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Continuous Particulate Matter
(PM2.5) Monitoring
Tom Dann
Luc White, Alain Biron
Environment Canada, Ottawa
NESCAUM Monitoring and Assessment Committee Meeting
Newport, RI May 16/17, 2006.
Environment Environnement
Canada
Canada
NAPS
National Air Pollution Surveillance
(NAPS) Network
the NAPS program is a cooperative
federal-provincial-territorial network of
over 800 ambient air quality monitoring
instruments across Canada
http://www.etc-cte.ec.gc.ca/NAPS
Canada-wide Standard (CWS)
for PM2.5
a CWS of 30 µg/m³, 24-hour averaging time by
year 2010. Achievement to be based on the 98th
percentile ambient measurement annually,
averaged over 3 consecutive years.
daily sampling required
no annual standard
no prescribed measurement method
no prescribed temp. & pressure for concentration
units
reference to a Monitoring Protocol document
Existing PM2.5 Monitoring Sites in
Canada (2004) reporting to NAPS
98th Percentile PM2.5 Concentrations (µg/m³)
2001-2003 (U.S. FRM and Canada Adjusted
TEOM or Dichot.)
Seasonal Variations in Ammonium Nitrate at
Canadian Sites (2004 -2005)
20
18
16
14
12
10
8
AMMONIUM NITRATE (µg/m³)
6
4
2
0
1 2 3 4 5 6 7 8 9 10 11 12
1 2 3 4 5 6 7 8 9 10 11 12
1 2 3 4 5 6 7 8 9 10 11 12
Canterbury
St. Anicet
Montreal - Ontario St.
1 2 3 4 5 6 7 8 9 10 11 12
1 2 3 4 5 6 7 8 9 10 11 12
1 2 3 4 5 6 7 8 9 10 11 12
Toronto - Gage
Abbotsf ord
Burnaby
20
18
16
14
12
10
8
6
4
2
0
Linear regression results for 24h PM2.5 data –
R&P Dichotomous Sampler vs. R&P Partisol
(Ottawa)
40
1:1 Line
35
30
Dichot (µg/m³)
25
20
15
Cold Season Bias
10
DICH = 0.3 + 0.931 * PART r2 = 0.977
Precision = 9.5%
Overall Average = 9.1 µg/m³
CCV = 0.665
5
0
0
5
10
15
20
Partisol (µg/m³)
25
30
35
40
Linear regression results for 24h data – TEOMSES Ottawa (2004-2006)
70
1:1 Line
60
TEOM_W
TEOM_C
TEOM-SES (µg/m³)
50
40
30
Cold Season Bias
20
10
TEOM_W = -0.94 + 1.00 * DICH
TEOM_C = -0.02 + 0.69 * DICH
r2 = 0.969
r2 = 0.969
0
0
10
20
30
40
Dichot/Partisol (µg/m³)
50
60
70
Linear regression results for 24h data for
TEOM-SES and TEOM40 - Ottawa
(Winters 2004-2006)
70
1:1 Line
TEOM_SES
TEOM_40
60
TEOM (µg/m³)
50
40
30
Cold Season Bias
20
10
TEOM_SES = -0.03 + 0.69 * DICH r2 = 0.969
TEOM_40 = 0.61 + 0.52 * DICH r2 = 0.936
0
0
10
20
30
40
Dichot/Partisol (µg/m³)
50
60
70
Met-One BAM
low-level C14 radiation source
uses beta-ray attenuation and a
filter tape system
inlet is heated but filter is at
ambient (station) temperature
humidity problems in early
units caused higher readings in
the summer
‘smart heater’ is turned on by a
relative humidity sensor
hourly average output
Linear regression results for 24h data
BAM-SH Ottawa (Warm Seasons 2004-2006)
60
BAM45_W
BAM35_W
50
BAM (µg/m³)
40
30
20
BAM45_W = -0.34 + 1.31 * DICH r2=0.979
BAM35_W = -1.60 + 1.15 * DICH r2=0.970
10
0
0
10
20
30
Dichot/Partisol (µg/m³)
40
50
60
Linear regression results for 24h data
BAM-SH with 35% Humidity Setting
Ottawa (2005-2006)
50
BAM35_W
BAM35_C
BAM (µg/m³)
40
30
20
10
BAM35_W = -1.6 + 1.15 * DICH
BAM35_C = -1.4 + 1.00 * DICH
r2=0.970
r2=0.968
0
0
10
20
30
Dichot/Partisol (µg/m³)
40
50
TEOM-FDMS
Linear regression results for 24h data
TEOM-FDMS Ottawa (2004-2006)
80
FDMS_W
FDMS_C
70
TEOM-FDMS (µg/m³)
60
50
40
30
20
FDMS_W = -0.57 + 1.14 * DICH r2 = 0.976
FDMS_C = -0.90 + 1.07 * DICH r2 = 0.987
10
0
0
10
20
30
40
50
Dichot/Partisol (µg/m³)
60
70
80
Warm Season Linear regression results for 24h
data: BAM and TEOM-FDMS (Ottawa)
50
BAM35_W
FDMS_W
BAM/TEOM-FDMS (µg/m³)
40
30
20
10
BAM35_W = -1.60 + 1.15 * DICH
FDMS_W = -0.57 + 1.14 * DICH
r2 = 0.970
r2 = 0.976
0
0
10
20
30
Dichot/Partisol (µg/m³)
40
50
Grimm 180 Multi-channel Aerosol Spectrometer
Simultaneous measurement of PM1.0, PM2.5 and PM10
Grimm 180 Results – Ottawa 2005
25
Conc. (µg/m³)
20
15
Grimm
Dichot
10
5
0
10/15/05
10/29/05
11/12/05
11/26/05
12/10/05
Grimm = 0.67 + 0.97*DICH r2 = 0.970
Cold season linear regression results for 24h
data: Grimm 180 (Ottawa)
30
25
GRIMM25 (µg/m³)
20
15
10
5
GRIMM25 = 0.70 + 0.95 * DICH r2 = 0.964
0
0
5
10
15
Dichot/Partisol (µg/m³)
20
25
30
Cold Season Linear regression results for
24h data: BAM35, GRIMM and TEOMFDMS (Ottawa)
80
70
BAM35
FDMS
GRIMM25
Continuous Instruments (µg/m³)
60
50
40
30
20
BAM35 = -1.35 + 1.00 * DICH r2 = 0.968
FDMS = -0.90 + 1.07 * DICH r2 = 0.987
GRIMM25 = 0.70 + 0.95 * DICH r2 = 0.964
10
0
0
10
20
30
40
50
Dichot/Partisol (µg/m³)
60
70
80
Linear regression results for 24h data:
GRIMM PM10 (Ottawa)
50
45
40
Grimm PM10 (µg/m³)
35
30
25
20
15
GRIMMPM10Daily Avg = -1.5 + 1.05*x
r2 = 0.951
10
5
0
0
5
10
15
20
25
30
Dichot PM10 (µg/m³)
35
40
45
50
Cost Comparisons for Continuous PM2.5
Instruments:
Met-One BAM 1020
R&P 1400AB TEOM
R&P SES Kit
R&P 8500 FDMS Kit
GRIMM 180 (PM10, PM2.5, PM1.0)
$25,000
$26,500
$ 4,750
$12,700
$31,100
NAPS Working Groups
Recommendations and actions:
a reference method and standard operating procedure for
PM2.5 mass is required - all filter-based and continuous mass
measurements should be referenced to this
a NAPS Managers committee has developed a draft reference
method and draft SOPs for current field instruments
these are being incorporated into CWS probably through the
Monitoring Protocol document
data quality objectives still need to be developed to determine
acceptable comparability between instruments on a 24-hr
basis
an inter-comparison network is in operation (~15 sites) and
instrumentation has been deployed
Thanks!
Analytical Descriptions
ICP-MS – Agilent 7500c ICP-MS
Water extraction – 20 metals - DL 0.02 – 0.2 ng/m³
Acid digested (Near-total) – 20 metals – DL 0.02 – 0.4 ng/m³
Frequency of Detection of Metals
Element
Se
Cd
Pb
As
Mn
Cr
Frequency of
Detection
(XRF)
Frequency of
Detection
(ICP-MS)
Mean
Concentration
(ng/m³)
28 %
11 %
66 %
25 %
68%
16 %
52 %
93 %
100 %
92 %
100 %
95 %
0.4
0.2
2.6
0.9
2.5
2.3
Comparison of Arsenic Concentrations
(ng/m³) by Site and Month
7
6
5
4
3
2
Arsenic (ng/m³)
1
0
1 2 3 4 5 6 7 8 9 10 11 12
1 2 3 4 5 6 7 8 9 10 11 12
1 2 3 4 5 6 7 8 9 10 11 12
Canterbury
St. Anicet
Montreal-Ontario St.
1 2 3 4 5 6 7 8 9 10 11 12
1 2 3 4 5 6 7 8 9 10 11 12
1 2 3 4 5 6 7 8 9 10 11 12
Toronto-Gage
Abbotsf ord
Burnaby
7
6
5
4
3
2
1
0