Page 1 of 10 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 fab s, 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 method s ; testing and collected data does not allow for development of fab

- wide emission factors.

2. The NF 3 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 NF 3 consumption and the NF 3 emission rate were lower in August. We think
that Tables 3

- 9 and 2

- 1

- 1 may have inadve rtently 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 Aug ust fou nd 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 Au gust em i ssions 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 D a ta from Tables 2

- 1

- 1 and 3

- 9 Showing the Corrected Values

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.Page 2 of 10

3. Slid e 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. D etermine 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 determi ned 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 me thods 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 facto r 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 pre

abated EF under this approach sho uld 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. Estimat e 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 t he value

t pd : the total time, in minutes, that the abatement system is not operational for the reporting year f

or each abatement system.

Add the values for all systems together and divide by 60 to determine the total number of abatement downtime hours ex perienced.

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 emissio ns = 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.Page 3 of 10

Example calculation

Annual CF4 use = 5

, 000 k g
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

U nabated annual CF4 emissions rate = 5

, 000 k g *0.8 = 4

, 000 k g
Average hourly unabated CF4 emissions = 4000/8760 = 0.46 k g /hr

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

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

Total incremental emissions f rom downtime = 0. 0 44 k g /hr x 200 hrs. = 8.8 k g

CF4 GWP = 6500

Total incremental downtime emissions = 8.8 k g x 6500/ 1 000 = 57.2 metric tons CO2e

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

Measuring gas consumption dur ing 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 t hat 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 tempe rature 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 m easuring 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 g as usage measurement. For gases stored outdoors, temperature has an impact

a nd should be monitored during the gas use determination period.

Accuracy is dependent on th e usage rate and the container size (see examples below) . For low use gases, SIA prop oses 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, dependingPage 4 of 10

largely upon the container size. Typical container capacities range from less than a cubic foot, to more than 40 cubic feet.

Fabs select contai ner sizes largely based on gas u sage 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; t he majority of
the material contained in the cylinder is in liquid f orm. The liquid volatizes in accordance with

its temperature and pressure , and so its vapor pressure establishes the maximum potential line delivery pressure. M any, but not all liquefied gas cylinders used by Fabs are mounted on scales, which provide a mea ns for direct ly 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 i nclude CF4 and NF3; t he usage rate is usually
determin ed by monitoring the pressure within the gas cylinder over time. In some Fabs, a pressurized gas cylinder may be mounted on a sc ale, however, this is a relatively inf requent

pra ctice. D e termination of gas usage rates from pressure measurements requires the use of an equation of state to convert from the pressure with in the ga s cylinder to the mass of gas
contained in the cylinder. For gas cylinders that experience temperature variation, particularly those located outdoors, the tem perature can have a signif icant e ffect

. 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, i f there is one; the ac curacy of the equation of state, and the usage rate. The role of t h ese factors in determining the accuracy of compressed gas usage rates is described below, with examples.

Impact of Temperature and Press ure on Determining Gas Use

Figure 4

- 1 shows the pressure and temperature record for a particular NF 3 cylinder

, which is
located outdoors. O ver the duration of th is record , the pressure drops from 1,019 psia to 211 psia, and the temperature varies with diu rnal cycles over a range between 40 and 80
de grees 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; wh ich is contained within the fixed volume of the cylinder, and results in a pressure increase.

The mass of NF

3 contained within the cylinder, that corresponds to a given temperature (T) and pressure (P)

, must be determined using an equation of state method

. The blu e 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) aver age usage rate.Page 5 of 10

Figure 4

- 1

. The Variation of Pressure, Temperature and Mass of NF3 Cylinder with Time

Figure 4

- 2 sho ws a plot of NF3 density as a function o f pressure, at 70 F, as computed using both the ideal gas law, and the RKS method. The compress ibility factor, known as the Z

factor, 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 mor e significant at higher pressures.

Figure 4

- 2

. The Variation NF3 D ensity at 70 F with Pressure U sing R eal and I deal G as
P roperties.Page 6 of 10

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, i

f the temperature were assumed to be a constant 70F, then the calculated usage
rate would b e 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 pre ssure of the gas.

Table 4

- 1 : NF3 usage rate computed under different assumptions

.

It’s interesting to note that the long term average usage rate for NF 3 at this Fab, as determined from the record of cylinder cha nges, differs by only 0.5 % from the sho rt term usage rate as determined from P & T measurements during the stack test. The data from the

NF 3 cylinder change log (record of dates on which empty cylinders were replaced with full cylinders) for the enti re 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 missi on of 300mm wafer production, at several diff erent technology nodes (90, 65, 45, 32 nm), as well

as actively devel oping 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 dif ferent 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

.Page 7 of 10

Figure 4

- 3 . Long term average NF 3 usage as determined from the cylinder change log

.

Gas cylinders which are stored indoors typ ically 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 i s 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 e rror for an NF 3 cy linder that operates within a 10 degree F band.Page 8 of 10

Figure 4

- 5

. Maximum e rror for a CF 4 cylinder that operates within a 7 .2 degree F band.

Gas Use Measurement Error

T he magnitude of measurement error , or uncertainty, in determining gas usage rates depe nds on the gas draw rat e relative to the cylind er 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

, cha nge over the duration of the measurement period ; and thus helps provide s a high signal to noise ratio.

Consider the measurement err or associated with 3 d ifferent sized CF4 cylinders , each charged to 2,000 psia, and for which the limiting factor is that the pressure measurements

a re 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 cy linder is the product of the internal volume of the cylinder, and the gas d ensity, 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 t he relative error remains the same (0.83 %)

Table 4

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

.

Next, using Table 4

- 3, the role of uncertainty in the pressure measurement can be considered relative to the cylinder size, draw rat e, and measureme nt duration

. Here we assume a draw rate of 1.2 (lbs/hr) from the three different sized cylinders, for measurement durations of 8Page 9 of 10

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.

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 w hich 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 typicall y used for measur ing 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 requir ed 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 a n average temperature for the area where the cylinders are stored. Monitoring of temperature during the test is not required.

6. G ases which have the lowest usage rate relative to their cylinder size result in the greatest uncertainty in the usage determin ation. However, typically gases which have low usage rates usu ally 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
determin ed from cylinder change records. W e propose that gas usage rates for the purpose of determining emission factors be collected ov er a period that brackets, and is representative of the chemical usage during the stack test. In many situations, the appropriate period for col lecting chemical usage data may be a 1 month period bracketing the p eriod of the stack test or the average leng th 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.Page 10 of 10

5. Based on the p resentations, 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, l ower 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 meth od. Ambient atmospheric concentration levels of N2O are on the order of ~300ppb 1 and detection limits
belo w ambient are not meaningful . In fact, we should be adjusting any N2O measure ments to back out the ambient air contribution

.

Co uld this be do ne 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)