I. Title Page
Title:
Refining Estimates of Atmospheric Deposition for Sediment
Particles and Particulate Nutrients in the Lake Tahoe Basin
Subtheme this proposal is
responding to
Theme: Air Quality
Subtheme: Improving the estimates of atmospheric deposition
Principal Investigator and
Receiving Institution
L.-W. Antony Chen, Ph.D.
Division of Atmospheric Sciences
Desert Research Institute
2215 Raggio Parkway
Reno, NV 89512
Phone: 775-674-7028
Fax: 775-674-7009
Email: antony@dri.edu
John G. Watson, Ph.D.
Division of Atmospheric Sciences
Desert Research Institute
Email: johnw@dri.edu
Co-Principal Investigator
Xiaoliang Wang, Ph.D.
Division of Atmospheric Sciences
Desert Research Institute
Email: Xiaoliang.Wang@dri.edu
Agency Collaborator
Grants Contact Person
Funding requested:
Total cost share (value of
financial and in-kind
contributions):
Wen-Ming Chien, Ph.D.
Department of Chemical & Materials Engineering
University of Nevada, Reno
Phone: 775-784-7789
Fax: 775-327-5059
Email: wmchien@unr.edu
N/A
Lycia Ronchetti
Business Manager
Division of Atmospheric Sciences
Desert Research Institute
2215 Raggio Parkway
Reno, NV 89512
Phone: 775-673-7411
Fax: 775-674-7016
Email: Lycia.Ronchetti@dri.edu
$237,128
Not applicable unless agency awards a cooperative agreement.
0
II. Proposal Narrative
a. Project Abstract
Deposition of sediment particles and particulate nutrients into Lake Tahoe seriously influences
the Total Maximum Daily Load (TMDL) and threats the lake clarity. The current deposition estimates
derived from inferential methods with limited temporal and size resolution need to be improved. This
project will employ innovative multi-channel deposition samplers to collect dry and wet deposition
particles at sites representative of offshore, near-shore, and upper watershed environments in the Lake
Tahoe Basin for a full year. Samples of 24-hr duration will be analyzed in the laboratory by a scanning
electron microscopy/energy-dispersion X-ray spectroscopy (SEM/EDX) method to determine the number
count, size distribution, and chemical composition of deposited particles, which are in turn translated into
the deposition fluxes and annual loads of particles and particulate nutrients. Contrasts between different
environments and chemical information should reveal the significance of near-shore activities and inland
pollutants on particulate deposition, which leads to best management practices (BMPs) for mitigating the
impact. Simultaneous measurements of PM10 and TSP (particulate matter with aerodynamic diameter <10
µm and total suspended particles, respectively) concentration by DustTrak® at the monitoring sites will
evaluate their use as an indicator for particulate deposition on a routine, cost effective basis.
b. Justification Statement
This proposal responds to the Air Quality Subtheme 3a: Improving the estimates of atmospheric
deposition. Specifically, the proposed project will develop a new monitoring approach to facilitate
determining total (i.e., dry and wet, direct and indirect) atmospheric deposition fluxes of sediment
particles and particulate nutrients into Lake Tahoe, reduce one of the largest uncertainties in current
estimates, and better inform lake clarity modeling and priority of restoration efforts. This is to be achieved
by establishing a yearlong passive monitoring program coupled with offline analytical methods which
measure number concentration, size distribution, and chemical composition of deposited particles
simultaneously. In addition, the project will contribute to the Integrating Science Subtheme 4b:
Identifying environmental indicators and development of approaches for monitoring and evaluations. The
possibility of using continuously measured ambient PM concentrations, along with local wind speed, as
an indicator for particulate deposition will be critically evaluated. The project team consists of Desert
Research Institute (DRI) and University of Nevada, Reno (UNR) researchers with extensive experience in
ambient and source monitoring in the Lake Tahoe Basin and state-of-art laboratory analysis techniques.
c. Background and Problem Statement
Lake Tahoe, a pristine sub-alpine lake located in the eastern Sierra Nevada on the border of
Nevada and California, is known for its extraordinary clarity and deep blue color. Because of its scenic
quality and ecological assets, Lake Tahoe has been designated an “Outstanding National Water Resource”
in which no long-term degradation is permitted. However, Lake Tahoe clarity has decreased during the
last four decades (1967–1997) as a result of increased sediment (particularly particles less than 16
micrometer [PM16]) loading and algal growth stimulated by nutrient (particularly nitrogen [N] and
phosphorus [P]) input from atmospheric deposition and urban/forest runoff (Jassby et al., 1994; 1999).
Increases in sediments and nutrients negatively affect many beneficial uses of Lake Tahoe, from aesthetic
enjoyment by residents and tourists to the health of aquatic life.
The Lake Tahoe Total Maximum Daily Load (TMDL; Smith and Kuchnicki, 2010) represents a
decade of collaborative effort between government agencies and public stakeholders to better understand
the causes of lake clarity impairment and to develop a cost-effective, workable plan for improvement.
Atmospheric deposition is identified by the TMDL as a primary source of pollutants, contributing 15% of
PM16, 55% of N, and 15% of P loading to the lake, mostly through dry deposition (Roberts and Reuter,
2007). The estimates of dry and wet deposition flux mainly result from the Lake Tahoe Atmospheric
Deposition Study (LTADS, see Dolislager et al. (2006; 2009)) and a longer-term monitoring program by
1
University of California-Davis (UC-Davis) Tahoe Environmental Research Center (TERC).
The LTADS evaluated dry deposition using observed ambient concentrations in conjunction with
modeled deposition velocities. Most particulate and nutrient species were quantified on time-integrated
filter samples (up to 2-week averaging time), which provided limited temporal and size resolution. To
calculate particle deposition flux, i.e., product of ambient concentration and size-dependent deposition
velocity (Vd), average particle sizes needed be estimated. Uniformity assumptions were made regarding
particle chemical composition within a sampling size range and an averaging period. These assumptions,
along with potential biases in the deposition models, led to uncertainties in the dry deposition estimates
with respect to PM16 and particulate N and P. Moreover, active sampling with pumping requirement
restricts the choices of sampling site and/or duration (if powered by battery) and incurs a higher operating
cost than passive sampling for the long run.
Eddy correlation methods provide the most reliable estimates of deposition. However, they
require high frequency (>10 Hz) and accuracy measurements that are often not available. Sampling
deposition on a surrogate surface represents another feasible approach, especially for larger particles (>2
µm) where the specific nature of the surface is not as important as the particle size (Seinfeld and Pandis,
1998). In a study of particle deposition onto Lake Michigan (Lin et al., 1993; 1994), the use of a smooth
surrogate surface to directly measure dry deposition fluxes was shown to compare very well to fluxes
estimated with a multistep deposition model. UC-Davis TERC has been employing automated buckets in
Ward Valley to collect dry, wet (precipitation), and total deposition for offline analysis. Water-soluble N
and P species were determined from rinsates of the bucket surfaces. One particular drawback is that the
analysis does not provide estimates for particle deposition; the mass or number of particles in rinsates
were never quantified. It is also not possible to isolate particulate contributions of nutrient deposition.
As pointed out by Reuter et al. (2007), “the uncertainty associated with PM deposition requires
additional study as these were the first estimates and only measured over a limited time”. This proposed
study seeks to improve the estimates of dry and wet PM deposition by introducing an innovative sampling
and analysis approach based on multichannel deposition sampler (MDS) and scanning electron
microscope/energy-dispersive X-ray spectroscopy (SEM/EDX) analysis. The approach will allow

direct deposition measurement at 24-hour resolution or less, thus reducing uncertainties in
deposition calculations;

size-resolved particle deposition measurements to facilitate the current Lake Clarity Model which
requires a full set of seven size classes (0.5–1 μm, 1–2 μm, 2–4 μm, 4–8 μm, 8–16 μm, 16–32 μm,
and 32–64 μm) as the input data (Swift et al., 2006);

lower power consumption and greater automation so that multiple-site, long-term operating cost is
reduced;

semi-quantitative measurement of particulate N and P to evaluate the relative importance of
particulate nutrient deposition; and

examination of particle morphology and elemental composition to help understand sources/
pathways of particle deposition.
d. Goals, Objectives, and Hypotheses
This research project will: 1) establish yearlong temporal- and size-resolved PM deposition
monitoring that complements current monitoring efforts; 2) refine estimates of dry/wet deposition loads
for PM and particulate N and P; 3) determine Vd suitable for the Lake Tahoe and surrounding watersheds;
and 4) evaluate ambient PM10 and/or TSP concentrations (real-time) as a deposition indicator.
One major hypothesis is that the deposition flux is inhomogeneous over the lake as near-shore
atmospheric deposition, particularly with respect to PM16, is higher than offshore due to more human
2
activities. PM from the watershed to the lake by surface water may also be significant compared to direct
deposition onto the lake. These hypotheses will be tested in this study.
e. Approach, Methodology and Location of Research
The configuration of deposition samplers and SEM/EDX analysis method will first be described
in this section, followed by location of research and a breakdown of research tasks.
e.1 Multichannel Deposition Samplers (MDS)
Two types of MDS will be used for this study. The dry deposition version (MDSdry) consists of
eight shallow, round stainless steel sample holders (Figure 1[a]). Each sample holder is fastened to a
rotation axle via a straight rod and can accommodate a 47-mm-diameter polycarbonate filter (Millipore
type GTTP, pore size 0.22 µm, coated with Apezion L grease) as the surrogate surface for dry deposition.
A flat, stainless steel cover coated with 1 mm of low friction Vespel SP22 (Vespel with 40% graphite by
weight, manufactured by DuPont Chemicals) minimizes disturbance to the air flow and seals the filters
against deposition and any potential contamination prior to and after sampling in field. At any given time,
only one sample is exposed to the ambient air through a gap in the cover. The axle is rotated by a
programmable stepper motor to change the sampling position. Both the filter holder and cover are made
of conducting material to avoid static charges that may influence the deposition pattern. A 12-V battery
can power the stepper motor and controller uninterruptedly for more than a week.
(a)
(b)
Figure 1. Schematic diagram of multi-channel (a) dry and (b) wet deposition sampler. The stepper motors
are powered by a 12-V battery through a programmable controller (not shown).
The design of wet deposition MDS (MDSwet) is similar to MDSdry but the filter holders are
replaced with hoops to hold rain/snow collection bottles 10−15 cm (4−6 inches) deep (Figure 1[b]).
MDSdry and MDSwet are expected to operate side by side. The sampling duration for individual
filters/collectors should be 24 hrs (e.g., rotating sample holders every midnight) or less. MDSdry filters are
representative of dry deposition conditions only if no precipitation occurs during the sampling period. In a
typical year, more than 70% of spring, summer, and fall days and > 50% of winter days record zero
precipitation (see Figure S1 in Section V: Supplemental Figures). These days would be adequate
statistically for determining the seasonal 24-hr dry deposition flux. Small-to-moderate precipitation (<4
inches/day) in either rain or snow form will be collected by MDSwet bottles and analyzed in the laboratory
for suspended particles. For heavy precipitation that is beyond the MDSwet collection capacity, only a
fraction of precipitation will be collected and analyzed though it should already scavenge most
atmospheric particles. Such events most often occur during winter snow storms. The design of MDS has
emphasized on protecting the exposed filters and bottles against severe weather conditions before the field
operator(s) have a chance to recover them and recondition the samplers.
3
The exposed polycarbonate filters from MDSdry are ready for SEM/EDX analysis of size-number
distribution and chemical composition of deposited particles. Filters that are possibly interfered by rain or
any other visible contaminants should be invalidated. Dry deposition flux (Fdry) is calculated by dividing
the areal density of particle number, volume, or mass on the filters by the filter exposure time. Annual dry
PM flux is then estimated from all valid Fdry, i.e.,
Annual dry PM flux = Average daily Fdry × 365 days/year
(1)
Water samples from MDSwet need to be first sonicated and filtered through 0.2-µm (non-coated)
polycarbonate filters. This should retain most sediment particles of concern. The dried filters can then be
analyzed by SEM/EDX for total (wet + dry) deposition fluxes (Ftotal). The total PM flux for all the
rainy/snowy days during a year is:
Total PM flux (wet days) = Sum of daily Ftotal (wet days)
(2)
and the annual wet and total deposition can be calculated by:
Annual wet PM flux = Total PM flux (wet days) - Average daily Fdry × Number of wet days/year
(3)
Annual total PM flux = Annual dry PM flux + Annual wet PM flux
(4)
e.2 SEM/EDX Analysis
SEM/EDX technique has long been used to study ambient particulate matter including PM2.5 and
PM10 (Watson et al., 1999; Casuccio et al., 2004; Yue et al., 2006). Typically, particles as small as 0.05
µm can be imaged by SEM, providing information on the physical properties of particles such as size,
shape, and surface morphology. SEMs equipped with EDX can further provide information on the
elemental associations within individual particles, which leads to classification and source attribution of
the particles. SEM/EDX analysis is suitable for this study since dry and wet PM deposition within 24 hrs
are expected to be low and below the detection limits of most bulk analysis techniques such as
gravimetry, X-ray fluorescence (XRF), and water-extraction ion chromatography (IC) method (see Chen
et al., 2011 for a summary of these methods). SEM offers superior sensitivity by imaging and counting
individual particles. In addition, SEM resolves size distribution of the deposited particles, thus facilitating
the Lake Clarity Model. It is also possible to determine the abundance of N or P-rich particles from EDX
and estimate the particulate N and P deposition.
The SEM/EDX analysis will be carried out using an Hitachi S-4700 Field-Emission Scanning
Electron Microscope (available at UNR Department of Chemical and Materials Engineering) following
the U.S. EPA guideline (Willis and Conner, 2003). A small portion (~1 cm2) of the particle-laden filter
will be mounted onto a SEM sample stub using conductive adhesive and then coated with a thin gold film
(<10 nm) to avoid charge build-up. Inside the SEM, a focused electron beam (1−20 kV) is scanned over
the sample in parallel lines, which interacts with the sample and produces an array of secondary effects,
such as back-scattering (BSE) and secondary electrons (SE), that can be detected and converted into an
image (e.g., Figure S2). The image can then be digitized and presented to an image analyzer such as
ImagePro-Plus (Media Cybernetics, Inc. Bethesda, MD), which uses predefined automated algorithms to
identify individual particles and record detailed information about their size and morphology. In the
meanwhile, the X-ray spectrum produced by electron beam-particle interaction is collected by the EDX
analyzer for chemical composition analysis.
For particle size and morphology analysis, images of several different magnifications will be
obtained to seek particle size distributions with minimal sizing error. Equivalent particle diameter (Dp) is
typically calculated using the projected area (Ap) of the particle:
2
⁄
(5)
and particle volume (Vp) is estimated assuming particles are ellipsoid shape (Coz et al., 2009):
4
(6)
where Dmax and Dmin are the longest and shortest axis of the particle. The size distribution of Saharan dust
particles in Figure S2 is derived and presented in Figure S3. These dust particles are found to center at ~5
µm diameter. The size distribution can be processed into 7 size bins for the Lake Clarity Model input.
The EDX analyzer collects X-ray signal for ~10 s and parses the spectrum into 2048 channels
with 10 eV width. The position and shape of the peaks will be compared to a library spectrum to identify
elements, and, with proper calibration, the X-ray intensities of peaks will be used to semi-quantitatively
derive elemental fractions in the particles. The EDX detection limit for elements Na to U in individual
particles larger than 1-µm diameter is about 0.5 wt% (Willis and Conner, 2003). Light elements such as
carbon (C) and N are measurable but with larger detection limits (Laskin and Cowin, 2001). Figure S4
shows an example of SEM image with EDX spectrum for particle deposition collected in Davenport,
California (Watson et al., 1999). It shows that nearly all coarse particles are calcium rich, probably
resulting from a nearby cement plant.
Fractions of nutrient elements N and P in PM will be quantified from EDX. However, due to the
difficulties to correct X-ray yields from particles with irregular surfaces and thicknesses less than the
incident electron range (Buseck and Bradley, 1982), substantial uncertainties are inherent in quantitative
EDX analysis. Nonetheless, particles can be categorized into different groups according to their chemical
compositions (Watson et al., 1999; Willis and Conner, 2003). For example, road dust typically contains
high percentage of Si, Al, Fe, and K; Asian dusts from inter-continental transport are rich in Ca; biomass
burning particles contain high C and K; and secondary sulfate aerosols have high S. The chemical
composition of individual particles will provide insight into the origin of the deposited particles. How N
and P distribute in these particles should infer the pathway of nutrient deposition.
e.3 Sampling Locations and Planned Measurements
Deposition monitoring will be conducted at three sites representing offshore, near-shore, and
upper watershed environments (Figure S5). Research buoys operated by NASA Jet Propulsion Laboratory
and UC-Davis are ideal offshore monitoring sites. However, the space on the buoys is limited and
deposition measurement will likely be interfered by large solar panels onboard. It is also costly to access
the site once a week. The Crystal Bay Peninsula that is surrounded by Agate Bay and Crystal Bay and ~3
km into the lake represents a reasonable and logistically feasible alternative. Sampling instruments will be
located at a local high point at the end of the Peninsula ~40 m above the lake surface. The sampling site
should be away from major commercial/tourism activities by at least 200 m.
Near-shore monitoring will be set up at the Lake Vista pier belonging to the North Tahoe Public
Utility District. The pier once served as a monitoring site for LTADS. It is close to Crystal Bay (~5 km
away) so that the differences between the two sites would reveal additional deposition caused by nearshore activities including traffic (CA-28), boating, and beach games. Several other piers on the north
shore of Lake Tahoe can be our backup monitoring sites. The upper watershed site seeks to measure
deposition further inland. Gertler et al. (2006) pointed out that local air pollutants threaten Lake Tahoe's
clarity. These pollutants are more elevated in major population centers around the lake (Chen et al.,
2011). We select the current air quality monitoring site at the Incline Village Library (operated by the
Washoe County) as the upper watershed deposition site since it represents air quality conditions in Incline
Village and, to some extent, the Incline Creek Watershed. The site is already part of a SNPLMA Round
11 project (PI: Antony Chen) to evaluate prescribed burning impact on ambient PM and ozone (O3)
levels. An alternative choice would be UC-Davis’s TERC building in Incline Village.
The sampling suite at each site will include a pair of dry/wet MDSs and a pair of DustTrak® (TSI
Instrument, Shoreview, MN) measuring ambient PM10 and TSP concentrations in real time. Sampled air is
drawn (1.7 liter/min) through a size-cut inlet into the DustTrak® detection zone where it is illuminated by
5
a laser beam, and the scattered light detected at 90±30° relative to the sensing zone is converted to PM
concentration at 1-sec resolution. DustTrak® is battery powered and very portable. The 24-hr deposition
measured from MDSs will be related to PM10 and TSP from DustTrak® (i.e., [PM10]DT and [TSP]DT) by:
Fdry = a × ∫t Vd’(ū) × [PM10]DT dt + b × ∫t Vd”(ū) × ([TSP]DT - [PM10]DT)dt
(7)
Fwet = c × ∫t [PM10]DT dt + d × ∫t ([TSP]DT - [PM10]DT)dt
(8)
where Vd’(ū) and Vd”(ū) are the theoretical dry deposition velocity of PM10 and PM>10 (i.e., PM > 10 µm
diameter), respectively, as a function of horizontal wind speed ū. Figure S6 illustrates the theoretical Vd
values over water and the critical importance of particle size in determining deposition. Mean particle size
for PM10 and PM>10 will be determined from the SEM size distribution measurements and used, along
with on-site wind speed data, to calculate Vd’(ū) and Vd”(ū). a, b, c, and d are fitting parameters. How well
Eq. (7) and (8) can be fitted determines the usefulness of PM10 and TSP measurement as an indicator for
particulate deposition. It also provides an estimate of true Vd for PM10 and PM>10.
Although the field study focuses on northern Lake Tahoe, the results are expected to inform
models used to assess conditions for the entire Lake Tahoe Basin. If real-time PM10 or TSP is proved to be
effective particulate deposition indicator, measurements commonly made at air quality monitoring
stations such as South Lake Tahoe (by California Air Resource Board), Stateline (by Tahoe Regional
Planning Agency [TRPA]), Tahoe City, and Kings Beach (by Placer County) could be integrated into the
regional deposition modeling.
e.4 Project Tasks
Task 1: Assemble deposition samplers and develop sampling/analysis protocol
Three pairs of MDSdry and MDSwet will be assembled following the design in Figure 1. They will
first be tested at DRI for 24-hr exposure under various weather conditions. Adjustments will be made
where necessary. Different SEM magnifications will be explored for optimal images with respect to
particle counting and size distribution measurements on loaded polycarbonate filters. This will depend on
the nominal size of environmental particles and their concentrations on the filters. Through nebulization
and resuspension, standard filters containing ammonium sulfate ([NH4]2SO4), ammonium nitrate
(NH4NO3), amino acids, monosodium, sodium phosphate (NaH2PO4), road dust, and/or soot particles will
be made to calibrate the EDX signal. EDX-derived elemental concentrations, including N and P, will be
verified by conventional XRF and IC methods.
Task 2: Year-long deposition monitoring at three Lake Tahoe sites
MDSs, along with DustTraks® and weather stations, will be deployed at three sites shown in
Figure S5 for at least one year. Dry and wet (bottle) samples will be collected every day and retrieved by
a field operator every week. The operator will also visit the site when there is doubt that severe weather
conditions may have impacted the samplers. During the visit, the operator will flag samples with visible
contamination, including water on polycarbonate filters, install new filters/bottles, and replace the battery.
Samples will be brought to the DRI laboratory, stored in the refrigerator at ~4°C, and queued for analysis.
Task 3. Laboratory analysis for particle number, size distribution, and chemical composition
Excluding samples marked invalid, it is expected that half of the dry samples (~120, or ~30 from
each season) and most of the wet samples (i.e., filtered residues) from each site will be analyzed by SEM
for particle number concentration and size distribution, from which the deposition fluxes will be
calculated. EDX analysis will be performed on selected samples (at least 10%) to determine element-,
particularly N- and P-, specific fluxes. The analysis will focus on dry samples as particulate nutrients may
be depleted in water samples (i.e., dissolve into water). Particles will also be categorized according to
their chemical composition and morphology to facilitate further data analysis.
Task 4. Integrated data analysis for deposition rate, pathway, and potential indicators
6
Data analysis will be conducted to address the research objectives and hypotheses. First, annual
PM flux through dry and wet deposition will be calculated through Eq. (1)−(4). We will evaluate the
spatial homogeneity of deposition by comparing the offshore and near-shore deposition flux. Chemical
composition data should suggest the nature and source of additional particles at the near-shore site. The
first-order estimate of flux of pollutants from the Incline Creek watershed to the lake will be achieved by
multiplying the deposition flux measured at the Incline Village site by the surface area of all streams in
the watershed. More sophisticated modeling, though beyond the scope of this project, can certainly use
the data derived from this study. The degree to which PM10 and TSP measurements can indicate
particulate deposition will be evaluated through Eq. (7)−(8).
f. Relationship of the Research to Previous and Current Studies
This project complements the benchmark LTADS by providing an independent assessment of dry
and wet PM deposition. The two studies are based on different but both scientifically sound methods;
their discrepancies may quantify the level of uncertainty and identify areas for further research. Several
PM monitoring and source apportionment studies, including the Lake Tahoe Source Characterization
Study (Kuhns et al., 2004), Lake Tahoe Visibility Impairment Source Apportionment Analysis (Green et
al., 2011), and SNPLMA Round 10 & 11 Lake Tahoe biomass burning studies (PI: D. Orbist and A.
Chen), have been conducted to understand the origins of PM and particulate nutrients in the Lake Tahoe
atmosphere. This study seeks to perform similar source attribution analysis by examining chemical
signature and morphology of actually deposited particles.
g. Strategy for Engaging with Managers
The DRI/UNR research team will consult TRPA for obtaining access to the planned or alternative
monitoring sites. An arrangement has been made with Washoe County to use the Incline Village site. In
order to ensure that the TMDL implementation and lake clarity modeling will benefit from the new
information, data obtained as part of this study will be communicated to key constituents working on
water quality issues (research, regulation, etc.) in the basin, particularly TRPA, California State Water
Resource Control Board, Nevada Department of Environmental Protection, U.S. Forest Service, Lahontan
Regional Water Quality Control Board, UC-Davis TERC, and EPA Regional 9, through
presentations/discussions at the Science and Management Integration Team and Lake Tahoe Integrated
Monitoring Program meetings as well the biannual Tahoe Science Symposium. Data and reports will be
made available to the general public, transitioned to stakeholders involved in state implementation plan
(SIP) formulation, and published in peer-reviewed scientific journals.
h. Deliverables and Products

Transportable, battery-powered multi-channel samplers for dry and wet PM deposition.

A working SEM/EDX protocol and relevant documentations for analyzing number concentration, size
distribution, and chemical composition of deposited particles in the Lake Tahoe Basin.

Estimates of dry and wet deposition fluxes, by season, at representative offshore, near-shore, and
upper watershed environments. This dataset can readily serve as input to the Lake Clarity Model.

Assessment of the importance of near-shore activities and inland air pollution to PM and particulate
nutrient deposition. The assessment is expected to result in recommendations to the ongoing
restoration efforts.

A potential indicator for particulate deposition based on real-time PM10 and/or TSP measurements.
The final report will contain all measurement results, data analysis, conclusions, and
recommendations. It will be delivered within 3 month after the project period. Progress will be tracked
through regular e-mails and conference calls with the program manager(s). Research results will be made
available online via the DRI server. A least two scientific publications will be generated from this study.
7
III. Schedule of Milestones
The project is expected to be completed in 24 months (7/1/2012–6/30/2014).
Milestone/Deliverables
Prepare progress reports
Deposition monitoring
system and protocol
Deposition monitoring
program
Laboratory analysis for
particles of dry and wet
deposition
Integrated Data Analysis
Draft Report
Final Report
Start Date
End Date
Description
7/1/2012
6/30/2014 Submit brief progress report to Tahoe
Science Program (TSC) coordinator by the
1st of July, October, January, and April.
Prepare summary of annual accomplishments
in October.
7/1/2012
9/30/2012 Assemble deposition samplers and develop
sampling/analysis protocol. Finalize study
design and sampling plan.
10/1/2012
9/30/2013 Carry out yearlong ambient monitoring
program. Conduct weekly visit to the
monitoring sites.
11/1/2012 12/31/2013 Analyze PM number concentration, size
distribution, and chemical composition by
SEM/EDX.
12/1/2012
2/28/2014 Analyze data for deposition fluxes,
spatiotemporal distribution, and PM source
attribution.
3/1/2014
5/31/2014 Complete draft report. Draft report submitted
to TSC by 5/31/2014.
6/1/2014
8/31/2014 Complete revisions to final report and
prepare associated manuscript(s) for
submission to peer-review journal(s).
8
IV. Literature Cited
Buseck, P.R.; Bradley, J.P. (1982). Electro beam studies of individual natural and anthropogenic
microparticles: compositions, structures and surface reactions. In Heterogeneous Atmospheric
Chemistry, Schryer, D. R., Ed.; American Geophysical Union Geoplysical Monograph: 57-76.
Casuccio, G.S.; Schlaegle, S.F.; Lersch, T.L.; Huffman, G.P.; Chen, Y.Z.; Shah, N. (2004). Measurement
of fine particulate matter using electron microscopy techniques. Fuel Processing Technology,
85(6-7):763-779. WOS:000221031200027.
Chen, L.-W.A.; Watson, J.G.; Wang, X. (2011). Visibility Monitoring and Standards for Lake Tahoe
Basin: Assessment of Current and Alternative Approaches. prepared by Desert Research Institute,
Reno, NV, for USDA Forest Service Pacific Southwest Research Station, Berkeley, CA;
http://www.fs.fed.us/psw/partnerships/tahoescience/documents/final_rpts/P060LakeTahoeVisibili
tyFinalReport0720.pdf.
Coz, E.; Gomez-Moreno, F.J.; Pujadas, M.; Casuccio, G.S.; Lersch, T.L.; Artinano, B. (2009). Individual
particle characteristics of North African dust under different long-range transport scenarios.
Atmos. Environ., 43(11):1850-1863.
Dolislager, L.J.; Lashgari, A.; Pederson, J.; VanCuren, T. (2006). LAKE TAHOE ATMOSPHERIC
DEPOSITION STUDY (LTADS). prepared by California Air Resource Board, Sacramento, CA,
for Lahontan Regional Water Quality Control Board, Lahontan Regional Water Quality Control
Board,
and
Lahontan
Regional
Water
Quality
Control
Board,
http://www.arb.ca.gov/research/ltads/final/intro.pdf.
Dolislager, L.J.; VanCuren, R.; Pederson, J.R.; Lashgari, A.; McCauley, E. (2009). A summary of the
Lake Tahoe atmospheric deposition study (LTADS). Atmos. Environ., in press.
Gertler, A.W.; Bytnerowicz, A.; Cahill, T.A.; Arbaugh, M.; Cliff, S.; Kahyaoglu-Koracin, J.; Tarnay, L.;
Alonso, R.; Fraczek, W. (2006). Local air pollutants threaten Lake Tahoe's clarity. California
Agriculture, 60(2):53-58.
Green, M.C.; Chen, L.-W.A.; DuBois, D.W.; Molenar, J.V. (2011). Lake Tahoe visibility impairment
source apportionment analysis. prepared by Desert Research Institute, Reno, NV, for USDA
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10
V. Supplemental Figures
Figure S1. Statistics of 24-hr total precipitation at the South Lake Tahoe Airport for 2008−2010 (data
obtained from http://www.wunderground.com/history/airport/KTVL/2011/10/18/DailyHistory.html).
Table shows the number of days in each precipitation category in the three years.
Figure S2. Secondary electron SEM images of Saharan dust particles collected near Puerto Rico on
7/21/2000 at four magnifications: (a) 1000X, (b) 2000X, (c) 4000X, and (d) 12000X (Reid et al., 2003).
The spherical dots in the images are pores of the polycarbonate filter.
11
PM16
Figure S3. Size distribution of particles obtained from SEM images similar to those in Figure S2 (MBL:
marine boundary layer; SAL: Saharan air layer) (Reid et al., 2003). Dashed lines indicate the Lake Clarity
Model size bins.
Figure S4. Low magnification SEM image of particle deposition from Davenport, California (upper left)
and examples of EDX spectrum of Ca-rich particles (Watson et al., 1999).
12
Figure S5. Proposed offshore (deep water), near shore, and upper watershed deposition monitoring sites
in northern Lake Tahoe. TB1 and TB4 indicate research buoys operated by NASA/UC-Davis.
Figure S6. Modeled particle dry deposition velocities to water surfaces as a function of wind speed U
(near-neutral stability) and particle diameter (Pryor and Barthelmie, 2000).
13