epa/federal highway administration (fhwa) near road … · 2012. 8. 15. · epa/federal highway...
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EPA/Federal Highway Administration (FHWA) Near Road CollaborationProject: National Near-Road MSAT StudyProject: National Near-Road MSAT Study
National Association of Clean Air AgenciesAmbient Monitoring Subcommittee Meetingg gJuly 19, 2012
Sue Kimbrough1, Gayle Hagler1, Richard Baldauf1, Nealson Watkins2, Tim Hanley2, Victoria Martinez3.1U.S. Environmental Protection Agency, Office of Research and Development2U S E i t l P t ti A Offi f Ai Q lit Pl i d St d d2U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards3Federal Highway Administration
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Office of Research and DevelopmentAugust 8, 2012
Some Initial Objectives/ Science QuestionsScience Questions
• What is the spatial and temporal variability of traffic related pollutants near roadways?traffic-related pollutants near roadways?
• How do traffic (volumes, speeds, fleet mix, etc.) d i t l ( t l t h t )and environmental (meteorology, topography, etc.)
conditions affect vehicle emissions and near road air quality?y
• What tools are available, or can be produced, to identify the relationships of traffic emissions toidentify the relationships of traffic emissions to population exposures to adverse health effects for use in regulatory decision making and transportation planning?Office of Research and Development
transportation planning?1
Las Vegas study: I-15 monitoring site
Approximate Location of Site
I-15 Site
Kimbrough, S., Baldauf, R., Hagler, G., Shores, R.C., Mitchell, W., Whitaker, D.A., Croghan, C.W., Vallero, D.A., 2012. Long-term continuous
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measurement of near-road air pollution in Las Vegas: Seasonal variability in traffic emissions impact on local air quality. Air Quality, Atmosphere & Health.
I-15 site
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Summary of continuous
Measurement ParameterSampling Approach,
Instrument Make/ModelSample
Type and Frequency
20 Meter Roadside
100 Meter Downwind
300 Meter Downwind
100 Meter
Upwind
COinfrared analyzer, Drager
X X X X continuousmeasurements conducted at each
it i it
CO2 Polytron IRX X X X
CO
nondispersive infrared, EC 9830T
X X X X
nondispersive infrared, Serinus 30
X --- --- ---
monitoring siteNOxchemiluminescence, EC
9841TX X X X
SO2pulsed fluorescence, EC
9850T--- X --- X
BCMagee Scientific –
X X X X
(5 minute)
BCAethalometer (AE 21)
X X X X
PM2.5, PM10, PM Coarsetapered element oscillating
microbalance (TEOM), Thermo--1405DF FDMS
X X X X
i RMWind Speed, Wind Direction
sonic anemometer, RM Young Model 81000
X X X X
Air Temperaturetemperature probe, Vaisala
HMP45D--- X --- ---
% Relative Humidityrelative humidity sensor,
V i l HMP45A--- X --- ---y
Vaisala HMP45A
Rain Gaugerain bucket, Ecotech Rain
Gauge--- X --- ---
Solar Radiationsolar radiation, MetOne 394
Pyranometer--- X --- ---
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Sound microphone, Extech 407764 X X --- ---
Particle scattering coefficient.light scattering, Aurora 3000
(nephelometer)--- --- --- X
Summary of integratedmeasurements
Measurement Parameter
Sampling Approach, Instrument
Sample Type and Frequency
20 Meter Roadside
100 Meter Downwind
300 Meter Downwind
100 Meter
Upwind measurements conducted at each monitoring site
Make/ModelUpwind
PM2.5PM2.5 FRM method,
FRM BGI PQ20024-hour
integratedX X X X
Acetaldehyde, F ld h d
U.S.EPA Method TO-11A, Atec 2200 X X X X g
FormaldehydeCartridge Sampler
1-hour integratedAcrolein, Benzene,
1,3-Butadiene
U.S.EPA Method TO-15, Entech 1800 Canister Sampler
X X X X
1 3 B diSemi-continuous GC,
S i i1,3-Butadiene, Benzene
,Chromatotec airtoxic
866 GC
Semi-continuous (30 min.)
X X X X
Ultrafine particle
Size classification by Differential Mobility Analyzer (DMA) and Continuous p
county ( )detection by electrometer,
(15 min.)X --- X ---
TSI Model 3031200
VideoVideo, Axix 223M
and Vivotek SD7151Continuous X X --- X
and Vivotek SD7151
Particle count TSI CPC 3781 Continuous X X X X
Vehicle Count, Wavetronix radar unit
(10.525 GHz
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Vehicle Speed, Vehicle Type
(frequency modulated
continuous wave (FMCW)
(15 min.) Data supplied by NDOT
Instrument performance andmethods issues
• Most instruments performed well…..exceptions…. Thermo 1405DF FDMS TEOMs (Las Vegas, lesser extent Detroit)
Design problems Manufacturing issues
TSI CPCs – Model 3781 (Las Vegas) Maintenance issues Design issues w/ orifice
Canister Samplers (Las Vegas) Tablet computers Replaced with netbooks
• Most methods worked well…..exception…. Acrolein measurements (TO-15)
Data unreliable Research task is in ORD’s Air, Climate & Energy Research Action Plan
t fi / l i
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to refine/resolve issues
Las Vegas Traffic data
• I-15 supports >200,000 Average A l D il T ffi (AADT)
Average Hourly Traffic Volume Northbound/Southbound -- I-15
10,000
12,000
Annual Daily Traffic (AADT)• Truck traffic constitutes ~10%
of total volume6,000
8,000
affic
Vol
ume
2,000
4,000
Tra
Traffic Volume
Average Hourly Traffic Volume by Month Northbound/Southbound -- I-15
12,000
00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour
6,000
8,000
10,000
c Vo
lum
e
Jan-09Feb-09Mar-09Apr-09May-09Jun-09J l 09
• No clear morning/ afternoon rush
2,000
4,000
Traf
fic Jul-09Aug-09Sep-09Oct-09Nov-09Dec-09
afternoon rush
• Monthly differences correspond to tourist seasons
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00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Hour
seasons
Traffic Volume = Number of Vehicles
Average hourly traffic volume and speed I-15 site from December, 2008 through December, 2009
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Kimbrough, S., Baldauf, R., Hagler, G., Shores, R.C., Mitchell, W., Whitaker, D.A., Croghan, C.W., Vallero, D.A., 2012. Long-term continuous measurement of near-road air pollution in Las Vegas: Seasonal variability in traffic emissions impact on local air quality. Air Quality, Atmosphere & Health.
Observed wind variability
Downwind
Office of Research and Development 9Kimbrough, S., Baldauf, R., Hagler, G., Shores, R.C., Mitchell, W., Whitaker, D.A., Croghan, C.W., Vallero, D.A., 2012. Long-term continuous measurement of near-road air pollution in Las Vegas: Seasonal variability in traffic emissions impact on local air quality. Air Quality, Atmosphere & Health.
Las Vegas: concentration gradients as a function of distance from roadwayNO2
60 60
NOX
35
40
45
50
55
60
n (ppb
)
All wind directions
Winds from west
35
40
45
50
55
on (p
pb)
All wind directions
Winds from west
10
15
20
25
30
Concen
tration
10
15
20
25
30
Concen
tratio
0
5
‐100 0 100 200 300 400Distance (m)
0
5
‐100 0 100 200 300 400Distance (m)
CO BC
0.4
0.5
0.6
ppb)
All wind directions
Winds from west1.5
2.0
/m3 )
All wind directions
Winds from west
0.2
0.3
Concen
tration (p
0.5
1.0
Concen
tration (µg/
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0.1
‐100 0 100 200 300 400Distance (m)
0.0‐100 0 100 200 300 400
Distance (m)
0 8
1.0
nsAll wind directions
Concentration
0.6
0.8
ed c
once
ntra
tion
normalized to 20 meter roadside site
0.2
0.4
Nor
mal
ize
NO2NOX COBC
for each pollutant
1.0Wind from west
0.0-100 0 100 200 300 400
Distance (m)
0.6
0.8
conc
entr
atio
ns
Pollutants exhibit
0.2
0.4
Nor
mal
ized
c
NO2NOX CO
similar spatial gradient patterns
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-100 0 100 200 300 400Distance (m)
BC
11
Air pollutant concentration trends and influence of meteorological conditionsinfluence of meteorological conditions
10,0001.0
CO Concentration and Traffic Volume by Hour CO concentration trends
with increase in traffic volume (5-7 AM)
7,000
8,000
9,000
0.7
0.8
0.9volume (5-7 AM)
CO concentration appear to decrease through morning and early afternoon hours
4,000
5,000
6,000
0.4
0.5
0.6
Traf
fic V
olum
e
cent
rato
iion
(ppm
) 100 Meter Upwind20 Meter Roadside100 Meter Downwind300 Meter Downwind
CO concentrations begin to increase again beginning around 3 PM
1,000
2,000
3,000
0.1
0.2
0.3Con
c
Traffic Volume Influence of meteorological
Conditions
• Solar heating and
00.00 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
atmospheric Mixing
• Increased wind speedsHour of Day
Office of Research and Development 12Kimbrough, S., Baldauf, R., Hagler, G., Shores, R.C., Mitchell, W., Whitaker, D.A., Croghan, C.W., Vallero, D.A., 2012. Long-term continuous measurement of near-road air pollution in Las Vegas: Seasonal variability in traffic emissions impact on local air quality. Air Quality, Atmosphere & Health.
(a) (b) (c)
250
300
250
300NO2 concentration box plots highest
wind speed wind direction
0
50
100
150
200
N
0
50
100
150
200
N
box plots highest 10% of Site 1 for all wind conditions
(d) (e)
b)
80
100
00 1 2 3 4 5 6 7 8
wind speed (m/s)
0 60 120 180 240 300 360
wind direction (deg)
300 150
conditions
hr. traffic volume hour of day
Con
cent
ratio
n (p
pb
20
40
60
50
100
150
200
250
N
50
100
N
(f) (g) Distance
-100 20 100 300
C
0
200
0 3000 6000 9000 12000
hourly traffic volume
00 2 4 6 8 10 12 14 16 18 20 22
hour of day
200 200day of week month of year
100
150
200
N 100
150
200
N
y y
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50
1 2 3 4 5 6 7
day of week
0
50
1 2 3 4 5 6 7 8 9 10 11 12
month of year
Polar Plot: mean concentration of NO2 by wind speed and direction.NO2 by wind speed and direction.
Highway
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Integrated PM2.5 filter samples (all wind conditions)Data from mid-December 2008 to mid-December 2009
24-Hr AverageIntegrated PM 2.5 Filter Samples
25 Legend
station1
station2
t ti 3
20 Meter Roadside
100 Meter Downwind
300 Meter Downwind
15
20 station3
station4
300 Meter Downwind
100 Meter Upwind
3 )µg
/m3
10
15
PM2.
5(µ
g/m
3
5
0
c200
8n2
009
n200
9n2
009
b200
9b2
009
r200
9r2
009
r200
9r2
009
y200
9y2
009
n200
9n2
009
l200
9l2
009
l200
9g2
009
g200
9p2
009
p200
9t2
009
t200
9v2
009
v200
9c2
009
c200
9c2
009
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18D
ec01
Jan
15Ja
n29
Jan
12Fe
b26
Feb
12M
ar26
Mar
09A
pr23
Apr
07M
ay21
May
04Ju
n18
Jun
02Ju
16Ju
30Ju
13A
ug27
Aug
10S
ep24
Sep
08O
ct22
Oct
05N
ov19
Nov
03D
ec17
Dec
31D
ec
Summary – Las Vegas
• Initial trends analysis suggest concentration gradients existed for gaseous pollutants and black carbon associated with traffic volume and wind speed strongly influencing results
For example, the mean CO concentration for the 20 meter road is approximately 22 % higher than the 100 meter upwind site for all wind directions. The mean CO concentration for the 20 meter road is approximately 55 % higher than the 100 meter upwind site for downwind conditions (winds from road).)
• Additional ongoing analyses investigate specific research questions, such as:
Evaluating the degree of other urban sources contributing to measurements under specific wind conditions [e g Henry et al (2011)]under specific wind conditions [e.g., Henry et al., (2011)]
Assessing how the highway and surrounding topography affect dispersion of near-road air pollutants (e.g., Baldauf et al., in preparation)
Understanding relationships between measured pollutants and influential factors (meteorology, traffic trends, etc.)
Evaluating data utilizing new real-time measurement approaches
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g g pp
Overview map of Detroit
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Detroit site: Eliza Howell Park
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North View
Ground level views
East View West ViewEast View West View
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Additional Analyses:Mobile monitoringg
• Real-time air pollution measurements on-board a mobile platform – allow greater spatial coverage of data representing 2-3 hour sampling periods.Vehicle as operated in Las Vegas and Detroit for 1 month mapping air• Vehicle was operated in Las Vegas and Detroit for ~1 month, mapping air pollution concentrations on-road and along side roads.
Real-time data:L ti (GPS)Location (GPS)Carbon monoxideBlack carbonParticle count in about 80 size binsParticle count in about 80 size bins (spans ~6 nanometers – 20 µm)Forward-facing video
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Mobile monitoring• Example black carbon map for Las Vegas (multiple laps over 3 hour sampling
periods averaged into 20 m spatial increments)Weekday, 8 11 AMb 8-11 AMbusy
arterials
highwayhighway
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Ultrafine particles: measurementTwo UFP 3031s (TSI) and two EPC 3783s (TSI) tested in Las Vegas, Detroit, and at an ambient site in RTP.
3031 operation: particles charged, sized by electrical mobility, then counted via electrometer. -15 min data, six size bins (range 20 to >200 nm)
P f t bl t ti f- Performance: very stable autonomous operation for long periods of time. We had some data logging issues after a firmware upgrade that have been resolved.
3783 operation: particles grown through condensing water to their surface, counted by light scattering. -1 s (max rate) data, one size range (~ 7 nm – 1 µm).- Performance: initially problematic at near-road site and minimal data collection achieved. After system impro ements no ha e stable sampling at o r
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improvements now have stable sampling at our ambient site. Requires monthly maintenance (wick change, water source).
Ultrafine particles: measurementBoth technologies demonstrated good precision at our ambient monitoring site in RTP
UFP3031#1 vs.
UFP3031#2
R = 0.994Mean(Y./X) = 1.06
R = 0.994Mean(Y./X) = 0.984
C3 83 #1EPC3783 #1 vs.
EPC3783 #2
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Ultrafine particles: observations
Example comparison - March-April, LV (2010), Detroit (2011), RTP (2012)
600060006000
Las Vegas (20 m from road) RTP (ambient)Detroit (<10 m from road)
4000
5000
(cm
-3)
4000
5000
()
4000
5000
(cm
-3)
# cm
-3)
1000
2000
3000
PN
(
1000
2000
3000
1000
2000
3000
PN
(PN
(#
020-30 nm 30-50 nm 50-70 nm 70-100 nm 100-200 nm
020-30 nm 30-50 nm 50-70 nm 70-100 nm 100-200 nm
020-30 nm 30-50 nm 50-70 nm 70-100 nm 100-200 nm
Particle size (nm)20-30 30-50 50-70 70-100 100-200
Particle size (nm)20-30 30-50 50-70 70-100 100-200
Particle size (nm)20-30 30-50 50-70 70-100 100-200
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~205,000 AADT ~180,000 AADTPN = particle number
Future plans…
• Raleigh NO2 Near Road Site In Collaboration with NCDENR
• Health Studies………..
Cardiovascular Study: Research Triangle Area Mobile Source E i i St d (RAMSES)Emissions Study (RAMSES)
Asthma Study: Near Roadways Exposure to Urban Air Pollutants Study (NEXUS)Pollutants Study (NEXUS)
• Roadway Design Studies………..
Sound walls
Vegetation
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g
Who are the members of the EPA/FHWA Near Road team?Near Road team?
Project Team:• Strategic Project/Science Management
– Dan CostaCarlos Nunez– Carlos Nunez
– Doug Mckinney– Richard Baldauf– David Kryak– Prakash Bhave
• NRMRL – Project Management– Sue Kimbrough– Richard Shores
• EPA/FHWA Technical Working Group (including above)Vi t i M ti (FHWA) IAG P j t Offi– Victoria Martinez (FHWA) -- IAG Project Officer
– Dan Vallero (EPA IAG Project Officer)– Bill Mitchell– Donald Whitaker– Richard Baldauf– Gayle Hagler– James Hirtz– Jason Herrington– Carry Croghan
Paul Solomon
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– Paul Solomon– Other EPA technical staff ……..
26
Appendixpp
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Site selection criteria(many from Sierra Club/FHWA Settlement Agreement)
Selection Considerations Monitoring Protocol Criteria
Annual Average Daily Traffic (AADT) (> 150,000)
Only sites with more than 150,000 annual average daily traffic (AADT) are considered as candidates.
The geometric design of the facility, including the layout of ramps, interchanges and similar Geometric Design facilities, will be taken into account. Where geometric design impeded effective data
collection on MSATs and PM2.5, those sites were excluded from further consideration.
Topology (i.e., Sound Barriers, Road Elevation)
Sites located in terrain making measurement of Mobile Source Air Toxic (MSAT) concentrations difficult or that raise questions of interpretation of any results were not considered For example sharply sloping terrain away from a roadway could result in underElevation) considered. For example, sharply sloping terrain away from a roadway could result in under representation of pollutants.
Geographic Location Criteria applicable to representing geographic diversity within the U.S. as opposed to within any given city.
Availability of Data (Traffic Volume Data)Any location where data, including automated traffic monitoring data, meteorological or MSAT concentration data, was not readily available or instrumentation cannot be brought in y ( ) , y gto collect such data were not considered for inclusion in the study.
MeteorologySites will be selected based on their local meteorological conditions to assess the impact of climate on dispersion of emissions and atmospheric processes that affect chemical reactions and phase changes in the ambient air.
While not explicitly included in the Monitoring Protocol, the following selection criteria were deemed important to the selection process and were included
Downwind Sampling Any location where proper siting of downwind sampling sites was restricted due to topology, existing structures, meteorology, etc., excluded otherwise suitable sites for consideration.
Potentially confounding air pollutant sources The presence of confounding emission sources sometimes excluded otherwise suitable sites from consideration.
were included.
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Site Access (Admin/Physical) Any location where site access, was restricted or prohibited either due to administrative or physical issues, was not considered for inclusion in the study.
Conceptual site design
Upwind Site (100 Meters)
Roadside Site (10 Meters)
100 Meter Downwind Site
300 Meter Downwind Site
(100 Meters)
Concentration Gradientce
ntra
tion
Concentration Gradientce
ntra
tion Hypothetical
Wind Flow
Distance
Con
c
Distance
Con
c
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DistanceDistance
Overview map of Las Vegas
I-15 Site
S G
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Source: Google Maps
Meteorology: McCarran Airport
Winds generally from the SSW, although diurnal variations exist
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CO concentration box plots for full data set from December, 2008 through December, 2009: all sites, all wind directions (mean is the dotted line in each (box) (a) and histograms of the wind speed (b), wind direction (c), traffic volume (d)
Kimbrough, S., Baldauf, R., Hagler, G., Shores, R.C., Mitchell, W., Whitaker, D.A., Croghan, C.W., Vallero, D.A., 2012 Long-term continuous2012. Long-term continuous measurement of near-road air pollution in Las Vegas: Seasonal variability in traffic emissions impact on local air quality. Air Quality, Atmosphere & Health
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Atmosphere & Health.
NO2 concentration box plots for full data set from December, 2008 through December, 2009: all sites, all wind directions (mean is the dotted line in each box) (a) and histograms of the wind speed (b), wind direction (c), traffic volume (d)
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Seasonal NO2 trends (all wind directions)80
n (p
pb) 60
cent
ratio
n
40
Con
c
20
R d Li I id
nter
ring
mer Fall nter
ring
mer Fall nter
ring
mer Fall nter
ring
mer Fall
0-100 Meters 20 Meters 100 Meters 300 Meters
Red Line Inside Box = Mean
Black Line Inside Box = Median
Individual Points
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Wint
Sprin
Summ Fa
Wint
Sprin
Summ Fa
Wint
Sprin
Summ Fa
Wint
Sprin
Summ FaIndividual Points
= Outliers
Hourly average NO2/NOX ratio box plots ( ) ll it ll i d diti (b) ll(a) all sites, all wind conditions; (b) all sites, downwind conditions (mean is the dotted line in each box))
1.2 1.2All wind conditions Winds from west
X R
atio
0.8
1.0
X R
atio
0.8
1.0
NO
2/N
OX
0.2
0.4
0.6
NO
2/N
OX
0.2
0.4
0.6
Distance (m)-100 20 100 300
0.0
Distance (m)-100 20 100 300
0.0
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Black carbon (BC)
Black Carbon(all wind directions)
Black Carbon(winds from road)
m3 )
4000
5000
m3 )
4000
5000
ncen
tratio
n (n
g m
1000
2000
3000
ncen
tratio
n (n
g m
2000
3000
- 100 Meters 20 Meters 100 Meters 300 Meters
Con
0
1000
- 100 Meters 20 Meters 100 Meters 300 MetersC
on
0
1000
Red Line Inside Box = MeanBlack Line Inside Box = Median
All outliers not shown
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Black Line Inside Box = MedianIndividual Points = Outliers
Hourly average PM2.5 box plots (a) all sites, all wind conditions; (b) all sites, downwind ; ( ) ,conditions (mean is the dotted line in each box)
50 50
All wind conditions Winds from west
Not all Not all
atio
n (µ
g/m
3 )
30
40
µg/m
3 30
40outliers shown
outliers shown
Con
cent
ra
0
10
20
0
10
20
Distance
-100 20 100 300
0
Distance
-100 20 100 300
0
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Summary of continuous particulate (PM10, PM2 5 and PMC ) observations(PM10, PM2.5 and PMCoarse) observations with acceptable system status and volumetric flows
Location
Observations (Obs.) a System Status Volumetric Flows +/- 2 %Location y
Normal and Operating Mode Fully Functional
A (3 lpm)
B (1.67 lpm)
By Pass (12 lpm)
Station 1 108,714 95,601S i 2 112 464 8 40Station 2 112,464 85,405Station 3 106,245 48,769Station 4 103,868 14,088a TEOM data from Station 4 is from 12/11/2008 02/15/2010a TEOM data from Station 4 is from 12/11/2008-02/15/2010.
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Detroit: Instrument Deployment - Overview
Core Instruments 10 Meters @ I-96 Roadside
100 Meter Downwind
300 Meter Downwind
100 Meter Upwind
EPA Method TO-11A Cartridge sampling X X X X
EPA Method TO-15 Canister sampling X X X Xp g
Continuous gas chromatograph X X X X
Continuous gas monitoring (CO, NOx ) X X X X
Continuous black carbon monitoring (Aethalometer) X X X X
Continuous fine particle (TEOM) X X X X
Integrated PM2.5 (FRM) X X X X
Wind speed/wind direction (sonic anemometer) X X X X
Meteorological monitoring (temp, RH, solar, etc.) X
Study Enhancements
Continuous Ultrafines (20 nm – 200+ nm) X X
Water-based CPC X X
Continuous CO2 monitoring X X X X
Michigan DOT -- Traffic data
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Vehicle count, Vehicle speed, Vehicle class
Las Vegas Cut Section MeasurementsLong-Term MeasurementsFHWA/EPA Sites:Continuous and integrated samplingsampling4 sites (100 m upwind; 20, 100, 300 m downwind)Over one year of sampling ( )(Dec, 2008 – March, 2010)
Intensive MeasurementsSt ti hi l liStationary vehicle sampling:Continuous air quality measures~3 hrs per day (Oct-Nov, 2009)
Mobile Sampling:Electric car equipped with air quality analyzersDriving route 4-5x per day
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Driving route 4 5x per day (~3 hrs, Oct-Nov, 2009)
Monitoring details
Mobile Electric Vehicle ~3 hrs per day (3-4 driving routes)Particulate MatterParticulate MatterUFP size distributions (EEPS)Coarse and fine size distributions (APS)Black carbon (Micro-aethalometer)
C t S ti M t
( )Gases
CO (Single Quantum Cascade Laser)
Cut Section MeasurementsCO and BC at bottom, middle and top
of cut section (Dec 2008-2009)Sonic anemometers at bottom and topSonic anemometers at bottom and top
of cut section (Nov 2009-March 2010)Bottom: 3m and 6m heightsTop: 6m and 10m heights
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Top: 6m and 10m heights
Cut section effects
R lt i di t dResults indicated highest levels
occurred at-grade, during calm winds,during calm winds,
with this site impacted more by “fresh”
emissions
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Wind Tunnel Simulation of Las Vegas Studyy
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Wind Tunnel Simulation
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