0.5 mL of HF, and 5 mL of H3 BO3 .
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If the silica content of the samples can be measured or estimated, the use of HF can be minimized. In this paper, we examine the use of trace amounts of HF in digesting aerosol filter samples for trace element analysis. We begin by using a certified NIST standard reference material (SRM) to test the recovery of trace elements using the digestion procedure developed here. Next, we apply the digestion procedure to ambient PM2.5 and PM10 collected in Pittsburgh, PA on cellulose filters with analysis by ICP-MS. We then compare SRM samples digested with and without HF to quantify the influence of using this acid. Finally, we compare the ambient PM analysis by ICP-MS using the new digestion procedure with non-destructive analysis by X-ray fluorescence (XRF) for samples collected at other sites in the Pittsburgh region.
2. Experimental The Pittsburgh Air Quality Study (PAQS) took place during July 2001–September 2002. The study included more than 20 different types of analyses of gas and aerosol samples, including analysis of trace elements in aerosol particles. Most samples were collected at the main monitoring station in Schenley Park, adjacent to the Carnegie Mellon University campus [3]. This location is approximately 6 km east of downtown Pittsburgh in the densely populated neighborhood of Oakland. Ambient air was sampled for concentrations of elements using PM10 and PM2.5 high-volume (hi vol) samplers from Andersen Instruments Inc. (Smyrna, Georgia) using 20 cm × 25 cm filters. The hi vols operated at a flow rate of 1.13 m3 /min, and they were specially equipped with brushless motors to minimize contamination. Many types of Teflon filters are commercially available, and these filters are useful for non-destructive analysis methods such as XRF or proton induced X-ray emission. In the current study, cellulose filters (Whatman 41, Whatman Inc., Clifton, NJ) were used as they completely digest in the acids, leaving a liquid solution for injection into the ICPMS. Retention efficiency of the Whatman 41 filters varies with particle size, with a minimum value at 0.3 m diameter of 92% at a face velocity of 45.2 cm/s. [4]. This is admittedly somewhat lower than the minimum 99.7% retention efficiency for Teflon filters [5]. However, the efficiency is over 99% for particles larger than 1.0 m diameter [4]. 2.1. Reagents All reagents were purchased in the purest form available: redistilled nitric acid (70%) and custom redistilled 70% nitric/0.5% hydrofluoric acid blend from GFS Chemicals (Columbus, OH), as well as semiconductor grade hydrogen peroxide (30–32%) from Sigma Aldrich (St. Louis, MO). Distilled, deionized water from a NANOpure ultrapure water system was used (Barnstead/Thermolyne, Dubuque, IA).
Fig. 1. Temperature-controlled program for the MARS 5 digestion method.
2.2. Microwave description The microwave used was a MARS 5 (CEM Corp., Matthews, NC) equipped with an EST-300 Plus temperature sensor and an ESP-1500 Plus pressure sensor. The microwave digestion vessels, HP500 Plus, had working maximum pressure and temperature of 2.4 × 10 N/m and 195 ◦ C, respectively. The microwave could accommodate digestion of up to 14 samples simultaneously. For sample preparation, Standard EPA Method 3052 was followed with some adaptations [6]. The microwave method developed for sample digestion was controlled by temperature and is illustrated in Fig. 1. The slower ramp time between 105 and 135 ◦ C allowed for slower decomposition of the cellulose filter material without a very large or very rapid increase in pressure. 2.3. ICP-MS description Analyses were performed at Duquesne University using an Agilent 4500 ICP-MS (Agilent Technologies, Palo Alto, CA). The ICP-MS was equipped with a concentric nebulizer and a quartz torch. Operating parameters are listed in Table 1. All other parameters, such as torch position, sample depth, extraction, and ion focusing lenses voltages, Omega lenses voltages, quadrupole settings, and carrier and blend gas flow rates were tuned at the start of each analysis session such that the sensitivity was optimized. Oxides and doubly charged ion ratios were kept below 2%. Table 1 ICP-MS operating parameters RF power (kW) RF matching (V) Plasma gas flow rate (L/min) Auxiliary gas flow rate (L/min) Peristaltic pump flow (rps) Measurement mode Number of measurements per peak Integration time Number of repetitions Time per sample measurement (min) Rinse time (min)
1.4–1.5 1.99 15 1 0.10 Spectrum analysis mode 3 (full quant. mode) 0.10 s/point 3 2–3 1
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2.4. Filter handling Filters were handled in ways to minimize contamination. Blank filters were handled identically to the samples, but were run on the hi vol for only 1 min. For the first two months of the study, field blanks were taken once per filter change. Subsequently, field blanks were taken once weekly. For the majority of the study period, 24-h samples were taken. After collection of the samples, filter cassettes were delivered to the laboratory in clean, sealed bags. Filters were removed from the cassettes under a laminar flow hood and cut into strips using a polypropylene template and disposable stainless steel knife blades. Cutting the filter into smaller sections was necessary to get the sample mass below 0.5 g, which is the working limit of the microwave vessels, and also allowed for comparison of analysis results from multiple strips per filter. For the first two months of the study, the filter-cutting template made seven strips per filter, each sized 2.5 cm × 17.8 cm. Subsequent filters were cut with a larger template, which made six strips per filter, sized 3.2 cm × 17.8 cm. Individual filter strips were transferred to sterilized polypropylene centrifuge tubes (tested to be clean for metals) and labeled, sealed in a clean plastic bag (KNF Clean Room Products Corp., Ronkonkoma, NY) and stored in a freezer to minimize biological activity until digestion and analysis. With the exception of the filter loading and removal at the sampling site, all work was conducted under HEPA-filtered laminar flow hoods. 2.5. Sample preparation We can estimate the amount of HF needed to dissolve all of the silicate material in a typical sample. Based on Rees et al. [7], the crustal component of the samples is estimated to account for about 4% of the PM2.5 mass. For the hi vol samples collected at the main site, the annual average 24-h air volume was 1630 m3 and the annual average PM2.5 mass concentration was 17 g/m3 . If we assume conservatively that all crustal mass was SiO2 , the typical amount of Si in a strip comprising 1/6 of the total filter would be 1.8 × 10−4 g. The amount of HF necessary for complete digestion of the SiO2 can be determined from the following reaction: Heat
SiO2 + 4HF −→ SiF4 (g) + 2H2 O
(1)
Results show that 1.2 × 10−5 moles of HF (2.5 × 10−4 g), or less than 0.1% HF in the digestion solution, completely digests all of the crustal material in an average sample. A concentration of 0.5% HF was therefore chosen to digest the crustal material in all the samples. HF at this low concentration can be purchased already blended with nitric acid, and thus it is not necessary to use the stringent precautions invoked for more concentrated HF. Also, the sample introduction system for the ICP-MS does not have to be replaced with an expensive inert system needed for more concentrated HF. Only one quartz torch was used for the duration of this
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study that involved analysis of over 3200 samples during the course of one year. Hydrogen peroxide can reduce NO fumes as well as pressure in the closed microwave vessel. The pressure-reducing mechanism is described by the following chemical reactions [8]: Heat
2H2 O2 −→ 2H2 O + O2 (g)
(2)
2NO(g) + O2 (g) → 2NO2 (g)
(3)
2NO2 (g) + H2 O → HNO3 + HNO2
(4)
Boric acid is sometimes used to complex the HF at higher concentrations but was not used here. Other reagents sometimes used include perchloric and hydrochloric acid, neither of which was used in this study since ClO, ClOH, and ArCl can cause interference problems in the measurement of As, Se, V, and Cr by ICP-MS [9]. Using Teflon-coated forceps, filter strips were transferred to the digestion vessels, the solution was added, and the vessels were capped. The digestion solution consisted of 9 mL custom redistilled 70% nitric/0.5% hydrofluoric acid blend and 2 mL hydrogen peroxide. After digestion in the microwave, the vessels were transferred to the CEM Microvap assembly, connected to a vacuum pump, and heated in the microwave until the volume of the sample decreased to approximately 0.5 mL. This allowed evaporation of the acid without loss of the analytes [10]. The samples were then removed and poured into sterilized, graduated sample cups already containing the internal standard solution. Deionized water was added to bring the total volume to 10 mL. Each sample contained 50 ppb of the internal standard solution because this concentration level was approximately mid-calibration range for most elements. The final acid concentrations in the samples were approximately 4% nitric acid and 0.02% hydrofluoric acid. 2.6. Analysis Samples were transported to the Duquesne University Laboratory clean room in airtight plastic containers. The ICPMS was tuned and calibrated. A check standard was analyzed after the initial calibration and subsequently after every 10 samples. If the measured check standard concentrations were not within 10% of actual concentrations, the instrument was recalibrated and the previous 10 samples were re-analyzed. If a sample concentration was higher than the highest calibration standard for an element, the sample was diluted and re-analyzed for that element. External ICP-MS calibration standards were custommade from SCP Science (Champlain, NY). Because of the great difference in concentrations of various elements in each sample, a standard stock solution was made to reflect these differences, and five calibration standards were mixed from the stock solution. Maximum standard concentration for elements of lowest concentrations in the samples was 200 ppb,
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while maximum for elements of highest concentrations was 8000 ppb. The multi-element internal standard solution, also from SCP Science, contained Sc, In, Tb, Ho, Y, and Bi. The internal standard solution was added to every external calibration standard and sample. Addition of the internal standard helped to account for matrix effects. Selection of the appropriate internal standard element for each sample element depends on similarities in mass number, ionization potential, and chemical characteristics. Table 2 shows selected internal standard elements for each analyte.
3. Results and discussion 3.1. Recovery of NIST standard reference material Success of the digestion procedure was measured by the recovery of elements in the NIST SRM 1648, Urban Dust, and also the agreement between two different strips per filter. For each batch of samples digested, one microwave vessel contained a measured mass of the SRM, approximately 1.0 mg to represent sample mass, in the same digestion solution. Also, one microwave vessel per digestion batch contained only reagents to examine contamination from the reagents. The reagent blank sample concentrations (RGB) were subtracted from the NIST SRM samples (SRMmeasured ) prior to calculating recovery. Percent recovery, %R, was calculated as: %R =
SRMmeasured − RGB × 100% SRMcertified
(5)
where SRMcertified is the concentration of the element in the SRM as certified by NIST. Minimum detection limits (MDLs) were established as per EPA Method 200.8 [9] and are listed for each element in Table 2. Where concentrations of elements in either the SRM or the RGB samples were below the MDL, they were replaced with the MDL as a conservative upper limit of the concentration, and were listed as an upper limit. For blank correction, typically either the SRM was many times the RGB or both the SRM and RGB were below the MDL; there were not a significant number of cases in which the subtraction of a RGB replaced by the MDL for an element resulted in a substantial decrease from the true concentration that would therefore render the recovery unacceptable. Elements in a sample for which either the measured concentration or the NIST certified concentration were less than two times the reagent blank concentration were flagged as below detection. Also in Table 2 is the number of samples analyzed that were above detection out of a possible total of 139. This total does not include values deleted due to a malfunction of the balance. Note that early tests of this method included a blank filter strip along with the NIST SRM in some samples; the presence of the filter strip did not affect the results and hence further
work with the SRM samples did not incorporate blank filter strips. Recoveries for each element are shown in Table 2. Data for Na and Al are unreliable and therefore are not given. All other elements are within the target recovery of 100 ± 15% with the exception of Cr (59%) and Cs (82%). The precision and accuracy of the results of this study compare well with recoveries of the NIST SRM 1648 reported by others, despite much higher concentrations of HF used in their studies. Jalkanen and Hasanen [1], using a 3:1 mixture of HNO3 and HF, report recoveries in the range of 80–98% for several elements in 10 samples with the exception of a very low recovery of Cr (28%). Yang et al. [2] and Wu et al. [11], both using a digestion solution of HNO3 /H2 O2 /HF/H3 BO3 report recoveries of 90–110% for several elements, with lower recoveries of 70% and 77% for Se and Cr, respectively, reported by Yang et al. Swami et al. [12] find similar recoveries for most elements at varying amounts of HF in a HNO3 /H2 O2 digestion solution. Precision and recovery of Se decreased with increasing amounts of HF, although recovery of Cr improved. The low recovery of chromium in the NIST SRM 1648 is a documented problem [13]. It has been hypothesized that the high soot content of NIST SRM 1648 signifies the presence of organic material that somehow inhibits dissolution of all the chromium [1]. Most of the samples had concentrations below detection for Cs. Therefore, the low recovery of Cs is likely due to detection limit problems. The SRM did not have certified concentrations for several elements analyzed, namely Li, Be, Ca, Ga, Sr, Mo, and Tl. 3.2. Trace elements in ambient PM Data from either two or three filter strips have been averaged for every filter used in this study to report airborne concentrations [14]. However, agreement between filter strips is discussed here only for two typical months, October 2001 (two strips per filter) and January 2002 (three strips per filter). Ambient concentrations were determined by subtracting the average of the field blank filter mass from the filter sample mass, and dividing by the volume of air sampled. For a sample to be considered above detection, concentration must be greater than 3.3 times the standard deviation of the field blank concentrations [9]. Field blank concentrations varied by element, ranging from 0.001 to 4 ng/m3 . Table 3 shows the average difference between concentrations from the two strips divided by the daily average mass concentration for each element for the month of October 2001, termed the percent error. For both PM10 and PM2.5 , the average errors are almost always less than 30%. For the January 2002 filters, the relative standard deviation of the data from three strips was smaller than the values of the average percent error given in Table 3 for nearly all elements. These levels of error are acceptable for using the data with such source–receptor models as positive matrix factorization (PMF) and Unmix [14].
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Table 2 Percent recovery for each element Element
Internal standard element
Minimum detection limit (ppb)
Li Be Mg K Ca Ti V Cr Mn Fe Co Ni Cu Zn Ga As Se Rb Sr Mo Ag Cd Sb Cs Ba Ce Tl Pb
Sc Sc Sc Sc Sc Sc Sc Sc Sc Sc Sc Y Y Y Y Y Y Y Y Y In In In In In In Bi Bi
0.076 0.048 0.439 66.1 5.26 0.506 0.155 0.358 0.372 50.5 0.070 0.268 0.129 0.340 0.031 0.039 0.536 0.039 0.037 0.115 0.060 0.071 0.092 0.083 0.312 0.101 0.025 0.032
Number of samples above detection (139 total samples)
Recovery (%) (S.D., %) of NIST SRM 1648
125 139
96 (18) 96 (18)
139 139 139 139 139 118 137 139 139
86 (12) 103 (21) 59 (17) 95 (22) 102 (17) 91 (33) 96 (34) 93 (17) 97 (19)
139 121 136
89 (15) 88 (48) 85 (21)
86 139 129 28 139 69
85 (35) 95 (14) 87 (22) 82 (33) 105 (15) 97 (32)
130
95 (19)
For Ag, Ce, and Cs, a large fraction of the NIST samples were below detection because of significant reagent blanks. For all other elements, the NIST sample concentrations exceeded the reagent blanks by a factor of six or more except in two instances (Co and Rb). Certified concentrations were not given by NIST for some elements.
3.3. Comparison of recoveries from the SRM with and without HF To show that the addition of a trace amount of HF to the digestion solution improved recovery of the elements in NIST SRM samples, a batch of seven NIST samples, three with trace HF and four without HF, were prepared and analyzed according to the procedure described above. Table 4 presents the results of this comparison. The improved recoveries of the elements in the NIST SRM samples for K, Ti, Cr, Rb, Sb, Cs, and Ba were statistically significant with the addition of trace HF at the P = 0.05 level of significance. The other elements showed recoveries that were not statistically different between the two sets of samples with the exception of Mg. Recovery of Mg in these samples significantly decreased with the addition of HF, but recoveries of Mg as reported in Table 2 are quite good. The reason for the low recovery of Mg in the three samples digested with HF presented in Table 4 as compared to the good recovery of Mg in the samples reported in Table 2 is unknown. 3.4. Comparison of ambient PM analyzed by ICP-MS and XRF During July 2001 and January 2002, daily Teflon filter samples were collected at four satellite sites surrounding the
main Pittsburgh sampling site, and these filters were analyzed by XRF by Research Triangle Institute, Triangle Park, NC. The main Pittsburgh sampling site, the Lawrenceville site, and the Hazelwood site are located within the Pittsburgh city limits. The rural Florence site is located 50 km west of Pittsburgh, which is typically upwind of the city, and the Greensburg site is located 55 km east of Pittsburgh, typically downwind. More information about the locations of the four satellite sites and details of sample collection are given in Tang et al. [15]. Ambient concentrations of many elements analyzed by XRF appear noisy as compared to the ICP-MS results for the main site due to the smaller air volumes sampled for XRF analysis and the higher detection limits of XRF as compared to ICP-MS. Nevertheless, several elements with high concentrations show reasonable agreement, namely K, Ti, V, Mn, Fe, Zn, As, Se, and Pb. The correlation coefficient ρ and the number of valid samples for comparison n are shown in Table 5. Note that sampling at the Pittsburgh main site began on July 11, 2001, while sampling at the four satellite sites was continuous beginning on June 30 until July 31, 2001. Based on a two-tailed t-test with n − 2 degrees of freedom, the correlation coefficients were tested against the hypothesis that they were significantly greater than zero. The level of significance of the correlation is given in Table 5 as well. Figs. 2 and 3
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Table 3 A comparison of the concentrations measured on two different strips for samples collected in October 2001 Element
PM10
Li Be Mg K Ca Ti V Cr Mn Fe Co Ni Cu Zn Ga As Se Rb Sr Mo Ag Cd Sb Cs Ba Ce Pb
PM2.5
Number of samples above detection (31 total samples)
Percent error
Number of samples above detection (31 total samples)
Percent error
22 22 31 31 31 31 31 31 30 31 21 26 28 31 31 30 31 29 31 28 15 30 30 23 31 29 31
7.4 50.2 13.1 23.2 14.7 16.5 25.8 20.2 28.0a 7.1 37.0a 12.6 14.0 15.9 16.5 9.3 26.1 14.2 4.9 11.0 26.1 11.0a 16.6 24.6 9.1 10.8 12.1
20 19 31 31 30 29 29 28 30 31 13 22 14 26 23 30 31 25 26 19 14 28 26 17 31 13 30
6.6 16.5 8.7 9.5 14.1b 19.2 7.9 34.4 21.7b 21.3 21.9 21.8 17.6 9.4 36.8 8.3 9.6 4.6 19.9b 11.9 32.1 6.4b 35.9 6.0 29.0 13.9 5.6
All Tl concentrations were below detection in October 2001. a One outlier pair was removed from the full dataset for each of these elements (total 3 outlier pairs out of 769 pairs). b One outlier pair was removed from the full dataset for each of these elements (total 4 outlier pairs out of 670 pairs).
Table 4 A comparison of samples digested with and without trace HF
Mg K Ca Ti V Cr Mn Fe Co Ni Cu Zn As Se Rb Ag Cd Sb Cs Ba Pb
Samples digested without HF (n = 4)
Samples digested with HF (n = 3)
µ
µ
0.831 0.517 0.845 0.408 0.829 0.421 0.864 0.793 0.754 0.781 0.720 0.689 0.722 0.637 0.411 1.126 1.010 0.463 0.609 0.849 0.867
0.126 0.055 0.138 0.062 0.133 0.018 0.153 0.123 0.131 0.116 0.126 0.108 0.105 0.096 0.052 0.181 0.124 0.042 0.140 0.128 0.139
0.693 0.716 0.717 0.605 0.841 0.626 0.788 0.734 0.751 0.724 0.600 0.903 0.614 0.533 0.590 1.024 0.910 0.939 1.041 1.003 0.806
0.051 0.052 0.06 0.093 0.067 0.038 0.067 0.062 0.136 0.099 0.137 0.610 0.120 0.113 0.118 0.034 0.042 0.053 0.033 0.048 0.071
tobs
P-value
−1.99 4.87 −1.66 3.17 0.16 8.66 −0.89 −0.84 −0.03 −0.69 −1.19 0.60 −1.25 −1.23 2.45 −1.10 −1.50 12.75 5.95 2.20 −0.75
0.05 0.003 0.08 0.012 0.44 0.0002 0.21 0.22 0.49 0.26 0.14 0.29 0.13 0.13 0.029 0.16 0.10 0.00003 0.001 0.04 0.24
Average recovery, µ, is the measured concentration divided by the certified concentration and σ is the standard deviation of the recoveries for each element. The test statistic tobs , based on a student’s t-test, is given for each element and P-values are given for all elements.
Table 5 Comparison of ICP-MS data from the Pittsburgh Supersite and XRF data from the Lawrenceville, Hazelwood, Greensburg, and Florence sites Ti
V
Mn
Fe
Zn
As
Se
Pb
July 2001 Pittsburgh–Lawrenceville Pittsburgh–Hazelwood Pittsburgh–Greensburg Pittsburgh–Florence Lawrenceville–Hazelwood Lawrenceville–Greensburg Lawrenceville–Florence Hazelwood–Greensburg Hazelwood–Florence Greensburg–Florence
0.65/20/1% 0.53/19/2% 0.77/20/1% 0.63/20/1% 0.97/30/1% 0.93/31/1% 0.78/31/1% 0.87/30/1% 0.67/30/1% 0.87/31/1%
0.70/20/1% 0.36/19/NC 0.35/20/NC 0.35/20/NC 0.73/30/1% 0.59/31/1% 0.26/31/NC 0.60/30/1% 0.35/30/10% 0.37/31/5%
0.69/20/1% 0.76/19/1% 0.45/20/5% 0.48/20/5% 0.67/30/1% 0.70/31/1% 0.09/31/NC 0.10/30/NC 0.26/30/NC 0.18/31/NC
0.16/20/NC 0.10/19/NC 0.16/20/NC 0.05/20/NC −0.04/30/NC 0.00/31/NC 0.47/31/1% −0.18/30/NC −0.20/30/NC 0.14/31/NC
0.46/20/5% 0.28/19/NC 0.48/20/5% 0.40/20/10% 0.11/30/NC 0.73/31/1% 0.42/31/2% 0.00/30/NC −0.10/30/NC 0.37/31/5%
0.46/19/5% 0.09/19/NC −0.10/19/NC −0.06/19/NC 0.24/30/NC 0.06/31/NC 0.22/31/NC 0.07/30/NC −0.07/30/NC 0.23/31/NC
−0.14/19/NC −0.22/19/NC −0.04/19/NC 0.32/19/NC −0.32/30/NC 0.23/31/NC −0.35/31/NC 0.09/30/NC −0.06/30/NC 0.01/31/NC
0.65/19/1% 0.49/19/5% 0.47/19/5% 0.05/19/NC 0.70/30/1% 0.47/31/1% −0.08/31/NC 0.08/30/NC −0.04/30/NC −0.13/31/NC
0.65/19/1% 0.73/19/1% 0.35/19/NC 0.64/19/1% 0.42/30/2% 0.51/31/1% 0.44/31/2% −0.12/30/NC 0.27/30/NC 0.44/31/2%
January 2002 Pittsburgh–Lawrenceville Pittsburgh–Hazelwood Pittsburgh–Greensburg Pittsburgh–Florence Lawrenceville–Hazelwood Lawrenceville–Greensburg Lawrenceville–Florence Hazelwood–Greensburg Hazelwood–Florence Greensburg–Florence
0.66/18/1% 0.79/18/1% 0.79/21/1% 0.57/19/2% 0.82/16/1% 0.74/18/1% 0.63/18/1% 0.97/16/1% 0.62/16/1% 0.66/19/1%
0.10/18/NC 0.31/18/NC 0.53/21/2% 0.23/19/NC −0.29/16/NC 0.43/18/10% 0.21/18/NC 0.31/16/NC 0.25/16/NC 0.40/19/10%
0.03/18/NC 0.19/18/NC 0.09/21/NC 0.08/19/NC 0.09/16/NC 0.20/18/NC 0.35/18/10% −0.22/16/NC −0.39/16/NCa 0.39/19/10%
0.91/18/1% 0.55/18/2% 0.73/20/1% −0.31/19/NC 0.72/16/1% 0.70/18/1% −0.22/18/NC 0.36/16/10% −0.21/16/NC −0.06/19/NC
0.92/18/1% 0.89/18/1% 0.83/20/1% 0.10/19/NC 0.90/16/1% 0.88/18/1% 0.02/18/NC 0.86/16/1% 0.02/16/NC 0.09/19/NC
0.86/18/1% 0.95/18/1% 0.89/21/1% 0.16/19/NC 0.91/16/1% 0.92/18/1% 0.22/18/NC 0.93/16/1% 0.18/16/NC 0.32/19/10%
0.73/18/1% 0.30/18/NC 0.11/21/NC 0.60/19/1% 0.32/16/NC 0.32/18/10% 0.67/18/1% 0.47/16/10% 0.66/16/1% 0.60/19/1%
0.86/18/1% 0.93/18/1% −0.10/21/NC −0.07/19/NC 0.87/16/1% 0.00/18/NC 0.01/18/NC −0.03/16/NC −0.23/16/NC −0.08/19/NC
0.47/18/5% 0.60/18/1% 0.81/21/1% 0.52/19/5% 0.43/16/10% 0.46/18/10% 0.48/18/5% 0.66/16/1% 0.25/16/NC 0.34/19/10%
Given in each cell are: correlation coefficient, ρ; number of valid datapoints to compare, n; level of significance of correlation, tested at the 1%, 2%, 5%, and 10% level. Correlations not significant at the 10% level or better are listed as not correlated, NC. a Correlation is negative at the 10% significance level.
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K
275
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Fig. 2. Airborne concentrations during June 30–July 31, 2001 for the Pittsburgh Supersite and XRF data for four satellite sites in the Pittsburgh area. Concentrations are shown in g/m3 . () Pittsburgh; (䊉) Florence; ( ) Greensburg; () Lawrenceville; ( ) Hazelwood.
show time series graphs of these elements for the two months. Potassium correlation coefficients are high among all sites for both months. The large peak in early July 2001 is likely due to Fourth of July fireworks, as most fireworks contain potassium salts for ignition. Titanium concentrations are significantly correlated among the sites for July, but there is more scatter in the January XRF data and not as many of the site pairs are correlated. Concentrations of titanium are slightly higher on average during July as compared to January, so poorer correlations in January may be due to decreased detection capability of the XRF. Most site-to-site correlations of vanadium concentrations are insignificant in January. There is more day-to-day variability in the concentration data in July, and correlations are in general higher. Concentrations of manganese, iron, and zinc tend to be higher at the city sites, suggesting that there are significant sources of these elements within the city. Manganese and zinc concentrations show poor correlations between the sties in July. Correlations of iron data for July are significant for many of the site pairs. In January, the rural Florence site data do not correlate well with any other site for manganese, iron, and zinc, but the other sites are significantly correlated.
Fig. 3. Airborne concentrations during January 2–22, 2002 at the same sites as in Fig. 2. Concentrations are shown in g/m. () Pittsburgh; (䊉) Florence; ( ) Greensburg; () Lawrenceville; ( ) Hazelwood.
Arsenic shows reasonable agreement among all sites in January with most site-to-site correlations being significant, but there is more scatter in the XRF data in July where none of the site pairs correlate significantly. Concentrations on average are approximately equal for the two months. Selenium concentrations show some significant correlations but also several poorly correlated site pairs, especially in January. Concentrations of arsenic and selenium are relatively low in PM2.5 , making these elements more difficult to detect by XRF. Lead data show most sites significantly correlated for both months with the concentrations at the Lawrenceville site somewhat elevated on some dates. It is possible that there is a local source of lead near this site. Overall, there are many significant correlations between the Supersite and the satellite site data for July 2001 and January 2002. Instances of uncorrelated data could be due to differences in emissions at the five sites, not just analytical differences. The method developed here for measurement of trace element concentrations in ambient PM and analysis by ICP-MS compares reasonably well with non-destructive XRF analysis using different filter media. 4. Conclusions The method described in this paper for digestion and analysis of trace elements in ambient aerosol samples is suitable
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for routine analysis of the large number of samples commonly generated in air quality monitoring studies. Sample preparation by microwave digestion minimizes contamination and allows for digestion of silicate materials with the use of nitric/hydrofluoric acid blend and hydrogen peroxide solution. Results suggest that only a trace amount of HF is required for essentially complete digestion. Recovery of the NIST SRM 1648 Urban Dust is acceptable using this method, with recoveries within 15% of certified values for all analyzed elements except Na, Al, Cr, and Cs. Comparison of element concentrations measured on two or three different strips from the same filter allows a quantitative examination of uncertainty, which was within 20% for PM10 and PM2.5 for nearly all elements. The method developed here for digestion of cellulose filter samples and analysis by ICP-MS shows results that compare well with non-destructive XRF analysis of Teflon filters exposed simultaneously to ambient PM at other sites in the Pittsburgh area.
Acknowledgments This research was conducted as part of the Pittsburgh Air Quality Study, which was supported by US Environmental Protection Agency under contract R82806101 and the US Department of Energy National Energy Technology Laboratory under contract DE-FC26-01NT41017. Support was also provided by the US National Science Foundation under grant BES-9714162. This paper has not been subject to EPA’s peer and policy review, and therefore does not necessarily reflect the views of the Agency. No official endorsement should be inferred. We would like to thank Dr. H.M. “Skip” Kingston and his group at Duquesne University for guidance in microwave digestion method development and instruction and use of their ICP-MS. The analyses provided by R.K.M. Jayanty at Research Triangle Institute are greatly appreciated. We would also like to thank Carnegie Mellon University students and researchers Dr. Andrey Khlystov, Dr. Wei Tang, Satoshi Taka-
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