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TRAKER: A Method for Fast Assembly and Update of Paved and Unpaved
Road Dust Emission InventoriesV. Etyemezian, H. Kuhns, G. Nikolich, A. Gertler
Desert Research Institute , Las Vegas, NV
D. Fitz, K. BumillerCE-CERT, Riverside, CA
R. Merle, and R. LangstonClark County DAQEM, Las Vegas, NV
Outline
• Road Dust Introduction• Mobile Platform for Road Dust Measurement
– The TRAKER Concept– TRAKER Characteristics and Calibration
• Examples of completed TRAKER Applications– Las Vegas, NV– Lake Tahoe, NV/CA– Treasure Valley (Near Boise), ID
• Conclusions and Plans for Future Work
Road Dust Emissions
• PM emissions of fugitive dust from paved and unpaved roads due to vehicle travel
• Road Dust Emission Measurement– Towers upwind and downwind of road
segment– Silt loading/content
• Calibrated against upwind/downwind measurements
– Vehicle-based technologies (DRI, CE-CERT)
Road Dust Measurement
• Planning agencies largely use silt loading (paved roads) and silt content (unpaved roads) to determine emission factors (AP-42 guidance document)
• Silt loading (paved roads)– Lane closure– Vacuum/sweep material– Use sieves to determine silt– Per Sample/Location ~ 10 labor hours + planning +
hazards
Testing Re-Entrained Aerosol Kinetic Emissions from Roads (TRAKER)
Fron
tTop ViewFr
ont Top View
Fron
t Side View
Fron
t Side View
Background Monitor
Background Monitor
Influence Monitor
Influence MonitorFron
tTop ViewFr
ont Top View
Fron
t Side View
Fron
t Side View
Background Monitor
Background Monitor
Influence Monitor
Influence Monitor
Background Monitor
Background Monitor
Influence Monitor
Influence Monitor
TRAKER
• Particle Sensors– TSI DustTrak
5820– Grimm Particle
Size Analyzer 1.108
• GPS
Data Acquisition and Processing• Lab View program
displays and logs data from – 6 DustTraks– 3 Grimms– 1 GPS
• Uniform time stamp applied to all data for synchronization
• Data tables are loaded into MS Access for processing and analysis
TRAKER Signal vs Vehicle Speed
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
0 5 10 15 20 25 30 35
Speed (m/s)
TRA
KER
Sig
nal (
mg/
m3 )
Treasure Valley RegressionT=0.00017*speed2.96
R2 = 0.972
0
0.5
1
1.5
2
2.5
0 5 10 15 20 25 30 35 40
Speed (m/s)
TRA
KER
Sig
nal (
mg/
m3 )
Ft. Bliss RegressionT=0.00012*speed2.75
R2 = 0.923
• T = Ctire – Cbkgrnd• T = a S3
• On the same paved road the TRAKER signal increases with the speed cubed
• Factoring out speed leaves a signal proportional to the emission potential of the road.
TRAKER Calibration with Upwind/Downwind Flux Towers
T=TT-TB
Unpaved Road EMF (g/veh-km) = 8.36 T1/3
Paved Road EMF (g/veh-km) = 0.33 T1/3
Example TRAKER Use: Las Vegas
• 150 km loop in Las Vegas Valley• Covering Road Types, Locations,
Construction Influence• TRAKER operated:
– 6/30/04, 7/1/04 (Loop 1)– 2/14/05 – 2/17/05 (Loop 2)
Emission Potentials
(g/veh-km) on 2/14/05
Average of PM10Emission Factor
(g/vkt) on a road link basis for all 4 days of sampling (2/14/05 –
2/17/05)
0
50
100
150
200
-100 -80
-60
-40
-20 0 20 40 60 80 100
% Difference from Average
Freq
uenc
y
0%
20%
40%
60%
80%
100%
120%02/14/05 2.0%
0
50
100
150
200
250
-100 -80
-60
-40
-20 0 20 40 60 80 100
% Difference from Average
Freq
uenc
y
0%
20%
40%
60%
80%
100%
120%02/15/05 4.3%
0
50
100
150
200
-100 -80
-60
-40
-20 0 20 40 60 80 100
% Difference from Average
Freq
uenc
y
0%
20%
40%
60%
80%
100%
120%02/16/05 0.1%
0
50
100
150
200
250
-100 -80
-60
-40
-20 0 20 40 60 80 100
% Difference from Average
Freq
uenc
y0%
20%
40%
60%
80%
100%
120%02/17/05 -6.9%
0
50
100
150
200
-100 -80
-60
-40
-20 0 20 40 60 80 100
% Difference from Average
Freq
uenc
y
0%
20%
40%
60%
80%
100%
120%02/14/05 2.0%
0
50
100
150
200
250
-100 -80
-60
-40
-20 0 20 40 60 80 100
% Difference from Average
Freq
uenc
y
0%
20%
40%
60%
80%
100%
120%02/15/05 4.3%
0
50
100
150
200
-100 -80
-60
-40
-20 0 20 40 60 80 100
% Difference from Average
Freq
uenc
y
0%
20%
40%
60%
80%
100%
120%02/16/05 0.1%
0
50
100
150
200
250
-100 -80
-60
-40
-20 0 20 40 60 80 100
% Difference from Average
Freq
uenc
y0%
20%
40%
60%
80%
100%
120%02/17/05 -6.9%
Comparison of Link-averaged emissions potentials from 4 consecutive days of TRAKER measurement in Las Vegas
0
2
4
6
8
10
12
2/14
/05
0:00
2/14
/05
6:00
2/14
/05
12:0
02/
14/0
5 18
:00
2/15
/05
0:00
2/15
/05
6:00
2/15
/05
12:0
02/
15/0
5 18
:00
2/16
/05
0:00
2/16
/05
6:00
2/16
/05
12:0
02/
16/0
5 18
:00
2/17
/05
0:00
2/17
/05
6:00
2/17
/05
12:0
02/
17/0
5 18
:00
2/18
/05
0:00
Time
Win
d Sp
eed
(mph
)
.
Day 1: +2.0%
Day 3: +0.1%
Day 2: +4.3%
Day 4: -6.9%
What about wind
effects?
Correction for Cross-winds
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
0 5 10 15 20 25 30 35
TRAKER Speed (m/s)C
oeffi
cien
t of V
aria
tion
Ft BlissTreasure Valley
Avoid cross-wind effects by considering data where TRAKER speed > 10 mph
Example TRAKER Use: Lake Tahoe
• 13 runs over a mountain pass
• 9 circuits around the lake
• Comparison with flux tower measurements
Emission Factors Using Stationary Flux Tower
Sampling Period
Condition PM2.5 EMF (mg/km)
PM10 EMF (mg/km)
1 Baseline 76 229
2 After salting 99 310
3 1st dry day after storm
112 612
4 2nd dry day 133 660
5 After sweeping
211 735
Emission Factor Using TRAKER
0
0.1
0.2
0.3
0.4
0.5
0.63/
31/2
003
4/7/
2003
4/14
/200
3
4/21
/200
3
4/28
/200
3
5/5/
2003
5/12
/200
3
5/19
/200
3
5/26
/200
3
6/2/
2003
6/9/
2003
6/16
/200
3
6/23
/200
3
6/30
/200
3
7/7/
2003
7/14
/200
3
Date of Measurement
Emis
sion
Fac
tor (
g/vk
t)
TotalBest Linear Fit to Data
Paved Road CalibrationUnpaved EF = 8.36 T1/3
0.1
1
10
100
1000
0.1 1 10 100 1000 10000
Traker Signal (mg/m3)
Em
issi
on F
acto
r (g/
vkt)
Lake Tahoe PavedEF = 0.33 T1/3
Example TRAKER Use: Treasure Valley, ID
• Winter/Summer TRAKER measurements over a closed loop
• Develop emission inventories based on road characteristics and traffic speeds/volumes
• Assess effect of road sanding, street sweeping, seasons
Time Series of Emissions from RoadsPrincipal Arterial Emissions Factors (g/VKT)
0123456789
102/
27/2
001
3/1/
2001
3/3/
2001
3/6/
2001
3/10
/200
1
3/15
/200
1
3/17
/200
1
7/12
/200
1
7/14
/200
1
7/19
/200
1
7/20
/200
1
7/22
/200
1
Date
EF (g
/VK
T)
Winter Summer
End of Road Sanding for Winter
Use Roadway Properties To Extend TRAKER Results to Entire Network
Winter - Ada - Rural
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 5 10 15 20 25 30 35Speed (m/s)
Emis
sion
s Po
tent
ial [
g/vk
t/(m
/s)]
TRAKER SpeedsPosted SpeedsExponential Fit
Summer - Canyon - Rural
0
0.2
0.4
0.6
0.8
1
1.2
1.4
0 5 10 15 20 25 30 35Speed (m/s)
Emis
sion
s Po
tent
ial [
g/vk
t/(m
/s)]
TRAKER SpeedsPosted SpeedsExponential Fit
Statistically significant differences found based on Season, County, Setting (urban/Rural), and Road Speed.
Use Traffic Demand Model to Obtain Link-level Emission Inventory
Another Interesting Finding About Street Sweepers
0
0.000005
0.00001
0.000015
0.00002
0.000025
0.00003
QUARTERBefore
QUARTER After STILLWELLBefore
STILLWELLAfter
Spe
ed C
orre
cted
TR
AK
ER
Sig
nal
Left PM10Right PM10
SWEPT NOT SWEPT
Conclusions• Vehicle-based methods for road dust emissions
measurement are efficient and comparatively fast– Cover 100’s of mile of road– No need to worry about “picking” representative sections of road
• For TRAKER– Las Vegas Study shows day to day differences (precision) is on
the order of 5% overall and generally better than 20% on a link by link basis
– Important to recognize the effect of cross-winds– Can use to
• Efficiently assemble emission inventories for road dust• Test effects of parameters : sweeping, sanding, season, location,
construction, traffic volume, etc• Technology has been around for 6 years and multiple
studies
Planned Future Work• Increase # calibration data points for paved roads using
upwind/downwind technique (Las Vegas, summer 2005)• Quantitatively compare with CE-CERT SCAMPER
(summer 2005)• Redesign towards achieving turnkey application (Winter,
2006). Features for TRAKER III will include:– New Platform: Dodge Sprinter– On-the-fly span and zero for DustTraks onboard– On-the-fly switching between paved and unpaved road sampling– Real-time mapping of dust emission potentials and factors
Acknowledgements
• Clark County Department of Air Quality and Environmental Management
• Idaho Department of Environmental Quality
• DoD – Strategic Environmental Research and Development Program
• California Air Resources Board