Upload
gerard-reeves
View
214
Download
2
Tags:
Embed Size (px)
Citation preview
Performance of Continuous
PM2.5 Monitors at a Monitoring Site in Ottawa, Canada
Performance of Continuous PM2.5 Monitors at a Monitoring
Site in Ottawa, Canada
Tom Dann
Luc White, Alain Biron
Environment Canada, ETC, Ottawa
Tom Dann
Luc White, Alain Biron
Environment Canada, ETC, Ottawa
Environment EnvironnementCanada Canada
NESCAUM Monitoring and Assessment Committee Meeting Troy, NH April 24/25, 2007
Ottawa Monitoring Site
Study Period: May 2004 – present> 500 days of data for 1 or more continuous instruments with filter-based data
24h PM2.5 Max: 64 µg/m³ 98th Perc: 37 µg/m³ Mean: 10.0 µg/m³
Temperature Range: -27°C to 29°C Filter based samplers: R&P Partisol FRM
and R&P Partisol Sequential Dichot
Ottawa Monitoring Site
Met-One BAM 1020 May 2004
Met-One BAM 1020 (new) Nov 2006
TEOM SES (30°C) May 2004
TEOM FDMS July 2004
GRIMM 180 (PM10, PM2.5, PM1.0) Oct. 2005
Thermo SHARP 5030 June 2006
Met-One BAM 1020
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 dataBAM Ottawa (Warm Seasons 2004-2006)
0 10 20 30 40 50 60
Filter Based Sampler (µg/m³)
0
10
20
30
40
50
60
BA
M 1
02
0 (
µg
/m³)
BAM 45%
BAM 35%
BAM45 = -0.9 + 1.34 * FILTERr = 0.984 n = 54BAM35 = -0.6 + 1.09 * FILTERr = 0.961 n = 152
Linear regression results for 24h dataBAM with 35% Humidity Setting Ottawa (2005-2006)
0 10 20 30 40 50
Filter Based Sampler (µg/m³)
0
10
20
30
40
50
BA
M3
5 (
µg
/m³)
BAM35_Cold
BAM35_Warm
BAM35_Cold = -1.7 + 1.02 * FILTERr = 0.983 n = 72BAM35_Warm = -0.6 + 1.09 * FILTERr = 0.961 n = 152
Replacement of BAM
Linear regression results for 24h dataTEOM-FDMS Ottawa (2004-2006)
0 10 20 30 40 50 60 70 80
Filter-based Sampler (µg/m³)
0
10
20
30
40
50
60
70
80
TE
OM
-FD
MS
(µ
g/m
³)
FDMS_Cold FDMS_Warm
FDMS_Cold = -0.8 + 1.07 * FILTERr = 0.993 n = 167FDMS_Warm = -0.3 + 1.08 * FILTERr = 0.969 n = 180
Grimm 180 Multi-channel Aerosol Spectrometer
Simultaneous measurement of PM1.0, PM2.5 and PM10
Particle counts by size (31 channels) and mass determinationusing algorithmsNo size cut on inlet – moisture control using Nafion dryerTruly continuous (real-time)
Results for 24h PM2.5 data: Grimm 180 (Ottawa) Jan. 2006 – Dec. 2006
0 5 10 15 20 25 30 35 40
Filter-based Sampler (µg/m³)
0
5
10
15
20
25
30
35
40
GR
IMM
(µ
g/m
³)
GRIMM_Cold Season GRIMM_Warm Season
GRIMM_Cold = 0.5 + 1.05 * FILTERr = 0.964 n = 47GRIMM_Warm = 0.03 + 1.07 * FILTERr = 0.941 n = 60
Grimm 180 Results – Ottawa Summer 2006
0
5
10
15
20
25
30
35
Conc.
(µg/m
³)
GrimmDichot
Humidity Effects on Grimm 180 (Ottawa)?
-10 -5 0 5 10 15 20 25
Dew Point Temp. (°C)
-6
-4
-2
0
2
4
6
8
GR
IMM
min
us
FIL
TE
R (
µg
/m³)
24h DataApril - September 2006
Results for 24h Coarse data: Grimm 180 (Ottawa) Jan. 2006 – Mar. 2007
0 5 10 15 20 25 30
Dichot Coarse (µg/m³)
0
5
10
15
20
25
30
GR
IMM
PM
10 -
PM
2.5 (µ
g/m
³)
GRIMM Coarse Before RecalGRIMMC = 0.8 + 0.24 * DICH r = 0.711
GRIMM Coarse After RecalGRIMMC = -1.0 + 0.82 * DICH r = 0.977
Results for 24h PM10 data: Grimm 180 (Ottawa) Jan. 2006 – Mar. 2007
0 5 10 15 20 25 30 35 40 45
Dichot PM10 (µg/m³)
0
5
10
15
20
25
30
35
40
45
GR
IM P
M10
(µ
g/m
³)
GRIMM PM10 Before RecalGRIMM10 = -0.4 + 0.85 * DICH r = 0.947
GRIMM PM 10 After RecalGRIMM10 = -0.2 + 0.93 * DICH r = 0.928
Grimm 180 Results – Ottawa January 29-31, 2007
0
10
20
30
40
50
60
70
80
Conc.
(µg/m
³)
FINECOARSE
Thermo SHARP 5030 Synchronized Hybrid Ambient Real-time Particulate Monitor
Truly continuous (real-time) Combination nephelometer
& beta-ray attenuation Light scattering photometer
is continuously calibrated by beta attenuation mass sensor
Intelligent Moisture Reduction (IMR) System heating the inlet tube; threshold is set at 40%
Linear regression results for 24h data: Sharp 5030 (Ottawa Jun. – Dec. 2006)
0 5 10 15 20 25 30 35 40 45
Filter-based Sampler (µg/m³)
0
5
10
15
20
25
30
35
40
45
Th
erm
o S
ha
rp (
µg
/m³)
TSHARP = 1.20+1.00*FILTERr = 0.958 n = 68
Performance During Air Mass Change (Ottawa September 2006)
10:00 14:00 18:00 22:00 02:00 06:00 10:00 14:00 18:00 22:00 02:00 06:00 10:00
Hour of Day
-6
-4
-2
0
2
4
6
8
10
12
14
16
18
20
22
24
Co
nce
ntr
atio
n (
µg
/m³)
TEOM SES
TEOM FDMS
GRIMM
THERMO SHARP
September 27 - 29, 2006
Cost Comparisons for Continuous PM2.5 Instruments (Canadian$):
Met-One BAM 1020$25,000
R&P 1400AB TEOM$25,400
R&P SES Kit $ 4,750
R&P 8500 FDMS Kit$10,700
TEOM-FDMS$36,100
GRIMM 180 (PM10, PM2.5, PM1.0)
$31,000 Thermo SHARP 5030
$26,500
2006 Performance Based on EPA ARM Template
Instrument N Slope Intercept
r
TEOM-SES 133 0.80 0.04 0.940TEOM-FDMS
126 1.06 -0.43 0.961
BAM 126 1.01 0.34 0.942GRIMM 107 1.06 0.27 0.953SHARP 68 1.00 1.20 0.958
PM Workshop – Ottawa April 2007
Presentations and Summary:
http://www.etc-cte.ec.gc.ca/NAPSAnnualRawData/Password: ozoneFolder: PMWORKSHOP2007