memorandum
Date
January 24, 2014
To
Mohit Singh-Chhabra and Charlie Grist
Regional Technical Forum, Wood Smoke Subcommittee
From
Jonathan Dorn, Anna Belova, Jacqueline Haskell, and David Cooley
Abt Associates, Inc.
Subject
Proposed Methodology for Monetizing the Health Impacts of Wood Smoke
The project on monetizing the health impacts of wood smoke involves four distinct tasks:
 Task A: Collect Data on Sources of Emissions
 Task B: Construct Baseline Model
 Task C: Scenario Analysis
 Task D: Apply the Monetary Value of Avoiding Emissions
This memorandum will discuss the proposed methodology for completing these tasks, including
discussion of the required inputs, which are summarized in Table 4 at the end of the
memorandum.
Task A: Collect Data on Sources of Emissions
There are at least two potential sources of data that will allow Abt Associates to estimate the
baseline emissions from residential wood combustion in the Pacific Northwest: (1) the Northwest
Energy Efficiency Alliance’s Residential Building Stock Assessment;1 and (2) the Residential
Wood Combustion Tool (RWC Tool), developed by the U.S. Environmental Protection Agency’s
(EPA) Office of Air Quality Planning and Standards (OAQPS).2 This memorandum will describe
the information available from each data source and make recommendations to the Regional
Technical Forum Wood Smoke Subcommittee for the data source(s) that Abt Associates should
use to estimate wood smoke emissions in the Pacific Northwest (PNW) study area. The counties
included in the PNW study area are included in Exhibit A3.
RBSA
Ecotope, Inc. conducted the RBSA study in 2011 and the study involved field surveys of 1,404
single-family homes in the PNW study area, along with 230 manufactured homes and 321 multifamily housing units. The survey included the collection of more than 700 data points covering a
wide range of topics related to the house, including HVAC systems, lighting, appliances, and the
demographics of the occupant. Several of these data points involve wood combustion, including
1
Baylon, D., P. Storm, K. Geraghty, B. Davis. 2011. Northwest Energy Efficiency Alliance. 2011
Residential Building Stock Assessment. http://neea.org/resource-center/regional-data-resources/residentialbuilding-stock-assessment (accessed January 2014)
2
The RWC Tool has not yet been released to the public, but Abt Associates has been working with EPA to
make improvements to the tool. EPA is hopeful of issuing a public release in Spring of 2014.
3
Exhibit A available on Page 10.
whether the occupant uses a fireplace or a woodstove as the primary or secondary heating source
and the approximate amount of wood (cords or pellets) burned.
The surveys were conducted in each of the four states in the PNW study area (Idaho, Montana,
Oregon, and Washington), and the data are compiled in a Microsoft Access database.
RWC Tool
EPA developed the RWC Tool to estimate the emissions from residential wood combustion for its
National Emissions Inventory (NEI). Approximately every three years the NEI estimates the
emissions of nonpoint sources4, such as residential wood combustion, using the best available
data and methodologies. The RWC Tool is a Microsoft Access database that estimates the
number of wood burning appliances in each county in the United States in 11 different categories
(Table 1). The tool uses survey data, as discussed below, to estimate the fraction of households in
each county that use each appliance, and multiplies that fraction by the number of occupied
houses in each county.
The tool also determines the amount of wood burned (cords or pellets) by heating type (primary,
secondary and pleasure heating), then it converts this into a uniform unit of tons using countylevel data on the density of firewood supplied by the U.S. Forest Service.5 Burn rates are
estimated by applying climate zone-based adjustment factors to national average burn rates
obtained from U.S. Department of Agriculture (USDA) Forest Service documents6 describing
state residential wood consumption surveys or from more detailed state, local, or tribal (S/L/T)
agency data supplied to EPA.7 The tons of wood burned are then used to estimate emissions of 36
pollutants, including criteria pollutants and hazardous air pollutants (HAPs) using EPA-approved
emission factors.8
4
Nonpoint sources are small stationary sources of air pollution which by themselves may not emit very
much, but collectively their emissions can be of concern - particularly where large numbers of sources are
located in heavily populated areas. Nonpoint sources are also referred to as area sources and are generally
too small or too numerous to be inventoried individually.
5
Density is calculated using the U.S. Forest Service Timber Products Output data for fuel wood
consumption. Average density of fuel wood for each county is calculated by dividing total mass of fuel
wood consumed by total volume. http://www.fia.fs.fed.us/program-features/tpo/ (accessed January 2014)
6
U.S. Department of Agriculture (USDA) Forest Service, available at http://www.ncrs.fs.fed.us/pubs/
(accessed January 2014)
7
County-level climate zones are used to adjust burn rate profiles to account for the fact that less wood is
burned in warmer states. The Commercial Buildings Energy Consumption Survey (CBECS) climate zones
are groups of climate divisions, as defined by the National Oceanic and Atmospheric Administration
(NOAA), which are regions within a state that are as climatically homogeneous as possible. Each NOAA
climate division is placed into one of five zones based on its 30-year average heating degree-days (HDD)
and cooling degree-days (CDD) for the period 1971 through 2000. Burn rates for all SCCs in the national
default are multiplied by the ratio of the average British thermal unit (Btu) consumption to heat a house in
each climate zone to the average Btu consumption in climate zone 1. The ratios are 0.30 for climate zone 5,
0.44 for climate zone 4, and 0.77 for climate zone 3.
8
The emission factors for fireplaces and wood stoves are based on EPA’s AP-42 Compilation of Air
Pollutant Emission Factors. http://www.epa.gov/ttnchie1/ap42/ (accessed January 2014). Emission factors
for wood-fired furnaces and pellet stoves are from the Mid-Atlantic Regional Air Management Association
2002 Emissions Inventory. http://www.marama.org/technical-center/emissions-inventory/el-improvementsprojects/residential-wood-combustion (accessed January 2014)
2
Table 1. Wood burning appliances included in the EPA RWC Tool.
#
1
2
3
4
5
6
7
8
9
10
11
Wood Burning Appliance
Fireplace: general
Woodstove: fireplace inserts; non-EPA certified
Woodstove: fireplace inserts; EPA certified; non-catalytic
Woodstove: fireplace inserts; EPA certified; catalytic
Woodstove: freestanding, non-EPA certified
Woodstove: freestanding, EPA certified, non-catalytic
Woodstove: freestanding, EPA certified, catalytic
Woodstove: pellet-fired, general
Furnace: Indoor, cordwood-fired, non-EPA certified
Hydronic heater: outdoor
Outdoor wood burning device (e.g. firepits, chimineas)
The RWC Tool relies on data from several different surveys to determine the number of
appliances and amount of wood burned in each county. The most important survey in the tool is
the U.S. Census Bureau’s American Housing Survey.9 However, for most of the PNW study area,
the tool uses more specific local surveys for most counties. In particular, the data from Oregon
comes from the Oregon Department of Environmental Quality Residential Wood Combustion
Survey (n = 1,298),10 and the data for Washington comes from survey data supplied by the
Washington State Department of Ecology Air Quality Program (n = 1,764).11 Idaho and Montana
lack statewide residential wood combustion surveys, but there are local surveys for the counties
of Ada, Canyon, and Elmore in Idaho (n = 751),12 and for Lincoln13 and Silver Bow14 in Montana.
Counties in Idaho and Montana that do have specific county-level survey data use either the
American Housing Survey or one of the other PNW surveys as a proxy to estimate the number of
wood burning appliances and the amount of wood burned.
Comparison of RBSA and RWC Tool
The survey data used in the RWC Tool has a higher sample size for each state as compared with
the RBSA (Table 2). There is also a finer geographic resolution, as the RWC Tool has data for
each county in Oregon and Washington, while the RBSA does not necessarily have data for each
county. However, the RWC Tool does not have data for each county in Idaho and Montana, but
rather relies on proxy data from neighboring states or from the American Housing Survey.
9
U.S. Census Bureau. American Housing Survey. http://www.census.gov/programs-surveys/ahs/ (accessed
January 2014)
10
Johnson, A.B., T. Conklin, and D. Elliot. 2009. Residential Wood Combustion Survey: Results Report.
Oregon Department of Environmental Quality.
http://www.deq.state.or.us/aq/burning/woodstoves/psuReport_6_18_09.pdf (accessed January 2014)
11
Unpublished report provided to Abt Associates by the Washington State Department of Ecology.
12
Chavero, D.M. and N.E. Holobow. 2010. Residential Wood Combustion Inventory Survey: Treasure
Valley Airshed. Aurora Research Group. Prepared for Idaho Department of Environmental Quality.
13
Eagle, B. and J. Houck. 2007. Phase II of the Libby, Montana, Woodstove Changeout Program. Omni
Environmental Services, Inc. Prepared for U.S. EPA. These data are the results of a woodstove change-out
program in Libby, Montana, in which older, non-certified woodstoves were replaced with EPA-certified
stoves.
14
Unpublished report provided to Abt Associates by the Butte-Silver Bow County Air Quality Program.
3
Table 2. Sample size (n) of surveys completed in the RBSA by state.
State
Idaho
Montana
Oregon
Washington
Total
Sample Size
RBSA RWC Tool
185
751a
169
368b
314
1,298
736
1,764
1,404
4,184
a
The sample size for Idaho survey data in the EPA RWC tool only includes the counties of Ada, Canyon,
and Elmore.
b
The sample size for Montana survey data in the EPA RWC tool only includes the county of Silver Bow.
The tool also includes data from Lincoln County, but it came from the results of a woodstove change-out
program, rather than from a survey.
The RBSA has data for most of the counties for which the RWC Tool does not have survey data,
but in most cases there are not enough samples within any county to determine the rate of wood
burning at the county level with sufficient statistical power. Therefore, Abt proposes to use the
state-level RBSA data for Idaho and Montana to determine the wood burning rate for the counties
that are not covered by local survey data in the RWC Tool. Abt will use data from the singlefamily home RBSA database, and could also use data from the multi-family and manufactured
home databases, pending discussion with the RTF Wood Smoke Subcommittee. One issue is that
data are not available on the breakdown of single-family, multi-family, and manufactured homes
at the county level; only the total number of occupied units is available at the county level from
the U.S. Census Bureau. However, the Census Bureau does provide a national-level breakdown
that could be used to estimate the number of single-family, multi-family, and manufactured
homes by multiplying the national percentages by the number of occupied units in each county.
Then, data from the three RBSA databases can be used to determine the fraction of homes in each
housing category (single family, multi-family, and manufactured) that have each type of wood
burning appliance.
This fraction will then be multiplied by the number of homes in each housing category in each
county to estimate the total number of wood burning appliances in each county. This will then be
multiplied by the estimated amount of wood burned each year, and the EPA-approved emission
factors from the RWC Tool to estimate the total wood smoke emissions for the counties in Idaho
and Montana that are not covered by local survey data in the RWC Tool. The total emissions for
each state (not including the counties in the RWC Tool) will be estimated and apportioned to each
county based on the county’s percentage of total occupied housing units for all counties not
covered by local survey data in the RWC Tool.15The RBSA only contains information on
fireplaces, woodstoves, and pellet stoves. Abt will use county-level data from the RWC Tool to
fill in gaps for other types of wood burning appliances, including wood-fired furnaces, woodfired boilers, and outdoor burning devices, such as firepits.
This combination of data from the RBSA and RWC Tool will provide the most accurate and upto-date information about county-level wood smoke emissions in the PNW study area.
15
U.S. Census Bureau, American Fact Finder, available at:
http://factfinder2.census.gov/faces/nav/jsf/pages/index.xhtml (accessed January 2014)
4
Task B: Construct Baseline Model
The EPA RWC Tool and RBSA data will be used to estimate the baseline wood smoke emissions
at the county level for the PNW study area. The RWC Tool estimates emissions by estimating the
number of wood burning appliances in each county, based on the number of occupied houses in
the county, and survey data indicating the fraction of houses in each county that use wood
burning appliances.
The tool also contains survey data on the average amount of wood burned in each device in each
county. This information is used with EPA-approved emission factors to determine the total
emissions of 36 pollutants, including criteria pollutants and hazardous air pollutants (HAPs).
The result of running this tool will be a baseline level of wood smoke emissions for all counties in
the PNW study area. This will be accompanied by a memorandum explaining the methodology
and assumptions used to determine the baseline wood smoke emissions. In addition, the baseline
from the RWC Tool will be compared to the baseline wood smoke emissions in COBRA and
adjustments will be made, if necessary.
Task C: Scenario Analysis
To conduct the scenario analysis, Abt Associates will, in conjunction with the RTF Wood Smoke
Subcommittee, determine specific scenarios of wood smoke reduction levels.
There are two potential methods for conducting analysis with the wood smoke reduction
scenarios. The most straightforward approach would involve simply applying a fixed percentage
reduction to the baseline emissions in each county. This would assume that all wood burning
appliances would have the same reduction in wood smoke.
A more nuanced approach would involve applying reductions only to certain appliances. For
example, the scenario could involve reductions in smoke only from woodstoves but not from
fireplaces. To accomplish this, the inputs to the RWC Tool will be updated to reflect these
scenarios, and the tool will be run to determine the emission levels for each scenario for each
county in the PNW study area.
The specific approach used will be decided in consultation with the RTF Wood Smoke
Subcommittee. The results of the scenario analysis will be discussed in a memorandum
explaining the methodology used and assumptions for each scenario. The memorandum will also
discuss the linearity of the results of COBRA runs for each scenario, so that health benefits of
other untested scenarios can be estimated.
Task D: Apply the Monetary Value of Avoiding Emissions
COBRA is a tool that provides screening-level estimates of the impact of air pollution emission
changes on ambient particulate matter (PM2.5) air pollution concentrations, translates this into
health effect impacts, and then monetizes these impacts. Components of COBRA are: emissions
inventories, a simplified air quality model, health impact equations, and economic valuations
5
ready for use, based on assumptions that EPA currently uses as reasonable best estimates. For
each alternative scenario, county-level changes (relative to baseline emissions) in wood smoke
emissions will be entered into COBRA. Specifically, changes in PM2.5, SO2, NOx, NH3, and
volatile organic compounds are each entered separately. COBRA then conducts the analysis using
both a 3% and 7% discount rate, in accordance with OMB (Office of Management and Budget)
guidelines. Abt will present these results in the final memorandum, but the undiscounted stream
of benefits will also be presented to allow for analysis using a different discount rate.
COBRA’s air quality outputs provide the county-level changes in annual average PM2.5
concentration between the baseline emissions scenario and the control scenario, as well as the
change between the two scenarios (Delta PM2.5). For health effects, COBRA outputs the change
in the number of cases for each health effect, and the associated economic values. These changes
in the number of cases are derived using the health impact functions described in Appendix C of
the COBRA User’s Manual, while the economic valuation is described in Appendix F.16
16
The COBRA User Manual is available online at: http://epa.gov/statelocalclimate/documents/pdf/cobra2.61-user-manual-july-2013.pdf (accessed January 2014)
6
Table 3 lists the health endpoints and unit values that are used for the economic valuation of
health effects in COBRA. These values are EPA best estimates that are used in COBRA and
BenMAP17 and are discussed in Appendix F of the COBRA User’s Manual. For the present
analysis, Abt will make adjustments to the COBRA outputs to make the results consistent with
RTF’s projected population and income for 2017.
See EPA’s BenMAP User’s Manual:
http://www.epa.gov/air/benmap/models/BenMAPManualOct2012.pdf (accessed January 2014)
17
7
Table 3. Health Effects and their Economic Values ($/person).
Health Incident Avoided
Adult Mortality
Infant Mortality
Non-Fatal Heart Attacks
Hospital Admissions (Respiratory,
Cardiovascular-related)
Asthma Emergency Room Visits
Acute Bronchitis
Respiratory Symptoms (Upper, Lower)
Asthma Exacerbations (attacks, shortness of
breath, and wheezing)
Minor Restricted Activity Days
Work Loss Days
Economic Value ($2010)
3% discount rate
7% discount rate
$8,434,924
$7,512,853
$9,401,680
$9,401,680
$33,259 - $263,795
$31,446 - $253,247
$15,430 - $41,002
$15,430 - $41,002
$388 - $464
$477
$21 - $33
$388 - $464
$477
$21 - $33
$57
$57
$68
$151
$68
$151
Adjustments in Projected Population
Population projections are needed to calculate the number of cases of health effects.18 For each
county in the PNW study area, Abt will calculate the ratio of the 2017 population projections
(supplied by the RTF) to the 2017 population projections in COBRA (based on Census 2010 data
and projections by Woods & Poole Economics, Inc.). Abt will calculate these ratios based on the
relevant population for each health effect, since the health impact functions are specific to
different age groups. Abt will then multiply the number of cases for the health effect in the
COBRA outputs by the respective population projection ratios.
Figure 1, below, depicts the difference in the projected population in the PNW study area (all
counties) from these two data sources.
18
Epidemiological relationships, on which COBRA health impact functions are based, predict changes in
probability of adverse health effect as a result of exposure to air pollution. To calculate the number of cases
of adverse health effects avoided, the estimated change in probability needs to be multiplied by the size of
the affected population.
8
Comparison of 2017 Population Projections
Population (millions)
3.0
2.5
2.0
1.5
1.0
0.5
0.0
0 thru 15 thru 25 thru 35 thru 45 thru 55 thru 65 and
14
24
34
44
54
64
Older
COBRA
RTF Subcommittee Data
Age Group (years)
Figure 1. Comparison of 2017 population projects from COBRA and the RTF.
Adjustments in Income Growth
The second adjustment is for income. The unit values presented above in Table 3 are based on
published estimates of: costs of treating the illness (can include both direct medical costs and
opportunity costs of lost productivity); willingness-to-pay (WTP) to avoid the illness or to reduce
the risk of premature death (i.e., value per statistical life, VSL). The unit values based on WTP
estimates reflect expected growth in real income over time. This is consistent with economic
theory, which argues that WTP for most goods (such as health risk reductions) will increase if
real incomes increase. Empirical evidence in the US suggests that the WTP value rises at a slower
rate than real income.
The income adjustments in COBRA followed the approach used by EPA (2005, p. 4-17) and
account for real income growth between the year when a WTP study was conducted and the year
for which benefits are estimated (i.e., 2017). EPA (2005, p. 4-18) used different income elasticity
estimates to adjust the WTP for: minor health effects (0.14), severe and chronic health effects
(0.45), and premature mortality (0.40). Income growth adjustments to WTP were done using the
following equation:
WTP2017 = WTP Year of Study × (Income2017 / Income Year of Study) Elasticity
COBRA uses income growth adjustment factors supplied by EPA for the valuation of mortality
and other health endpoints.19 However, these factors are national estimates. Thus, for the analysis
of wood smoke emissions in the PNW study area, Abt will use the projected 2017 income data
See p. 113 of EPA’s BenMAP User’s Manual:
http://www.epa.gov/air/benmap/models/BenMAPManualOct2012.pdf (accessed January 2014)
19
9
(supplied by the RTF subcommittee) to generate new income growth adjustment factors. Abt will
then calculate the ratio of these new factors to the factors supplied by EPA, and apply the ratio to
obtain the unit values that reflect projected income growth for the study area.
The income adjustment will be done for the following health effects, given the type of valuation
and original study income level (and the elasticities described above): mortality, acute bronchitis,
upper and lower respiratory symptoms, asthma exacerbations, and minor restricted activity days.
(See the Appendix F of the COBRA User Manual for details on the studies and original income
levels for each health effect.)
Finally, the unit value for work loss days is based on the median weekly wage divided by 5. In
COBRA, Abt uses a national estimate of the median weekly wage in 2000$, inflated using the
Bureau of Labor Statistics’ (BLS) Employment Cost Index for Wages & Salaries in Private
Industry Workers (ECIWAG). Abt will adjust the COBRA unit values for this endpoint to use the
employment weighted-average non-farm wage across the counties in the PNW study area, using
the Real Wage Disbursement data provided by the RTF subcommittee.
Deliverables
The final deliverables will include a memorandum explaining the methodology, assumptions, and
results from the analysis of the monetary value of a reduction in wood smoke emissions,
including the establishment of the baseline using the RWC Tool and RBSA data, the specific
scenarios analyzed, and the results of the COBRA runs. The memorandum will be presented to
the RTF Wood Smoke Subcommittee prior to a presentation to the full RTF.
10
Table 4. Summary of data inputs required to monetize health effects of reduced wood smoke emissions.
Data Input
Wood Smoke
Emissions for Oregon,
Washington, Idaho
(Ada, Canyon, and
Elmore Counties), and
Montana (Lincoln and
Silver Bow Counties)
Source
EPA RWC
Tool





Reference
Idaho (Ada, Canyon, and Elmore Counties): Chavero, D.M. and N.E. Holobow. 2010.
Residential Wood Combustion Inventory Survey: Treasure Valley Airshed. Aurora Research
Group. Prepared for Idaho Department of Environmental Quality.
Oregon: Johnson, A.B., T. Conklin, and D. Elliot. 2009. Residential Wood Combustion Survey:
Results Report. Oregon Department of Environmental Quality.
http://www.deq.state.or.us/aq/burning/woodstoves/psuReport_6_18_09.pdf (accessed January
2014)
Montana (Lincoln County): Eagle, B. and J. Houck. 2007. Phase II of the Libby, Montana,
Woodstove Changeout Program. Omni Environmental Services, Inc. Prepared for U.S. EPA.
Montana (Silver Bow County): Unpublished report provided to Abt Associates by the ButteSilver Bow County Air Quality Program.
Washington: Unpublished report provided to Abt Associates by the Washington State
Department of Ecology.
Baylon, D., P. Storm, K. Geraghty, B. Davis. 2011. Northwest Energy Efficiency Alliance. 2011
Residential Building Stock Assessment. http://neea.org/resource-center/regional-dataresources/residential-building-stock-assessment (accessed January 2014)
Wood Smoke
Emissions for Idaho and
Montana Counties not
included in EPA RWC
Tool
Economic Value of
Health Effects
RBSA

COBRA
2017 Population and
Income Projections
RTF
 U.S. EPA. User’s Manual for the Co-Benefits Risk Assessment (COBRA) Screening Model.
2012. http://epa.gov/statelocalclimate/documents/pdf/COBRA_manual.pdf (accessed January
2014)
 Data supplied by RTF
Exhibit A. Counties in the PNW study area.
County
Ada
Adams
Bannock
Bear Lake
Benewah
Bingham
Blaine
Boise
Bonner
Bonneville
Boundary
Butte
Camas
Canyon
Caribou
Cassia
Clark
Clearwater
Custer
Elmore
Franklin
Fremont
Gem
Gooding
Idaho
Jefferson
Jerome
Kootenai
Latah
Lemhi
Lewis
Lincoln
Madison
Minidoka
Nez Perce
Oneida
Owyhee
Payette
State
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
ID
County
Power
Shoshone
Teton
Twin Falls
Valley
Washington
Beaverhead
Broadwater
Deer Lodge
Flathead
Gallatin
Glacier
Jefferson
Lake
Lewis and
Clark
Lincoln
Madison
Mineral
Missoula
Pondera
Powell
Ravalli
Sanders
Silver Bow
Teton
Baker
Benton
Clackamas
Clatsop
Columbia
Coos
Crook
Curry
Deschutes
Douglas
Gilliam
Grant
Harney
State
ID
ID
ID
ID
ID
ID
MT
MT
MT
MT
MT
MT
MT
MT
County
Hood River
Jackson
Jefferson
Josephine
Klamath
Lake
Lane
Lincoln
Linn
Malheur
Marion
Morrow
Multnomah
Polk
Sherman
Tillamook
Umatilla
Union
Wallowa
Wasco
Washington
Wheeler
Yamhill
Adams
Asotin
Benton
Chelan
Clallam
Clark
Columbia
Cowlitz
Douglas
Ferry
Franklin
Garfield
Grant
Grays Harbor
Island
MT
MT
MT
MT
MT
MT
MT
MT
MT
MT
MT
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
12
State
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
OR
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
County
Jefferson
King
Kitsap
Kittitas
Klickitat
Lewis
Lincoln
Mason
Okanogan
Pacific
Pend Oreille
Pierce
San Juan
Skagit
Skamania
Snohomish
Spokane
Stevens
Thurston
Wahkiakum
Walla Walla
Whatcom
Whitman
Yakima
State
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA