I
Project Team and Contact Information
I.a
Principal Investigators: Dr. Hampden Kuhns (PI), Dr. John Gillies (Co-I), Dr.
Vicken Etyemezian (Co-I), and Dr. Alan Gertler (Co-I), Dr. Steven Cliff (Co-I)
I.b
Institution: Desert Research Institute with subcontract to University of California
Davis
I.c
Address: 2215 Raggio Parkway, Reno, NV 89512
I.d
Phone: (775) 674 7111 Fax: (775) 674 7060 Email: hkuhns@dri.edu
I.e
Business Manager: Lycia Ronchetti; Phone: (775) 673 7411, Fax: (775) 674 7016,
Email: lycia@dri.edu
I.f
Project Theme: Theme 1. Role of Air Quality Management to Control Lake Clarity
Conditions. Sub-Theme A. Dust and air-borne sediment control demonstration
projects.
II Justification Statement
Lake Tahoe is a unique environmental asset that has been designated an “Outstanding National
Water Resource” by the US Environmental Protection Agency (EPA) to protect its water quality
and its scenic characteristics. Of particular concern to resource management agencies in the
basin is that optical clarity in Lake Tahoe has been steadily decreasing during the last four
decades. This is the result of increased algal growth from excess nutrient inputs and from the
accumulation of fine sediment particles in the lake due to watershed runoff and atmospheric
deposition (Byron and Goldman, 1986; Goldman et al., 1993; Jassby et al., 1999).
Recent work by Swift et al. (2006) has shown that fine inorganic particles are causing about 58%
of light attenuation in Secchi disk measurements of water clarity. That study noted that particle
sizes from 0.5–10 microns are of particular concern due to their light scattering characteristics
and relative abundance. Studies conducted for development of the Tahoe total maximum daily
load (TMDL) estimate (Roberts, 2006) have determined that atmospheric deposition is a major
source of these pollutants, and that the control of local atmospheric sources could provide
significant load reductions.
Emissions studies conducted by Kuhns et al. (2004) indicate that nearly 300 metric tons of fine
particulates (less than 10 microns) are contributed annually to the atmosphere by vehicles
traveling on paved roads in the Tahoe Basin. Other sources of particulate emissions in the basin
include wind blown dust, unpaved road dust, and fires. An improved emission inventory will
help to bound the contribution of the various local sources. However the mechanism for delivery
of these materials into the lake is extremely complicated and highly uncertain, making it difficult
to develop and implement strategies to reduce the flux of atmospheric pollutants to the lake. In
order to address this deficiency, the proposed study seeks to directly assess the impact of a series
of best management practices (BMPs) designed to reduce the contribution from resuspended
road dust, one of the major sources of atmospheric particulates in the basin.
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III Background/Problem Statement
A number of current and previous studies have demonstrated that BMPs can directly impact
emissions of resuspended road dust. Gertler et al. (2006) measured the effects of precipitation
events, brine application, sanding and street sweeping on paved road dust emissions on Nevada
Highway 28, 200 m south of the entrance to Sand Harbor state park. The results indicated the
use of liquid deicers contributed less to road dust emissions than abrasives. Street sweeping was
found to increase the PM10 re-entrainment rate of the remaining road dust during the short term;
however, emission factors for roads in the study area tended to decrease significantly from late
Spring to early Summer by as much as a factor of 4, suggesting that street sweeping may provide
longer term reductions in PM10 emissions.
These results prompted the current year (2006-2007) SNPLMA-supported study with the
TRAKER vehicle to monitor the annual variations in road dust emissions. In addition, that
project is conducting a survey within many of the General Improvement Districts (GID) to
determine what types of management practices are in place to reduce road dust emissions.
Most recently, Etyemezian et al. (2007) conducted an extensive TRAKER calibration procedure
using upwind and downwind towers on a paved road in Boulder City, Nevada. Analysis of these
data found that the relationship between road dust emissions and TRAKER signal does show a
continuum from paved roads to unpaved roads although the relationship does not appear to be
linear as total emissions increase (see Figure A in attachments). The Etyemezian et al. (2007)
study provides further confidence that TRAKER provides an effective and efficient means to
measure road dust emissions and identify areas where these emissions are high.
Moreover, a street sweeper was also operated on the course in Boulder City to analyze the
effectiveness of street sweeping. Consistent with previous measurements (Kuhns et al., 2003;
Gertler et al., 2006), emission were observed to increase immediately after the passage of the
sweeper. Unlike the previous studies, the Boulder City study tracked these emission factors over
multiple vehicle passes after the sweeping. The time series indicated a rapid decrease in
emission factors to a value less than those measured prior to sweeping after ~10 vehicle passes.
It is hypothesized that the sweeper lifts particles from pocks and divots in the paved road surface
and avails them to entrainment by vehicle tires. After a short period, these particles are depleted
from the road surface and the total emission factor is reduced following sweeping.
Based on these studies, we observe that a limited set of BMPs (street sweeping and the use of deicers/abrasives) can affect road dust resuspension, and therefore particle deposition to the lake.
In order to implement cost effective strategies to reduce this major source of atmospheric
particulate matter input, additional BMPs such as road shoulder treatments, curbs, alternative deicers/abrasives, and street sweeping practices need to be assessed. The proposed study seeks to
accomplish this assessment through the direct measurement of particle emissions and
chemical/physical properties under a range of BMPs.
IV Goals, Objectives, and Statement of Hypotheses to be
Tested
The goal of this program is to quantify the cost effectiveness of different road dust control
strategies applied in the Lake Tahoe Basin. This goal will be achieved via the following
objectives:
2
•
Measure particle emission factors and chemical/physical properties from roads
employing a variety of emission control strategies.
•
Measure the deposition velocity and flux of PM at several points downwind of a road in
areas representing a variety of fetches common to the Tahoe basin.
•
Calculate the emission control effectiveness and the fraction of emissions deposited to the
ground in the first 100 m of fetch near the road.
•
Use calculated values along with emission control costs to determine cost effectiveness of
various emission control strategies.
•
Prioritize emission control strategies based on cost effectiveness to prevent PM from dry
depositing to the lake surface.
Specific hypotheses that will be tested and ultimately quantified by this project include:
•
Street sweepers are effective means of controlling dust emissions from roads.
•
Anti-icing reduces road dust emissions when compared to the application of abrasives for
traction control.
•
Paving shoulders and installing curbing prevents material from washing onto the roadway
and being emitted into the air.
•
Vegetation by the side of the road reduces the fraction of emissions that can be
transported over the lake surface.
•
Phosphorous concentrations in resuspended road dust are greatest in the largest sizefractions, which are the most likely to deposit.
•
The majority of the particles that can potentially deposit fall out prior to reaching the
lake.
V Approach, Methodology, and Geographic Location of
Research
The approach for this project is to directly measure particulate matter emission factors and the
associated deposition velocities from roads maintained over a range of best management
practices (e.g., shoulder paving, street sweeping, curbs, abrasives/de-icers). All measurements
will take place on roads within the Tahoe basin.
Task 1. Study design and site selection.
A critical component of this study will be to identify representative sites for testing. GID Survey
data from the SNPLMA Round 6 TRAKER study will be used to select sites representing a range
of management practice variables including: street sweeper type, sweeping frequency, use of
curbing, paved shoulder, unpaved shoulder, and traction control measures. The GID survey data
will also, upon completion, clearly indicate locations of consistently high road dust emissions,
which can also serve to guide site selection (see Figure B in Attachments). In addition, site visits
will be conducted to evaluate the fetch downwind of the road. A clear fetch is likely to have
significantly lower deposition velocities than a densely vegetated fetch. With the proposed
funding, we will conduct measurements at five sites during both the summer and winter seasons.
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In addition, monitoring will be conducted at the ingress and egress points of at least one
construction site to evaluate the strength of this source. The study plan will be prepared once the
GID survey has been completed and notification of award for the proposed project has been
received. The study plan will be submitted as a workplan prior to the receipt of funding.
Task 2.
Measure emission factors, chemical composition, and deposition velocities at
selected sites.
Emission factors will be measured using DRI’s proven flux tower system (Abu-Allaban et al.,
2003; Etymezian et al., 2004; Gillies et al., 2005; Gillies et al., submitted). The tower consists of
a series of TSI DustTrak instruments that measure the light scattering of particles at various
heights. To infer true PM mass measurements, a Tapered Element Oscillating Microbalance or
TEOM (Thermo Electron Corporation) is collocated with one of the DustTraks. A correction
factor is calculated from these measurements to convert DustTrak data into PM mass based on
the TEOM Federal Equivalent Method. Road tube counters will be installed on the roadway in
front of the tower to measure vehicle class, speed, and direction. Chemical speciation and size
distributions will be determined using the UCD Drum sampler that will allow for comparison
with similar data collected from the on lake deposition study funded in SNPLMA round 6.
In addition to the emission factor measurements, a unique particle deposition monitoring system
will be constructed and deployed. DRI’s Electronic Low Pressure Impactor or ELPI (Dekati,
Inc. Finland) will be upgraded to measure particle size distribution at a frequency of 10 Hz. This
instrument will be collocated with a sonic anemometer on a cart that can be easily moved
downwind of the road. The combination of measurements will be used to calculate particle
deposition velocities using the eddy correlation method (Vong et al., 2004; Buzorius et al.,
2002), which requires collocated, high-time resolution measurement of wind conditions and
particle size distributions. These measurements will be conducted over a variety of fetches
around the lake to improve estimates of particle deposition velocities near their sources. In turn,
this information can be used to prioritize areas for road dust mitigation. For example, if PM
deposition fluxes are determined to decrease by 95% after 100 m of densely vegetated forest,
then resources used to clean these roads may be better applied to roads in open areas where a
much higher fraction of the particles can be transported over the lake surface.
The DRI flux tower system will be deployed within 2 meters of the roadway edge to provide the
greatest sensitivity to measure road dust emission factors. The deposition monitoring system
will be deployed at a range of intervals downwind of the road (i.e., 10 m, 25 m, 50 m and 100 m)
for 1 hour sampling. The results of the deposition monitoring system will indicate how much of
the plume is deposited very close to the source and how much can travel longer distances and
potentially reach the lake surface.
Task 3. Compare emission factors based on different best management practices and
calculate efficiencies associated with each control.
The emission factors measured with the flux towers will be assembled into a database for
analysis. Each road is likely to have different emission factors based on material loading, traffic
volume, and average vehicle speed. Empirical relationships of emission factors and these
variables, such as those reported by Etyemezian et al. (2003), will be used to normalize
emissions from different roads so that an accurate comparison of the BMP effectiveness can be
determined. The relative differences can then be attributed to the application of the control
measure (e.g., roads that are swept weekly versus roads that are swept once in spring time).
4
Task 4. Integrate results of year round TRAKER study with proposed measurements to
prioritize best management practices for application throughout basin.
The cost effectiveness of the BMP will be determined by considering the magnitude and location
of the source (i.e., does it have the potential to deposit PM to the lake?), the relative effectives of
the control strategy, and the cost of the control. An equation to calculate cost effectiveness is
shown below:
Cost Effectiveness ($/g PM10 reduced) =
Cost per kilometer controlled ($/vkt)
Emission Factor (g PM10/vkt) ⋅ (1 - Control Efficiency) ⋅ (1 - Fraction Deposited)
A survey of costs will be conducted with the local GIDs to provide accurate values for the Lake
Tahoe basin. When these data are not readily available, standard cost estimator software will be
used to estimate the cost of the control.
Task 5. Project management and reporting.
Project management will involve coordination with researchers at UCD, DRI, and the sponsors
to schedule and execute field measurements. We will also be in contact with representatives
from Tahoe’s GIDs to obtain information about current and future emission control strategies.
The PI will be responsible to ensure all tasks are completed on time and within the available
budget.
Quarterly reports will be provided to document progress throughout the project. These reports
will list the progress of each task, present measured data, and note any changes/difficulties
encountered during the testing. All methods, analyses, and results will be documented in a draft
final report delivered one month prior to the completion of the project. Sponsors will have 2
weeks to evaluate the final report and recommend changes. Two weeks following the receipt of
the comments/changes, a final version of the report will be submitted.
VI Deliverables/Products
The primary deliverable for this project will be a report summarizing our results and providing
recommendations on the most cost effective control measures for use in the Tahoe basin. In
addition, at least one peer reviewed paper will be submitted describing the tests performed and
the results obtained. The data from this project will be of great value to urban and transportation
managers in the basin since it will provide specific recommendations on the effectiveness of
various emission control strategies.
VII Schedule of Events/Reporting and Deliverables
The timeline for the completion of the study is based on the assumption that funding will be
received in January, 2008. Delays in the receipt funding may affect the schedule and require a
no cost extension for completion of the project.
November – December, 2007: Task 1: Complete study plan with list of sites and emissions
controls to be tested at each location.
January – April, 2008: Prepare instrumentation for field measurements. Test deposition
monitoring system at DRI, Reno to ensure proper operation, determine limits of detection, and
perfect data reduction and analysis.
May – August, 2008: Task 2: Conduct summertime emission factor deposition measurements.
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August – November, 2008: Tasks 3 & 4: Analyze summertime data to determine emission
factors and deposition fraction.
December, 2008 – February, 2009: Task 2: Conduct wintertime emission factor and deposition
measurements.
March – August, 2009: Tasks 3 & 4: Analyze wintertime data to determine emission factors and
deposition fraction.
August – September 2009: Prepare draft final report.
October, 2009: Revise and finalize final report.
References
Abu-Allaban, M., J.A. Gillies, and A.W. Gertler (2003). Tailpipe, resuspended road dust, and
brake-wear emission factors from on-road vehicles. Atmospheric Environment 37: 52835293.
Byron, E.R. and C.R. Goldman (1986). A technical summary of changing water quality in Lake
Tahoe: The first five years of the Lake Tahoe Interagency Monitoring Program. Tahoe
Research Group Institute of Ecology. Univ. of Calif. at Davis. 62pp.
Buzorius, G., Ü. Rannik, E.D. Nilsson, T. Vesala, and M. Kulmala (2003) Analysis of
measurement techniques to determine dry deposition velocities of aerosol particles with
diameters less than 100 nm, Aerosol Science 34, 747–764.
Etyemezian V., H. Kuhns, J. Gillies, M. Green, M. Pitchford, and J. Watson (2003) VehicleBased Road Dust Emissions Measurement (I): Methods and Calibration. Atmospheric
Environment, 37, 4559 - 4571.
Etyemezian, V., J.A. Gillies, H. Kuhns, D. Gillette, S. Ahonen, D. Nikolic, and J. Veranth
(2004). Deposition and removal of fugitive dust in the arid southwestern United States:
measurements and model results. Journal of the Air and Waste Management Association 54:
1099-1111.
Etyemezian, V., H. Kuhns, J. Gillies, S. Uppapalli, G. Nikolich, and D. Zhu (2007). Clark
County Alternative Technologies for Paved Road Dust Emissions Measurement. Report
prepared for Clark County Department of Air Quality and Environmental Management, 500
S. Grand Central Pky., P.O. Box 551741, Las Vegas, NV 89155-1741.
Gertler, A., H. Kuhns, M. Abu-Allaban, C. Damm, J. Gillies, V. Etyemezian, R. Clayton, and D.
Proffitt (2006). A case study of the impact of winter road sand/salt and street sweeping on
road dust re-entrainment. Atmospheric Environment 40 (31): 5976-5985.
Gillies, J.A., V. Etyemezian, H. Kuhns, D. Nickolic, and D.A. Gillette (2005). Effect of vehicle
characteristics on unpaved road dust emissions. Atmospheric Environment 39: 2341–2347.
Gillies, J.A.,V. Etyemezian, H. Kuhns, J. Engelbrecht, S. Uppapalli, and G. Nickolich (2007).
Dust emissions caused by backblast from Department of Defense artillery testing. Journal of
the Air & Waste Management Association (accepted).
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Goldman, C.R., A.D. Jassby, and S.H. Hackley. 1993. Decadal, interannual, and seasonal
variability in enrichment bioassays at Lake Tahoe, California-Nevada, U.S.A. Can. J. Aquat.
Sci. 50: 1489-1496.
Jassby, A.D., C.R. Goldman, J.E. Reuter, and R.C. Richards. 1999. Origins and scaledependence of temporal variability in the transparency of Lake Tahoe, California-Nevada
(USA). Limnol. Oceanogr. 44 (2): 282-294.
Kuhns H., V. Etyemezian, M. Green, K. Hendrickson, M. McGown, K. Barton, and M. Pitchford
(2003). Vehicle-based road dust emissions measurement (II): Effect of precipitation, winter
time road sanding, and street sweepers on PM10 fugitive dust emissions from paved and
unpaved roads. Atmospheric Environment, 37, 4573 - 4582.
Kuhns H., M.-C.O. Chang, J.C. Chow, V. Etyemezian, L.-W.A. Chen, N. Nussbaum, S. K.K.
Nathagoundenpalayam, D. Trimble, S. Kohl, M. MacLaren, M. Abu-Allaban, J. Gillies, A.
Gertler, C. Damm, C. Denney, C. Gallery, and J. Skotnik (2004). DRI Lake Tahoe Source
Characterization Study: Final Report. Prepared for California Air Resources Board by
Desert Research Institute, Reno, NV October 22, 2004.
Roberts, D. (2006). Lake Tahoe Sediment and Nutrients Total Maximum Daily Load: Progress to
Date and Preliminary Results. Presentation to the PATHWAY Forum, April 27, 2006.
Swift, T.J., J. Perez-Losada, S.G. Schladow, J.E. Reuter, A.D. Jassby, and C.R. Goldman (2006).
Water clarity modeling in Lake Tahoe: Linking suspended matter characteristics to Secchi
depth. Aquat. Sci. 68: 1-15.
Vong, R.J., D. Vickers, and D.S. Covert (2004) Eddy correlation measurements of aerosol
deposition to grass Tellus B 56 (2), 105–117.
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X Attachments
.
10000
El Paso Unpaved Road
Lake Tahoe Paved Road
Clark County Paved Road
y = 7.8432x0.3565
2
R = 0.7922
1000
Emission Factor (g/vkt)
Paved Road Best Power Fit
Unpaved Road Best Power Fit
100
10
0.7995
y = 0.6053x
R2 = 0.8486
1
0.1
0.01
0.01
0.1
1
10
100
1000
10000
Traker Signal (mg/m3)
Figure A. Integrated emission factor calibration for TRAKER vehicle operating on both paved
and unpaved roads. Data from paved roads in Boulder City, Nevada are consistent
with the measurements conducted near Sand Harbor State Park in Lake Tahoe (after
Etyemezian et al., 2007).
20
A
B
Legend
Emission Factors
Average EF (g/vkt)
0.000 - 0.301
0.302 - 0.983
2.074 - 4.320
4.321 - 16.316
0.984 - 2.073
Figure B. Road dust emission potential survey data measured by TRAKER, which can be used
to identify zones of consistently high road dust emission potential. (A) Represents the
TRAKER survey of 2006/11/30 following a snow event 2 days prior to sampling, road
is wet. (B) Represents the TRAKER survey of 2006/12/20 following a snow event 2
days prior to sampling, road is dry.
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