Evaporative Emissions from On-road
Vehicles in MOVES2014
United States
Environmental Proloclion
Agency
-------
Evaporative Emissions from On-road
Vehicles in MOVES2014
Assessment and Standards Division
Office of Transportation and Air Quality
U.S. Environmental Protection Agency
NOTICE
This technical report does not necessarily represent final EPA decisions or
positions. It is intended to present technical analysis of issues using data
that are currently available. The purpose in the release of such reports is to
facilitate the exchange of technical information and to inform the public of
technical developments.
United States
Environm«nl.»l ProlecliQn
Agency
EPA-420-R-14-014
September 2014
-------
Contents
1 Background 3
2 Test Programs and Data Collection 7
3 Design and Analysis 8
3.1 Fuel Tank Temperature Generator 9
3.1.1 Fuel Tank Temperature for Hot and Cold Soaks 9
3.1.2 Fuel Tank Temperature while Running 11
3.2 Permeation 13
3.2.1 Base Rates 13
3.2.2 Temperature Adjustment 15
3.2.3 Fuel Adjustment 15
3.3 Tank Vapor Venting 16
3.3.1 Altitude 17
3.3.2 Cold Soak 18
3.3.3 Hot Soak 31
3.3.4 Running Loss 38
3.4 Inspection/Maintenance (I/M) Program Effects 41
3.4.1 Leak Prevalence 44
3.5 Liquid Leaks 45
3.6 Refueling 46
4 Glossary of Terms 49
Appendices 50
Appendix A Notes on Evaporative Emission Data 50
Appendix B Peer Review Comments 52
Appendix C Relevant MOVES Evaporative Tables 67
-------
5 References 103
-------
1 Background
EPA's Office of Transportation and Air Quality (OTAQ) has developed the Motor Vehicle Emission
Simulator (MOVES). The MOVES model estimates emissions for mobile sources covering a broad
range of pollutants and allows multiple scale analysis. MOVES currently estimates emissions from
cars, trucks and motorcycles.
Evaporative processes can account for a significant portion of gaseous hydrocarbon emissions from
gasoline vehicles. Volatile hydrocarbons evaporate from the fuel system while a vehicle is refueling,
parked or driving. MOVES does not include estimates for emissions from non-fuel sources such
as window washer fluid, paint, plastics, and rubber. Evaporative processes differ from exhaust
emissions because they don't directly involve combustion, which is the main process driving exhaust
emissions. For this reason, evaporative emissions require a different modeling approach. In the
MOBILE models and certification test procedures, evaporative emissions were quantified by the
test procedures used to measure them:
Running Loss - Vapor lost during vehicle operation.
Hot Soak - Vapor lost after turning off a vehicle.
Diurnal Cold Soak - Vapor lost while parked at ambient temperature.
Refueling Loss - Vapor lost and spillage occurring during refueling.
For MOVES, a new approach has been adopted to model the underlying physical processes involved
in evaporation of fuels. This "modal" approach characterizes the emissions by physical modes of gen-
eration. This improvement in MOVES is consistent with significant changes made in MOVES2010
when, for example, the model diverged from MOBILE6 speed bins to vehicle specific power (VSP)
bins. Likewise, evaporative emissions can be separated by different emissions generation processes,
each having its own engineering design characteristics and failure rates. This way, certain physical
processes can be isolated, for example, ethanol (EtOH) has a unique effect on permeation, which
occurs in all the above modes. The approach used in MOVES categorizes evaporative emissions
based on the evaporative mechanism, using the following processes:
Permeation - The migration of hydrocarbons through materials in the fuel system.
Tank Vapor Venting (TVV) - Vapor generated in fuel system lost to the atmosphere,
when not contained by evaporative emissions control system.
Liquid Leaks - Liquid fuel leaking from the fuel system, ultimately evaporating.
Refueling Emissions - Spillage and vapor displacement as a result of refueling.
These processes occur in each operating mode (Running Loss, Hot Soak, Cold Soak) used in the
MOVES model. Each emission process can be modeled over a user-defined mix of operating modes,
shown in Table 1. This makes for more accurate modeling of scenarios that do not replicate test
procedures. The emission processes used by MOVES and the operating modes used for evaporative
processes are shown in Table 2.
Figure 1 illustrates the evaporative emission processes. Permeation occurs continuously through
the tank walls, hoses, and seals. It is affected by fuel tank temperature and fuel properties. Vapor
-------
Table 1: MOVES operatingMode Table
opModelD Operating mode description
150 Hot Soaking
151 Cold Soaking
300 Engine Operation
Table 2: MOVES emissionProcess Table
processID Emission process description
11 Evap permeation
12 Evap vapor venting losses
13 Evap liquid leaks
18 Refueling displacement vapor losses
19 Refueling fuel spillage
is generated by increasing tank temperature. These vapors are typically mitigated by a charcoal
canister. If the canister is saturated or there are leaks in the system, vapors can bypass the
emissions control system directly to the atmosphere. Liquid leaks can occur anywhere in the fuel
system. Moreover, refueling displaces the vapor in the tank and can also result in spillage.
Evaporative emissions are a function of many variables. In MOVES, these variables include:
Ambient Temperature
Fuel Tank Temperature
Model year group (as a surrogate for technology an certification standard)
Vehicle age
Vehicle class
Passenger Vehicle
- Motorcycle
Short/Long-haul Trucks
Fuel Properties
Ethanol content
- Reid Vapor Pressure (RVP)1
Failure Modes
Presence of inspection and maintenance (I/M) programs
Both ambient temperature and engine operation cause increases in fuel tank temperature. An
lrrhe MOVES fuel supply table provides the characteristics of gasoline sold in each county and month. For vapor
venting calculations, the MOVES Tank Fuel Generator uses the fuel supply information to account for the effects of
"comingling" ethanol with non-ethanol gasoline and for the "weathering" effect on RVP for in-use fuel.
-------
Figure 1: Illustration of Evaporative Processes
VaporA/enting
Permeation
Liquid Leaks
increase in fuel tank temperature will generate more vapor in the tank. Activated charcoal canisters
are a control technology commonly used to adsorb the generated vapor. During engine operation,
the canister is purged periodically and the captured vapor is diverted to the engine and burned
as fuel. The emission certification standards for a vehicle (associated with model year and vehicle
class) influence the capacity of the canister system. When the generated vapor exceeds the capacity
of the canister, the vapor is vented to the atmosphere. This can occur when a fuel undergoes a large
ambient temperature increase, or if a fuel with higher volatility is used, or when a vehicle canister
collects vapor for many days without purging. MOVES accounts for co-mingling ethanol and non-
ethanol gasoline, and for RVP weathering of in-use fuel. Details on the Tank Fuel Generator are
provided in the MOVES Software Design and Reference Manual.
Fuel systems can develop liquid and vapor leaks that circumvent the vehicle emissions control
system. Some inspection and maintenance (I/M) programs explicitly intend to identify vehicles
in need of evaporative system repairs. Specific states also implement Stage II programs at gas
stations to capture the vapors released during refueling. These programs capture refueling vapor
with technology installed at the pump rather than internal to the vehicle.
The model year groups for evaporative emissions are shown in Table 3. They reflect evaporative
emission standards and related technological improvements. Early control saw the introduction of
activated charcoal canisters for controlling fuel vapor emissions. Later controls included fuel tanks
and hoses built with more advanced materials less prone to allowing permeation emissions. Also,
reduction of fittings and connections became an important consideration for vapor mitigation.
Evaporative emissions are not directly affected by the combustion process, thus hydrocarbons such
as methane that are not present in uncombusted fuels will not appear in evaporative emissions.
Table 4 contains a list of the evaporative pollutants calculated by MOVES.
As shown, MOVES produces aggregate species (e.g Total hydrocarbons, Volatile Organic Com-
pounds) and specific hydrocarbon species (e.g. benzene, ethanol) which are important mobile-source
air toxics (MSATs). The MS AT emission rates are produced as ratios from the aggregate species
as documented in a separate MOVES2014 report [15] [17].
The data used for this evaporative analysis was collected on light-duty gasoline vehicles but will
also be applied to heavy-duty gasoline vehicles since heavy-duty gasoline data is not available.
-------
Table 3: Model Year Groups in MOVES
Model year group Evaporative emissions standard or technology level
1971-1977
1978-1995
1996
1997
1998
1999-2003
2004-2015
2016-2017
2018-2019
2020-2021
2022+
P re-control
Early control
80% early control, 20% enhanced evap
60% early control, 40% enhanced evap
10% early control, 90% enhanced evap
100% Enhanced evap
Tier 2, LEV II
40% Tier 3
60% Tier 3
80% Tier 3
Tier 3
Table 4: MOVES Pollutant IDs (pollutant table)
pollutantID
1
20
21
22
40
41
42
45
46
79
80
86
87
185
pollutantName
Total FID Hydrocarbons
Benzene
Ethanol
Methyl tert-butyl ether
2,2,4-Trimethylpentane
Ethyl Benzene
Hexane
Toluene
Xylene
Non-Methane Hydrocarbons
Non-Methane Organic Gases
Total Organic Gases
Volatile Organic Compounds
Naphthalene gas
NEIPollutantCode
HC
71432
1634044
540841
218019
206440
85018
123386
NMHC
NMOG
TOG
VOC
91203
shortName
THC
Benzene
ETOH
MTBE
2 , 2 ,4-Trimethylpentane
Ethyl Benzene
Hexane
Toluene
Xylene
NMHC
NMOG
TOG
VOC
Naphthalene Gas
-------
For diesel vehicles, it is assumed that there are no evaporative emission losses except for refueling
spillage. Due to the low vapor pressure of diesel fuel, diesel evaporative losses are considered
negligible.
For compressed natural gas (CNG) vehicles, we are not aware of any relevant evaporative emissions
data. CNG fuel systems and refueling procedures are significantly different from those of liquid
petroleum-based fuels. For the current release of MOVES, all evaporative emission rates for CNG
vehicles are set at zero.
We significantly updated the evaporative emission calculations and rates in MOVES2014 based
on updated emissions data, failure rates, and vehicle activity in MOVES2014. In the process
of updating the evaporative emissions, we discovered an error in the MOVES2010b evaporative
calculator that overestimated evaporative cold soak emissions by many times the intended value.
The updated evaporative data was expected to significantly increase the evaporative emissions in
MOVES2014 compared to MOVES2010b. However, due to the error in MOVES2010b, users may
observe a decrease in evaporative emissions in MOVES2014.
2 Test Programs and Data Collection
The modeling of evaporative emissions in MOVES is based on data from a large number of studies.
Over a decade of research has greatly modernized evaporative emissions modeling. New test proce-
dures provide modal emissions data that greatly advance the state of the science. For example, the
CRC E-77 test programs [20] [23] [21] [22] measured permeation emissions separately from vapor
emissions. Implanted leak testing from these studies along with further field research has provided
the first large database regarding the prevalence and severity of evaporative leaks and other mal-
functions. Discoveries from these studies are introduced in MOVES2014 with the explicit modeling
of vapor leaks. High evaporative emissions field studies used a portable test cell (PSHED) to mea-
sure in-use hot soak emissions on a large number of vehicles. The studies utilized an innovative
sampling design which recruited the higher end of emissions more heavily with the aid of infrared
ultraviolet remote sensing devices [12] [11].
Appendix A has a more detailed summary of these test programs.
-------
Table 5: List of Research Programs
Program
# of Vehicles
CRC E-9 Measurement of Diurnal Emissions from In-Use Vehicles [2] 151
CRC E-35 Measurement of Running Loss Emissions in In-Use Vehicles [19] 150
CRC E-41 Evaporative Emissions from Late-Model In-Use Vehicles [3] [4] 50
CRC E-65 Fuel Permeation from Automotive Systems [24] 10
CRC E-65-3 Fuel Permeation from Automotive Systems: EO, E6, E10, and E85 [25] 10
CRC E-77 Vehicle Evaporative Emission Mechanisms: A Pilot Study [20] 8
CRC E-77-2 Enhanced Evaporative Emission Vehicles [23] 8
CRC E-77-2b Aging Enhanced Evaporative Emission Vehicles [21] 16
CRC E-77-2c Aging Enhanced Evaporative Emission Vehicles with E20 Fuel [22] 16
High Evap field studies [12] [11] Thousands
Fourteen Day Diurnal study [28] 5
PI Leakage Study [5] Not Avail.
API Gas Cap Study [29] Not Avail.
EPA Compliance Testing [1] Thousands
3 Design and Analysis
Fuel tank temperature is closely correlated with permeation and vapor venting as observed in the
CRC E-77 pilot testing program [20]. This program tested ten vehicles in model years 1992 through
2007. The results showed that fuel temperature strongly influences evaporative emissions in all
testing regimes. Fuel tank temperature is dependent on the daily ambient temperature profile and
vehicle operation patterns. Modern vehicles (enhanced-evap, 1996 & later) do not recirculate fuel
from the engine to the fuel tank and therefore have a lower temperature rise than older vehicles
during operation. In Figure 2, the permeation emissions are plotted over a 3-day California diurnal
test (65-105°F) as the low temperature range, and 85-120°F as the high temperature range. Both
the effects of temperature and fuel volatility can be observed.
As emission standards have tightened, fuel system materials and connections have become more
efficient at containing fuel vapors. Purge systems and canister technologies have also advanced,
resulting in less vented emissions. Fuel tank temperature can be used in modeling permeation
and vapor emissions. However, liquid leaks occur regardless and therefore are not dependent on
temperature.
-------
Figure 2: Permeation Temperature and RVP effects
4500
4000
3500
* 3000
e
.9
1 2500
o.
| 2000
i
i
5 1500
1000
500
Low Temp-7 Psi
High Temp -1 Psi
Low Te mp - 9 Psi
High Temp-9 Psi
10
20
30 40 50
Test Time- hours
60
70
3.1 Fuel Tank Temperature Generator
MOVES calculates fuel temperature (also referred to as fuel tank temperature) for a given ambient
temperature profile and vehicle trip schedule based on the vehicle type and model year. Different
equations are used depending on the operating mode of the vehicle: running, hot soak, or cold soak.
Fuel tanks are warmer during running operation than the ambient temperature. The routing of hot
exhaust, vehicle speed, and airflow can all affect tank temperature. Immediately after the engine
is turned off, the vehicle is in a hot-soak condition, and the fuel tank begins to cool to ambient
temperature. In cold soak mode, the vehicle has reached ambient temperature.
Input parameters for the fuel tank temperature generator are:
Hourly ambient temperature profile (zoneMonthHour table)
Key on and key off times (sampleVehicleTrip table)
Day and hour of first KeyON (hourDay table)
Vehicle Type (Light-duty vehicle, Light-duty truck, Heavy-duty gas truck)
Pre-enhanced or enhanced evaporative emissions control system
3.1.1 Fuel Tank Temperature for Hot and Cold Soaks
Equation 1 is used to model tank temperature as a function of ambient temperature.
dt
(1)
-------
IVarafc is the fuel tank temperature, Tair is the ambient temperature, and A; is a constant proportion-
ality factor (k = 1.4 hr"1, reciprocal of time constant). The value of k was established from EPA
compliance data. Compliance data was available on 77 vehicles that underwent a 2-day diurnal test
and had a 1-hour hot soak (See Appendix A). No distinction was made between hot and cold soak
for this derivation. We assume that during any soak, the only factor driving change in the fuel tank
temperature is the difference between the tank temperature and the ambient temperature.
This equation only applies during parked conditions, which include the following time intervals:
From the start of the day (midnight) until the first trip (keyON)
From a keyOFF time until the next keyON time
From the final keyOFF time until the end of the day
For more information on the activity data used to determine the time of keyOn and keyOff events,
see the MOVES technical report [16] and supporting contractor reports [32] [33]. The activity
information is in the process of being updated for the next version of MOVES.
Mathematical steps:
1. At time to = 0 or KeyOFF (start of soak), TTank = Tj. This value will either be the ambient
temperature at the start of the day, or the fuel tank temperature at the end of a trip.
2. Then, for all t >0 and KeyOFF, the next tank temperature is calculated by integrating
numerically2 over the function for temperature change, using Equation 2
(TTank)n+l = TTank + k(Tair Tyarafc)At (2)
where:
T^Tank = Tank temperature
Tair = Ambient air temperature
t = Time
k = Temperature constant
Figure 3 demonstrates the Euler approximation for calculating the tank temperature based on
ambient temperature.
2Numerical integration is used to perform this step using the Euler method, one of the simplest methods of
integration. The smaller the time step At, the more accurate the solution. MOVES uses a At of 15 minutes, which
is accurate enough for our modeling purposes without causing tremendous strain on computing resources.
10
-------
Figure 3: Example Day Modeled with Euler Method
85 i
80 -
75
S
Q.
70 -
65
60
>Calculated Tank
Temperature
Ambient Temperatu re
10
14
18
Hourof Day
22
3.1.2 Fuel Tank Temperature while Running
Vehicle trips are short compared to the length of the day. Therefore, we assume a linear temperature
increase during a trip to improve model performance with minimal compromise to accuracy.
In this algorithm, we initially calculate the tank temperature increases over a period of 4,300
seconds (1.19 hr), which is the duration of the certification running loss test. To determine ATtorafc,
tank temperature, we must first find ATtorafc95, the average increase in tank temperature during
a standard 4300 second, 95°F running loss test. The algorithm models the increase in fuel tank
temperature using the tank temperature at KeyON time, the amount of running time, and the
vehicle type and technology. Newer technologies are able to reduce the heat transferred to the fuel
tank. The MOVES ATtorafcg5 temperatures are as follows:
If the vehicle is pre-enhanced (pre-1996), vehicle type affects ATtorafcg5: [19]
LDV ATtorafc95 = 35°F
LDT ATtorafc95 = 29°F
If the vehicle is evap-enhanced (1996+):
ATtorafc95 = 24°F
These values are used to calculate the ATtorafc for starting fuel tank temperatures using Equation
3.
ATTarafc = 0.352(95 -
-Tank,KeyON)
AT-
TankQ5
(3)
The parameters in Equation 3 are derived from regression analyses of light-duty vehicles driving
the running loss drive cycle with varied starting temperatures [9]. The lower the initial tank tem-
perature, the larger the increase over a given drive cycle. The average ratio of fuel temperature
11
-------
Figure 4: Modeled Vehicle Tank Temperature During a Day of Operation
120
110
cr 100
M>
UJ
2,
0)
= 90
80 -
Ambient Temperature
Hot Soak Operation
Running Operation
60
-1
14
19
24
Hour of Day
increase to initial fuel temperature is -0.352. This gives us the increase in tank temperature so we
can create a linear function that models fuel tank temperature for each trip.
where:
Tank
4300/3600
(t tkeyON) + TTank,KeyON
(4)
Tank temperature
Time
Time of engine start
The 4300/3600 in the Equation 4 denominator converts seconds to hours (4300 seconds in the
running loss certification test), maintaining temporal consistency in the algorithm. The resultant
tank temperatures for an example temperature cycle are illustrated in Figure 4. Running operation
is shown as a red line, and hot soak operation is shown as a blue line.
Assumptions:
The first trip is assumed to start halfway into the hour stated in the first trips HourDaylD.
The effect of a change in ambient temperature during a trip is negligible compared to the
temperature change caused by operation.
The KeyON tank temperature is known from calculation of tank temperature from the pre-
vious soak.
12
-------
3.2 Permeation
Permeation emissions are specific hydrocarbon compounds that escape through micro-pores in pipes,
fittings, fuel tanks, and other vehicle components (typically made of plastic or rubber). They differ
from leaks in that they occur on the molecular level and do not represent a mechanical/material
failure in a specific location. In MOVES, base permeation rates are estimated, and then adjusted
for non-standard tank temperature and fuel property conditions.
3.2.1 Base Rates
Permeation base rates are developed using the mg/hour emission rate during the last six hours of
a 72-96-72°F diurnal test (also known as cold soak/resting loss) The diurnal tests were measured
on the federal cycle (72F-96°F) for the CRC E-9 and E-41 programs [2] [3] [4]. Together, these two
programs represent a total of 151 vehicles with model years ranging from 1971 to 1997. The final
six hours of the diurnal are the most appropriate times to isolate the effect of permeation since
the emission rate, ambient temperature, and fuel temperature are relatively stable or constant.
Permeation should be the only evaporative process occurring. The rates are developed for distinct
model year and age groups. Model years 1996-1998 are represented individually to reflect the
20/40/90% phase-in of enhanced evaporative emissions standards. Recent data from the E-65 and
E-77 programs were not significantly different from the previous findings and served to validate the
MOVES Tier 2 permeation base rates. Tier 3 standards will be introduced in 2018, and phase in over
model years 2018-2022. The Tier 3 permeation standard reflects a 40% reduction from the previous
standard and the introduction of 10% ethanol to the certification fuel. MOVES base rates exist
as if the fuel contains no ethanol. As will be explained later in the fuel effects section, with other
factors remaining constant, the presence of ethanol increases permeation emissions approximately
twofold, therefore the resultant 0% ethanol base rate is approximately 80% less than the previous
standard. Permeation base rates for are presented in Table 6.
13
-------
Table 6: Base Permeation Rates at 72F
Model year group
1971-1977
1978-1995
1996
1997
1998
1999-2015
2016-2017
2018-2019
2020-2021
2022+
Age group
10-14
15-19
20+
0-5
6-9
10-14
15-19
20+
0-5
6-9
10-14
15-19
20+
0-5
6-9
10-14
15-19
20+
0-5
6-9
10-14
15-19
20+
All Ages
All Ages
All Ages
All Ages
All Ages
Base permeation rate [g/hr]
0.192
0.229
0.311
0.055
0.091
0.124
0.148
0.201
0.046
0.075
0.101
0.120
0.163
0.037
0.059
0.079
0.093
0.125
0.015
0.018
0.022
0.024
0.029
0.010
0.007
0.006
0.004
0.003
14
-------
3.2.2 Temperature Adjustment
The E-65 permeation study found that permeation rates, on average, double for every 18°F increase
in temperature. [24] This study tested 10 vehicle fuel systems (the vehicle body was cut away from
the fuel system, which remained intact on a frame) at 85°F and 105°F. The vehicles ranged in
model year from 1978-2001. In MOVES the base permeation rates are calculated at 72°F, the same
temperature as the certification test.
Equation 5 is derived from this study and used to adjust the base permeation rate.
P ,. R
*adj + base
Where:
= Base Permeation Rate
= Tank Temperature
= Base Temperature for a given cycle (e.g. 72° for a federal diurnal test)
3.2.3 Fuel Adjustment
Ethanol affects evaporative emissions from gasoline vehicles due to the increased permeation of
specific hydrocarbon compounds through tanks and hoses. This behavior highlights a key MOVES
feature to account for independent fuel effects for each unique emissions process.
Permeation fuel effects were developed from the CRC E-65 and E-65-3 programs, which measured
evaporative emissions from ten fuel systems that were removed from the vehicles and filled with EO,
E5.7, and E10 fuels. This method assures that the emissions measured are purely from permeation
(assuming the systems were not leaking). Additional data was provided from the CRC E-77-2 and
E-77-2b programs, which measured evaporative emissions from sixteen intact vehicles. For this
analysis, vehicles certified to enhanced-evaporative and Tier 2 standards are analyzed separately
from vehicles certified to earlier standards. Enhanced evaporative standards were phased in from
1996-1999 and imposed a 2.0 gram standard over a 24-hour diurnal test. Standards previously in
effect applied a 2.0 gram standard to a 1-hour simulated diurnal.
The ethanol effect is estimated with a mixed model developed in this report. The evaporative
certification level, ethanol content, and RVP were modeled as fixed effects and the particular vehicle
modeled as a random effect. The natural logarithm of the emission rates over the 65-105-65°F
diurnal cycle provided a normally distributed dataset to the model. The dataset was not large
enough to find a significant effect for three ethanol levels within each evaporative certification bin.
Therefore, E5.7 and E10 test results were binned into one category of ethanol-containing fuel.
Ethanol was then seen to have a significant effect compared to EO fuel. The percent difference
between the ethanol rate and the EO rate is used in MOVES as the fuel adjustment. Due to the
enhanced-evaporative certification standards phase in from 1996-1999 (20/40/90/100%), the two
fuel adjustments must also be phased in for those model years. The fuel adjustment in MOVES is
based on a variable called fuelModelYearlD. Table 7 lists the fuel adjustments used for E5 through
E85 for the fuelModelYearlDs used in MOVES.
15
-------
Table 7: Ethanol effect for Permeation Emissions
Model Years Percent increase due to ethanol
f995 and earlier 65.9
f996 75.5
f997-2000 107.3
200f and later 113.8
There is additional information regarding permeation emissions in the final releases of the CRC E-
77-2b and E-77-2c studies that may be used to update the permeation estimates in future versions
of MOVES.
3.3 Tank Vapor Venting
Vapor generated in the tank can escape to the atmosphere during a process labeled Tank Vapor
Venting (TVV). Hydrocarbons emitted by this process originate from a variety of sources. As tank
temperature rises and vapor is generated within the tank, the vapors are forced out of the tank
from increased pressure. Fully sealed gas tanks are rare as they must be constructed with metal to
prevent bloating. Using metal as a tank material can be expensive, heavy, and difficult to shape
into tightly packed modern vehicles. Instead, most vehicles are equipped with an activated charcoal
canister to adsorb the vapors as they are generated. Later, the vapors are consumed as they purge to
the engine (through the intake manifold) during vehicle operation. The canister is open (or vented)
to the atmosphere to prevent pressure from building within the fuel system. Consequently, if the
engine is not operated for a long period of time (several days), fuel vapors can diffuse through the
charcoal, or even freely pass through a completely saturated canister. Tampering, mal-maintenance,
and system failure can result in excess evaporative emissions. Inspection and maintenance (I/M)
programs can also influence how leaks and other problems are controlled over the life of a vehicle.
Integral to the understanding of Tank Vapor Venting (TVV) is the calculation of Tank Vapor
Generated (TVG). Tank vapor generated depends on the rise in fuel tank temperature (F), ethanol
content (vol.%), vapor pressure (RVP, psi) and altitude. Calculations in MOVES use the Wade-
Reddy equation for vapor generation.
TVG = AeB*RVP(eCT*-eCTi) (6)
Where:
TI = Initial temperature
Tx = Temperature at time x
In Equation 6, coefficients A,B,C vary by altitude and fuel ethanol content. These coefficients are
shown in Table 8.
16
-------
Table 8: TVG Constants for Equation 6
EO Gasoline E10 Gasoline
Constant Sea Level Denver alt. Sea Level Denver alt.
A
B
C
0.00817
0.2357
0.0409
0.00518
0.2649
0.0461
0.00875
0.2056
0.0430
0.00665
0.2228
0.0474
The vapor venting emission process occurs during all three operation modes: running, hot soak,
and cold soak. While running, vapors are generated as the fuel system is warming and active.
During hot soak, vapor generation is caused by latent heat transfer due to fuel recirculation and
other convective processes. Cold soak vapor generation is concurrent with ambient temperature
increases.
3.3.1 Altitude
Evaporative vapor generation is affected by the lower ambient pressure at high altitudes. MOVES
accounts for this effect during the calculation of tank vapor generated. This process relies on the
coefficients found in the tank vapor generation equation (Equation 6) for differing altitudes: a high
altitude (Denver, CO) and a low altitude (Sea Level).
The MOVES database contains a binary flag for each county that determines which set of altitude
coefficients to use. This either contains L or H for low or high altitude. Characterizing altitude this
way creates a discontinuity in the calculation of evaporative emission rates.
In reality, evaporative vapor generation increases continuously as ambient pressure drops with in-
creasing altitude. Counties with altitudes higher than sea level but lower than the cut-off for the
MOVES high altitude flag produce additional vapor not accounted for in MOVES2010, shown in
Figure 5.
Update to MOVES Altitude Correction The tank vapor generated process has been up-
dated from MOVES2010b to calculate evaporative emissions at all altitudes. A linear interpolation
between sea level and Denver is performed to account for additional vapor generated between the
low and high altitude equations. For counties with an altitude greater than that of Denver, an
extrapolation is performed to calculate the additional vapor generation at higher altitude. This
interpolation and extrapolation is show in Figure 5.
17
-------
Figure 5: Illustration of Vapor Generation by Altitude
Interpolation
accounts for most
of the'missing'
vapor
OJ
c
m
(D
o
Q.
Altitude
3.3.2 Cold Soak
Cold soak vapor emissions occur while a vehicle is not operating and the engine and fuel system have
cooled to ambient temperature. Emissions occurring under these conditions are also referred to as
diurnal emissions. MOVES2014 introduces the modeling of multiple-day cold soaks and leaks. As a
vehicle sits through multiple diurnal cycles, the carbon canister accumulates vapor every day. It can
only adsorb vapor until it reaches its capacity; then it begins to vent to the atmosphere. A canister
with degraded/damaged carbon may have reduced capacity, and eventually every canister will vent
to the atmosphere once it reaches saturation. During cooling hours, a canister back purges to the
fuel tank and regains some capacity. Then, during the subsequent warming period the canister is
re-filled with vapor and any vapor generated beyond capacity will escape to the atmosphere.
The history of inventory quantification started with the measurement of emissions based on a stan-
dard regulatory test cycles. Examples included the FTP (tailpipe), 2 day diurnal/running loss test
procedures (evap) etc. Over the years, as the emissions levels over the test cycles became more
controlled with added technologies, there was concern over off-cycle emissions that occur outside
of the constraints of the test procedure. In MOVES2010, the model incorporated modal vehicle
specific power (VSP) rates based on physical and causal mechanisms for tailpipe emissions forma-
tion. The higher VSP bins in this load-based model were designed to capture off-cycle emissions.
In this updated model, we attempt to quantify the evaporative emissions from off-cycle evaporative
events, which we believe have the potential to significantly impact the emissions inventory. Off-cycle
evaporative emissions occur during deviations from certification temperature ranges or fuel RVP,
and also include multiple day diurnals emissions when a vehicle sits for longer than two or three
days.
18
-------
Figure 6: Multiday Vapor Accumulation in Charcoal Canister
Empty warming cooling warming cooling
Canister Day 1 Day 2
warming cooling
Day 3
Figure 6 illustrates the dynamic behavior of vapor within a charcoal canister over three days of
continuous cold soaking. During the first day, vapor accumulates within but does not exceed the
canister capacity. During the cooling period of day 1, we observe backpurge when some of the fuel
vapors that were previously adsorbed to the charcoal flow back into the cooling tank. The fresh
air is drawn in through the canister vent while the vapor condenses in the tank during the cooling
portion of the cycle. During warming on day 2, we see generated fuel vapors that exceed the canister
capacity (though some canisters may be constructed to hold more than 2 days of vapor). These
emissions are lost to the atmosphere, and only what remains in the canister can be backpurged
during the subsequent cooling cycle. In day 3, more vapor is generated and consequently lost to the
atmosphere. Any additional days without engine purge during normal driving (i.e. inactivity) will
exhibit the same behavior as day 3. It should be mentioned that plug-in hybrid electric vehicles
that are mainly driven on short (electric only) trips, may also exhibit similar breakthrough over
time. However, modeling of these vehicles is beyond the scope of this effort at this time as the
penetration rates of these technologies are quite low, and we are not aware of any multi-day diurnal
data collected on PHEVs.
Modeling a fleet of vehicles involves a diverse population of canisters with differing capacities. A
given amount of vapor will be fully contained by some vehicles but exceed the canister capacity
in others. Figure 7 demonstrates the methodology for calculating the vapor vented (TVV) as a
function of the vapor generated (TVG). Several factors accommodate this modeling approach. The
importance of each variable will be explained along with relevant data sources and analysis. The
following variables are included in the MOVES default database in the 'cumTvvCoeffs' table:
Back Purge Factor
Average Canister Capacity
Tank Size
19
-------
Tank Fill Fraction
Leak Fraction
Leak Fraction IM
TVV Equation
Leak Equation
Back Purge Factor The back purge factor is the percent of hydrocarbon vapor that is desorbed
from a vehicle's canister during cooling hours. Pressure decreases within the tank, drawing ambient
air in through the canister vent. In the real-world, this process occurs nightly as temperatures cool
and restore some canister capacity. In the Multiday Diurnal Study [28], test vehicles soaked for 14
consecutive 72°F-96°F diurnals (the Federal Test Procedure temperature cycle). During this time,
the vehicle canister mass was measured continuously. During the cooling period, the measured mass
of the vehicle canisters decreased. This cyclical effect can be observed in Figure 8.
An average value of 23.8% backpurge was developed from these results and is used in the MOVES
model. For example, a vehicle canister with 100 grams of hydrocarbons will backpurge 23.8 grams
and begin the next day with 76.2 grams. A more complex model for backpurge was considered
(similar to vapor generation), but would require a large computation demand and potentially slow
model performance considerably. As diurnal temperatures are more or less symmetrical, heavy
modeling on the front end (vapor generation) has already provided a high level of precision to the
back end, justifying a simpler model.
Average Canister Capacity The canister capacity reflects how much vapor generated in the
tank can be contained by the canister before breaking through. To calculate a sales-weighted average
canister size, we used sales data [6] and EPA evaporation certification data [1]. Certification data
includes the evaporative family code which contains the Butane Working Capacity (BWC) of the
canister. It is found in digits 7, 8 and 9 for enhanced evap vehicles, and in digits 5, 6 and 7 for
pre-enhanced vehicles. The BWC represents the ability of a canister to capture butane vapor, rather
than gasoline vapor, so it must be adjusted by a factor of 0.92 [26]. Exact matches between sales-
data and cert-data are not possible for every vehicle make/model. Fortunately, canister size tends
to correlate closely to tank size as onboard refueling vapor recovery (ORVR) also influences canister
design. Since tank size is much more readily available information, an average tank-to-canister ratio
for each model year is used for top-selling vehicle models with incomplete information.
TVV
Figure 7: Vapor Vented Curve
Average Canister
Capacity
^ ^ ?. ^!?. [9. 4 § f1.
Day 2 Breakthrough
fWHItiSBSiSSS?
Day 1 Breakthrough
TVG
20
-------
Figure 8: Vehicle X Canister Mass, 14-day Diurnal Test
150-
03
03 03
0 S,
^ a
0-
Legend
^llORVPfuel
9 RVP fuel
SHED Temperature
5000
15000
10000
Test Time (Minutes)
Table 9: Average Canister Capacity by Model Year
20000
Model Year Group
1960-1970
1971-1977
1978-1995
1996
1997
1998
1999-2003
2004
2005
2006
2007
2008
2009
2010+
Average Canister Capacity (grams)
0
64.7
72.8
78.7
83
115.4
122.9
145
150.7
145.3
142.9
138.6
136.2
137.5
Data is only available for model years 1990-2010. For years beyond 2010, the 2010 average canister
capacity was used. Evaporative control was introduced in 1971, so for model years 1971-1989, a
linear extrapolation is drawn backwards to 1971 through model years 1996-1990. The calculated
average canister capacities for cars and trucks combined are listed in Table 9. A peak in average
21
-------
Table 10: Sales-Weighted Average Fuel Tank Size
Model Year Group
1960-1970
1971-1977
1978-1995
1996-1997
1998
1999-2003
2004
2005
2006
2007
2008
2009-2030
HD Vehicles
Tank Size (gal)
28
27.3
18.6
19.1
19.5
19.9
20.5
20.3
20
19.7
19
19.1
38
canister size at model year 2005 corresponds to greater sales of cars with larger fuel tanks.
Tank Size The average tank size for a given model year is an important facet of the vapor
generation calculation because a larger tank will have more space in which vapor can accumulate.
Both sales data [6] and tank size information [13] were required to calculated a sales-weighted
average tank size for model years 1990-2010. For this analysis, car and truck sales, and tank sizes
were combined. For vehicles with multiple styles (i.e. different cab sizes on pick-up trucks) with
different tank sizes, the average available tank size was used as sales information is unavailable
by style. Data sources only span from 1990-2010, so past and future values must be projected.
Vehicles in the 1990-2010 range have tanks with an average capacity of 1.25 times greater than a
calculated 300 mile range, so this ratio is applied. Fuel economy becomes sufficient to estimate tank
size, for which we have data to 1975 [14]. Vehicles pre-1975 use the 1975 fuel tank size. For future
vehicles, tank size is assumed to stay constant from 2010 on. It is also possible that manufacturers
will maintain range constant with a decreasing fuel tank, this will be updated in future versions to
account for changes in consumer behavior and vehicle production. The calculated sales-weighted
tank sizes are in Table 10.
Tank Fill Fraction The tank fill fraction is an important input used in calculating tank vapor
generation. The more vapor space above the liquid fuel, the more capacity there is for vapors to
accumulate. The average tank fill fraction used in the model is 40% fill. This is a typical fill level
for certification procedures and many of the test programs from which our data originates. It is
also a figure supported by existing research on tank filling behavior by consumers [8].
Leak Prevalence In order to accurately quantify emissions from leaking vehicles, one must not
only estimate emission rates from leaks of various sizes, but also the frequency of occurrence or the
22
-------
prevalence of leaks in the fleet. This corresponds to an emissions rate and its corresponding activity.
Our estimates of leak prevalence are informed by the analysis of a field study which took place at
the Ken Caryl IM Station in Denver, CO during the summer of 2009 [11]. In this study, a remote
sensing device (RSD) was used to recruit high emitting vehicles which were then measured in a
Portable Sealed Housing for Evaporative Detection (PSHED). The vehicle's hydrocarbon emissions
were measured over 15 minutes during hot-soak conditions, and vehicles were inspected to identify
the cause/source of the leaks when possible. The set of hot-soak measurement from individual
vehicles, with inverse-probability sampling weights and solicitation response weights applied to all
vehicles, allows the prevalence of leaks in the fleet to be estimated.
We have defined a vapor leaker as any vehicle that would fail the enhanced evaporative standard
of 2 grams. The standard sums the emissions from the worst day of a 3-day diurnal test and the
hot soak. To develop a surrogate standard for a 15-minute hot soak test, we used knowledge of
certification testing to attribute 0.4 grams (g) of the 2g standard to the hot soak portion, and 76%
of 0.4 g to the first 15 minutes of the hour-long hot soak test. This approach suggests that 0.3 g
can be taken as a surrogate standard for a 15 minute hot soak.
Figure 9: Prevalence of Vapor Leaks above a given Threshold in the 2009 Ken Caryl Fleet
100
0-
Denver, CO 1 2
Sea Level 0.71 1.42
Model Year Group
1961-1970
1971-1980
1981-1995
1996-2003
2004-2010
5 10
3.55 7.09
Vapor Leak Size
(g/15min)
20
14.18
50
35.46
100
70.92
Table 11 (Plotted in Figure 9) displays leak prevalence at various emission thresholds for what
constitutes a "leak". Observing the difference between any two points determines how many vehicles
fall into a particular range. Looking at Table 11, in model year group 1981-1995, 2.6% of vehicles are
leaking at more than 20 grams and 4.2% of vehicles are leaking at more than 10 grams. Subtracting
these two values yields that 1.6% of vehicles in the model year group have a leak between 10 and
20 grams.
The data only contain prevalence rates for PSHED measurements as low as 1.0g/15min. Failure
rates are extrapolated to 0.3g/15min. Using aggregate data from the Ken Caryl station, it is
found that 0.3g/15min PSHED measurements are 50% more prevalent than 1.0g/15min PSHED
measurements.
23
-------
Table 11: Prevalence of Leaks above a given Threshold (g/15min)
Model Year Denver 100
Sea Level (MOVES) 70.9
1961
1971
1981
1996
2004
- 1970
- 1980
- 1995
- 2003
- 2010
0
0
0.004
0
0
50
35.5
0
0
0.004
0
0
20
14.1
0.53
0
0.026
0
0
10
7
0.53
0.3
0.042
0.02
0
5
3.6
0
0
0.
0.
.68
.85
083
021
0
2
1.4
0
0
0.
.68
1
.22
029
0
1
.7
1
1
0.26
0.033
0
0.3
.2
1
1
0.39
0.064
0
Because the data used to estimate leak prevalence was collected in Denver, Colorado at an altitude
of 5,280 feet above sea level, measurements must be adjusted to sea level. At sea level, the amount
of vapor generated will be less due to higher atmospheric pressure. To determine the appropriate
correction factor, we performed the Wade-Reddy calculation and found that under identical condi-
tions, the higher altitude will generate 41% more vapor. Colorado is a strategic location to perform
a leak quantification program because a given vapor leak will produce higher levels of emissions at
a higher altitude, therefore making it easier to detect. Each of the leak magnitude bins have been
corrected for altitude by this factor. For example, the prevalence of leaks at lg-2g levels in Denver
will be the same prevalence of leaks at .71g-1.42g levels at sea level.
Because this was a cross-sectional study, many model year and age group combinations are not
possible to measure, yet must exist in the model. A set of linear regressions is used to model vapor
leak prevalence for ages and model years where data is not available. We divide model year groups
in years when new technologies or standards were introduced. Modeling is based on the assumption
that newer cars will have lower leak prevalence than older cars due to the advancing technology and
use of more durable materials. Therefore, data from the 1996-2003 model year group is used as a
surrogate for new vehicles in the 1971-1980 and 1981-1995 model year groups. However, because
vapor leaks also occur due to tampering and mal-maintenance, deterioration is not the only factor
involved in occurrence of vapor leaks. The regressions from the older model year show more rapid
vehicle deterioration rates than newer model years.
Figure 10 shows the vapor leak prevalence as the percent of the vehicle fleet with a leak larger
than 0.3g/15min. For model years 1996 and later, the estimate for leak prevalence at ages 0-3 was
developed with I/M data from five states. The analysis revealed that 1-2% of vehicles consistently
arrived at I/M stations with an evap Diagnostic Trouble Code (DTC) set. The vast majority of the
DTCs set specifically indicated a vapor leak detected. The green diamonds in the 1971-1980 and
1981-1995 model year groups are an assumption made based on the 1996-2003 data to describe these
vehicles' leak rates when they were new. The slope of the 2004-2010 prevalence rates was developed
by applying the 5-10 year old 1996-2003 data point to the 10-15 year old 2004-2010 point.
Tier 3 and LEVIII Leak Prevalence To model the leak prevalence rates of LEVIII and Tier
3 vehicles, the effectiveness of improved OBD systems and the efficacy of vehicle leak testing were
quantified. In the above mentioned field study performed in Colorado, it was found that 70% of
evaporative leaks were due to deterioration of the evaporative system (e.g. corroded fuel lines, filler
24
-------
Figure 10: Non-IM Vapor Leak Prevalence, Extrapolated from data
100
1
03
1 50 H
03
25-
0-1
1961-1970
1971-1980
1981-1995
1996-2003
2004-2010
LEVIII
TierS
Data Source
11961-1970
11971-1980
1981-1995
1996-2003
lAge 4-5; 96-03 regression
OBD
5 10152025 5 10152025 5 10152025 5 10152025 5 10152025 5 10152025 5 10152025
Vehicle Age
neck, cracked hoses etc.) that could be improved with new design and material considerations. The
remaining 30% of evaporative leaks were beyond manufacturer control, (e.g. Improper maintenance,
tampering, missing gas caps, etc)
OBD effectiveness and OBD readiness are also important factors in the detection and repair of
leaks after they occur. OBD effectiveness refers to the ability of diagnostic systems to identify leaks
within the fuel system and alert the driver by illuminating a warning light. OBD readiness refers
to the time during which vehicle diagnostics are actively assessing the integrity of the vehicle fuel
system.
Our reference case assumes 40% OBD effectiveness and 95 percent OBD readiness. These numbers
are based on an assessment of vehicles with OBD-detectable leaks and whether or not the leak was
identified by the vehicle and the driver alerted via a check engine light. [36]
We estimate the implementation of LEVIII to immediately reduce the 70% of deterioration-caused
leaks by 33% simply due to the lower emissions standard. Longitudinally, we see reductions in
leak prevalence associated with lower emissions standards. We also estimate that due to improved
vehicle diagnostic systems, 80% of detectable leaks will be discovered and reported by the vehicle.
In addition, we are assuming with the increased rigor of requirements the readiness will increase to
99%.
We estimate the implementation of Tier 3 to immediately reduce the 70% of deterioration-caused
leaks by 66% due to the additional benefit of the Tier 3 leak standard. As in LEVIII estimates, we
also estimate that 80% of detectable leaks will be discovered and reported by tier 3 vehicles, as well
as an increase of 99% readiness.
These estimates result in an overall reduction of leak frequency of 26% for the LEVIII program and
49% for the Tier 3 program.
25
-------
Table 12: Emission Program Factors
Base Inputs
# of Leaks >0.020"
% Mai-Repair
% Durability
Reference Case
OBD Ready %
OBD Effectiveness
fOO
30%
70%
95%
40%
LEVIII Control Case
% of "durability" leaks prevented 33%
OBD Ready % 99%
OBD Effectiveness 80%
Tier 3 Control Case
% of "durability" leaks prevented 66%
OBD Ready % 99%
OBD Effectiveness 80%
Figure ff: LEVIII, Tier 3 Leak PRevalence Estimates
£ 80
60
c £40 -
'
0 -
ULeaks Prevented
Leaks w/ MIL on
Leaks w/MIL off
Reference LEV III Case With Tier 3
26
-------
Leak Emissions Equation In MOVES2014, leak vapor emissions are a distinct emissions mode,
separate from vapor emissions vented from the canister during normal operation. It is important
to characterize leaking emissions separately because they can potentially be orders of magnitude
higher than the other emissions modes described above. Unlike non-leak emissions, leak emissions
can be modeled as a linear function with vapor generation. In Figure 12, measured vapor emissions
are plotted on the y-axis against the calculated tank vapor generated. The average for four vehicles
is overlaid and is used as the representative leak emission rate in MOVES.
Vapor generated in the tank (TVG) is calculated using the Wade-Reddy equation, thus requiring
fuel RVP, fuel ethanol content, and temperature data. Two datasets containing this information
were used in developing leak emission rates. The E-77 suite of programs 8, 9, 10, 11 measured
high-emitting vehicles, with known fuel properties and artificially implanted leaks on the California
(65°F-105°F) diurnal cycle. In another effort, the Colorado Department of Public Health and
Environment (CDPHE) carried out a repair effectiveness program during the summer of 2010 in
collaboration with the Regional Air Quality Council (RAQC). This program [27] measured 16
vehicles with identified leaks. A 6-hour test was performed with a temperature increase of 72°F-
96°F. This effort was less resource-intensive than the full diurnal procedure and still provides the
necessary information to calculate TVG. The SHED measurements of Tank Vapor Vented (TVV)
and calculated TVG form the basis for a linear regression of TVV vs. TVG for each vehicle. The
resulting slope represents the mass of vapor vented per mass of vapor generated. The average of the
regressions becomes the leak rate for that severity bin. This approach can be observed in Figure 12.
Permeation and leak vapor emissions were indistinguishable using this testing procedure. However,
permeation for these vehicles is assumed to be negligible during the 6 hour test given the severity
of the leak emissions. In the E-77 program, TVV emissions were collected in a canister external to
the SHED. The external canister was connected to the vent on the vehicle canister. No permeation
was included in the measurement.
Because the emissions measured are highly variable, spanning several orders of magnitude, the
emissions data for leaking vehicles are binned by magnitude. Accordingly, both emission rates and
prevalence are calculated within these bins. As the leak prevalence estimates were measured at
high altitude in Denver, it is essential to develop adjustments to apply the binning process at lower
altitudes, such as sea level. Application of Equation 6 suggests that an E10 fuel in Denver generates
1.41 times as much vapor as at sea level. For example, a vapor leak at 0.3g/15min in Denver would
have an equivalent rate of 0.21g/15min at sea level. The bins used to categorize leak severity as
well as the average leak emission rate for that bin are listed in Table 13.
Each data point is binned by its hot soak measurement from the E-77 programs or PSHED (Portable
Table 13: Leak Emission Rates by Bin
Denver bins (g/15min) Sea Level bins (g/15min) Grams vented / Grams generated
0.3 - 2 0.2 - 1.4 0.12
2-5 1.4 - 3.6 0.27
5 - 10 3.6 - 7.1 0.65
>10 >7.1 1.33
27
-------
Figure 12: SHED Leak Emissions for one Severity Bin
V Veh3
Calculated Tank Vapor Generated (g)
70
SHED) measurement from the Denver program. The PSHED tests are 15 minute hot soak mea-
surements.
Figure 13 illustrates the leak emission rates for each leak severity bin. The average emission rate for
vehicles with 15-min hot soak measurements greater than lOg exceeds 1. It is possible to measure
more fuel vapor in the SHED than is calculated with Equation 6. It is known that the equation
is less reliable at higher temperatures. Also, complicated factors such as fuel sloshing and tank
geometry can influence vapor generation beyond the estimation capabilities of the Wade-Reddy
equation.
28
-------
50 -
40 -
|30 -
o
Q.
£20
10 -
Figure 13: Leak Emission Rates by Leak Severity Bin
Leak Severity
Bin (g/15min)
10+
5-10
2-5
0.3-2
Tank Vapor Generated
30
35
Estimation of Tank Vapor Vented For normally operating non-leaking vehicles, tank vapor
vented (TVV) from the canister is calculated. This quantity of vapor is calculated with Equation
6 in g/gal-headspace. The model uses tank size and tank fill to calculate the headspace volume
for a given vehicle. This information allows calculating the total vapor generated inside the tank.
Equation 7 is the final calculation of TVG, where a, b, and c are the appropriate coefficients.
TVG = (aeb(RVP\ect2 - ectl)) * (tankSize * (f - tankFill))
(7)
With TVG as an input, the TVV equation estimates the amount of vapor vented. During a model
run, MOVES20f 4 calculates vapor vented for consecutive days. The algorithm accounts for average
canister capacity (ACC) and backpurge factor. Daily backpurge removes fuel vapors from the
canister, increasing capacity to store vapor generated during successive days. Vapor generated
above the ACC is lost to the atmosphere, therefore backpurge only applies to what remains in the
canister.
IfXn < ACC, thenXn+1 = ((1 - backpurgeFactor) * Xn) + TVG
IfXn > ACC, thenXn+l = ((I - backpurgeFactor) * ACC) + TVG
(8a)
(8b)
In Equation 8a, Xn represents the TVG on Day n. The conditions in Equation 8a will determine the
vapor generated for each day until n=5. To maintain model performance, emissions are calculated
for a maximum of five successive days. Beyond five days, the algorithm assumes that breakthrough
has occurred and that behavior over additional days has stabilized. The vapor emissions are fleet
averages by model year group. Emissions rise as more vehicles are exceeding their canister capacities
and begin venting fuel vapors. The development of the emission rates is covered in greater detail
in the DELTA report. [7]
29
-------
Activity Vehicles in MOVES2010 have trip and soak activity data for one day. However, as we
have shown, diurnal evaporative emissions are dependent on the number of consecutive days soaking.
In order to properly account for these off-cycle emissions, MOVES must account for the different
emissions rates of short (several hours) and long (multiple day) soaks. Because MOVES20f 0 only
simulates activity for a single day, the fraction of vehicles soaking since midnight on a typical day
includes vehicles having soaked for one or more days. As vehicles begin starting throughout the
day, the soaking population dwindles until only a small fraction remains soaking at the end of the
day.
For any modeled day, there is a sub-population of vehicles exhibiting Ist, 2nd, 3rd, nth day diurnal
emissions. The fractional allocations for Ist, 2nd, 3rd, uth day diurnals are calculated from the
sampleVehicleTrip and sampleVehicleDays tables in MOVES. SampleVehicleTrip assigns numbers
of first starts during each hour of the day. For the fraction of vehicles having soaked since at
least midnight, the first engine start ends the cold soak episode. SampleVehicleDay contains the
population of vehicles for each sourceTypelD. Combining information for both tables, it is simple
to calculate the fraction of vehicles having soaked since midnight at any given hour. For example,
at 1:OOAM, some fraction of vehicles less than 100% have not yet started. The fraction continuously
decreases throughout the day as more and more vehicles start. At 12:OOAM, the fraction only
represents vehicles that were not driven.
Once the fraction of vehicles soaking at a given hour has been calculated, it must be estimated
how many prior days each has been soaking. We classify vehicles as Ist day, 2nd day, 3rd day,
4th day, or 5+ days. We assume that after the 5th day, vehicles will exhibit repeat emissions
since the evaporative canister will either have broken through or be in conditions that will never
cause breakthrough. Via an activity study performed by Georgia Technological University [18] and
discussions with author Randall Guensler, it was found that 16% of vehicles drive less than 3,000
miles per year. The MOVES inputs are based on the conservative estimate that 50% of these
low-mileage vehicles, or 8% of all vehicles, have been soaking for more than 5 days on any given
day.
The sampleVehicleSoakingDayBasis table establishes the fraction of vehicles soaking for 5+ days.
It contains 5 values, one for each soak day. The value for SoakDaylD 1 is the percentage of vehicles
soaking at the final hour of day 1. The product of SoakDayID=l and SoakDayID=2 is the percent
of vehicles soaking at the final hour of day 2. The product of all five values is the percent of vehicles
soaking for five days or longer.
Figure 14 presents the fraction of soaking vehicles throughout the day. The majority of vehicles
have driven the previous day, and are on their first day soaking. The fractions of vehicles on 2nd
through 4th day soaking are developed from the remainder of 1st day soaking vehicles at hour 24.
The fraction of vehicles soaking for 5 days or longer is 8% at hour 24. This method models bimodal
vehicle usage, with most vehicles being driven almost daily and the remaining vehicles being driven
more intermittently.
30
-------
Figure 14: Passenger Car soak Distribution
1.0 -
0.8 -
0)0.6
|o.4H
o
W0.2H
-------
translation cannot be made using a simple 4 multiplier due to non-linear cooling of engines and
fuel systems. Measurements made on fuels with RVP higher or lower than 9.0 psi need appropriate
corrections to estimate equivalent base values at 9.0 psi. Finally, measurements made thousands of
feet above sea level need correction for the increased vapor generation occurring at higher altitudes.
The vehicles in Colorado that participated in the studies were recruited in-situ and therefore were
subject to a wide range of leak mechanisms. It was observed that some vehicles emitting more than
50 grams in 15 minutes in the PSHED had liquid leaks present. All vehicles with a calculated 15
minute measurement greater than 50g/15min were removed from vapor leak analysis.
Vehicles in the E-77 program were tested multiple times with different fuels, whereas each vehicle
in the Colorado population was tested once. In order to not over-represent the E-77 vehicles in our
sample, one measurement from each vehicle was selected with preference given to the measurements
on 9 RVP, E10 fuels (where available).
First, it is necessary to develop a correction factor to translate 15-minute measurements to 1-hour
equivalents and vice versa. Every datum requires a 15-minute mass and a one-hour mass. Base
rates in the MOVES input table must be expressed in grams per hour; however, our method for
distinguishing leaks from non-leaks uses the 15 minute rate. Furthermore, if a measurement is
designated as from a leaking vehicle, the 15 minute measurement is used to project its rate of
occurrence in the fleet.
Existing data is used to develop this correction factor. In the E-77 suite, the cumulative time
series data for hot-soak tests on a minute-by-minute scale is readily available, enabling estimation
of vapor emissions over 15 minutes. Each set of vehicle data also contains a permeation rate. The
permeation rate is subtracted from the 15 minute hot soak measurement. The result is the assumed
vapor emissions during 15 minutes of hot soak. Similarly, hourly permeation is subtracted from
the 1-hour hot soak measurement. After compiling the 15-min and 1-hour values, the fraction of
emissions occurring in the first 15 minutes can be calculated.
All of the Denver testing programs provide similar vehicle measurements to augment the E-77
dataset. A subset of the vehicles was transported to a lab to receive a Hot Soak test. Readings
were taken at both 15 and 60 minutes.
Figure 15 serves as an illustration of evaporative emissions occurring during a Hot Soak test. Vapor
emitted by permeation is assumed to accumulate at a linear rate while vapor emissions attributed
to the hot soak accumulate rapidly following engine shutoff but more slowly as the engine cools.
Using the combined data from E-77 and Denver testing, we developed the average fraction of
emissions in the first fifteen minutes following engine shutoff. At first, it was thought that this
fraction would vary among groups of vehicles certified to different evaporative standards. However,
analysis of test results by certification groups did not seem to yield notably different results. This
analysis resulted in a single fraction developed from all available data to be applied fleet-wide.
It was estimated that 54% of emissions from a one-hour hot soak occur in the first 15 minutes.
Conversely, emissions from a 15 minute hot soak must be multiplied by 1.85 to estimate an hours
emissions.
Another correction must be applied to each measurement so that emission rates values are expressed
as though measured using fuel with a vapor pressure of 9.0 psi. This value is simply the base level
32
-------
Figure 15: Hot Soak and Permeation Illustration
Hot Soak
Permeation
15
45
60
30
Time(m)
used as a reference in MOVES. Also, fuel effects for Hot Soak emissions are developed and applied
on the assumption that the base rates reflect a fuel vapor pressure of 9.0 psi.
Results in the available datasets were measured at varying levels of RVP. Some programs recorded
RVP, while other data has no explicit RVP information. Our first step is to estimate the RVP for
all measurements that do not contain this information.
The majority of the data with unknown RVP was gathered in the summer months in locations
with available fuel survey data. The mean RVP for June through August 2010 in Denver was 8.40
RVP (standard deviation 0.20 RVP), and this value was assumed for all vehicles tested from May
through September. For non-summer months, RVP information was collected with a small subset
of the vehicle measurements. In the case of a non-summer measurement without RVP information,
the mean of all non-summer months is assumed. The mean RVP for non-summer vehicles is 10.67
(standard deviation 1.75 RVP). The testing at the Lipan station was all performed in the summer,
so the RVP of the Lipan dataset is assumed to be 8.4.
Associating an RVP value with every measurement enables calculation of corrections for altitude.
All vehicles were tested either in Colorado (Elev. = 5,130 ft) or Mesa, AZ (Elev. = 1,243 ft). Both
locations are far enough above sea-level that it would be erroneous to assume their emissions are
representative of sea-level emissions. Our approach is to solve Equation 9a for RVP (Equation )9b)
and calculate the equivalent RVP at sea level that would generate the same amount of emissions.
The E10 coefficients were used for this analysis.
RVPseaLevel =
* In
^low
TVGhi
high
* (eCi°»*Tl eCl°*T°]
(9a)
(9b)
This application requires the assumption that vapor emissions will increase/decrease proportionally
to vapor generation. As a rule, to generate the same amount of vapor at high altitude as generated
33
-------
at sea level, a fuel will have a lower RVP. Temperature values were also chosen arbitrarily for this
calculation. However, after a monte-carlo analysis of varying starting and ending temperatures, the
effect of either was found to be negligible within the conditions these vehicles are likely to experience
during testing. Therefore, temperatures TO = 60°F and Tl = 65°F were chosen for this analysis.
The Wade-Reddy equation provides no coefficients for Mesa, AZ elevation so the adjustment is a
simple linear interpolation between Sea Level and Denver elevations. For example, to solve for the
h used in Equation 9a corresponding to Mesa, Equation 10 was used.
TVGMesa = TVGL + (TVGH - TVGL) * esa
Elevation Denver
At this point in the analysis, every measurement is paired with an RVP value that would generate
the same emissions at sea level. The next step is to estimate the equivalent result as though
measured on fuel with 9.0 psi.
In order to calculate an adjustment for each measurement, the same assumptions were employed
as above. Using the same temperature values, vapor generated at the sea level RVP and at 9.0
RVP was calculated. The ratio between these two values was applied to the original emissions
measurement, in Equation lla, and becomes the base MOVES emission rate.
TVGmeasRVP =
(lib)
TT i n 7 TT i n 7 -^ * ^measRVP /-, -, \
HotSoakMovES = HotSoakMeasured* -7^777-, - (He)
1 V(j MOVES
At this point, for each measurement we have an emission rate for both 15 minutes and 60 minutes,
at sea level, and with 9 RVP fuel. There were some necessary QA steps to be performed at this
point. The result of our 15 minute emissions to 60 minute conversion and the results are plotted in
Figure 16.
As expected, the estimated hourly emissions (red circles) from the 15 minute measurements model
the measurements (blue triangles) where data at both test lengths were available.
Quality assurance checks were also performed on the emissions values before and after calculating
their equivalences at Sea Level and 9.0 psi fuel. As expected, the tests measured with higher RVP
fuels at high altitude were reduced by wider margins under the influence of the two corrections.
34
-------
Figure 16: Hot Soak Measurement Test Length
102 -
S
-i-»
e
CD
E 0
CD 10° -
3
cc
CD
^
h- 10"1 -
3
0
.c
^~
ID"2 -
A
-egend ^f**^
1 hour estimated ^^^
A Data available for both lengths *!*:* *
si*
^^r
-4>
AA^*
A 3r^
A .^^A A
A ^^r
J^ ^
; A^^
A_^^^A
^^*
*^^
A* A
A
A
"ill
10"' __,_ 1Q-J 10° 101
15 minute Measurement'^)
Figure 17: Hot Soak Measurement Normalization to 9.0 RVP
40 -
o>
§30 -
'E
LU
1
cc
0-10 -
0 -
RVP
V
T
8
9 *
10
11 . .
12
X*
13 X
14 ..* .* *
15 ^f *
,**^
^r «(
* 0*** *
,**
IT
1.0.
I.O. ..15 .20 26
Normalized Emissions (g)
30
35
After normalizing the complete dataset, it was imported into the MOVES database. In the MOVES
emission rates tables, emission rates must exist for all model year and age group combinations. As
with most cross-sectional datasets, this requires additional modeling. For example, there is no data
for 20 year old, model year 2010 vehicles, or brand new 1980 vehicles. To address this problem, we
extrapolated the emission rate values. Table 15 describes the data.
In ranges where no data could be collected, leak and non-leak measurements are extrapolated from
similar MY/age groups. In MY/age groups where very small amounts of data were collected, the
measurements are combined with similar MY/age groups. Figure 18 illustrates how to populate
35
-------
Table 15: Hot Soak Measurements by Model Year and Age
Age Group
SH
rt
!>H £<
"« S
^ o
Leak?
1961-1970
1971-1980
1981-1995
1996-2003
2004-2010
Total
0-3 4-
N Y N
1
12 3 26
12 3 27
5 6-7 8-9 10-14 15-19 20+
Y N
26
2 5
2 31
Y N Y N
6
6 36 6 53
6 36 6 59
Y N
15 46
30
45 46
Y N Y
5
8
55 8 39
55 8 52
Total
5
8
169
158
48
388
Figure 18: Measurement Averaging
Age Groups
0-3 4-5 6-7 8-9 10-14 15-19 20-99
Model Year
-------
Figure 19: Calculate Weighted Evaporative Emissions
>10g/Qhr >5g/Qhr >2g/Qhr >0.3g/Qhr <0.3g/Qhr
Non-l(
Leak Measurements measur
mean mean mean
^^^^^^j^^^^^l
X X X X
Prevalence Prevalence Prevalence Prevalence
Leak Prevalence Non-Leak Prevalence
MOVES
> Emission
Figure 20: Hot Soak Emission Base Rates (9.0 RVP at Sea Level)
20-
5-
0-
1961-1970
o oooo o o
1971-1980
'
j
")
1981-1995
8 °
o
oo
8 o
1996-2003
... *
8 Sooo °
2004-2010
Model Version
o MOVES2010
MOVES2014
« 888* ° °
j;
\
-39
W
5 10 15 20 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20 0 5 10 15 20
Vehicle Age
37
-------
3.3.4 Running Loss
Pre Tier 2 Emission Rates Running Loss emissions consist of vapor venting during vehicle
operation. Data used to develop running loss emission rates for Pre-tier 2 vehicles is from CRC
E-35 [19] and CRC E-41 [3] [4]. These two programs tested 200 vehicles with model years ranging
from 1971-1997.
For each vehicle, fuel tank temperature is calculated at the end of the running loss test using the
fuel tank temperature algorithm (See Section 3.1). The running loss test performed in E-41 was
the federal test procedure LA-4 NYCC NYCC LA-4 drive schedule, with two minute idle periods
following the first LA-4, the second NYCC, and the final LA-4.
The data is filtered/reduced such that each test meets the following requirements:
Non-liquid-leakers (emissions <137.2 g/hour323)
As received vehicles (no retests)
Fuel system pressure test result must be pass, fail, or blank
The average tank temperature is calculated by assuming a linear increase in temperature. Thus,
the average is calculated by averaging the start temperature of the test and the final temperature.
The average temperature is used to estimate the permeation rate using default permeation rates
and the permeation temperature adjustment.
Gram/hour rates are calculated by dividing total emissions by the duration of the running loss test
(4300 seconds). Permeation is subtracted for each hour to segregate tank vapor venting (TVV)
emissions. After analysis of TVV data, running loss TVV rates are separated by model year only.
Table 16 shows the results of the analysis.
An I/M effect is not observable from this data so the running loss TVV rates for I/M and non-I/M
rates are the same.
Tier 2 & Later Emission Rates Running loss emission rates for Tier 2 and later vehicles were
developed from a 2014 study on 5 Tier 2 vehicles. [34] In this study, vehicles were tested at two
fuel RVP levels (7.51psi and 10.33psi) with and without implanted vapor leaks. Vapor leaks were
installed at either the canister or top of fuel tank, and at either 0.020" or 0.040" diameters, for a
3M6.EVP.009, Section 2.4, Table 2-1
Table 16: Pre-Tier 2 Running Loss Emission Rates by Model Year and Age
Model year group TVV mean [g/hr]
Pre-1971
1971-1977
1978-1995
1996-2003
12.59
12.59
11.6
0.72
38
-------
Figure 21: Tier 2 fe Tier 3 Running Loss Rates
0.5-
S-H
^0.4 H
CD
M
(S
DH
C0.3
o
Tier 2 & Tier 3 Running Loss Rates
[JIM
[^ non-IM
Certification
2
lier 3
MQVES2Q1 Oh rate
W0.2-
00
W
So.l-
0.0-I
10
Vehicle Age
15
20
total of 4 possible leak configurations. The canister and fuel tank locations were chosen due to their
high rate of occurrence in the fleet. [27]
MOVES running loss emission rates are expressed in grams per hour and with a fuel vapor pressure
of 9 psi. Results from this testing are expressed in grams per test (4300 seconds) and at two fuel
vapor pressures (7.51 and 10.33). Therefore, the reported results must be normalized to MOVES
dimensions.
Similarly to the development of Pre-Tier 2 emission rates, gram/hour rates are calculated by dividing
total emissions by the duration of the running loss test (4300 seconds). The measurements are
then adjusted to a 9-RVP equivalent emissions measurement using the equations and coefficients
described in Section 3.3.4
Because our determination of a given vapor leak's rate of occurrence among all vapor leaks is
based on it's hot soak emissions, each running loss test was immediately followed by a standard
one hour hot soak procedure. Using the same process as in Section 3.3.3, the hour hot soak
results are multiplied by .54 to estimate the emissions at the 15 minute point. With this result,
each measurement is binned as in Table 17 and the weighted average leak emissions rate can be
determined.
Using the average non-leak value, the weighted average leak value, and the leak prevalences from
Figure 3.3.2, an average emissions rate is calculated. Tier 2 and later running loss emission rates
are the first running loss rates in MOVES to account for vapor leak emissions. The calculated rates
are shown in Figure 21.
39
-------
Running Loss Fuel & Temperature Effects Running Losses are affected by both tempera-
ture and fuel Reid Vapor Pressure (RVP). The adjustments used in MOVES20f4 are taken from
MOBILE6 and are applied to all model years and source types. MOBILE6 was run for a series of
temperatures and RVP levels for passenger cars. A linear model was fit to the MOBILE6 results.
The mean base emission rate for running losses in MOVES is located in the 'EmissionRateByAge'
table. Running loss rates were assumed to be measured at 9 RVP and 95°F. The results from MO-
BILE6 were normalized to the MOVES emission rates as multiplicative adjustments to the mean
base rates. For example, a multiplicative adjustment of 1 would be applied to a 9 RVP fuel at 95°F.
The running loss adjustments:
Are multiplicative adjustments.
Apply to all gasoline source types and model years.
Are the same at temperatures below 40°F as at 40°F.
Are applied as a function of both RVP and ambient temperature.
Will use the 7 RVP coefficients for RVP values below 7 psi.
Will use the 10 RVP coefficients for RVP values above 10 psi.
Will not be applied for RVP at temperatures below 40°F.
AdjustedRunningLoss = RunningLoss * Adjustment(Temperature, RVP) (12)
The adjustment coefficients are in a table in the default MOVES database, so that they can be
changed without altering the MOVES code. The RVP adjustment range is dynamic; if new sets of
coefficients for RVP values greater than 10 or less than 7 are added to the table, MOVES will use
those values and set new minimum and maximum RVP values. Figure 22 illustrates the correction
to base rates at 9 RVP.
40
-------
Figure 22: Running Loss Temperature and RVP Effect
1
0.7
0.6
10 RVP
9 RVP
8 RVP
7 RVP
40
50 60 70 80 90
Ambient Temperature (degrees Fahrenheit)
100
3.4 Inspection/Maintenance (I/M) Program Effects
Inspection and Maintenance program efforts vary widely in their procedures for testing evaporative
emissions. Some locations use a fill pipe pressure check and gas cap check, while others use just a
scan of the onboard diagnostics (OBD), and others will use all three approaches. These types of
tests do not guarantee the detection of a vapor leak within a vehicle.
MOVES assumes tank vapor venting is the only evaporative process where I/M benefits are realized.
The types of evaporative tests performed in I/M programs do not affect permeation or liquid leaks.
I/M Factor An I/M factor describes the overall effectiveness of an I/M program and can be used
as a basis to compare two separate programs. A higher I/M factor indicates a more effective I/M
program. Data from four I/M programs were used in the development of MOVES I/M factors.
The Phoenix, AZ program contained the most extensive data, for which reason we have used it to
represent a reference condition, relative to which other programs can be assessed. Data from the
programs in Tucson, AZ, Colorado, and North Carolina were used to adjust the Phoenix numbers
for differences in I/M programs.
NOTE: In order to develop I/M factors, failure data was used from I/M. The failure
frequencies are only used to estimate the effectiveness of differing evaporative I/M
programs. They are not used to model the actual prevalence of evaporative leaks.
For information on the modeling of leak prevalence please see Section 3.3.2.
-------
Table 17: Description of I/M Programs [31]
Gas Cap Test OBD Pressure test Frequency
Colorado
N. Carolina
Phoenix
Tucson
Y
N
Y
Y
Advisory
Y
Y
Y
N
N
Y
N
Biennial
Annual
Biennial
Annual
Network
Hybrid
Decentralized
Centralized
Centralized
Years
2003-2006
2002-2006
2002-2006
2002-2006
Table 18: OBD Evaporative Emission Trouble Codes
OBD Code Description
P0440
P0442
P0445
P0446
P0447
P1456
P1457
Evaporative Emission Control System Malfunction
Evaporative Emission Control System Leak Detected (small leak)
Evaporative Emission Control System Purge Control Valve Circuit Shorted
Evaporative Emission Control System Vent Control Circuit Malfunction
Evaporative Emission Control System Vent Control Circuit Open
EVAP Emission Control System Leak Detected (Fuel Tank System)
EVAP Emission Control System Leak Detected (Control Canister System)
The Phoenix evaporative I/M program performed gas-cap tests on all vehicles, OBD scans on OBD-
equipped vehicles, and fill-pipe pressure tests on pre-OBD vehicles. The OBD codes used to assign
evaporative failures are listed in Table 18 for all vehicle makes and additionally P1456 and P1457
for Honda and Acura vehicles. Vehicles with one or more of these faults were flagged as failing
vehicles, analogous to pre-OBD vehicles that failed the pressure test. Very few vehicles failed both
the gas cap test and the pressure/OBD test. Therefore, the total number of failures is the sum of
gas cap and pressure/OBD failures.
The I/M failure frequencies are developed from the Phoenix data using initial and final results for
a vehicle in a given I/M cycle. For passing vehicles, the initial and final tests are the same. The
initial and final failure frequencies were averaged to develop an I/M failure frequency for each model
year and age group. Using the initial failure frequencies alone would neglect the required repairs
occurring on most failing vehicles, and using only final failure frequencies would neglect the prior
existence of failing vehicles. To develop non-I/M failure frequencies, the sample is restricted to
vehicles registered in states that do not have any I/M programs.
The Tucson data was used to determine the effect of I/M program frequency (annual vs. bi-
ennial). For OBD-equipped vehicles, Tucson performs gas-cap and OBD tests annually, while
Phoenix performs them biennially. Therefore, we were able to develop for the effectiveness ratio of
Annual/Biennial programs by analyzing the Tucson data.
The North Carolina data was used to estimate the effectiveness of using the OBD scan as the
sole test in a program. In North Carolina, expansion of I/M program boundaries has led to many
vehicles being tested for the first time. These vehicles were effectively non-I/M until their first
42
-------
test. Vehicles were flagged as non-I/M tests if they were tested before the official start of the I/M
program or were registered in a new I/M county.
Failure frequencies of the non-I/M vehicles were compared to vehicles tested in I/M areas. The
I/M effectiveness of an OBD only I/M program is estimated to be a 63% reduction in failures or a
non-I/M to I/M failure ratio of f .6. This ratio was then applied to Phoenix OBD and pressure test
failure frequencies to determine non-I/M failure frequencies.
The Colorado data was used to determine the effectiveness of gas cap tests. In Colorado, the I/M
data is primarily from the Denver and Boulder metropolitan areas. However, many residents are
new to this area, having moved from non-I/M counties and states. These vehicles were effectively
non-I/M until their first test. Vehicles were flagged as non-I/M if they were registered in a state
without an I/M program, or in a non-I/M county within Colorado. Colorado OBD data was not
used, because OBD in Colorado is only advisory and does not pass or fail a vehicle.
The failure rates of the non-I/M vehicles were compared to those in the I/M fleet. The effectiveness
of a gas cap only I/M program is estimated to be a 45% reduction in failures or a non-I/M to
I/M failure ratio of 1.2. This was then applied to gas cap failure frequencies to determine non-I/M
failure frequencies.
The I/M factor in MOVES adjusts emission rates depending on the characteristics of a given
county's I/M program. Our reference program, Phoenix, has an IM factor of f. Non-I/M areas
have an IM factor of 0. The failure frequencies from the other counties are used to calculate I/M
factors for the diverse types of evaporative I/M procedures. The I/M factor is assumed to have
a linear relationship with failure frequency. Figure 23 illustrates how the I/M factor varies with
different I/M programs. Different programs fall on the line as determined by the analysis from
above, based on specific evaporative tests performed. For the vehicles in Figure 23, Tucsons OBD
and gas cap tests are annual, compared to Phoenixs biennial requirement, which gives Tucson a
lower failure frequency, thus a higher I/M factor. Colorados frequency is biennial, but their OBD
test is non-enforcing. As a result, their data shows a higher failure frequency, resulting in a lower
I/M factor.
43
-------
4.0%
Figure 23: I/M Factor, MY 1999-2003, Age 4-5
Non-l/M
Denver
Phoenix
Tucson
1.5%
0.2
0.4
0.6 0.8
I/M Factor
1.2 1.4
3.4.1 Leak Prevalence
The I/M factor is applied to the leak prevalence rates developed in Section 3.3.2 Cold Soak. The leak
prevalence rates were developed from a test program in the Denver, CO area. The MOVES default
database contains non-IM and IM emission rates that represent I/M factors of 0 and 1. Because the
I/M factor for Denver is a value of neither 0 (no I/M program) nor 1 (the reference I/M program),
the Denver leak prevalence rates, as is, are not used as base prevalence rates in MOVES. From
Figure 23, the I/M failure frequency in Denver is 30% less than non-IM (I/M factor = 0) and 30%
higher than Phoenix (I/M factor = 1) so the leak prevalence rates developed from Denver data
are adjusted accordingly before being added to the MOVES database. This adjustment reflects the
analysis described in the previous section and can be observed in Figure 23. For example, during
a MOVES run for the Denver area, the Denver I/M factor will be applied and emissions will be
modeled with the same prevalence rates originally estimated for Denver.
44
-------
Figure 24: Adjusting Denver Leak Prevalence Data
Denver Leak Frequency
I
-------
Table 20: Percentage of Liquid Leaks by Age
Age group Percentage of leakers in fleet
0-9
10-14
15-19
20+
0.09 %
0.25 %
0.77 %
2.38 %
The estimates of liquid leak prevalence are shown in Table 20. It is assumed that most leaks do not
occur until vehicles are 15 years or older.
Table 21 contains the fleet-weighted liquid leak rate. There is insufficient data to conclude that
these rates change with model year or are affected by I/M programs.
Table 21: Weighted Liquid Leak Emissions (g/hr)
Age group
0-9
10-14
15-19
20+
Cold soak
0.009
0.025
0.075
0.235
Hot soak
0.017
0.048
0.145
0.452
Operating
0.158
0.450
1.360
4.230
Similar to vapor leaks, we expect a reduction in the occurrence of liquid leaks due to improved system
design and integrity. We believe that remaining liquid leaks occurring in advanced evaporative
systems will be primarily caused by tampering and mal-maintenance. Therefore, we estimate Tier
3 to prevent half as many liquid leaks as vapor leaks.
Table 22: Weighted Tier 3 Liquid Leak Emissions (g/hr)
Age group
0-9
10-14
15-19
20+
Cold soak
0.007
0.019
0.058
0.180
Hot soak
0.013
0.037
0.113
0.348
Operating
0.123
0.342
1.054
3.258
3.6 Refueling
Refueling emissions are the displaced fuel vapors when liquid fuel is added to the tank. The
calculation of vapor losses includes any liquid fuel that is spilled during refueling and evaporates.
Refueling emissions are estimated from the total volume of fuel dispensed (gallons). This volume is
46
-------
estimated from the average daily distance travelled (VMT) and estimated fuel consumption. Both
the spillage and the vapor displacement associated with refueling events are in terms of grams spilled
per gallon of fuel dispensed. Diesel vehicles are assumed to have negligible vapor displacement, but
fuel spillage is included in the refueling emissions.
Uncontrolled and unadjusted refueling emissions are the displaced grams of fuel vapor per gallon
of liquid fuel, plus the grams per gallon for spillage. AP-42 Volume I Section 5.2.2.3 [5] lists the
spillage as 0.7 lb/1000 gallons, which is 0.31g/gallon of dispensed fuel. The vapor displaced by
refueling is a function of temperature and gasoline Reid Vapor Pressure (RVP) [10]:
E = -5.909 - 0.0949dT + 0.0884TDF + OA85RVP (13)
Where:
E = Displaced Vapor (non-methane grams)
RVP = Reid Vapor Pressure (psi)
TDF = Dispensed gasoline temperature (degF)
TDF = 20.30 + 0.8l*Tamb
dy = Temperature difference between tank and dispensed
dT = 0.418*TDF -16.6
Dispensed fuel temperature is the temperature of the fuel flowing from the pump. Based on a 2008
California study [35], this temperature is calculated as 20.30 + 0.81 * T, where T is the monthly
average temperature, computed from the zoneMonthHour table. The monthly average temperature
must be between 45 and 90 degrees Fahrenheit. For ambient temperatures beyond those limits, the
dispensed fuel temperature is set to the value calculated at the limit. Furthermore, the dT value
cannot be greater than 20 degrees. The dy equation is developed in an Amoco study. In that study,
the difference in temperature was never greater than 20 degrees.
Two emission control strategies exist to limit fuel lost during refueling. First, there are programs
designed to capture refueling vapors at the pump. These are often referred to as Stage II vapor con-
trol programs. Second, vehicles manufactured since 199823 have onboard refueling vapor recovery
(ORVR) systems that store refueling vapors in the vehicle's evaporative emission canister.
The implementations of Stage II systems vary from area to area and affect the displaced fuel vapors
affected and the amount of reducing spillage. MOVES uses two factors to adjust the refueling losses
and account for this variation.
1. The refueling vapor program adjustment is a value between zero and one indicating the
percent reduction of total potential vapor losses by state or local programs (such as
Stage II recovery programs).
2. The refueling spill program adjustment is a value between zero and one indicating the
percent reduction of refueling spillage losses by state or local programs (such as Stage
II recovery programs).
These program adjustments in MOVES are applied by county. Each county has a unique value
47
-------
Table 23: Phase-In of Onboard Refueling Vapor Recovery
Model Year Passenger Cars Light Trucks <6,000 Light Trucks 6,000- Heavy Duty Trucks
Ibs GVWR 8,500 Ibs GVWR
1998
1999
2000
2001
2002
2003
2004
2005
2006 and Newer
40%
80%
100%
100%
100%
100%
100%
100%
100%
0%
0%
0%
40%
80%
100%
100%
100%
100%
0%
0%
0%
0%
0%
0%
40%
80%
100%
0%
0%
0%
0%
0%
0%
40%
80%
100%
for vapor and spillage program adjustments. The program adjustment values for each county and
calendar year are stored in the default MOVES 'County Year' table.
MOVES uses a separate factor to address the on-board refueling vapor recovery (ORVR) systems on
vehicles. MOVES applies a 98 percent reduction in refueling vapor losses and 50 percent reduction
in refueling spillage losses for ORVR equipped vehicles. The effects of ORVR technology is phased
in beginning in model year 1998.
1. The refueling tech adjustment is a number between zero and one which indicates the re-
duction in full refueling spillage losses that result from improvements in vehicle technol-
ogy (such as the Onboard Refueling Vapor Recovery rule). The technology adjustment
is applied the same in all locations.
The technology adjustment values are stored in the default MOVES 'Source Type Tech Adjustment'
table.
MOVES applies both the program and technology adjustment to all model years. This means that
Stage II programs are assumed to affect vehicles not equipped with ORVR and additionally, any
refueling emissions that are not captured by the ORVR systems. MOVES does not account for
any interaction between ORVR systems and gasoline dispensing stations equipped with Stage II
equipment.
48
-------
4 Glossary of Terms
backpurge - as the temperature decreases a vacuum is created in the fuel system which pulls
the hydrocarbons from the charcoal canister into the fuel tank, creating more space in the
canister for hydrocarbons to adhere during the next heating period
breakthrough - when the vapor generated by the fuel system overwhelms the charcoal can-
ister and uncontrolled hydrocarbons are released into the atmosphere
canister - the device in an evaporative emission control system that captures and stores
evaporative emissions generated within the vehicle for later combustion by the engine; a
canister typically contains activated carbon as a storage medium
CRC - Coordinating Research Council, a consortium of auto and oil industry members which
sponsors common research programs
diurnal cold soak - Vapor lost while vehicles are parked at ambient temperature.
HC - hydrocarbon, an organic compound consisting entirely of hydrogen and carbon; a com-
bustible fuel source which can be either gaseous or liquid
hot soak - Vapor lost in the time period immediately after turning off a vehicle.
I/M - Inspection and Maintenance program run by States to find and correct emissions
problems for vehicles registered in the State
light duty vehicle/LDGV - passenger cars
MOVES - MOtor Vehicle Emissions Simulator; official US EPA model for estimating emis-
sions from national fleet of onroad vehicles
MSAT - Mobile Source Air Toxic rule which regulates toxic mobile source emissions such as
benzene and ethanol
permeation - the migration of hydrocarbons through materials in the fuel system
OBD - Onboard Diagnostics, an electronic automotive system with the ability to continually
track the functionality of emissions control and other components, and alerts the driver and/or
vehicle inspector when a problem is found
ORVR - Onboard refueling vapor recovery system which is designed to capture fuel vapors
at time of refueling
PSHED - portable SHED for evaporative emissions field measurements
purge - evaporative emissions control system that creates a vacuum in the fuel system to
pull the hydrocarbons from the charcoal canister while the engine is running for combustion
refueling loss - Vapor lost and spillage occurring during refueling
running loss - Vapor lost during vehicle operation.
RVP - Reid Vapor Pressure, a measure of volatility in the gasoline at 100 degrees Farenheit,
as determined by the test method ASTM-D-323
SHED - Sealed Housing for Evaporative emissions Determination; structure for evaporative
testing in a laboratory
Stage II - vapor control programs at refueling stations to recover fuel vapor losses from fuel
displacement at the refueling pump
tank vapor generated (TVG) - vapor generated in the fuel system as temperature rises
tank vapor vented (TVV) - vapor generated in fuel system lost to the atmosphere, when
not contained by evaporative emissions control systems
Tier 2 - vehicle emissions certification standards phased in from 2004 through 2007
Tier 3 - vehicle emissions certification standards will phase in from 2017 through 2025
49
-------
Appendix A Notes on Evaporative Emission Data
Parameters: Vehicle Numbers, Test No., Ambient Temperature, RVP, Model Year, Fuel System,
Purge, Pressure, Canister, Gram HC, Retest
E-41 CRC Late Model In-Use Evap. Emission Hot Soak Study (1998)
50 vehicles (30 passenger cars and 20 light duty trucks)
Model years 1992 to 1997
Average RVP: 6.5 psi
Diurnal Temperature: 72 to 96°F
Fuel System: Port Fuel Injection, Throttle Body Injection
Vehicle fuel tank drained and refilled to 40% of capacity with Federal Evaporative Emission
Test Fuel
Driving schedule will be a full LA-4-NYCC-NYCC-LA4 sequence, with two minute idle periods
following the first LA-4, the second NYCC, and the final LA-4.
Hydrocarbon readings will be taken continuously throughout the running loss test.
Cumulative mass emissions will be reported at one minute intervals.
Ambient Temperature in running loss enclosure: 95°F
E-9 CRC Real Time Diurnal Study (1996)
151 vehicles (51 vehicles MY 1971-1977, 50 vehicles MY 1980-1985, 50 vehicles MY 1986-1991)
Odometers range from 39,000 to 439,000 miles
Fuel tank volume was 15% of the rated capacity
RVP: 6.62 psi (average sum of 47 vehicles)
Diurnal temperature: 72 to 96°F
Fuel System: Port Fuel Injection, Carburetor, Throttle Body Injection
CRC E-35 Running Loss Study (1997)
150 vehicles (50 vehicles MY 1971-1977, 50 vehicles MY 1980-1985, 50 vehicles MY 1986-1991)
Ambient Temperature in running loss enclosure: 95°F
RVP: 6.8 psi
Fuel System: Port Fuel Injection, Carburetor, Throttle Body Injection
EPA Compliance Data
2-Day Test
Length of the hot soak: 1 hour
77 vehicles
RVP: average 8.81 psi
Ambient Temperature:
Federal Standard (72 to 96°F) Diurnal
Gal. (65 to 105°F) Diurnal
50
-------
Hot Soak: 81.67°F
Fuel System: Port Fuel Injection
MSOD (Mobile Source Observation Database):
Hot Soak 1 hour hot soak evaporative test
FTP Federal test procedure (19.53 mph), also referred to as the UDDP schedule
NYCC New York City Cycle Test (7.04 mph)
BL1A 1 hour Breathing Loss Evap. Test Gas Cap left On
BL1B 1 hour Breathing Loss Evap. Test Canister as reed.
ST01 Engine Start cycle test
4HD 4 hour Diurnal test
24RTD 24 Hour Real Time Diurnal
33RTD 33 Hour Real Time Diurnal
72RTD 72 Hour Real Time Diurnal
3Rest 3 Hour Resting Loss Evap. Emission Test (follows 1 HR Hot Soak)
CY6084 Real time diurnal temperature pattern: range 60 to 84 F
CY7296 Real time diurnal temperature pattern: range 72 to 96 F
CY8210 Real time diurnal temperature pattern: range 82 to 102 F
DIURBL Standard temperature rise for 1 hour diurnal or breathing loss evaporative emis-
sion test
F505 Bag 1 of federal test procedure (25.55 mph)
ASM Acceleration Simulation Mode Test Procedure
ATD Ambient Temperature diurnal evaporative Test, shed temp constant, vehicle begins 24
degree cooler
51
-------
Appendix B Peer Review Comments
52
-------
Peer Review
1. Reviewers' Responses to Charge Questions
1.1, Evaporative Emissions Report
This section provides a verbatim list of peer reviewer comments submitted in response to the charge
questions for the Evaporative Emissions Report. EPA responses are in bold italics below the comment.
Adequacy of Selected Data Sources
Does the presentation give a description of selected data sources sufficient to allow the reader to form a
general view of the quantity, quality and representativeness of data used in the development of emission
rates? Are you able to recommend alternate data sources might better allow the model to estimate
national or regional default values?
1.1.1.1. Chris Kite
No response.
1.1.1.2. Dr. Robert Sawyer
New evaporative emissions data come largely from the extensive Coordinating Research Council studies
reported in 2006-2010. These data, particularly quantification of permeation data, are a major
improvement over the sparse data previously available. The report documents these data thoroughly
and clearly.
Clarity of Analytical Methods and Procedures
Is the description of analytic methods and procedures clear and detailed enough to allow the reader to
develop an adequate understanding of the steps taken and assumptions made by EPA to develop the
model inputs? Are examples selected for tables and figures well chosen and designed to assist the reader
in understanding approaches and methods?
Chris Kite
No response.
1.1.2.2. Dr. Robert Sawyer
Descriptions of methods and procedures are particularly good. Explanation of the operation of
evaporative control systems and the nature and mechanism of emissions is excellent. The writing in this
53
-------
report is concise, direct, and clear. The use of graphics to show relationships, and agreement with
experimental data as available are very well done.
Appropriateness of Technical Approach
Are the methods and procedures employed technically appropriate and reasonable, with respect to the
relevant disciplines, including physics, chemistry, engineering, mathematics and statistics? Are you able
to suggest or recommend alternate approaches that might better achieve the goal of developing
accurate and representative model inputs? In making recommendations please distinguish between
cases involving reasonable disagreement in adoption of methods as opposed to cases where you
conclude that current methods involve specific technical errors.
Chris Kite
No response.
Dr. Robert Sawyer
The estimation of fuel system evaporative emissions depends strongly upon the "fuel tank
temperature". The use of this term is a bit ambiguous. I believe that it refers the temperature of the fuel
in the fuel tank. This should be made clear.
Text was added to the definition of fuel tank temperature to make it clear that it is the
temperature of the fuel in the tank itself that is referred to in MOVES and the documentation
with the term "fuel tank temperature".
For hot and cold soaks, modeling of the change in fuel temperature based on the fuel temperature, air
temperature, and a transfer coefficient (equation 1) is probably adequate for the purposes of the model,
however it fails to capture difference in fuel tank design, "k" comes from EPA compliance test data.
Reporting of the variability in "k" would give some sense of the adequacy of the model.
Similar questions arise in the use of equation 3 to model fuel tank temperature during running
operation. Vehicle to vehicle variation is likely to be even larger and should be quantified. Note: MOVES
projects fleet average emissions, which will change as vehicle designs change. Use of a fleet-average
constant will not capture possible changes as older model years disappear from the fleet. A model-year
or binned model year constant would be an improvement.
The variability of the "k" values and the fuel tank temperatures is not readily available at this
time. EPA plans on another major enhancement of the calculation of evaporative emissions
that will make less use of averages and more use of distributions. This should improve the
ability of the model to account for differences in design and technology across model years in
future versions of MOVES.
54
-------
Appropriateness of Assumptions
In areas where EPA has concluded that applicable data is meager or unavailable, and consequently has
made assumptions to frame approaches and arrive at solutions, do you agree that the assumptions
made are appropriate and reasonable? If not, and you are so able, please suggest alternative sets of
assumptions that might lead to more reasonable or accurate model inputs while allowing a reasonable
margin of environmental protection.
Chris Kite
No response.
Dr. Robert Sawyer
Inadequate or missing data is always a problem. The assumptions used to deal with inadequate data are
clearly stated. The use of current and projected emissions standards to project future vehicle fleet
emissions has a history of underestimating emissions.
The use of light-duty vehicle evaporative emissions composition data for non-existent heavy-duty
gasoline vehicle data is reasonable. There is no reason to expect that differences in vehicle designs
between these two categories of vehicles would affect evaporative emissions significantly.
Linear interpolation and extrapolation for the estimation of altitude effects is reasonable.
The assumption that fuel tank size will remain constant at the current level of 19 gallons over the 2009-
2030 period, page 21, is incorrect. With an improvement of fuel economy by nearly a factor of two over
this period, than size will decrease by roughly the same factor, as occurred in the 1970s.
It has been difficult to obtain accurate information about fuel tank size from existing sources.
More effort will be needed to better document changes in the distribution of fuel tank sizes by
model year. MOVES2014 has been designed to allow different model years to have different
average fuel tank capacity, which should allow simple updates to the default data, once
additional data becomes available. In addition, EPA plans on another major enhancement of
the calculation of evaporative emissions that will make less use of averages and more use of
distributions. This should improve the ability of the model to account for differences in design
and technology across model years in future versions of MOVES.
Consistency with Existing Body of Data and Literature
Are the resulting model inputs appropriate, and to the best of your knowledge and experience,
reasonably consistent with physical and chemical processes involved in exhaust emissions formation and
control? Are the resulting model inputs empirically consistent with the body of data and literature that
has come to your attention?
55
-------
Chris Kite
No response.
Dr. Robert Sawyer
Model inputs are consistent with the goal of MOVES to be more data driven. However, major gaps
remain in the available data. Particularly sparse are data on liquid running losses, Table 17. The
methodology of subtracting modeled estimated vapor emissions from total measured vapor emissions
from vehicles excluded from inspection and maintenance testing is suspect.
Although comparing modeled vapor emissions to measurements cannot replace the need and
desire to have a more detailed breakdown of measured vapor emissions, the technique of
subtracting the modeled emissions from the total measured vapor emissions avoids double
counting the non-leaking vapor emissions when the measurements are used in the model.
EPA is planning to continue to investigate methods to better estimate the evaporative
emissions from vehicles that allows a breakout of the sources of the vapors.
Liquid spillage during refueling comes from AP-42 and data apparently dating from the 1970s. This is a
major shortcoming of the MOVES2014 model and deserves attention in a future revision or updating.
The effective regulation of other emissions increases the importance of unregulated or weakly regulated
emissions.
Additional information on the Wade-Reddy equation for vapor generation (equation 6) is needed as this
relation is used extensively in the modeling. First, no reference is provided. Second, having a figure in
which the data to which the equation was fitted with the coefficients of Table 7 would strengthen the
rationale for the use of this empirical relation. I believe that this relation comes from work first
published in the 1970s (perhaps: Wade et. al., "Mathematical Expressions Relating Evaporative
Emissions from Motor Vehicles without Evaporative Loss-Control Devices to Gasoline Volatility," SAE
Paper 720700, 1972?) and has been cited extensively over the years in EPA publications on evaporative
emissions. I have not reviewed the source paper. It is a reasonable mathematical curve-fit relation, but
its original justification probably was with data of the 1970s. The data are modern and appropriate, but
how well the model fits the data should be shown.
Additional text was added to the description of the use of the Wade-Reddy equation in Section
3.3, including a reference, which includes more descriptive material regarding the fit of the
model.
Improvements in Proposed Methodology
Compared to current methods, is the proposed methodology for estimating evaporative emissions a
significant improvement? Would a simpler application of the ideas contained in this method be
56
-------
adequate? Are there other existing models for evaporative emissions that might be possible candidates
for inclusion in MOVES?
Chris Kite
No response.
Dr. Robert Sawyer
Improvements in the treatment of evaporative emissions are substantial. The data base, the modeling of
emissions, and their integration with fleet composition and activity all are significant improvements over
the current MOVES model. Treatment of the addition of ethanol is straight forward, carefully done and
presented, and an important addition.
1.1.7. General/Catch-All Reviewer Comments
Please provide any additional thoughts or review of the material you feel important to note that is not
captured by the preceding questions.
1.1.7.1. Chris Kite
« Overall, the technical report is very informative and well written. While reviewing the report for
areas in which I have some background, I came across many sections where I was less informed, so
it was a very positive experience to learn more about evaporative emission processes and how the
MOVES model treats them.
« While reviewing, I noticed some minor grammatical issues that I noted with recommendations for
correction, rewording, etc. These may be of help in preparing the final version of the report, but
since such suggestions are rather minor and not essential for a peer review, they are highlighted
with notes in the attached draft but not mentioned here.
Appropriate modifications have been made to the text.
« The report included a few references that may need to be corrected once the final version is
prepared so that someone reading it a few years from now will not be confused:
* The draft mentions a MOVES2014 version of the model. Will the evaporative emission impacts
referenced in the report be included in the upcoming MOVES2013 version? If so, then just
change the reference to MOVES2013. If not, is a MOVES2014 version of the model already
under development that will include these impacts? Or, if there will not be a MOVES2014
version of the model, just change this to MOVES2015, MOVES2016, etc. as needed.
At the time the report was drafted, EPA had not yet announced the change in the naming of
the next publically released version of the MOVES model All references to MOVES2014 in
the documentation refer to what was (then) publically known as MOVES2013. So,
MOVES2013 andMOVES2014 are the same and there will not be a "MOVES2013" version
released to the public by EPA. c 7
-------
The report draft was probably written when 2016 was being considered as a model year start
for Tier 3 standards with a phase-in from 2016-2022. Based on the Tier 3 proposal from earlier
this year, this should be changed to a 2017 model year start with a phase in from 2017-2025. In
the event that Tier 3 implementation is delayed beyond 2017, then the report draft should be
modified accordingly.
The model and the report have been adjusted to reflect the correct final Tier3 Rule phase-in for
evaporative standards, including the leak standard. See Table 3 and the discussion of leak
prevalence in Section 3.3.3 "Hot Soak".
The report draft mentions the Stage 2 program, but we recommend referring to it as Stage II since
the latter is typically how the rule is typically referenced in the Clean Air Act and by EPA.
The text has been updated in Section 3.6 "Refueling" to make this change to be consistent with the
Clean Air Act.
In footnote #2 on page 9, a 15-minute time increment is referenced for hot and cold soak emission
calculations. This time increment seems very reasonable, but I was left wondering how MOVES
handles temperature figures for each 15-minute increment. Are they just linearly interpolated from
the hourly MOVES model inputs? The manner in which I prepare MOVES temperature inputs are
averages for the entire hour, so if data were collected at several meteorological stations from 7-8
AM, then I would average all of these and associate the input with an hourlD of 8 in the
zonemonthhour table. Pretend I had a 7-8 AM figure of 70 F and an 8-9 AM figure of 74 F. Would
the evaporative calculations put the 70 F and 74 F estimates right at the top of the hours, which
would be 7 AM and 8 AM, respectively? Or, would these be put at the mid-point of the hours, which
would be 7:30 AM and 8:30 AM, respectively? Assuming the latter, then would the evaporative
calculations be based on a linear interpolation of 70 F at 7:30 AM, 71 F at 7:45 AM, 72 F at 8:00 AM,
73 F at 8:15 AM, and 74 F at 8:30 AM? If this is documented elsewhere, then just reference that
literature instead of including a full and rather tedious explanation in this report.
Hot soaks occur at trip ends. If a trip ends at 7AM, or at any time in the hour from 7:00 8:00,
the temperature used for hot soak calculations is the temperature provided by the user to the hour
from 7AM 8 AM. For cold soak MOVES takes the temperature at the beginning of the hour and
looks at the temperature for the next hour and interpolates in 15 minute increments for the tank
temperature calculation. The resulting hourly temperature is approximately an average of the two
hourly temperatures input by the users.
The approach described on page 16 to vary evaporative effects by altitude (instead of "low" versus
"high" categories) is excellent. With the MOVES county database table now include a numeric
elevation field to perform this calculation?
The MOVES database does not include a value to indicate elevation. Instead, each county has a
value for average barometric pressure based on the meteorological measurements used to obtain
temperature and humidity values. The equations can use the barometric pressure values directly.
58
-------
The summary is very good about how MOVES handles diurnal emissions from vehicles parked for
several days without initiating trips. Figure 13 on page 27 is particularly good at communicating the
necessary points. I looked at the samplevehicleday and samplevehicletrip tables in the
MOVES2010b database, and couldn't figure out how to obtain the fractions of vehicles cold soaking
for several consecutive days. The current tables look like they were designed for a sample vehicle
on a single day. Perhaps these tables will be expanded for a future version of MOVES? If so, then I
recommend including an extract of the expanded table(s) in Appendix B. Also, the
samplevehiclesoakingday table referenced on page 27 is currently empty within the MOVES2010b
database. Perhaps this contains the needed information to view multiple-day cold soak profiles? If
so, then I recommend including an Appendix B extract of this table as well. Maybe only have these
example extracts focus on the gasoline passenger car source use type to keep them small.
Whatever approach is taken should make it very clear to the reader about how to connect all the
tables together. I do not expect that many MOVES users will have their own multi-day soaking data
for populating these tables (and will instead rely on defaults), but the necessary methodology
should be outlined clearly in the event that users do want to provide their own information.
MOVES2014 does not have sample vehicle trips for more than a single day. The Software Design
and Reference Manual (SDRM) for MOVES describes in a step-by-step manner how the sample
vehicle trips are converted to activity parameters (such as starts and parking). Vehicles soaking
for more than one day cannot exceed the vehicles that did not drive in the previous day. MOVES
calculates the vehicles soaking for more than one day as a fraction of the vehicles soaking in the
previous day.
In Section 3.3.4 on page 36, it says that MOBILES was run to obtain the effects of temperature and
gasoline RVP on running loss emissions. I understand that this may have been necessary in lieu of
having superior data, but are there no newer data sets available that can be used for this purpose?
To understand how MOBILES handles this, I came across a report entitled Estimating Running Loss
Evaporative Emissions in MOBILES, M6.EVP.008,EPA420-R-01-023, April 2001, which is on the
MOBILES Technical Documentation site (http://www.epa.gov/otaq/models/mobile6/r01023.pdf).
Under Section 5, Conclusions, on page 7, it says: "EPA proposes, for MOBILES, to use the MOBILES
model to estimate the running loss emissions from that portion of the fleet that does not contain
vehicles that are gross liquid leakers." Is there justification available to indicate that the changes in
vehicle technology over the last 20-25 years are not sensitive to the response of temperature and
fuel RVP to running loss emission rates? If not, that should be emphasized in the report so that
readers are aware that newer data of this sort be assigned appropriate priority for future research.
MOBILES was released before the introduction of Tier 1 and LEV-I vehicles into the fleet, so it is
likely that the raw data upon which the MOBILES running loss impacts were developed dates back to
vehicles tested from 1980-1990. Assuming that some updates were done for estimating running
loss emissions with MOBILES, the test data then would have perhaps included Tier 1 and LEV-I
vehicles that were available from 1990-2000. Since the current light-duty fleet is dominated by
2004-and-newer Tier 2 activity, it would be ideal for MOVES to not rely on data of such vintage,
particularly for a model that will be used to estimate future fleet emissions dominated by both Tier
2 and Tier 3 vehicles. _
-------
EPA is just completing a study1 on the effects of temperature on running losses utilizing an
environmental chamber. This new information will provide EPA with the information needed to
update the effects of temperature on running losses currently used by MOVES. However, the
testing was not completed in time to provide enough time for proper quality assurance and
ana lysis for use in MOVES2014.
In Section 3.6 on page 42, it says: "Refueling emissions are estimated from the total volume of fuel
dispensed (gallons). This volume is estimated from the average daily distance travelled (VMT) and
estimated fuel consumption." Is this how MOVES performs the calculations "under the hood" for
refueling? If MOVES2010b is run to obtain refueling emission rates, the three types of output are
grams/mile, grams/start, and grams/hour for the respective activity types of miles traveled, number
of starts, and number of extended idling hours for diesel-fuel combination long-haul trucks. These
are the same emission process/rate combinations when estimating carbon dioxide (CO2) and energy
consumption. I have not been able to obtain gallons pumped/consumed directly from MOVES
output, and have instead relied on post-processing CO2 and/or energy consumption for these
purposes. Will future versions of MOVES estimate gallons pumped/consumed directly or output
refueling emission rates in units of grams/gallon? If not, then the report language referenced above
about how MOVES calculates refueling emissions may need to be revised.
MOVES is able to calculate gallons of fuel consumed internally by converting the estimate of
energy consumption to fuel using the values of energy content contained in the default MOVES
database. Most users have been converting the energy or CO2 in the output of MOVES to gallons
as you describe. However, as typical fuels become more complex (such as ethanol blends), it will
not be possible to accurately estimate fuel quantity without more detailed output from MOVES,
either including results by fuel subtype or by direct output of MOVES fuel quantity estimates. This
feature was not planned for MOVES2014, but could be considered for future updates to MOVES.
Could this report or some other MOVES documentation include options/recommendations about
how specific evaporative emission processes should be matched to profiles from EPA's SPECIATE
database? Refer to slides 8 and 9 of the attached file entitled "mvs-custom-scc-and-speciation-
tceq.pdf" [See tables below, "slides 8 and 9 are Gasoline and Diesel Profile tables]. Based on the
most recent information that we could obtain, this is how we are matching up evaporative emission
processes to SPECIATE profiles. For example, evaporative permeation from running vehicles is
matched to profile descriptions that begin with "dynamic permeation". Off-network evaporative
permeation from parked vehicles is matched to profile descriptions that begin with "static
permeation". Vapor/venting processes get matched to "headspace vapor", while leaking/spillage
profiles get matched to liquid fuel composition. This was the best matching I could come up with,
but it took a lot of staff time to develop, and it will likely be very helpful for new MOVES users to
have some guidance/direction about where to start in case they have similar questions. If you feel
that these tables reflect a good starting point, feel free to use them. Prior to 2008, ethanol had not
fully penetrated the fuel supply in Texas, so we are relying on gasoline profiles that have both 0%
1 M. Sabisch, S. Kishan, J. Stewart, G. Glinsky Fuel Tank Temperature Profile Development for Highway Driving,
March 2014 60
-------
and 10% ethanol. If you feel that we could take an improved approach with this matching, please
let us know.
MOVES2014 will apply the appropriate SPECIATE factors in order to generate some of the
pollutants reported by MOVES. The mapping of the MOVES emission processes to the SPECIATE
profiles is found in MOVES2014 Technical Report: Speciation of Total Organic Gas and Paniculate
Matter Emissions from On-road Vehicles in MOVES2014[17].
MOVES Custom Classification Codes
Ten-digit source classification code (SCC) is the essential identifier for photochemical model
emissions processing:
tracking and reporting by fuel type, source use type, etc,;
- chemical speciation (e.g., gasoline versus diesel, exhaust versus evaporative); and
- spatial/temporal allocation, post-processing, and control strategy adjustments,
Custom numeric approach proposed by TCEQ based on the existing mobile SCC structure:
begins with U22.,.";
digits 3 and 4 are for fuel type;
- digits 5 and 6 are for source use type;
digits 7 and 8 are for roadway type; and
- digits 9 and 10 are for emission process.
If the current numeric MOVES database codes are used in this sequence, no overlap would occur
with the existing 1,175 on-road and non-road mobile SCCs.
Custom alpha coding can be more convenient than numeric coding for emissions processing:
- instant identification for fuel type, source use type, roadway type, and emission process; and
- some categories can be aggregated to increase processing efficiency when no differences
exist in speciation, temporal allocation, and/or spatial allocation (e.g., emission processes for
running exhaust and crankcase running exhaust).
Running exhaust from a gasoline-powered passenger car on an urban restricted access roadway:
- 2201210401 under a numeric approach; or
- MVGSPCURRX under an alpha approach.
61
-------
n
MOVES Custom Classification
Codes for Fuel Types
MOVES
Code
1
2
3
4
5
9
MOVES
Description
Gasoline
Diesel Fuel
Compressed Natural Gas (CNG)
Liquefied Petroleum Gas (LPG)
Ethanol (£85)
Electricity
Alpha
Code
GS
DS
CN
LP
ET
EL
Numeric
Code
01
02
03
04
05
09
= =
MOVES Custom Classification
Codes for Source Use Types
MOVES
Code
11
21
31
32
41
42
43
51
52
53
54
61
62
MOVES
Description
Motorcycle
Passenger Car
Passenger Truck
Light Commercial Truck
Intercity Bus
Transit Bus
School Bus
Refuse Truck
Single Unit Short-Haul Truck
Single Unit Long-Haul Truck
Motor Home
Combination Short-Haul Truck
Combination Long-Haul Truck
Alpha
Code
MC
PC
PT
LC
IB
TB
SB
RT
SS
SL
MH
CS
CL
Numeric
Code
11
21
31
32
41
42
43
51
52
53
54
61
62
62
-------
MOVES Custom Classification
Codes for Roadway Types
MOVES
Code
1
2
3
4
5
8
9
MOVES
Description
Off- Network
Rural Restricted Access
Rural Unrestricted Access
Urban Restricted Access
Urban Unrestricted Access
Rural Ramps
Urban Ramps
Alpha
Code
OF
RR
RU
UR
UU
RP
UP
Numeric
Code
01
02
03
04
05
08
09
MOVES Custom Classification Codes for Highway
Performance Monitoring System (HPMS) Roadway Types
HPMS Roadway
Type Description
Rural Interstate
Rural Other Principal Arterial
Rural Minor Arterial
Rural Major Collector
Rural Minor Collector
Rural Local
Urban Interstate
Urban Other Freeways and Expressways
Urban Other Principal Arterial
Urban Minor Arterial
Urban Collector
Urban Local
HPMS
Numeric Code
110
130
150
170
190
210
230
250
270
290
310
330
MOVES Numeric
Code (no alpha)
11
13
15
17
19
21
23
25
27
29
31
33
63
-------
MOVES Custom Classification
Codes for Emission Processes
MOVES
Code
l
15
2
16
90
17
91
11
12
13
18
19
MOVES
Description
Running
Exhaust
Crankcase
Running Exhaust
Start
Exhaust
Crankcase
Start Exhaust
Extended
Idle Exhaust
Crankcase
Extended Idle Exhaust
Auxiliary Power
Exhaust
Evaporative
Perm cation
Evaporative
Fuel Vapor Venting
Evaporative
Fuel Leaks
Refueling Displacement
Vapor Loss
Refueling Spillage
Loss
Alpha
Code
RE
CR
SE
CS
IE
CI
AX
EP
EV
EL
RD
RS
Numeric
Code
01
15
02
16
90
17
91
11
12
13
18
19
Aggregation
Description
Running
Exhaust
Start
Exhaust
Idle
Exhaust
Auxiliary
Exhaust
Evaporative
Permeation
Evaporative
Venting
Evaporative
Leaks
Refueling
Displacement
Refueling
Spillage
Aggregation
Alpha Code
RX
SX
IX
AX
EP
EV
EL
RD
RS
64
-------
Gasoline VOC Profiles from EPA SPECIATE
Database by MOVES Emission Process
Emission
Process
Running Exhaust
Start Exhaust
Running Evaporative Permeation
Off-Network Evaporative Permeation
Running Evaporative Fuel Vapor Venting
Off-Network Evaporative Fuel Vapor Venting
Refueling Displacem ent Vapor Loss
Running Evaporative Fuel Leaks
Off-Network Evaporative Fuel Leaks
Refueling Spillage Loss
Profile
Code
8756
8757
8759
8760
8848
8849
8850
8851
8853
8836
8837
8838
8839
8841
8762
8763
5492
5493
SPECIATE
Version
4.3
4.3
4.3
4.3
4.3
4.3
4.3
4.3
4.3
4.3
4.3
4.3
4.3
4.3
4.3
4.3
4.2
4.2
Entry
Date
10/2/2009
10/2/2009
10/2/2009
10/2/2009
10/15/2010
10/15/2010
10/15/2010
10/15/2010
10/15/2010
10/15/2010
10/15/2010
10/15/2010
10/15/2010
10/15/2010
10/2/2009
10/2/2009
2/12/2008
2/12/2008
Profile
Description
Gasoline Exhaust - Tier 2 Light-Duty Vehicles
Using 0% Ethanol - Composite Profile
Gasoline Exhaust - Tier 2 Light-Duty vehicles
Using 10% Ethanol - Composite Profile
Gasoline Exhaust - Cold Start - Tier 2 Light-Duty
Vehicles Using 0% Ethanol - Composite Profile
Gasoline Exhaust - Cold Start - Tier 2 Light -Duty
'j'ehides Using 10% Ethanol - Composite Profile
Dynamic Permeation Evaporative Emissions from
Gasoline Vehides Using 0% Ethanol at 7 RVP
Dynamic Permeation Evaporative Emissions from
Gasoline Vehides Using 0% Ethanol at 9 RVP
Dynamic Permeation Evaporative Emissions from
Gasoline Vehides Using 0% Ethanol - Combined
Dynamic Permeation Evaporative Emissions from
Gasoline Vehides Using 10% Ethanol at 7 RVP
Dynamic Permeation Evaporative Emissions from
Gasoline Vehides Using 10% Ethanol - Combined
36°F Static Permeation Evaporative Emissions from
Gasoline Vehides Using 0% Ethanol at 7 RVP
E!6°F Static Permeation Evaporative Emissions from
Gasoline Vehides Using 0% Ethanol at 9 RVP
86°F Static Permeation Evaporative Emissions from
Gasoline Vehides Using 0% Ethanol - Combined
86°F Static Permeation Evaporative Emissions from
Gasoline Vehides Using 10% Ethanol at 7 RVP
E!6°F Static Permeation Evaporative Emissions from
Gasoline Vehides Using 10% Ethanol - Combined
Gasoline Headspace Vapor Using 0% Ethanol -
Composite Profile
Gasoline Headspace Vapor Using 10% Ethanol -
Composite Profile
Liquid Gasoline Composition -
Reformulated Gasoline
.iquid Gasoline Composition -
E10 Ethanol Gasoline
Diesel Fuel VOC Profiles from EPA SPECIATE
Database by MOVES Emission Process
Emission
Process
Running Exhaust
Start Exhaust
Auxiliary Power Exhaust
Refueling Spillage Loss
Profile
Code
8774
8775
DX12
DX18
5552
8774
4673
SPECIATE
Version
4,3
4,3
Entry
Date
6/13/2010
6/13/2010
Profile
Description
Diesel Exhaust Emissions from Pre-2007
Model Year Heavy-Duty Diesel Trucks
Diesel Exhaust Emissions from 2007 Model
Year Heavy -Duty Diesel Engines with Controls
Combination of 8774 and 8775 Based on Diesel Exhaust VOC
Distribution from MOVESZOlOb Default Analyses for 2012
Combination of 8774 and 8775 Based on Diesel Exhaust VOC
Distribution from MOVES2010b Default Analyses for 2018
4.2
4,3
4.0
4/15/2008
6/13/2010
9/29/2004
Diesel Exhaust - Low Aromatic Diesel -
Cold Start
Diesel Exhaust Emissions from Pre-2007 Model Year
Heavy-Duty Diesel Trucks
Diesel Composition
*Note: EPA has updated spec/at/on mapping profiles, which make the above slides out of date.
They are included here for completeness of the peer review comments. Please use the list in EPA
documentation [17].
Overall, excellent report and thanks for the opportunity to review.
65
-------
Dr. Robert Sawyer
« The treatment of evaporative emissions in MOVES2014 is a significant improvement over the
previous treatment. The incorporation of extensive new data, reorganization of the computation of
total evaporative emissions, and integrating evaporative emissions with data on fleet composition
and operating modes all contribute to this improvement. Non-tailpipe emission sources not treated
include window washer fluid, paint, and plastics and rubber off-gassing. Some of these sources may
not be significant, but for completeness they deserve recognition.
Text was added to the description of evaporative emissions in Section I "Background", to
clearly indicate that these sources are not included in our estimates and may be a factor in
overall emissions from vehicles.
m Increasing skewness in evaporative emissions, as in tailpipe emissions, points to the importance of
getting the high emitter effect correct. Both emissions rates and activity data require refinement.
Model-year emissions in MOVES vary by a factor of 50 or more.
Significant resources from the EPA and other sources have been spent in recent years specifically
to address the issue of high emitters as they relate to evaporative emissions. It was those
measurement efforts that allow the MOVES model to have an accounting for poorly performing
evaporative control systems in the fleet. EPA intends to continue to investigate and refine our
estimates for both current technologies and emerging technologies in the coming years with
additional measurements.
m A glossary would be useful.
We added a glossary of terms to the document.
66
-------
Appendix C Relevant MOVES Evaporative Tables
Table 24: MOBILE6 LDGV Running Losses (g/mi)
Temperature(F)
40
45
50
55
65
70
75
80
85
90
95
100
7 RVP (psi)
3.06
3.00
2.88
2.69
2.62
2.57
2.56
2.70
2.85
3.03
3.24
3.42
8 RVP (psi)
3.06
3.02
2.91
2.76
2.71
2.68
2.69
2.85
3.04
3.30
3.58
3.91
9 RVP (psi)
3.07
3.05
2.96
2.84
2.80
2.79
2.83
3.03
3.29
3.62
3.98
4.57
10 RVP (psi)
3.09
3.10
3.06
3.04
3.05
3.08
3.16
3.39
3.76
4.23
4.69
5.42
67
-------
Table 25: MOVES Cumulative Tank Vapor Vented Table
RegClass
10
10
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
MYG
19711977
19781995
1996
1996
1996
1996
1996
1996
1996
1997
1997
1997
1997
1997
1997
1997
1998
1998
1998
1998
1998
1998
1998
2004
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
2006
2006
Age Bckpurge
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
AvgCan TankGal FillFrac
0.00
0.00
78.70
78.70
78.70
78.70
78.70
78.70
78.70
83.00
83.00
83.00
83.00
83.00
83.00
83.00
115.40
115.40
115.40
115.40
115.40
115.40
115.40
145.00
145.00
145.00
145.00
145.00
145.00
145.00
150.70
150.70
150.70
150.70
150.70
150.70
150.70
145.30
145.30
145.30
145.30
145.30
145.30
3.00
3.00
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.50
19.50
19.50
19.50
19.50
19.50
19.50
20.50
20.50
20.50
20.50
20.50
20.50
20.50
20.30
20.30
20.30
20.30
20.30
20.30
20.30
20.00
20.00
20.00
20.00
20.00
20.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
LeakEq LeakPct LeakPctIM
0.814TVG
0.814TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
1.00
0.65
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
1.00
0.48
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
68
-------
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
2006
2007
2007
2007
2007
2007
2007
2007
2008
2008
2008
2008
2008
2008
2008
2009
2009
2009
2009
2009
2009
2009
2010
2010
2010
2010
2010
2010
2010
2016
2016
2016
2016
2016
2016
2016
2018
2018
2018
2018
2018
2018
2018
2020
2020
2020
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
145.30
142.90
142.90
142.90
142.90
142.90
142.90
142.90
138.60
138.60
138.60
138.60
138.60
138.60
138.60
136.20
136.20
136.20
136.20
136.20
136.20
136.20
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
20.00
19.70
19.70
19.70
19.70
19.70
19.70
19.70
19.00
19.00
19.00
19.00
19.00
19.00
19.00
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.02
0.03
0.04
0.06
0.08
0.12
0.01
0.02
0.03
0.04
0.05
0.07
0.10
0.01
0.02
0.03
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.02
0.03
0.04
0.05
0.08
0.01
0.01
0.02
0.02
0.03
0.04
0.06
0.00
0.01
0.01
69
-------
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
20
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
2020
2020
2020
2020
2022
2022
2022
2022
2022
2022
2022
19601970
19711977
19711977
19711977
19781995
19781995
19781995
19781995
19781995
19781995
19781995
19992003
19992003
19992003
19992003
19992003
19992003
19992003
1996
1996
1996
1996
1996
1996
1996
1997
1997
1997
1997
1997
1997
1997
1998
1998
1998
809
1014
1519
2099
3
405
607
809
1014
1519
2099
2099
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
0.00
64.70
64.70
64.70
72.80
72.80
72.80
72.80
72.80
72.80
72.80
122.90
122.90
122.90
122.90
122.90
122.90
122.90
78.70
78.70
78.70
78.70
78.70
78.70
78.70
83.00
83.00
83.00
83.00
83.00
83.00
83.00
115.40
115.40
115.40
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
28.00
27.30
27.30
27.30
18.60
18.60
18.60
18.60
18.60
18.60
18.60
19.90
19.90
19.90
19.90
19.90
19.90
19.90
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.50
19.50
19.50
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.952TVG
0.782TVG
0.79TVG
0.796TVG
0.524TVG
0.408TVG
0.388TVG
0.376TVG
0.365TVG
0.357TVG
0.351TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.03
0.04
0.06
0.09
0.01
0.02
0.02
0.03
0.04
0.05
0.08
1.00
0.54
0.78
1.00
0.05
0.12
0.18
0.23
0.32
0.45
0.66
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.02
0.02
0.03
0.04
0.00
0.01
0.01
0.01
0.01
0.02
0.03
0.85
0.40
0.57
0.85
0.04
0.09
0.13
0.17
0.24
0.33
0.48
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
70
-------
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
1998
1998
1998
1998
2004
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
2006
2006
2006
2007
2007
2007
2007
2007
2007
2007
2008
2008
2008
2008
2008
2008
2008
2009
2009
2009
2009
2009
2009
2009
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
115.40
115.40
115.40
115.40
145.00
145.00
145.00
145.00
145.00
145.00
145.00
150.70
150.70
150.70
150.70
150.70
150.70
150.70
145.30
145.30
145.30
145.30
145.30
145.30
145.30
142.90
142.90
142.90
142.90
142.90
142.90
142.90
138.60
138.60
138.60
138.60
138.60
138.60
138.60
136.20
136.20
136.20
136.20
136.20
136.20
136.20
19.50
19.50
19.50
19.50
20.50
20.50
20.50
20.50
20.50
20.50
20.50
20.30
20.30
20.30
20.30
20.30
20.30
20.30
20.00
20.00
20.00
20.00
20.00
20.00
20.00
19.70
19.70
19.70
19.70
19.70
19.70
19.70
19.00
19.00
19.00
19.00
19.00
19.00
19.00
19.10
19.10
19.10
19.10
19.10
19.10
19.10
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.07
0.10
0.13
0.18
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.05
0.07
0.10
0.14
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
71
-------
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
2010
2010
2010
2010
2010
2010
2010
2016
2016
2016
2016
2016
2016
2016
2018
2018
2018
2018
2018
2018
2018
2020
2020
2020
2020
2020
2020
2020
2022
2022
2022
2022
2022
2022
2022
19601970
19711977
19711977
19711977
19781995
19781995
19781995
19781995
19781995
19781995
19781995
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
2099
1014
1519
2099
3
405
607
809
1014
1519
2099
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
0.00
64.70
64.70
64.70
72.80
72.80
72.80
72.80
72.80
72.80
72.80
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
28.00
27.30
27.30
27.30
18.60
18.60
18.60
18.60
18.60
18.60
18.60
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.952TVG
0.782TVG
0.79TVG
0.796TVG
0.524TVG
0.408TVG
0.388TVG
0.376TVG
0.365TVG
0.357TVG
0.351TVG
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.02
0.03
0.04
0.06
0.08
0.12
0.01
0.02
0.03
0.04
0.05
0.07
0.10
0.01
0.02
0.03
0.03
0.04
0.06
0.09
0.01
0.02
0.02
0.03
0.04
0.05
0.08
1.00
0.54
0.78
1.00
0.05
0.12
0.18
0.23
0.32
0.45
0.66
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.02
0.03
0.04
0.05
0.08
0.01
0.01
0.02
0.02
0.03
0.04
0.06
0.00
0.01
0.01
0.02
0.02
0.03
0.04
0.00
0.01
0.01
0.01
0.01
0.02
0.03
0.85
0.40
0.57
0.85
0.04
0.09
0.13
0.17
0.24
0.33
0.48
72
-------
30
30
30
30
30
30
30
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
19992003
19992003
19992003
19992003
19992003
19992003
19992003
1996
1996
1996
1996
1996
1996
1996
1997
1997
1997
1997
1997
1997
1997
1998
1998
1998
1998
1998
1998
1998
2004
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
122.90
122.90
122.90
122.90
122.90
122.90
122.90
78.70
78.70
78.70
78.70
78.70
78.70
78.70
83.00
83.00
83.00
83.00
83.00
83.00
83.00
115.40
115.40
115.40
115.40
115.40
115.40
115.40
145.00
145.00
145.00
145.00
145.00
145.00
145.00
150.70
150.70
150.70
150.70
150.70
150.70
150.70
145.30
145.30
145.30
145.30
19.90
19.90
19.90
19.90
19.90
19.90
19.90
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.50
19.50
19.50
19.50
19.50
19.50
19.50
20.50
20.50
20.50
20.50
20.50
20.50
20.50
20.30
20.30
20.30
20.30
20.30
20.30
20.30
20.00
20.00
20.00
20.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
73
-------
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
2006
2006
2006
2007
2007
2007
2007
2007
2007
2007
2008
2008
2008
2008
2008
2008
2008
2009
2009
2009
2009
2009
2009
2009
2010
2010
2010
2010
2010
2010
2010
2016
2016
2016
2016
2016
2016
2016
2018
2018
2018
2018
2018
2018
2018
2020
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
145.30
145.30
145.30
142.90
142.90
142.90
142.90
142.90
142.90
142.90
138.60
138.60
138.60
138.60
138.60
138.60
138.60
136.20
136.20
136.20
136.20
136.20
136.20
136.20
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
20.00
20.00
20.00
19.70
19.70
19.70
19.70
19.70
19.70
19.70
19.00
19.00
19.00
19.00
19.00
19.00
19.00
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.02
0.03
0.04
0.06
0.08
0.12
0.01
0.02
0.03
0.04
0.05
0.07
0.10
0.01
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.02
0.03
0.04
0.05
0.08
0.01
0.01
0.02
0.02
0.03
0.04
0.06
0.00
74
-------
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
41
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
2020
2020
2020
2020
2020
2020
2022
2022
2022
2022
2022
2022
2022
19601970
19711977
19711977
19781995
19781995
19781995
19781995
19781995
19781995
19781995
19992003
19992003
19992003
19992003
19992003
19992003
19992003
1996
1996
1996
1996
1996
1996
1996
1997
1997
1997
1997
1997
1997
1997
1998
1998
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
2099
1014
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
0.00
64.70
64.70
72.80
72.80
72.80
72.80
72.80
72.80
72.80
122.90
122.90
122.90
122.90
122.90
122.90
122.90
78.70
78.70
78.70
78.70
78.70
78.70
78.70
83.00
83.00
83.00
83.00
83.00
83.00
83.00
115.40
115.40
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
19.10
28.00
27.30
27.30
18.60
18.60
18.60
18.60
18.60
18.60
18.60
19.90
19.90
19.90
19.90
19.90
19.90
19.90
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.952TVG
0.814TVG
0.796TVG
0.524TVG
0.408TVG
0.388TVG
0.376TVG
0.365TVG
0.357TVG
0.351TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.02
0.03
0.03
0.04
0.06
0.09
0.01
0.02
0.02
0.03
0.04
0.05
0.08
1.00
1.00
1.00
0.05
0.12
0.18
0.23
0.32
0.45
0.66
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.01
0.01
0.02
0.02
0.03
0.04
0.00
0.01
0.01
0.01
0.01
0.02
0.03
0.85
0.85
0.04
0.09
0.13
0.17
0.24
0.33
0.48
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
75
-------
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
1998
1998
1998
1998
1998
2004
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
2006
2006
2006
2007
2007
2007
2007
2007
2007
2007
2008
2008
2008
2008
2008
2008
2008
2009
2009
2009
2009
2009
2009
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
115.40
115.40
115.40
115.40
115.40
145.00
145.00
145.00
145.00
145.00
145.00
145.00
150.70
150.70
150.70
150.70
150.70
150.70
150.70
145.30
145.30
145.30
145.30
145.30
145.30
145.30
142.90
142.90
142.90
142.90
142.90
142.90
142.90
138.60
138.60
138.60
138.60
138.60
138.60
138.60
136.20
136.20
136.20
136.20
136.20
136.20
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.06
0.07
0.10
0.13
0.18
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.04
0.05
0.07
0.10
0.14
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
76
-------
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
2009
2010
2010
2010
2010
2010
2010
2010
2016
2016
2016
2016
2016
2016
2016
2018
2018
2018
2018
2018
2018
2018
2020
2020
2020
2020
2020
2020
2020
2022
2022
2022
2022
2022
2022
2022
19601970
19711977
19711977
19781995
19781995
19781995
19781995
19781995
19781995
19781995
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
2099
1014
2099
3
405
607
809
1014
1519
2099
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
136.20
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
0.00
64.70
64.70
72.80
72.80
72.80
72.80
72.80
72.80
72.80
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.952TVG
0.814TVG
0.796TVG
0.524TVG
0.408TVG
0.388TVG
0.376TVG
0.365TVG
0.357TVG
0.351TVG
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.02
0.03
0.04
0.06
0.08
0.12
0.01
0.02
0.03
0.04
0.05
0.07
0.10
0.01
0.02
0.03
0.03
0.04
0.06
0.09
0.01
0.02
0.02
0.03
0.04
0.05
0.08
1.00
1.00
1.00
0.05
0.12
0.18
0.23
0.32
0.45
0.66
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.02
0.03
0.04
0.05
0.08
0.01
0.01
0.02
0.02
0.03
0.04
0.06
0.00
0.01
0.01
0.02
0.02
0.03
0.04
0.00
0.01
0.01
0.01
0.01
0.02
0.03
0.85
0.85
0.04
0.09
0.13
0.17
0.24
0.33
0.48
77
-------
42
42
42
42
42
42
42
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
19992003
19992003
19992003
19992003
19992003
19992003
19992003
1996
1996
1996
1996
1996
1996
1996
1997
1997
1997
1997
1997
1997
1997
1998
1998
1998
1998
1998
1998
1998
2004
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
122.90
122.90
122.90
122.90
122.90
122.90
122.90
78.70
78.70
78.70
78.70
78.70
78.70
78.70
83.00
83.00
83.00
83.00
83.00
83.00
83.00
115.40
115.40
115.40
115.40
115.40
115.40
115.40
145.00
145.00
145.00
145.00
145.00
145.00
145.00
150.70
150.70
150.70
150.70
150.70
150.70
150.70
145.30
145.30
145.30
145.30
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
78
-------
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
2006
2006
2006
2007
2007
2007
2007
2007
2007
2007
2008
2008
2008
2008
2008
2008
2008
2009
2009
2009
2009
2009
2009
2009
2010
2010
2010
2010
2010
2010
2010
2016
2016
2016
2016
2016
2016
2016
2018
2018
2018
2018
2018
2018
2018
2020
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
145.30
145.30
145.30
142.90
142.90
142.90
142.90
142.90
142.90
142.90
138.60
138.60
138.60
138.60
138.60
138.60
138.60
136.20
136.20
136.20
136.20
136.20
136.20
136.20
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.02
0.03
0.04
0.06
0.08
0.12
0.01
0.02
0.03
0.04
0.05
0.07
0.10
0.01
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.02
0.03
0.04
0.05
0.08
0.01
0.01
0.02
0.02
0.03
0.04
0.06
0.00
79
-------
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
46
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
2020
2020
2020
2020
2020
2020
2022
2022
2022
2022
2022
2022
2022
19601970
19711977
19711977
19781995
19781995
19781995
19781995
19781995
19781995
19781995
19992003
19992003
19992003
19992003
19992003
19992003
19992003
1996
1996
1996
1996
1996
1996
1996
1997
1997
1997
1997
1997
1997
1997
1998
1998
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
2099
1014
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
0.00
64.70
64.70
72.80
72.80
72.80
72.80
72.80
72.80
72.80
122.90
122.90
122.90
122.90
122.90
122.90
122.90
78.70
78.70
78.70
78.70
78.70
78.70
78.70
83.00
83.00
83.00
83.00
83.00
83.00
83.00
115.40
115.40
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.952TVG
0.814TVG
0.796TVG
0.524TVG
0.408TVG
0.388TVG
0.376TVG
0.365TVG
0.357TVG
0.351TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.02
0.03
0.03
0.04
0.06
0.09
0.01
0.02
0.02
0.03
0.04
0.05
0.08
1.00
1.00
1.00
0.05
0.12
0.18
0.23
0.32
0.45
0.66
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.01
0.01
0.02
0.02
0.03
0.04
0.00
0.01
0.01
0.01
0.01
0.02
0.03
0.85
0.85
0.04
0.09
0.13
0.17
0.24
0.33
0.48
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
80
-------
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
1998
1998
1998
1998
1998
2004
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
2006
2006
2006
2007
2007
2007
2007
2007
2007
2007
2008
2008
2008
2008
2008
2008
2008
2009
2009
2009
2009
2009
2009
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
115.40
115.40
115.40
115.40
115.40
145.00
145.00
145.00
145.00
145.00
145.00
145.00
150.70
150.70
150.70
150.70
150.70
150.70
150.70
145.30
145.30
145.30
145.30
145.30
145.30
145.30
142.90
142.90
142.90
142.90
142.90
142.90
142.90
138.60
138.60
138.60
138.60
138.60
138.60
138.60
136.20
136.20
136.20
136.20
136.20
136.20
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.06
0.07
0.10
0.13
0.18
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.04
0.05
0.07
0.10
0.14
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
81
-------
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
47
2009
2010
2010
2010
2010
2010
2010
2010
2016
2016
2016
2016
2016
2016
2016
2018
2018
2018
2018
2018
2018
2018
2020
2020
2020
2020
2020
2020
2020
2022
2022
2022
2022
2022
2022
2022
19601970
19711977
19711977
19781995
19781995
19781995
19781995
19781995
19781995
19781995
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
2099
1014
2099
3
405
607
809
1014
1519
2099
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
136.20
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
0.00
64.70
64.70
72.80
72.80
72.80
72.80
72.80
72.80
72.80
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.952TVG
0.814TVG
0.796TVG
0.524TVG
0.408TVG
0.388TVG
0.376TVG
0.365TVG
0.357TVG
0.351TVG
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.02
0.03
0.04
0.06
0.08
0.12
0.01
0.02
0.03
0.04
0.05
0.07
0.10
0.01
0.02
0.03
0.03
0.04
0.06
0.09
0.01
0.02
0.02
0.03
0.04
0.05
0.08
1.00
1.00
1.00
0.05
0.12
0.18
0.23
0.32
0.45
0.66
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.02
0.03
0.04
0.05
0.08
0.01
0.01
0.02
0.02
0.03
0.04
0.06
0.00
0.01
0.01
0.02
0.02
0.03
0.04
0.00
0.01
0.01
0.01
0.01
0.02
0.03
0.85
0.85
0.04
0.09
0.13
0.17
0.24
0.33
0.48
82
-------
47
47
47
47
47
47
47
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
19992003
19992003
19992003
19992003
19992003
19992003
19992003
1996
1996
1996
1996
1996
1996
1996
1997
1997
1997
1997
1997
1997
1997
1998
1998
1998
1998
1998
1998
1998
2004
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
122.90
122.90
122.90
122.90
122.90
122.90
122.90
78.70
78.70
78.70
78.70
78.70
78.70
78.70
83.00
83.00
83.00
83.00
83.00
83.00
83.00
115.40
115.40
115.40
115.40
115.40
115.40
115.40
145.00
145.00
145.00
145.00
145.00
145.00
145.00
150.70
150.70
150.70
150.70
150.70
150.70
150.70
145.30
145.30
145.30
145.30
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.03
0.05
0.06
0.07
0.10
0.13
0.18
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.02
0.04
0.04
0.05
0.07
0.10
0.14
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
83
-------
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
2006
2006
2006
2007
2007
2007
2007
2007
2007
2007
2008
2008
2008
2008
2008
2008
2008
2009
2009
2009
2009
2009
2009
2009
2010
2010
2010
2010
2010
2010
2010
2016
2016
2016
2016
2016
2016
2016
2018
2018
2018
2018
2018
2018
2018
2020
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
0.24
145.30
145.30
145.30
142.90
142.90
142.90
142.90
142.90
142.90
142.90
138.60
138.60
138.60
138.60
138.60
138.60
138.60
136.20
136.20
136.20
136.20
136.20
136.20
136.20
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
137.50
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
38.00
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.40
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.524TVG
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.03
0.04
0.05
0.07
0.10
0.15
0.01
0.02
0.03
0.04
0.06
0.08
0.12
0.01
0.02
0.03
0.04
0.05
0.07
0.10
0.01
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.03
0.04
0.05
0.08
0.11
0.01
0.02
0.02
0.03
0.04
0.05
0.08
0.01
0.01
0.02
0.02
0.03
0.04
0.06
0.00
84
-------
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
48
2020 405
2020 607
2020 809
2020 1014
2020 1519
2020 2099
2022 3
2022 405
2022 607
2022 809
2022 1014
2022 1519
2022 2099
19601970 2099
19711977 1014
19711977 2099
19781995 3
19781995 405
19781995 607
19781995 809
19781995 1014
19781995 1519
19781995 2099
19992003 3
19992003 405
19992003 607
19992003 809
19992003 1014
19992003 1519
19992003 2099
0.24 137.50
0.24 137.50
0.24 137.50
0.24 137.50
0.24 137.50
0.24 137.50
0.24 137.50
0.24 137.50
0.24 137.50
0.24 137.50
0.24 137.50
0.24 137.50
0.24 137.50
0.24 0.00
0.24 64.70
0.24 64.70
0.24 72.80
0.24 72.80
0.24 72.80
0.24 72.80
0.24 72.80
0.24 72.80
0.24 72.80
0.24 122.90
0.24 122.90
0.24 122.90
0.24 122.90
0.24 122.90
0.24 122.90
0.24 122.90
38.00 0.40 0.524TVG 0.02
38.00 0.40 0.524TVG 0.03
38.00 0.40 0.524TVG 0.03
38.00 0.40 0.524TVG 0.04
38.00 0.40 0.524TVG 0.06
38.00 0.40 0.524TVG 0.09
38.00 0.40 0.524TVG 0.01
38.00 0.40 0.524TVG 0.02
38.00 0.40 0.524TVG 0.02
38.00 0.40 0.524TVG 0.03
38.00 0.40 0.524TVG 0.04
38.00 0.40 0.524TVG 0.05
38.00 0.40 0.524TVG 0.08
38.00 0.40 0.952TVG 1.00
38.00 0.40 0.814TVG 1.00
38.00 0.40 0.796TVG 1.00
38.00 0.40 0.524TVG 0.05
38.00 0.40 0.408TVG 0.12
38.00 0.40 0.388TVG 0.18
38.00 0.40 0.376TVG 0.23
38.00 0.40 0.365TVG 0.32
38.00 0.40 0.357TVG 0.45
38.00 0.40 0.351TVG 0.66
38.00 0.40 0.524TVG 0.03
38.00 0.40 0.524TVG 0.05
38.00 0.40 0.524TVG 0.06
38.00 0.40 0.524TVG 0.07
38.00 0.40 0.524TVG 0.10
38.00 0.40 0.524TVG 0.13
38.00 0.40 0.524TVG 0.18
0.01
0.01
0.02
0.02
0.03
0.04
0.00
0.01
0.01
0.01
0.01
0.02
0.03
0.85
0.85
0.04
0.09
0.13
0.17
0.24
0.33
0.48
0.02
0.04
0.04
0.05
0.07
0.10
0.14
Table 26: MOVES Cumulative Tank Vapor Vented Table (2)
RegCls
10
10
10
10
10
10
10
10
10
10
MYG TankVaporVentingEquation
1996 -(-lx+85)-
1997 -(-lx+85)-
1998 -(-lx+85)-
2004 -(-lx+85)-
2005 -(-lx+85)-
2006 -(-lx+85)-
2007 -(-lx+85)-
2008 -(-lx+85)-
2009 -(-lx+85)-
2010 -(-lx+85)-
Fsqrt(((-lx+85)*(-lx-
Fsqrt(((-lx+85)*(-lx-
Fsqrt(((-lx+85)*(-lx-
Fsqrt(((-lx+85)*(-lx-
Fsqrt(((-lx+85)*(-lx-
Fsqrt(((-lx+85)*(-lx-
Fsqrt(((-lx+85)*(-lx-
Fsqrt(((-lx+85)*(-lx-
Fsqrt(((-lx+85)*(-lx-
Fsqrt(((-lx+85)*(-lx-
h85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25))
|-85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25))
|-85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25))
|-85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25))
|-85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25))
|-85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25))
|-85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25))
|-85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25))
|-85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25))
|-85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25))
85
-------
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
20
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
19711977
19781995
19992003
20312050
1996
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
-(-lx+85)
.8*(-(-lx-f
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-sqrt(((-lx+85)*(-lx-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-85))-(4*1.25)*(-0.25xx+.2x-
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
-70)))/(2*1.25))
85))-(4*1.25)*(-0.25xx+.2x-
.8*(-(-lx+85)+sqrt(((-lx+85)*(-lx+85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25)+.2*(-(-
1.34x+115)+sqrt(((-1.34x+115)*(-1.34x+115))-(4*1.90)*(-0.125xx+2.70x+23)))/(2*1.90)))
20 1997 .6*(-(-lx+85)+sqrt(((-lx+85)*(-lx+85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25)+.4*(-(-
1.34x+115)+sqrt(((-1.34x+115)*(-1.34x+115))-(4*1.90)*(-0.125xx+2.70x+23)))/(2*1.90)))
20 1998 .l*(-(-lx+85)+sqrt(((-lx+85)*(-lx+85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25)+.9*(-(-
1.34x+115)+sqrt(((-1.34x+115)*(-1.34x+115))-(4*1.90)*(-0.125xx+2.70x+23)))/(2*1.90)))
20 2004 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx+3.12x+20)))/(2*1.15;
20 2005 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx+3.12x+20)))/(2*1.15;
20 2006 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx+3.12x+20)))/(2*1.15'
20 2007 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2008 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2009 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2010 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2011 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2012 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2013 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2014 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2015 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2016 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2017 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2018 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
20 2019 -(-1.21x+187)+sqrt(((-1.21x+187)*(-1.21x+187))-(4*1.15)*(-0.071xx-
-3.12x+20)))/(2*1.15
-3.12x+20)))/(2*1.15
-3.12x+20)))/(2*1.15;
-3.12x+20)))/(2*1.15;
-3.12x+20)))/(2*1.15'
-3.12x+20)))/(2*1.15
-3.12x+20)))/(2*1.15
-3.12x+20)))/(2*l-15
-3.12x+20)))/(2*1.15'
-3.12x+20)))/(2*1.15
-3.12x+20)))/(2*1.15
-3.12x+20)))/(2*l-15
-3.12x+20)))/(2*1.15'
86
-------
20 2020 -(-1.21x+187)+sqrt(((-1.21x+18
20 2021 -(-1.21x+187)+sqrt(((-1.21x+18
20 2022 -(-1.21x+187)+sqrt(((-1.21x+18
20 2023 -(-1.21x+187)+sqrt(((-1.21x+18
20 2024 -(-1.21x+187)+sqrt(((-1.21x+18
20 2025 -(-1.21x+187)+sqrt(((-1.21x+18
20 2026 -(-1.21x+187)+sqrt(((-1.21x+18
20 2027 -(-1.21x+187)+sqrt(((-1.21x+18
20 2028 -(-1.21x+187)+sqrt(((-1.21x+18
20 2029 -(-1.21x+187)+sqrt(((-1.21x+18
20 2030 -(-1.21x+187)+sqrt(((-1.21x+18
20 19601970 -(-lx+85)+sqrt(((-lx+85)*(-lx-
20 19992003 -(-1.34x+115)+sqrt(((-1.34x+ll
20 20312050 -(-1.21x+187)+sqrt(((-1.21x+18
7)*(-1.21x+187))-(4*1.15)
7)*(-1.21x+187))-(4*1.15)
7)*(-1.21x+187))-(4*1.15)
7)*(-1.21x+187))-(4*1.15)
7)*(-1.21x+187))-(4*1.15)
7)*(-1.21x+187))-(4*1.15)
7)*(-1.21x+187))-(4*1.15)
7)*(-1.21x+187))-(4*1.15)
7)*(-1.21x+187))-(4*1.15)
7)*(-1.21x+187))-(4*1.15)
7)*(-1.21x+187))-(4*1.15)
*(-0.071xx+3.12x+20)))/(2*1.15
*(-0.071xx+3.12x+20)))/(2*1.15
*(-0.071xx+3.12x+20)))/(2*1.15
*(-0.071xx+3.12x+20)))/(2*1.15
*(-0.071xx+3.12x+20)))/(2*1.15
*(-0.071xx+3.12x+20)))/(2*1.15
*(-0.071xx+3.12x+20)))/(2*1.15
*(-0.071xx+3.12x+20)))/(2*1.15
*(-0.071xx+3.12x+20)))/(2*1.15
*(-0.071xx+3.12x+20)))/(2*1.15
*(-0.071xx+3.12x+20)))/(2*1.15
h85))-(4*1.25)*(-0.25xx+.2x+70)))/(2*1.25))
5)*(-1.34x+115))-(4*1.90)
7)*(-1.21x+187))-(4*1.15)
*(-0.125xx+2.70x+23)))/(2*1.90
*(-0.071xx+3.12x+20)))/(2*1.15
Table 27: MOVES Permeation Rates
RegClass MYG AgeGroup
Doesn't Matter 1970 and earlier 2099
Doesn't Matter 1971 thru 1977 1014
Doesn't Matter 1971 thru 1977 1519
Doesn't Matter 1971 thru 1977 2099
Doesn't Matter 1978 thru 1995 3
Doesn't Matter 1978 thru 1995 607
Doesn't Matter 1978 thru 1995 1014
Doesn't Matter 1978 thru 1995 1519
Doesn't Matter 1978 thru 1995 2099
Doesn't Matter 1996 3
Doesn't Matter 1996 607
Doesn't Matter 1996 1014
Doesn't Matter 1996 1519
Doesn't Matter 1996 2099
Doesn't Matter 1996 thru 2003 3
Doesn't Matter 1997 3
Doesn't Matter 1997 607
Doesn't Matter 1997 1014
Doesn't Matter 1997 1519
Doesn't Matter 1997 2099
Doesn't Matter 1998 3
Doesn't Matter 1998 607
Doesn't Matter 1998 1014
Doesn't Matter 1998 1519
Doesn't Matter 1998 2099
Doesn't Matter 1999 thru 2003 3
MeanBaseRate MeanBaseRatelM
0.31
0.19
0.23
0.31
0.06
0.09
0.12
0.15
0.20
0.05
0.08
0.10
0.12
0.16
0.01
0.04
0.06
0.08
0.09
0.12
0.01
0.02
0.02
0.02
0.03
0.01
0.31
0.19
0.23
0.31
0.06
0.09
0.12
0.15
0.20
0.05
0.08
0.10
0.12
0.16
0.01
0.04
0.06
0.08
0.09
0.12
0.01
0.02
0.02
0.02
0.03
0.01
87
-------
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
Doesn't Matter
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031 thru 2050
1980 and earlier
1981 thru 1982
1983 thru 1984
1985
1986 thru 1987
1988 thru 1989
1990
1991 thru 1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
0.12
-------
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
RegClass
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031 thru 2050
Table 28
MYG
1970 and earlier
1971 thru 1977
1971 thru 1977
1971 thru 1977
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1980 and earlier
1981 thru 1982
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
: MOVES Hot
0.12
0.12
0.12
0.12
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
Soak Rates
0.12
0.12
0.12
0.12
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
0.01
AgeGroup MeanBaseRate MeanBaseRatelM
2099
1014
1519
2099
3
607
809
1014
1519
2099
3
3
5.45
3.10
5.15
5.45
0.63
1.45
1.47
2.08
3.49
3.82
8.53
8.53
5.12
2.96
4.88
5.12
0.61
1.43
1.46
1.96
3.22
3.49
8.53
8.53
89
-------
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
1983 thru 1984
1985
1986 thru 1987
1988 thru 1989
1990
1991 thru 1993
1994
1995
1996
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1997
1998
1999
1999 thru 2003
1999 thru 2003
1999 thru 2003
1999 thru 2003
1999 thru 2003
1999 thru 2003
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
3
3
3
3
3
3
3
3
3
3
607
809
1014
1519
2099
3
3
3
3
607
809
1014
1519
2099
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.53
0.63
1.45
1.47
2.08
3.49
3.82
8.53
8.53
8.53
0.63
1.45
1.47
2.08
3.49
3.82
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.53
0.61
1.43
1.46
1.96
3.22
3.49
8.53
8.53
8.53
0.61
1.43
1.46
1.96
3.22
3.49
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
90
-------
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031 thru 2050
1970 and earlier
1971 thru 1977
1971 thru 1977
1971 thru 1977
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1996
1996
1996
1996
1996
1996
1996
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1997
1997
1997
1997
1997
1997
1997
1998
1998
1998
1998
3
3
3
3
3
3
3
3
3
3
2099
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
23.29
9.00
12.77
16.38
0.82
1.39
1.76
2.13
2.78
3.74
5.19
0.29
0.46
0.57
0.68
0.92
1.21
1.66
0.29
0.46
0.57
0.68
0.92
1.21
1.66
0.29
0.46
0.57
0.68
0.92
1.21
1.66
0.29
0.46
0.57
0.68
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
19.85
6.71
9.50
13.98
0.66
1.08
1.36
1.63
2.11
2.83
3.93
0.24
0.37
0.45
0.53
0.72
0.93
1.27
0.24
0.37
0.45
0.53
0.72
0.93
1.27
0.24
0.37
0.45
0.53
0.72
0.93
1.27
0.24
0.37
0.45
0.53
91
-------
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
1998
1998
1998
1999 thru 2003
1999 thru 2003
1999 thru 2003
1999 thru 2003
1999 thru 2003
1999 thru 2003
1999 thru 2003
2004
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
2006
2006
2006
2007
2007
2007
2007
2007
2007
2007
2008
2008
2008
2008
2008
2008
2008
2009
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
0.92
1.21
1.66
0.29
0.46
0.57
0.68
0.92
1.21
1.66
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.72
0.93
1.27
0.24
0.37
0.45
0.53
0.72
0.93
1.27
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
92
-------
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
2009
2009
2009
2009
2009
2009
2010
2010
2010
2010
2010
2010
2010
2011
2011
2011
2011
2011
2011
2011
2012
2012
2012
2012
2012
2012
2012
2013
2013
2013
2013
2013
2013
2013
2014
2014
2014
2014
2014
2014
2014
2015
2015
2015
2015
2015
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
93
-------
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
2015
2015
2016
2016
2016
2016
2016
2016
2016
2017
2017
2017
2017
2017
2017
2017
2018
2018
2018
2018
2018
2018
2018
2019
2019
2019
2019
2019
2019
2019
2020
2020
2020
2020
2020
2020
2020
2021
2021
2021
2021
2021
2021
2021
2022
2022
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
0.86
1.24
0.16
0.23
0.31
0.38
0.51
0.70
1.01
0.16
0.23
0.31
0.38
0.51
0.70
1.01
0.15
0.20
0.27
0.34
0.46
0.62
0.89
0.15
0.20
0.27
0.34
0.46
0.62
0.89
0.14
0.18
0.24
0.30
0.40
0.54
0.77
0.14
0.18
0.24
0.30
0.40
0.54
0.77
0.13
0.16
0.65
0.93
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.12
0.13
0.17
0.21
0.27
0.37
0.52
0.12
0.13
0.17
0.21
0.27
0.37
0.52
0.11
0.10
0.13
0.16
0.21
0.27
0.38
0.11
0.10
0.13
0.16
0.21
0.27
0.38
0.10
0.08
94
-------
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
2022
2022
2022
2022
2022
2023
2023
2023
2023
2023
2023
2023
2024
2024
2024
2024
2024
2024
2024
2025
2025
2025
2025
2025
2025
2025
2026
2026
2026
2026
2026
2026
2026
2027
2027
2027
2027
2027
2027
2027
2028
2028
2028
2028
2028
2028
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
95
-------
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
RegClass
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
2028
2029
2029
2029
2029
2029
2029
2029
2030
2030
2030
2030
2030
2030
2030
2031 thru 2050
2031 thru 2050
2031 thru 2050
2031 thru 2050
2031 thru 2050
2031 thru 2050
2031 thru 2050
Table 29:
MYG
1970 and earlier
1971 thru 1977
1971 thru 1977
1971 thru 1977
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1980 and earlier
1981 thru 1982
1983 thru 1984
1985
1986 thru 1987
1988 thru 1989
1990
1991 thru 1993
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
MOVES Running Loss
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
Rates
AgeGroup MeanBaseRate
2099
1014
1519
2099
3
607
809
1014
1519
2099
3
3
3
3
3
3
3
3
5.45
3.10
5.15
5.45
0.63
1.45
1.47
2.08
3.49
3.82
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.53
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
MeanBaseRatelM
5.12
2.96
4.88
5.12
0.61
1.43
1.46
1.96
3.22
3.49
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.53
96
-------
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
MC
1994
1995
1996
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1997
1998
1999
1999 thru 2003
1999 thru 2003
1999 thru 2003
1999 thru 2003
1999 thru 2003
1999 thru 2003
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
3
3
3
3
607
809
1014
1519
2099
3
3
3
3
607
809
1014
1519
2099
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
8.53
8.53
8.53
0.63
1.45
1.47
2.08
3.49
3.82
8.53
8.53
8.53
0.63
1.45
1.47
2.08
3.49
3.82
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.53
8.53
8.53
0.61
1.43
1.46
1.96
3.22
3.49
8.53
8.53
8.53
0.61
1.43
1.46
1.96
3.22
3.49
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.53
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
8.67
97
-------
MC
MC
MC
MC
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
2028
2029
2030
2031 thru 2050
1970 and earlier
1971 thru 1977
1971 thru 1977
1971 thru 1977
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1978 thru 1995
1996
1996
1996
1996
1996
1996
1996
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1996 thru 2003
1997
1997
1997
1997
1997
1997
1997
1998
1998
1998
1998
1998
1998
1998
1999 thru 2003
1999 thru 2003
1999 thru 2003
3
3
3
3
2099
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
8.67
8.67
8.67
8.67
23.29
9.00
12.77
16.38
0.82
1.39
1.76
2.13
2.78
3.74
5.19
0.29
0.46
0.57
0.68
0.92
1.21
1.66
0.29
0.46
0.57
0.68
0.92
1.21
1.66
0.29
0.46
0.57
0.68
0.92
1.21
1.66
0.29
0.46
0.57
0.68
0.92
1.21
1.66
0.29
0.46
0.57
8.67
8.67
8.67
8.67
19.85
6.71
9.50
13.98
0.66
1.08
1.36
1.63
2.11
2.83
3.93
0.24
0.37
0.45
0.53
0.72
0.93
1.27
0.24
0.37
0.45
0.53
0.72
0.93
1.27
0.24
0.37
0.45
0.53
0.72
0.93
1.27
0.24
0.37
0.45
0.53
0.72
0.93
1.27
0.24
0.37
0.45
98
-------
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
1999 thru 2003
1999 thru 2003
1999 thru 2003
1999 thru 2003
2004
2004
2004
2004
2004
2004
2004
2005
2005
2005
2005
2005
2005
2005
2006
2006
2006
2006
2006
2006
2006
2007
2007
2007
2007
2007
2007
2007
2008
2008
2008
2008
2008
2008
2008
2009
2009
2009
2009
2009
2009
2009
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
0.68
0.92
1.21
1.66
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.53
0.72
0.93
1.27
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
99
-------
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
2010
2010
2010
2010
2010
2010
2010
2011
2011
2011
2011
2011
2011
2011
2012
2012
2012
2012
2012
2012
2012
2013
2013
2013
2013
2013
2013
2013
2014
2014
2014
2014
2014
2014
2014
2015
2015
2015
2015
2015
2015
2015
2016
2016
2016
2016
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.18
0.27
0.37
0.46
0.63
0.86
1.24
0.16
0.23
0.31
0.38
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.16
0.21
0.28
0.35
0.48
0.65
0.93
0.13
0.16
0.21
0.26
100
-------
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
2016
2016
2016
2017
2017
2017
2017
2017
2017
2017
2018
2018
2018
2018
2018
2018
2018
2019
2019
2019
2019
2019
2019
2019
2020
2020
2020
2020
2020
2020
2020
2021
2021
2021
2021
2021
2021
2021
2022
2022
2022
2022
2022
2022
2022
2023
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
0.51
0.70
1.01
0.16
0.23
0.31
0.38
0.51
0.70
1.01
0.15
0.20
0.27
0.34
0.46
0.62
0.89
0.15
0.20
0.27
0.34
0.46
0.62
0.89
0.14
0.18
0.24
0.30
0.40
0.54
0.77
0.14
0.18
0.24
0.30
0.40
0.54
0.77
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.12
0.13
0.17
0.21
0.27
0.37
0.52
0.12
0.13
0.17
0.21
0.27
0.37
0.52
0.11
0.10
0.13
0.16
0.21
0.27
0.38
0.11
0.10
0.13
0.16
0.21
0.27
0.38
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
101
-------
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
2023
2023
2023
2023
2023
2023
2024
2024
2024
2024
2024
2024
2024
2025
2025
2025
2025
2025
2025
2025
2026
2026
2026
2026
2026
2026
2026
2027
2027
2027
2027
2027
2027
2027
2028
2028
2028
2028
2028
2028
2028
2029
2029
2029
2029
2029
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
102
-------
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
LDV
2029
2029
2030
2030
2030
2030
2030
2030
2030
2031 thru 2050
2031 thru 2050
2031 thru 2050
2031 thru 2050
2031 thru 2050
2031 thru 2050
2031 thru 2050
1519
2099
3
405
607
809
1014
1519
2099
3
405
607
809
1014
1519
2099
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.13
0.16
0.21
0.26
0.34
0.46
0.65
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
0.10
0.08
0.10
0.11
0.14
0.18
0.24
5 References
[1] EPA Certification Data, http://www.epa.gov/otaq/certdata.htm.
[2] CRC E-9 Measurement of Diurnal Emissions from In- Use Vehicles, http: //www. crcao. com/
reports/emission/eg.htm, September 1998.
[3] CRC E-41-1 Real World Evaporative Testing of Late-Model In-Use Vehicles, http://www.
crcao.com/reports/emission/e41.htm, October 1999.
[4] CRC E-41-2 Evaporative Emissions from Late-Model In-Use Vehicles, http://www.crcao.
com/reports/emission/e41.htm, October 1999.
[5] Transportation And Marketing Of Petroleum Liquids, http://www.epa.gov/ttnchiel/ap42/
ch05/final/c05s02.pdf, June 2008.
[6] Wards Automotive Group. Summary Sales Data,, http://http://wardsauto.com/keydata/
historical/UsaSaOlsummary.
[7] J. Brown. The DELTA Model: Improved Evaporative Emissions Modeling for EPA
MOVES. http: //www. epa. gov/otaq/models/moves/documents/f aca-meet ing-j an2013/
04-delta.pdf, 2011.
[8] P. Caffrey and P. Machiele. In-use Volatility Impact of Commingling Ethanol and Non-Ethanol
Fuels, http://papers.sae.org/940765/, 1994.
[9] T. Cam, K. Cullen, S. Baldus, and K. Sime. Running Loss Temperature Profiles, http:
//papers.sae.org/930078/, 1993.
103
-------
[10] P. Cingle and D. McClement. Uncontrolled Automotive Refueling Emissions. http://www.
ntis.gov/search/product.aspx?ABBR=PB88193099, January 1988.
[11] Timothy H. DeFries. Estimated Summer Hot-Soak Distributions for Denvers Ken Caryl IM
Station Fleet, 2013.
[12] Timothy H. DeFries, J. Lindner, S. Kishan, and C. Palacios. Investigation of Techniques for
High Evaporative Emissions Vehicle Detection: Denver Summer 2008 Pilot Study at Lipan
Street Station, 2009.
[13] Edmund's. Vehicle Fuel Tank Data, http://www.edmunds.com/.
[14] U.S. EPA. MOBILE6 Emissions Model, http://www.epa.gov/otaq/m6.htm.
[15] U.S. EPA. Air Toxic Emissions from On-road Vehicles in MOVES2014- http://www.epa.
gov/otaq/models/moves/documents/420rl4021.pdf, September 2014.
[16] U.S. EPA. Population and Activity of on-road vehicles in MOVES2014- http://www.epa.gov/
otaq/models/moves/documents/420dl4002.pdf, 2014.
[17] U.S. EPA. Speciation of Total Organic Gas and Particulate Matter Emissions from On-road
Vehicles in MOVES2014. http: //www. epa. gov/otaq/models/moves/documents/420r 14020.
pdf, September 2014.
[18] Randall Guensler and Georgia Institute of Technology. Atlanta Commute Vehicle Soak and
Start Distributions and Engine Starts per Day: Impact on Mobile Source Emission Rates.
http://transportation.ce.gatech.edu/sites/default/files/files/atlanta_commute_
vehucle_soak_and_start_time_distributions_and_engine_starts.pdf, April 2007.
[19] Harold M. Haskew and Associates Inc. CRC E-35 Measurement of Running Loss Emissions
from, In-Use Vehicles, http://www.crcao.com/reports/emission/e35.htm, February 1998.
[20] Harold M. Haskew and Thomas F. Liberty. CRC E-77 Vehicle Evaporative Emission
Mechanisms: A Pilot Study. http://www.crcao.com/reports/recentstudies2008/E-777o
20Pilot7.20Study/E-777.20Pilot7.20Study7.20Final7.20Report7.206.24.08.pdf, June 2008.
[21] Harold M. Haskew and Thomas F. Liberty. CRC E-77-21) Evaporative Emissions From In-use
Vehicles: Test Fleet Expansion, http://www.epa.gov/otaq/emission-factors-research/
420rl0025.pdf, October 2010.
[22] Harold M. Haskew and Thomas F. Liberty. CRC E-77-2c Study to Deter-
mine Evaporative Emission Breakdown, Including Permeation Effects and Diurnal Emi-
sisons Using E20 Fuels on Aging Enhanced Evaporative Emisisons Certified Vehi-
cles, http: //www. crcao. com/reports/recentstudies2011/E-77-2c/E-77-2c7.20Final7.
20Report7.20for7.20sure7.201-28-ll.pdf, December 2010.
[23] Harold M. Haskew and Thomas F. Liberty. CRC E-77-2 Enhanced Evaporative Emission
Vehicles. http://www.crcao.com/reports/recentstudies2010/E-77-2/E-77-2_Final_
Report__March_2010.pdf, March 2010.
104
-------
[24] Harold M. Haskew, Thomas F. Liberty, and Dennis McClement. CRC E-65 Fuel Perme-
ation from Automotive Systems. http://www.crcao.com/reports/recentstudies2004/E657o
20Final7.20Report7.2097.2027.2004.pdf, September 2004.
[25] Harold M. Haskew, Thomas F. Liberty, and Dennis McClement. CRC E-65-3 Fuel Permeation
from Automotive Systems: EO, E6, E10, E20, and E85. http://www.crcao.com/reports/
recentstudies2006/E-65-3/CRC7.20E-65-3%20Final7.20Report .pdf, December 2006.
[26] H.R. Johnson and R.S. Williams. Performance of Activated Carbon in Evaporative Loss Control
Systems, http://papers.sae.org/902119/, 1990.
[27] Jim Kemper. High Evaporative Emitter Repairs, http://www.sae.org/servlets/works/
upcomingmeetingResources.do?eventGenNum=10105, December 2010.
J Linder and G Glinsky. Multi-Day Diurnal Testing, February 2012.
E.M. Liston, American Petroleum Institute, and Stanford Research Institute. A Study of
Variables that Effect the Amount of Vapor Emitted During the Refueling of Automobiles, http:
//books.google.com/books?id=KW2IGwAACAAJ, 1975.
S.R. Reddy and Society of Automotive Engineers. Prediction of Fuel Vapor Generation from
a Vehicle Fuel Tank as a Function of Fuel Reid Vapor Pressure and Temperature, http:
//books.google.com/books?id=JTvEHAAACAAJ, 1989.
[31] Sierra Research. United States Motor Vehicle Inspection and Maintenance (I/M) Programs.
http://www.sierraresearch.com/ReportListing.htm, December 2005.
[32] Sierra Research. Development of Trip and Soak Activity Defaults for Passenger Cars and Trucks
in MOVES2006. http://www.sierraresearch.com/ReportListing.htm, March 2006.
[33] Sierra Research. Development of Trip and Soak Activity Defaults for Passenger Cars and
Trucks in MOVES. http://www.sierraresearch.com/ReportListing.htm, June 2007.
[34] M. Sabisch, S. Kishan, Inc. Eastern Research Group, J. Stewart, G. Glinsky, and SGS Envi-
ronmental Testing Corporation. Running loss testing with implanted leaks, 2014.
[35] G. Schremp and California Energy Commission. Fuels & Transportation Division. Ab 868
: Fuel delivery temperature study staff report overview and findings: Committee workshop.
http://books.google.com/books?id=MdOJPwAACAAJ, 2008.
M. Weatherby, M. Sabisch, and S. Kishan. Analysis of Evaporative On-Board Diagnostic (OBD)
Readiness and DTCs Using I/M Data, 2014.
105
------- |