Evaluation of Prescribed Burning Emissions and Impacts on
Air Quality in the Lake Tahoe Basin
Final Report
L.-W. Antony Chen
Tom Malamakal
Xiaoliang Wang
Mark G. Green
Judith C. Chow
John G. Watson
Division of Atmospheric Sciences
Desert Research Institute
Nevada System of Higher Education
Reno, NV 89512
December 31, 2014
This research was supported through an agreement with the USDA Forest Service Pacific
Southwest Research Station, using funds provided by the Bureau of Land Management through
the sale of public lands as authorized by the Southern Nevada Public Land Management Act
(Round 11)
Executive Summary
Prescribed burning has been conducted in and around the Lake Tahoe Basin (LTB) to
maintain natural succession of plant communities and to reduce wildfire danger. During 20112012, approximately 2000 acres of wildland in the LTB were subjected to understory or slashpile burns. Although these prescribed burns are conducted under strict guidelines, they can still
be an important source of air pollutants, particularly fine particulate matter (PM2.5), in the LTB.
This research combines ambient air quality monitoring, in-plume source measurements, and
dispersion modeling to characterize prescribed burning emissions and evaluate the magnitude
and spatiotemporal distribution of smoke impacts.
Combustion efficiencies (CEs) and emission factors (EFs) for PM2.5 mass and black
carbon (BC), along with gaseous nitrogen oxides (NOx), ammonia (NH3), and carbon monoxide
(CO) were determined based on four prescribed burns in/around the LTB. Lower CEs were
found for understory burns of natural vegetation (CE < 0.9) than for slash pile burns (CE > 0.9).
Low CEs were associated with higher EFPM2.5 and EFNH3, implying a larger environmental
impact by understory burns with respect to air quality and nutrient (i.e., nitrogen) deposition. As
EFPM2.5 generally increases with decreasing CE, the EFPM2.5/(1 - CE) ratio varies widely, by a
factor of six. The low-end EFPM2.5 is consistent with laboratory combustion tests of dry LTB
fuels and the assumptions of Fire Emission Production Simulator (FEPS), an operational
emissions model. The high-end EFPM2.5 agrees with laboratory tests of relatively moist fuels. For
simulation of the largest possible impacts, the CE and EFPM2.5 coefficients in the FEPS need to
be adjusted according to the in-plume measurements. This increases the modeled PM2.5 emission
rates (g/hr), particularly for the smoldering phase and moist fuel conditions.
Ambient PM2.5 monitoring by real-time and integrated filter methods at five background
or community exposure sites in the LTB during 2011 and 2012 established baseline diurnal
patterns that facilitated identification of PM2.5 episodes for further assessment. PM2.5 episodes
associated with prescribed burns were as short as 1–2 hours and seldom lasted more than several
hours. This is consistent with the proximity of the burn plots to the monitoring sites and fastchanging meso-scale winds. Impacts from distant wildfires were more spatially homogeneous
within the LTB and lasted longer (e.g., >48 hours). A dispersion model based on FEPS and
Hybrid Single Particle Lagrangian Integrated Trajectory (FEPS-HYSPLIT) run with highresolution (2 km x 2 km) Weather Research and Forecasting (WRF) meteorological data
confirmed the short duration of the prescribed burn impacts. The model-predicted PM2.5 episodes
due to prescribed burning agree in time with measured PM2.5 concentrations in many cases,
providing initial validation of the model. This suggests that the prescribed burning impact cannot
be ignored, even though no exceedances to the ambient 24-hr PM2.5 or 8-hr visibility standards
were reported at ambient monitors.
The FEPS-HYSPLIT approach reveals that smoke from the ignition and first several
hours of burning usually rises and moves away from population centers, as expected by the
smoke management plan. However, smoldering combustion can continue long after the active
ignition period. The smoldering smoke often impacts the community due to changes in wind
direction. Therefore, it is insufficient to initiate the prescribed burning decision solely based on
weather conditions of the burn day. A longer-term forecast (e.g., 72 hours) should be considered,
i
especially for burns close to population centers. Contributions of the smoldering combustion to
ambient PM2.5 concentrations depend on the emission rates, which are subject to a large
uncertainty in the current model.
The FEPS-HYSPLIT model, as a product of this study, provides fire agencies with an
additional tool to make/evaluate burn decisions. At this stage, the modeled PM2.5 concentrations
have not been evaluated adequately due to the lack of smoke-specific measurements at the
ambient monitoring sites. Recommendations are made to further refine and validate the model,
which include the development of a cross-agency, post-burn reporting system to archive accurate
burn information and the examination of spring and summer prescribed burns with specific
biomass burning markers.
ii
Table of Contents
1
2
3
4
5
Introduction .......................................................................................................................... 1-1
1.1
Background ................................................................................................................... 1-1
1.2
Prescribed Burning in the Lake Tahoe Basin (LTB)..................................................... 1-2
1.3
Understanding Prescribed Burning Emissions and Impacts: A Research Framework . 1-5
1.4
Guide to the Report ....................................................................................................... 1-8
Technical Approaches .......................................................................................................... 2-1
2.1
Ambient Monitoring Network ....................................................................................... 2-1
2.2
In-Plume Source Measurement ..................................................................................... 2-4
2.3
Laboratory Combustion Experiment ............................................................................. 2-8
2.4
Fire Emission and Dispersion Simulation ..................................................................... 2-9
Summary of Ambient PM2.5 Monitoring.............................................................................. 3-1
3.1
Meteorology and Wildfires ........................................................................................... 3-1
3.2
PM2.5 Concentration, Diurnal Variation, and Episodes ................................................. 3-1
3.3
PM2.5 Chemical Composition ...................................................................................... 3-11
Characterization of Prescribed Burning Emissions ............................................................. 4-1
4.1
Combustion Efficiency and Emission Factor ................................................................ 4-1
4.2
Time-integrated Emissions and PM2.5 Chemical Composition ..................................... 4-5
Smoke Forecast and Impact Assessment ............................................................................. 5-1
5.1
Integration of Smoke Forecast Tools ............................................................................ 5-1
5.2
Simulation and Verification of Measured Burn Events ................................................ 5-4
5.3
Assessment of Prescribed Burning Impacts: Case Studies ........................................... 5-9
5.4
Wildfire Impacts: Case Studies ................................................................................... 5-13
6
Conclusions and Recommendations .................................................................................... 6-1
Acknowledgement ....................................................................................................................... 7-1
References .................................................................................................................................... 8-1
Appendix A Prescribed Burn Conducted in 2011................................................................... 9-1
Appendix B Prescribed Burn Conducted in 2012 ................................................................... 9-5
Appendix C
Fuel Type and Fuel Load Breakdown for Prescribed Burns Studied ............... 9-10
iii
List of Figures
Figure 1. Land management/fire protection agencies and their boundaries in the Lake Tahoe
Basin (LTBMU, 2007). ................................................................................................................ 1-4
Figure 2. Maps of (a) wildfire susceptibility and (b) planned fuels reduction schedule (2007–
2016) for the Lake Tahoe Basin. Adapted from LTBMU (2007). ............................................... 1-5
Figure 3. A research framework for evaluating prescribed burning emissions and impact in the
Lake Tahoe Basin. It shows the relevancy of the three main tasks in this study: source
measurement, ambient monitoring, and fire emission/dispersion modeling. .............................. 1-7
Figure 4. Locations of ambient PM2.5 monitoring sites (blue balloons) in the Lake Tahoe Basin
(LTB) during 2011-2012 study periods: 1) Incline Village; 2) Tahoe City; 3) Bliss State Park; 4)
South Lake Tahoe; and 5) Cave Rock. Also shown are the locations of four prescribed burns
(stars ☆) measured by the In-Plume system: Skyland (SKY), Donner Memorial State Park
(DSP), Tunnel Creek (TNC), and Cold Creek (CLC). Solid circles indicate 60 recorded
prescribed burns carried out by Lake Tahoe Basin Management Unit (red), California State Park
(pink), Nevada Division of Forestry (green), and North Lake Tahoe Fire Protection Department
(yellow) throughout fall (September-November), 2011. ............................................................. 2-1
Figure 5. MiniVol sampling configuration, species measured, and analytical methods (Chow,
1995). XRF: X-ray fluorescence; IC: Ion Chromatography; AC: Automated Colorimetry; TOR:
Thermal/Optical Reflectance by the IMPROVE_A protocol (Chow et al., 2007). ..................... 2-2
Figure 6. Configuration of the In-Plume sampling system as deployed for prescribed burning
measure-ments (adapted from Wang et al., [2012]). ................................................................... 2-5
Figure 7. In-Plume measurements of prescribed burning smoke for (a) DSP and (b) TNC burn
with different accessibility. .......................................................................................................... 2-7
Figure 8. The 8 m3 combustion chamber with a typical sample burn and a schematic of the
experimental configuration with online and time-integrated measurements. The Potential Aerosol
Mass (PAM) flow reactor was not applied in this study. ............................................................. 2-9
Figure 9. Comparison of original and corrected DustTrak data with collocated (a, c) MiniVol
and (b, d) IMPROVE PM2.5 measurements. Only DustTrak data that covers >75% of the
integrated sampling periods were included. The corrections in (b)/(d) are based on regression
curves from (a)/(c). See Table 1 for the sampling periods in 2011 and 2012. Incline Village data
from 2012 were excluded............................................................................................................. 3-2
Figure 10. 24-hr averaged PM2.5 measured by DustTrak at five sites in LTB for 2011 (8/1/2011–
11/22/2011). Missing data are left blank. Also shown in the figure are time-integrated MiniVol
(weekly, black ba r) and IMPROVE (24-hr, green dot) PM2.5 concentrations. Basin-wide
episodes are marked by vertical dotted lines (red). No exceedances to the 24-hr PM2.5 NAAQS of
35 µg/m3 were observed. ............................................................................................................. 3-3
Figure 11. 24-hr averaged PM2.5 measured by DustTrak at five sites in the LTB for 2012
(5/1/2012– 8/31/2012). Missing data are left blank. Also shown in the figure are time-integrated
MiniVol (weekly, black bar) and IMPROVE (24-hr, green dot) PM2.5 concentrations. Basin-wide
episodes are marked by vertical dotted lines (red). No exceedances to the 24-hr PM2.5 NAAQS of
35 µg/m3 were observed. ............................................................................................................. 3-4
Figure 12. Boxplots based on hourly DustTrak data showing diurnal variations of PM2.5 by site
for the 2011 and 2012 monitoring periods. Hour of day corresponds to Pacific Standard Time
(PST). Circles indicate the medians and boxes show the interquartile range (IQR). Whiskers
iv
extend to the most extreme data points not considered outliers, and outliers, i.e., data outside
[Q1 – 1.5IQR, Q3 + 1.5IQR], are plotted individually as red crosses. Julian days in the year
corresponding to the outliers are also marked. DustTrak DRX at Incline Village appeared to have
been influenced by ambient temperature during 2012, so the measurements are not reliable. Note
that only three hourly outliers at the South Lake Tahoe site on Julian Days 271 and 306 exceed
35 µg/m3....................................................................................................................................... 3-5
Figure 13. Diurnal variations of PM2.5 at five sites during: (a) 2011 and (b) 2012 monitoring
periods, based on median hourly DustTrak data. The circle in (a) illustrates the basin-wide
mixing period. .............................................................................................................................. 3-8
Figure 14. Spatiotemporal variation of PM2.5 components and gaseous NH3 in the LTB during
the 2011 observing period. Horizontal bars indicate South Lake Tahoe concentrations as a
benchmark. Concentrations are based on weekly speciation data for: (a) PM2.5, (b) ammonium
sulfate, (c) ammonium nitrate, (d) OM, (e) EC, (f) fine soil, (g) salt, (h) non-crustal K (surrogate
for biomass burning), and i) NH3. Sampling sites: 1) Tahoe City, 2) South Lake Tahoe, 3) TRPA
Stateline, 4) Incline Village. ...................................................................................................... 3-11
Figure 15. PM2.5 chemical composition for the fall 2011 observing period for: (a) Tahoe City,
CA, (b) Incline Village, NV, (c) South Lake Tahoe, CA, (d) TRPA Stateline, NV. ................ 3-15
Figure 16. Time series of In-Plume measurements (1-min time resolution) during the Tunnel
Creek (TNC) burn on 10/20/2011 for: a) carbon (i.e., C) concentrations and combustion
efficiency (i.e., CEs) and b) PM2.5 concentrations and emission factors. Notes: Total C emission
includes carbon in CO2, CO, and BC. Arrows indicate the ignition time. Flaming, transition, and
smoldering phases are separated empirically (see text for details). All times are in PST. .......... 4-1
Figure 17. Distribution of 1-min CE during the CLC and SKY pile burns and the DSP and TNC
prescribed burns. Only data points with [CO] + 0.58×[PM2.5] > 200 µg/m3C are included in the
analysis to mitigate the influence of uncertainties on the baselines. This resulted in 107, 128,
193, and 121 data points for the CLC, SKY, DSP, and TNC burns, respectively. ...................... 4-2
Figure 18. Distribution of 1-min emission factors for: (a) CO and (b) NOx during the CLC and
SKY pile burns as well as the DSP and TNC understory burns. Only data points with 0.43 ×
[CO] + 0.58 × [PM2.5] > 200 µg/m3C are included. This resulted in 107, 128, 193, and 121 data
points for the CLC, SKY, DSP, and TNC burns, respectively. EFNOx are reported as gNO/kg dry
fuel. .............................................................................................................................................. 4-3
Figure 19. Distribution of 1-min emission factors for: (a) PM2.5 and (b) BC during the CLC and
SKY pile burns and the DSP and TNC prescribed burns. Only data points with [CO] + 0.58 ×
[PM2.5] > 200 µg/m3C are included in the analysis. This resulted in 107, 128, 193, and 121 data
points for the CLC, SKY, DSP, and TNC burns, respectively. ................................................... 4-4
Figure 20. Scatter plot of EFPM2.5 as a function of CE (1-min data) for: (a) three prescribed
burning events (i.e., SKY, DSP, and TNC) in 2011 and b) one prescribed burn event (i.e., CLC)
in 2013 and laboratory burns. The lower bound of the distribution is the FEPS default
parameterization while the upper bound is determined from the top 10th percentile of data with
respect to the EFPM2.5 / (1 - CE) ratio. Blue triangles and green diamonds indicate data from
laboratory combustion of wet and dry fuels, respectively (Chen et al., 2010). ........................... 4-5
Figure 21. Material balance of PM2.5 for: (a) SKY, (b) DSP, and (c) TNC burns. The mass
percentages are calculated from average of respective filter samples as shown in Table 7. See
v
Eqs. (9)-(13) for the construction of each component. Data were not available for the CLC burn.
...................................................................................................................................................... 4-8
Figure 22. FEPS modeled results for: (a) fuel consumption (by FLA, STS, and LTS phases) and
heat release and (b) combustion efficiency and emission rates (CO, PM2.5 and CH4) at hourly
resolution for the TNC burn (10/20/2011, the second peak in the figures). A burn conducted in an
adjacent 7-acre plot starting at 1000 PST on 10/19/2011 was also modeled. Default CE and EF
coefficients were used in the FEPS model (see Eqs. [6] and [7]). ............................................... 5-1
Figure 23. FEPS modeled hourly combustion efficiency (CE) and PM2.5 emission rates (default
and upper limit) for the TNC burn (10/20/2011). Adjusted coefficients were used to calculate CE
and the upper limit of PM2.5 emission. Actual PM2.5 emission rates are likely in the shaded area.52
Figure 24. Comparison of WRF surface winds with observations at: (a) four weather stations:
Slide Mountain (slm), Diamond Peak (dip), Incline Village (inv), and Sand Harbor (sah) closest
to TNC. Wind components in the east-west (U) and north-south (V) directions are compared in
(b) and (c), respectively. The yellow bars indicate the standard deviation of WRF winds across
the four sites. ................................................................................................................................ 5-2
Figure 25. Matlab® graphic user interface (GUI) for creating HYSPLIT control file for the TNC
burn. ............................................................................................................................................. 5-3
Figure 26. Matlab® graphic user interface (GUI) for executing the HYSPLIT model and
analyzing the output data. The monitoring sites are noted by 1-5 in the contour plot: 1: Incline
Village; 2: Tahoe City; 3: Bliss State Park; 4: South Lake Tahoe; and 5: Cave Rock. The
diamond indicates the TNC burn plot. The snapshot is for TNC burn 6 hours after ignition. Note
a burn conducted at an adjacent plot in the previous day (7 acres, started at 1000 PST on
10/19/2011) was also modeled here. ............................................................................................ 5-4
Figure 27. Time series of smoke transport (every 6th hour in PST) of surface PM2.5
concentrations (μg/m3 during 10/19-22/2011 for the two prescribed burns near Tunnel Creek
(Diamond). Five ambient monitoring sites around Lake Tahoe are also marked. (See Figure 26
for site identifications; the same latitudes and longitudes are used as in Figure 26.) .................. 5-5
Figure 28. Impact of Tunnel Creek (TNC) burns on five monitoring sites in the LTB, as
predicted by the FEPS-HYSPLIT model. Arrows indicate the start of burns on 10/19/2011 and
10/20/2011. .................................................................................................................................. 5-6
Figure 29. Comparison of hourly ambient PM2.5 measurements with FEPS-HYSPLIT predicted
PM2.5 contribution from Tunnel Creek burns for the: (a) Incline Village; (b) Tahoe City; and (c)
Bliss State Park sites. The median line indicates typical diurnal pattern determined from the
median concentrations throughout the fall 2011 observing period. Arrows indicate the burn start
times. See text for explanations of Peaks A–G. ........................................................................... 5-7
Figure 30. Impact of prescribed burn for: (a) SKY (6/11/2011); (b) DSP (10/3/2011); and (c)
CLC (6/24/2013) on ambient PM2.5 concentrations in the LTB, as predicted by the FEPSHYSPLIT model. See Table 2 for detailed burn information. Arrows indicate the burn start times.
Transport maps represent: a) 19; b) 10; and c) 7 hours after ignition. See Figure 26 for
explanation of the maps. .............................................................................................................. 5-8
Figure 31. Measured hourly PM2.5 concentrations in the LTB as compared to modeled
accumulative contributions of multiple prescribed burns (i.e., TNC, TNC, NTFPD1, NTFPD2,
vi
and LTBMU1) conducted between 10/17/2011 and 10/20/2011 on the north shore of Lake
Tahoe. PM2.5 episodes are identified (in circles) based on diurnal patterns (Table 5). ............. 5-10
Figure 32. Measured hourly PM2.5 concentrations in the LTB as compared to modeled
accumulative contributions of multiple prescribed burns (i.e., NTFPD3 near Incline Village, and
LTBMU2 in the Angora area) conducted between 10/31/2011 and 11/4/2011. PM2.5 episodes are
identified (in circle) based on baseline diurnal patterns (see Table 5). Ambient data from the
Tahoe City and Bliss State Park sites are not available for this period. .................................... 5-12
Figure 33. Snapshots of FEPS-HYSPLIT model simulated smoke transport for the two
prescribed burns: a) LTBMU2 (near Angora on 11/2/2011) and b) LTBMU3 (near Tahoe City on
11/15/2011). Colorbar indicates surface (0-25 m) PM2.5 concentrations in µg/m3 (log scale). See
Figure 26 for further explanations of the map. .......................................................................... 5-13
Figure 34. Salt Fire as observed by: (a) satellite and (b)-(d) PM2.5 measurements in the LTB. The
satellite image was acquired by NASA MODIS with 2 km x 2 km resolution at 1300 PST on
9/9/2011. Red dots indicate fire detected. Both measured and median (from Figure 12) PM2.5
concentrations between 9/7/2011 and 9/13/2011 are shown in Figure 34(b)-(d). Dashed lines in
Figure 34(c) mark the peaks corresponding to the morning and evening rush hours at the Tahoe
City site. ..................................................................................................................................... 5-14
Figure 35. Robbers Fire as observed by: (a) satellite and (b)-(d) PM2.5 measurements in the LTB.
The satellite image was acquired by NOAA at 1300 PST on 7/14/2012. Both measured and
median (see Figure 12) PM2.5 concentrations between 7/9/2012 and 7/16/2012 are shown in
Figure 35(b)-(d). Dashed lines in Figure 35(b) mark the peaks corresponding to the morning and
evening rush hours at the Tahoe City site. ................................................................................. 5-15
vii
List of Tables
Table 1. Summary of ambient monitoring network established for the 2011-2012 prescribed
burning impact assessment. ......................................................................................................... 2-3
Table 2. Prescribed burns measured with an In-Plume monitoring system. ............................... 2-4
Table 3. Specifications of continuous monitors included in the In-Plume system for measuring
prescribed burning emissions during the LTB field study. .......................................................... 2-6
Table 4. Meteorological conditions in the Lake Tahoe Basin for the fall 2011 and spring/summer
2012 observing periods (data from South Lake Tahoe Airport). ................................................. 3-1
Table 5. Summary of PM2.5 episodes in the 2011 and 2012 observing periods (according to
outliers in Figure 12) and potential causes based on fire and meteorological records. ............... 3-9
Table 6. Time-integrated combustion efficiencies and emission factors of PM2.5, EC, BC, CO,
NOx, and NH3 for CLC, SKY, DSP, and TNC burns. ................................................................. 4-5
Table 7. Chemical composition of PM2.5 (in percentage) for time-integrated filter samples
acquired from the SKY, DSP, and TNC burns. ........................................................................... 4-7
viii
1
1.1
Introduction
Background
The Lake Tahoe Basin (LTB) is situated in the northern Sierra Nevada mountain range of
the western U.S. and straddles the California/Nevada border. Lake Tahoe is designated an
Outstanding National Resource Water under the U.S. Environmental Protection Agency Water
Quality Standards Program and the Clean Water Act (U.S.EPA 1987, 2012). The designation is
reserved for exceptional waters with unique ecological and social significance. With this
designation, Lake Tahoe has been receiving the highest level of protection under the antidegradation policy.
The clarity of Lake Tahoe and its unique blue color is attributed to a granitic lake bed
with extremely low levels of nutrient content, vegetative growth, and suspended particulate
matter (PM). However, water clarity has been declining since the 1960s. This is mainly due to
the input of fine PM and algal growth stimulated by nutrient loading from runoff and
atmospheric deposition (Jassby et al., 1994). The Truckee River provides the only outlet with
limited flushing, resulting in long residence times in the lake. With regard to particles, it can be
assumed that depositions of sediments and nutrients remain in the lake indefinitely; either
suspended in the water column or settled on the lake bed (LRWQCB, 2012).
Besides the clear lake water, good air quality and visibility are important assets of the
LTB as a major tourist destination. The annual PM2.5 (airborne fine PM with aerodynamic matter
<2.5 µm) concentrations were 3.5 and 9.0 μg/m3 for 2000-2004 (Green et al., 2011) measured at
Bliss State Park and South Lake Tahoe, representative of rural and urban environments,
respectively, in the basin. These levels are well below the National Ambient Air Quality
Standard (NAAQS) of 12 µg/m3 (U.S.EPA, 2013). Exceedances to the 24-hr PM2.5 NAAQS of
35 µg m-3 and 8-hr California visibility standard of 70 Mm-1 were also seldom reported (Chen et
al., 2011). Major sources of air pollutants, including PM2.5, PM10 (particles with aerosol dynamic
diameter <10 μm), nitrogen oxide (NO), nitrogen dioxide (NO2), carbon monoxide (CO), and
ozone (O3), within the LBT are: 1) biomass burning; 2) on-road engine exhausts; 3) off-road
engine exhausts; 4) road dust; and 5) natural dust (Kuhns et al., 2004; Chen et al., 2011). Air
pollution is of particular concern because the bowl shaped geography and cool lake surface
makes the basin susceptible to meteorological conditions that can trap pollutants near the surface
of lake water (Cliff and Cahill, 2000; Green et al., 2011; Green et al., 2012). On average, longrange transport from outside the LTB does not contribute as much as local sources (Gertler et al.,
2006).
Chen et al. (2011) reviewed the visibility trend at Bliss State Park based on chemical
extinction data from the Interagency Monitoring of PROtected Visual Environments
(IMPROVE) network. Despite an improving visibility condition with respect to annual median
extinction coefficient (bext), the 90th percentile bext, which represents regional visibility on the
haziest days, exhibited zero to slightly increasing trends since 1990. This could mostly be related
to wildfires as the wildfire frequency and intensity have been increasing in the western U.S.
(Westerling et al., 2006). On the other hand, Chen et al. (2011) identified episode days occurring
in spring and winter without any evidences of wildfires. These episodes might reflect the
influence of prescribed burning and/or residential wood combustion (RWC).
1-1
Prescribed burning activities inside and around the LTB have the potential to impact air
quality, visibility, and human exposure to air toxics. It can also impact the water quality through
deposition. The Lahontan Regional Water Quality Control Board estimated that ~15% of particle
loads to Lake Tahoe originated from atmospheric sources (Roberts and Reuter, 2007). The
importance of prescribed burning contributions is increasing as regulations over other sources
such as motor vehicles, RWC, and road dust, have been implemented and shown measurable
effectiveness in the last two decades (Chen et al., 2011).
This study characterizes prescribed burning emissions typical of the LTB and evaluates
the impacts of prescribed burning on ambient PM2.5 concentrations. The study focuses on two
prescribed burning seasons: fall 2011 (September-November) and spring/summer 2012 (MayJuly). The research methods include: 1) in-plume source measurements at field; 2) ambient air
quality (i.e., PM2.5) monitoring; and 3) emission/smoke dispersion modeling. Findings from the
study represent a first step to developing strategies that will maximize benefits of prescribed
burning while minimizing its effects on air and water quality.
1.2
Prescribed Burning in the Lake Tahoe Basin (LTB)
The climate of LTB is characterized by seasonal summer dryness followed by 50-80% of
annual
precipitation
falling
between
October
and
March
(http://www.wrcc.dri.edu/climatedata/comparative/). Moist winters are favorable for abundant
spring vegetation growth, much of which dry out during the summertime allowing dead fuels to
accumulate rapidly. Rates of organic matter decomposition are slow due to dry summers and
cold winters (Johnson et al., 2009). In addition to natural buildup of fuels, forest fire suppression
over the past century has resulted in a more homogeneous landscape and has increased fuel loads
throughout the Sierra Nevada (Beaty and Taylor, 2008). Several studies have indicated that the
frequency and intensity of wildfires is likely to increase in many regions due to climate change.
Consequently, environmental and ecological impacts from wildfires are likely to increase (Taylor
and Beaty, 2005; Westerling et al., 2006; Jaffe and Wigder, 2012). Moreover, changes in forest
characteristics have increased fire hazards putting property, public safety, and natural resources
at risk.
Forest conditions during the Euro-American settlement and prior to the extensive
Comstock logging era (ca. 1860–1920) have long been used by ecologists and managers as a
reference to characterize the variability in ecological processes and structures at a time when
ecosystems were less affected by humans (Taylor et al., 2012). Forests in the LTB have been
dramatically altered by land use practices; thus, reference conditions are used as a guide to
identify restoration goals and treatments in places where contemporary forest conditions are
outside of their historic ranges. The desired basin forest condition is conceived as being similar
to those in the pre-Comstock period. During the Comstock era, forests in the LTB were nearly
clear-cut to meet demand for wood in the silver mines in Virginia City, Nevada (Strong, 1984).
The second growth forests along with fire suppression have resulted in an increased presence of
high-density, small diameter trees that are more susceptible to catastrophic wildfires. Today, the
LTB forests are experiencing mortality due to drought, lack of natural fire, high tree density, and
beetle infestation, further increasing the risk of wildfire (Schwilk et al., 2006; Fule et al., 2012).
Pre-settlement fire ecology reconstructed from tree rings studies show that frequent fires
1-2
shaped the LTB forest. Modeled reference conditions of forest characteristics show that the
lower montane forests burned at relatively low intensity with a mean fire return interval of 13-20
years while upper montane forests burned every 80-95 years (Taylor et al., 2012). Knowledge of
reference conditions is used to determine ecological implications of implementing fuel
treatments on an appropriate landscape scale. For example, more intensive treatments may be
appropriate on landscapes that historically burned at higher severity.
Mechanical and hand-thinning activities were introduced in the 1980s in order to reduce
fire hazards and create stands structurally similar to inferred pre-settlement conditions
(McKelvey et al., 1996; Raumann and Cablk, 2008). Thinning activities focused on the removal
of dead or dying trees. The resulting slash was disposed of through commercial sales of wood,
chipping and removal, or burning of slash-piles and understory growth. Forest fuel treatments
can be expensive depending on the removal method, the amount of material, and the terrain and
location. Mechanical treatments are generally expensive, therefore prescribed burning is often
the preferred method to reduce surface and ladder fuels. Research has shown that low intensity
fires can improve forest health by mimicking the natural role of fire (Certini, 2005). Benefits of
prescribed burning include the reduction of dead and downed material, recycling of forest
nutrients, minimizing insect epidemics and spread of disease in crowded stands, and protection
of lives and property from catastrophic fire.
In recent years, the activities of thinning and prescribed burning have been used
extensively throughout the LTB in an effort to return Sierra Nevada forests to a more sustainable,
fire-resilient condition. Due to the air quality restrictions, most prescribed burns follow a Burn
Plan with a short ignition window during which efficient smoke dispersal is forecasted. Basin
land management/fire protection agencies (Figure 1) develop a multi-year Burn Plan that follows
a NWCG (National Wildfire Coordinating Group) standardized format, including parameters for
fire behavior, environmental conditions (i.e. weather), required notifications, smoke
management, etc. Prior to burning, the managing agency must obtain a burn variance from the
local air district. The LTB has four permitting air districts: Washoe County and the Nevada
Division of Environmental Protection (NDEP) on the east side of the basin, and Placer and
Eldorado Counties on the west side.
Before conducting a prescribed burn, crews from a fire district must: 1) register the burn
with the corresponding air district(s); 2) obtain an air district and/or fire agency burn permit; 3)
submit a smoke management plan (SMP); and 4) obtain air district approval of the SMP. The
SMP specifies the “smoke prescription,” which is a set of air quality, meteorological, and fuel
conditions needed before burn ignition may be allowed. Depending on the size and complexity
of the burn, the SMP will contain some or all of the following information:
1. Burner name and contact information;
2. Burn method/fuel type (e.g., pile or understory);
3. Nearby population center(s);
4. Planned burn time;
5. Acceptable burn ignition conditions;
6. Contingency planning;
7. Burn monitoring procedures;
1-3
8. Location and size of the burn;
9. Expected air emissions;
10. Smoke travel projections;
11. Duration of the burn;
12. Smoke minimization techniques;
13. Description of alternatives to burning;
14. Public notification procedures;
Figure 1. Land management/fire protection agencies and their boundaries in the Lake Tahoe Basin
(LTBMU, 2007).
Two types of burn methods (i.e., pile or understory) need to be specified :

Pile Burning: Cut material piled either by hand or mechanical, resulting from logging or
fuel management activities are burned during the wetter months (i.e., winter and spring)
to reduce damage to residual stand and to confine fire to the size of the pile. Piling allows
for the material to cure and dry, producing less smoke and rapid consumption when
burned.

Understory burning/Underburning: A fire that consumes surface fuels but not the
overstory vegetation is used after initial thinning treatment or a maintenance burn, to
maintain the desired fuel loading conditions.
For the safety of nearby residential areas, slash pile burning is usually the preferred method
following thinning treatments in overly dense stands. This would prevent the intense underburn
that causes unacceptable levels of tree scorch and mortality. Depending on location of the burn,
notification must be given to the permitting agency the day before. On the day of the burn, the
burn coordinator (i.e., burn boss) relies on National Weather Service (NWS) spot weather
forecasts, on-site weather data, and personal judgment with local conditions to determine if there
1-4
would be an ignition.
Approximately 58,200–65,560 acres of forestlands in the LTB is classified as having a
moderate to high wildfire susceptibility (Figure 2[a]). The basin-wide Burn Plan guides when
and where treatments should take place (Figure 2[b]). Over 14,000 acres of fuels reduction
treatments (thinning and prescribed burning) have been completed since 2000, with an average
annual treatment of 1,856 acres in 2005–2006 (Holl, 2007). Approximately 4,900 acres would be
burned annually if all initial and maintenance treatments were completed as scheduled (Holl,
2007). However, information from the fire protection agencies identified 70 burns of ~1000
acres in 2011 (May to December) and 79 burns of ~800 acres in 2012 (see Appendixes A and B)
that corresponded to this study period. Slash pile burning was the most common method of
treatment, accounting for ~80% of the burn acreages.
(a)
(b)
Figure 2. Maps of (a) wildfire susceptibility and (b) planned fuels reduction schedule (2007–2016) for the
Lake Tahoe Basin. Adapted from LTBMU (2007).
1.3
Understanding Prescribed Burning Emissions and Impacts: A Research Framework
Plant biomass mainly consists of cellulose, hemicellulose, and lignin with carbon (C) and
oxygen (O) accounting for ~90% of the mass with the rest being hydrogen (H) and nitrogen (N).
Oxidation and pyrolysis of these materials occur during biomass burning processes. Typically a
high-temperature flaming front passes rapidly through a fuel bed followed by sustained lowtemperature smoldering combustion. Flaming combustion leads to nearly complete oxidation,
1-5
converting C and N to carbon dioxide (CO2) and reactive nitrogen oxides (NOx: NO + NO2),
respectively, while smoldering smoke contains higher fractions of partially reduced compounds
such as CO, ammonia (NH3), volatile organic compounds (VOCs), and PM2.5/PM10 (Crutzen and
Andreae, 1990). The fraction of C emission in the form of CO2 is defined as combustion
efficiency (CE). In general, CE = 0.9 is a lower threshold for flaming combustion (Sinha et al.,
2004; Chen et al., 2007; McMeeking et al., 2009). Fuel consumption by flaming versus
smoldering depends on fuel type, loading, moisture content, arrangement of fuel layers (e.g., pile
versus understory) as well as environmental conditions such as wind speed (WS) and relative
humidity (RH) (Ottmar, 2014).
Biomass burning emissions in a burn plot can be calculated from:
  
(1)
(Seiler and Crutzen, 1980) where Ei represents the total emission of pollutant i in kg or ton; A is
the burn area (ha or acre); B is the fuel loading (kg/ha or ton/acre); C is the fraction of fuel
consumed during the fire; and EFi is the emission factor of pollutant i from the combustion (g/kg
or lb/ton). EFi quantifies the mass of a pollutant released per mass of dry fuel consumed
(Andreae and Merlet, 2001; Chen et al., 2007). Time integrated emissions are usually adequate
for developing an emission inventory, while air quality assessments need high time-resolution
(e.g., hourly) Ei as source inputs into dispersion or air quality models.
The Fire Emission Production Simulator (FEPS), developed by the U.S. Forest Service
(Anderson et al., 2004), is an integrated platform for modeling wild- or prescribed fire emissions.
FEPS contains default values for fuel loading and fraction of fuel consumed specific to most
vegetation type/moisture content combinations in the U.S. Based on the information and user
supplied hourly burned area and meteorological conditions (i.e., WS at flame height [ufh] and
RH), FEPS calculates fuel consumption by flaming (FLA), short-term smoldering (STS), and
long-term smoldering (LTS) phases. Each vegetation type is characterized by the above-ground
(e.g., canopy, shrub, grass, woody, litter, and piles) and below-ground (duff) fuel loads, with
their hourly consumptions estimated separately. Canopy is assumed to burn only during severe
wildfires. Dynamic emission factors, modulated by combustion efficiency (i.e., based on the
hourly fuel consumption of FLA, STS, and LTS), are used to determine the hourly emission
rates. Outputs from FEPS include hourly heat release (kJ/hr) from the fire, which is useful for
calculating the plume height (Briggs, 1969; Harrison and Hardy, 1992). Plume height is a critical
input for dispersion models to advect the plume downstream and predict downwind pollutants
concentrations.
In this study, FEPS served as the core tool for evaluating prescribed burning emissions
and impacts on air quality in LTB due to its comprehensiveness and flexibility. FEPS provides
emission estimates to the best of knowledge while all the default assumptions can be adjusted if
better values and/or field measurements become available.
A research framework centered around FEPS is demonstrated in Figure 3. Ground data
from the fire protection agencies and satellite data such as SmartFire Fire Information System
(http://www.airfire.org/smartfire/ and see Raffuse et al., 2009) provide basic burn information
for FEPS including burn location, burn size, start and end time, and in some cases fuel moisture
content, loading, and local meteorological conditions. Satellite data covers most of burn types
1-6
that exceed 100 acres in- and outside the LTB. While satellite data does not usually detect
prescribed burns, it helps to screen impacts of nearby wildfires from prescribed burns. The Fuel
Characteristic Classification System (FCCS, Ottmar et al., 2007; Prichard et al., 2013) provides
vegetation type at 1 km  1 km resolution over the continental U.S. and estimates of fuel loading
separated into canopy (above ground), shrub, grass, woody, litter, and duff. This information can
be readily used for FEPS modeling of underburns if local estimates (e.g., from fire agencies) are
not available. Canopy fuels are assumed not to be consumed by prescribed burning. For pile
burns, additional information of pile fuel loads would be needed. FEPS considers ufh and RH in
the calculation of fuel consumption by STS and LTS phases. Weather models (e.g., Weather
Research Forecasting [WRF]) provide these parameters since they are not usually documented in
the fire protection agencies’ reports.
Figure 3. A research framework for evaluating prescribed burning emissions and impact in the Lake
Tahoe Basin. It shows the relevancy of the three main tasks in this study: source measurement, ambient
monitoring, and fire emission/dispersion modeling.
FEPS calculates combustion efficiencies and PM2.5 emission factors (EFPM2.5) based on
fuel consumption by FLA, STS, and LTS phases. EFPM2.5 in the model was derived from limited
laboratory studies and may not be applied to real-world fires. Measurements in the smoke
plumes (i.e., in-plume source measurement in Figure 3) directly quantify combustion efficiencies
and emission factors and examine their relationships throughout a burn. This evaluates the
current model setups and allows improvements to be made. In addition, in-plume measurements
provide opportunities to determine emissions of gaseous pollutants such as CO and NOx and
chemical source profiles of PM2.5 from prescribed burns. The source profiles can then be used in
chemical mass balance (CMB) receptor modeling for source apportionment of ambient PM2.5
(e.g., Green et al., 2012; Chen et al., 2012).
Field in-plume measurements are often limited by the accessibility of prescribed burns in
1-7
the LTB. Decision on a fire ignition would not be made until the day before and could be
canceled anytime due to fast-changing weather conditions, which limits the time for preparing
and transporting the In-Plume system. In addition, many of the LTB burns are not accessible by
vehicles or even outdoor carts due to the steep terrain. Experiments with laboratory combustion
chambers can complement field measurements if they simulate prescribed burning reasonably
with respect to atmospheric dilution, fuel type, moisture content, and combustion temperature
(Yokelson et al., 2013).
The hourly PM2.5 emission from FEPS, along with heat release, serves as point source
inputs for the NOAA Air Resource Laboratory (ARL) HYSPLIT – Hybrid Single Particle
Lagrangian Integrated Trajectory model (Draxler and Hess, 1997; Draxler, 1999) to calculate
plume rise and smoke dispersion. The HYSPLIT model is developed and maintained by the
NOAA Air Resource Laboratory (ARL) (Draxler and Hess, 1998; Draxler, 1999; Draxler and
Rolph, 2013). The steep terrain around the basin and interaction with the lake surface can lead to
complex atmospheric circulations influencing plume transport. Therefore, to improve the model
precision, 2 km x 2 km resolution meteorological forecasts generated by the WRF model was
acquired, converted to the ARL format, and used in HYSPLIT calculations.
HYSPLIT output is a 3-dimensional distribution of PM2.5 concentrations as a function of
time following the ignition of burn plot(s). The impact of burn on ambient PM2.5 level at a
specific receptor site/location can then be determined through interpolation. Ambient monitoring
at 1-hr resolution or better would allow evaluation of the model output and provide feedback to
the model assumptions. The hourly PM2.5 and integrated weekly filter samples with chemical
speciation at background or community exposure sites characterize PM2.5 episodes based on
spatiotemporal variation and chemical composition. When compared with prescribed burn
records and HYSPLIT simulation, it provides a synergetic impact assessment for prescribed
burning in the LTB (Figure 3).
1.4
Guide to the Report
This report contains six chapters. Chapter 1 provides background information regarding
prescribed burning in the LTB and formulates a research framework for evaluating the
prescribed burning emissions and impacts on air quality. Chapter 2 describes measurement and
modeling approaches. Chapter 3 summarizes the ambient monitoring data for characterizing sitespecific diurnal pattern and identifying PM2.5 episodes related to prescribed burning. Chapter 4
summarizes the in-plume measurement data for distribution of combustion efficiencies and
emission factors as well as PM2.5 chemical composition. Chapter 5 investigates the smoke
transport of individual burns using dispersion modeling and ambient measurements. Chapter 6
synthesizes conclusions and recommendations to future studies. References and Appendixes A to
C following Chapter 6 provide additional information relevant to the project.
1-8
2
2.1
Technical Approaches
Ambient Monitoring Network
Ambient PM2.5 monitoring was conducted in the LTB from July through November 2011
and from May through November 2012, covering both the fall (2011, 2012) and spring (2012)
prescribed burning seasons. Five monitoring sites were established around the perimeter of Lake
Tahoe at Incline Village, Tahoe City, Bliss State Park, South Lake Tahoe, and Cave Rock
(Figure 4). The Incline Village (NV), Tahoe City (CA), and South Lake Tahoe (CA) sites were
located near the center of the respective township representing community exposure to air
pollutants. The Bliss State Park site is 206 m above Lake Tahoe and has been part of the
IMPROVE network since 1990. It represents the Desolation and Mokelumne Wilderness Class I
areas according to the Clean Air Visibility Rule (CAVR, see U.S.EPA, 2005). Cave Rock is a
pier located on the east shore of Lake Tahoe. The site is considered rural but could be influenced
by emissions from boats and US-50 traffic (~50 m above the site).
Figure 4. Locations of ambient PM2.5 monitoring sites (blue balloons) in the Lake Tahoe Basin (LTB)
during 2011-2012 study periods: 1) Incline Village; 2) Tahoe City; 3) Bliss State Park; 4) South Lake
Tahoe; and 5) Cave Rock. Also shown are the locations of four prescribed burns (stars ☆) measured by
the In-Plume system: Skyland (SKY), Donner Memorial State Park (DSP), Tunnel Creek (TNC), and
Cold Creek (CLC). Solid circles indicate 60 recorded prescribed burns carried out by Lake Tahoe Basin
Management Unit (red), California State Park (pink), Nevada Division of Forestry (green), and North
Lake Tahoe Fire Protection Department (yellow) throughout fall (September-November), 2011.
In 2011, each site was equipped with a DustTrak 8520 (TSI, Shoreview, MN), a portable
laser photometer measuring particle light scattering at 1-minute time resolution with built-in data
logging. The DustTraks were equipped with a 2.5-µm particle impactor, and PM2.5
concentrations were inferred from light scattering according to factory-set calibration factors. In
2012, the DustTrak 8520 was replaced with DustTrak DRX (Wang et al., 2009). Through an
2-1
optical sizing technique, the DustTrak DRX reports five particle size fractions: PM1, PM2.5, PM4,
PM10, and PM15 simultaneously. All sites except the Bliss State Park also contained two
collocated MiniVol samplers (AirMetrics, Eugene, Oregon) equipped with PM2.5 size-selective
inlet sampling air through a filter cartridge at a flow rate of 5 L/min. One MiniVol used a 47-mm
Teflon-membrane filter for gravimetric mass and elemental composition measurement. The other
used a 47-mm quartz-fiber filter followed by citric acid-impregnated cellulose-fiber filter for
quantification of water-soluble ions as well as organic carbon (OC), elemental carbon (EC), and
gaseous NH3 concentrations. Figure 5 shows the sampling configuration and analytical methods.
PM2.5 Impactor
PM2.5 Impactor
5 L/min
5 L/min
Teflon-membrane
Filter
Quartz-fiber Filter
Ions (Cl-, NO3-, SO4=, Na+,
Mg++, K+, Ca++ by IC and
NH4+ by AC)
OC, EC, and carbon
fractions by TOR
mass by gravimetry
elemets (Na-U) by XRF
Citric acidimpregnated filter
NH3 as NH4+ by AC
Figure 5. MiniVol sampling configuration, species measured, and analytical methods (Chow, 1995). XRF:
X-ray fluorescence; IC: Ion Chromatography; AC: Automated Colorimetry; TOR: Thermal/Optical
Reflectance by the IMPROVE_A protocol (Chow et al., 2007).
An additional set of MiniVols were deployed on the rooftop of the Tahoe Regional
Planning Agency (TRPA) building at Stateline, CA. The site was within 3 km and generally
downwind of the South Lake Tahoe site. Integrated weekly (Wednesday to Wednesday) PM2.5
samples were acquired. Occasional power-off and/or instrument malfunction caused shorter
sampling time or loss of filter data. MiniVol sampling was not carried out at the Bliss State Park
since 24-hr filter samples have been collected every 3rd day and analyzed as part of the
IMPROVE program (Green et al., 2012). The analytical methods adapted for this study are
compatible with those used in IMPROVE. Table 1 summarizes the ambient monitoring network.
2-2
Table 1. Summary of ambient monitoring network established for the 2011-2012 prescribed burning
impact assessment.
Site
(Lat/Lon/Alt)
Sampling Period
2011/2012a
# of Valid Filter
Samplesb
2011/2012
Incline Village
(39o 15’ 1.49”N,
119o 57’ 24.19”W,
58 m ALLc)
7/25/11 – 11/22/11
5/9/12 – 11/21/12
12
23
Tahoe City
(39o 9’ 57.63”N,
120o 8’ 55.74”W,
12 m ALLc)
7/11/11 – 11/22/11
5/9/12 – 11/21/12
10
22
Bliss State Park
(38o 58’ 33.63”N,
120o 6’ 8.73”W,
206 m ALLc)
8/25/11 – 11/18/11
5/9/12 – 11/21/12
N/A
N/A
South Lake Tahoe
(38o 56’ 42.26”N, 7/11/11 – 11/14/11
119o 58’ 13.99”W, 5/9/12 – 11/21/12
5 m ALLc)
Cave Rock
(39o 2’ 37.12”N,
119o 56’ 54.83”W,
1 m ALLc)
Stateline
(38o 57’ 58.53”N,
119o 55’ 51.30”W,
64 m ALLc)
Remarksc
DustTrak/MiniVols were situated on the rooftop of the
Forest Service office. The inlet was ~9 m above the
ground (ABL) with ponderosa pine trees surrounding the
site. Washoe County has established an ozone (O3)
monitor at the site.
Located ~100 m from Highway 89, on top of a shed 7 m
ABL. Sources affecting the site included cars and trucks
entering/leaving the parking lot. Placer County Air
Quality District has monitored O3 and PM10/PM2.5 (by
BAMsd) since November 2010.
The DustTrak was located next to IMPROVE samplers
which have been acquiring 24-hr chemically-speciated
PM2.5 measurements and PM10 mass on every 3rd day
since 1999.
DustTrak/MiniVols were situated on the rooftop of the A
to Z Insurance building with the inlet ~10 m ABL. This
urban site is operated by CARBe, which maintains
measurements of PM10 by BAM and meteorological
parameters.
15
27
10/7/11 – 11/22/11
5/9/12 – 11/21/12
0
12
DustTrak/MiniVols were placed on the rooftop of the
public restroom. The site is ~40 m to the west of
Highway 50 and sits ~18 m below the road.
9/8/11 – 11/22/11
5/9/12 – 11/21/12
4
24
MiniVols were situated on the rooftop of the TRPA
building. The site is generally downwind of South Lake
Tahoe, CA. TRPA also monitors O3, NOx, PM10, and
meteorology during the study period.
Total
41a
108a
Footnotes:
a
PM2.5 mass were quantified for filter samples acquired in both 2011 and 2012, but only the 2011 samples were fully
speciated due to budget constraint.
b
Each sample is a Teflon-membrane/quartz-fiber/cellulose-fiber filter pair.
c
ALL: Above lake level.
d
Beta Attenuation Monitor
e
California Air Resources Board
As part of QA/QC, DustTraks were zeroed and flow checked every week and particle
impactors were cleaned and greased every two weeks. The consistency of all DustTrak
measurements, including PM2.5 by DustTrak 8520 and DustTrak DRX, were established in the
laboratory with nebulized ammonium sulfate ([NH4]2SO4) particles every 6 months. PM2.5 mass
measured on Teflon-membrane filters were used to further calibrate the DustTrak data.
Instruments at Tahoe City were run with two co-located Beta Attenuation Mass monitors
(BAMs, Met One Instrument, Grants Pass, OR) for PM2.5 and PM10. The BAM is a federal
equivalent method (FEM) for continuous (1-hr resolution) PM2.5 or PM10 measurement (Chow et
al., 2006b). Placer County provided QA/QC for the BAMs at Tahoe City. Another BAM that
2-3
monitored PM10 concentration was located at the South Lake Tahoe site and maintained by
California Air Resources Board (CARB).
2.2
In-Plume Source Measurement
Source measurements were conducted for four prescribed burns in or around LTB using a
mobile In-Plume monitoring system. Three of the prescribed burns (SKY, TNC, and CLC)
located on the northeastern-southeastern side of the LTB, and the other burn (DSP) located
outside of the basin near Truckee, CA (see Figure 4). Details of the burn plot are shown in Table
2. According to FCCS (1-km resolution Map of the Conterminous U.S. with MODIS Enhanced
Canopy Fuels, downloaded from http://www.fs.fed.us/pnw/fera/fccs/maps.shtml), the SKY and
CLC burn sites are classified as “Ponderosa pine/Jeffery pine forest - mature conifer forest of the
Sierra Nevada (Code 37)”, while DSP is classified as “Douglas fir/sugar pine/tanoak forest mixed forest common in northern Sierra Nevada and coastal Pacific Northwest (Code 7)” and
TNC is classified as “Red fir forest: Pure stands of red fir widespread in the central and southern
Sierra Nevada (Code 17)”. The FCCS coding was confirmed by the visual observations. With the
code, the understory fuel loading was estimated, to which piled fuel loading, if applicable, was
added to determine the total fuel load in Table 2.
Table 2. Prescribed burns measured with an In-Plume monitoring system.
Burn Type Burn Area Fuel Moisture Ignition Start
Burn
Fuel Loadc
b
(acres)
Time (PST) Duration (tons/acre)
(hours)
Understory
39o01’02”N
SKY
6/11/2011
27
10 (pile)–100%
1000
3
28
119o57’00”W
/Piles
o
39 18’29”N
DSP
10/03/2011 Understory
9
70–100%
1000
5
35.6
120o14’43”W
39o13’45”N
TNC
10/20/2011 Understory
7
90–100%
1100
4
16.7
119o53’20”W
38o53’56”N
CLC
6/24/2013
Pile
10
30–50%
1000
3
30
119o57’22”W
Footnotes:
a
SKY, TNC, and CLC were burns conducted within the basin and DSP was located outside the basin (Figure 4).
SKY and CLC are considered as spring burns while DSP and TNC are considered as fall burns according to the time
they occurred.
b
Duration of active ignition determined by fire agencies. Fire continues after ignition.
c
Estimated from agencies’ report and Fuel Characteristic Classification System (FCCS); canopy and duff excluded.
Burn plots and fuel load breakdowns are shown in Appendix C.
Burn
IDa
Burn
Location
Date
Understory burning consumed surface fuels but not the overstory vegetation (i.e.,
canopy). Burn crews typically started the fire at one side of the burn plot and progressed steadily
toward the other. Pile burning generally consumed only the materials piled either by hand or
mechanical thinning. In both cases, agencies followed a SMP and precautions were taken to
prevent fire escapes and/or ignition of canopy fuels throughout the burn. Chunking the piles, i.e.,
moving unburned materials from the outside perimeter into the center of the still burning piles,
was not applied to the burns studied.
The In-Plume system (Figure 6) consists of high-rise sampling inlets (3–5 m), and a suite
of real-time instruments capable of characterizing gases and particles in smoke plumes (Wang et
2-4
al., 2012). Continuously monitored species/parameters include CO2 by non-dispersive infrared
sensor (SBA-4, PP Systems, Amesbury, MA); CO, NO, and NO2 by electrochemical detector
(Model 350S, Testo Inc., Sparta, NJ); sulfur dioxide (SO2); UV-ionizable compounds
(isobutylene equivalent) by photoionization detector (Model 102+, PID Analyzers LLC,
Pembroke, MA); size-segregated PM mass by DustTrak DRX, and black carbon (BC) by microaethalometer (AE51, Magee Scientific, Berkeley, CA). To improve the sensitivity of NO, NO2,
and NOx measurements, a trace level reactive nitrogen oxides analyzer based on the
chemiluminescence principle (Model 400 and 401, 2B Technologies, Inc.) was added to the
system. Table 3 summarizes the instrumentation, measurement range, precision, and data rate.
Prescribed
Burning
Sampling
Inlet
19.51 L/min
Teflon
Filter
Filter
sampler
Flow
meter
TSI DustTrak DRX
(PM1, PM2.5, PM4,
PM10, PM15)
Pump
NO/NO2
Valve
Testo 350
(CO, CO2, NO, NO2,
SO2, O2,T, P)
Pump
2B 400/401
(NO/O2)
2B 205
(O3)
PID 102+
(VOC)
1.2 L/min
0.05 L/min
3 L/min
5 L/min
5 L/min
1 L/min
0.16 L/min
0.5 L/min
1.8 L/min
1.0 L/min
PM2.5
impactor
0.7 L/min
14.95 L/min
4.56 L/min
Grimm 1.108 OPC
(Size distribution
0.3-25 µm)
Magee AE51
(BC)
Teflon
Quartz + Citric acid
TSI CPC 3007
(Concentration 0.01-1 µm)
Batteries
PP Sys
(CO2)
Figure 6. Configuration of the In-Plume sampling system as deployed for prescribed burning measurements (adapted from Wang et al., [2012]).
Commercial 12V deep-cycle marine batteries were used to power the entire system,
which consisted of three heavy-duty storage boxes loaded on a pickup truck for transportation
before, during and after a burn experiment. Data from the real-time instruments were sent to a
data acquisition/archive computer in digital format via RS232 or USB communication ports. A
LabView (National Instruments, Austin, TX) program controls the instruments and displays data
for on-site inspection (Watson et al., 2012).
2-5
Table 3. Specifications of continuous monitors included in the In-Plume system for measuring prescribed
burning emissions during the LTB field study.
Monitoring System
CO2 analyzers;
Model SBA-4 (PP Systems,
Amesbury, MA)
Observables
CO2
Measurement
Range
0–100,000
0–50,000
0–5,000 ppm
Data Rate
1.5 sec
1 sec
1 sec
+/- 1% of reading
1 sec
±20%
1 sec
±0.100 μg BC/m3 for 1 min avg.,
at 150 cm3/min flow rate
1 sec
±20% (for calibration aerosol)
6 sec
±2.5%
0-2000 ppbv
1 sec
±3%
1-250 ppm
2 sec
±2%
0–500 ppm
CO2
0–50% vol.
NO
0–3,000 ppm
NO2
0–500 ppm
SO2
0–5,000 ppm
O2
0–25% vol.
Total
UV-ionizable
Photoionization
compounds
detector;
0.1–3000 ppm
(isobutylene
Model 102+ (PID Analyzers
LLC, Pembroke, MA)
equivalent)
Condensation Particle
Size: >10 nm
PM number
Counter;
Number: 0–100,000
concentration
Model 3007 ( TSI Inc.,
/cm3
Shoreview, MN)
Micro-aethalometer;
Model AE51 (Magee
Scientific, Berkeley, CA)
Black carbon (BC)
concentration
CO2: <1% of span concentration
CO: < 2 ppm (0–39.9 ppm)
< 5% of measured value (mv;
≥40 ppm)
CO2: ±0.3% vol.+1% of mv (0–25%
vol.)
±0.5% vol. +1.5% of mv (>
25% vol.)
NO: < 2 ppm (0–39.9 ppm)
< 5% of mv (40–300 ppm)
NO2: < 5 ppm (0–99 ppm)
< 5% of mv (>99 ppm)
SO2: < 5 ppm (0–99 ppm)
< 5% of mv (100–2,000 ppm)
< 10% of mv (2,001–5,000 ppm)
O2: <0.2% of mv
CO
Emission Analyzer;
Model 350 S (Testo Inc.,
Sparta, NJ)
Nominal Precision/Accuracy
0–1 mg BC/m3 for
15-min avg. at 50
cm3/min flow rate
PM mass
Size: ~ 0.1–15 µm
concentration (PM1,
Mass: 0.001–150
Model 8534 (TSI Inc.,
PM2.5, PM4, PM10,
Shoreview, MN)
mg/m3
and PM15)
Size: 0.3–25 µm in
Optical Particle
15 channels
Counter;
Particle size
Number: 0.001–
Model 1.108 (Grimm
distribution
2,000/cm3
Aerosol Technik GmbH &
Mass: 0.0001–100
Co., KG, Ainring, Germany)
mg/m3
DustTrak DRX;
NO/NO2/NOx analyzer;
Model 400 &401 (2B Tech.,
Boulder, CO)
NO/NO2/NOx
Ozone analyzer;
Model 205 (2B Tech.,
Boulder, CO)
O3
2-6
The In-Plume system contains four channels for integrated filter sampling. Two channels
were used during the field measurements with filter configurations identical to those of ambient
MiniVol sampling (Figure 5). The sampling duration was typically 1–2 hours and 3–4 samples
were acquired for each burn event. These samples were refrigerated (<4°C) before submitting to
laboratory for analysis of PM2.5 mass, elements, water-soluble ions, ammonia, and OC and EC
concentrations following the same protocol for analyzing ambient samples.
The in-plume system was generally located downwind just a few meters outside of the
fire perimeter. It might be moved to better capture the smoke if the prevailing wind direction
changed during sampling, as in the case of the SKY burn. In the cases (SKY, DSP, and CLC)
where the fire perimeter was accessible by vehicle, the In-Plume system stayed on the truck
throughout the burn (Figure 7[a]). For the TNC burn, parts of the system were carried to the fire
perimeter separately and then assembled for sampling (Figure 7[b]). Due to quickly varying local
wind directions, the In-Plume system was not always in the plume, resulting in some pollutant
concentrations of nearly background levels. These data were excluded from analysis of smoke
properties.
(b)
(a)
Figure 7. In-Plume measurements of prescribed burning smoke for (a) DSP and (b) TNC burn with
different accessibility.
The fuel-based emission factors (EFs) were calculated following Nelson (1982), Andreae
and Merlet (2001), and Chen et al. (2007):




(2)
where :
•
•
EFi: emission factor of pollutant i (e.g., g/kg)
i:
concentration of pollutant measured above background levels (e.g., µg/m3)
2-7
•
CMFfuel: carbon mass fraction of dry fuel
•
CMFi: carbon mass fraction of species i, including CO2, CO, VOCs, and PM2.5.
The combustion efficiency (CE), defined as the fraction of carbon in the fuels ending up in CO2,
would be calculated by:





(3)
while the modified combustion efficiency (MCE) that ignores VOCs and PM terms is used more
commonly in the literature, thus:



(4)
where xco2 and xco is the mixing ratio of CO2 and CO, respectively, in the plume.
VOCs were subject to a higher measurement uncertainty than CO2, CO, and PM. Since
the contribution of VOCs to carbon is generally minor, the VOCs term in Eqs. (2) and (3) was
ignored. Chen et al. (2010) suggested that CMFfuel of 0.49 is reasonable for a mixture of forest
fuels in the LTB, and filter analysis (see Chapter 3) showed an average CMFPM of 0.58.
Background concentrations were determined before the burn and subtracted from the in-plume
measurements. Except for CO2, background levels were negligible compared with the levels in
the plume. EFi, CE, and MCE can be calculated for each minute (i.e., 1-min average) during a
burn as well as the filter integrating periods.
The carbon-balance theory assumes a well-mixed plume so that measurements made at
one point is representative of the whole plume with respect to smoke chemical composition
(Nussbaum et al., 2009). As observed in the field, real-world prescribed burns deviate from the
assumption owing to variable burn phases across the burn plot, e.g., a part of the plot is in
flaming phase while the others in smoldering phase. Nonetheless, these measurements evaluate
the range of emission factors and combustion efficiencies that can be compared with laboratory
results and default emission model parameters.
2.3
Laboratory Combustion Experiment
In addition to the field In-Plume measurements, emissions from combustion of the LTB
piled fuels were examined in the laboratory. Experiments used DRI’s 8-m3 combustion chamber
equipped with both online and time-integrated measurements (Figure 8). Instrument intake ports
were located approximately 20 cm from the top of the chamber in the exhaust duct. Exhaust fan
speeds in the vent duct was adjusted to provide 1 m3/min of dilution air into the chamber. At this
dilution rate, smoke was rapidly cooled to room temperature. Measured parameters generally
coincided with those of the In-Plume system (Table 3).
Fuels tested were collected from pre-burned piles in a plot on the east side of Lake Tahoe.
They mainly consisted of Ponderosa pine branches, needles, and cones naturally dried for a few
months after they were slashed. Each experiment burned 100‒200 grams of fuels. The combustion
efficiencies and fuel-based emission factors were calculated following Eqs. (2)-(4).
2-8
Figure 8. The 8 m3 combustion chamber with a typical sample burn and a schematic of the experimental
configuration with online and time-integrated measurements. The Potential Aerosol Mass (PAM) flow
reactor was not applied in this study.
2.4
Fire Emission and Dispersion Simulation
For a prescribed burn event to be simulated, the burn records, most importantly ignition
time, burn size, and burn duration, were obtained from field observations (for SKY, DSP, TNC,
and CLC) and/or records of fire protection agencies and air districts. These data served as inputs
to the FEPS model to estimate fuel consumption, emission, and heat release by the burn. The
FEPS provides a flexible interface for updating burn parameters including burn type (e.g.,
understory or pile), fuel load, and moisture content when additional information is available.
Since only a limited number of burns were observed in this study, fuel loading was primarily
determined by matching the burn plot with the FCCS map (1 km × 1 km resolution) for the
continental U.S., supplemented by the SMP of fire agencies. The SMPs were especially
important for slash-pile burns. They often, though not always, provided information such as fire
shape (e.g., rate of progress), ignition time, and fuel moisture content.
Based on the fuel information and user supplied hourly burned area, the FEPS calculated
fuel consumption by FLA, STS, and LTS phases. Flaming combustion with high CE produces
relatively complete oxidation converting fuel carbon to CO2, while smoldering smoke contains
higher fractions of partially reduced compounds such as CO, VOCs, and PM (Crutzen and
Andreae, 1990). Dynamic EFs, modulated by CE (i.e., based on the consumption rate [CR] of
FLA, STS, and LTS at each hour), are used to determine the hourly emission rates:
(5)
CRtotal,j = CRFLA,j + CRSTS,j + CRLTS,j



(6)
ERi,j = CRtotal,j × EFi,j = CRtotal,j ×(ai – bi × CEj)
Where:
2-9
(7)
• CRj: fuel consumption rate (e.g., kg/hr) at hour j
• CEj: combustion efficiency at hour j
• kFLA, kSTS, and kLTS: FLA, STS, and LTS combustion efficiency coefficient, respectively
(default kFLA = 0.9, kSTS = 0.76, and kLTS = 0.76).
• ERi,j: emission rate of pollutant i at hour j (e.g., g/hr)
• EFi,j: emission factor of pollutant i at hour j (e.g., g/kg)
• ai, bi: emission factor constant and coefficient for pollutant i (default ai = 67.4 g/kg and
bi = 66.8 g/kg for PM2.5).
Outputs from FEPS also include hourly heat release (kJ/hr) from the fire, which is useful
for calculating the plume height:
Qj = CRtotal,j × CEj × BEj × EEj
(8)
Where:
• Qj: heat release (e.g., kJ/hr) at hour j
• CEj: combustion efficiency at hour j
• BEj: buoyant efficiency at hour j
• EEj: entrainment efficiency at hour j
With the predicted hourly emission file(s) from FEPS, HYSPLIT calculated plume
dispersion and determined 3-D distributions of air pollutants on an hourly basis. Advection and
diffusion calculations are made in a Lagrangian framework and concentrations are calculated on
a fixed grid (Draxler and Hess, 1997). The dispersion of a pollutant can be calculated by
assuming either puff or particle dispersion, while a mixed mode of top-hat horizontal puff and
vertical particle distribution was used in this study. This approach takes advantage of the greater
accuracy of the particle mode in vertical dispersion parameterization. It also expands the number
of puffs to represent pollutant distribution as the spatial coverage of the pollutant increases over
time (Draxler and Hess, 1998). Each prescribed fire was simulated as a point source centered at
the burn area typically of 2 to 100 acres, with hourly PM2.5 emission rates from FEPS. The plume
rise was computed assuming an air parcel’s rise based on the buoyancy terms (Briggs, 1969;
Arya, 1999) using the fire heat release provided by the FEPS. This approach is generally
compatible with the U.S. Forest Service’s BlueSky smoke modeling framework (Larkin et al.,
2009).
The steep mountain terrain around the LTB influences smoke plume transport; therefore,
meteorological data with fine temporal and spatial resolution, is critical for dispersion modeling.
To provide adequate space and time characterization of an air parcel, hourly 2 km x 2 km
resolution meteorological forecasts generated by the WRF model was acquired from the Climate
Ecosystems and Fire Applications (CEFA) group at Desert Research Institute (DRI). Fortran
conversion programs, available at http://ready.arl.noaa.gov/HYSPLIT_data2arl.php, converted
WRF data to the HYSPLIT compatible format. A batch script configured to run in UNIX
2-10
automatically converted hourly forecasts updated every 00Z and 12Z (GMT) for April-December
2011 and May-August 2012.
The WRF (Lu et al., 2012) employed the Lambert Conformal map projection centered at
38N, 121W and consists of three nested grids. The outermost grid (18 km horizontal resolution,
186  186  31 grid cells) covered the western U.S., parts of Mexico/Canada, and the eastern
Pacific. For this study, the innermost grid (2 km horizontal resolution, 487  535  31 grid cells)
covering California and Nevada boundaries was used. Twice daily forecasts were initialized
using the National Centers for Environmental Prediction Eta model 00/12 UTC forecast outputs
(40-km horizontal resolution) at 7AM/PM PST. Forecasted data closest to prescribed fire start
time was used for dispersion modeling.
Even with precise parameterization of emission rates, the forecasted PM2.5 concentrations
are subject to large uncertainties due to insufficient wind field resolution and estimated sub-grid
motion. The model’s performance is sensitive to the low-level wind profile (for boundary layer
trajectories), the vertical mixing coefficients (for air concentrations), and the interaction of the
vertical pollutant distribution. These are related to how well the vertical atmospheric structure
could be reproduced, either in the meteorological fields of the input data driving the calculations,
or in the parameterizations used to estimate pollutant vertical mixing (for more detail about
HYSPLIT model see Draxler and Hess, 1997). Another cause of error in determining plume
transport and impact at a monitoring site is due to ignition times as an estimated start time was
usually given, but the actual start time could vary by a few hours depending on operational
considerations.
Simulations in this study assess whether particles from a prescribed burn are transported
to the monitoring site(s), though the model forecasted PM2.5 concentrations may not be accurate.
In some cases, the prescribed burning impact is evident as a downwind site showing clear
deviation from the normal PM2.5 levels and/or when multiple sites show concurrent pollution
signals. A time series analysis of ambient PM2.5 concentrations is given in Chapter 3. Prescribed
burning records identify episodes possibly caused by prescribed fires for case studies in Chapter
5, where modeled and measured PM2.5 concentrations are compared.
The Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and
Aqua satellites offers another method of detecting fires and their impacts, especially for largescale wildfires. The MODIS fire product is based on thermal signatures (Giglio, 2010).
Whenever the MODIS detects a "hot spot," it flags the signal's location in the data set. Under
near-ideal conditions - nadir (straight-down) view with no clouds in the way, not too much
smoke, relatively cool background terrain for comparison, etc. - the product can detect fires as
small as 50 m2. Under typical circumstances, the algorithm can detect a fire about the size of a
quarter acre, though the size of the fire may not be estimated for burns of <100 acres.
2-11
3
3.1
Summary of Ambient PM2.5 Monitoring
Meteorology and Wildfires
The fall 2011 observing period (September–November 2011) featured above average
temperatures and below average precipitation in western Nevada, leading to presumably dry fuel
conditions. Combined with the abundance of vegetation growth due to an abnormally wet spring
in 2011 and sufficient ignition sources, it led to an active wildfire season (Nevada Climate Office,
2012). Sierra snow fall was below historical norms. No measureable snowfall accumulation was
noted with early October storms at South Lake Tahoe. The first snowfall in the basin was
recorded starting 11/3/2011. Major wildfires within 160 km of Lake Tahoe included the
Yosemite Motor Fire (8/25–9/4/2011) and Buckeye Fire (9/25–27/2011). In November, the Reno
metropolitan area, 40 km northeast of the Tahoe basin, experienced the worst urban wildfire (i.e.,
Caughlin Fire, 11/18– 21/2011) in state history, when a pre-frontal wind event arced power lines
due to broken tree limbs. This sparked a blaze that spread quickly with winds gusting to 80 miles
per hour, scorching more than 2,000 acres and 29 structures in southwest Reno.
Following one of the driest winters in Nevada’s history, RH and precipitation in the
spring-summer 2012 observing period (May–July 2012) were well below average. The extreme
drought in the Sierra Nevada continued into the early summer with above-normal temperatures.
Prescribed burns were held off for the most part. Major wildfires within 200 km of Lake Tahoe
included Topaz Ranch Estate Fire (5/20-23/2012) and Robbers Fire (7/11-20/2012). Several
wildfires occurred later in August–September 2012. Table 4 summarizes the meteorological
conditions of the six observing months.
Table 4. Meteorological conditions in the Lake Tahoe Basin for the fall 2011 and spring/summer 2012
observing periods (data from South Lake Tahoe Airport).
9/2011
10/2011
11/2011
5/2012
6/2012
7/2012
Mean Temp. (°C)
14.9
8.9
3.3
9.3
12.6
16.4
Mean Dew Point Temp. (°C)
3.3
-0.2
-6.8
-2.8
0.0
3.9
Mean Daily Precipitation (mm Rain
or Snow)
0.31
1.10
0.62
0.11
0.39
0.34
Mean Wind (m/s)
1.5
1.9
2.6
1.9
2.4
1.6
1005
1004
1003
1001
1000
1002
Parameters\Month
Mean Pressure (MSL, mbar)
3.2
PM2.5 Concentration, Diurnal Variation, and Episodes
DustTraks reported 1-min averaged PM2.5 concentrations at Tahoe City, Bliss State Park,
South Lake Tahoe, Cave Rock (starting in October 2011), and Incline Village for the fall 2011
observing period. Missing data occurred occasionally due to unstable power supply, which was
later mitigated by the installation of an uninterrupted power system at each site. In addition,
some DustTraks were not available for the Tahoe City and Cave Rock sites during 9/14-28/2011.
Filters provided weekly PM2.5 mass measurements.
Figure 9(a) compares PM2.5 concentrations from the DustTraks with collocated filter data
for respective integrated periods. Despite a good correlation (R2=0.92), DustTraks overestimated
PM2.5 concentrations. A calibration curve was established using quadratic instead of linear
3-1
regression to achieve a better correlation coefficient (Figure 9[a]). The regression constant was
set to zero since all the DustTraks were zeroed frequently using a HEPA filter throughout the
sampling period. Hereafter all discussions for year 2011 are based on DustTrak data corrected
with this calibration curve. The corrected DustTrak PM2.5 at the Bliss State Park agrees well with
independent 24-hr PM2.5 measurements taken independently as part of the IMPROVE network,
i.e., linear regression slope and correlation (R2) of 1.02 and 0.87, respectively (Figure 9[b]). A
non-zero intercept (0.63 µg/m3) may result from IMPROVE samples being subtracted for
organic sampling artifact. The organic sampling artifact was determined from the backup filters
collected at selected IMPROVE sites (Chow et al., 2010), and is most likely overestimated for
Bliss, a relatively clean site. Similar calibration results were found for 2012 (Figure 9[c]-[d]),
though correlations between DustTrak DRX and filter PM2.5 are slightly lower, likely due to
seasonal variation over a longer monitoring period.
10
y = 0.06x2 + 1.32x
R²= 0.92
25
Corrected DustTrak PM2.5 (µg/m3)
Uncorrected DustTrak PM2.5 (µg/m3)
30
20
15
10
2011
5
0
y = 1.02x + 0.63
R²= 0.87
8
6
4
2011
2
0
0
5
10
MiniVol Time Integrated PM2.5 (µg/m3)
15
0
(a)
10
(b)
30
10
Corrected DustTrak DRX PM2.5 (µg/m3)
Uncorrected DustTrak DRX PM2.5 (µg/m3)
2
4
6
8
IMPROVE PM2.5 at Bliss (µg/m3)
y = 0.03x2 + 1.56x
R²= 0.85
25
20
15
10
2012
5
0
0
5
10
MiniVol Time Integrated PM2.5 (µg/m3)
y = 0.92x + 0.10
R²= 0.81
8
6
4
2012
2
0
0
15
(c)
2
4
6
8
IMPROVE PM2.5 at Bliss (µg/m3)
10
(d)
Figure 9. Comparison of original and corrected DustTrak data with collocated (a, c) MiniVol and (b, d)
IMPROVE PM2.5 measurements. Only DustTrak data that covers >75% of the integrated sampling
periods were included. The corrections in (b)/(d) are based on regression curves from (a)/(c). See Table 1
for the sampling periods in 2011 and 2012. Incline Village data from 2012 were excluded.
3-2
PM2.5 (µg m-3)
Time series of 24-hr average DustTrak data for 2011 are shown in Figure 10, along with
MiniVol and IMPROVE PM2.5 (at Bliss only) concentrations. Large day-to-day variability often
occurred within the weeklong MiniVol samples. The highest 24-hr PM2.5 of 16.1 µg/m3 was
recorded at the South Lake Tahoe site on 11/9/2011; well below the NAAQS standard of 35
µg/m3. Concurrent PM2.5 concentrations at other sites were <5 µg m-3, indicating a localized
event. A few cross-the-basin episodes were identified, such as 9/9–10/2011, when Tahoe City,
South Lake Tahoe, and Incline Village all reported 12–13 µg/m3 PM2.5 concentrations, and Bliss
reported 9 µg/m3, over 2.5 times higher than the average level of 3.7±2.5 µg/m3 at the site.
Similar episodes include 8/26–27/2011, 9/2–4/2011, and 10/12/2011 (Figure 10). During 9/27–
29/2011, Bliss recorded the highest PM2.5 concentration, up to ~16 µg/m3, within the basin. This
is unusual considering the absence of sources around the site. This episode is consistent in time
with the Buckeye Fire originating from Humboldt County, California, ~100 km south of the
LTB. Smoke from the fire was seen in the Truckee Meadows (i.e., Reno and Sparks, Nevada) on
9/27/2011 (see http://www.kolotv.com/home/headlines/130597048.html).
Tahoe City
30
20
10
0
PM2.5 (µg m-3)
8/1
30
8/8
8/15
8/22
8/29
9/5
9/12
9/19
9/26
10/3
10/10
10/17
10/24
10/31
11/7
11/14
11/21
8/29
9/5
9/12
9/19
9/26
10/3
10/10
10/17
10/24
10/31
11/7
11/14
11/21
8/22
8/29
9/5
9/12
9/19
9/26
10/3
10/10
10/17
10/24
10/31
11/7
11/14
11/21
8/22
8/29
9/5
9/12
9/19
9/26
10/3
10/10
10/17
10/24
10/31
11/7
11/14
11/21
8/29
9/5
9/12
9/19
9/26
10/3
10/10
10/17
10/24
10/31
11/7
11/14
11/21
Bliss State Park
20
10
0
PM2.5 (µg m-3)
8/1
30
8/8
8/15
8/22
South Lake Tahoe
20
10
0
PM2.5 (µg m-3)
8/1
8/8
8/15
Cave Rock
30
20
10
0
PM2.5 (µg m-3)
8/1
30
8/8
8/15
Incline Village
20
10
0
8/1
8/8
8/15
8/22
Figure 10. 24-hr averaged PM2.5 measured by DustTrak at five sites in LTB for 2011 (8/1/2011–
11/22/2011). Missing data are left blank. Also shown in the figure are time-integrated MiniVol (weekly,
black ba r) and IMPROVE (24-hr, green dot) PM2.5 concentrations. Basin-wide episodes are marked by
vertical dotted lines (red). No exceedances to the 24-hr PM2.5 NAAQS of 35 µg/m3 were observed.
3-3
PM2.5 (µg m-3)
Figure 11 shows the time series of 24-hr averaged DustTrak data for the 2012 springsummer burning season along with MiniVol and IMPROVE PM2.5 (at Bliss State Park site only)
concentrations. The highest 24-hr PM2.5 of 13.5 µg/m3 was recorded at Cave Rock on 8/23/2012.
Concurrent PM2.5 concentrations at other sites were also relatively high (>10 µg/m3), indicating a
basin-wide event. The Ponderosa Fire (8/18-31/2012) and a few smaller wildfires were recorded
in Northern California during this period with smoke potentially impacting the LTB. The Cave
Rock site also recorded highest concentrations (>10 µg/m3) within the LTB on 6/1, 7/3, and
7/4/2012 that warrant further investigations. The IMPROVE network recorded a high value (13.6
µg/m3) at the Bliss State Park on 7/23/2012; concurrent DustTrak data was not available.
Records indicate that a fire burning in the Gardnerville area brought smoke into the LTB during
7/22-23/2012 (http://www.laketahoenews.net/2012/07/gardnerville-area-fire-brings-smoke-intotahoe-basin/). South Lake Tahoe generally recorded PM2.5 concentrations lower than those in late
fall of 2011, which were likely influenced by RWC as home heating demands increased.
Tahoe City
30
20
10
0
PM2.5 (µg m-3)
5/1
30
5/8
5/15
5/22
5/29
6/5
6/12
6/19
6/26
7/3
7/10
7/17
7/24
7/31
8/7
8/14
8/21
8/28
5/29
6/5
6/12
6/19
6/26
7/3
7/10
7/17
7/24
7/31
8/7
8/14
8/21
8/28
5/29
6/5
6/12
6/19
6/26
7/3
7/10
7/17
7/24
7/31
8/7
8/14
8/21
8/28
5/29
6/5
6/12
6/19
6/26
7/3
7/10
7/17
7/24
7/31
8/7
8/14
8/21
8/28
5/29
6/5
6/12
6/19
6/26
7/3
7/10
7/17
7/24
7/31
8/7
8/14
8/21
8/28
Bliss State Park
20
10
0
PM2.5 (µg m-3)
5/1
30
5/8
5/15
5/22
South Lake Tahoe
20
10
0
PM2.5 (µg m-3)
5/1
5/8
5/15
5/22
Cave Rock
30
20
10
0
PM2.5 (µg m-3)
5/1
30
5/8
5/15
5/22
Incline Village
20
10
0
5/1
5/8
5/15
5/22
Figure 11. 24-hr averaged PM2.5 measured by DustTrak at five sites in the LTB for 2012 (5/1/2012–
8/31/2012). Missing data are left blank. Also shown in the figure are time-integrated MiniVol (weekly,
black bar) and IMPROVE (24-hr, green dot) PM2.5 concentrations. Basin-wide episodes are marked by
vertical dotted lines (red). No exceedances to the 24-hr PM2.5 NAAQS of 35 µg/m3 were observed.
3-4
Site-specific diurnal variations of PM2.5 are examined between 8/1/2011 and 11/22/2011
and between 5/4/2012 and 8/31/2012. These are based on all valid hourly data which contain at
least 45 minutes (75%) of data. The middle 50-percentile (i.e., 25 [Q1]–75 [Q3]%) of data, i.e.,
the interquartile range (IQR), define the “typical” or “baseline” condition. The IQRs are
controlled by cyclic (diurnal) sources/sinks, such as morning/afternoon rush-hour traffic
emissions, RWC in the evening, and turbulent mixing in the afternoon. The extended range of
the data is determined by “Q1 – 1.5IQR” and “Q3 + 1.5IQR.” Data outside the extended range
are considered outliers. Outliers are expected to be caused by unusual, non-repeatable events
such as wildfires, prescribed burning, dust storm, accidents, etc. The diurnal range and outliers,
by site, are shown in Figure 12. This analysis helps identify noticeable episodes related to
prescribed burns around the LTB.
Tahoe City (Aug-Nov/2011)
Tahoe City (May-Aug/2012)
252
253
253
253
239
15
10
271
271
253
293
213213 253
295
253253
213
253293 286
213
213213213
238239
293 238
238
293
298
252
252 252
253
213239239
213 252
272272
239
271
14
252252
252
291
291
238
-3
-3
PM2.5 ( g m )
253
PM2.5 ( g m )
20
186
16
252
252
294
298
237
237
298
292 292
294237
292291
12
10
8
154
154154
154
140140
140
140137 137 140
195
140195
137 154137
195
195
140
153
153
189
181
153194194
194
194195
139139
195195
194195
139
195
139
195
195
195
195169
153
139
6
4
5
2
0
0
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
Hour of Day
Hour of Day
(a)
(b)
Figure 12. Boxplots based on hourly DustTrak data showing diurnal variations of PM2.5 by site for the
2011 and 2012 monitoring periods. Hour of day corresponds to Pacific Standard Time (PST). Circles
indicate the medians and boxes show the interquartile range (IQR). Whiskers extend to the most extreme
data points not considered outliers, and outliers, i.e., data outside [Q1 – 1.5IQR, Q3 + 1.5IQR], are
plotted individually as red crosses. Julian days in the year corresponding to the outliers are also marked.
DustTrak DRX at Incline Village appeared to have been influenced by ambient temperature during 2012,
so the measurements are not reliable. Note that only three hourly outliers at the South Lake Tahoe site on
Julian Days 271 and 306 exceed 35 µg/m3.
3-5
Bliss State Park (Aug-Nov/2011)
Bliss State Park (May-Aug/2012)
236236 236236
236
236
272
272
272 272
30
15
-3
PM2.5 ( g m )
272
-3
PM2.5 ( g m )
25
20
15
272272272
272
272
272
239
305
10
239239
239
240
238
239
240
238238
239239 239
240
240
239239
285
285
272
272
321
272
239
238
297
304 238
297
238
285
303
237
320
237237
237
272
297301
292
301
292
10
140199
137
211
235235
156
236
236236
209
235
236
211
185
236
209
228 230
236
186
230
230
228228
140
228
235
152
228
230
131228
235 139139
236
131131
230
195
139139139
135 131
140140
228139139
137
230
131
5
5
0
0
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
Hour of Day
Hour of Day
(c)
(d)
South Lake Tahoe (Aug-Nov/2011)
314
314 300
306302306
271
300
306
313313
312
303
314
300
285
297
314
303
313
313
317
301
303
314
311302
312
-3
PM2.5 ( g m )
30
25
20
15
10
272
314
315
304
313303
299301
313
313
317
253 253 312
272
253
253
295
317
301
156
156
186
15
186
173
-3
272
173
271
271
PM2.5 ( g m )
306
35
South Lake Tahoe (May-Aug/2012)
317
311
297
272272
314
252252
307312
272
239
313
317
239
296
297
301
304239
252
303
239
252 316
272
271252
271
272
272
253
252 272 307
239
252 253307
253 254253
238
254
313
271254
254252
253
238
229302
253
314
187
134
195
169
168
140186
10
5
5
0
0
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
Hour of Day
Hour of Day
(e)
(f)
Figure 12. (Continued).
3-6
Cave Rock (Oct-Nov/2011)
30
Cave Rock (May-Aug/2012)
321
25
25
236 236
297
306
297
304
304
304
304
291
301301 303
321
303
301 306
307
301
303301320
301
321
321
15
321
10
304
302
305302 302302
302
236
236
5
235
236
236
-3
20
20
PM2.5 ( g m )
-3
PM2.5 ( g m )
297
235
235
235
236
236 236
236
236
236
15
187186
187186
187187187
186
186
154154
228
228
228
186
230
228228
186
153
186228
235
186
185
186
186
10
5
0
0
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
Hour of Day
Hour of Day
(g)
(h)
Incline Village (Aug-Nov/2011)
30
306
15
10
271
271
253
253
239
253
270
304 271
239
238301301
253 301
238 238271
254
254254254253
307
156
50
40
-3
253
253
304
306
252
252
252
304
252
316304
252252252252
306
252
304 296
252
303
252 252
306
272272
314301316
272
316
304
303291
239
304
252
239
237
253 253
252
271
238271272
313
271
254
254
271
238239
254
254 253
PM2.5 ( g m )
-3
PM2.5 ( g m )
25
20
Incline Village (May-Aug/2012)
5
30
235235
236236
236
236236236
20
10
0
235
236 236236167
236
166
230
236
230
230
230
131
230
137
137
168137137231
137135
135
135230
137135
137
137
166
168231
137231
168
168
135
135
137168
135168
165
135
136
135
135
165
168
231
133136136
136
168136
231
136136
165
140
230
154
154
131
161
134
132
140134
132
133
132
140131
139
144
132
165 131134
133
167
133
235
235
228228230
231
140
136136
136
167134
167
135
135
132
164
140
131
0
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
1 2 3 4 5 6 7 8 9 101112131415161718192021222324
Hour of Day
Hour of Day
(i)
(j)
Figure 12. (Continued)
For 2011 (Figure 13[a]), the traffic influences are most apparent at the Tahoe City site
with distinguishable morning (0700–0900 PST) and evening (1600–1800 PST) rush hour peaks.
For the South Lake Tahoe site, another urban site, the same morning peak is visible but the
evening peak appears to delay until 2000–2300 PST. This possibly reflects a combined effect of
traffic emissions, commercial/entertainment activities (e.g., restaurants, casinos, etc.), and RWC
during late fall. RWC, but not traffic, might also influence the Incline Village site. The Cave
Rock site at lake level and the Bliss State Park site ~200 m above the lake without significant
sources nearby served as the low and elevated background sites, respectively, for the LTB. The
cold lake surface develops a strong (~10°C), shallow (~30 m) inversions throughout most of the
3-7
year (Cahill, 2009). While little diurnal variation of PM2.5 was observed at the Bliss State Park
site, a mid-afternoon peak at the Cave Rock site is consistent with downward mixing by
turbulence when PM2.5 concentrations aloft (e.g., 30 m) are higher than those near the surface.
This has often been observed at rural sites where pollutants mostly result from transport and/or
secondary aerosol formation (e.g., Chow et al., 2006a; Grivas et al., 2008). Figure 13(a) shows
that PM2.5 levels were relatively uniform across the basin during 1200–1600 PST, suggesting
extensive horizontal mixing besides vertical mixing in the afternoon. Figure 13 compares diurnal
variations based on median hourly PM2.5 concentrations.
May-Aug/2012
Aug-Nov/2011
20
20
Tahoe City
Bliss State Park
South Lake Tahoe
Cave Rock
Incline Village
15
PM2.5 (µg m-3)
PM2.5 (µg m-3)
15
Tahoe City
Bliss State Park
South Lake Tahoe
Cave Rock
Incline Village
10
Basin-wide
Mixing
5
10
5
0
0
0
4
8
12
16
20
24
Hour of Day
0
4
8
12
16
20
24
Hour of Day
(a)
(b)
Figure 13. Diurnal variations of PM2.5 at five sites during: (a) 2011 and (b) 2012 monitoring periods,
based on median hourly DustTrak data. The circle in (a) illustrates the basin-wide mixing period.
Diurnal variations of PM2.5 in 2012 are generally weaker than those in 2011 (Figure
13[b]). This is likely due to a relatively uniform, both spatially and temporally, boundary layer in
the LTB during the spring-summer observing period and lack of RWC emissions. The only
exception at the Incline Village site is attributed to malfunction of the DustTrak DRX, which
appears to have been influenced by ambient temperature at the site. It is striking that the Cave
Rock site generally recorded the highest PM2.5 levels among the five sites, while the Bliss State
Park site recorded the lowest. Increased emissions from traffic on Highway 50 and recreational
boats at the pier related to tourist activities offer an explanation.
Table 5 summarizes PM2.5 episodes that warrant further investigations, based on the
outliers identified in Figure 12, along with the maximum 24-hr and 8-hr PM2.5 concentrations
during the episodes and possible explanations. The LTB was frequently influenced by smoke
from wildfires in California, Nevada, Oregon, and sometimes Idaho. The wildfire season
typically starts from mid-July through mid-October. In 2011, DustTrak data corroborated the
timelines of the Motor Fire, Salt Fire, Buckeye Fire, and Tamarack Fire, while the impact of the
Buckeye Fire (9/27-29/2011, Julian Days 270-272) was most apparent. For 2012, the impact of
the Ponderosa Fire in northern California (8/22-23/2012, Julian Days 235-236) was most obvious
(Figure 11). Prescribed burns generally were not conducted during the wildfire season, except for
3-8
a small overlap in mid-October. Spring burns in 2012 were all called off according to the fire
agencies’ reports due to unfavorable weather conditions. Therefore, impact assessment for
prescribed burning has been focused on October and November of 2011.
The Angora Fire (6/24–7/2/2007) was the largest wildfire within the LTB in the last
decade, burning 3100 acres of forest south of Lake Tahoe (Safford et al., 2009). Since the
Angora Fire, the Lake Tahoe Basin Management Unit (LTBMU) has been carrying out
prescribed burns in the Angora area (Angora and Fallen Leaf Lakes) to reduce surface fuels and
mitigate future fire danger. At least four such Angora burns were consistent in time with PM2.5
episodes (e.g., 10/12-13, 10/20-21, 11/2, and 11/16-17, 2011, see Table 5). The North Lake
Tahoe Fire Protection Department (NLTFPD) and Nevada Division of Forestry (NDF) have
consistently conducted small-scale (<10 acres) prescribed burns around the north shore of Lake
Tahoe. Due to the proximity to the burn areas, Incline Village and Tahoe City may sometimes
experience the smoke (e.g., 10/19-20 and 10/31, 2011). Prescribed burns on the western bank of
Lake Tahoe had sometimes been carried out by LTBMU and CA State Park (CSP). The smoke
could be transported northeast impacting Tahoe City and Incline Village (e.g., 10/18 and 11/1617, 2011). Besides wildfire and prescribed burning, PM2.5 episodes might be caused by traffic
and/or RWC under a “very” calm, stagnant condition (i.e., little winds) as well as special events
such as the July 4th firework (e.g., 7/3-5, 2012).
Table 5. Summary of PM2.5 episodes in the 2011 and 2012 observing periods (according to outliers in
Figure 12) and potential causes based on fire and meteorological records.
Episode
Month/Days
Sites Impacted (with
hourly outliers)
Max 24-hr
PM2.5 (µg/m3)
Max 8-hra
PM2.5 (µg/m3)
Remarks
2011 (August–November)
8/1 (JD213)
8/17
8/25-28
Tahoe City
South Lake Tahoe
Incline Village, Tahoe
City, Bliss, and South
Lake Tahoe
Incline Village, Tahoe
City, and South Lake
Tahoe
Incline Village, Tahoe
City, Bliss, and South
Lake Tahoe
Tahoe City, Bliss, and
South Lake Tahoe
11.4
4.1
9.7
9.8
5.4
10.5
12.9
16.1
16.0
12.8
Buckeye Fire (Humboldt County,
California)
10.3
7.5
7.5
6.0
10/19
Incline Village, Tahoe
City, and Cave Rock
Tahoe City and Bliss
Tamarack Fire (Mariposa County,
California) near Yosemite
National Park. Prescribed burns
near South Lake Tahoe (Angora)
and Incline Village
Prescribed burns near Tahoe City
8.4
6.8
10/20-21
Tahoe City
9.1
7.8
9/9-11
9/27-29
10/12-13
10/18
3-9
Prescribed burns near Tahoe City
Motor Fire (Mariposa County,
California) near Yosemite
National Park
Salt Fire (Salmon-Challis Forest,
Idaho)
Prescribed burns near Incline
Village
Prescribed burns near Incline
Village (TNC, see Fig. 4) and
South Lake Tahoe (Angora)
Table 5. (Continued)
Episode
Days
Sites Impacted (with
hourly outliers)
Max 24-hr
PM2.5
Max 8-hra
PM2.5
(µg/m3)
(µg/m3)
Remarks
10/23
Incline Village
7.3
6.3
10/24
Bliss, South Lake
Tahoe, and Cave Rock
Incline Village, Bliss,
South Lake Tahoe, and
Cave Rock
Incline and South Lake
Tahoe and Cave Rock
9.9
9.7
11.4
5.8
Prescribed burns near Incline
Village. High RWC potential
12.2
4.0
Prescribed burns near South Lake
Tahoe (Angora). High RWC
potential
Prescribed burns near South Lake
Tahoe (Stateline and Kingsbury)
and Truckee, CA. High RWC
potential
Veterans Day weekend. High
RWC potential
Prescribed burns near Tahoe City,
South Lake Tahoe (Angora), and
Truckee, CA. High RWC
potential
10/31
11/2
11/9-10
Incline Village and
South Lake Tahoe
16.1
10.8
11/12
Incline Village and
South Lake Tahoe
Bliss and Cave Rock
5.9
2.9
7.6
6.0
11/16-17
Prescribed burns near Incline
Village
2012 (May–August)
5/18-19
6/1-2
6/4 (JD156)
6/21
7/3-5
7/12-13
7/27
8/17
8/22-23
b
Incline Village , Tahoe
City, Bliss, and South
Lake Tahoe
Incline Villageb, Tahoe
City, and Cave Rock
Incline Villageb, Bliss,
and South Lake Tahoe
South Lake Tahoe
Tahoe City, Bliss,
South Lake Tahoe, and
Cave Rock
Tahoe City, Bliss, and
South Lake Tahoe
Bliss
Incline Villageb, Bliss,
and Cave Rock
Incline Villageb, Bliss,
and Cave Rock
7.9
7.3
Calm, low-wind conditions
11.1
10.7
Calm, low-wind conditions
5.6
5.8
7.7
12.8
10.1
11.5
Calm, low-wind conditions
National Day celebration
(fireworks)
8.8
9.5
Robbers Fire (Placer County,
CA)
5.3
8.0
6.0
8.5
7.0
8.1
a
Rush Fire (Lassen County, CA)
Ponderosa Fire (Tehama and
Shasta County, CA) and Chips
Fire (Plumas County, CA)
1000-1800 PST, corresponding to the California 8-hr visibility standard for the Lake Tahoe Air Basin (U.S. EPA,
2005).
b
Large measurement uncertainty due to instrument malfunction. Values are not included in determining 24-hr and 8hr maximums.
3-10
It should be noted that the maximum 24-hr PM2.5 concentrations during these episodes
were well below the NAAQS (35 µg/m3). Using the average PM2.5 mass extinction efficiency of
4.2 m2 g-1 at South Lake Tahoe (Green et al., 2012), the California 8-hr visibility standard is
equivalent to a threshold of 16.7 µg m-3 PM2.5. No exceedances were observed, though some
close levels coincided with potential impact of wildfires (e.g., 9/9-11/2011 and 9/27-29/2011).
3.3
PM2.5 Chemical Composition
PM2.5 speciation measurements on weekly-averaged MiniVol filter samples were subject to
Levels I and II data validation, including: 1) sampling flow rate and duration; 2) filter inspection;
3) elemental sulfur (S) versus water-soluble sulfate (SO42-); 4) elemental potassium (K) versus
water soluble potassium ion (K+); 5) elemental chlorine (Cl) versus water soluble chloride (Cl-);
6) anion-cation balance; and 7) material balance (Louie et al., 2005). Most invalidated data
resulted from power failure of the sampler(s). Valid data were then used for material balance
based on the concentrations of major PM2.5 components including ammonium sulfate
([NH4]2SO4), ammonium nitrate (NH4NO3), organic matter (OM), elemental carbon (EC), fine
soil, and salt by:
[(NH4)2SO4] = 4.125 × [S]
(9)
[NH4NO3] = 1.29 × [NO3-]
(10)
[OM] = 1.4 × [OC]
[Fine Soil] = 2.2 × [Al] + 2.49 × [Si] + 1.63 × [Ca] + 2.42 × [Fe] + 1.94 ×
[Ti]
(11)
[Sea Salt] = [Na+] + [Cl]
(13)
(12)
Also, non-crustal potassium (nc-K), a surrogate of biomass burning, was calculated as:
[nc-K] = [K] – 0.075 [Si]
(14)
according to a [K]/[Si] ratio of 0.075 in source profiles of local dusts (Kuhns et al., 2004). The
nc-K agrees well with K+ concentration (i.e., [nc-K] = 1.037  [K+] + 0.005 µg/m3; R2 = 0.87). It
can better serve as biomass burning marker due to missing/invalidated K+ data. Figure 14 shows
the spatiotemporal variation of PM2.5 major components as well as gaseous NH3 concentrations.
PM2.5 Species (µg m-3)
Tahoe City
15
South Lake Tahoe
TRPA
Incline Village
PM2.5
10
5
0
8/4/2011
8/25/2011
9/15/2011
10/6/2011
10/27/2011
(a)
Figure 14. Spatiotemporal variation of PM2.5 components and gaseous NH3 in the LTB during the 2011
observing period. Horizontal bars indicate South Lake Tahoe concentrations as a benchmark.
Concentrations are based on weekly speciation data for: (a) PM2.5, (b) ammonium sulfate, (c) ammonium
nitrate, (d) OM, (e) EC, (f) fine soil, (g) salt, (h) non-crustal K (surrogate for biomass burning), and i)
3-11
NH3. Sampling sites: 1) Tahoe City, 2) South Lake Tahoe, 3) TRPA Stateline, 4) Incline Village.
PM2.5 Species (µg m-3)
2.0
PM2.5 Species (µg m-3)
0.4
PM2.5 Species (µg m-3)
10
PM2.5 Species (µg m-3)
2.0
PM2.5 Species (µg m-3)
Tahoe City
2.0
TRPA
Incline Village
Ammonium Sulfate
1.5
1.0
0.5
0.0
8/4/2011
(b)
Tahoe
City
South9/15/2011
Lake Tahoe
8/25/2011
TRPA
10/6/2011
Incline
Village
10/27/2011
Ammonium Nitrate
0.3
0.2
0.1
0.0
8/4/2011
(c)
Tahoe
City
South9/15/2011
Lake Tahoe
8/25/2011
TRPA
10/6/2011
Incline
Village
10/27/2011
TRPA
10/6/2011
Incline Village
10/27/2011
TRPA
10/6/2011
Incline
Village
10/27/2011
10/6/2011
10/27/2011
OM
5
0
8/4/2011
(d)
Tahoe City
South Lake Tahoe
8/25/2011
9/15/2011
EC
1.5
1.0
0.5
0.0
8/4/2011
(e)
(f)
South Lake Tahoe
Tahoe
City
South9/15/2011
Lake Tahoe
8/25/2011
Fine Soil
1.5
1.0
0.5
0.0
8/4/2011
8/25/2011
9/15/2011
Figure 14. Continued.
3-12
Tahoe City
Tahoe City
South Lake Tahoe
South Lake Tahoe
0.2
2.0
TRPA
TRPA
Incline Village
Incline Village
PM2.5 Species (µg m-3)
PM2.5 Species (µg m-3)
SaltSoil
Fine
1.5
0.1
1.0
Tahoe City
South Lake Tahoe
8/25/2011
9/15/2011
8/25/2011
9/15/2011
PM2.5 Species (µg
0.0
8/4/2011
Gas Species (µg
m-3)
(h)
(i)
TRPA
10/6/2011
10/6/2011
non-Crustal K
m-3)
(g)
0.5
0.0
0.0
8/4/2011
8/4/2011
0.1
Tahoe
City
South9/15/2011
Lake Tahoe
8/25/2011
2.0
Incline Village
10/27/2011
10/27/2011
TRPA
Incline
Village
10/6/2011
10/27/2011
Ammonia
1.0
0.0
8/4/2011
8/25/2011
9/15/2011
10/6/2011
10/27/2011
Figure 14. Continued.
Green et al. (2012) reported similar PM2.5 concentrations between urban and rural sites in
in the LTB during summer (June–August). The urban increments of PM2.5 mass increased
through fall to winter months. This is partly attributed to a more uniformly mixed boundary layer
within the basin in summer and to higher RWC emissions from the urban neighborhoods in
winter. For the fall 2011 observing period, the urban South Lake Tahoe site always recorded the
highest weekly PM2.5 levels after September 1, followed by the Tahoe City site (Figure 14[a]).
The spatial variation was not related to secondary inorganic aerosols as (NH4)2SO4 was relatively
homogeneous across the basin (Figure 14[b]) and NH4NO3 concentrations were low (<0.25
µg/m3). There are no substantial sources of SO2, i.e., precursor of sulfate, in the LTB. Thereby,
sulfate is transported into the basin, presumably by the prevailing westerly winds (Elliot-Fisk et
al., 1997; Molenar et al., 1994). This explains occasionally high (NH4)2SO4 levels at the Tahoe
City site, the westernmost site of the network. Before 10/27/2011, NH4NO3 concentrations were
generally below 0.1 µg/m3. The increase of NH4NO3 during November corresponded to a
decrease in gaseous NH3 concentration (see Figures 14[c] and [i]). Lower temperatures in late
fall would promote NH4NO3 formation from NH3 and nitric acid (HNO3) (West et al., 1999).
NOx, the major precursor of HNO3, mainly originated from mobile exhausts and biomass burning
(Chen et al., 2012). A few elevated NH4NO3 events prior to the active RWC season, such as 9/8-
3-13
14/2011 at the Incline Village site and 9/29-10/5/2011 at the Tahoe City, South Lake Tahoe, and
Incline Village sites coincided with the Salt Fire and Buckeye Fire, respectively.
OM and EC are the dominant products of biomass burning (Chen et al., 2007; 2010). For
OM, the spatial variability was minor prior to 10/27/2011 when RWC was insignificant,
although higher concentrations always occurred at the South Lake Tahoe site (Figure 14[d]).
Before 10/27/2011, OM concentrations at the Tahoe City and Incline Village sites differed from
the South Lake Tahoe site by 3–34% and 11–51%, respectively. Major sources of OM besides
RWC include mobile and wildfire emissions (Green et al., 2012), of which contributions are
either relatively constant (for mobile emissions) or uniform (for wildfires far outside the basin).
If these data contain periods where prescribed burning influenced only one of these sites,
contributions from the prescribed burning would unlikely exceed 30–40% of OM on a weekly
basis. After 10/27/2011, RWC might play an important role at the South Lake Tahoe site, though
a number of prescribed burns were carried out in the basin through November 2011 (see Table 5
and Appendix A). The increase in OM concentrations largely explains the PM2.5 trend in Figure
14(a). EC spatiotemporal patterns follow closely to those of OM (Figure 14[e]), with a
correlation coefficient (R2) of 0.81 between EC and OM.
Concentrations of fine soil were higher at the Tahoe City site (Figure 14 [f]), consistent
with the proximity of the site to a major road (NV-89). Green et al. (2012) suggest both local and
regional dust sources in the basin, while local dust dominates during September-November.
Figure 14(f) shows that fine soil concentrations at the TRPA and Incline Village sites were
similar, likely representing the regional (background) dust levels. Salt concentrations were low
(<< 0.1 µg/m3) except for the high values observed after 11/3/2011 at the South Lake Tahoe site
(Figure 14[g]). The high levels were related to salting activities after snowfalls (note: the first
snow in fall 2011 was reported on 11/3/2011). The nc-K concentration at the South Lake Tahoe
site increased over time from August to November 2011 except for a few exceptions.
Concentrations of nc-K at other sites were lower without clear trends (Figure 14[h]). The
abnormally high nc-K at the Tahoe City site during 8/18-24/2011 may have been impacted by a
local combustion event (e.g., prescribed burning on 8/17/2011).
Average PM2.5 chemical composition for the fall of 2011 observing period is shown in
Figure 15. Carbonaceous aerosol (OM + EC), the most dominant component, accounts for 4956% of PM2.5 mass. Higher PM2.5 concentration at the urban South Lake Tahoe site was expected
to mostly result from OM (Green et al., 2012). However, the lower OM fraction in the South
Lake Tahoe site than the Tahoe City and Incline Village sites (Figure 14[d]) signifies deviations
from the conceptual model. It is possible that OM and EC are underestimated at the South Lake
Tahoe site and TRPA sites due to variability in the particle size-cut inlet, as PM2.5 mass and OM
were measured from different samplers. This also explains the large fractions of unidentified
mass at these two sites and a negative correlation between mass fraction of OM and unidentified
mass. The material balance is improved with a higher multiplier (e.g., 1.8) to convert OC to OM,
as suggested by Pitchford et al. (2007). Fine soil and ammonium sulfate (derived from sulfur
concentration) were quantified from the same Teflon-membrane filter as PM2.5 mass and
therefore their mass fractions should be more accurate.
3-14
Tahoe City: avg measured PM 2.5 mass = 5.81 ug/m3
Incline Village : avg measured PM 2.5 mass = 4.12 ug/m3
10%
12%
18%
11%
0%
Fine Soil
16%
0%
Fine Soil
Sea Salt
Sea Salt
19%
OM
OM
EC
1%
EC
Ammonium Nitrate
Ammonium Sulfate
8%
Unidentifed Mass
Ammonium Nitrate
Ammonium Sulfate
2%
Unidentifed Mass
6%
50%
47%
(a)
(b)
South Lake Tahoe: avg measured PM 2.5 mass = 7.46
TRPA: avg measured PM2.5 mass = 5.32 ug/m3
ug/m3
9%
11%
1%
1%
24%
24%
11%
Fine Soil
Fine Soil
Sea Salt
Sea Salt
OM
OM
EC
EC
Ammonium Nitrate
Ammonium Nitrate
Ammonium Sulfate
45%
1%
45%
15%
Unidentifed Mass
Ammonium Sulfate
Unidentifed Mass
7%
2%
(c)
4%
(d)
Figure 15. PM2.5 chemical composition for the fall 2011 observing period for: (a) Tahoe City, CA, (b)
Incline Village, NV, (c) South Lake Tahoe, CA, (d) TRPA Stateline, NV.
3-15
4
4.1
Characterization of Prescribed Burning Emissions
Combustion Efficiency and Emission Factor
This analysis is based on four prescribed burns listed in Table 2. One-minute average
data from the In-Plume system was used for calculating real-time combustion efficiencies (CEs)
and emission factors (EFs). In addition, 10 valid time-integrated filter samples were acquired (2,
4, 2, and 2 for the SKY, DSP, TNC, and CLC burns, respectively) for chemical speciation. The
DustTrak PM2.5 data had been calibrated to the gravimetric PM2.5 mass measured on Teflonmembrane filters.
Tunnel Creek Burn on 10/20/2011
(a)
800000
600000
400000
200000
0
11:55
1
0.9
0.8
Total C Measured
C in CO2
CE
12:24
CE
C Concentration (µg/m 3)
Figure 16 shows the time series of In-Plume measurements for the TNC burn as an
example. An initial flaming combustion phase was recognized during the first ~15 minutes of
burning (1243-1300 PST), when CE generally exceeded 0.9 (Figure 16[a]) with the highest
PM2.5 and BC concentrations measured. BC is known to be generated mostly from flaming
combustion (Kuhlbusch and Crutzen, 1995; Chen et al., 2006). The EFPM2.5 during the period
was below 30 g/kg and EFBC ranged 0.3–0.7 g/kg. Following the flaming phase was an
approximately 30 minute transition period featuring CE of 0.8 to 0.9 with much higher EFPM2.5
(up to 90 g/kg). BC concentrations and EFs remained high, though there were apparently
increasing influences of smoldering combustion. One hour after ignition, CE fluctuated between
0.75 and 0.85 with variable EFPM2.5 while EFBC decreased gradually to nearly zero (Figure
16[b]). The later period would be dominated by smoldering emissions (i.e., STS + LTS). The
phase separation was not as clear for the other burns, probably due to a greater heterogeneity
within the burn plot.
0.7
12:53
13:22
13:50
0.6
14:48
14:19
(b)
50000
40000
30000
20000
10000
0
11:55
PM_2.5
BC x 10
EF_PM2.5
EF_BC x 10
12:24
12:53
13:22
13:50
14:19
120
100
80
60
40
20
0
14:48
PM Emission Factor (g/kg)
PM Concentration (µg/m3)
Time on 10/20/2011
Time on 10/20/2011
Figure 16. Time series of In-Plume measurements (1-min time resolution) during the Tunnel Creek (TNC)
burn on 10/20/2011 for: a) carbon (i.e., C) concentrations and combustion efficiency (i.e., CEs) and b)
PM2.5 concentrations and emission factors. Notes: Total C emission includes carbon in CO2, CO, and BC.
Arrows indicate the ignition time. Flaming, transition, and smoldering phases are separated empirically
(see text for details). All times are in PST.
4-1
9:58
9:59
10:00
10:01
10:02
10:03
10:04
10:05
10:06
10:07
10:08
10:09
10:10
10:11
10:12
10:13
10:14
10:15
10:16
10:17
10:18
10:19
10:20
CLC
SKY
0.6-0.64
0.64-0.68
0.68-0.72
0.72-0.76
0.76-0.8
0.8-0.84
0.84-0.88
0.88-0.92
0.92-0.96
Pile Burns
0-0.6
50%
40%
30%
20%
10%
0%
>0.96
Frequency
Histograms provide another means to characterize the burns. Figure 17 compares the
distribution of 1-min CE for pile (CLC and SKY) and understory (DSP and TNC) burns using all
In-Plume data above a threshold of smoke impact. The threshold is based on CO and PM2.5
concentrations, i.e., 0.43×[CO] + 0.58×[PM2.5] > 200 µg/m3C (carbon equivalent), which
corroborates levels significantly higher than the background (~0.2 ppm for CO and 10 µg/m3 for
PM2.5). Pile burns are dominated by high combustion efficiencies, e.g., CE > 0.92, consistent
with a more complete combustion than understory burns. Despite this, low CE < 0.84 were
observed during the CLC burn, showing some smoldering components. On the contrary, TNC
was most often measured for CE between 0.80–0.84. Pre-chopped burn piles generally contained
lower moisture contents than live understory vegetation, and it has been shown in the laboratory
study that fuel moisture lowers CEs and increases EFs of pollutants such as CO and PM (Chen et
al., 2010). Other effects to differentiate pile and understory burns include the fuel density and
burn temperature. Piles are composed of compacted woody fuels with a higher fuel bulk density
than those of the dispersed grass, shrub, woody, and litter surface fuels found in understory burn
sites. The denser piled fuels generally lead to higher combustion temperatures and more
thorough combustion. The CE distribution of DSP is broader, possibly due to a more complex
fuel matrix.
0.6-0.64
DSP
TNC
0.64-0.68
0.68-0.72
0.72-0.76
0.76-0.8
0.8-0.84
0.84-0.88
0.88-0.92
0.92-0.96
Underburns
0-0.6
50%
40%
30%
20%
10%
0%
>0.96
Frequency
Combustion Efficiency (CE)
Combustion Efficiency (CE)
Figure 17. Distribution of 1-min CE during the CLC and SKY pile burns and the DSP and TNC
prescribed burns. Only data points with [CO] + 0.58×[PM2.5] > 200 µg/m3C are included in the analysis to
mitigate the influence of uncertainties on the baselines. This resulted in 107, 128, 193, and 121 data
points for the CLC, SKY, DSP, and TNC burns, respectively.
The EFCO directly reflects CE and MCE. Pile burns with relatively high CE show EFco of
<100 g/kg (dry fuel) most of the time, while for understory burns EFco is often > 100 g/kg
(Figure 18[a]). EFco of 100 g/kg roughly corresponds to a CE of 0.9, a threshold for flaming
combustion (Chen et al., 2007). This confirms higher STS/LTS contributions during underburns.
Emission factor of another criteria pollutant, EFNOx, depends on both CE and fuel N content.
4-2
Fuel N is mostly in reduced forms (e.g., protein and amino acid), and flaming combustion
oxidizes N to NOx more efficiently due to a higher combustion temperature. The two understory
burns appear to yield higher EFNOx (Figure 18[b]), possibly due to higher herbaceous, thus higher
N, fractions in the fuels (Northup et al., 2005). Nitrogen gas (N2) is an important yet unquantified
N product in addition to NOx from flaming combustion (Kuhlbusch et al., 1991; Chen et al.,
2010). The partitioning between NOx and N2 contributes to the variability in observed EFNOx.
Smoldering combustion emits more reduced forms of N, mainly in NH3 and organic particulate
nitrogen but also small quantities of HCN, HONO, CH3CN, and HNCO (Burling et al., 2010).
60%
CLC
SKY
Pile Burns
40%
Frequency
20%
20%
CO Emission Factor (g/kg)
>5.5
5-5.5
4.5-5
4-4.5
3.5-4
3-3.5
2.5-3
2-2.5
NOx Emission Factor (g/kg)
60%
60%
Underburns
40%
DSP
TNC
Frequency
20%
DSP
TNC
20%
CO Emission Factor (g/kg)
>5.5
5-5.5
4.5-5
4-4.5
3.5-4
3-3.5
2.5-3
2-2.5
1.5-2
1-1.5
0-0.5
>550
500-550
450-500
400-450
350-400
300-350
250-300
200-250
150-200
100-150
0-50
0%
50-100
0%
Underburns
40%
0.5-1
Frequency
1.5-2
1-1.5
0-0.5
>550
500-550
450-500
400-450
350-400
300-350
250-300
200-250
150-200
100-150
0-50
0%
50-100
0%
CLC
SKY
Pile Burns
40%
0.5-1
Frequency
60%
NOx Emission Factor (g/kg)
(a)
(b)
Figure 18. Distribution of 1-min emission factors for: (a) CO and (b) NOx during the CLC and SKY pile
burns as well as the DSP and TNC understory burns. Only data points with 0.43 × [CO] + 0.58 × [PM2.5]
> 200 µg/m3C are included. This resulted in 107, 128, 193, and 121 data points for the CLC, SKY, DSP,
and TNC burns, respectively. EFNOx are reported as gNO/kg dry fuel.
The higher CE observed during the CLC burn (Figure 17[a]) is consistent with lower
EFPM2.5, mostly <10 g/kg (Figure 19[a]), though some high values up to 137 g/kg were also
recorded. Histogram of EFPM2.5 peaks at 20–30 g/kg for the CLC burn with a relatively narrow
distribution. Higher EFPM2.5 (>40 g/kg) were nearly absent during the SKY burn but were found
>10% and 30% of the time throughout the DSP and TNC burns, respectively. DSP also recorded
some very low EFPM2.5 (<10 g/kg). Despite a wide distribution of EFPM2.5 for some of the burns,
understory burns tend to emit more PM2.5 per unit of fuel consumed than pile burns.
BC and/or EC are indicators for flaming combustion. The EFBC are low compared to
laboratory studies. Chen et al. (2007; 2010) reported EFEC of 1-10 g/kg with higher values
towards flaming combustion and dry plant leaves. Figure 19(b) shows that EFBC of >1 g/kg were
rarely observed, except for the CLC burn, where 14% of EFBC were greater than 5 g/kg. There
are two possibilities: 1) flaming smoke which contains most of BC (or EC) were not sampled by
the In-Plume system due to rapid plume rises; and 2) inconsistency in BC and EC measurements
result from the influence of brown carbon (BrC), a light absorbing OC enriched in biomass
burning particles. Nonetheless, the field experiment results support a positive correlation of CE
with EFBC.
4-3
PM2.5 Emission Factor (g/kg)
>5.5
5-5.5
4.5-5
4-4.5
3.5-4
3-3.5
>5.5
5-5.5
DSP
TNC
4.5-5
4-4.5
3.5-4
3-3.5
2.5-3
0-0.5
>110
100-110
80-90
90-100
70-80
60-70
50-60
40-50
30-40
20-30
0-10
10-20
0%
2-2.5
20%
Underburns
1.5-2
DSP
TNC
1-1.5
Underburns
0.5-1
Frequency
2.5-3
BC Emission Factor (g/kg)
60%
40%
2-2.5
0-0.5
>110
100-110
80-90
90-100
70-80
60-70
50-60
40-50
30-40
20-30
0-10
10-20
PM2.5 Emission Factor (g/kg)
1.5-2
100%
80%
60%
40%
20%
0%
0%
CLC
SKY
Pile Burns
1-1.5
100%
80%
60%
40%
20%
0%
0.5-1
20%
Frequency
CLC
SKY
Pile Burns
40%
Frequency
Frequency
60%
BC Emission Factor (g/kg)
(a)
(b)
Figure 19. Distribution of 1-min emission factors for: (a) PM2.5 and (b) BC during the CLC and SKY pile
burns and the DSP and TNC prescribed burns. Only data points with [CO] + 0.58 × [PM2.5] > 200 µg/m3C
are included in the analysis. This resulted in 107, 128, 193, and 121 data points for the CLC, SKY, DSP,
and TNC burns, respectively.
EFPM2.5 is expected to be anti-correlated with CE since incomplete combustion produces
higher PM emissions. The relationship should also depend on the fuel type (Janhall et al., 2010).
As shown in Malamakal et al. (2013), the field measurements from SKY, DSP, and TNC
prescribed burning events in 2011 show a wide range of EFPM2.5 for any measured CE. They can
be bounded, however, between two extremes (Figure 20[a]). The default FEPS equation, Eq. (7),
closely describes the lower bound EFPM2.5. The upper bound can be parameterized by using ai
and bi of 431.8 and 429.7 g/kg, respectively, in Eq. (7), as derived from the highest 10th
percentile data with respect to the EFPM2.5 / (1 - CE) ratio. Figure 20(b) shows a similar range of
scattering in EFPM2.5 v.s. CE for the CLC burn in 2013, though data points are concentrated
around CE of 0.9–1.
As also shown in Figure 20, the FEPS default algorithm underestimates the observed
PM2.5 emissions in most cases. The bias could be up to a factor of 6. A recent laboratory
combustion study using the forest fuels from the LTB (Chen et al., 2010) highlights the
sensitivity of EFPM2.5 to fuel moisture content. The EFPM2.5-CE relationship for wet fuels across
several species (e.g., pines, bitterbrush, manzanita, etc.) and types (e.g., stems, leaves, duffs, etc.)
in Chen et al. (2010) agrees better with the upper bound in Figure 20. For dry fuels (<10%
moisture content), however, the relationship closely follows the lower bound in Figure 20 and
FEPS estimates. Given that most laboratory studies focus on dried fuels (e.g., Hays et al., 2002;
McMeeking et al., 2009), extrapolating the laboratory data to predict wildland fire emissions
would require some positive adjustments, especially for smoldering combustion with low CE.
Other factors such as wind and scale of burn could also impact the comparison of emissions
between field and laboratory burnings (Yokelson et al., 2013).
4-4
140
SKY
EFPM2.5 = 431.8 - 429.7 x CE
DSP
TNC
Upper Bound
Lower Bound (FEPS Default)
120
100
PM2.5 Emission Factor (g/kg)
PM2.5 Emission Factor (g/kg)
140
80
60
EFPM2.5 = 67.4 - 66.8 x CE
40
20
CLC
EFPM2.5 = 431.8 - 429.7 x CE
Upper Bound
Lower Bound (FEPS Default)
Lab Data (Dry Fuels)
Lab Data (Wet Fuels)
120
100
80
60
40
EFPM2.5 = 67.4 - 66.8 x CE
20
0
0
0.2
0.4
0.6
0.8
Combustion Efficiency (CE)
0.2
1
0.4
0.6
0.8
Combustion Efficiency (CE)
1
(b)
(a)
Figure 20. Scatter plot of EFPM2.5 as a function of CE (1-min data) for: (a) three prescribed burning events
(i.e., SKY, DSP, and TNC) in 2011 and b) one prescribed burn event (i.e., CLC) in 2013 and laboratory
burns. The lower bound of the distribution is the FEPS default parameterization while the upper bound is
determined from the top 10th percentile of data with respect to the EFPM2.5 / (1 - CE) ratio. Blue triangles
and green diamonds indicate data from laboratory combustion of wet and dry fuels, respectively (Chen et
al., 2010).
4.2
Time-integrated Emissions and PM2.5 Chemical Composition
Table 6 summarizes the time-integrated EFs corresponding to all valid filter samples
acquired from the four (i.e., CLC, SKY, DSP, and TNC) prescribed burns with the In-Plume
measurements. This confirms the relatively high CEs (>0.9) for pile burns (i.e., CLC and SKY)
and low CEs (<0.9) for understory burns (i.e., DSP and TNC). For a similar range of fireintegrated CEs (0.85–0.95, or MCE of 0.89–0.96), Burling et al. (2011) reported EFPM2.5 of 10 to
25 g/kg for conifer forest understory burns from airborne measurements of smoke plume. Their
results compare well with those observed in this study (11 to 33 g/kg). Laboratory combustion of
small piles (100‒200 g) of dry Ponderosa pine branches, needles, and cones shows generally much
higher combustion efficiencies (CE = 0.98-0.99) and lower CO and PM2.5 EFs than those measured
in the field.
Table 6. Time-integrated combustion efficiencies and emission factors of PM2.5, EC, BC, CO, NOx, and
NH3 for CLC, SKY, DSP, and TNC burns.
Burn
Sampling
Period
11:09-12:02
CLC
(6/24/2013)
13:06-14:03
Average
CE &
MCE
0.96
0.97
0.93
0.95
0.95±0.02
0.96±0.01
EFPM2.5
(g/kg)
EFEC
(g/kg)
EFBC
(g/kg)
EFCO
(g/kg)
EFNOx
(g/kg)
EFNH3
(g/kg)
7.3
N.A.
0.44
39
0.75
N.A.
16
N.A
3.4
56
2.5
N.A
11±5
N.A
1.9±1.5
47±9
1.6±0.9
N.A
*See Table 2 for prescribed burning and Section 2.3 for laboratory burn information; all but EC and NH3
emission factors were derived from real-time measurements. The calculations assume a universal fuel
carbon mass fraction of 0.49. Uncertainties were based on the standard deviations; N.A.: Not measured.
4-5
Table 6. Continued.
Burn
Sampling
Period
11:55-12:50
SKY
(6/11/2011)
12:51-13:51
Average
11:32-11:55
12:00-13:00
DSP
(10/3/2011)
13:05-14:05
14:10-15:10
Average
12:35-13:35
TNC
13:37-14:37
(10/20/2011)
Average
13:42-14:02
14:28-14:48
Laboratory
Dry Pile Burn
15:16-15:37
(3/20-4/20,
2014)
16:05-16:25
CE &
MCE
0.93
0.96
0.91
0.93
0.92±0.01
0.94±0.02
0.86
0.89
0.85
0.87
0.87
0.90
0.86
0.89
0.86±0.01
0.89±0.01
0.88
0.91
0.83
0.87
0.85±0.03
0.89±0.03
0.98
0.99
0.98
0.99
0.99
0.99
0.99
0.99
0.98±0.01
0.99±0.0
EFPM2.5
(g/kg)
EFEC
(g/kg)
EFBC
(g/kg)
EFCO
(g/kg)
EFNOx
(g/kg)
EFNH3
(g/kg)
22
1.4
0.45
50
0.91
1.0
22
1.1
0.20
74
0.65
1.8
22±1
1.3±0.2
0.32±0.14
62±12
0.78±0.13
1.4±0.4
32
0.97
0.27
120
0.60
2.3
19
0.99
0.19
144
0.49
6.1
28
0.99
0.19
109
0.67
2.5
24
1.7
0.21
127
0.54
3.9
26±6
1.2±0.4
0.21±0.04
125±15
0.58±0.08
3.7±1.8
30
1.3
0.47
102
1.4
2.0
36
1.2
0.30
142
0.80
4.7
33±3
1.3±0.1
0.38±0.09
122±20
1.1±0.3
3.4±1.4
8.9
N.A
N.A
16
1.7
N.A
3.0
N.A
N.A
14
2.0
N.A
2.6
N.A
N.A
12
3.2
N.A
2.9
N.A
N.A
12
1.7
N.A
4±3
N.A.
N.A
13±2
2.1±0.7
N.A
In general, N emissions are in the form of NOx and NH3 and the NH3/NOx ratio increases
with decreasing combustion efficiency. Low combustion temperatures during the smoldering
phases preserve more reduced forms of N, such as NH3, as suggested by Chen et al. (2010). The
flaming phase of the SKY burn (i.e., 1155-1250 PST) produced both EFNOx and EFNH3 of ~1
g/kg, which later turned to ~0.7 g/kg for EFNOx and 1.8 g/kg for EFNH3 when smoldering
contribution phased in (1251-1351 PST). The trend was also similar during the TNC burn, but
with substantially higher EFs (up to 5 g/kg for NH3). The prescribed burn emission factors in
Table 6 are somewhere between laboratory combustion results with dry and moderately wet fuels
(i.e., Moisture Levels I and II, respectively, in Chen et al. 2010), as EFPM2.5 are higher than the
Level I level and EFNOx+NH3 are close to the Level I level. The NH3/NOx ratio, however, appears
to be much higher for the field than laboratory burns. Again, this might partly be attributed to the
heterogeneity in the smoke during field measurement.
4-6
Percentage of chemical composition in PM2.5 acquired from the prescribed burning is
presented in Table 7. This source profile can be used for source apportionment by receptor
modeling. Carbonaceous material, particularly OC, dominates the PM2.5 mass. Other significant
species include Cl-, NO3-, SO4=, NH4+, K+, K, Cl, S, and calcium (Ca). A narrow range of
K+/PM2.5 ratio (0.2–0.4%) supports potassium (K+ and/or K) as a good marker for biomass
burning. The material balance is examined in Figure 21 using Eqs. (9)-(13), as those for ambient
Table 7. Chemical composition of PM2.5 (in percentage) for time-integrated filter samples acquired from
the SKY, DSP, and TNC burns.
Burn
Sampling
Period
Cl-
SKY (6/11/2011)
11:55-12:50
12:51-13:51
DSP (10/3/2011)
11:32-11:55
12:00-13:00
13:05-14:05
TNC (10/20/2011)
14:10-15:10
12:35-13:35
13:37-14:37
00.035±00.146 00.085±00.132 00.137±00.040 00.411±00.086 00.059±00.056 00.139±00.150 00.083±00.021 00.073±00.020
NO3
-
00.324±00.147 00.416±00.133 00.092±00.036 00.170±00.067 00.112±00.056 00.375±00.151 00.127±00.020 00.116±00.019
SO4=
00.311±00.147 00.309±00.132 00.442±00.044 00.440±00.070 00.266±00.058 00.480±00.151 00.241±00.023 00.158±00.019
NH4+
00.284±00.148 00.279±00.133 00.084±00.036 00.185±00.067 00.088±00.056 00.235±00.150 00.076±00.019 00.063±00.018
+
Na
00.000±00.085 00.000±00.076 00.000±00.021 00.000±00.038 00.000±00.032 00.000±00.087 00.040±00.011 00.000±00.010
K+
00.282±00.023 00.251±00.021 00.399±00.024 00.359±00.023 00.211±00.014 00.253±00.022 00.311±00.019 00.174±00.011
OC
49.776±03.395 51.720±03.463 54.322±03.450 52.937±03.398 27.690±01.818 52.405±03.553 55.975±03.528 55.166±03.476
EC
06.503±00.672 05.129±00.549 03.020±00.281 05.242±00.490 03.554±00.342 07.328±00.739 04.357±00.386 03.470±00.309
Al
00.000±00.034 00.000±00.031 00.000±00.008 00.053±00.016 00.000±00.013 00.000±00.035 00.008±00.004 00.001±00.004
Si
00.000±00.005 00.031±00.005 00.003±00.001 00.035±00.003 00.000±00.002 00.046±00.006 00.000±00.001 00.002±00.001
P
00.000±00.005 00.000±00.004 00.000±00.001 00.000±00.002 00.000±00.002 00.003±00.005 00.002±00.001 00.001±00.001
S
00.086±00.041 00.078±00.036 00.198±00.014 00.157±00.020 00.196±00.019 00.133±00.042 00.106±00.007 00.071±00.006
Cl
00.039±00.005 00.044±00.005 00.127±00.007 00.367±00.019 00.105±00.006 00.045±00.006 00.073±00.004 00.070±00.004
K
00.380±00.020 00.273±00.014 00.474±00.024 00.447±00.023 00.496±00.025 00.296±00.016 00.324±00.016 00.211±00.011
Ca
00.020±00.016 00.037±00.014 00.015±00.004 00.106±00.009 00.015±00.006 00.055±00.016 00.012±00.002 00.015±00.002
Ti
00.000±00.005 00.000±00.004 00.000±00.001 00.000±00.002 00.000±00.002 00.000±00.005 00.000±00.001 00.000±00.001
V
00.000±00.005 00.001±00.004 00.000±00.001 00.000±00.002 00.000±00.002 00.001±00.005 00.000±00.001 00.000±00.001
Cr
00.000±00.005 00.001±00.004 00.001±00.001 00.004±00.002 00.001±00.002 00.002±00.005 00.000±00.001 00.001±00.001
Mn
00.000±00.008 00.000±00.007 00.000±00.002 00.003±00.004 00.003±00.003 00.000±00.008 00.001±00.001 00.000±00.001
Fe
00.000±00.008 00.008±00.007 00.005±00.002 00.037±00.004 00.004±00.003 00.009±00.008 00.001±00.001 00.002±00.001
Co
00.000±00.005 00.003±00.004 00.000±00.001 00.000±00.002 00.000±00.002 00.000±00.005 00.000±00.001 00.000±00.001
Ni
00.000±00.005 00.000±00.004 00.000±00.001 00.002±00.002 00.001±00.002 00.000±00.005 00.000±00.001 00.000±00.001
Cu
00.000±00.005 00.000±00.004 00.000±00.001 00.000±00.002 00.000±00.002 00.000±00.005 00.000±00.001 00.000±00.001
Zn
00.007±00.005 00.008±00.004 00.007±00.001 00.049±00.003 00.009±00.002 00.005±00.005 00.008±00.001 00.006±00.001
As
00.000±00.005 00.000±00.004 00.000±00.001 00.000±00.002 00.000±00.002 00.000±00.005 00.000±00.001 00.000±00.001
Se
00.000±00.005 00.000±00.004 00.000±00.001 00.000±00.002 00.000±00.002 00.001±00.005 00.000±00.001 00.000±00.001
Br
00.000±00.005 00.000±00.004 00.001±00.001 00.004±00.002 00.001±00.002 00.000±00.005 00.004±00.001 00.002±00.001
Rb
00.002±00.005 00.001±00.004 00.001±00.001 00.003±00.002 00.002±00.002 00.001±00.005 00.000±00.001 00.000±00.001
Sr
00.001±00.005 00.001±00.004 00.000±00.001 00.000±00.002 00.002±00.002 00.000±00.005 00.001±00.001 00.001±00.001
Pb
00.000±00.008 00.000±00.008 00.001±00.002 00.000±00.004 00.000±00.003 00.000±00.009 00.001±00.001 00.001±00.001
*See Section 2.1 for analytical methods/protocols.
4-7
samples. Major uncertainties include the OM/OC ratio and organic sampling artifacts (Chow et
al., 2010; Watson et al., 2009). Applying a 1.4 multiplier to convert OC to CM led to substantial
unidentified mass. A higher multiplier (e.g., 1.8), usually corresponding to more oxidized OM,
may be applied for biomass burning aerosol (El-Zanan et al., 2005; Pitchford et al., 2007).
Average EC fraction is the highest in SKY and lowest in TNC, consistent with CEs of the
burns, i.e., flaming combustion with high CE dominates EC production (Chen et al., 2006;
2007). The EC fraction in PM2.5 was 3.0–7.3% across the SKY, DSP, and TNC burns, higher
than the BC fraction of 0.7–2%. The discrepancies between EC and BC measured by different
principles were discussed before (see Watson et al., 2005; Chow et al., 2009 and references
therein). Nonetheless, the EC (or BC) fractions in smoke PM2.5 for field measurements appeared
to be lower than those acquired from laboratory combustion experiments (Chen et al., 2007;
2010). There are two additional explanations for the difference: 1) substantial OC were generated
from soil or duff materials which were not often tested in the laboratory; and 2) secondary
organic aerosol (SOA) formation had been much faster and more efficient in the field than in the
laboratory. Both of these mechanisms increase OC fraction and decrease EC fraction in PM2.5
from prescribed burning.
SKY
0.1%
0.1%
22.0%
Fine Soil
Salt
0.4%
0.5%
OM
EC
5.8%
Amm Nitrate
Amm Sulfate
71.1%
Unidentified Mass
(a)
Figure 21. Material balance of PM2.5 for: (a) SKY, (b) DSP, and (c) TNC burns. The mass percentages
are calculated from average of respective filter samples as shown in Table 7. See Eqs. (9)-(13) for the
construction of each component. Data were not available for the CLC burn.
4-8
DSP
0.2%
0.3%
28.9%
Fine Soil
Salt
OM
0.6%
EC
Amm Nitrate
0.2%
65.8%
4.0%
Amm Sulfate
Unidentified Mass
(b)
TNC
0.04%
17.70%
0.14%
Fine Soil
0.27%
Salt
0.16%
OM
3.90%
EC
Amm Nitrate
Amm Sulfate
77.78%
(c)
Figure 21. Continued.
4-9
Unidentified Mass
5
Smoke Forecast and Impact Assessment
5.1
Integration of Smoke Forecast Tools
The emission data was first obtained from FEPS. Using the TNC burn (10/20/2011) as an
example, Figure 22 shows the time series of fuel consumption, heat release, combustion
efficiency, and emission rates of CO, methane (CH4), and PM2.5, as modeled by FEPS with
default CE and EF coefficients. Note that a burn was conducted at an adjacent 7-acre plot on the
previous day (10/19/2011). The FLA and STS phases corresponded to the active ignition period
(3-4 hours), while LTS continued throughout the day and into the next day (10/21/2011). The
FLA, STS, and LTS phases consumed 35%, 15%, and 50% of the fuel, respectively. Heat
releases, however, are mostly associated with the flaming phase, leading to a maximum plume
height (Brigg H max) of 53 m during the first hour of burning. The TNC burn generated ~560
kg CO and 45 kg PM2.5.
3.0E+04
6.0E+07
FLA Consumption (kg/hr)
STS Consumption (kg/hr)
LTS Consumption (kg/hr)
Plume Heat Release (kJ/hr)
TNC Burn
(10/20/2011)
2.0E+04
4.0E+07
3.0E+07
2.0E+07
1.0E+04
0.0E+00
10/19/11 0:00
5.0E+07
1.0E+07
10/20/11 0:00
10/21/11 0:00
Heat Release
(kJ/hr)
Fuel Consumption
(kg/hr)
4.0E+04
0.0E+00
10/22/11 0:00
(a)
4.0E+02
3.0E+02
1.00
CO/10 Emissions (g/sec)
CH4 Emissions (g/sec)
PM2.5 Emissions (g/sec)
Combustion Efficiency
0.95
0.90
0.85
2.0E+02
0.80
1.0E+02
0.0E+00
10/19/11 0:00
0.75
10/20/11 0:00
10/21/11 0:00
Combustion
Efficiency
Emission Rates
(g/sec)
5.0E+02
0.70
10/22/11 0:00
(b)
Figure 22. FEPS modeled results for: (a) fuel consumption (by FLA, STS, and LTS phases) and heat
release and (b) combustion efficiency and emission rates (CO, PM2.5 and CH4) at hourly resolution for the
TNC burn (10/20/2011, the second peak in the figures). A burn conducted in an adjacent 7-acre plot
starting at 1000 PST on 10/19/2011 was also modeled. Default CE and EF coefficients were used in the
FEPS model (see Eqs. [6] and [7]).
The lowest and highest CE determined by FEPS is 0.76 and 0.86, respectively (Figure
22[b]), significantly different from the measured range of 0.76-0.96. The FLA and STS CE
coefficients need to be adjusted in conjunction with adjustments for EFPM2.5 (as shown in Figure
20). If kFLA and kSTS in Eq. (6) are set to 0.99 and 0.90, respectively, and ai and bi in Eq. (7) are
set to 431.8/429.7 (i.e., the upper limit in Figure 20), FEPS would predict a maximum CE of 0.95
for TNC (Figure 23). This is in good agreement with the In-Plume measurement. The PM2.5
emission rates would increase by a factor of 2–4 (i.e., the upper limit in Figure 23). Due to the
wide range of observed EFPM2.5, the actual PM2.5 emission rates are uncertain, likely between the
upper limit and default curves in Figure 23. The new parameters also increase the total heat
release by ~10%, allowing the maximum plume height to reach 57 m. For impact assessment, the
5-1
higher emission rates should be considered, with the understanding of uncertainties in EFs and
fuel consumption.
TNC Burn
Figure 23. FEPS modeled hourly combustion efficiency (CE) and PM2.5 emission rates (default and upper
limit) for the TNC burn (10/20/2011). Adjusted coefficients were used to calculate CE and the upper limit
of PM2.5 emission. Actual PM2.5 emission rates are likely in the shaded area.
To calculate smoke dispersion, the meteorological data were obtained from the WRF
model with 2 km x 2 km resolution. Figure 24 compares WRF surface wind forecasts with
measurements at four weather stations (http://www.wrcc.dri.edu/) closest to the TNC burn plot.
WRF predicted generally southwesterly winds throughout 10/20–21/2011, pushing smoke out of
WRF U (avg)
East-West Wind (m/s)
12
obs U (inv)
obs U (dip)
10
obs U (sah)
8
obs U (slm)
obs U (avg)
6
4
2
0
-2
-4
10/20/12 0:00
10/21/12 0:00
Date
(b)
WRF V (avg)
obs V (inv)
obs V (dip)
obs V (sah)
obs V (slm)
obs V (avg)
North-South Wind (m/s)
12
10
8
6
4
2
0
-2
-4
10/20/12 0:00
(a)
10/21/12 0:00
Date
(c)
Figure 24. Comparison of WRF surface winds with observations at: (a) four weather stations: Slide
Mountain (slm), Diamond Peak (dip), Incline Village (inv), and Sand Harbor (sah) closest to TNC. Wind
components in the east-west (U) and north-south (V) directions are compared in (b) and (c), respectively.
The yellow bars indicate the standard deviation of WRF winds across the four sites.
5-2
the LTB. The observed wind data did not show a narrow range among the four sites as the WRF
simulation does, likely due to the influence of local topography and subgrid turbulence. However,
averaged wind components tracked the WRF forecasts reasonably. This justifies the use of WRF
data to support dispersion modeling.
A graphic user interface (GUI, see Figure 25) was developed as part of the project to
generate control files for running the HYSPLIT model. The GUI converts FEPS output to
emission files that contain hourly PM2.5 and heat release rates acceptable by HYSPLIT. Multiple
WRF weather files can be specified, along with key parameters such as model domain, spatial
resolution (in degrees of latitude/longitude), vertical integrating levels, as well as particle size
and density (for calculating deposition). Three vertical levels, 25 m, 100 m, and 500 m, were
usually selected. Each vertical level for the HYSPLIT particle mode (as in this study) indicates
the “average” PM2.5 concentration between that level and the previous level (or the ground for
the first level). The 25-m level was used to compare with surface PM2.5 measurements obtained
from the five ambient monitoring sites (Figure 4).
GMT Time (PST +8)
Emission File
Vertical Levels
Weather Files
Save Control File
Figure 25. Matlab® graphic user interface (GUI) for creating HYSPLIT control file for the TNC burn.
Model execution and visualization were accomplished by another GUI (Figure 26). The
output from HYSPLIT is a gridded distribution of hourly PM2.5 from the ignition time to a
5-3
specified end time. A dynamic distribution map is presented through a contour-plot of the
gridded data (Figure 26). Though not explicitly modeled by HYSPLIT, the terrain effect has
been represented in the WRF meteorological data files. The GUI also calculates and plots PM2.5
concentrations (in µg/m3) at the five ambient monitoring sites as a function of time using a
“gridded to station” function of HYSPLIT.
Perform HYSPLIT Model
Analyze HYSPLIT Results
TNC Burn Started
(10/20/2011)
PM2.5 concentration in µg/m3
Latitude
Longitude
Colorbar: Surface (0-25 m) PM2.5
concentration in µg/m3 (log scale)
PST (from the day of ignition)
Figure 26. Matlab® graphic user interface (GUI) for executing the HYSPLIT model and analyzing the
output data. The monitoring sites are noted by 1-5 in the contour plot: 1: Incline Village; 2: Tahoe City; 3:
Bliss State Park; 4: South Lake Tahoe; and 5: Cave Rock. The diamond indicates the TNC burn plot. The
snapshot is for TNC burn 6 hours after ignition. Note a burn conducted at an adjacent plot in the previous
day (7 acres, started at 1000 PST on 10/19/2011) was also modeled here.
5.2
Simulation and Verification of Measured Burn Events
Figure 27 shows the smoke transport in terms of surface PM2.5 concentration for two
prescribed burns conducted near Tunnel Creek on 10/19/2011 and 10/20/2011 (i.e., the TNC
burn) (see Figure 22). The upper-limit PM2.5 emission (Figure 23) based on revised FEPS
parameters were used in the modeling. The initial plume transport within a few hours after
ignition generally followed the planned path, i.e., moving away from the LTB (Figure 27[a] and
[f]). Winds sometimes shift direction in the evening, causing the smoke to return to the LTB
(Figure 27[b]-[c]). Although in this case, the PM2.5 concentrations would have been substantially
diluted before reaching the monitoring sites. It should be noted that smoldering can continue
from hours to days after ignition and eventually impact the air quality. One day after the TNC
5-4
burn, substantial PM2.5 elevation up to 6 µg/m3 was predicted across the LTB (Figure 27[i]-[l]).
This is mostly attributed to the LTS emission from the burn plots. The impact would be <2
µg/m3 if the default FEPS CE and EFPM2.5 parameters were used (Malamakal et al., 2013).
Despite the uncertainty, the model reveals potential air quality/visibility impact of prescribed
burning, even when a SMP and strict selection of the burn windows are enforced.
39.6  N
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
39.6  N
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
39.6  N
39.5  N
39.5  N
39.5  N
39.4  N
39.4  N
39.4  N
39.3  N
39.3  N
1
39.2  N

39.1 N
3
4

38.9 N
3
38.9 N
38.8  N
38.7  N
38.7  N
38.7  N
38.6  N
38.6  N
1
2
4
8
16
0.25
39.6  N




38.6  N
0.5
1
2
4
8
16
0.25
(b) 10/19 18:00
(a) 10/19 12:00

120.4 120.2
W
120.0
W
119.8
W
119.6
W
W
39.6  N
39.6  N
39.5  N
39.5  N
39.4  N
39.4  N
39.4  N
39.3  N
39.3 N
1
39.2  N
2
39.1  N
5
39.0  N
3
3
38.8  N
38.8  N
38.7  N
38.7  N
38.7  N
38.6  N
38.6  N
0.5
1
2
4
8
16
0.25
(d) 10/20 06:00
39.6  N
39.6  N
1
2
4
8
16
39.5 N
39.5 N
39.4  N
39.4  N
39.3  N
39.2  N
39.6  N
3
38.9 N
5
3
38.9 N
38.8  N
38.7  N
38.6  N
38.6  N
4
(g) 10/21 00:00
8
16
0.25
PM2.5
μg/m3
5
3
4
38.9  N
38.7  N
2
16
1
39.0  N
4

38.8  N
1
8
2
39.1  N
38.7  N
0.5
4
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
39.2  N
38.8  N
0.25
2
39.3  N
2
39.0  N
4

1
39.4  N
1
39.1  N
5
39.0  N
0.5
39.5 N
39.2  N
2
39.1  N
0.25

39.3  N
1
4
(f) 10/20 18:00
120.4  120.2
W  120.0
W  119.8
W  119.6
W W


PM2.5
μg/m3
38.6  N
0.5
(e) 10/20 12:00
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
16
5
3
38.9  N
38.8  N
0.25
8
1
39.0  N
4
38.9  N
4
2
39.1  N
5
39.0  N
4
38.9  N
2
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
39.2  N
2
39.1  N
1
39.3  N
1
39.2  N
0.5
(c) 10:20 00:00
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
39.5  N

4
38.9 N
38.8  N
0.5
3

38.8  N
0.25
5
39.0  N
4

2
39.1  N
5
39.0  N
1
39.2  N
2
39.1  N
5
39.0  N
39.3  N
1
39.2  N
2
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
38.6  N
0.5
1
2
4
(h) 10/21 06:00
8
16
0.25
0.5
1
2
4
8
16
(i) 10/21 12:00
Figure 27. Time series of smoke transport (every 6th hour in PST) of surface PM2.5 concentrations (μg/m3
during 10/19-22/2011 for the two prescribed burns near Tunnel Creek (Diamond). Five ambient
monitoring sites around Lake Tahoe are also marked. (See Figure 26 for site identifications; the same
latitudes and longitudes are used as in Figure 26.)
5-5
PM2.5
μg/m3
39.6  N
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
39.6  N
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
39.6  N
39.5  N
39.5  N
39.5  N
39.4  N
39.4  N
39.4  N
39.3  N
39.3  N
1
39.2  N
2
39.1  N
3
38.9 N
39.1 N
3
4

38.9 N
38.8  N
38.7  N
38.7  N
38.6  N
38.6  N
2
4
8
16
(j) 10/21 18:00
0.25
4
38.9 N
38.7  N
1
3

38.8  N
0.5
5
39.0  N
38.8  N
0.25
2

5
39.0  N
4

1
39.2  N
2
39.1  N
5
39.0  N
39.3  N
1
39.2  N
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
38.6  N
0.5
1
2
4
8
16
(k) 10/22 00:00
0.25
0.5
1
2
4
8
16
PM2.5
μg/m3
(l) 10/22 06:00
Figure 27. (Continued)
The site-specific impact of the TNC burn, as modeled by FEPS-HYSPLIT, is shown in
Figure 28. PM2.5 peaks are short-lived, lasting for up to several hours. This reflects quickly
changing wind directions. Smoldering smoke with relatively low plume heights influenced all
the sites in the evening of 10/21/2011, while the maximum contributi on of ~6 µg/m3 PM2.5 was
found at Tahoe City. The impact levels are moderately high considering average PM2.5
concentrations of 5–10 µg/m3 in the LTB (Figure 12). In fact, only the Tahoe City and Bliss
State Park sites recorded abnormalities that are qualified as episodes within 10/19–22/2011
(Table 5). It should be noted that the highest weekly PM2.5 of 7.3 µg/m3 and nc-K (a biomass
burning marker) of 0.03 µg/m3 at Tahoe City occurred for the week of 10/20–26/2011 (Figure
14).
PM2.5 Contribution
(µg m-3)
15
10
Incline Village
Tahoe City
Bliss
South Lake Tahoe
Cave Rock
5
0
10/19/11
10/20/11
10/21/11
10/22/11
10/23/11
10/24/11
Time
Figure 28. Impact of Tunnel Creek (TNC) burns on five monitoring sites in the LTB, as predicted by the
FEPS-HYSPLIT model. Arrows indicate the start of burns on 10/19/2011 and 10/20/2011.
Figure 29 compares the FEPS-HYSPLIT predicted TNC burn contributions to PM2.5 with
ambient measurements at the Incline Village, Tahoe City, and Bliss State Park sites. The
forecasted burn peaks correspond well with observed peaks in time (within 1–2 hours),
particularly those occurring in the evening of 10/21/2011 (i.e., Peaks A, B, and F in Figure 29[a],
[b], and [c], respectively). Neither peaks A nor B follows the typical diurnal pattern, e.g.,
morning and/or evening rush hours. Peak B is the outlier causing 10/21/2011 to be declared as an
5-6
PM2.5 Concentration
(µg m-3)
episode at the Tahoe City site (Table 5). All these evidences corroborate the influence of TNC
burns. Peak F is not as evident since PM2.5 dropped to a very low level before the smoke impact.
25
20
15
Median
Measured
TNC Burn Contribution
Incline Village
10
A
5
0
10/14/11
10/16/11
10/18/11
10/20/11
Date
Time
10/22/11
10/24/11
PM2.5 Concentration
(µg m-3)
(a)
25
20
15
Median
Measured
TNC Burn Contribution
Tahoe City
D
C
B
E
10
5
0
10/14/11
10/16/11
10/18/11
10/20/11
Date
Time
10/22/11
10/24/11
PM2.5 Concentration
(µg m-3)
(b)
25
20
15
Median
Measured
TNC Burn Contribution
Bliss State Park
G
10
5
0
10/14/11
F
10/16/11
10/18/11
10/20/11
Date
Time
10/22/11
10/24/11
(c)
Figure 29. Comparison of hourly ambient PM2.5 measurements with FEPS-HYSPLIT predicted PM2.5
contribution from Tunnel Creek burns for the: (a) Incline Village; (b) Tahoe City; and (c) Bliss State Park
sites. The median line indicates typical diurnal pattern determined from the median concentrations
throughout the fall 2011 observing period. Arrows indicate the burn start times. See text for explanations
of Peaks A–G.
Three days (10/19-20/11 and 10/22/2011) are declared as PM2.5 episodes for the Tahoe
City site due to Peaks C, D, and E (Figure 29[b]), respectively. 10/19/2011 is also an episode for
the Bliss State Park site due to Peak G (Figure 29[c]). Peaks D and E occurred around 0700–
5-7
0900 PST, possibly due to an increased traffic contribution under stagnant conditions. There are
several other peaks like Peak C and G during the 10/19–22/2011 period that cannot be explained
by the typical diurnal pattern and/or TNC burn(s). One possibility may be due to model
uncertainty, including vertical inhomogeneity that leads to underestimate of smoke impact. Other
prescribed burns conducted in the same period will be discussed in the next section. While no
wildfires are known to impact the LTB during this period, some of the peaks can result from
other sources such as transport of fugitive dust and secondary aerosols (i.e., NH4[SO4]2, NH4NO3,
and OM) from outside the LTB. The lack of unique markers at hourly resolution and/or a fullscale air quality model that includes all the sources prevents a direct proof or disproof of the
hypotheses. The short-term nature of most peaks and non-uniformity across the basin, however,
suggest more localized events within the LTB.
The smoke transport of SKY, DSP, and CLC burns were also calculated using the same
modeling protocol. Only the SKY burn (6/11/2011) shows appreciable impact on air quality for
the Bliss State Park, South Lake Tahoe, and Cave Rock sites on the day after ignition (Figure 30).
PM2.5 Contribution
(µg m-3)
30
25
20
15
Incline Village
Tahoe City
Bliss
South Lake Tahoe
Cave Rock
39.6  N
SKY
39.4  N
39.3  N
1
39.2  N
2
39.1  N
10
39.0  N
5
38.8  N
0
6/11/11
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
39.5  N
5
3
4
38.9  N
38.7  N
38.6  N
6/12/11
6/13/11
6/14/11
6/15/11
0.25
0.5
1
2
4
8
16
Date
Time
(a)
PM2.5 Contribution
(µg m-3)
30
25
20
15
Incline Village
Tahoe City
Bliss
South Lake Tahoe
Cave Rock
39.6  N
DSP
39.4  N
39.3  N
1
39.2  N
2
39.1  N
10
39.0  N
5
38.8  N
0
10/3/11
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
39.5  N
5
3
4
38.9  N
38.7  N
38.6  N
10/4/11
10/5/11
Date
Time
10/6/11
10/7/11
0.25
0.5
1
2
4
8
16
(b)
PM2.5 Contribution
(µg m-3)
30
25
20
15
Incline Village
Tahoe City
Bliss
South Lake Tahoe
Cave Rock
39.6  N
CLC
39.4  N
39.3  N
1
39.2  N
2
39.1  N
5
39.0  N
10
3
4
38.9  N
5
0
6/24/13
120.4  120.2
W  120.0
W  119.8
W  119.6
W W
39.5  N
38.8  N
38.7  N
38.6  N
6/25/13
6/26/13
Date
Time
6/27/13
6/28/13
0.25
0.5
1
2
4
8
16
(c)
Figure 30. Impact of prescribed burn for: (a) SKY (6/11/2011); (b) DSP (10/3/2011); and (c) CLC
(6/24/2013) on ambient PM2.5 concentrations in the LTB, as predicted by the FEPS-HYSPLIT model. See
Table 2 for detailed burn information. Arrows indicate the burn start times. Transport maps represent: a)
19; b) 10; and c) 7 hours after ignition. See Figure 26 for explanation of the maps.
5-8
Like the TNC burn, smoke from these burns were largely transported outside the basin during the
first several hours of burning, confirming a good selection of the burn windows. For the DSP and
CLC burns, the wind directions were consistent throughout the 3-day (72 hours) modeling period,
while winds turned to the opposite direction on the second day (6/12/2011) for the SKY burn,
circulating smoke within the LTB. The SKY burn contribution to PM2.5 concentrations would
mainly depend on smoldering combustion emissions, which are subject to a substantial
uncertainty in the FEPS simulation. Unfortunately, no ambient data were available to compare
model results for the SKY burn. Nonetheless, the impact appears to last only a few hours,
causing 24-hr PM2.5 concentration to increase on 6/12/2011 by 1.9, 2.8, and 1.6 µg/m3 at the
Bliss State Park, South Lake Tahoe, and Cave Rock sites, respectively. PM2.5 would be much
lower (<0.5 µg/m3) if default FEPS parameters were used. Ambient data are available for the
DSP modeling period. However, no episode days were identified between 10/3/2011 and
10/6/2011 (see Table 5).
5.3
Assessment of Prescribed Burning Impacts: Case Studies
Attempts were made to examine whether PM2.5 episodes, such as those identified in Figure
29, can be explained by known prescribed burning events. If so, this would provide additional
validations to the model for quantifying the prescribed burning contributions to PM2.5. A major
challenge was found to be the lack of burn records. Data from fire agencies were not in the same
format and some critical information, including fuel load, moisture content, ignition time, rate of
progress, and burn duration, were missing or inaccurate. Since these records were based on burn
plan(s) before the burn, it did not reflect adjustments made in the field. Such adjustments were
common, as observed in this study. In some cases, a planned burn was cancelled but still shown
in the record. In other cases, some known burns were completely missing in the records. Since
field observations could not be made for all the burns, best judgments were made to parameterize
FEPS. Inaccurate burning parameters added uncertainty to the predictions of smoke transport and
impact on air quality.
Three prescribed burns conducted during 10/17–19/2011, two by NTFPD (NTFPD1,
10/17/2011; NTFPD2: 10/19/2011) near Incline Village and one by LTBMU near Tahoe City
(LTBMU1; 10/18/2011), might have caused the basin-wide event during the evenings of
10/18/2011 and 10/19/2011 (e.g., Peaks C and G in Figure 29). These burns were all assumed to
begin in the late morning (~1000 PST) and continue through early afternoon to take advantage of
the strong turbulent updraft at that time. The active ignition period lasted for 3–5 hours
depending on the burn size (see Appendix B). Comparison of FEPS-HYSPLIT forecasted smoke
transport and ambient measurement (Figure 31) indicates strong influence of the prescribed
burns on air quality at the Incline Village and Tahoe City sites, owing to proximity of the burn
plots to these two monitoring sites. Though the smoke arrival time is generally consistent with
observed PM2.5 peaks, smoke contributions to PM2.5 appear to be inconsistent, i.e., overestimated
in some cases and underestimated in others. For example, the model predicted hourly PM2.5
concentrations for the NTFPD1 burn (Figure 31[a]) to exceed 300 µg/m3 at the Incline Village
site for 1600–2400 PST on 10/18/2011. Forecasting in this case is particularly challenging. In
addition to uncertainties in burn information, the distance between the burn plot and monitoring
site is close to the model grid size and it is difficult to model boundary layer movement
(Pournazeri et al., 2012). FEPS-HYSPLIT suggests that the Tahoe City episode on 10/19/2011 is
5-9
related to the NTFPD2 burn (Figure 31[b]), but the impact seems small compared to the
observed PM2.5 abnormality.
Figures 31(c)-(e) illustrate that smoke resulting from multiple burns on the north shore of
Lake Tahoe (i.e., TNC, NTFPD1, NTFPD2, and LTBMU1) could be transported to the south
shore impacting air quality at the Bliss State Park, South Lake Tahoe, and Cave Rock sites. This
is illustrated by the transport pattern in Figure 27(b). The impacts are relatively minor but do
coincide with PM2.5 peaks and explain the only episode occurring at the Bliss State Park site
(10/19/2011, see Figure 31[c]. However, the Cave Rock episode on 10/18/2011 and several
elevated PM2.5 concentrations (non-episodes) during nighttime at the South Lake Tahoe site
cannot be explained by any of the burns. They might be caused by RWC under a relatively calm
boundary layer (e.g., wind speed <1 km/hr at South Lake Tahoe between 1800 and 2200 PST,
10/18/2011).
PM2.5 (µg m-3)
25
20
15
10
TNC
NTFPD 2
LTBMU 1
NTFPD 1
Median
Measured
Incline Village
5
0
10/17/11
10/18/11
10/19/11
10/20/11
10/21/11
10/22/11
10/21/11
10/22/11
10/21/11
10/22/11
Date
(a)
PM2.5 (µg m-3)
25
20
15
10
TNC
NTFPD 2
LTBMU 1
NTFPD 1
Median
Measured
Tahoe City
5
0
10/17/11
10/18/11
10/19/11
10/20/11
Date
(b)
PM2.5 (µg m-3)
25
20
15
10
TNC
NTFPD 2
LTBMU 1
NTFPD 1
Median
Measured
Bliss State Park
5
0
10/17/11
10/18/11
10/19/11
10/20/11
Date
(c)
Figure 31. Measured hourly PM2.5 concentrations in the LTB as compared to modeled accumulative
contributions of multiple prescribed burns (i.e., TNC, TNC, NTFPD1, NTFPD2, and LTBMU1)
conducted between 10/17/2011 and 10/20/2011 on the north shore of Lake Tahoe. PM2.5 episodes are
identified (in circles) based on diurnal patterns (Table 5).
5-10
PM2.5 (µg m-3)
25
20
15
10
TNC
NTFPD 2
LTBMU 1
NTFPD 1
Median
Measured
South Lake Tahoe
5
0
10/17/11
10/18/11
10/19/11
10/20/11
10/21/11
10/22/11
10/21/11
10/22/11
Date
(d)
PM 2.5 (µg m-3)
25
20
15
10
TNC
NTFPD 2
LTBMU 1
NTFPD 1
Median
Measured
Cave Rock
5
0
10/17/11
10/18/11
10/19/11
10/20/11
Date
(e)
Figure 31. (Continued)
Prescribed burning in the Angora area, however, can severely impact air quality at the
South Lake Tahoe and Cave Rock sites. Two prescribed burns identified in the LTB for the
period of 10/31/2011-11/4/2011 were the NTFPD3 burn near Incline Village and the LTBMU2
burn near Angora. The forecasted impacts of the two burns are consistent (in time) with the
Incline Village episode days on 10/31/2011 and 11/2/2011 as well as the South Lake Tahoe and
Cave Rock episode days on 11/2/2011 (Figure 32[a]-[c]), though the smoke intensity is likely
overestimated. Since all of these are evening episodes under low ambient temperatures (<0°C),
the relative contributions of prescribed burning and RWC emissions to PM2.5 concentrations
warrant further investigations.
The NTFPD3 burn contributes to two PM2.5 episodes at the Incline Village site (Figure
32[a]) which are consistent with westerly winds as the burn plot was located to the west of the
site. The second episode (11/2/2011) received exclusively smoldering emissions from the burn.
The contributions from the LTBMU2 burn to the South Lake Tahoe and Cave Rock sites are
consistent with southwesterly winds during the first several hours of the burn. Two-to-four hours
after ignition, smoke started to impact the South Lake Tahoe and Cave Rock sites, and to a lesser
degree, the Bliss State Park site. Figure 33(a) shows the smoke transport from the LTBMU2 burn
11 hours after the ignition. The smoke appears to be trapped along the eastern corridor of the
basin with horizontal transport limited by the steep eastern slope. The model also predicted a
secondary PM2.5 peak at both the South Lake Tahoe and Cave Rock sites around midnight of
11/3/2011 (Figure 32[b]-[c]). There were no prescribed burning records for the next day
(11/3/2011), but a continuous operation of the fire crew in adjacent plots (i.e., unrecorded burns)
was possible. Snowfall began ~1900 PST on 11/3/2011, which likely extinguished the
combustion and removed particles from the air.
5-11
PM2.5 (µg m-3)
40
Incline Village
30
Snow started
20
LTBMU 2
NTFPD 3
Median
Measured
10
0
10/31/11
11/1/11
11/2/11
11/3/11
11/4/11
11/5/11
Date
(a)
PM2.5 (µg m-3)
40
South Lake Tahoe
30
Snow started
20
LTBMU 2
NTFPD 3
Median
Measured
10
0
10/31/11
11/1/11
11/2/11
11/3/11
11/4/11
11/5/11
Date
(b)
PM2.5 (µg m-3)
40
Cave Rock
30
Snow started
20
LTBMU 2
NTFPD 3
Median
Measured
10
0
10/31/11
11/1/11
11/2/11
11/3/11
11/4/11
11/5/11
Date
(c)
Figure 32. Measured hourly PM2.5 concentrations in the LTB as compared to modeled accumulative
contributions of multiple prescribed burns (i.e., NTFPD3 near Incline Village, and LTBMU2 in the
Angora area) conducted between 10/31/2011 and 11/4/2011. PM2.5 episodes are identified (in circle)
based on baseline diurnal patterns (see Table 5). Ambient data from the Tahoe City and Bliss State Park
sites are not available for this period.
5-12
11 hrs after ignition
5 hrs after ignition
(a)
(b)
Figure 33. Snapshots of FEPS-HYSPLIT model simulated smoke transport for the two prescribed burns:
a) LTBMU2 (near Angora on 11/2/2011) and b) LTBMU3 (near Tahoe City on 11/15/2011). Colorbar
indicates surface (0-25 m) PM2.5 concentrations in µg/m3 (log scale). See Figure 26 for further
explanations of the map.
Considering the prevailing westerly to southwesterly winds in the LTB, prescribed burns
on the west side of the LB may pose a greater threat to air quality than those on the east side. The
LTBMU3 burn on 11/15/2011 is an example of west-side burn. Smoke from the burn is
transported to the Cave Rock, South Lake Tahoe, and Bliss State Park sites ~5 hours after
ignition (Figure 33[b]), while the maximum contributions to PM2.5 are minor, i.e., <3 µg/m3,
according to FEPS-HYSPLIT. This is mainly because most of the smoke has been lifted aloft
before reaching the monitoring sites. Therefore, it is possible to mitigate the smoke impact even
for the "west-side" burns by selecting appropriate burn windows.
Case studies presented in this section support the model prediction of potential prescribed
burning smoke impact on air quality in the LTB, based on a projection of smoke transport over
major communities within ~72 hours of ignition. This observation applies to prescribed burns on
almost any parts of the basin, including those with an approved SMP. However, a quantitative
assessment of the prescribed burning contributions to PM2.5 and other pollutants and how they
compare with other sources cannot be made without further improvement and validation of the
current model.
5.4
Wildfire Impacts: Case Studies
Large-scale wildfires outside the basin often influence air quality in the LTB. Several
such examples were identified in Table 5. Compared to prescribed fires, wildfires are much
larger in size and usually last for days to weeks. They produce more uniformly high PM2.5
concentrations in both space and time.
During the Salt Fire event (Figure 34), smoke was carried into the LTB from several
wildfires in Idaho by an unusual northeasterly transport. Similarly elevated PM2.5 levels up to 25
5-13
PM2.5 Concentration
(µg m-3)
µg/m3 were observed at all monitoring sites within the basin (Figure 34[b]-[d]). The highest
concentrations were detected at the Incline Village site, the northeast point of the LTB. The
smoke impact lasted for more than 48 hours, within which measurements among the three
monitoring sites were highly correlated. This contrasts the short-term prescribed burning impacts
shown in the previous section. Typical diurnal pattern appears to be superimposed onto the
smoke PM2.5, as most evidenced by the data from the Tahoe City site (Figure 34[c]).
25
20
Median
Measured
Incline Village
15
10
5
0
9/6/11
9/7/11
9/8/11
9/9/11
9/10/11
9/11/11
9/12/11
9/13/11
Date/Time
PM2.5 Concentration
(µg m-3)
(b)
25
20
Median
Measured
Tahoe City
15
10
5
0
9/6/11
9/7/11
9/8/11
9/9/11
9/10/11
9/11/11
9/12/11
9/13/11
Date/Time
PM2.5 Concentration
(µg m-3)
(c)
25
20
Median
Measured
South Lake Tahoe
15
10
5
0
9/6/11
9/7/11
9/8/11
9/9/11
9/10/11
9/11/11
9/12/11
9/13/11
Date/Time
(d)
(a)
Figure 34. Salt Fire as observed by: (a) satellite and (b)-(d) PM2.5 measurements in the LTB. The satellite
image was acquired by NASA MODIS with 2 km x 2 km resolution at 1300 PST on 9/9/2011. Red dots
indicate fire detected. Both measured and median (from Figure 12) PM2.5 concentrations between
9/7/2011 and 9/13/2011 are shown in Figure 34(b)-(d). Dashed lines in Figure 34(c) mark the peaks
corresponding to the morning and evening rush hours at the Tahoe City site.
Figure 35 shows the Robbers Fire in July 2012 (see http://archive2.capradio.org/articles/
2012/07/12/placer-officials-warn-of-smoke-hazard-from-robbers-fire). Compared to Salt Fire,
the Robbers Fire is smaller in scale but closer to the LTB. Since the burn area was located to the
west of the LTB, the Tahoe City site experienced the largest impact between 7/12/2012 and
7/14/2012 when south-southwesterly winds prevailed. Winds shifted to southerly by the
afternoon of 7/14/2012. The impact lasted for more than 48 hours, although the highest PM2.5
concentrations only reached ~10 µg/m3. Smoke impacts on other sites such as Bliss State Park
and South Lake Tahoe were also appreciable, but they did not track those at the Tahoe City site
as well as they did during the Salt Fire. Due to the nature of smoke dispersion, fires farther away
from the LTB should produce more uniform and longer-term impacts when their smoke is indeed
transported to the LTB. However, large wildfires do not necessarily produce hourly PM2.5
concentrations higher than those by prescribed burns within the LTB, which are much closer to
the monitoring sites.
5-14
PM2.5 Concentration
(µg m-3)
25
20
Median
Measured
Tahoe City
15
10
5
0
7/9/12
7/10/12
7/11/12
7/12/12
7/13/12
7/14/12
7/15/12
7/16/12
7/14/12
7/15/12
7/16/12
7/14/12
7/15/12
7/16/12
Date/Time
PM2.5 Concentration
(µg m-3)
(b)
25
20
Median
Measured
Bliss State Park
15
10
5
0
7/9/12
7/10/12
7/11/12
7/12/12
7/13/12
Date/Time
PM2.5 Concentration
(µg m-3)
(c)
25
20
Median
Measured
South Lake Tahoe
15
10
5
0
7/9/12
7/10/12
7/11/12
7/12/12
7/13/12
Date/Time
(d)
(a)
Figure 35. Robbers Fire as observed by: (a) satellite and (b)-(d) PM2.5 measurements in the LTB. The
satellite image was acquired by NOAA at 1300 PST on 7/14/2012. Both measured and median (see
Figure 12) PM2.5 concentrations between 7/9/2012 and 7/16/2012 are shown in Figure 35(b)-(d). Dashed
lines in Figure 35(b) mark the peaks corresponding to the morning and evening rush hours at the Tahoe
City site.
5-15
6
Conclusions and Recommendations
This study carried out ambient and in-plume measurements and developed/tested
modeling tools for evaluating prescribed burning impacts on air quality (i.e., PM2.5 level) in the
Lake Tahoe Basin (LTB). Major findings are listed below:
 Laboratory tests and emission models underestimate prescribed burn emissions
and combustion efficiencies
EFPM2.5 determined from the in-plume measurements of prescribed burning generally
increases with decreasing CE, but with a wide range of EFPM2.5/(1 - CE) ratios (Figure
20). The operational emissions model (i.e., FEPS), with its default settings, reports lower
CEs than measured values due to a predefined flaming phase CE coefficient of 0.9. Much
higher CEs (~0.99) were detected in the field. FEPS also underestimates EFPM2.5 for a
given CEs by up to a factor of six. The low-end EFPM2.5 predicted by FEPS are consistent
with laboratory combustion tests for dry LTB fuels while the high-end EFPM2.5 as
measured by the in-plume measurements agree with laboratory tests of moist fuels. For
proper simulation of the largest possible impacts, CE coefficients in FEPS were increased
to 0.99 for flaming and 0.9 for smoldering, and the EFPM2.5 coefficients were increased by
a factor of six. This substantially increases the modeled PM2.5 emission rates, particularly
for the smoldering phase.
 Understory burns show higher emission factors than slash pile burns, implying
larger environmental effects
Lower overall combustion efficiencies were found for understory burns (i.e., DSP and
TNC: CE < 0.9) of natural vegetation than for slash-pile burns (i.e., SKY and CLC: CE >
0.9). This is likely due to a higher moisture content and lower fire intensity. Higher
emission factors for PM2.5 and NH3 associated with the low combustion efficiencies imply
larger environmental impacts from understory burns with respect to air quality and
nutrient (i.e., nitrogen) deposition. This should be of additional concern since more
emissions from understory burns are associated with smoldering combustion which is
accompanied by a relatively low heat release rate and plume height (i.e., staying longer
near the surface). PM2.5 from pile burns, however, contain a higher fraction of lightabsorbing BC or EC, which impacts visibility (or lake clarity when depositing into the
water) more than light-scattering particles such as NH4NO3, (NH4)2SO4, OM, and
fugitive dust.
 Despite enforcement of smoke management plans, prescribed burning impacts air
quality in the Lake Tahoe Basin
Multiple agencies have been carrying out prescribed burning in the LTB, with strict
guidelines for smoke management. Preferred weather conditions include an unstable
boundary layer (i.e., no inversion) with moderate winds to carry smoke outside the basin.
Except for occasional misforecasts, smoke from the ignition and first several hours of
burning usually rises and moves away from the population centers as expected. However,
smoldering combustion can continue long after the active ignition period. The model
prediction indicates that the smoldering smoke often impacts communities due to changes
6-1
in wind direction. The impact often shows up in the evening under a shallow surface
layer. This could happen for prescribed burns in any part of the basin. The extent of
smoke impacts depends on the smoldering emission rate (i.e., emission factor × fuel
consumption), which appears to be minor if using the default FEPS parameters
(Malamakal et al., 2013). With modified settings, the smoke impact is appreciable as
compared to ambient PM2.5 levels in the LTB. However, it does not cause exceedances of
the 24-hr PM2.5 air quality standards of 35 µg/m3 or the 8-hr California visibility standard
for the Lake Tahoe Air Basin (bext = 70 Mm-1, or equivalently 16.7 µg/m3 of PM2.5) at the
current monitoring sites.
 Individual prescribed burn impacts are inhomogeneous and of short duration
compared with wildfires
Prescribed burning impacts on air quality can be identified as episodic by examining
baseline diurnal patterns (Figure 12) in conjunction with wildfire and prescribed burn
records (Table 5). PM2.5 episodes associated with prescribed burning can be as short as
1–2 hours and rarely last more than several hours. This is confirmed by FEPS-HYSPLIT
modeling. Transport of the smoke plume depends on meso-scale winds, which change
direction frequently. The spatial distribution of smoke is also inhomogeneous. The
Incline Village site is often influenced by nearby prescribed burns conducted by the
NTFPD and NDF, while the Tahoe City site is more likely to experience smoke from
burns on the west shore. Prescribed burns by the LTBMU in the Angora and Fallen Leaf
areas could impact the South Lake Tahoe and Cave Rock sites more than other sites.
Impacts from distant wildfires are usually more spatially homogeneous within the basin
and last longer (e.g., >48 hours), and therefore can be clearly identified.
 Further model development and validation are required to quantify prescribed
burning contributions to pollutants versus contributions from other sources
The FEPS-HYSPLIT model, driven by the high-resolution (2 km x 2 km) WRF
meteorological data, is useful for simulating smoke transport around the LTB. The
model-predicted PM2.5 episodes due to prescribed burning are consistent in time with
measured PM2.5 concentrations in many cases. The model provides fire agencies with an
additional tool to make/evaluate burn decisions. However, the model predictions are not
reliable for "quantifying" prescribed burning contributions to PM2.5 and other pollutants.
The real-world in-plume measurements helped to refine the emission factors in FEPS.
However, the model is still limited by fuel consumption estimates and
inaccurate/incomplete burn information such as ignition time, burn duration, rate of burn
progress, and fuel conditions. Improved model resolution is also needed. For the fall
burns, prescribed burning impacts on air quality often peak in the late evening, coinciding
with a maximum impact from residential wood combustion. The current ambient PM2.5
chemical speciations do not offer markers to distinguish particles from these two sources
to further validate the model. Model validation would preferably be made with spring or
summer burns, which are not available in this study due to unexpected weather conditions
in 2012 and a short project duration (i.e, no prescribed burns in spring/summer 2012 with
no ambient measurements in spring/summer 2011 and 2013).
6-2
Recommendations for future prescribed burning practice and research include:
 Burn decisions should consult longer-term weather forecasts coupled with
dispersion modeling
To address the potential impact of prolonged smoldering combustion emissions, it is not
sufficient to base the prescribed burn decision solely on weather conditions of the burn
day. A longer-term forecast (e.g., 72 hours) should be consulted, especially for burns
close to population centers. This can be further rectified by dispersion modeling using
updated combustion efficiencies and emission factors as described in this report.
 A cross-agency, post-burn reporting system should be available
The current burn records are mainly for acquiring a burn permit and do not reflect
adjustments (e.g., ignition time and burn plot) made in the field. A post-burn reporting
system needs to be developed, which would provide accurate burn information, facilitate
hindcasting of smoke dispersion, and update emission inventories. The burn information
needs to be entered into the system by a burn officer after each burn and made accessible
on-line.
 Further research should focus on spring and summer burns for validating the
emission and dispersion models
Source- and receptor-oriented modeling will be the ultimate tools for quantifying
prescribed burning impacts on air quality and environment health. These models need to
be continuously developed and validated. Spring and summer burns would be the
preferred cases for validating models, since contributions from residential wood
combustion are small and contributions from wildfires can be clearly distinguished. This
study provides examples of smoke plume dispersion and characterization. Future research
should include hourly measurements of more specific biomass burning markers, such as
brown carbon, water-soluble potassium, and levoglucosan, at the ambient monitoring
sites to reduce the ambiguity in model evaluation.
6-3
7
Acknowledgement
This project was funded by the USDA Forest Service through the Southern Nevada
Public Land Management Act (SNPLMA Round 11). The authors thank John Washington from
the Lake Tahoe Basin Management Unit and Roland Shaw from the Nevada Division of Forestry
for their assistance in the field and for providing the burn information. The authors also
appreciate the following DRI colleagues: Tim Brown provided WRF data, Keith Szelagowski
organized the database, and Steve Kohl as well as other DRI Environmental Analysis Facility
(EAF) staffs for laboratory analysis. Comments from the reviewers, including Drs. Tim Brown,
Susan Prichard, Roger Ottmar, and Shawn Urbanski, are greatly appreciated. The conclusions are
those of the authors and do not necessarily reflect the views of the sponsoring agencies.
7-1
8
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9
Appendix A
Table A-1: Prescribed burns conducted in 2011
Burn Date
a
Agency
Latitude
Longitude
Type
of
Burn
b
Burn
Area
(acres)
Tons/
Acre
3
30
5/16/11
CSP
39.770
120.693
5/16/11
CSP
39.756
120.693
5/16/11
CSP
39.133
120.163
3
30
5/17/11
CSP
39.770
120.674
2
30
5/17/11
CSP
39.133
120.163
2
30
5/23/11
CSP
39.756
120.693
0.5
30
5/24/11
CSP
39.770
120.693
0.5
30
6/6/11
0.5
30
CSP
39.770
120.674
6/11/11
LTBMU
39.017
119.950
U
27
8/17/11
LTBMU
39.250
120.077
P
2
8/18/11
LTBMU
40.250
121.077
P
3
10/3/11
CSP
39.308
120.245
U
9
4
10/4/11
NLTFPD
39.279
120.227
P
10
16
10/5/11
LTBMU
38.944
120.107
P
24
Time of
Ignition
(PST)
10:00
Harvest
Date of
Fuel
Type of
Vegetation
Duff
Depth
Site
Slope
Fuel
Moisture
Surface
wind
speed
2008
Conifer
1-3"
0-10%
9%
10 SKY
DSP
2007
9:00
2011
10/5/11
LTBMU
38.887
120.050
10/5/11
CSP
39.756
120.693
10/5/11
CSP
39.770
120.674
10/6/11
LTBMU
38.944
120.107
P
29
1.5
9:30
1
9:30
2011
10/8/11
P
LTBMU
38.887
120.050
10/10/11
CSP
39.756
120.693
3
30
10/10/11
CSP
39.133
120.163
0.5
30
10/12/11
LTBMU
38.872
120.050
41
10:00
2011
P
108
7"
40%
25%
(dead)
3
0.01"
50%
128% (live)
15
3"
10%
25%(dead)
5
0.01"
60%
125% (live)
4
0.01"
10%
125%(live)
8
30
2007
P
White Fir,
Manzanita
Ponderosa,
Jeffery Pine,
Bitterbush
10:30
9-1
White Fir,
Manzanita
Ponderosa,
Jeffery Pine,
Ponderosa,
Jeffery Pine
Table A-1 (continued)
b
Longitude
Type
of
Burn
39.276
119.939
U
13
10:00
LTBMU
38.859
120.240
U
100
7:30
10/17/11
NLTFPD
39.262
119.972
U
12
10:00
10/18/11
LTBMU
39.134
120.218
P
10/19/11
CSP
39.785
120.674
10/19/11
CSP
39.770
120.674
a
Burn Date
Agency
10/12/11
NLTFPD
10/15/11
Latitude
Burn
Area
(acres)
Tons/
Acre
Time of
Ignition
Harvest
Date of
Fuel
Type of
Vegetation
Shrub,
Conifer,
Litter
Duff
Depth
Site
Slope
Fuel
Moisture
2-3"
25-50%
Manzanita
Shrub,
Conifer,
Litter
5"
20%
10-14%
10%
(dead)
6-8"
35-50%
10-14%
2006
2
31
39.264
119.976
U
8
10:00
10/19/11
NDF
39.229
119.889
U
7
10:00
2011
38.872
120.050
10/20/11
CSP
39.785
120.674
10/20/11
CSP
39.770
120.674
P/U
32
19
5
0-10
NLTFPD1
LTBMU1
NLTFPD
LTBMU
0-10
7
10/19/11
10/20/11
Surface
wind
speed
7:00
Shrub,
Conifer,
Litter
Brush,
Mountain
Chaparral
Ponderosa,
Jeffery Pine,
Bitterbush
2-3"
35-50%
10-14%
0-10
NLTFPD2
0-4
inches
5%25%
90-100%
3-5
0.01"
25%
125%(live)
15
0-4
inches
5%25%
90-100%
3-5 TNC
2-3"
35-50%
10-14%
0-10
0.01"
50%
125%(live)
6-8"
24-45%
10-14%
18
0-10
NLTFPD3
7
10/20/11
NDF
39.229
119.889
U
10
10:00
10/23/11
NLTFPD
39.261
119.975
U
11
10:00
2011
10/25/11
LTBMU
38.887
120.050
P/U
40
8:00
10/31/11
NLTFPD
39.262
119.967
U
10
10:00
9-2
Brush,
Mountain
Chaparral
Shrub,
Conifer,
Litter
Ponderosa,
Jeffery Pine,
Bitterbush
Shrub,
Conifer
Table A-1 (continued)
b
Longitude
Type
of
Burn
38.874
120.050
P
CSP
39.770
120.693
CSP
39.756
120.693
11/2/11
CSP
39.770
120.674
11/5/11
LTBMU
39.113
120.159
2
11/7/11
CSP
39.323
120.226
11
11/7/11
CSP
39.323
120.245
11/8/11
NDF
39.172
119.937
P
11/9/11
LTBMU
38.986
119.931
P/U
11/9/11
LTBMU
38.986
119.913
P/U
11/9/11
LTBMU
38.963
119.911
P/U
11/9/11
CSP
39.191
120.133
P
1
11/9/11
NDF
38.961
119.926
P
5
11/10/11
CSP
39.323
120.226
11/10/11
CSP
39.323
120.245
11/10/11
CSP
39.756
120.693
11/13/11
NLTFPD
39.247
119.933
a
Burn Date
Agency
11/2/11
LTBMU
11/2/11
11/2/11
11/14/1
1 CSP
Latitude
39.756
Burn
Area
(acres)
120.693
Time of
Ignition
Harvest
Date of
Fuel
Type of
Vegetation
Duff
Depth
Site
Slope
Fuel
Moisture
32
18
P
Tons/
Acre
LTBMU2
7
7.5
3
10:00
30
8:00
20092010
2007
White Fir 212 inches
Lodge Pole,
White Fir,
Manzanita
0-6
inches
5%20%
3"
30%
4-6
10-30%
(dead)
3-10
20
9:30
6
7.5
3
30
8
1
Surface
wind
speed
9:00
2010
Summer
Shrub,
Hardwood
Piles N/A
15-35%
2007
White Fir,
Manzanita
6"
30%
0-15
30
11/14/11
LTBMU
39.162
120.162
P
1.44
11/15/11
LTBMU
39.133
120.163
P
26.7
11/15/11
LTBMU
39.118
120.165
P
1
11/15/11
CSP
39.756
120.693
1
30
11/15/11
CSP
39.133
120.163
2
30
10:00
9-3
18%
(dead)
8
Table A-1 (continued)
Burn Date
a
Agency
Latitude
Longitude
Type
of
Burn
b
Burn
Area
(acres)
Tons/
Acre
1
30
1
30
11/16/11
CSP
39.756
120.693
11/16/11
CSP
39.133
120.163
11/17/11
LTBMU
38.884
120.048
P
41
11/17/11
LTBMU
38.871
120.052
P
108
11/17/11
CSP
39.191
120.133
0.5
20
11/17/11
CSP
39.323
120.226
12
7.5
11/17/11
CSP
39.323
120.245
11/19/11
LTBMU
39.147
120.162
Time of
Ignition
Harvest
Date of
Fuel
2007
P
3
10:30
11/21/11
NLTFPD
39.235
120.005
P
15
0.67
9:00
11/21/11
NLTFPD
39.262
119.981
P
20
0.68
9:00
Footnotes:
a
CALFIRE: California Department of Forestry and Fire Protection
CSP: California State Park
CTC: California Tahoe Conservancy
LTBMU: Lake Tahoe Basin Management Unit
NDF: Nevada Division of Forestry
NLTFPD: North Lake Tahoe Fire Protection Department
b
U=Understory; P=Pile
9-4
2010
Summer
2010
Summer
Type of
Vegetation
Duff
Depth
White Fir,
Manzanita
6"
Conifer
Conifer
Site
Slope
20
15 35%
10 30%
Fuel
Moisture
Surface
wind
speed
15%
(dead)
7
0-15
0-15
Appendix B
Table B-1: Prescribed burns conducted in 2012
Burn
Date
a
Agency
Latitude
Longitude
Type
of
Burn
b
Burn
Area
(acres)
Tons/
Acre
Time of
Ignition
1/19/12
LTBMU
38.914
120.032
P
20
10:00
1/24/12
NDF
39.223
119.925
P
4
9:30
CTC
39.144
120.163
P
2
12.6
CTC
39.144
120.163
2
12.6
NDF
39.223
119.925
1/24/12
1/25/12
Harvest
Date of
Fuel
2011
summer
2011
2011
1/25/12
1/25/12
1/26/12
P
2
NDF
39.961
119.927
P
5
CTC
39.144
120.163
P
2
NDF
39.223
119.925
P
2
9:30
10:00
2008 2009
12.6
2011
1/26/12
1/26/12
1/30/12
NDF
39.961
119.927
P
2
CTC
39.144
120.163
P
1
NDF
39.223
119.925
P
1
CTC
39.144
120.163
P
2
9:30
10:00
2008 2009
12.6
2011
1/30/12
1/31/12
9:30
12.6
2011
1/31/12
NDF
39.223
119.925
P
1
9:30
1/31/12
NDF
39.961
119.927
P
10
10:00
2/1/12
NDF
39.223
119.925
P
2
9:30
2/1/12
NDF
39.961
119.927
P
7
10:00
9-5
2008 2009
2011
2008 - 09
Type of
Vegetation
Conifer
White Fir,
Manzanita
Jeffrey Pine,
White Fir
Jeffrey Pine,
White Fir
White Fir,
Manzanita
Duff
Depth
Site
Slope
Fuel
Moisture
Surface
wind
speed
0-20%
15%
0-30
0-20%
10 40%
<10
0-30%
<10
Conifer
Jeffrey Pine,
White Fir
White Fir,
Manzanita
<12
Conifer
Jeffrey Pine,
White Fir
White Fir,
Manzanita
Jeffrey Pine,
White Fir
White Fir,
Manzanita
<12
<10
1025%
<10
0-15%
<10
Conifer
White Fir,
Manzanita
<12
20%
<10
Conifer
20%
<12
Table B-1 (continued)
Burn
Date
a
Agency
Latitude
Longitude
Type
of
Burn
b
Burn
Area
(acres)
Tons/
Acre
Time of
Ignition
2/6/12
NDF
39.961
119.927
P
20
10:00
2/7/12
NDF
39.961
119.927
P
35
10:00
2/7/12
NDF
39.223
119.925
P
1
9:30
2/9/12
NDF
39.961
119.927
P
1
10:00
2/13/12
NDF
39.961
119.927
P
10
10:00
2/14/12
NDF
39.961
119.927
P
1
10:00
2/15/12
NDF
P
10
9:30
2/15/12
NDF
P
1
9:30
2/16/12
NDF
2/21/12
NDF
2/21/12
NDF
39.223
39.961
39.223
119.925
119.927
119.925
P
5
10:00
P
15
9:30
P
3
9:30
Harvest
Date of
Fuel
2008 2009
2008 2009
2011
2008 2009
2008 2009
2008 2009
2010 2011
2011
2008 2009
2010 2011
2011
2011
2/22/12
2/27/12
NDF
NDF
39.223
119.925
P
P
2
9:30
10
Duff
Depth
Site
Slope
Fuel
Moisture
Surface
wind
speed
Conifer
<12
Conifer
White Fir,
Manzanita
<12
Conifer
Conifer
<10
2550%
<12
0-10%
2050%
<12
Conifer
White Fir,
Manzanita
25%
<12
5%
<10
Conifer
20%
<12
Conifer
Conifer
White Fir,
Manzanita
White Fir,
Manzanita
<12
<12
25%
<10
<10
9:30
2011
Conifer
<12
2010 2011
2011
White Fir
<12
Conifer
<12
White Fir
<12
Conifer
<12
Conifer
<12
2/27/12
NDF
P
5
10:00
2/28/12
NDF
P
5
9:30
2/28/12
NDF
P
5
10:00
3/5/12
NDF
P
12
9:30
3/5/12
NDF
P
5
9:30
9-6
Type of
Vegetation
2010 2011
2010 2011
2011
Table B-1 (continued)
Burn
Date
3/7/12
3/8/12
a
Agency
Latitude
Longitude
Type
of
Burn
b
Burn
Area
(acres)
Tons/
Acre
CTC
39.111
120.161
P
4
12.6
CTC
39.111
120.161
P
2
12.6
Time of
Ignition
3/14/12
NDF
P
12
9:30
3/14/12
NDF
P
2
9:30
Harvest
Date of
Fuel
2010 2011
2011
3/15/12
NDF
P
2
10:00
3/16/12
NDF
P
7
10:00
3/20/12
NDF
P
5
10:00
3/20/12
NDF
P
2
9:30
2010 2011
2010 2011
2010 2011
2011
10:00
2008 2010
3/22/12
NDF
3/22/12
3/23/12
39.223
119.925
P
5
CSP
P
6
CSP
P
4
2009
spring
2009
spring
Type of
Vegetation
Jeffrey Pine,
White Fir
Jeffrey Pine,
White Fir
Surface
wind
speed
Conifer
<12
Conifer
<12
Conifer
<12
Conifer
<12
Conifer
<12
Manzanita
<12
38.941
120.053
P
19
9:00
10/18/12
LTBMU
38.900
119.930
P
17
8:00
CSP
39.194
120.242
P
5
30
CSP
39.193
120.131
P
3
30
10/26/12
CALFIRE
39.189
120.096
P
2
0.75
Conifer
10/29/12
LTBMU
39.134
120.161
P
1
15
Conifer
10/29/12
LTBMU
39.124
120.164
P
2
9.45
Conifer
10/30/12
LTBMU
39.134
120.161
P
1
15
Conifer
11/1/12
LTBMU
39.134
120.161
P
0.5
15
Conifer
11/1/12
NLTFPD
39.249
120.034
P
5
2
Conifer
9-7
Fuel
Moisture
<12
LTBMU
10/25/12
Site
Slope
Conifer
10/15/12
10/24/12
Duff
Depth
Aspen
8%
10
Aspen
Jeffrey Pine,
White Fir
Jeffrey Pine,
White Fir
9%
10
Table B-1 (continued)
Burn
Date
11/2/12
a
Agency
LTBMU
Latitude
39.177
Longitude
Type
of
Burn
120.143
P
b
Burn
Area
(acres)
Tons/
Acre
0.5
0.75
Time of
Ignition
Harvest
Date of
Fuel
Type of
Vegetation
LTBMU
39.142
119.920
P
14
10:00
11/6/12
NLTFPD
36.264
119.987
U
30
10:00
11/13/12
11/14/12
NLTFPD
39.250
120.035
P
8
9:00
LTBMU
39.173
120.141
P
0.25
1.26
Conifer
11/15/12
LTBMU
39.173
120.141
P
0.25
1.26
Conifer
NLTFPD
11/19/12
P
23
9:00
NDF
P
12
10:00
11/26/12
NDF
P
10
9:30
11/27/12
NDF
P
5
9:30
11/28/12
11/28/12
NDF
P
3
LTBMU
39.134
120.177
P
50
11/29/12
LTBMU
39.133
120.175
P
60
10:00
Nov
NLTFPD
39.119
119.918
P
50
9:00
12/4/12
LTBMU
38.985
119.938
P
1
9:00
12/5/12
LTBMU
39.147
119.928
P
100
8:00
P
12
9:30
12/11/12
NDF
39.272
119.964
Site
Slope
Fuel
Moisture
Surface
wind
speed
12%
5-10
10-14%
0-15
Conifer
2009
spring
11/5/12
11/16/12
Duff
Depth
9:30
2011
Summer
2008,
2009
Summer
2009 2010
20092010
2009 2010
2009 2010
10
Conifer
Conifer,
Shrub, Litter
2-3"
Brush
0-15
Shrub,
Conifer
0-15
Conifer
<12
Conifer
<12
Conifer
<12
Conifer
<12
Conifer
9-8
2004
summer
2009,
2010,
2011
Summer
2009
summer
2010
summer
2009 2010
Conifer
16%
Conifer
5-20
0-15
Conifer
10%
0-10
Conifer
8-12%
05-20
Conifer
<12
Table B-1 (continued)
Type
of
Burn
b
Burn
Area
(acres)
Burn
Date
Agency
12/11/12
NDF
P
8
10:00
12/12/12
NDF
P
9
9:30
12/12/12
NDF
P
4
10:00
12/13/12
NDF
P
12
9:30
12/13/12
NDF
P
3
10:00
12/14/12
12/18/12
NDF
P
3
10:00
P
3
a
NLTFPD
Latitude
39.220
Longitude
120.092
Tons/
Acre
Time of
Ignition
4.2
Harvest
Date of
Fuel
2009 2010
2009 2010
2009 2010
2009 2010
2009 2010
2009 2010
Type of
Vegetation
9-9
Site
Slope
Fuel
Moisture
Surface
wind
speed
White Fir
<12
Conifer
<12
White Fir
<12
Conifer
<12
White Fir
<12
White Fir
<12
Conifer
Footnotes:
a
CALFIRE: California Department of Forestry and Fire Protection
CSP: California State Park
CTC: California Tahoe Conservancy
LTBMU: Lake Tahoe Basin Management Unit
NDF: Nevada Division of Forestry
NLTFPD: North Lake Tahoe Fire Protection Department
b
U = understory; P = pile
Duff
Depth
Appendix C
Table C-1: Fuel loads breakdown for four prescribed burns researched in this study
Burn
ID
SKY
DSP
TNC
CLC
Total Load*
(tons/acre)
28
35.6
16.7
30
Canopy
(tons/acre)
21.50
24.24
42.24
21.50
Shrub
(tons/acre)
2.53
0.74
0
2.53
Grass
(tons/acre)
0.31
0.02
0.06
0.31
Woody
(tons/acre)
9.4
33.60
11.8
9.4
*
Litter
(tons/acre)
0.88
1.22
4.84
0.88
Piles†
(tons/acre)
15
0
0
17
Total loads do not include canopy and duff.
Piles load is estimated by fire agency, whereas other loads are obtained from FCCS implemented into the FEPS model.
†
SKY
Figure C-1: Pictures of vegetation in the SKY, DSP, and TNC burn plots in fall 2011.
9-10
Duff
(tons/acre)
22.10
19.21
54.64
22.10
DSP
TNC
Figure C-1: (Continued)
9-11