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Response to EPA’s Stack Test Questions

Frequency of stack testing (emission factor variability): The answers to these questions will 

help EPA to determine the appropriate frequency of stack testing.

1. Please provide the per-gas emission factors (EFs) and by-product emission factors (BEFs) 

across fabs (kg emissions/kg input) that you have collectively measured. Please provide 

each EF and BEF for each measurement campaign at each fab (i.e., not averages over 

multiple months or years). Please identify the fabs, linewidths, product mixes, and dates 

from which the emission factors come. If Company D measured N2O emissions during the 

March and August runs, what were these emissions and emission factors? 

Response: Emission Factor calculations are in progress for Company D Fabs 1 and 2, Company F 

fab 1 and fab 2, and Company E fab. We expect to provide the results to EPA during the week of

February 20, 2012. Company D Fab 3 is not included because data required to generate emission 

factors was not collected. IBM testing occurred on a subset of the fab’s stacks for the purpose of 

validating the FTIR method and evaluating stack sampling methods; testing and collected data 

does not allow for development of fab-wide emission factors. 

2. The NF3 emissions in Company D’s report are higher in Table 3-9 (August) than in Table 2-

1-1 (March), even though Company D’s presentation and December 14 update indicate 

that both NF3 consumption and the NF3 emission rate were lower in August. We think 

that Tables 3-9 and 2-1-1 may have inadvertently been reversed. (That is, Table 3-9 

actually shows the March results, while Table 2-1-1 actually shows the August results.) 

Can you confirm this?

Table 3-9 and Table 2-1-1 were not reversed; however, a follow-up analysis of the data for 

August found that emissions were erroneously calculated in August due to a copy syntax 

error (August Table 3-9). This resulted in the use of the molecular weight of SF6 for the 

conversion of ppbv to lbs./hr. for both CF4 and NF3 for the August test. The data from the 

two tables and the corrected values are shown in Table 2-1. The August emissions values for 

both CF4 and NF3 now agree very well with the December update. The emission factor 

calculations were not affected by this error.

Table 2-1: Summary of the Data from Tables 2-1-1 and 3-9 Showing the Corrected Values 

Dec. 2011 

Update

Dec. 2011 

Update 

NF3 NF3 NF3 CF4 CF4 CF4

Fab 1, Stacks 1 & 2 Kg/24 hrs lb/hr lb/hr Kg/ 24hrs lb/hr lb/hr

Table 2-1-1 March 5.57 0.51 0.50 6.97 0.64 0.61

Table 3-9 August 8.39 0.77 0.32 10.65 0.98 0.57

Table 3-9 August corrected 0.33 August corrected 0.59

Erroneous data

Sept. 2011 Report Sept. 2011 Report

Emissions Emissions

Accounting for destruction device downtime: The answer to this question will help EPA to 

determine how a facility would account for emission rate increases when destruction devices 

are off.
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3. Slide 4 of the technical presentation states that the method will need to track abatement 

downtime and adjust annual emissions of each gas accordingly. Does SIA mean that stack 

EFs should be adjusted accordingly? If so, how would SIA propose they be adjusted? Such 

an adjustment would apparently require estimates of DRE and gas flows (i.e., 

apportioning) to the affected tools. 

Response: 

Procedure for estimating impact of downtime on annual emissions

1. Determine the number of process tools using a given F-gas

2. Determine the total annual (or monthly) consumption of that F-gas

3. Decide what the average overall DRE for the abatement devices treating the tools using 

that F-gas is. The DRE will either be the default factor under the rule or the fab specific 

DRE determined by the testing prescribed under the rule.

4. Apply an emission factor to the chemical use to estimate the annual (or monthly) 

emissions of that F-gas. The emission factor should be the one established by the 

reporting rule, or developed via stack test methods as defined in the reporting rule. If 

reporting rule defaults are used, the pre-abated emissions estimate is simply equal to the 

chemical use times the EF without applying a DRE value for abatement. If stack test 

results are used, the emission factor already accounts for abatement. POU abatement 

status must be tracked during testing and the calculated stack EF should be based on the 

emissions that would occur if 100% of the abatement systems were operating. The preabated EF under this approach should be calculated by assuming that all of the 

abatement devices are turned off, using the information collected in steps 1-3 above. 

For example, if 100% of the process tools using that gas have abatement with an 

average DRE of 95%, pre-abated emissions = (post abated emissions)/(1-.95). 

5. Develop an hourly pre-abated emissions estimate for that F-gas by assuming emissions 

are steady throughout the year and dividing the annual (or monthly) pre-abated number 

by the number of hours per year (or month).

6. Estimate the unabated hourly emissions per tool by assuming use is evenly divided 

among the tools and dividing the hourly number developed in step 5 by the number of 

tools using that F-gas, as determined in step 1 

7. From internal monitoring systems, determine the value

tpd: the total time, in minutes, that the abatement system is not operational for the 

reporting year for each abatement system. 

Add the values for all systems together and divide by 60 to determine the total number 

of abatement downtime hours experienced. 

8. The incremental emissions due to downtime will be the emissions over and above what 

would have occurred if the abatement unit had been operating. This can be calculated 

as shown:

Incremental emissions = Hourly unabated emissions x average DRE

This value should be multiplied by the number of downtime hours determined in step 7 and 

should then be added to the annual total emissions calculated from the emission factor 

values determined from the stack tests. 
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Example calculation

Annual CF4 use = 5,000 kg

Average emission factor = 0.8

Number of CF4 using tools = 10

Number of tools with POU abatement devices = 5

Average point of use device DRE = 95%

Total # of hrs of downtime, all devices combined = 200 hours

Unabated annual CF4 emissions rate = 5,000 kg *0.8 = 4,000 kg

Average hourly unabated CF4 emissions = 4000/8760 = 0.46 kg/hr

Average unabated hourly CF4 emissions per tool = 0.46/10 = 0.046 kg/hr

Incremental unabated emissions per tool = 0.046 x (0.95) = .044 kg/hr

Total incremental emissions from downtime = 0.044 kg/hr x 200 hrs. = 8.8 kg

CF4 GWP = 6500

Total incremental downtime emissions = 8.8 kg x 6500/1000 = 57.2 metric tons CO2e

This value should be added to the emissions calculated from the stack test method.

Measuring gas consumption during the test period: The answer to this question will help EPA 

understand the information SIA presented regarding factors that affect gas consumption 

measurements during emission tests and the resulting EF.

4. Based on the presentations SIA gave, it appears that measurements of gas consumption 

may sometimes be affected by temperature fluctuations and/or low drawdown rates.

These issues may have a significant impact on the short-term gas consumption 

measurements used to establish emission factors. Where temperature fluctuations or low 

drawdown rates occur, what is the minimum error with which facilities can measure gas 

consumption over a test period (e.g., 8 hours, 24 hours)? Please consider methods that 

could be used to reduce error in these cases, such as measuring the temperature of the 

gas container to estimate consumption. 

Response: Summary: For those greenhouse gases which are stored indoors in climate 

controlled areas, temperature fluctuations are limited and are expected to have a minimal 

impact on gas usage measurement. For gases stored outdoors, temperature has an impact 

and should be monitored during the gas use determination period. 

Accuracy is dependent on the usage rate and the container size (see examples below). For 

low use gases, SIA proposes that gas usage rates for the purpose of determining emission 

factors be collected over a period that brackets, and is representative of the chemical usage 

during the stack test. In many situations, the appropriate period for collecting chemical 

usage data may be a 1 month period bracketing the period of the stack test or the average 

length of time required to consume one full cylinder, whichever is less. 

The process GHGs used by the semiconductor industry are comprised of a combination of 

liquefied and compressed gases that are stored both in and outside of the fab, depending
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largely upon the container size. Typical container capacities range from less than a cubic 

foot, to more than 40 cubic feet. 

Fabs select container sizes largely based on gas usage rate. The systems in place to monitor 

the usage rate at most Fabs are designed to assure that the Fab does not run out of a gas.

Therefore, in most cases, fabs monitor how full a container is rather than the flow rate from 

the container. Accordingly, the determination of usage rate typically involves a timed 

sequence of measurements of the container fullness. 

For liquefied gases, which include C2F6, C4F8, SF6, and N2O, among others; the majority of 

the material contained in the cylinder is in liquid form. The liquid volatizes in accordance with 

its temperature and pressure, and so its vapor pressure establishes the maximum potential 

line delivery pressure. Many, but not all liquefied gas cylinders used by Fabs are mounted on 

scales, which provide a means for directly measuring the rate of gas usage via a timed 

sequence of scale readings. The accuracy of the weight scale relative to the gas cylinder size, 

the resolution of the weight scale data acquisition system, if there is one, and the draw rate, 

all influence the accuracy with which the usage rate of liquefied gases can be determined. 

Examples of the accuracy of usage measurements are described below. 

For compressed, or pressurized, gases, which include CF4 and NF3; the usage rate is usually 

determined by monitoring the pressure within the gas cylinder over time. In some Fabs, a 

pressurized gas cylinder may be mounted on a scale, however, this is a relatively infrequent

practice. Determination of gas usage rates from pressure measurements requires the use of 

an equation of state to convert from the pressure within the gas cylinder to the mass of gas 

contained in the cylinder. For gas cylinders that experience temperature variation, 

particularly those located outdoors, the temperature can have a significant effect. The 

accuracy of gas usage rates that are determined from pressure readings is influenced by the 

accuracy of the pressure gauge/transducer; the range of temperature variation, and the 

accuracy of the temperature measurement; the resolution of the data acquisition system, if 

there is one; the accuracy of the equation of state, and the usage rate. The role of these 

factors in determining the accuracy of compressed gas usage rates is described below, with 

examples. 

Impact of Temperature and Pressure on Determining Gas Use

Figure 4-1 shows the pressure and temperature record for a particular NF3 cylinder, which is 

located outdoors. Over the duration of this record, the pressure drops from 1,019 psia to 

211 psia, and the temperature varies with diurnal cycles over a range between 40 and 80 

degrees F. It can be noted from the pressure and temperature curves that the pressure 

readings “flatten” out when the temperature increases. This is anticipated because the 

temperature increase expands the gas; which is contained within the fixed volume of the 

cylinder, and results in a pressure increase. 

The mass of NF3 contained within the cylinder, that corresponds to a given temperature (T)

and pressure (P), must be determined using an equation of state method. The blue triangles 

plotted on Figure 4-1 were calculating from the P & T data using the Redlich-Kwong-Soave

(RKS) method, which is one of several well known methods for calculating the properties of 

real gases. It can be seen that at the initial reading there are 712 lbs of NF3 in the cylinder, 

at the final reading there are 112 (lbs) of NF3 in the cylinder. As indicated on the chart, a 

linear regression of the mass of NF3 in the cylinder over time has a slope that corresponds to 

the 213.15 (lbs/day) average usage rate. 
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Figure 4-1. The Variation of Pressure, Temperature and Mass of NF3 Cylinder with Time

NF3 cyinder P, T, and mass in cylinder

NF3(lbs) = -213.15 (lbs/day) * days 

R

2

 = 0.9969

0

100

200

300

400

500

600

700

800

900

1,000

1,100

10/3/2011 12:00 10/4/2011 0:00 10/4/2011 12:00 10/5/2011 0:00 10/5/2011 12:00 10/6/2011 0:00 10/6/2011 12:00 10/7/2011 0:00 Pressure (psia) and mass in cyinder (lbs)

0

10

20

30

40

50

60

70

80

90 Temperature (deg F)

~P (psia) Lbs in cylinder RKS est T (F) Linear (Lbs in cylinder RKS )

Figure 4-2 shows a plot of NF3 density as a function of pressure, at 70 F, as computed using 

both the ideal gas law, and the RKS method. The compressibility factor, known as the Zfactor, is a factor that represents the deviation between real and ideal gas behavior. As 

shown on Figure 4-2, there is a significant difference between the real and ideal gas densities 

for NF3, and that the divergence is more significant at higher pressures. 

Figure 4-2. The Variation NF3 Density at 70 F with Pressure Using Real and Ideal Gas 

Properties. 

NF3 gas density and Z-factor at 70 F (RKS method)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

0 100 200 300 400 500 600 700 800 900 1,000 1,100 1,200 1,300 1,400

Cylinder Pressure (psi) gas density (lb/ft3)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0 Z-factor

d (lb/ft3) d_ideal (lb/ft3) Z
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Table 4-1 illustrates the above points in context of the NF3 usage rates measured during a 

recent stack test. The NF3 usage rate measured over the test period is 213.2 (lbs/day) when 

both the measured temperature and pressure are used to calculate the real gas properties. 

However, if the temperature were assumed to be a constant 70F, then the calculated usage 

rate would be 196 (lbs/day). If the usage rate had been calculated using the ideal gas 

equation, it would have been only 157 (lb/day). Clearly for the outdoor storage of NF3, it is 

important to use a real gas relation that accounts for both the temperature and the pressure 

of the gas. 

Table 4-1: NF3 usage rate computed under different assumptions.

(lb/hr) (lb/day) (kg/day) % Delta

RKS(P,T) : 8.8813 213.1512 96.68

RKS(P,T=70F) : 8.1813 196.3512 89.06 -7.88%

IDEAL(P,T) : 6.1123 146.6952 66.54 -31.18%

2011 avg: 214.18 97.15 0.48%

NF3 use w/wo T correction

It’s interesting to note that the long term average usage rate for NF3 at this Fab, as 

determined from the record of cylinder changes, differs by only 0.5 % from the short term 

usage rate as determined from P & T measurements during the stack test. The data from the 

NF3 cylinder change log (record of dates on which empty cylinders were replaced with full 

cylinders) for the entire year is plotted in Figure 4-3, and it can be noted that the usage rate 

is very constant, as reflected in the R

2

value of 0.997. Several points regarding the data in 

this table bear remark, particularly in light of the fact that the Fab has a joint mission of 

300mm wafer production, at several different technology nodes (90, 65, 45, 32 nm), as well 

as actively developing additional technology nodes:

The measured rate of gas use over the short term duration of the stack test and the

annual average rate produce virtually the same number, using two different and 

independent means of estimating gas usage.

The draw rate, which reflects the collective operation of nearly 200 process GHG

manufacturing tools, is remarkably constant despite the dynamic manufacturing and 

development mission

The ideal gas law provides significantly different values than an equation of state that

takes into account gas compressibility and temperature.
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Figure 4-3. Long term average NF3 usage as determined from the cylinder change log. 

NF3 tube trailers 2011

NF3 (lbs) = (214.18 (lbs/day) * days) - 3945.6

R

2

 = 0.9974

0

20,000

40,000

60,000

80,000

100,000

120,000

100 150 200 250 300 350 400 450 500

elapsed days NF3 (lbs)

Gas cylinders which are stored indoors typically experience much less temperature variation, 

and therefore the influence of temperature on gas usage estimates for pressurized gases is 

far less significant than for gases located outdoors. Temperature records for IBM’s 300mm 

subfab, for instance show that the temperature is generally within a few degree bandwidth. 

Figure 4-4 shows the error in assuming that a NF3 cylinder is 65 F, when it is actually 75 F. 

Figure 4-5 shows the error in assuming that a CF4 cylinder is 68 F, when it is actually 74.2 F. 

Based upon these data, we believe that temperature corrections are unnecessary for 

cylinders that are stored in doors and will undergo less than a 10 degree F temperature 

variation over the duration of the test. 

Figure 4-4. Maximum error for an NF3 cylinder that operates within a 10 degree F band. 

Mass in 15.82 (ft3) NF3 cylinder assuming 65 vs 75 F

0

100

200

300

400

500

600

700

0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200

cylinder pressure (psig) Lbs NF3 in cylinder

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

mass @ 65 F mass @ 75 F % delta
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Figure 4-5. Maximum error for a CF4 cylinder that operates within a 7.2 degree F band. 

Mass in a 14.49 ft3 CF4 cylinder as a function of P, assuming 68 vs 75.2 deg F

0

100

200

300

400

500

600

700

0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000

Pressure (psia) lbs CF4 in cylinder

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

mass at 68 F mass at 75.2 F % delta

Gas Use Measurement Error

The magnitude of measurement error, or uncertainty, in determining gas usage rates

depends on the gas draw rate relative to the cylinder size. This effect can be evaluated in 

term of the signal strength to noise level; where in general, a large draw rate from a small 

cylinder produces a large weight, or pressure, change over the duration of the measurement 

period; and thus helps provides a high signal to noise ratio.

Consider the measurement error associated with 3 different sized CF4 cylinders, each 

charged to 2,000 psia, and for which the limiting factor is that the pressure measurements 

are accurate to 1.0% of full scale range, or 20 psia. At 2,000 psia and 68 F, the CF4 

density is 44.73 (lb/ft3), and the 20 psia corresponds to 0.37 (lbs/ft3). That is: 

2,000 20 psia 44.74 0.37 (lbs/ft3)

The mass of gas contained in the cylinder is the product of the internal volume of the 

cylinder, and the gas density, as indicated in Table 4-2. Note that for the 3 example cylinders, 

the absolute magnitude of the mass measurement uncertainty increases within increasing 

cylinder size, but the relative error remains the same (0.83 %)

Table 4-2: Measurement error for 3 different size, 2,000 psia CF4 cylinders.

Gas

Cylinder 

Vol (ft3)

CF4 density 

at 2,000 psia, 

and 68 F 

(lb/ft3)

Mass of NF3 in 

cylinder at 2,000 

psig and 68F 

( lbs)

Pressure measurement 

error assuming it 

corresponds to 1% of full 

scale (psi)

CF4 density error 

corresponding to a +- 20 

psia uncertainty at 2,000 

psia (lb/ft3)

CF4 mass 

corresponding to a 20 

psia measurement 

error (lbs)

CF4 1.55 44.73 69.33 20 0.37 0.57

CF4 4.46 44.73 199.50 20 0.37 1.65

CF4 14.49 44.73 648.14 20 0.37 5.36

Next, using Table 4-3, the role of uncertainty in the pressure measurement can be considered 

relative to the cylinder size, draw rate, and measurement duration. Here we assume a draw 

rate of 1.2 (lbs/hr) from the three different sized cylinders, for measurement durations of 8 
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and 24 hours. For CF4 drawn at 1.2 (lb/hr) from a 1.55 ft3 cylinder for 8 hrs the relative 

uncertainty in the usage is 6 %, and if the measurement extends for 24 hours, the relative 

uncertainty drops to 2 %. As expected, measuring over a longer duration, and/or from a 

smaller cylinder size relative to the usage rate, reduces the magnitude of the uncertainty in 

the measurement. 

Table 4-3: Example CF4 measurement error.

GAS

Cylinder 

Vol (ft3)

Assumed 

use rate 

(lbs/hr)

 measurement 

error as mass 

(lbs)

Qty used in 8 

hrs (lbs)

Relative % uncertainty in 

the usage measurement 

conducted over 8 hrs

Qty used in 

24 hrs 

(lbs)

Relative % uncertainty in 

the usage measurement 

conducted over 24 hrs

CF4 1.55 1.2 0.57 9.6 5.98% 28.8 1.99%

CF4 4.46 1.2 1.65 9.6 17.19% 28.8 5.73%

CF4 14.49 1.2 5.36 9.6 55.86% 28.8 18.62%

As indicated in these charts, the gases which have the lowest usage rate relative to their 

cylinder size result in the greatest uncertainty in the usage determination. However, typically 

gases which have low usage rates come in small cylinders and also have correspondingly 

small emission rates, and contribute the least to the sites overall CO2e emissions. 

Key Points: 

1. Both liquefied and pressurized gases are used by fabs.

2. Weight scales typically used for measuring the quantity of gas in a cylinder, have 1 % 

of full scale accuracy as required by the rule. 

3. Pressure gauges/transducers used to determine the quantity of gas in a cylinder also 

come with an accuracy of 1 % of full scale as required by the rule.

4. The determination of the usage rates for pressurized gas cylinders that are located 

outdoors should be based upon both pressure and temperature measurements; with the 

quantity of gas in the cylinder at a given time determined on the basis of an equation of 

state relation that accounts for real gas properties. 

5. The determination of the usage rates for pressurized gas cylinders that are located 

within indoor areas where room temperature varies by less than 10 degrees F allows for 

the use of an average temperature for the area where the cylinders are stored. 

Monitoring of temperature during the test is not required. 

6. Gases which have the lowest usage rate relative to their cylinder size result in the 

greatest uncertainty in the usage determination. However, typically gases which have 

low usage rates usually come in small cylinders and also have correspondingly small 

emission rates, and contribute the least to the sites overall CO2e emissions

7. Based upon the data we reviewed, gas usage rates are typically quite uniform, and short 

term gas usage measurements have been shown to mirror long term gas usage rates as 

determined from cylinder change records. We propose that gas usage rates for the 

purpose of determining emission factors be collected over a period that brackets, and is 

representative of the chemical usage during the stack test. In many situations, the 

appropriate period for collecting chemical usage data may be a 1 month period 

bracketing the period of the stack test or the average length of time required to consume 

one full cylinder, whichever is less.

Detection limits (particularly N2O): The response to this question will help EPA determine if 

the stack testing method can be used to establish an emission factor for N2O.
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5. Based on the presentations, the detection limits for N2O appear to be consistently higher 

than those for the fluorinated GHGs, and the difference is large enough that CO2-

equivalent emissions of N2O at the detection limit are a factor of 10 or more higher than 

those of the fluorinated GHGs at their detection limits. If N2O emissions were lower, 

could the N2O detection limit be lowered to ensure that the N2O emissions were still 

detectable? 

Response: N2O is a strong infrared absorber and lends itself to detection via FTIR. Yes, 

lower detection limits can be achieved; however, lower detection limits for N2O are not 

typically required because emissions are typically high and the higher detection limit is 

consistent with the measured stack concentrations per the EPA method. Ambient 

atmospheric concentration levels of N2O are on the order of~300ppb1and detection limits 

below ambient are not meaningful. In fact, we should be adjusting any N2O measurements 

to back out the ambient air contribution. 

Could this be done without increasing the detection limits of the fluorinated GHGs? 

Response: Yes. The detection limits can be reduced without increasing the detection limits 

for the F-gases but this will have added cost and testing burden. Under normal 

circumstances, some trade-off will occur. Importantly, with ambient concentrations ~ 

300ppb, we do not see a practical need for a lower detection limit for N2O; it will be 

counterproductive in our testing and it will add to the sizeable costs we are already facing.

 

1

The Chemistry and Physics of the Atmosphere: From Air Pollution to Climate Change by John 

Seinfeld and Spyros Pandis, p. 22. (1998)