clean air hamilton strategy
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Air Pollution in Hamilton – Health Effects and Sources November 22, 2006 McMaster Centre for Spatial Analysis. Clean Air Hamilton Strategy. Risk Management Approach Applied to Community Wide Actions Identify Problem Measure/Evaluate Prioritize Risks Inform Community Cooperative Actions. - PowerPoint PPT PresentationTRANSCRIPT
Air Pollution in Hamilton – Health Effects and Sources
November 22, 2006
McMaster Centre for Spatial Analysis
Clean Air Hamilton Strategy
Risk Management Approach Applied to Community Wide Actions
• Identify Problem• Measure/Evaluate• Prioritize Risks • Inform Community• Cooperative Actions
www.cleanair.hamilton.ca
The Problem
0
50
100
150
200
250
300
350
400
450
500
Deaths Resp Cardio
Deaths/Admissions
Sahsuvaroglu & Jerrett 2003
Health Impacts of Air Pollutants in Hamilton
Health Impacts in Hamilton – by Air Pollutant
0
20
40
60
80
100
120
140
160
180
200
Deaths Resp Cardio
O3
NO2
SO2
P10
CO
Sahsuvaroglu & Jerrett 2003
Study Objectives, Phase 1“Where is it coming from?”
Identify and rank sources, including transportation sources, of NOx, SO2, Airborne Particles and CO, using mobile monitoring techniques (no direct local sources of Ozone).
Investigate the effect of idling vehicles at a designated school during student drop off and pickup times.
Investigate trackout/road dust issues
National Pollutant Release Inventory – Hamilton Point Sources
• PM1056 Sources
• CO 14 Sources
• NOx 13 Sources
• SO2 9 Sources
Total Point Source Emissions by Contaminant
0
5,000
10,000
15,000
20,000
25,000
30,000
35,000
CO SOx NOx PM10
Tonnes
CO SOx NOx PM10
30,632 11,875 8,188 2,010Tonnes
What We’d Expect to See
• Carbon Monoxide – 66% Transportation, 23% Industry
• Sulphur Dioxide – 92% Industry, 5% Transportation
• Nitrogen Oxides – 57% Transportation, 37% Industry
• PM10 – 73% Open Sources/Road Dust, 18% Industry
Note: MOE identified trackout/road dust resuspension as a major problem
Emission Sources by Regions in Hamilton
Flamborough/Waterdown
East Mtn
NE Ind
Stny Crk
Mobile Command Centre
Instrument Rack Mounts
A/D Converter, Data Logger, GIS Software
Roof Mounting
Sampling Intakes
Gaseous/Particulate
GPS Head, Garmin 18, GIS Display
City/Traffic Monitoring
1. City Wide Sampling
2. Road Dust/Road Impacts
3. Intersection Impacts
4. Arterial Road Impact/ Burlington St.
5. Cycle Routes/ Anti Idling
Sampling Track, City Wide Scan
City Wide Sampling
11:0
7
11:1
7
11:2
7
11:3
7
11:4
7
11:5
7
12:0
7
12:1
7
12:2
7
12:3
7
12:4
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12:5
7
13:0
7
13:1
7
13:2
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13:3
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13:4
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13:5
7
14:0
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14:1
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14:2
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14:3
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14:4
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14:5
7
15:0
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15:1
7
15:2
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15:3
7
15:4
7
15:5
7
16:0
7
16:1
7
16:2
7
16:3
7
16:4
7
16:5
7
SO2
CO
NO
P10
Road Dust
BartonSt
Road Dust
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No
December 8, 2005
1 0 1 2 Kilometers
Wind
NO ppb
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P10
1 0 1 2 Kilometers
December 8, 2005
Wind
0
5
10
15
20
25
30
35
40
45
50
T/M R/C F/M B/A E44/Q E18/V M/W E
Location
SO2
CO
NOP10
City Wide Sampling, Residential Locations
0
20
40
60
80
100
120
Uppr Jmes Fennel Cannon Mhk/U Jmes Barton/20 Road avge Resident
SO2
CO
NO
P10
Roads vs Residential Areas
0
20
40
60
80
100
120
140
160
180
Time
P10
ug/
m3
NO
ppb SO2
CO
NO
PM10Mohawk and Upper James
Barton and Centennial Pkwy
= idling impact
--NO Residential
--PM10 Residential
Stoplight Idling – Concentrations Downwind
Burlington St. Upwind Downwind
10:5
210
:54
10:5
610
:58
11:0
011
:02
11:0
411
:06
11:0
811
:10
11:1
211
:14
11:1
611
:18
11:3
011
:32
11:3
411
:36
11:3
8
NO
NO2
P2.5
P10
Downwind
Upwind
Burlington St Contribution(Approx. 600 Trucks/Hr)
0
10
20
30
40
50
60
70
80
90
P10 P2.5 P1 NO NO2 SO2 CO
Difference
CARS
Vehicle Idling outside Schools
“Natural Experiment”
0
5
10
15
20
25
30
35
8:59
9:05
9:11
14:0
0
14:0
6
14:1
2
14:1
8
14:2
4
14:3
0
14:3
6
14:4
2
14:4
8
14:5
4
15:0
0
15:0
6
15:1
2
15:1
8
15:2
4
15:3
0
15:3
6
15:4
2
15:4
8
15:5
4
NO (ppb)
MorningStudent Dropoff
AfternoonStudentPickup
Natural Experimentpp b
Morning – Idling Vehicles
Trackout/Diesel Trucks
1. PM2.5, PM1 Components
2. Photos
3. Sample Trace
4. Consolidated PM10 Data
5. Comparison Previous Data
Road Dust , Covariance 20xPM1, 10xPM2.5, PM10
0
500
1000
1500
2000
2500
3000
3500
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79 82
20xP1
10xP2.5
P10
P2.5/P10 R2 = 0.7
P2.5/P1 R2 = 0.98
Road Dust/Trackout
18 Locations Monitored, 14 Sources Identified
0
500
1000
1500
2000
2500
PM10 ug/m3
Strathearne
Kenilworth N
Depew
Vict. NPortAuth
Nebo
Hwy 20Goder
Brampton
Pier 25
Imperial
Brant
BurlSher/Burl
Burl/Parkdale
Sherman
ChathamFrid
Parkdale
McKeil
ug
/m3
PM10 ROAD DUST
Ben Garden, Savas Kanaroglou, Pat DeLuca, Spatial analysis Unit, McMaster University
Source Tracking
1. Photos
2. SO2 Tracing3. Other Contaminants
4. SO2 Data Consolidation
5. Source Ranking/NPRI Comparison, SO2, NO, PM10
B
Sources B
Source AY
All Scans 21 March
-200
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1000
12009:
46
9:57
10:0
8
10:1
9
10:3
0
10:4
1
10:5
2
11:0
3
11:1
4
11:2
5
11:3
6
11:4
7
11:5
8
12:0
9
12:2
0
12:3
1
12:5
3
13:0
4
13:1
5
13:2
6
13:3
7
13:4
8
13:5
9
14:1
0
14:2
1
14:3
2
14:4
3
14:5
4
15:0
5
15:1
6
15:2
7
15:3
8
SO2 ppb
NO ppb
P10 ug/m3
SO2 Company A
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9:46
9:49
9:52
9:55
9:58
10:0
110
:04
10:0
710
:10
10:1
310
:16
10:1
910
:22
10:2
510
:28
10:3
110
:34
10:3
710
:40
10:4
310
:46
10:4
910
:52
10:5
510
:58
11:0
1
SO2 ppb
pp
b
Company A
Source
Plume
Back Tracking
Impact
Source
SO2 Company A
0
50
100
150
200
250
300
9:46
9:49
9:52
9:55
9:58
10:0
110
:04
10:0
710
:10
10:1
310
:16
10:1
910
:22
10:2
510
:28
10:3
110
:34
10:3
710
:40
10:4
310
:46
10:4
910
:52
10:5
510
:58
11:0
1
SO2 ppb
pp
b
Company A
NO Company A
0
50
100
150
200
250
300
Time
9:48
9:51
9:54
9:57
10:0
010
:03
10:0
610
:09
10:1
210
:15
10:1
810
:21
10:2
410
:27
10:3
010
:33
10:3
610
:39
10:4
210
:45
10:4
810
:51
10:5
410
:57
11:0
0
SO2
NO
Company A
SO2
NOpp
b
19 Jan SO2
0
10
20
30
40
50
60
70
80
90
10:0
210
:1410
:2610
:3810
:5011
:0211
:1411
:2611
:3811
:5012
:0212
:1412
:2612
:3812
:5013
:0213
:1413
:2613
:3813
:5014
:0214
:1414
:2614
:3814
:5015
:0215
:1415
:2615
:3815
:5016
:0216
:1416
:26
SO2
C
Eastport
B
Burning rubber
D
A
B
pp
b
Ambient SO2 vs NPRI
0
50
100
150
200
250
300
A B AN C G B A D CP Loco
Ambient SO2
NPRI SO2BAN
C
G
AB
D CP
1.1km
.09
1.1
.25
3.5
3.2
.2 .02
0.8km
A
SO2 Point Sources: A-Integrated Steel, B-Integrated Steel, AN- Steel Byproducts, C-Carbon Black, G-Steel, B-Integrated Steel, A-Integrated Steel, D-Lime, CP-Rail Yard.
Ambient NO vs NPRI
0
50
100
150
200
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350
B CP G A AN D C AM AT
Ambient NO
NPRI Emission NO
0.8
0.2
0.3
0.03
0.25
G
0.1
AN
0.32.3
CD
AM
AT
CP1.5km
B
A
NO Point Sources: B-Integrated Steel, CP-Rail Yard, G-Steel, A-Integrated Steel, AN- Steel Byproducts, D-Lime, C-Carbon Black, AM-Cogeneration, AT-Chemical.
Ambient PM10 vs NPRI
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1200
1400
1600
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2000
B ABP AY AG AU AT M G CP A AM C
Ambient P10
NPRI P10
1.5km
0.3
0.2
0.25CP
0.02 1
0.2
0.1 2.3
B
ABP
AT
G
A
M
AM
C
AY
0.1
AG
0.2 0.3
AU
PM10 Point Sources: B-Integrated Steel, ABP-Recycling, AY-Agricultural Product Handling, AG-Aggregate or AZ-Steel Handling, AU-Recycling, AT-Chemical, M-Foundry, G-Steel, CP-Rail Yard,
A-Integrated Steel, AM-Natural Gas Cogeneration Facility, C-Carbon Black.
Ambient CO vs NPRI
0
5
10
15
20
25
30
35
40
AM AT AN B A G C CP
Ambient CO
NPRI CO
AM
AT
AN B
A
GC
CP
0.2km
0.10.1
2.5
0.251.1
0.03
3.6
CO Point Sources: AM-Cogeneration, AT-Chemical; AN- Steel Byproducts; B-Integrated Steel; A-Integrated Steel; G-Steel; C-Carbon Black; CP-Rail Yard.
Lake Ontario
Hamilton Harbour
HAMN Air MonitoringNetwork
N
SO2TRS
TRSPM10
PM10 TRS
Parkdale
Ottaw a
Sherman
Burlington St.
QEW
SO2TRSNOX
PM10
Continuous Monitoring Locations
Centre Industrial
SO2
SO2
SO2
NE
Conclusions• These data are limited to Winter season and for
relatively short periods of time.• Point sources in the industrial area are sufficiently
close together that specific compounds needed to be used as tracers to separate impacts.
• Residential areas have relatively low levels of pollutants, however city impacts increase as distance downwind from the city edge increases.
• Concentrations increase sharply from residential areas to main roads, increasing again at intersections. Peak concentrations may increase by factors of 20-50.
• Time pattern of concentrations near intersections shows that idling vehicles at stop lights are a very significant source of pollutant exposure.
• Short survey near a school pickup and drop-off point showed that air pollution concentrations experienced by students can be significantly reduced by turning off engines in waiting cars.
Conclusions (contd)• Road dust includes elevated PM10, PM2.5 and PM1.• Trackout resuspension by large diesel trucks is a major problem. Some
levels doubled from same period in previous year.• 14 severe Trackout locations identified and monitored.• Peak ambient values of NO, SO2, PM10 and CO from 15 point sources were
quantified and ranked.• NPRI data rank industrial emissions in Hamilton in the order CO, SO2, NO
and PM10, and total emissions in the order CO, PM10 , NO, SO2. Mobile monitoring to date is showing an order of CO, PM10, NO, SO2, even in the industrial area.
• Large differences in distance from point source to fencelines heavily modify direct impacts compared to NPRI emissions data.
• Even allowing for distance variations there are significant differences between ambient and NPRI data for some sources. Other sources show good agreement.
• Mobile monitoring has different strengths than fixed network monitoring and both are necessary.
• Combination of simple GIS analysis and air pollutant monitoring proved very useful. A more sophisticated GIS analysis would be worthwhile.
• Data can be used to refine Regulation 419 models
Recommendations• Move cycle lanes off main roads, innovative signage.• Reduce idling emissions, including at school dropoff locations (enlist parent teacher
groups).• Monitor school bus idling.• Prioritize trackout reduction - paving, wheel washing, front gate dust monitoring.• Reinstate/enhance targeted road cleaning in industrial areas.• Reduce large diesel truck trips, it’s the combination of heavy trucks and dirty roads
that is a problem.• Gateway monitoring of diesel exhaust at city entry/exit points, industrial arterials.• Continue reducing point source remissions of SOx, NOx and PM10 (both ambient and
NPRI data) in order to improve/reduce health impacts.• Review existing fixed network stations and locations to refocus on adverse health
causing pollutants, e.g. NOx, monitoring gaps.• Compare mobile data to MOE STAC data, more detailed GIS analysis.• Review NPRI data variances with ambient.• Extend mobile monitoring to other seasons for more definitive source separation in
complex areas and documenting different met regime impacts, particularly inversions.• Extend mobile monitoring to other communities.• Use mobile data to refine local source inputs to Regulation 419 models.Disclaimer:- All recommendations and opinions are the sole responsibility of D. Corr and do not necessarily represent the policy or position of
funding agencies or others.
Phase 2 Proposal• Perform a more sophisticated and comprehensive GIS analysis
of existing data to develop traffic impact and source impact mapping visualization
• Re equip instrumentation and modify the data collection system in the Mobile Unit for consolidated air pollution/GPS data collection.
• Meet with stakeholders to finalize monitoring targets and locations.
• Support the MOE and City of Hamilton Fugitive Emission Control Initiative through monitoring of control activities for effectiveness.
• Test existing models of city wide distribution of air pollution and extend mobile monitoring to fill data gaps across the City, e.g. Dundas, Stoney Creek.
• Perform Smog day/Inversion day monitoring, upwind of City and across City to identify Regional and Transboundary impacts and compare to City impacts.
Phase 2 Proposal• Perform sampling on major arterial roads, at intersections
and drive thrus.• Monitor downwind impacts of roads and intersections on
residential areas.• Perform more intensive monitoring of NPRI and other point
sources identified in Phase 1 in consultation with MOE staff.• Utilize McMaster University advanced spatial analysis
capabilities for pollution source visualization and in depth data analyses.
• Provide monitoring data to modelling initiatives for ongoing model calibration, e.g., GTA/Hamilton modelling exercise (Phase 2.
• Generate recommendations for air quality improvements. • Develop and give presentations on findings and
recommendations.