Introduction
It has long been known that increased air pollution, specifically
particle pollution, is associated with adverse health effects (Brunekreef and
Holgate, 2002; Kelly et al., 2012). Particulate matter (PM) also affects
atmospheric visibility and radiative forcing (Fuzzi et al., 2015). PM is not
a homogenous air pollutant but rather a complex mixture; it varies in
chemical and physical composition depending on the contributing sources and
the atmospheric processes (AQEG, 2005). The composition of PM influences its
harmfulness and therefore it is important to gain better knowledge about
which chemical components might cause particle toxicity (Kelly and Fussell,
2015). Understanding the chemical composition of PM also provides information
on the sources and thus helps implement policies on targeting these emission
sources (WHO, 2013). Trace metals in particular, even though they do not
contribute substantially to the mass of PM, act as markers for specific
source categories (Visser et al., 2015a) and evidence is emerging that some
metals in ambient PM are associated with adverse health effects at
concentrations near to current ambient levels (Chen and Lippmann, 2009).
Accurate measurements of the PM composition are important and are mostly
carried out by collecting PM on filters using high or low volume filter
samplers (e.g. Digitel-DAH-80, Partisol 2025) and subsequently digesting and
analysing these in a laboratory. These filters are collected over a period of
time, usually 24 h to a week, and then analysed for different components
such as metals (Brown et al., 2008), polyaromatic hydrocarbons (Pandey et
al., 2011), elemental and organic carbon (Chu, 2004) and inorganic ions
(Beccaceci et al., 2015). This approach is time consuming, labour intensive
and prone to positive and negative sampling artefacts for some components
(Chow et al., 2015). Also, it only gives compositional information with a
considerable time delay and at low temporal resolution which cannot be
effectively associated with meteorological variability or short term
variations in emissions.
To run the above filter samplers on a higher time resolution means they
become even more labour intensive to operate. To address this limitation,
sampling devices were developed to collect PM either hourly or sub-hourly
without the need for frequent filter changes. These include the rotating drum
impactor (Bukowiecki et al., 2005), which collects three size ranges:
PM10-2.5 (coarse), PM2.5-1.0 (intermediate) and PM1.0-0.3
(fine), by passing sequentially through three rectangular nozzles of
decreasing size; and the Streaker (PIXE International Corporation) which
consists of two collecting substrates rotating at constant speed producing a
circular continuous deposition of both PM10-2.5 and PM2.5 (Formenti
et al., 1996). Nevertheless the analysis is still performed in the laboratory
and thus does not improve the time delay of the analysis.
Several online high time resolution instruments have also been developed in
recent years which address some of the sampling artefact, resource and time
resolution limitations of laboratory approaches. These include aerosol mass
spectrometers such as the ACSM (Aerodyne Research Inc.) (Ng et al., 2011);
ion chromatography approaches such as the MARGA (Metrohm) (Rumsey et al.,
2014), PILS (Brechtel) (Weber et al., 2001) and URG's 9000 ambient ion
monitor (Beccaceci et al., 2015); and x-ray fluorescence (XRF) such as the
XACT instrument (Cooper Environmental Services) (Park et al., 2014). However,
these high time resolution instruments only measure a subset of chemical
components each, depending on their collection, extraction and analysis
methodology. Therefore multiple co-located instruments are needed to measure
the full PM composition. Furthermore, the high time resolution instruments
tend to measure a narrower range of components with a higher limit of
detection (LOD) than equivalent laboratory based methods, generally because
less material is collected on each sample. For example, the synchrotron
radiation-induced XRF (SR-XRF) used by Visser et al. (2015b) measured
elements with atomic numbers greater than 11 while the XACT measures elements
with atomic numbers greater than 14 thereby missing important contributors to
PM mass such as Na, Mg and Al; the LODs reported for the SR-XRF analysis
(Visser et al., 2015b) are generally lower than those for the XACT (Furger et
al., 2017; Park et al., 2014).
Despite these limitations, the XACT is unique in measuring elements
automatically using energy dispersive XRF (ED-XRF) and has been successfully
evaluated in a number of field studies (Furger et al., 2017; Park et al.,
2014; US-EPA, 2012). In a verification test carried out by the US-EPA (2012)
measurements of Ca, Cu, Mn, Pb, Se and Zn by the XACT were compared to filter
based measurements (filters analysed using ICP-MS). This verification test
showed that the daily average XACT 625 results were highly correlated and in
close quantitative agreement with ICP-MS analysis results for the six metals,
except Cu, which was close to the detection limit of the ICP-MS analysis and
the quantitation limit of the XACT 625. Park et al. (2014) found a good
agreement between the XACT and 24 h filters collected in South Korea
(filters analysed using ED-XRF). Furger et al. (2017) tested the XACT during
a summer campaign in Switzerland in 2015 and compared the XACT data with
measurements made using ICP-OES (inductively coupled plasma optical emission
spectrometry), ICP-MS and gold amalgamation atomic absorption spectrometry on
filters sampled for 24 h (both PM10) as well as ACSM measurements
(PM1). They found an excellent correlation, with R2
values ≥ 0.95, between the XACT and ICP-MS data for 10 elements (S, K,
Ca, Ti, Mn, Fe, Cu, Zn, Ba and Pb). However, they found that the XACT was
systematically higher than the filter based technique. In Jeong et al. (2017)
hourly trace elements measured by the XACT were included in positive matrix
factorisation (PMF), which allowed a more robust apportionment of PM sources
(Jeong et al., 2017).
For all analytical techniques, in the field and laboratory, the confidence in
measurements largely depends on high quality, traceable calibration of the
instruments (Indresand et al., 2013). In the case of the XACT, the
calibration is carried out using thin film standards, which are thin element
films deposited on Nuclepore substrates and are available for elements
between atomic number 11 and 82 (EPA Compendium Method IO-3.3 for the
Determination of Inorganic Compounds in Ambient Air, EPA/625/R-96/010a,
Table 2, p. 3.3-16). This is an established method but has been reported to
have various limitations (Indresand et al., 2013): the standards are much
higher in concentration than most ambient samples; the element mix of the
standard might not be representative of ambient particle mix; and the
collection properties on a filter may also differ. Alternative calibration
methods have therefore been tested to address these issues. For example
Indresand et al. (2013) produced sulfur reference materials that replicated
PM samples to successfully calibrate XRF systems.
In this study a novel mass-based calibration technique for the XACT 625 has
been developed to independently assess the accuracy of the XRF method for a
range of elements at more atmospherically relevant concentrations. This study
also reports the field evaluation of the XACT at both traffic and industrial
sites in the UK where it was compared to independent measurements of
PM2.5 and PM10 on daily filters, analysed by ICP-MS, and also to
alternative high time resolution chemical speciation instruments (ion
chromatography and aerosol mass spectrometry). Additionally, the ability of
the XACT to analyse PM10 filter samples in the laboratory was piloted
and the results compared to co-located in situ XACT measurements. Using the
instrument in this way potentially diversifies experimental sampling
programmes with this single resource by deploying additional sampling
devices.
Materials and methods
XACT 625
The instrument measures 24 elements between Silicon and Uranium at a time
resolution between 15 min and 4 h using ED-XRF. The size fraction
of the PM sample collected onto the Teflon filter tape depends on the size
selective inlet chosen. The instrument samples with a volumetric flow rate of
1 m3 h-1 through an inlet tube heated to 45 ∘C when the
ambient relative humidity (RH) exceeds 45 % to avoid water depositing on
the tape. Sampling and analysis is performed continuously and simultaneously,
except for the time required to advance the filter tape (∼ 20 s) from
the sample to the analysis position. During the analysis, the sample is
excited using an x-ray source (Rhodium anode, 50 kV, 50 Watt) in three
successive energy conditions, which target three different suites of
elements. The resulting x-ray fluorescence is measured with a silicon drift
detector and the spectra are analysed using a proprietary spectral analysis
package which takes into account all peaks associated with a given element.
Daily automated quality assurance checks are performed every night at
midnight and consist of an energy alignment (an energy calibration using a
copper rod, inserted into the analysis area); an upscale measurement to
monitor the stability of the instrument response (for Cd, Cr and Pb); and a
flow check through an independent mass flow sensor. Additional quality
assurance checks employed here included flow calibrations, regular external
standard checks, field blanks performed using a HEPA filter as well as tape
blanks before and after each tape change.
For the field studies the instrument sampled PM10 or PM2.5 as
detailed below (see Sect. 2.3.1). The elements measured are As, Ba, Ca, Cd,
Ce, Cl, Cr, Cu, Fe, K, Mn, Mo, Ni, Pb, Pt, S, Sb, Se, Si, Sr, Ti, V and Zn and
were chosen to represent a range of source categories (i.e. regulatory,
traffic, industry), plus the internal palladium (Pd) standard. The internal
standard measurement is the reported response from a Pd rod inserted in a
fixed position under the filter tape.
Schematic of instrument set up during laboratory calibration.
![]()
Laboratory experiments
An independent mass-based calibration technique was developed for the XACT.
This used laboratory generated aerosols and a schematic of the instrument
set-up is shown in Fig. 1. Ammonium sulfate
((NH4)2SO4, ACS reagent grade, Sigma-Aldrich),
potassium chloride (KCl, analytical grade, VWR Chemicals) and zinc acetate
(Zn(O2CCH3)2, analytical grade, VWR Chemicals) were dissolved in
high purity water (18.2 MΩ, TOC < 5 µg L-1,
PURELAB® Ultra Analytic, ELGA, Veolia Water
Technologies) to obtain a range of standard solutions spanning the ambient
concentration range.
Overview of sites and instrumentation used.
Marylebone Road, London
Tawe Terrace, Pontardawe
Tinsley, Sheffield
PM10
PM2.5
PM10
PM10
XACT
1 Jul 2014 to
15 Oct 2014 to
25 Nov 2015 to
19 Jan 2017 to
11 Mar 2015
1 Dec 2014
24 Dec 2015
27 Mar 2017
ACSM (PM1)
NA
15 Oct 2014 to
NA
NA
1 Dec 2014
URG
7 Jan 2015 to
NA
NA
NA
11 Mar 2015
Partisol
NA
19 Jan 2017 to
15 Oct 2014 to
25 Nov 2015 to
27 Mar 2017b
1 Dec 2014a
24 Dec 2015b
17 Feb 2017 to
10 Mar 2017c
Filters were digested using a HF / HClO4
and b HNO3 / H2O2.
cFilters were analysed using the XACT in off-line mode.
Maximum concentration in field campaigns (ng m-3) and highest
and lowest concentration used in calibration test.
Concentration (ng m-3)
Field campaign
S
Cl
K
Zn
London kerbsite (PM10)
3700
22 000
470
310
London kerbsite (PM2.5)
3500
4600
4000
370
Wales industrial (PM10)
8900
21 000
1500
5500
Sheffield industrial (PM10)
4900
10 000
1020
4900
Lowest standard
2400
7200
8500
4900
Highest standard
30 000
35 000
39 000
20 000
Aerosols were generated using an ATM 226 – Clean Room Aerosol
Generator (Topas) and were driven through two Permapure™ driers set in reflux
method to reduce the relative humidity to approximately 40 %. The flow
was then split isokinetically using a TSI 3708 flow splitter and passed to
three instruments: a tapered element oscillating microbalance (1400ab TEOM,
Thermo), with which continuous direct mass measurements of particulates were
taken; a scanning mobility particle sizer (TSI SMPS 3080); and the XACT. HEPA
filtered make-up air was provided where necessary. The mass concentration of
the deposited (NH4)2SO4, KCl and
Zn(O2CCH3)2 as measured by the TEOM were used to calculate the S,
Cl, K and Zn mass concentrations and compared to the element concentration
measured with the XACT. The SMPS was used to give qualitative diagnostic
information on the size distribution of the aerosol.
Field experiments
Monitoring locations
Three field evaluation campaigns were carried out in the UK (Table 1): a
traffic site in central London (Marylebone Road:
51∘31′21′′ N, 0∘09′17′′ W) and two industrial
sites (Pontardawe in Wales: 51∘43′12′′ N,
3∘50′49′′ W; and Tinsley in Sheffield: 53∘24′38′′ N,
1∘23′46′′ W) (map in Supplement S1). Marylebone Road is a
kerbside monitoring station in a central London street canyon adjacent to a
six lane highway (60–80 000 vehicles day-1). During this deployment
the XACT sampled PM10 except for a period from October to December 2014
that sampled PM2.5. Pontardawe is an urban industrial site in South
Wales, surrounded by metallurgical industries. Tinsley, located north-east of
Sheffield, is approximately 200 m east of the M1 motorway, with a residential
area to the east and light industry to the west. In Pontardawe and Tinsley,
the XACT was co-located with the monitoring site belonging to the UK Ambient
Air Quality Metals Monitoring Network from which daily filters measured by
ICP-MS were available.
Comparison instruments
A number of comparison instruments were used to evaluate the XACT in the
field. The main comparison was carried out using filter samples collected
with a Partisol 2025 and subsequent ICP-MS analysis. Further, an Aerosol
Chemical Speciation Monitor (ACSM) and Ambient Ion Monitor-URG-900B (URG)
were used for the evaluation of XACT at a high time resolution. Although the
measurands are not directly comparable, they provide useful information for
studies where source contributions may be estimated by receptor modelling
using measurements of chemical components based on one of these measurement
techniques.
Partisol 2025
A Thermo Scientific Partisol 2025, with a flow rate of 1 m3 h-1,
was used to collect filter samples (mixed cellulose ester filters, VWR
514-0464) for subsequent analysis using ICP-MS. At Marylebone Road, where
samples were taken specifically for this study, a 23 h sampling period was
used (01:00–00:00 UTC) to ensure comparability with the XACT once the equivalent
hour lost to quality assurance was removed. The filters were acid-digested on
a hotplate using a 1:2 mixture of HClO4 and HF in open 10 ml
Teflon crucibles. After complete evaporation, HNO3 has been added
to each sample, and the remaining solution was made up to the required
volume. Filters were fully dissolved with this method (adapted from
ISO-14869-1:2001). For quality assurance, blank filters (field and laboratory
blanks), internal (rhyolite) and international (NIST SRM 1648a) certified
reference materials were also prepared following the same procedure. The
samples were analysed for a range of elements using ICP-MS (Table 3).
At Pontardawe and Tinsley, where an established measurement programme was
adapted for comparison, a 24 h period was sampled. Thus the frequency of
PM10 filter sampling at the adjacent UK Heavy Metals Network sites was
increased from weekly to daily for these field evaluations. The filters were
digested using HNO3 / H2O2 digestion following the
European reference method EN14902 and analysed for a range of elements
(Tables 4 and 5) using ICP-MS (Goddard et al., 2016).
The certified reference material was used for quality control in both filter
digestion protocols. As standard reference materials are usually not an exact
match for the matrix of the sample, the resulting recovery rates serve as a
quality control parameter rather than a calibrant. Samples were thus not
corrected for the recovery rate but checked for compliance with the
requirements described in EN14902; recovery rates for both digestions methods
are given in Supplement S5.
Overview of Marylebone Road, London measurements by XACT and ICP-MS
(ng m-3). The asterisk (*) denotes that only 18 samples were collected for XACT As).
XACT (ng m-3)
ICP / MS (ng m-3)
Species
Mean
SD
med
Min
Max
LOD
Mean
SD
Med
Min
Max
LOD
Marylebone Road, London (n = 19)
As*
1.51
2.4
0.40
0.001
8.8
0.00020
0.97
1.02
0.53
0.049
4.0
0.099
Ba
15.8
14.3
10.0
1.74
50
0.31
15.1
9.9
11.0
3.1
39
0.0166
Ca
67
35
61
19.5
157
1.11
71
32
65
23
142
0.0166
Cd
4.0
0.37
4.0
3.4
4.7
2.4
0.114
0.106
0.079
0.023
0.39
0.0046
Ce
1.07
0.198
1.09
0.61
1.42
0.135
0.38
0.128
0.36
0.182
0.62
0.00030
Cl
400
400
250
4.4
1180
2.1
Cr
1.33
0.52
1.35
0.46
2.4
0.025
Cu
21
7.3
21
6.5
35
0.29
16.5
6.6
14
3.7
29
0.187
Fe
470
124
450
240
710
5.4
380
90
360
230
600
1.52
K
230
230
103
59
870
7.9
230
230
110
48
890
8.1
Mn
4.9
1.32
4.6
3.0
8.1
0.076
3.9
1.33
3.8
1.91
7.3
0.045
Mo
0.64
0.109
0.62
0.46
0.97
0.40
Ni
0.73
0.60
0.54
0.25
2.2
0.099
1.33
0.74
1.14
0.50
2.8
0.0044
Pb
11.1
8.7
7.7
1.66
31
0.116
8.1
7.2
5.1
1.10
25
0.093
Pt
0.177
0.010
0.175
0.161
0.20
0.078
S
600
330
460
180
1600
3.3
Se
0.177
0.169
0.112
0.070
0.77
0.031
Si
110
70
85
72
340
65
Sr
3.8
5.8
0.95
0.47
19
0.25
2.9
4.3
0.93
0.106
14.6
0.026
Ti
4.4
2.7
3.4
1.80
12
0.158
2.9
2.5
1.97
0.28
9.1
0.067
V
0.84
0.81
0.67
0.138
2.7
0.085
Zn
27
16
21
5.2
57
0.195
22
10.9
17.7
7.5
39
1.43
Overview of Pontardawe, Wales measurements by XACT and ICP-MS (ng m-3).
XACT (ng m-3)
ICP / MS (ng m-3)
Species
Mean
SD
Med
Min
Max
LOD
Mean
SD
Med
Min
Max
LOD
Pontardawe, Wales (n = 25)
As
0.43
0.47
0.22
0.037
2.2
0.00020
0.23
0.31
0.081
0.030
1.12
0.037
Ba
1.41
0.63
1.10
0.97
3.1
0.31
Ca
191
109
155
50
510
1.11
Cd
3.0
0.35
2.9
2.5
3.8
2.4
0.085
0.080
0.068
0.004
0.31
0.0110
Ce
0.85
0.30
0.76
0.46
1.95
0.135
Cl
5200
3000
5000
330
12 700
2.1
Cr
1.62
2.4
0.41
0.065
9.8
0.025
1.52
0.81
1.26
1.26
4.8
1.43
Cu
3.8
2.2
3.9
0.67
8.9
0.29
4.0
2.2
3.7
0.63
9.1
0.099
Fe
230
196
154
28
780
5.4
210
168
183
41
700
6.0
K
154
60
138
83
340
7.9
Mn
3.1
2.7
2.3
0.55
11.0
0.076
2.7
2.5
2.1
0.180
9.9
0.071
Mo
1.15
2.1
0.58
0.45
10.2
0.40
Ni
20
64
2.5
0.24
320
0.099
21
58
3.0
0.192
290
0.54
Pb
3.7
4.3
2.6
0.29
21
0.12
2.9
3.5
1.99
0.140
16.6
0.22
Pt
0.30
0.47
0.189
0.162
2.5
0.078
S
530
240
450
196
1130
3.3
Se
0.24
0.164
0.197
0.096
0.88
0.031
1.34
0.37
1.32
0.73
1.92
0.190
Si
280
420
102
92
1820
65
Sr
2.5
1.43
2.2
0.49
6.3
0.25
Ti
8.7
15.4
2.8
0.61
65
0.158
V
1.11
1.29
0.45
0.159
4.3
0.085
1.10
1.18
0.62
0.094
3.9
0.0160
Zn
7.3
6.9
5.3
0.69
34
0.195
6.8
7.1
5.8
0.32
34
0.81
Overview of Tinsley, Sheffield measurements by XACT and ICP-MS (ng
m-3).
XACT (ng m-3)
ICP/MS (ng m-3)
Species
mean
SD
Med
Min
Max
LOD
Mean
SD
Med
Min
Max
LOD
Tinsley, Sheffield (n = 60)
As
2.9
4.8
1.35
0.035
33
0.00020
1.50
3.4
0.78
0.019
26
0.037
Ba
2.6
3.6
1.75
0.98
28
0.31
Ca
400
260
370
37
1100
1.11
Cd
3.4
0.57
3.3
2.7
6.6
2.4
0.80
1.64
0.32
0.035
11.7
0.0110
Ce
0.76
0.22
0.73
0.41
1.52
0.135
Cl
1370
1100
1140
36
5100
2.1
Cr
53
65
30
0.42
350
0.025
55
51
38
3.9
250
1.43
Cu
17.5
11.0
14.6
2.3
47
0.29
19.3
12.5
16.0
2.6
56
0.099
Fe
670
440
570
83
1950
5.4
680
420
580
92
1600
6.0
K
138
92
108
17.0
420
7.9
Mn
47
53
32
1.58
290
0.076
41
44
29
1.82
240
0.071
Mo
15.1
24
7.0
0.65
130
0.40
Ni
25
29
14.0
0.22
113
0.099
24
26
13.8
0.99
113
0.54
Pb
22
23
13.1
1.33
125
0.116
22
22
11.8
1.21
111
0.22
Pt
0.186
0.017
0.185
0.166
0.28
0.078
S
780
670
550
126
3400
3.3
Se
0.93
1.30
0.31
0.075
5.5
0.031
1.83
1.62
0.94
0.26
6.2
0.190
Si
210
150
164
71
780
65
Sr
1.15
0.68
1.10
0.41
3.6
0.25
Ti
23
36
14.3
1.42
220
0.158
V
1.16
2.0
0.60
0.179
12.9
0.085
1.45
1.47
1.02
0.171
9.6
0.0160
Zn
100
120
58
4.5
620
0.195
101
117
56
3.8
610
0.81
Overview of Marylebone Road, London hourly SO4 measurements
in PM2.5 by XACT and ACSM (ng m-3); and hourly SO4,
K, Cl, Ca measurements in PM10 by XACT and URG (ng m-3); The asterisk
(*) denotes that SO4 was calculated as non-sea salt SO4
using S and Cl measurements; the asterisk (**) denotes that SO4
was calculated as predicted SO4 using S measurements.
XACT (ng m-3)
ACSM (ng m-3)
Species
n
Mean
SD
Med
Min
Max
LOD
Mean
SD
Med
Min
Max
LOD
SO4*
737
2600
2200
1880
240
10 500
NA
2000
1700
1460
58
8300
35
XACT (ng m-3)
URG (ng m-3)
Species
n
mean
SD
med
min
max
LOD
mean
SD
med
min
max
LOD
SO4**
1045
1750
1210
1450
164
9000
NA
1040
810
810
54
6500
100
K
776
145
69
133
24
410
6.2
154
42
150
75
380
100
Cl
1045
2700
2400
2100
42
22000
9
1790
1530
1370
132
15 000
100
Ca
996
590
490
430
49
2900
3.3
440
300
360
97
2300
100
Aerosol Chemical Speciation Monitor (ACSM)
The ACSM measured the chemical composition of non-refractory PM1
(NO3, SO4, NH4 and organic mass) and is fully
described in Ng et al. (2011). Briefly, air was drawn through an URG
PM2.5 size selective inlet (URG-2000-30EQ) at 0.18 m3 h-1
and subsequently dried using a Permapure™ drier (Perma Pure PD Dryer,
PD-07018T-12MSS). Particles were focused using an aerodynamic lens with a
50 % transmission range of 75 to 650 nm (Liu et al., 2007) and
subsequently flash vaporised, ionised and analysed using mass spectrometry at
0 to 100 amu. The signal was resolved into NO3, SO4,
NH4 and organic mass using a library of known fragmentation
characteristics. The aerosol was sampled and analysed alternately with
background air, allowing a continuous air subtraction, and averaged to an
hourly time resolution. The ionisation efficiency of nitrate and the relative
ionisation efficiencies of ammonium and sulfate were calculated using a
mono-disperse supply of ammonium nitrate and ammonium sulfate aerosols.
These were size selected through a differential mobility analyser and counted
using a condensation particle counter (CPC) as described by Crenn et
al. (2015). The collection efficiency was calculated using the Middlebrook
parameterisation (Middlebrook et al., 2012), which calculates an optimum
collection based on aerosol acidity, inlet humidity and particle composition.
The ACSM measurements were combined with Aethalometer measurements
(PM2.5) and compared to PM2.5 mass measured using the TEOM FDMS or
PM1 mass estimated using SMPS measurements as described by Crenn et
al. (2015).
Ambient Ion Monitor- URG-900B (URG)
The URG-900B Ambient Ion Monitor continuously measured water-soluble anion
and cation concentrations (Cl-, SO42-,
NO3-, Na+, NH4+, K+,
Mg2+, and Ca2+) in PM10 and is described in
Beccaceci et al. (2015). Briefly, the sample was drawn at a flow rate of
1 m3 h-1 through a size selective inlet (PM10); the
sample was then split isokinetically through a flow splitter to allow a
0.18 m3 h-1 flow into a liquid diffusion denuder containing
H2O2 to remove interfering acidic and basic gases. The remaining
particles in this air stream were then enlarged in a super saturation chamber
and finally collected in an aerosol sample collector and injected into the
(anion and cation) ion chromatographs every hour.
Laboratory based filter analysis using the XACT
To trial a filter analysis technique using the XACT, PM10 was sampled
onto polytetrafluoroethylene (PTFE) filters (Zefluor, 0.5 µm,
47 mm disc, Pall Life Sciences 516-8908) for 24 h using a Partisol 2025
during the field campaign in Sheffield in February and March 2017. These PTFE
filters were a similar material to the XACT filter tape but the stronger
structure enables easier handling during punching and analysis. After
exposure a 25 mm punch was taken out of the exposed filters for analysis
with the XACT on its return to the laboratory. The punching tool was always
aligned with the edge of the exposed area. The punch was transferred into a
filter holder, identical to the one used for instrument calibration with thin
film standards, and transferred into the holder slot in the analysis block of
the XACT. The analysis was performed on a 15 min sample time using the XRF
control program in a manual analysis mode. The energy condition set up
remained the same as during the field sampling in the automation mode. Each
filter was analysed four times, and the filter punch was rotated 90∘
in the filter holder in between replicates in order to account for
non-uniformity of the particle deposit on the filter punch. The XACT results
were used to calculate daily ambient element concentrations, which were
compared to the daily mean concentration measured by the XACT in situ. A
total of 12 filters were analysed. For quality assurance field and laboratory
filter blanks were analysed and used to correct for the filter background.
The blank measurements were also used to calculate the limit of detection for
this method.
Regression analysis approach
All comparisons were carried out using the Deming regression which minimises
the sum of distances between the regression line and the X and Y variables
taking into account the uncertainties in both variables (Deming, 1943).
Treatment of measurements below limit of detection
In all comparisons data under the detection limit were used as measured
unless the value was zero or below, in which case 0.5*LOD was used to
replace the value. By including values below the LOD it was possible to
calculate daily XACT mean concentrations, which might have been lost if data
below the LOD had been excluded and the daily data capture had not been met.
Uncertainty evaluation
The expanded uncertainty, representing a 95 % level of confidence, was
calculated by taking the root of sum square of the separate sources of
uncertainty as shown below:
U=LODi2+b⋅ci2,
where LODi is the limit of detection of element i (here calculated
as 3 times the experimental standard deviation of field or laboratory
blanks), ci is the measured concentration of the element (in ng m-3),
and b is an element dependent factor, which was derived from
experimental and literature values (US-EPA, 1999). For the XACT measurements,
the combined uncertainty included contributions of 3√3 %
from flow (CEN, 2014), 5 % from calibration standard uncertainty (US-EPA,
1999), 2.9 % from long term stability (calculated from the standard
deviation of hourly internal Pd reference) and an element-specific
uncertainty associated with the spectral deconvolution calculated by the
instrument software for each spectra. The XACT LOD was determined using HEPA
field blank measurements during each campaign; these are shown in Table 3.
For the ACSM, the sulfate measurement uncertainty was estimated as 14 %
(coverage factor k = 2) for sulfate at a 30 min resolution by Crenn et
al. (2015) and the LOD was determined using HEPA field blank measurements as
34.9 ng m-3. For the URG, the chloride and sulfate LODs were reported
by the manufacturer as 100 ng m-3 and verified by Beccaceci et
al. (2015). The uncertainty of the species measured by ion chromatography was
estimated at 4.5 % (coverage factor k = 2) by Yardley et al. (2007) and
combined with the additional 97 % extraction efficiency of a
particle-to-liquid sampler system estimated by Orsini et al. (2003).
Deming regression of Cl (a), K (b), S (c)
and Zn (d) mass concentrations measured with the XACT and calculated
from TEOM mass measurements.
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Results and discussion
Laboratory experiment
For the calibration test a range of solution concentrations were produced to
assess the instrument response (see Supplement S2). A subset of
concentrations, which span the concentrations encountered during the field
campaign, was used for the final comparison (see
Table 2). The highest element concentrations in the
standards used for comparison were between 9 (S) and 25 (Zn) times lower
than the commercial thin film standards when compared as ng.
All calibrations resulted in a linear relationship between the mass
calculated using TEOM mass concentrations and measured by the XACT for the
standard range used. Sample self absorption effects were calculated to be
< 1 % for the maximum concentration of S (the lightest element
used) and therefore insignificant in the use of this instrument. All calibrations resulted in a linear relationship between
the mass calculated using TEOM mass concentrations and
measured by the XACT for the standard range used (Fig.2). TEOM and
XACT results agreed well in all cases with slopes between 0.94 and 0.99.
Slopes are not significantly different from the 1:1 line for all comparisons
(95% confidence interval). The coefficient of determination (R2)
ranged between 0.98 (S) and 0.99 (Cl, K, Zn). The XACT response to the
generated particles was thus comparable to the response of the commercial
standards used for calibration. A similar result was found by Indresand et
al. (2013) using prepared sulfur reference materials for XRF calibration.
Field evaluation: overview
An overview of the data recorded in each comparison is given in Tables 3–6
and includes the limit of detection for all elements. Sb was not included in
the analysis as spectral interference resulted in a high LOD.
Time series of K (a) and Ba (b) concentration
(µg m-3) using hourly XACT and daily ICP-MS measurements at
Marylebone Road, London.
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The sampling at Marylebone Road was carried out using a PM2.5 inlet
during a period when peak concentrations were dominated by fireworks activity
(October–December 2014). The mean concentrations across all elements measured during
this campaign ranged from 0.177 to 600 ng m-3 and elements
typically used in fireworks such as Ba, Sr, K and Ti (Godri et al., 2010;
Moreno et al., 2007; Vecchi et al., 2008) had high maximum concentrations.
Traffic emissions further influenced the metal concentrations at Marylebone
Road. Overall the order of the elements in terms of mean concentration was as follows:
S>Fe>Cl>K>Si>Ca>Zn>Cu>Ba>Pb>Mn>Ti>Cd>Sr>As>Cr>Ce>V>Ni>Mo>Pt>Se.
This dataset helps highlight that high time resolution data has the advantage
of giving much more detailed information on high pollution events, which can
be used e.g. in source apportionment (Vecchi et al., 2008) and for health
studies (Godri et al., 2010; Hamad et al., 2016). Figure 3 shows the daily
filter and hourly XACT measurements of K and Ba during a period of increased
bonfire and fireworks activity due to Diwali (Hindu festival of light) and
Guy Fawkes celebrations. The daily filter measurements show that the highest
concentrations of K, which is used as an oxidiser in fireworks (Moreno et
al., 2007) but also a tracer for biomass burning, were measured on the 5 and
6 November 2014, followed by slightly lower concentrations on the 7 and
8 November. On the other hand Ba, which is used in green fireworks (Moreno et
al., 2007), displays similarly high concentrations on all four days. Looking
at the K concentration in a higher time resolution as measured by the XACT,
it is evident that peak concentrations were comparable on the nights of the
5, 7 and 8 November (data are missing for 6 November due to instrument
failure) but the high concentrations did not last as long on 7 and
8 November. The highest Ba concentration on the other hand was measured on
8 November with lower concentrations on 5 and 7 November. This difference in
contribution might point to different fireworks being used.
Polar plot of the Cr concentrations (ng m-3) in Pontardawe,
Wales using daily ICP-MS measurements (a) and hourly XACT
measurements (b).
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Sampling at Pontardawe, Wales was carried out in an area dominated by
metallurgical industry, which is reflected by the high nickel concentrations
measured (i.e. the mean nickel concentration at Pontardawe was 27 times
higher than that measured at Marylebone Road). Overall, the mean elemental
concentrations measured in this campaign ranged from 0.24 to
5200 ng m-3. The concentrations and dominant elements will be
influenced by the site characteristics as well as the size range sampled;
e.g. Cl from sea salt is predominantly found in the coarse fraction and thus
much higher at Pontardawe as the sample site is closer to the sea and
sampling was carried out using a PM10 head. The order of elements in
terms of mean concentration in Wales was as follows:
Cl>S>Si>Fe>Ca>K>Ni>Ti>Zn>Cu>Pb>Mn>Cd>Sr>Cr>Ba>Mo>V>Ce>As>Pt>Se.
In Wales, the availability of high time resolution data, in conjunction with
meteorological data and source emission activity allowed us to pinpoint
pollution sources more accurately. Cr concentrations from local sources were
studied to identify contributions from different industries. As can be seen
in Fig. 4 the 24 h filter data leads to very different source directions
than the higher time resolution data by the XACT (Font et al., 2017). This
could be used to address policy breaches with more targeted abatement
measures.
Deming regression results and coefficient of determination for XACT
comparison with ICP-MS, separated by HF / HClO4 and
HNO3 / H2O2 digestions.
HF / HClO4
HNO3 / H2O2
Element
Slope
Intercept
R2
Slope
Intercept
R2
As
2.0 (1.49–2.6)
-0.33 (-0.65–0)
0.95
3.8 (1.90–5.7)
-0.23 (-0.49–0.020)
0.90
Ba
1.04 (0.73–1.35)
-1.50 (-4.8–1.79)
0.98
Ca
1.14 (0.84–1.45)
-9.2 (-31–13)
0.70
Cr
0.99 (0.92–1.06)
-1.70 (-2.6–0.79)
0.95
Cu
1.31 (1.05–1.57)
0.29 (-3.1–3.7)
0.93
0.95 (0.92–0.98)
-0.03 (-0.22–0.17)
0.89
Fe
1.26 (0.65–1.87)
-1.29 (-220–210)
0.89
1.03 (0.99–1.07)
-10 (-18.19–2.0)
0.96
K
1.03 (0.92–1.15)
-1.23 (-14.83–12.37)
0.96
Mn
1.28 (0.70–1.86)
0.050 (-1.97–2.1)
0.92
1.10 (1.07–1.14)
0.17 (0.020–0.32)
0.99
Ni
0.73 (0.48–0.98)
-0.20 (-0.45–0.05)
0.67
1.07 (1.00–1.14)
-1.21 (-1.64–0.77)
0.99
Pb
1.44 (1.31–1.57)
0.140 (-0.37–0.65)
1.00
1.02 (0.99–1.06)
0.36 (0.10–0.61)
0.99
Se
0.83 (0.73–0.94)
-0.45 (-0.57–0.33)
0.67
Sr
1.25 (1.14–1.36)
-0.0100 (-0.19-0.17)
1.00
Ti
1.44 (0.68–2.2)
0.91 (-0.42–2.2)
0.72
V
0.87 (0.74–1.01)
-0.130 (-0.22–0.04)
0.89
Zn
1.62 (1.17–2.1)
-4.4 (-13.15–4.5)
0.50
1.04 (0.98–1.09)
0.37 (-0.58–1.31)
0.94
The influence of the local industry in Tinsley, Sheffield was reflected by
high concentrations of metals like Ni and Cr, with mean concentrations more
than 30 times that found in the Marylebone Road campaign. The mean elemental
concentrations overall ranged from 0.186 to 1370 ng m-3.
The order of elements in terms of mean concentration in Tinsley was as follows:
Cl>S>Fe>Ca>Si>K>Zn>Cr>Mn>Ni>Ti>Pb>Cu>Mo>Cd>As>Ba>V>Sr>Se>Ce>Pt.
The mean hourly concentration of non-sea salt sulfate (XACT) and
non-refractory sulfate (ACSM) during the fireworks campaign at Marylebone
Road was 2600 and 2000 ng m-3, respectively, with hourly concentration
ranging from 240 to 10 500 ng m-3 SO4 (non-sea salt) and 58
to 8300 ng m-3 for non-refractory SO4.
The comparison of the XACT with the URG was carried out in PM10 at
Marylebone Road during winter 2014/2015. The hourly concentration of water
soluble anions and cations ranged from 154 ng m-3 (K) to
1790 ng m-3 (Cl) compared to 145 ng m-3 (K) to
2700 ng m-3 (Cl) in total element concentrations.
Time series of non-sea salt SO4 concentration (XACT,
calculated) and non-refractory SO4 (ACSM, measured) in ng m-3
at Marylebone Road, London.
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Deming regression of water soluble Ca (a), Cl (b),
K (c) and SO4 (d) as measured by URG and Ca, Cl,
K and calculated SO4 (from elemental S) measured by XACT
(ng m-3) at Marylebone Road, London.
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Slope values (+95 % confidence interval) of Deming regressions
(XACT vs. ICP-MS (split in HF / HClO4 and HNO3 / H2O2
digestion) and XACT vs. XACT, filter), split by element (a) and
corresponding box-and-whisker plots split by method (b).
![]()
Comparison with ICP-MS
The filter comparison results were split by the two digestion methods:
HF / HClO4 and HNO3 / H2O2. This had
the additional advantage of grouping the two industrial campaigns that were
carried out in PM10 and separating the campaign at Marylebone Road in
PM2.5. LODs were not consistently higher for either the ICP-MS or the
XACT measurements (Tables 3–5). All elements were compared using Deming
regression and a summary of all calculated slopes and intercepts are given in
Table 7 (including R2 values); the corresponding figures are available
in the supplementary information section. The XACT agreed well with the
ICP-MS measurements and R2 ranged from 0.50 to 1.00 and 0.67 to 0.99,
with a median of 0.91 and 0.95, following HF / HClO4 and
HNO3 / H2O2 digestion, respectively. Deming
regression for Fe resulted in slopes that were not significantly different
from unity for either subset. Slopes were also not significantly different
from unity for Ba, Ca, K, Mn and Ti following digestion with
HF / HClO4 and for Cr, Ni, Pb, V and Zn following digestion
with HNO3 / H2O2. For the element As the XACT recorded
significantly higher concentrations than those measured by ICP-MS,
irrespective of digestion method. This was also the case for elements Cu, Pb,
Sr and Zn after HF / HClO4 digestion and for Mn after
HNO3 / H2O2 digestion. For the elements Ni (after
HF / HClO4 digestion), Cu and Se (after
HNO3 / H2O2 digestion) the concentrations measured
by the XACT were significantly lower than those measured by the ICP-MS. Cr
and V were not reported for HF / HClO4 due to contamination of
the HClO4 used in the digestion. In case of Cd and Ce a large
number of hourly XACT concentrations were below the LOD, and thus the
elements were excluded from further comparison.
There are a variety of possible reasons for the differences observed between
the methods. In the case of the filter analysis, the blank filters were
found to be variable and thus subtracted values may result in an under- or
overestimation of the true concentration; the digestion recovery rates were
not taken into account; many concentrations were close to the detection
limit for the elements As in all campaigns and Ni during the Marylebone Road
campaign. These stated reasons might influence the two digestions methods to
different extents. Unfortunately, there was no opportunity to undertake both
digestions on the same samples. To provide some insight into how the two
digestion methods compared, the XACT measurements were grouped into
concentration appropriate bins and the associated ICP-MS measurements from
each digestion method were averaged and compared. These are shown in Supplement S6
(Deming regression of ICP-MS using different digestion methods). For the
XACT, the standards used in calibrations were much higher than ambient
concentrations and the calibration matrix differed from sample matrix
(Indresand et al., 2013). Despite every effort being made to co-locate the
sample inlets in all field trials, slight differences in inlet location,
especially when close to the road, could not be avoided. This and different
temperatures of the sample inlets may also contribute to differences
observed in concentrations. Nevertheless, the results of the XACT comparison
with ICP-MS in this study are comparable to those reported in other studies
(Furger et al., 2017).
Comparison with ACSM at Marylebone Rd
The hourly values of S and Cl measured with the XACT were used to calculate
hourly non-sea salt sulfate (SO4) based on their relative
abundance in sea water (Millero et al. 2008). It should be noted that Cl is
used in the absence of the preferred Na and Cl concentration measured could
be partially depleted by reaction between NaCl and nitric acid
(HNO3). The hourly non-sea salt sulfate was compared to the hourly
sulfate (predominantly ammonium sulfate) which is non-refractory measured
by the ACSM (Chang et al., 2011). The mean (median) concentrations were 2600
(1880) ng m-3 and 2000 (1460) ng m-3, respectively. The time
series of these measurements is shown in Fig. 5 and demonstrates the
excellent temporal agreement, which is reflected by an R2 of 0.93. The
correlation resulted in a slope of 1.41 (95 % confidence interval (CI)
1.35–1.46) and an intercept of 53 (95 % CI 13.4–93) ng m-3. The
larger non-sea salt SO4 means/medians and slope > 1
likely resulted from measuring different size fractions; PM2.5 for the
XACT vs. PM1 for the ACSM.
Comparison with URG
Hourly concentrations of water-soluble Cl, K and Ca measured by URG were
compared to the hourly measured total Cl, K and Ca measured by the XACT.
Furthermore, hourly measured water-soluble SO4 (URG) was compared
to hourly SO4 calculated from the S measurement by the XACT
instrument (Table 6, Fig. 6). The XACT measured higher concentrations for all
these components. The slopes were similar for the SO4 (1.65) and Cl
(1.68) and slightly higher for Ca (1.89). Deming regression for K resulted in
a very high slope (4.55) but this was likely the result of concentrations
being close to the LOD for the URG, the result was consistent with the findings
presented by Beccaceci et al. (2015). The R2 for Ca, Cl, K and
SO4 was 0.86, 0.93, 0.36 and 0.95, respectively.
The higher concentrations measured by the XACT relative to the URG was likely
caused by the low water-solubility of Cl, K, Ca and S containing minerals as
well as the penetration efficiency of larger aerosols through the URG annular
denuder (Beccaceci et al. 2015). The range of sources of these ions/elements
resulted in variations in particle size and solubility and hence the relative
response of the two instruments. When considering solubility, the larger
slopes are associated with the least soluble compounds. In order of
decreasing solubility (and increasing slope) SO4 exists
predominately as (NH4)2SO4 (solubility of
754 g L-1 in water), Cl is principally from marine sources as NaCl
(solubility of 359 g L-1 in water at 20 ∘C); Ca in the urban
environment is typically from mineral or construction sources and is
comprised of CaCO3 and CaSO4 ⚫ 2H20
(solubilities of 0.013 and 2.55 g L-1 respectively) as
well as calcium silicates (which are insoluble) (Dean and Lange, 1999). When
considering particle size, the sources of aerosols containing Cl, K, Ca and S
are often larger than PM2.5 and may therefore be influenced by the
reduced penetration efficiency of the URG annular denuder (Dick et al., 1995;
Visser et al., 2015b). The chemical composition of different size fractions
was sampled using a rotating drum impactor (RDI) and analysed with
synchrotron radiation-induced X-ray fluorescence spectrometry (SR-XRF) during
a winter campaign at Marylebone Road in 2012 (Visser et al., 2015b) and the
percentage of the element in the PM10-2.5 fraction can be used to
highlight how these elements are distributed between the fine and coarse
particle sizes: S 35 %, K 57 %, Ca 72 % and Cl 73 %. This
illustrates that a sampling bias, due to the penetration efficiency of the
annular denuder may play a role in the difference between the URG and the
XACT; however, due to the additional variation in solubility this is difficult
to quantify.
Laboratory based filter analysis using the XACT
With a mean R2 of 0.95 daily concentrations measured on the filter by
the XACT compared well with the measurements made by the XACT when deployed
in the field in Tinsley, Sheffield. The resulting regression slopes are
compared with those from the ICP-MS comparison (Fig. 7). The small sample
number (N=12) resulted in a higher uncertainty in the slopes but in
general the slopes were comparable to those from the ICP-MS filter analyses.
The intercepts for most elements were not significantly different from 0. The
slopes for the elements Ba, Cl, Cr, Cu, Mn, Ni, Sr, V and Zn were not
significantly different from the 1:1 line. For the elements As, Ca, Fe and
Ti the XACT measurements were lower when deployed in the field than when
measuring the 24 h filter samples. Whereas for the elements K, Mo, Pb, S and
Se online field measurements resulted in higher results than off-line filter
measurements. Reasons for the discrepancies in the slopes may be caused by
the difference between the filter material and analysis time used for the
filter samples (Zefluor, 15 min) in comparison to the online method
(proprietary PTFE tape, 1 h). Additionally the fitting routine used in the
deconvolution software is optimised for the filter tape used and might also
contribute to the observed differences. Full results can be found in the
supplementary information.
Punching and subsequent filter analysis was found to be practically
achievable, although time consuming, when compared to automated laboratory
techniques.
Conclusions
This study was performed to evaluate the XACT 625 in the field and under
laboratory conditions. In the field, the XACT was evaluated in three
contrasting environments and compared to laboratory-based ICP-MS analysis as
well as alternative high time resolution instrumentation. The XACT was found
to be a highly reliable measurement instrument which showed an excellent
correlation with standardised laboratory analysis (ICP-MS) albeit with a
slight overall positive bias (median 1.07). Differences in the individual
results were element specific but generally attributable to a combination of
variable filter blank levels, recovery rates from acid digestion, instrument
calibration, sampling temperature and small differences in inlet location.
When compared to the alternative aerosol mass spectrometry and ion
chromatography based high time resolution techniques, the XACT showed good
temporal agreement but with a clear positive difference (median 1.68)
compared to the ICP-MS; this was likely due to the differences in the size
selection methodology employed by the different techniques as well as
particle volatility and water solubility. However, these differences (size,
solubility and volatility) could be utilised to provide information about
different sources and their contributions; such as the difference between
refractory sodium chloride and non-refractory ammonium chloride.
The laboratory experiment, which compared the XACT measurements of the
elemental constituents of generated aerosols with the mass measured using a
TEOM, proved to be a successful method for verifying the response of the XACT
over environmentally relevant elemental concentrations. The slopes were close
to, and not significantly different from, unity (0.94–0.99). This suggests
that the XACT accurately measures elemental ambient aerosol composition and
that the positive bias, when compared to the ICP-MS measurements identified
in the field experiments in all locations, was not due to the XACT
calibration but more likely due to the remaining reasons listed above. It
further shows that generated aerosols can be used to calibrate the XACT to
provide ongoing quality assurance checks.
An ambient filter sampling analysis technique, using the XACT as a
laboratory based instrument, was also evaluated. The concentrations measured
on the sampled filter compared well with the in situ XACT with median slopes
of 1.07 and was therefore comparable with the ICP-MS filter-based
technique. This technique diversifies further the use of the XACT,
especially if the instrument has downtime between campaigns. This technique
also allows a direct comparison of the XACT and other XRF systems using a
filter sample.
Future work should include a repetition of the laboratory calibration using
an overall lower range of standards and combining solutions in order to have
a more complex particle composition. A standard reference material, either
in solution or on filter should also be included in future calibration
tests. Further, to develop the filter analysis method using the XACT and
piloted in this study, different filter materials should be tested and the
deconvolution approach optimised if necessary.