# TECHNICAL SUPPORT DOCUMENT FOR PROCESS
EMISSIONS FROM ELECTRONICS MANUFACTURE (e.g., MICRO-ELECTRO-MECHANICAL SYSTEMS, LIQUID CRYSTAL DISPLAYS, PHOTOVOLTAICS, AND SEMICONDUCTORS ):

PROPOSED RULE FOR MANDATORY REPORTING
OF GREENHOUSE GASES

REVISED – NOVEMEBER 2010

Office of Air and Radiation
U.S. Environmental Protection AgencySubpart I Technical Support Document



### DISCLAIMER

The Environmental Protection Agency (EPA) regulations cited in this technical support document (TSD) contain legallybinding requirements.

In several chapters this TSD offers illustrative examples fo r complying with the minimum requirements indicated by the regulations. This is done to provide information that may be helpful for reporters’ implementation efforts. Such recommendations are prefaced by the word s “may” or “should” and are to be considered advisory. They are not required elements of the regulations cited in this TSD. Therefore, this document does not substitute for the regulations cited in this TSD, nor is it a regulation itself, so it does not impose lega lly-binding requirements on EPA or the regulated community. It may not apply to a particular situation based upon the circumstances. Mention of trade names or commercial products does
not constitute endorsement or recommendation for use.

While EPA has made every effort to ensure the accuracy of the discussi on in this docume nt, the obligations of the regulated community are determined by statutes, regulations or other legally binding requirements. In the event of a conflict between the discussion in this document and any statute or regulation, this document would not be controlling.Subpart I Technical Support Document



### TABLE OF CONTENTS

1 SOURCE DESCRIPTION 1

1.1 T OTAL 

### U.S. E MISSIONS



### ............................................................................................................................... . 2
1.2 GHG S TO BE 

### R EPORTED 

### .............................................................................................................................. 2



### 2 OPTIONS FOR AND SELECTION OF REPORTING THRESHOLD 3

2.1 O PTIONS 

### C ONSIDERED FOR 

### R EPORTING 

### T HRESHOLDS 

### ............................................................................ 3
2.2 E MISSIONS 

### -B ASED 

### T HRESHOLD 

### C ALCULATIONS 

### ...................................................................................... 4
2.3 R EPORTER 

### T HRESHOLD 

### A PPLICABILITY 

### D ETERMINATIONS 

### .................................................................... 5



### 3 OPTIONS FOR EMISSIONS CALCUL ATION AND MONITORING METHODS 7

3.1 O PTIONS FOR 

### E STIMATING 

### F LUORINATED 

### GHG E MISSIONS FROM 

### E TCHING AND 

### C LEANING 

### ............. 7
3.1.1 2006 IPCC T IER 

### 1 M ETHOD 

### ........................................................................................................................ 8
3.1.2 2006 IPCC T IER 

### 2 A 

### M ETHOD 

### ...................................................................................................................... 9
3.1.3 2006 IPCC T IER 

### 2 B 

### M ETHOD 

### ...................................................................................................................... 9
3.1.4 M ODIFIED 

### T IER 

### 2 B 

### M ETHOD 

### ..................................................................................................................... 10
3.1.5 T IER 

### 2 C 

### M ETHOD 

### (D EFAULTS FOR 

### 5 P ROCESS 

### T YPES 

### /S UBTYPES 

### ) ........................................................... 10
3.1.6 T HE 

### R EFINED 

### M ETHOD 

### (D EFAULTS 

### F ACTORS FOR 

### 9 P ROCESS 

### T YPES 

### /S UBTYPES 

### ) .................................. 10
3.1.7 T IER 

### 2 D 

### M ETHOD 

### (D EFAULTS FOR 

### 4 P ROCESS 

### T YPES 

### /S UBTYPES


### , R ECIPE



### - SPECIFIC EMISSION FACTORS

FOR 

### 1 P ROCESS 

### T YPE 

### ) .............................................................................................................................. . 11
3.1.8 2006 IPCC T IER 

### 3 M ETHOD 

### ...................................................................................................................... 12
3.1.9 H YBRID 

### A PPROACH 

### A.............................................................................................................................. . 13
3.1.10 H YBRID 

### A PPROACH 

### B ............................................................................................................................. 1 3
3.1.11 C ONTINUOUS 

### E MISSIONS 

### M ONITORING 

### S YSTEMS 

### (CEMS).................................................................... 13
3.2 O PTIONS FOR 

### E STIMATING 

### F ACILITY 

### G AS 

### C ONSUMPTION 

### .................................................................... 13
3.2.1 IPCC D EFAULT 

### H EEL 

### F ACTOR 

### .................................................................................................................. 14
3.2.2 G AS



### - AND 

### F ACILITY 

### -S PECIFIC 

### H EEL 

### F ACTORS 

### .......................................................................................... 14
3.3 O PTION FOR 

### A PPORTIONING 

### G AS 

### C ONSUMPTION 

### ................................................................................... 15
3.3.1 E XAMPLE OF 

### F ACILITY 

### -S PECIFIC 

### E NGINEERING 

### M ODEL 

### B ASED ON 

### W AFER 

### P ASS 

### .................................. 16
3.4 O PTIONS FOR 

### E STIMATING 

### N ITROUS 

### O XIDE 

### (N 2 

### O) E MISSIONS 

### ............................................................. 17
3.5 O PTIONS FOR 

### E STIMATING 

### H EAT 

### T RANSFER 

### F LUIDS 

### (HTF S 

### ) E MISSIONS 

### ............................................ 18
3.5.1 IPCC T IER 

### 1 A PPROACH 

### ........................................................................................................................... 18
3.5.2 IPCC T IER 

### 2 A PPROACH 

### ........................................................................................................................... 18
3.6 O PTIONS FOR 

### R EPORTING 

### C ONTROLLED 

### E MISSIONS FROM 

### A BATEMENT 

### S YSTEMS 

### ............................ 19
3.6.1 P ROPER 

### I NSTALLATION


### , O PERATION


### , AND 

### M AINTENANCE 

### ...................................................................... 19
3.6.2 M ONITORING 

### A BATEMENT 

### S YSTEM 

### U PTIME 

### ............................................................................................ 19
3.6.3 EPA D EFAULT 

### DRE V ALUE 

### ..................................................................................................................... 20
3.6.4 P ROPER 

### M EASUREMENT OF 

### A BATEMENT 

### S YSTEM 

### DRE .......................................................................... 22



### 4 QA/QC REQUIREMENTS 22Subpart I Technical Support Document



### 5 PROCEDURES FOR ESTIMATING MISSING DATA 23

6 REPORTING AND RECORDKEEPING PROCEDURES 23

7 REFERENCES 27

APPENDIX A - DEFAULT EMISSION FACTORS FOR THRESHOLD APPLICABILITY
DETERMINATION AND ETCH AND CLEAN EMISSION ESTIMATION METHODS 29

APPENDIX B - DEVELOPMENT OF EPA PUBLISHED EMISSION FACTORS FOR THE
TIER 2C AND TIER 2D METHODS 34

APPENDIX C – EVALUATION OF UNCERTAI NTY ASSOCIATED WITH ALTERNATIVE
EMISSION ESTIMATION METHODS 39

APPENDIX D - SUPPORT FOR EPA’S DEFINITION OF SIMILAR RECIPE 45Subpart I Technical Support Document



### TABLE OF FIGURES

FIGURE 3-1. TYPOLOGY FOR CALCULATING FLUORINATED GHG EMISSIONS FROM ELECTRONICS
MANUFACTURING.................................................................................................................. ..................................... 8
FIGURE 3-2. EXPECTED SEMICONDUCTOR FACILI TY CONTRIBUTIONS TO TOTAL EMISSIONS ..................... 8 FIGURE B-1. DATA FORM SUBMITTED BY SEMICONDUCTOR DEVICE MANUFACTURERS AND EQUIPMENT
MANUFACTURER S TO SEMI.......................................................................................................... .......................... 37 FIGURE D-1. RIE ETCHING SHOWING (A) SPUTTERING, (B) CHEMICAL ETCHING AND (C) SPUTTERING
AND CHEMICAL ETCHING........................................................................................................... ............................ 46
FIGURE D-2. ILLUSTRATION OF HYSICAL AND CH ECMIAL PROCESSES AND INTERATCTION DURING CF4
PLASMA ETCHING OF SIN X FILM .......................................................................................................................... . 48
FIGURE D-3. C 2 F 6 EMISSIONS VS C 2 F 6 INLET FLOW RATE & PRESSURE AT 1:1 OXYGEN: C 2 F 6 RATIO........... 51



### TABLE OF TABLES

TABLE 1-1. SELECTED FLUORINATED GREENHOUSE GASES USED BY THE ELECTRONICS INDUSTRY ....... 1
TABLE 2-1. EMISSIONS- BASED THRESHOLD FOR ELECTR ONICS MANUFACTURE (1,000, 10,000, 25,000 AND 100,000 MT CO 2 E) ............................................................................................................................. ............................. 3
TABLE 2-2. RULE APPLICABILITY UNDER THE PROPOSED EMISSIONS-BASED THRESHOLDS....................... 4
TABLE 3-1. ILLUSTRATIVE CALCULATION FOR NF 3 EXAMPLE AT ONE FACILITY........................................... 17
TABLE 3-2. ILLUSTRATIVE VERIFICATION FOR HYPO THETICAL FACILITY-SPECI FIC GAS APPORTIONING
MODEL.......................................................................................................................... ................................................ 17
TABLE 3-3. DATA SET TO DE VELOP EPA DEFAULT DRE VALUE ........................................................................... 21 TABLE 3-4. SUMMARY STATISTICS AND DEFAULT DRE (LOWER ONE-SIDED TOLERANCE INTERVAL) .... 22
TABLE A-1. DEFAULT EMISSION FACTORS FO R THRESHOLD APPLICABILITY DETERMINATION

. .............. 29 TABLE A-2. DEFAULT EMISSION FACTORS (1-U IJ ) FOR GAS UTILIZATION (U IJ ) AND BY-PRODUCT FORMATION RATES (B IJK ) FOR MEMS, LCD, AND PV MANUFACTURING..................................................... 30 TABLE A-3. DEFAULT EMISSION FACTORS (1-UIJ) FOR GAS UTILIZATION (UIJ) AND BY-PRODUCT FORMATION RATES (BIJK) FOR SEMICONDUCTOR MANUFACTURING FOR 150 MM AND 200 MM
WAFER SIZES .................................................................................................................... .......................................... 31 TABLE A-4. DEFAULT EMISSION FACTORS (1-UIJ) FOR GAS UTILIZATION S (UIJ) AND BY-PRODUCT FORMATION RATES (BIJK) FOR SEMICONDUCTOR MANUFACTURING FOR 300 MM WAFER SIZE ..... 32
TABLE C-1. ANALOGIES MADE FOR EFS AND ERS FOR VARIOUS FLUORINATED GHGS FOR THE
ALTERNATIVE
METHODOLOGIES...................................................................................................................40 TABLE C-2. COMPARISON OF NOMINAL AND SIMULATED MEAN EMISSIONS (MMTCE) AND NORMALIZED
ESTIMATES OF PEE FOR FIVE ALTERNATICE EM ISSION ESTIMATION METHODS............................42
TABLE D-1 CHANGES IN NF 3 EMISSIONS (KGCE) AND UTILIZATION FOR VARIOUS INDICATED CHANGES
IN PARAMETERS FOR IN-SITU CH AMBER-CLEANING PROCESS.................................................................... 52
TABLE D-2. AFFECT OF ±10 PERCENT CHANGES IN O 2 AND N 2 O FLOW RATES ON C 3 F 8 UTILIZATION AND
CF 4 BY-PRODUCT FORMATION DURING NITRIDE AND OXIDE IN SITU PLAMSA CHAMBER CLEANING

............................................................................................................................... ......................................................... 52Subpart I Technical Support Document

November 2010 1 

### 1 Source Description

The electronics industry uses multiple lo ng-lived fluorinated greenhouse gases (fluorinated GHGs), as well as nitrous oxide (N 2 O) during manufacturing of electronic devices, including, but not limited to, liquid crystal displays (LCDs), microelectro-mechanical systems (MEM S), photovoltaic cells (PV), and semiconductors (including light-emitting diodes (LEDs) 1 ). Fluorinated GHGs are used mainly for plasma etching of silicon materials, cleaning deposition tool chambers, and wafer cleaning, but may be used in other types of electroni cs manufacturing processes. Besides dielectric film etching and chamber cleaning, much smaller quantities of fluorinated GHGs are used to etch polysilicon films and refractory metal films like tungsten. Additionally, some electronics manufacturing equipment may employ fluorinated GHG liquids as heat transfer fluids (HTFs). The most common fluorinated GHGs in use are trifluoromethane (HFC-23 or CHF 3 ), perfluoromethane (CF 4 ), perfluoroethane (C 2 F 6 ), nitrogen trifluoride (NF 3 ), and sulfur hexafluoride (SF 6 ), although other compounds such as perfluoropropane (C 3 F 8 ) and perfluorocyclobutane (c-C 4 F 8 ) are also used (EPA, 2008a). Table 1-1 presents examples of fluorinated GHGs known to be used during manufacture of different types of electronics. N 2 O, another GHG used in the manufacture of electronics, is used in depositing certain films and other manufacturing processes.

Table 1-1. Selected Fluorinated Greenhouse Gases Used by the Electronics Industry Product Type Fluorinated GHGs Used During Manufacture
Semiconductor CF 4 , C 2 F 6 , C 3 F 8 , c-C 4 F 8 , c-C 4 F 8 O, C 4 F 6 , C 5 F 8 , CHF 3 , CH 2 F 2 , NF 3 , SF 6 , and HTFs. a

MEMS b CF 4 , c-C 4 F 8 , and SF 6 LCD CF 4 , CHF 3 , c-C 4 F 8 , NF 3 , and SF 6 PV CF 4 , C 2 F 6 , CHF 3 , C 3 F 8 , NF 3 , SF 6

a For commonly used heat transfer fluids pl ease refer to the U.S. EPA report entitled “Uses and Emissions of Liquid PFC Heat Tran sfer Fluids” available at: http://www.epa.gov/semiconductor-pfc/doc uments/pfc_heat_tranfer_fluid_emission.pdf.

b IPCC guidelines do not specify the fluorinated GHGs used by the ME MS industry. Literature reviews revealed that among others, CF 4 , SF 6 , and the Bosch process (e.g., Bosch process c onsists of alternating steps of SF 6 and C 4 F 8 ) are used to manufacture MEMS. Source: IPCC, 2006; Lyshevshi, S., 2001; Gaitan, M. & Takacs, M., 2008.

The electronics manufacture source category consists of the five production processes described below.

• The etching process uses plasma-gener ated fluorine atoms and other reactiv e fluorine-containing fragments, which chemically react with exposed thin-films (e.g., dielectric, metals) or substrate (e.g., silicon), to selectively remove the desired portions of the material. The material removed, as well as undissociated fluorinated gases, flow into waste streams and, unless abatement system s are employed, into the atmosphere.

• Chambers used for depositing dielectric films are cleaned periodically using plasma-generated fluorine atoms and
other reactive fluorine-con taining fragments and other gases, such as N 2 O. During the cleaning cycle the gas is converted to fluorine atoms in plasma, which etches away residual material from ch amber walls, electrodes, and chamber hardware. Undissociated fluorinated gases and other products pass from the chamber to waste streams and, unless abatement systems are employed, are emitted into the atmosphere.

• During wafer processing, any residual photoresist material can be removed through an ashing process, which consists of placing partially processed wafers in an oxygen plasma to which CF 4 may be added. The edges of wafers (the bevel) may also require cleaning to remove yield-reducing residual material. Bevel cleaning may also use a plasma process with fluorinated GHG chemistry. In both of these wafer cl eaning processes, unused
fluorinated GHGs are emitted unless abated.

• Deposition is a fundamental step in the fabrication of a variety of electronic devices. During deposition, layers of dielectric, barrier, or el ectrically conductive films are deposited or gr own on a wafer or other substrate. Chemical vapor deposition (CVD) enables the deposition of dielectric or metal films. During the CVD process, gases that contain atoms of the material to be deposited react on the wa fer surface to form a thin film of solid material. Films deposited by CVD may be silicon oxide, single-layer crys tal epitaxial silicon, amorphous silicon, silicon nitride,

1 LEDs are a semiconductor light source. When a LED is switched on electrons are able to recombine with hol es within the device

, releasing energy in the form of light whos e color is governed by the nature of the semiconductor. Many LEDs are manufactured o n a wafer (usually different than silicon) using methods that are similar to the manufacture of integrated circuits.Subpart I Technical Support Document

November 2010 2 dielectric anti-reflective coatings, low-k dielectric, alum inum, titanium, titanium nitride, polysilicon, tungsten, refractory metals or silicides. N 2 O may be the oxidizer of choice during deposition of silicon oxide films.

• Additionally, fluorinated GHG liquids are frequently used as HTFs at semiconductor facilities to cool process equipment, to control temperature du ring device testing, to clean substr ate surfaces and other parts, and for soldering, and their high vapor pressures can lead to evaporative losses during use (EPA, 2008b; IPCC, 2006). Other electronics manufacturing facilities may also employ HTFs for similar uses. HTFs commonly used in electronics manufacturing include those sold unde r the trade names “Galden®” and “FluorinertTM.”



### 1.1 Total U.S. Emissions

Emissions of fluorinated GH Gs from 216 electronics manufacturing facilities were estimated to be 6.0 Tg CO 2 e in 2006. Below is a breakdown of emissions by electronics product type.

• Semiconductor : Emissions of fluorinated GHGs, including emi ssions from the use of HTFs, from 175 facilities were estimated to be 5.74 Tg CO 2 e in 2006 (EPA, 2008a; Burton, C.S., & Beizaie, R., 2001; ITRS, 2008; SEMI, 2008; VLSI Research, Inc., 2008). 2 Of the total semiconductor emissions 5.19 Tg CO 2 e are from etching/chamber cleaning at full-scale facilities and 0.55 Tg CO 2 e are from HTF usage from all facilities. 3 Only etching/cleaning
emissions from full-scale facil ities are accounted for in the U.S. Inventory of GHG Emissions and Sinks (EPA, 2008a). Partners of the PFC Reduction/Climate Partnership for Semiconductors comprise approximately 80 percent of U.S. semiconductor production capacity. Thes e Partners have committed to reduce their emissions (exclusive of HTF emissions) to 10 percent below their 1995 levels by 2010, and their emissions have been on a general decline toward attainment of this goal since 1999.

• MEMS : Emissions of fluorinated GHGs from 12 facilities were estimated to be 0.15 Tg CO 2 e in 2006 (SEMI,

2008. 4

• LCD: Emissions of fluorinated GHGs from 9 facilities were estimated to be 0.02 Tg CO 2 e in 2006 (DisplaySearch, 2007). 5

• PV : Emissions of fluorinated GHGs from 20 PV facilities were estimated to be 0.07 Tg CO 2 e in 2006 (Burton, 2006; Roedern, B.V. & Ullal, H.S. , 2008; Earth Policy Institute, 2007). 6



### 1.2 GHGs to be Reported

EPA is requiring the electronics industry to report emissions and consumption from the following processes and activities:

• Fluorinated GHGs emitted from plasma etching.

• Fluorinated GHGs emitted from chamber cleaning.

• Fluorinated GHGs emitted from wafer cleaning.

• N 2 O emitted from chemical vapor deposition or ot her electronics manufacturing processes.

• Fluorinated GHGs emitted from use of HTFs.

2 Total semiconductor facilities include both full-scale, pilot, and R&D facilities.

3 All full scale facilities are assumed to have the same utilization.

4 The estimated total number of MEMS faciliti es in the U.S. is an underestimate. Th e estimate was based on the World Fab Watch database, which provides an incomplete listing of total U.S. MEMS facilities (SEMI, 2007).

5 Estimated total LCD facilities include LC OS, a-Si TFT-LCDs, OLEDs (assuming active matrix), HTPS, TFT, Single Crystal AMLCD, LTPS facilities. Where, TFT = Thin Film Transistor; LCOS = Liquid Crystal on Silic on; a-Si = amorphous silicon; OLED = Organic Light Emitting Diode; HTPS = High Temperature Polysilicon; and AMLCD = Active Matrix Liquid Crystal Display.

6 Estimated total PV facilities includes only silicon based PV facilities (both crystalline and amorphous silicon based PV facil ities are included).Subpart I Technical Support Document

November 2010 3 • Consumption of all fluorinated GHGs and N 2 O, including gases used for manufacturing processes other than those
listed above.

• CO 2 , CH 4 , and N 2 O combustion emissions from stationary combustion units by following the requirements of 40 CFR part 98, subpart C (General St ationary Fuel Combustion Sources). 7



### 2 Options for and Selection of Reporting Threshold

2.1 Options Considered for Reporting Thresholds

EPA evaluated a range of emissions threshold options for electronics manufacturing facilities. 8 This range included emissions thresholds of 1,000, 10,000, 25,000, and 100,000 metric tons CO 2 e per year for each type of electronics device manufacturing facility. Table 2-1 shows these emissions-based threshold options and the number of electronics manufacturing facilities that are expected to be captured by the respective emissions thresholds. EPA selected 25,000
metric tons CO 2 e per year threshold, which covers 44 percent of el ectronics manufacturing facilities and 94 percent of the industry’s national emissions, thereby maximizing emissions reporting while excluding small facilities that do not contribute significantly to the overall GHG emissions.

Table 2-1. Emissions-Based Threshold for Electronics Manufacture (1,000, 10,000, 25,000 and 100,000 Mt CO 2 e)

Emissions Covered Facilities Covered

Emission Threshold
Level

(Metric tons CO 2 e/yr) Total
National
Emissions

(MtCO 2 e) Total National
Facilities Metric tons
CO 2 e/yr Percent Facilities Percent

1,000 5,984,463 216 5,962,091 99.6% 165 76%

10,000 5,984,463 216 5,813,200 97% 114 53%

25,000 5,984,463 216 5,622,570 94% 94 44%

100,000 5,984,463 216 4,737,622 79% 55 26%

Table 2-2 shows the estimated emissions th at would be covered and number of faciliti es that would report for each type of electronics manufacturing facility; semiconductors, ME MS, LCD, and PV, under the 25,000 metric tons CO 2 e emissionsbased threshold. The emissions-based threshold is estimat ed to include approximately 50 percent of facilities that manufacture semiconductors and approximately 17 percent an d 5 percent of the facilities manufacturing MEMS and PV, respectively. At the same time, the threshold is expected to cover 96 percent of fluorinated GHG emissions from facilities that manufacture semiconductors, 66 percent of fluorinate d GHG emissions from facilities manufacturing MEMS, and 47 percent of fluorinated GHG emissions from facilities manufacturing PVs.

7 On-site combustion emissions from electronics manufacturing faci lities are not addressed within this document; please see the Technical Support Document for Sta tionary Combustion (EPA-HQ-OAR-2008-050 8-046) for more information.

8 For more details on the subpart I threshol d analysis, please see the Subpart I Detail ed Threshold Analysis available in the do cket, EPAHQ-OAR-2009-0927.Subpart I Technical Support Document

November 2010 4 Facilities that manufacture LCDs are not expected to meet the 25,000 Mt CO 2 e threshold; however, the information available and used in the analysis at this time is limited and incomplete. Facilities that manufacture LCDs are nonetheless covered by the rule because they use similar fluorinated GHG and N 2 O manufacturing processes as semiconductor manufacturing, and because emissions are expected to increase due to high gr owth in the LCD manufacturing.

As part of this analysis, EPA also evaluated facilities that ma nufacture LEDs in the US. There are only a few facilities that manufacture LEDs in the US; however, the data that was used at this time is dated, limited, and incomplete. With a strong demand for energy efficient lighting, LED manufacturing is poised for high growth in the coming years. According to recent industry trade association report s, LED manufacturing is expected to gr ow significantly. “LED and solid state lighting (SSL) are two markets in the spotlight that attract a lo t of attention and new investments. Driven mostly by the surge of LED-backlight demand for LCD TV panels and the huge potential market in general lighting, demand for LED is set to explode in the coming years. In view of supply ti ghtness and market potential, new facility and capacity addition plans have suddenly emerged all over the world in the past year.” (Tsang, Clark, 2010). Therefore production processes
used to manufacture LEDs are covered under the electroni cs manufacturing source category as one specific type of
semiconductor device.

Table 2-2. Rule Applicability under th e Proposed Emissions-Based Thresholds

Emissions Covered Facilities Covered

Emissions
Source Threshold Total
National
Facilities Total
Emissions of Source (metric
tons CO 2 e) metric tons
CO 2 e/yr Percent Facilities Percent

Semiconductors 25,000 Mt CO 2 e. 175 5,741,676 5,492,066 96% 91 52%

MEMS 25,000 Mt CO 2 e 12 146,115 96,164 66% 2 17%

LCD 25,000 Mt CO 2 e 9 23,632 0 0% 0 0%

PV 25,000 Mt CO 2 e. 20 73,039 34,340 47% 1 5%



### 2.2 Emissions-Based Threshold Calculations

Emissions-based threshold estimations for each electronics manufacturing sector were derived in the following ways:

Semiconductors emissions-based threshold estimations were derived using outputs from the EPA PFC Emissions Vintaging Model (PEVM), as well as EPA PFC Reduction/Climate Partners hip for Semiconductors partner and non-partner shares of U.S. emissions. Additionally, the semiconductor emissions th reshold estimations determined accounted for heat transfer fluid emissions by assuming that these emissions were equivalent to 11 percent of total clean and etch emissions at a facility.

MEMS emissions-based threshold estimations were derived using an emission factor developed by EPA. EPA estimated an emission factor because no IPCC Tier 1 default emission factor exists. Assuming that MEMS are manufactured using the Bosch etching process, the utilization of SF 6 in the production of MEMS was assumed to be the same as the utilization of

SF 6 in the etching of semiconductors due to the simi larity between both of the manufacturing processes. 9 However, because SF 6 is used in only about 20 percent of semiconductor processes, the majority of which are etching processes, and

9 Although the Bosch etching process uses both SF 6 and C 4 F 8 , C 4 F 8 was not included because it has a high utilization rate (i.e., a high
fraction of C 4 F 8 is dissociated during the etching or cleaning process).Subpart I Technical Support Document

November 2010 5 it is assumed in this analysis that SF 6 is used in all MEMS processes, the 2006 IPCC Tier 1 SF 6 semiconductor emission factor (per area of substrate) was multiplied by five to estimate the MEMS emission factor per area of substrate. Additionally, the MEMS emission factor was scaled up by an additional factor of 1. 2 to account for increased SF 6 usage in MEMS manufacturing as compared to semiconductor manufacturing .

LCD and PV emissions-based threshold estimations were derived using 2006 IPCC Tier 1 emission factors.

Emissions reductions from the use of abatement systems were not accounted for in the any of the threshold analyses.



### 2.3 Reporter Threshold Applicability Determinations

Presented below are the methods reporters are required to use to determine whether thei r electronics manufacturing facility(ies) meets or exceeds the threshold of 25,000 metric tons CO 2 e.

Facilities that Manufacture Semiconductor and LCD: To determine whether a facility that manufactures semiconductors (including LEDs) or LCDs meets the threshold, the facility would use the IPCC Tier 1 approach and IPCC Tier 1 emission
factors. To account for heat transfer fluid use at semiconductor facilities, a f acility would add an additional 10 percent of their clean and etch emissions to their total facility emissions. 10

Facilities that Manufacture MEMS: To determine whether a facility that manufactures MEMS meets the threshold, the facility would use the IPCC Tier 1 approach and the EPA estimated emission factor for MEMS.

Facilities that Manufacture PV: To determine whether a facility that manuf actures PV meets the threshold, the facility would multiply annual fluorinated GHG purchases or consumpti on by the gas-appropriate 100-year GWPs (as defined in Table A-1 to subpart A of part 98). This method for PV fac ilities is expected to provide a more representative estimate of emissions than the IPCC Tier 1 approach and emission factors. IPCC Tier 1 factor s for PV are highly uncertain because they were developed based on analogy to the IPCC Tier 1 factors for LCD due to limited PV data availability.

Calculations to determine threshold applicability are presented below. Note that the equations below are to be used only for determining whether an electronics manufacturing facility falls above or below the threshold of 25,000 metric tons CO 2 e.

For calculating emissions of each fluorinated GHG i, for facilities that manufacture semiconductors or MEMS:



### 0.001 * * EF * E i

i i 

### GWP S = (Eq. 1)

Where:

E i = Annual production process emissions of input gas i (metric tons CO 2 e).

S = 100% of annual manufacturing capacity of a facility (m 2 ). (see Eq. 5)

EF i = Emission factor for input gas i (kg/m 2 ) (see Appendix A).

GWP i = Gas-appropriate GWP (see Table A-1 to subpart A, Global Warming Potentials).

0.001 = Conversion factor from kg to metric tons.

i = Input gas.

For calculating emissions of each fluorinated GHG i, for facilities that manufacture LCDs:

10 For simplicity, semiconductor facilities would estimate HTF em issions as 10% of total clean and etch emissions, as opposed to 11% which was used in our threshold analyses as presented above.Subpart I Technical Support Document

November 2010 6 

### 0.000001 * * EF * E i

i i 

### GWP S = (Eq. 2)

Where:

E i = Annual production process emissions of input gas i (metric tons CO 2 e).

S = 100% of annual manufacturing capacity of a facility (m 2 ). (see Eq. 5)

EF i = Emission factor for input gas i (g/m 2 ) (see Appendix A).

GWP i = Gas-appropriate GWP (see Table A-1 to subpart A, Global Warming Potentials).

0.000001 = Conversion factor from g to metric tons.

i = Input gas.

For calculating emissions of each fluorinated GH G i, for facilities that manufacture PVs:



### 001

. 0 * * E i i i 

### GWP C = (Eq. 3)

Where:

E i = Annual production process emissions of input gas i (metric tons CO 2 e).

C i = Annual fluorinated GHG (gas i) purchases or consumption (kg).

GWP i = Gas-appropriate GWP (see Table A-1 to subpart A, Global Warming Potentials).

0.001 = Conversion factor from kg to metric tons.

i = Input gas.

To sum emissions of all input gases i for all facilities: 

# ∑

=

i i 

### E 

### * E T 

### δ (Eq. 4)

Where:

E T = Annual production process emissions of all fluorinated GHGs (metric tons CO 2 e).

δ = Factor accounting for heat transfer fluid emissions, estimated as 10 percent of total annual production process emissions at a semiconductor facility. Set equal to 1.1 when calculating total annual production process emissions from semiconductor manufacturing. Set equal to 1 calculating total annual production process emissions from MEMS, LCD, or PV manufacturing.

E i = Annual production process emissions of input gas i (metric tons CO 2 e), as calculated Eqs. 1, 2, or 3.
i = Input gas.

For calculating a facility’s a nnual manufacturing capacity:

To determine 100 percent of annual manufacturing capacity, facilities would sum the maximum designed substrate starts of a facility over each month of a year as presented in Equation 5 below. Maximum designed substr ate starts is defined as the maximum quantity of substrates, expressed as surface area, that could be started eac h month during a reporting year if the facility were fully equipped as defined in the facility design specifications and if the equipment were fully utilized. It denotes 100 percent of annual manufacturing capacity of a facility.Subpart I Technical Support Document

November 2010 7 

# ∑

= 12 

### S

x x 

### W (Eq. 5)

Where:

S = 100 percent of annual manufacturing capacity of a facility (m 2 ).

W

x = Maximum designed substrate starts of a facility in month x (m 2 per month).

x = Month.

None of the methods for determining th reshold applicability account for controlled emissions by abatem ent systems. EPA is not permitting accounting for emissions reductions from ab atement systems because while electronics manufacturers may employ emissions abatement systems (e.g., thermal oxidizers) to lower their emissions and use the manufacturer published
destruction or removal efficien cy (DRE) for the system, abatement systems ma y fail to achieve their rated DREs for two reasons. First, the equipment may not be properly opera ted and maintained. Second, the DRE itself may have been incorrectly measured due to a failure to acco unt for the effects of dilution (e.g., CF 4 can be off by as much as a factor of 20
to 50 and C 2 F 6 can be off by a factor of up to 10 because of failure to properly account for dilution [Burto n, 2007].) In either event, the actual emissions from facilities employing abatement systems ma y exceed estimates based on the rated DREs of the systems and may therefore exceed the MtCO 2 e threshold without the knowledge of the facility operators. Hence, accounting for reductions in emissions from the use of abatement syst ems when determining if a facility exceeds the proposed 25,000 metric ton CO 2 e threshold limit is not permitted because the DRE used in such a calculation cannot be
verified.



### 3 Options for Emissions Calculat ion and Monitoring Methods

EPA evaluated a range of options for estimating process emissions from productions processes used in electronics manufacturing. Each one of these options is briefly described below.



### 3.1 Options for Estimating Fluorinated GHG Em issions from Etching and Cleaning

To estimate and report fluorinated GHGs fr om etching and cleaning, EPA evaluated th e 2006 IPCC Tier 1, Tier 2a, Tier 2b, and Tier 3 methods, as well as hybrids, refinements of, and modifications to those methods. 11 Lastly, EPA evaluated the use of continuous monitoring emissions systems (CEMS).

Many of the options described below, including the IPCC Tier 2b, Modified Tier 2b, Refined Method, Tier 2c, Tier 2d, and the IPCC Tier 3 methods use the typology presented in Figure 3-1 below. At the top of the typology figure are process types, which are broad groups of manufacturing steps used at a facility associated with substrate (e.g., wafer) processing during device manufacture for which fluorinated GHG emissions and fluorinated GHG usages are calculated and reported. The process types are plasma etching, chamber cleaning, and wafer cleaning. Process types for various methods include etching and chamber cleaning, and for some methods, wafer cleaning.

The second level in the figure consists of process sub-types. Pr ocess sub-types are sets of sim ilar manufacturing steps, more closely related within a broad process type. (Note, for clar ity, EPA is referring to what was previously termed processcategories in the April 2010 proposed rule (75 FR 18652) as process sub-types). Figure 3-1 only identifies process subtypes for the chamber cleaning process type, however in an option described below (mainly the Refined Method) process sub-types could be established for any process type. For example, under the plasma etching process type either film-based (e.g., oxide etch, nitride etch) or feature-based (e.g., gate etch, deep trench etch) process sub-types could be established; under the wafer cleaning process type, the sub-types of ashing and bevel cleaning could be established. At the lowest level of the typology tree in Figure 3-1 are production process recipes (“recipes”). The recipe typology is discussed further in
section 3.1.7.1 below.

11 It is important to note that the IPCC me thods were developed to estim ate national averages of emi ssions for specific sources ( e.g. national emissions from semiconductor manufacturi ng) and not for facil ity-specific emissions.Subpart I Technical Support Document

November 2010 8 Figure 3-1. Typology for Calculating Fluorinated GHG Emissions from Electronics Manufacturing

For some of the methods for estimating emissions from etching and cleaning discussed below, a distinction is made for facilities that manufacture semiconductors (see Tier 2c, Tier 2d, and Hybrid Approaches). Semiconductor manufacturing facilities would select the appropriate etch and clean emissi on estimation methods based upon facility size expressed in terms of annual manufacturing capacity.

The largest semiconductor manufacturing facilities are define d as those with a capacity of greater than 10,500 m 2 of substrate (e.g., silicon), as calculated using Equation 5 abov e. The largest semiconducto r manufacturing facilities account for nearly two-thirds of uncontrolled emissions from semiconductor manufact uring while accounting for less than 20 percent of all semiconductor facilities expected to report under s ubpart I. Applying this distinction, EPA expects that 29 of
the estimated 175 semiconductor facilities will be classified as “l arge” facilities. These results were based on the analysis illustrated in Figure 3-2 below. 12

Figure 3-2. Expected Fa cility Contributions to Total Emissi ons from Semiconductor Manufacturing

3.1.1 2006 IPCC Tier 1 Method

For the Tier 1 approach, the surface area of substrate (e.g., silicon, LCD or PV-cell) pr oduced during electronics manufacture is multiplied by default gas-specific emission factors. The advantages of the Tier 1 approach lie in its

12 See footnote 8.Subpart I Technical Support Document

November 2010 9 simplicity. However, this method does not account for the di fferences among process types (i .e., etching versus cleaning), individual processes, recipes, or tools, which leads to uncertainties in the default emission factors of up to 200 percent at the 95 percent confidence interval (IPCC, 2006). 13 Moreover, facilities routinely monitor gas consumption in the ordinary course of business, making it technically feasible to employ a me thod with the complexity of at least the 2006 IPCC Tier 2a approach without additional data collection efforts.

3.1.2 2006 IPCC Tier 2a Method

For the Tier 2a approach, chemical-specific gas consumption is multiplied by default emission factors for utilization, and by-product formation. The Tier 2a approach is relatively simple, given that gas consumption data is collected in the ordinary course of business. However, due to variation in gas utilization between etching and cleaning processes, the emissions estimated using the Tier 2a approach have greater uncertainty than emissions estimated using the Tier 2b approach.

3.1.3 2006 IPCC Tier 2b Method

For the Tier 2b approach, chemical-specific gas consumption by process type (etch or chamber clean) is multiplied by default emission factors for utilization and by-product formation. 14 This approach requires facilities to determine gas consumption by process type (etch and clean). Equation 6 below is used to estimate fluorinated GHG emissions for process type (j) for input gas (i), and Equation 7 below is used to estimate byproduct gas (k) that results from input gas (i) utilization during process type (j). 15



### 001

. 0 * ) d * a (1 * ) U (1 * E ij ij ij ij ij 

### − − = C (Eq. 6)

Where:

E ij = Annual emissions of input gas i from process type j (metric tons).
C ij = Amount of input gas i consumed for process type j (kg). (see Eq. 8)
U ij = Process utilization for input gas i for process type j (decimal fraction).

a ij = Fraction of input gas i used in process type j with abatement systems (decimal fraction).
d ij = Fraction of input gas i destroyed or removed in abatement systems connected to process tools where process type j is used (decimal fraction). (see Eq. 13) 0.001 = Conversion factor from kg to metric tons. i = Input gas. j = Process type.



### 001

. 0 * ) * 1 ( * * jk ij ij ijk ijk 

### d a C B BE

− = (Eq. 7)

Where:

BE ijk = Annual emissions of by-product k formed from input gas i from process type j (metric tons).

B ijk = Amount of gas k created as a by-product per kg of input gas i consumed for process type j (kg).
C ij = Amount of input gas i consumed for process type j (kg). (see Eq. 8)

13 This uncertainty refers only to semiconducto rs and LCDs. Tier 1 emission factor uncer tainty for PV was not estimated in the IP CC Guidelines (IPCC, 2006). Additionally, emissions from MEMS are not addr essed in the 2006 IPCC Guidelines.

14 For all methods based on default emission factors specified in th e final rule (e.g., the Tier 2b, Tier 2c, and Tier 2d methods ), a facility
must use the default factor s provided by EPA; the onl y exception is if a facility uses a fluorinated GHG for a particular proce ss type or sub-type for which default emissi on factors are not provided. Where defaults ar e not provided, the faci lity must either use ut ilization and by-product formation rates of 0 or, in th at particular instance, use directly meas ured recipe-specific emission factors followi ng the
methods outlined in section 3.1.7.1.

15 Note the 2006 IPCC Guidance for National Greenhouse Gas Inventories equations for estimating emissi ons and by-product emissions in the electronics industry (Equa tions 6.7 through 6.11) include a term for the h eel of gas cylinders/containers. However, the heel term has been excluded in Equations 6 and 7 because it is already a ccounted for when overall gas cons umption is estimated (shown in Equations 8 and 9).Subpart I Technical Support Document

November 2010 10 a ij = Fraction of input gas i used in process type j with abatement systems.
d

jk = Fraction of input gas i destroyed in abatement systems connected to proc ess tools where process type j is used (decimal fraction). (see Eq. 13) 0.001 = Conversion factor from kg to metric tons. i = Input gas. j = Process type. k = By-product gas.

Although the uncer tainty relative to Tier 2a is re duced, the Tier 2b approach also does not account for variation among individual recipes, processes or tools and, therefore, the esti mated emissions will have greater uncertainty compared to Tier 3 emissions estimates. The Tier 2b method, as shown in the uncertainty analysis performed by EPA, may understate actual emissions. (see Appendix C)

3.1.4 Modified Tier 2b Method

The Modified IPCC Tier 2b approach is based on the 2006 IPCC Tier 2b method (as described above). However, the Modified Tier 2b approach takes into account gas- and facility- specific heel factors, as opposed to utilizing a default value for heel factor as suggested in the IP CC Guidelines. Emission estimations using the Modified IPCC Tier 2b approach are
assumed to be less uncertain than estimati ons determined using the 2006 IPCC Tier 2b method. Th is is because when using a default heel factor, gas consumption is likely to be less representative of actual gas consumption, and hence emissions, in comparison to using gas- and facility- speci fic heel factors. (see section 3.2 for more discussion on the use of default versus gas- and facility- specific heel factors)

3.1.5 Tier 2c Method (Defaults fo r 5 Process Types/Subtypes)

The Tier 2c Method expands on the Modifi ed Tier 2b method for facilities that ma nufacture semiconductors. In the Tier 2c method, emissions would be estimated for five process type/subtypes: plasma etching, chamber cleaning (including in-situ plasma, remote plasma, and in-situ thermal), and wafer cleaning. For the Tier 2c Method, gas consumption apportioned to process types or sub-types is multiplied by default emission f actors for utilization and by-product formation, (dependent on the size of wafer manufactured at a facility) 16 , using Equations 6 and 7, respectively. 17 EPA considered the Tier 2c method
for facilities that manufacture semiconductor facilities and th at have annual manufacturing capacities of 10,500 m 2 or less (ass calculated using Equation 5). 18 Because the Tier 2c method is more gra nular than the IPCC and Modified Tier 2b methods, 19 EPA anticipates that its use will result in more accurate emission estimates.

3.1.6 The Refined Method (Defaults Fact ors for 9 Process Types/Subtypes)

The Refined Method, which was evaluated as part of the April 2010 proposal, expands on the two process types (etch and clean) of the IPCC Tier 2b method by re quiring that emissions be estimated from the etch, chamber clean and wafer clean process types by summing emissions from various process sub-types For the Refined Method, gas consumption apportioned by process sub-type is multiplied by default emission factors for utilization and by-product formation 20 , using Equations 6 and 7, respectively. 21

While process sub-types can be defined in many ways, the Re fined Method utilizes nine process sub-types which include four sub-types for etching, three sub-types for chamber cleaning, and two sub-types for wafer cleaning. The etching categories include oxide etch, nitride etch, silicon etch, and metal etch; the chamber cleaning categories include in situ

16 See Appendix A for the default factor s, and Appendix B for background on how th e default factors were developed.

17 When using Equations 6 and 7 for the Tier 2c met hod “j” indexes process sub- types or process types.
18 The Tier 2c method was finalized as part of the final rule , and all semiconductor facilities with annual manufacturing capacit ies of 10,500 m 2 substrate of less are required to calculate and report process em issions using this method. S ee the preamble for a discussion why EPA selected this method.

19 For the Tier 2c method emissions must be estimated for three chamber cleaning pro cess sub-types as opposed to just the broad chamber cleaning process type used in the Tier 2b methods.

20 EPA did not finalize default emission factors for the etch subtypes presented in the Refined Method.

21 When using Equations 6 and 7 for the Refined Method “j” indexes process sub-types as opposed to process types.Subpart I Technical Support Document

November 2010 11 plasma cleaning, remote plasma cleaning, and in situ thermal cleaning; and the wafer cleaning categories include bevel cleaning and ashing.

For the Refined Method EPA considered additional potential process sub-types for etching and chamber cleaning to replace or complement the process sub-types defined above. For etching, in addition to the four thin-film based sub-types defined above, EPA considered the use of the f eature-based sub-types contact etch, self-a lignment contact etch, gate etch, deep trench etch, isolation trench etch, through silicon vias and regular vias. Each of these represents a specific feature achieve d through etching (instead of subcategories based on the type of thin film etched). For chamber clean, alternative sub-types may distinguish between the types of films being removed from the chamber during cleaning. These might include distinguishing between chambers coated with tungsten an d silicon-based films, or distinguishing between thin-film deposition equipment manufacturers.

There are no published emission factors for the refined proce ss categories as defined in the Refined Method, therefore to obtain emission factors (i.e., u tilization and by-product form ation rates) for each proces s category, EPA undertook a process to collect data from industry, and evaluated its robustness and usefulness for creating emission factors through an averaging scheme, either simple or weight ed depending on information received. This process is further discussed in the TECHNICAL SUPPORT DOCUMENT (UPDATED) FO R PROCESS EMISSIONS FROM ELECTRONICSMANUFACTURE (e.g., SEMICONDUCTORS, LIQUID CRYSTAL DISPLAYS, PHOTOVOLTAICS, AND MICROELECTRO-MECHANICAL SYSTEMS): PROPOSED RULE FOR MANDATORY REPORTING OF GREENHOUSE GASES (March 22, 2010) and the Subpart I Notice of Data Availability (75 FR 26904). 22 EPA obtained a sufficient
amount of information to establish defau lt emissions factors for multiple chamber cl ean process sub-types, but there was an insufficient amount of information to support establishing de fault emission factors for multiple etch process sub-types. Therefore the Refined Method was not adopted for the final rule. 23

EPA considered the Refined Method for semiconductor facilitie s only, as semiconductor manufacturing is understood to be more variable and complex than other electronics manufacturing . The goal in establishing process sub-types under each process type is to account for variability in emission factors across processes to reduce uncertainty in emission estimates, while limiting the total number of process sub-types for which gas usage must be tracked. EPA expects that estimating emissions based on process sub-types for etch with robust default factors woul d result in more accurate facility-level emission estimates as compared to estima ting emissions using a single broad etch process type as presented in the IPCC
and Modified Tier 2b methods.

3.1.7 Tier 2d Method (Defaults for 4 Process Type s/Subtypes, Recipe-sp ecific emission factors for 1 Process Type)

For the Tier 2d method, 24 which uses the same process types/sub-types as the Tier 2c method, gas consumption is apportioned to the chamber cleaning process sub-types (including in-situ plasma, remote plasma, and in-situ thermal) and the wafer cleaning process type and is multiplied by various default emission factors for utilization and by-product formation, (dependent on the size of wafer manufactured at a facility, see Appendix A), using Equations 6 and 7, respectively. 25 However, for the plasma etching process type, emissions are estimated by apportioning gas consumption to etch recipes, each with directly measur ed recipe-specific emissions factors for utilization and by-product formation. Based on an uncertainty analysis conducted by EPA, the Tier 2d method appears to be more precise than the Tier 2c method (see Appendix C). EPA evaluated the Tier 2d method for th e largest semiconductor manufacturing facilities because, as discussed above, the largest facilities are ex pected to account for nearly 2/3 of a ll potential emissions , while accounting for less than 20 percent of all covered semiconductor facilities. 26

The Tier 2d method is focused on recipe -specific emission fact ors for etching processes because of the apparent gaps in the available emission factor knowledge base for etching processes used in the industry. While more than half of the gas consumed in semiconductor manufacturing is for chamber cleaning, most of the variability in gas consumption, and hence

22 Both documents are available in the docket at EPA-HQ-OAR-2009-0927.

23 Please see the preamble for more discussion on th e reasons why the Refined Method was not finalized.

24 The Tier 2d method was finalized as part of the final rule , and all large semiconductor facil ities (semiconductor facilities w ith annual manufacturing capacities greater than 10,500 m 2 substrate) are required to calculate and re port process emissions using this method. See the preamble for a discussion why EPA selected this method.

25 When using Equations 6 and 7 for the Tier 2d method “j” indexes recipes, process sub-types, or process types.

26 See the preamble for further discussion of EPA’s considerati ons for the Tier 2d method and steps taken to reduce burden.Subpart I Technical Support Document

November 2010 12 emissions, across many facilities is found for recipes used for etching. Semiconductor etch recipes utilize approximately six or more fluorinated GHGs, either alone or in combination and in various mixtures. Process recipes may vary between facilities because they are considered a function of company competitivene ss and innovation.

3.1.7.1 Development of Recipe-Sp ecific Emission Factors

Recipe-specific emission factors would be developed for each individual recipe, or for a set of similar recipes. An individual recipe refers a specific combination of gases, un der specific conditions of reactor temperature, pressure, flow, radio frequency (RF) power and duration, used repeatedly to fabricate a specific feature on a specific film or substrate. Recipe-specific emissions factors developed for measurements already made for an individual recipe may be applied to a set of similar recipes, where similar, with respect to recipe s means those recipes that are composed of the same set of
chemicals and have the same flow stab ilization times and where the documented differences, considered separately, in reactor pressure, individual gas flow rate s, and applied radio frequency (RF) power ar e less than or equal to plus or minus 10 percent. For purposes of comparing and documenting recipe s that are similar, facilities may use either the best known method provided by an equipment manufacturer or the process of record, for which emission factors for either have been measured. (Technical support for the definition of similar recipes can be found in Appendix D)

This definition of similar recipe applies to in-situ and RPS chamber cleaning as well as etching. It applies to in-situ chamber cleaning by virtue of the represen tative in situ chamber cleaning studies reviewed in Appendix D, which show that for changes in individual recipe variables of 10 percent or less results in corresponding changes in emissions of less than 10 percent. The recipes considered in Appendix D used NF 3 , C 2 F 6 and C 3 F 8 . The definition remains valid for contemporary RPS chamber cleaning recipes. As shown by Chen et. Al (2003), NF 3 utilization, which together with duration of cleaning time governs emissions during NF 3 -based RPS chamber cleaning, is relatively insensitive to changes in flow rate (over the wide range 2 to 6 lpm) and pressure (over the relatively wide range of 3 to 10 torr). Over these ranges, Chen et. al (2003) report NF 3 utilization efficiencies at 99 percent or above.

In a given reporting year, a facility must develop new recipe-sp ecific emission factors only for recipes that are not similar t o any recipe used in a previous reporting year. Three exampl es of how a facility may develop (or obtain) recipe-specific emission factors are presented below:

1. Make direct measurements on-site at the facility.

2. Obtain measurement information, and hence emission factors, from tests performed by a third-party, such as a tool supplier. (Any measurements made by a third-party are required to have been made for recipes that are similar recipes (as defined above) to those used at the facility.

3. Use factors from another facility that uses similar recipe s. (For example, there ar e instances where a company operating multiple facilities will use the same or similar recipes in more than one facility; in this instance, measured recipe-specific emission factors for a recipe used at one facility may also be used for estimating emissions from the use of a similar recipe at another facility.)

All recipe-specific emission factors must be measured using the International SEMATECH Technology Transfer (#06124825A-ENG) (December 2006) . A facility may use recipe-specific emissi on factors that were developed prior toJanuary 1, 2007, provided they were measured using the International SEMATECH Technology Transfer (#01104197AXFR) (December 2001).

3.1.8 2006 IPCC Tier 3 Method

The Tier 3 method uses the same equations as the IPCC Ti er 2b, Refined Method, Tier 2c and Tier 2d approaches (Equations 6 and 7) 27 , but requires facility-specific data on (1) gas consumption, (2) gas utilization, (3) by-productformation, rather than applying any default values. The 2006 IPCC Guidelines state that for the Tier 3 method, plantspecific values should be used for each indi vidual process or for each small sets of processes. There may be various ways processes or sets of processes could be defined, for instance by process platforms, processes or recipes. The Tier 3 method in the context of this rule uses gas consumption to be appor tioned to recipes, multiplied by re quires facility-specific, recipe

specific emission factors for utilization and by-production forma tion, developed for each individual recipe or set of similar

27 When using Equations 6 and 7 for the IPCC Tier 3 appr oach “j” indexes recipes as opposed to process types.Subpart I Technical Support Document

November 2010 13 recipes as discussed above in section 3.1.7.1. The use of the Tier 3 method is estimated to result in the least uncertain estimates amongst the methods presented by IPCC (IPCC 2006).

3.1.9 Hybrid Approach A

Hybrid Approach A, which was evaluated as part of the Apr il 2009 proposal, requires the largest semiconductor facilities (facilities with production capacities of greater than 10,500 m 2 silicon) to estimate their etching and cleaning emissions using an approach based on the IPCC Ti er 3 method; all other facilities (includi ng other semiconductor manufacturing and other electronics manufacturing facilities) would be required to use the IPCC Tier 2b method.

3.1.10 Hybrid Approach B

Hybrid Approach B, which was evaluated as part of the April 2009 proposal, requires Tier 3 reporting for all semiconductor facilities, but only for the top three gases emitted at each facility. For all other gase s, the Tier 2b approach is required. The top three gases emitted, based on data in the In ventory of U.S. GHG Emissions and Sinks, are C 2 F 6 , CF 4 , and SF 6 (EPA, 2008a). These top three gases accounted for approximately 80 percent of total fluorinated GHG emissions from semiconductor manufacturing during etching and chamber cleaning in 2006.

3.1.11 Continuous Emissions Monitoring Systems (CEMS)

CEMS requires facilities to install and operate CEMS to meas ure process emissions. A typical electronics manufacturing facility may have many individual process tools that influen ce emissions. Process tool exhaust is managed within the facility using stainless steel plumbing and ductwork. Due to the complexity of the manufacturing layout, CEMS would
either need to be attached to every tool or to a final exhaust point (e.g., scrubber stacks). One possible option is to use Fourier Transform Infrared Spectrometers (FTIRs) in scrubber st acks to measure facility emissions. FTIR spectroscopy is presently used to conduct short-term fluorinated GHG emission measurements on single tools. Another option would be to either continuously or intermittently bring a gas sample to one or more centrally located FTIRs, in which case any dilution issues that may arise when measuring fluorinated GHGs in stacks may be avoided.



### 3.2 Options for Estimating Facility Gas Consumption

Several of the estimation methods described above require gas consumption to be used to estimate emissions. Equations 8 and 9 below are used to estimate gas consumption for any input gas i used at an electronics manufacturing facility.



### C i 

### = (I Bi 

### – I Ei 

### + A i 

### – D i 

### ) (Eq. 8)

Where:

C i = Annual consumption of input gas i (kg).

I Bi = Inventory of input gas i stored in containers at the beginning of the reporting year, including heels (kg). 28

I Ei = Inventory of input gas i stored in cylinders or other containers at the end of the reporting year, including heels (kg). 29

A i = Acquisitions of input gas i during the reporting year through purchases or other transactions, including
heels in containers returned to the electronics manufacturing facility (kg).

D i = Disbursements of input gas i through sales or other transactions during the year, including heels in containers returned by the electronics manufacturing facility to the chemical supplier (kg). (see Eq. 9)
i = Input gas.

28 For containers in service at the beginning of a reporting year, account for the quantity in these containers as if they were f ull.

29 For containers in service at the end of a reporting year, account for the quantity in these containers as if they were full.Subpart I Technical Support Document

November 2010 14 

## ( )

i M

l il il il i 

### X F N h D + = 

# ∑

= 1 

### * * (Eq. 9)



### Where:

D i = Disbursements of input gas i through sales or other transactions during the reporting year, including heels in containers returned by the electronics manufacturing facility to the gas distributor (kg).

h il = Facility-wide gas-specific heel factor for input gas i and container size and type l (expressed as a decimal fraction), as determined in §98.94(b). 30

N il = Number of containers of size and type l returned to the gas distributor containing the standard heel of input gas i.

F il = Full capacity of containers of size and type l containing input gas i (kg).

X i = Disbursements under exceptional circumstances of input gas i through sales or other transactions during the reporting year, including those meas ured in exceptional circumstances (kg).
i = Input gas.
l = Size and type of gas container.
M = The total number of different sized container types. If only one size and container type is used for an input gas i, M=1.

For the heel factor 31 (h il ) used in Equation 9, EPA evaluated two options including the IPCC default heel factor and gas-and facility-specific heel factors. Both of these options are described below.

3.2.1 IPCC Default Heel Factor

The IPCC default value for the fraction of gas remaining in the shipping container (i.e. the “h eel”) is 10 percent (IPCC, 2006). This value is intended to be applicable to all gas containers, regardless of the gas type or container size or shape. However, heels may vary among gases and container sizes and shapes. Differences in gas usage practices may also exist between facilities which would not be accounted for when using the IPCC default heel factor. Therefore, the use of the IPCC default heel factor may result in misestimating gas consumption and emissions.

3.2.2 Gas-and Facility-Speci fic Heel Factors

Facility-specific heel fact ors for each gas and container type and size are base d on the residual weight or pressure of the gas container, or trigger point for change out, that a facility uses to change out that container for each container type for each gas used. By using these trigger points, along with the initia l mass of the container, gas-and facility-specific heel factors
can be calculated. 32

To account for exceptional circumstances 33 when gas containers are not changed pr ecisely when they reach the targeted trigger points, EPA evaluated the option of requiring reporters to weigh or determine the pressure of the gas container as opposed to using the facility-wide gas-specifi c heel factor as part of determining th e net amount of gas used at a facility. To account for changes in gas consumption pr actices, EPA considered two situations in which facility-wid e gas-specific heel

30 If a facility us es less than 50 kg of a fluorinated GHG or N 2 O in one reporting year, the facility may assume that any h il for that
fluorinated GHG or N 2 O is equal to zero.

31 Heel is defined as the amount of gas th at remains in a gas cylinder or container after it is discharged or off-loaded.

32 The initial mass of a container may be determined through gas supplier documents; however the reporter remains responsible for the accuracy of these records.

33 EPA is requiring an exceptional circumstan ce be defined as one in which a cylinder/c ontainer is changed at a residual mass or pressure that differs by more than 20 percent from the “trigger point fo r change out.” When using mass based trigger points for change, it should be determined if exceptional circumstances have occurred based on the net weight of gas in containers, excluding the tare weigh t of the
container.Subpart I Technical Support Document

November 2010 15 factors would have to be recalculated; both when the trigger point for change out used to establish a heel factor for a gas and container type differs by more than one percent or five percent from the previously used trigger point for change out.

The use of a gas-and facility-specific heel factor is expected to produce more accurate estimates of gas consumption in comparison to the use of the IPCC default value of 10 percent. This is because the amount of gas that remains in a gas container after it is discharged or off-loaded is not the same for every gas and container type, and the default value does not account for exceptional circumstances or variations in gas cons umption practices within or be tween facilities. Therefore applying a broad default value to every gas container will lead to estimations that may not be representative of actual facility gas consumption, and hence facility emissions.



### 3.3 Option for Apportioning Gas Consumption

When estimating emissions using methods such as the Modified IPCC Tier 2b or the Tier 2c or Tier 2d methods, and a fluorinated GHG is used in more than one process type or sub-type (e.g., C 2 F 6 used for both etch and clean processes), facility-wide gas consumption must be apportioned to the approp riate process types, process s ub-types, or recipes through the use of Equation 10. The product of that apportioned gas usage and the corresponding emission factor (either default or recipe-specific) will equate to a facility’s uncontrolled emissions for a specific process type, process sub-type, or recipe . These emissions can be summed within and over all process type s and categories at a facility to determine total facilitywide uncontrolled emissions.



### C ij 

### = f ij 

### * C i 

### (Eq. 10)

Where:

C ij = Annual amount of input gas i consumed for recipe, process subtype, or process type j (kg).

f ij = Recipe-specific, process sub-type-specific, or process type-specific gas apportioning factor (decimal fraction). 34

C i = Annual consumption of input gas i (kg). (see Eq. 8)
i = Input gas.
j = Recipe, process sub-type or process type.

Apportioning factors (f ij ) used in Equation 10, would be developed using facility-specific engineering models based on a quantifiable metric selected by a facility (such as wafer passes or wafer starts). 35 This model, utilizing measurable process information, may be based on the most appropriate quantifiable metric for each facility. Such a model utilizes facility process information to determine apportioni ng factors using the ratio of the amount of input gas i used per recipe (process category, process type) multiplied by the number of times that recipe is used on a tool and the number of tools that recipe is used on over the total amount of gas i used.

Given that facilities may select how to construct, and on wh ich quantifiable metric to base facility-specific engineering models for gas apportioning, EPA considered various documentation and verification steps for facilities to take.

Documentation

As part of recordkeeping requirements, in site GHG Monitori ng Plans (required in §98.3(g)(5)), specific information about their facility-specific engineering model, including definitions of variables, derivations of equations and formulas, and example calculations to ensure ap portioning factors are repeatable 36 would be documented and updated annually. This

34 See Section 3.3 discussion on apportioning.

35 Wafer passes is a count of the number of times a wafer substrate is processed in a specific process recipe, sub-type, or type. The total number of wafer passes over a reporting year is the number of wafe r passes per tool multiplied by the number of operational pro cess tools in use during the reporting year. Wafer starts means the number of fresh wafers that are intr oduced into the fabrication seque nce each month. It includes test wafers, which means wafers that are exposed to all of the conditions of process characterization, incl uding but not
limited to actual etch conditions or actual film deposition conditions.

36 Repeatable means that the variables used in the formulas for the facility’s engine ering model for gas apportioning factors are based on observable and measurable quantities that gov ern gas consumption rather than engineering judgment about those quantities or gas consumption.Subpart I Technical Support Document

November 2010 16 information would be updated eac h year for each facility to account for change s to tools or process at a facility between reporting years.

Verification

To verify engineering models used to apportion gas consumption, EPA requires facilities to demonstrate that the results from the model are repeatable and to co mpare the difference between modeled gas usage and actual gas usage. Facilities would verify a facility-specific engineering model through the following:

1. Analyzing at least a 30-day period of operation during which the capacity utilization of the facility equals or exceeds 60 percent of its design capacity. 37

2. Comparing the actual gas consumed of input gas i to the modeled gas consumed of input gas i for one fluorinated GHG used for the plasma etching pro cess type and one fluorinated GHG us ed for the chamber cleaning process type. The fluorinated GHGs selected for comparison would be the ones used in the largest quantities, on a mass basis, for each of the identified process types.

3. Ensuring that the comparison performed for the gas used in the largest quantity for the plasma etching process type does not result in a difference between the actual and modeled gas consumption that exceeds five percent relative to actual gas consumption, reported to one significant figure using standard rounding conventions.

3.3.1 Example of Facility-Specific Engineeri ng Model Based on Wafer Pass

One example of a quantifiable metric on which a facility may base an engineering model to apportion gas consumption is wafer pass. During semiconductor device manufacturing, counts of wafer passes for each manufacturing step, over the course of a year, carry information about fab productivity and fluorinated GHG usage. The design and profitable operation of a modern fab entails detailed considerations of the functional performance of the equipment and its cost-of-ownership. Cost of ownership is governed in large part by its productivity—the number of wafers processed per hour, the time to
maintain and time to failure.

Fab managers use information about counts of wafer passes to reduce variable costs by identifying practices that increase fab throughput and that reduce material costs. Wafer pass counts in modern fabs are typically available through the manufacturing execution software (MES) that comes with proces s equipment. MES is capable of tracking the activities associated with each piece of manufacturin g equipment. In older fabs that may not employ MES, wafer pass counts are available through process flow information for each product manufactured.

While wafer-pass-count information is available, it is not routin ely gathered. Instead, it’s gather ed at the request of fab and product line managers for purposes of managing work-in-process load, reducing fab cycle time, reducing product cycle time, identifying and removing process bottlenecks, etc.

For estimating gas usage, wafer pass counts could be collected either electronically or physically. For those fabs with MES, wafer pass counts could be collected electronically, either continuously or intermittently. In those fabs without MES, wafer pass counts would be collected intermittently at peri ods chosen to be representative of manufacturing over the reporting period.

The example following is a demonstration of the use of wafer pass in apportioning NF 3 consumption at a hypothetical facility for the following three process sub-types defined by the Refined Method: oxide etch, silicon etch, and remote plasma clean. For simplicity and demonstration purposes, it is assumed that at the hypothetical facility NF 3 is the gas used in the largest quantity, on a mass basis, for the plasma et ching process type and the chamber cleaning process type.

An illustrative case for a semiconductor facility that can be cons idered where wafer passes are the quantifiable metric of gas usage activity used, in a facility-specific engineering model, is a facility that uses NF 3 for chamber cleaning with remote plasma systems and for etching polysilicon an d oxide films. With knowledge of the NF 3 -specfic heel and the number of
NF 3 containers used, the facility knows the amount of NF 3 consumed. To estimate emissions the facility must now apportion NF 3 usage between the chamber cleaning, polysilicon etching, and oxide etching process sub-types. To do this it might use the total number of wa fer passes through each and every NF 3 -cleaning system together with the time and nominal (not measured actual) gas flow rate for each and every NF 3 -cleaning system and the corresponding figures for polysilicon

37 If a facility operates below 60 percent of its design capacit y during the reporting year, the period during which the facility experiences its highest 30-day average utilization w ould be used for model verification.Subpart I Technical Support Document

November 2010 17 etch processes and oxide etch processes to arrive at the proportion of NF 3 used for cleaning chambers and etching polysilicon and oxide films. Once developed, these apportioning factors could be used to estimate NF 3 gas usage for the cleaning and etching process sub-types proposed in our method. This example is illustrated further in Table 3-1 below.

Table 3-1. Illustrative Calculation for NF 3 Example at One Facility

Gas Type – Annual Usage, kg. Process Sub-type Apportioning Factor Process sub-type gas usage, kg.

RPS Chamber Cleaning 82% 46,202

Polysilicon Etch 17% 9,561 NF 3 – 56,286 kg

Oxide Etch 1% 523

Note: Annual gas usage presented is the modeled usage not the nominal usage.
For the example presented in Table 3-1, the an nual nominal gas usage is 56,009 kg of NF 3 , with 520 kg of NF 3 used for oxide etch, 9,514 kg of NF 3 use for polysilicon etch, and 45,974 kg of NF 3 used for RPS chamber clean. Using this information, as well as the modeled amount of gas consumed for each of the three process sub-types considered, an example verification is presented in below in Table 3-2.

Table 3-2. Illustrative Verification for Hypoth etical Facility-Specific Gas Apportioning Model Process Sub-Type Nominal Usage Modeled Usage Chamber Clean Process Type RPS 45,974 46,202 Comparison 0.5% Etch Process Type Oxide etch process 520 523 Silicon etch process 9,514 9,561 Total 10,034 10,084 Verification Comparison 0.5%

While the manufacturing process for other electronics manuf acturers are less complex as compared to semiconductor manufacturing as most gases are used for a single process ty pe, facilities that manufacture LCDs, MEMS and PV may also use engineering models based on quantifiable metrics of manufacturing activity for apportioning gas consumption by process type. The approach of using a facility-specific model may also be applied to apportion consumption of N 2 O.



### 3.4 Options for Estimating Nitrous Oxide (N 2 

### O) Emissions

EPA evaluated two methods to estimate emissions of N 2 O during CVD or other N 2 O-using manufacturing processes, such as chamber cleaning, both of which would utilize Equation 11 . The first option is the use of two facility-specific N 2 O
utilization factors for each CVD and other N 2 O-using manufacturing processes. These factors would be developed by directly measuring N 2 O utilization at a facility using the 2006 ISMI Guidelines or the 2001 ISMI Guidelines, provided the measurements were made prior to January 1, 2007. 38 Gas consumption used in Equation 11 would be determined using the estimation and apportioning methods discussed above in sections 3.2 and 3.3.



### 0.001 * ) d * a (1 * ) U (1 * O) E(N

, N

, N

, N

, N j 2 2 2 2 2 j O j O j O j O 

### C

− − = (Eq.11)

Where:

E(N 2 O) j = Annual emissions of N 2 O for N 2 O-using process j (metric tons).
C N2O,j = Amount of N 2 O consumed for N 2 O-using process j and apportioned to N 2 O processes (kg).
U N2O,j = Process utilization factor for N 2 O-using process j.

38 If a third party has measured facility-specific N 2 O utilization factors, the conditions under which the measurements were made must be representative of the facility’s N 2 O-emitting processes.Subpart I Technical Support Document

November 2010 18 a N2O,j = Fraction of N 2 O used in N 2 O-using process j with abatement systems.
d

N2O,j = Fraction of N 2 O for N 2 O-using process j destroyed by abat ement devices connected process j. 0.001 = Conversion factor for kg to metric tons. j = Type of N 2 O-using process.

Alternatively, default N 2 O utilization factors for CVD and other N 2 O-using manufacturing processes would be applied in Equation 11. The default N 2 O utilization factor for CVD used is 20 percent (emission factor of 0.8), which is the midpoint of the utilization range of 0 percent to 40 percent. EPA determined the upper bound of this range through information collected in an industry survey presented in a comment received in response to the Ap ril 2009 rule proposa l. This industry survey concluded that on average the utilization of N 2 O for all processes at a fab is ~40 percent. In the industry survey, the measured utilization factors were largely from newer 300 mm manufacturing equipment. EPA did not consider the 40 percent as representative because N 2 O utilization of older manufacturing equipment, such as 150 mm and 250 mm tools is not fully represented. In addition, the information provided did not fully identify the specific processes from which the average N 2 O utilization factor was calculated. EPA understands that the majority of N 2 O is used in CVD processes; therefore 40 percent was considered the upper bound of the range for the CVD default N 2 O utilization factor. To be conservative and to avoid the potential for underestimation of emissions the lower bound of ~0 percent was considered.

For other manufacturing processes, such as chamber cleaning, the default N 2 O utilization factor applied would be 0 percent (emission factor of 1.0), which is equivalent to assuming that all N 2 O used in manufacturing processes, other than CVD, is
emitted. EPA took this approach because of a lack of information about N 2 O utilization for other N 2 O-using process.



### 3.5 Options for Estimating Heat Transfer Fluids (HTFs) Emissions

3.5.1 IPCC Tier 1 Approach

The Tier 1 approach for HTF emissions is based on the utili zation capacity of a semiconductor facility multiplied by a default emission factor. Although, the Ti er 1 approach has the advantages of simplicity, it relies on a default emissions factor to estimate HTF emissions and has relatively high un certainty compared to the Ti er 2 approach (IPCC, 2006).

3.5.2 IPCC Tier 2 Approach

The IPCC Tier 2 approach, which is a mass-balance approach , uses company-specific data and accounts for differences among electronics manufacturing facilities’ HTFs (which vary in their global warming potentials), leak rates, and service practices, and has an uncertainty on the or der of ±20 percent at the 95 percent c onfidence interval (IPCC, 2006). Equation 12 below shows the company-specific mass-balance equation for estimating HTF emissions. Facilities are required to provide the total nameplate capacity (HTF charge) of equipment that contains fluorinated heat transfer fluids “newly installed” during the reporting period.



### 001

. 0 * ) ( * i iE i i i iB i i 

### D I R N P I density EH

− − +

− + = (Eq. 12)

Where:

EH i = Emissions of fluorinated GHG heat transfer fluid i (metric tons/year).

density i = Density of fluorinated heat transfer fluid i (kg/l).

Ii B = Inventory of fluorinated heat transfer fluid i in containers other than equipment at the beginning of the reporting year (in stock or storage) (l).

P i = Acquisitions of fluorinated heat transfer fluid i during the reporting year (l). Includes amounts purchased from chemical suppliers, amounts purchased from equipment suppliers with or inside of equipment, and amounts returned to th e facility after off-site recycling.

N i = Total nameplate capacity (full and proper charge) of equipment that uses fluorinated heat transfer fluid i and that is newly installed during the reporting year (l).

R i = Total nameplate capacity (full and proper charge) of equipment that uses fluorinated heat transfer fluid i and that is removed from service during the current reporting year (l).Subpart I Technical Support Document

November 2010 19 I iE = Inventory of fluorinated heat transfer fluid i (in containers other than equipment) at the end of the reporting year (in stock or storage) (l).

D i = Disbursements of fluorinated heat transfer fluid i during the reporting year (l). Includes amounts returned to chemical suppliers, sold with or inside of equipment, and sent off site for verifiable recycling or destruction.

0.001 = Conversion factor from kg to metric tons.

i = Heat transfer fluid.



### 3.6 Options for Reporting Controlled Emissions from Abatement Systems

While the 2006 IPCC Guidelines offer gas-specific default DREs , these values were optimized for specific processes and tools, and are not expected to be representative for all tools and gas flow rates. The IPCC default DRE values are also not applicable to abatement systems which cannot abate CF 4 at DREs greater than 85 perc ent (IPCC, 2006). Because of the
aforementioned reasons and to ensure the accuracy of controlled emissions 39 estimations, EPA evaluated the following two options for the reporting of controlled emissions: the use of an EPA developed DRE default value and the direct, proper measurement of DRE values using EPA’s Protocol for Measuring Destructi on or Removal Efficiency of Fluorinated Greenhouse Gas Abatement Eq uipment in Electronics Manuf acturing (EPA 430-R-10-003) (EPA DRE Protocol) (EPA, 2010)

. As part of both of these options, EPA evaluated requiring certification of proper installation, maintenance, and operation of abatement systems, as well as monitoring the uptime of abatement systems.

3.6.1 Proper Installation, Operation, and Maintenance

There are many abatement system manufactur ers, all of whom manufacture many mode ls of systems that are marketed as fluorinated GHG-destruction capable (Beu, L. 2005). While some of these systems may be capable of destroying some fluorinated GHGs, they may not be effective in abating CF 4 (Beu, L., 2005), which in some processes can constitute 10 percent – 20 percent (by volume) of fluorinated GHG exhaust composition (EPA, 2008d). This variability may be partially attributable to installation as well as operating and maintena nce practices (Beu, L. 2005), although variations in how destruction is measured may also contribute to this variab ility (Beu, L., 2005). Additionally it is well known across the industry that abatement system perform ance varies greatly depending on a variety of abatement device and process parameters such as temperature, flow and exhaust composition (Beu, L., 2005, EPA 2008c, 2008d)).
Therefore, ensuring that abatement syst ems are properly installed, operated, an d maintained according to manufacturers’ specifications is important to reduce the likelihood of inaccurate estimations of DREs. It should be noted that this is also i n line with 2006 IPCC applicability requirements for reporting controlled emissions due to abatement system use (IPCC,2006).

3.6.2 Monitoring Abatement System Uptime

Applying a DRE value that is not discounted for the time an abatement system at a facility is being operated within the range of parameters as specified in the operations manual provided by the system manufacturer (or is on “operational mode”), would result in an underestimation of total facility emissions. Uptime refers to the ratio of the total time during which the abatement system is in an operational mode with fluorinated GHGs or N 2 O flowing through production process tool(s) connected to that abatement system, to the total time during which fluorinated GHGs or N 2 O are flowing through production process tool(s) connected to that abatement system. An exception to this is time during which exhaust flows are passed through a redundant abatement system 40 that is in the same abatement system class 41 as the primary abatement system. Such time may be included in the uptime of the primary system.

39 Controlled emissions are defined as the quantity of emissions that are released to the atmosphere after application of an emis sion control device (e.g., abatement system).

40 A redundant abatement system is defined as a system that is specifically designed, in stalled and operated for the purpose of d estroying
fluorinated GHGs and N 2 O gases. A redundant abatement sy stem is used as a backup to the main fluorinated GHGs and N 2 O abatement system during those times when the main system is not functioning or operating in accordance with design and operating specific ations.

41 Class means a category of abatement syst ems grouped by manufacturer model number(s) and by the gas that the system abates, including N 2 O and carbon tetrafluoride (CF 4 ) direct emissions and by-product formation, and all other fluorinated GHG direct emissions and by-product formation. Cla sses may also include any other abatement system s for which the reporting facility wishes to repo rtSubpart I Technical Support Document

November 2010 20 Equation 13 below can be used to calculate the fraction of input gas destroyed or removed in abatement systems connected to process tools where a recipe, process sub-type, or process type is used. This number is used to calculate the annual emissions from input gas and by-product in the above Equations 6 and 7, respectively. Equation 14 below is used to calculate the uptime.



# ∑ ∑

=

p ijp p p ijp ijp

j i 

### C u d C

d * *

, (Eq. 13)

d ij = Fraction of input gas i destroyed or removed in abatement systems connected to process tools where recipe, process sub-type, or process type j is used (decimal fraction).

C ijp = Amount of input gas i consumed for recipe, process sub-type, or process type j fed into abatement system p (kg).

d ijp = Destruction or removal efficiency for input gas i in abatement system p connect ed to process tools where recipe, process sub-type, or process type j is used (decimal fraction).

u p = Uptime of abatement system (decimal fraction). (see Eq. 14)

i = Input gas.

j = Recipe, process sub-type, or process type.

p = Abatement system.

p p

p 

### T t

u = (Eq. 14)

u p = The uptime of abatemen t system p (decimal fraction).

t p = The total time in which abatement system p is in an operational mode when fluorinated GHGs or N 2 O are flowing through production process tool(s) connected to abatement system p (hours).

T p = Total time in which fluorinated GHGs or N 2 O are flowing through production process tool(s) connected to abatement system p (hours).

p = Abatement system.

EPA considered two options for values for d ijp expressed in Equation 13 above, the use of an EPA developed DRE factor, or properly measured DREs. Both of these op tions are discussed in the following sections.

3.6.3 EPA Default DRE Value

As discussed previously, the 2006 IPCC gas-specific default DR E values were optimized for specific processes and tools. However DREs are expected to vary across abatement systems and gas flow rates. For this reason, EPA estimates that the
use of the IPCC default DRE value will result in controlled emi ssions estimates that are not representative of actual facility operations. Manufacturer supplied DREs may also result in emi ssions estimates that are not representative of actual facility operations because the DRE itself may have been incorrectly m easured due to a failure to acco unt for the effects of dilution (e.g., CF 4 can be off by as much as a factor of 20 to 50 and C 2 F 6 can be off by a factor of up to 10 [Burton, 2007].) This understanding is supported by industry assessments as presented in Beu, 2005. Therefore, EPA developed a default DRE to be used to report controlled emissions provided that the abat ement system for which the default value is representing is properly installed, operated, and maintained and is specifically designed for fluorinated GHG and N 2 O abatement.

controlled emissions provided that class is identified.Subpart I Technical Support Document

November 2010 21 EPA developed the DRE default value using data from the EPA DRE measurement program, in which measurements have been made at three separate facilities. 42 All of the data collected through th e measurement program properly took into account the effects of dilution. Using the DRE data set fr om these measurement studies, the following data selection criteria were applied to determine values to in clude in the development of the default DRE.

• Data must be from abatement devices that were prop erly installed, operated, and maintained, as well as designed to abate fluorinated GHGs and N 2 O. 43 This is consistent with the requirements for all abatement systems for which emissions are reported. In cases wher e this criterion was not met, the DRE values measured were often indistinguishable from zero.

• Data must be in the form of a discrete value. Under the EPA DRE measurement program, some DRE measurements taken exceeded 99 percent. In these instan ce the measured data was expressed as a non-discrete value, (i.e. ≥ 99 percent (e.g. for CHF 3 , NF 3 , SF 6 )), which could not be applied to a method to determine a default
DRE value.

After evaluating the data based on these cr iteria, a set with a population of 11 meas ured DREs was used to develop the EPA
default DRE value. These 11 DREs in the set were for CF 4 , and were measured on two thermal abatement systems each attached to two etch tools, which, in turn, had four chambers. This data set, which can be referenced in Table 3-3 contains results from two measurement conditions: (a) DRE measurement when the process tool plasma is off, when just CF 4 and diluent gas from each chamber enters th e abatement system, and (b) measurement of DRE during wafer processing, when
CF 4 together with other waste effluents leave the tool durin g actual wafer processing enters the abatement system.
Measured DREs are shown for each etch to ol. These are regarded as independen t measurements of the DRE for abating
CF 4 for each abatement system.

Table 3-3. Data Set Used to Develop EPA Default DRE Value Experiment ID Comment about experiment Measured CF 4 DRE Source of data a FK15 #1 No plasma 87.5 Table IV FK15 #2 No plasma 63.1 Table IV FK15 #3 No plasma 79.4 Table IV FK15 #4 No plasma 77.4 Table IV FE05#1 No plasma 84.5 Table IV FE05#2 No plasma 82.2 Table IV FE05#3 No plasma 91.7 Table IV FE05#4 No plasma 96.0 Table IV Additional data from wafer tests, all chambers FK15 Trench etch, #1 & #3 only 83 Table VIII FK15 Via etch, #1 & #3 only 85 Table VIII FE05 FE etch #3 & #4 only 90 Table IX

a Source: EPA, 2009.
The summary statistics of the data set is presented in Table 3-3 is presented in

Table 3-4. Also presented in

42 For more information about the three studies, please see the following reports: Developing a Reliable Fluor inated Greenhouse Gas (FGHG) Destruction or Removal Efficiency (DRE) Measurement Met hod for Electronics Manufacturing: A Cooperative Evaluation with

IBM (EPA 430-R-10-004); Developing a Reliable Fluorinated Greenhouse Gas (F- GHG) Destruction or Removal Efficiency (DRE) Measurement Method for Elec tronics Manufacturing: A Cooperative Evaluation with NE C Electronics, Inc. (EPA 430-R-10-005); and Developing a Reliable Fluorinated Greenhouse Gas (F-GHG) Destruc tion or Removal Efficiency (D RE) Measurement Method for Electronics Manufacturing: A Cooperative Evaluation with Qimonda (EPA 430-R-08-017).
43 While the EPA DRE measurement program only looked at abatemen t systems performance for fluorinat ed GHGs, it was assumed, for this use, that abatem ent systems that were designe d to treat fluorinated GHGs we re also designe d to treat N 2 O.Subpart I Technical Support Document

November 2010 22 Table 3-4 is the default DRE determined under the assumption that the measured DREs are di stributed normally, and under the condition that 95 percent of the population will be above the value of 59% (i.e. the lower on e-sided tolerance interval). For simplicity the value was rounded to one significant figure, equating to a default DRE of 60 percent.

Table 3-4. Summary Statistics and Default DRE (Lower One-Sided Tolerance Interval)

Mean of Measured Values Stdev of Measured Values Lower One-Sided
Tolerance Interval

No Plasma Measured DRE 82.73 10.054
- All Measured DRE 83.62 8.70 59

3.6.4 Proper Measurement of Abatement System DRE

For purposes of this rule, proper measurement of DRE values are those measured in accordance EPA’s DRE Protocol. The EPA DRE Protocol provides a practical and reliable method for measuring DREs of POU abatement devices while also providing flexibility to users. In addition, the use of the EPA DRE Protocol will ensure dilution is properly accounted for when determining DREs. (Please refer to the EPA DRE Protocol for a more detailed discussion on the justification for the development and application of the Protocol).

A representative random sampling approach can be used to re duce burden associated with directly and properly measuring DREs of each abatement system at a fac ility. Therefore, EPA evaluated the use of a random sampling abatement system testing program (RSASTP) that would span all classes of abatement systems for which controlled emissions are reported. (Class means a category of abatement systems grouped by manufacturer model number(s) and by the gas that the system abates, including N 2 O and carbon tetrafluoride (CF 4 ) direct emissions and by-product formation, and all other fluorinated GHG direct emissions and by-product formation. Classes ma y also include any other abat ement systems for which the reporting facility wishes to report controlled emissions provided that class is identified. 44 )

EPA qualitatively evaluated a range of options, from 10 percen t to 100 percent, for what would constitute an appropriate annual representative sample of abatement systems to be tested in a reporti ng year. EPA selected 20 percent as it would balance the annual measurement burden for reporters and anticip ate reliable maintenance periods and useful lifetimes of abatement systems. The RSASTP, w ith the selected 20 percent sample size, is described below.

An annual representative sample would consist of three or 20 percent of installed abatement devices, whichever is greater, for each model type each year. In the cas e that 20 percent of total abatement sy stems at a facility does not equal a whole number, the number of devices to be tested should be rounded up. 45 Each reporting period the DRE for a different three or 20 percent set of devices would be measured. For systems for which a DRE has not been measured in a reporting period, a simple average of the measured DREs fo r systems of that specific class of abat ement system is used. If redundant abatement systems are tested during peri ods of maintenance or repair, then the most recently measured or class average DRE for that system may be used.

Using the RSASTP, as outlined in the paragraph above, would ensure the eventual measurement of each device but over the course of several years. The importance of measuring the DRE for each abatement device lies in the fact that the robustness of installed abatement systems varies by gas and operating principle. Therefore, while some abatement devices may receive regular maintenance and perform optimally, others may, because of the specific nature of the exhaust they treat, not be functioning properly. As well, it is well known across the industry that abatement system performance varies greatly depending on a variety of abatement device and process parameters such as temperature, flow and exhaust composition. (Beu, 2005) Facilities often develop and ultimately use new pr ocesses potentially every year, and the parameters of these processes vary, hence the use of the RSASTP will capture these changes over time.

44 CF 4 is a very stable chemical and especially difficult to effectively abate. It may be used as an input gas and generated as a by product
of other fluorinated GHG process reactions.

45 For example, 16 abatement devices, 20 perc ent of which equals 3.2; therefore, four abatement devices would be measured each ye ar, which exceeds three.Subpart I Technical Support Document

November 2010 23 

### 4 QA/QC Requirements

QA/QC methods for reporting fluorinated GHG and N 2 O emissions include:

• Following the 2006 ISMI Guidelines for QA/QC proced ures when measuring and calculating facility-specific, recipe specific fluorinated GHGs and N 2 O utilization and by-product formation rates.

• Where facility-specific, recipe-s pecific fluorinated GHG and N 2 O utilization and by-product formation rates weremeasured prior to January 1, 2007, verify that the QA/QC procedures in International SEMATECH #01104197AXFR (2001 ISMI Guidelines) were followed when the factors were measured and calculated.

• Following the QA/QC procedures in the EPA DRE Pr otocol when calculating abatement system DREs.

• Demonstrating that as part of normal facility operations th e inventory of gas stored in containers at the beginning of a reporting year is the same as the inventory of gas stored in containers at the end of the previous reporting year.

QA/QC methods for reporting em issions from HTFs use and annual gas c onsumption for each fluorinated GHG and N 2 O
used include:

• Reviewing inputs to the gas consumption equation and HTF mass balance equation (Eqs. 8 and 12), to ensure inputs and outputs are all accounted for.

• Ensuring no negative inputs are entered in the gas consumption equation and HTF mass balance equation (Eqs. 8 and 12) and negative emissions are not calculated.

• Ensuring that the beginning of year inventory is identical to the end of year inventory from previous year.

• Ensuring that the total quantity of gas in containers in serv ice at the end of the reporting year is accounted for as if
the in-service containers were full. En suring also that the same quantity is accounted for in the inventory of gas stored in containers at the beginning of the subsequent reporting year.

General QA/QC methods include:

• Ensuring all flowmeters, weigh scales, pressure gauges, an d thermometers used to measure quantities that are used to meet requirements of subpart I have an accuracy and precision of one percent of full scale or better.



### 5 Procedures for Estimating Missing Data

It is expected that collecting gas consumption data and quan tifiable metrics for apportioning gas consumption will always be feasible for facilities, with the exce ption of the time period facilities are permitted to use Best Available Monitoring Methods (BAMM). 46 When estimating HTF emissions, the use of the ma ss-balance approach requir es correct records for all inputs. Therefore facilities that use HTFs and have missing data for one or more of the inputs for the mass-balance equation (see Eq. 12) can estimate HTF emissions using the ar ithmetic average of the emission rates for the reporting year immediately preceding the period of missi ng data and the months immediately fo llowing the period of missing data. Alternatively, missing information may be estimated from the heat transfer fluid supplier’s records. All methods and values used for all missing data values must be documented.



### 6 Reporting and Recordkeeping Procedures

The following data, which is additional to the information gene rally required to be reported and/or retained as records for all facilities covered under the MRR (see §98.3(c) and §98.3(g) (74 FR 56379, October 2009), would be useful for confirming emissions calculations and/or calculating emission f actors that could be compared across facilities for quality control purposes:

• For each facility report:

46 See the Electronics Manufacturing section of the preamble to th e Final Rule for a discussion on the use of Best Available Moni toring Methods under subpart I.Subpart I Technical Support Document

November 2010 24 o Annual manufacturing capacity of a facility.

o For facilities that manufacture semiconductors, the diam eter of wafers manufactured at the facility.

o Annual emissions of:

 Each fluorinated GHG emitted from each process type for which the facility is required to
calculate emissions.

 Each fluorinated GHG emitted from each individual recipe (includi ng those in a set of similar recipes), or process sub-type.

 N 2 O emitted from each chemical vapor de position processes and from other N 2 O-using manufacturing processes.

 Each HTF emitted.

o The method used to calculate fluorinated GHG emissions.

o Annual production in terms of substrate su rface area (e.g., silicon, PV-cell, glass).

o When factors for fluorinated GHG process utiliza tion and by-product formation rates and/or N 2 O utilization factors other than the default values provided in the appendices are used, the following:

 The recipe-specific utilization and by-product formation rate s for each individual recipe (or set of similar recipes) and/or facility-specific N 2 O utilization factors.

 For recipe-specific utilization and by-product formation rates, the film or substrate that was etched/cleaned and the feature ty pe that was etched, as applicable.

 Certification that the recipes included in a set of similar recipes are similar.

 Certification that the measurements for all reported recipe-specific utilization and byproduct formation rates and/or facility specific N 2 O utilization factors were made using the 2006 ISMI Guidelines, or the 2001 ISMI Guidelines if measurements were made prior to January 1, 2007.

 Source of the recipe-specific utilization and by-product formation rates and/or facilityspecific-N 2 O utilization factors.

 Certification that the conditions under which the measurements were made for facilityspecific N 2 O utilization factors are representative of the facility’s N 2 O-emitting production processes.

o Annual gas consumption for each fluorinated GHG and N 2 O, including where the facility used less than 50 kg of a particular fluorinated GHG or N 2 O used at the facility. For all fluorinated
GHGs and N 2 O used at the facility for which emissions have not been calculated, the chemical name of the fluorinated GHG used, the annual consumption of the gas, and a brief description of
its use.

o All inputs used to calculate gas cons umption of each fluorinated GHG and N 2 O used.

o Disbursements of each fluorinated GHG and N 2 O during the reporting year.

o All inputs used to calculate disbursements for each fluorinated GHG and N 2 O used, including all facilitywide gas-specific heel factors us ed for each fluorinated GHG and N 2 O. If the facility used less than 50 kg of a particular fluorinated GHG duri ng the reporting year, facility-wide gas-specific heel factors do not need to be reported for those gases.

o Annual amount of each fluorinated GH G consumed for each recipe, proce ss sub-type, or process type, as appropriate, and the annual amount of N 2 O consumed for each chemical vapor deposition and other electronics manufacturing production process.

o All apportioning factors used to apportion fluorinated GHG and N 2 O consumption.

o For the facility-specific apportioning model used to apportion fluorinated GHG and N 2 O consumption the following:

 Identification of the quantifiabl e metric used in the facility-specific engineering model to apportion gas consumption.

 The start and end dates selected to monitor for verification of the model.Subpart I Technical Support Document

November 2010 25  Certification that the gases selected for co mparisons correspond to the largest quantities consumed on a mass basis, at the facility in th e reporting year for the plasma etching process type and the chamber cleaning process type.

 The result of the calculations comparing the actual and modeled gas consumptions.

o Fraction each fluorinated GHG or N 2 O fed into a recipe, process sub-type, or process type that is fed into tools connected to abatement systems.

o Fraction of each fluorinated GHG or N 2 O destroyed or removed in ab atement systems connected to process tools where a recipe, proces s sub-type, or process type is used, as well as all inputs and calculations used to determine the inputs to calculate this fraction.

o Inventory and description of all abatement devices through which fluorinated GHGs or N 2 O flow at the facility, including the number of devices of each manufacturer, model numbers,
manufacturer claimed fluorinated GHG and N 2 O DREs, if any, and records of DRE
measurements over their in-use lives. The invent ory of abatement systems must describe the tools with model numbers and the recipe(s), process sub-type, or process type for which these systems treat exhaust.

o For each abatement system through which fluorinated GHGs or N 2 O flow at the facility, for which controlled emissions are reported, the following:

 Certification that the abatement device has been installed, maintained, and operated in accordance with manufacturers’ specifications.

 All inputs and results of calculations made acco unting for the uptime of abatement systems used during the reporting year.

 The default DRE value or properly measured DR Es for each abatement system used in that reporting year.

 Where the default DRE value is used to repo rt controlled emissions, certification that the abatement systems for which emissions are bein g reported were specifically designed for
fluorinated GHG and N 2 O abatement. Documentation stating that the system was designed for
fluorinated GHG and N 2 O abatement should be provided to show this.

 Where properly measured DREs or class averag es of DREs are used, the following must be reported:

• A description of the class, including the abatement system manufacturer and model number, and the fluorinated GHG and N 2 O in the process effluent stream.

• The total number of systems in th at class for the reporting year.

• The total number of systems fo r which DREs were properly measured in that class for the reporting year.

• A description of the calculation used to determine the class average, including all inputs
of the calculation.

• A description of method of randomly selecting class members for testing.

o For HTF emissions, inputs used in the mass-ba lance equation for each fluorinated GHG used.

o Where missing data procedures were used to estimate inputs into the HTF mass-balance equation, the number of times missing data procedures were followed in the reporting year, the method used to estimate the missing data, and the estimates of those data.

o A brief description of each “best available monitoring method” us ed, the parameter measured or estimated using the method, and the time period during which the “best available monitoring
method” was used.

• Retain records of:

o All data used and copies of calculations made as a part of estimating gas consumption and
emissions.Subpart I Technical Support Document

November 2010 26 o Documentation for the values used for fluorinated GHG and N 2 O utilization and by-product formation rates. Where facility-specific, recipe -specific gas utilization and by-product formation rates were used, the following records must also be retained:

 Complete documentation and final report for measurements for recipe-specific utilization and by-product formation rates demonstrating that the values were measured using the 2006 ISMI Guidelines, provided the measurements were made prior to January 1, 2007.

 Documentation that recipe-specific utilization and by-product formation rates developed for the facility are measured for recipes that are similar to those used at the facility. Included in the documentation, recorded to two significant figures, should be reactor pressure, flow rates, chemical com position, applied RF power, direct current (DC) bias, temperature, flow stabilization time, and duration.

 Documentation that the facility’s N 2 O measurements are re presentative of the N 2 Oemitting processes at the facility.

 The date and results of the initial and any subsequent tests to determine utilization and by-product formation rates.

o Documentation for the facility-specific engineering model used to apportion fluorinated GHG
and N 2 O consumption. This documentation must be part of the site GHG Monitoring Plan. At a minimum, the following must be retained:

 A clear, detailed description of the facility-specific model, including how it was developed; the quantifiable metric used in the model; all sources of information, equations, and formulas, each w ith clear definitions of term s and variables; and a clear record of any changes made to the model while it was used to apportion fluorinated
GHG and N 2 O consumption across individual recipes (including those that are similar recipes), process sub-types, and/or process types.

 Sample calculations used for developing a recipe-specific, process sub-type-specific, or process type-specific gas apportioning factor for the fluorinated GHG used at a facility in the largest quantity, on a mass basis, during the repo rting year for each individual recipe (including those that are similar recipe), process sub-type, or process type.

o For each abatement device through which fluorinated GHGs or N 2 O flows at the facility, for which the facility is reporting controlled emissions, the following:

 Documentation to certify that the abatement device is installed, maintained, and operated in accordance with manufacturers’ specifications.

 Abatement system calibration and maintenance records.

 Where the default DRE value is used, do cumentation from the abatement system supplier describing the equipment’s designed purpose and emission control capabilities
for fluorinated GHG and N 2 O.

 Where properly measured DRE is used to report emissions, dated certification by the
technician who made the measurement th at the DRE was calculated according to methods in the EPA’s DRE Protocol, complete documentation of the results of any initial and subsequent tests, and final repo rts as specified in the EPA DRE Protocol.

o Purchase records for gas purchased.

o Invoices for gas purchases and sales.

o Documents and records used to monitor and calculate abatement system uptime.Subpart I Technical Support Document

November 2010 27 

### 7 References

Beu, L. (2005). “Reduction of Perfluorocarbon (PFC) Emissions: 2005 State-of-the-Technology Report”, TT#0510469AENG, International SEMATECH Manufacturing Initiative (ISMI), December 2005. Available at: http://www.epa.gov/highgwp/semiconductor- pfc/documents/final_tt_report.pdf.

Burton, C.S., & Beizaie, R. (2001). EPA’s PFC Emissions Model (PEVM) v. 2.14: Description and Documentation

. Prepared for Office of Global Programs, U. S. Environmental Protection Agency, Washington, DC. November 2001. Available at: http://www.epa.gov/highgwp/semiconductor-pfc/documents/pevm_draft.pdf.

Burton (2006). PV Emissions during Photovoltaic (PV) Cell Fabrication: A Scoping Report. Available in EPA docket EPA-HQ-OAR-2009-0927.

Burton (2007). Assessing the need for FC abatement standards , Solid State Technology, January 2007. Available at: http://www.electroiq.com/index/display/semiconductors-artic le-display/281422/articles/solid-state-technology/volume50/issue-1/departments/industry-forum/assessing-the-need-for-fc-abatement-standards.html.

Chen et. Al (2003). Chen, Xing, W. Holber, P. Loomis , E. Sevillano, S-Q Shao, S. Bailey and M. Goulding. Advances in Remote Plasma Sources for Cleaning 300 mm and Flat Panel CVD Systems . Semiconductor Magazine, August 2003, 6 pp. Available at: http://www.mksinst.com/docs/r/PRGcvdcleanTP.pdf.

DisplaySearch (2007). Flat Panel Fabs on a Disk . Q2 2007 Edition. Available for purchase at: http://www.displaysearch.com/cps/rde/x chg/displaysearch/hs.xsl/index.asp.

Earth Policy Institute (2007). Solar Cell Production Jumps 50 Percent in 2007 . Author: Jonathan G. Dorn. Available at: http://www.earth-policy.org/index.php?/indicators/C47/.

EPA (2008a) Inventory of U.S. Greenhouse Gas Emissions and Sinks: 1990-2007. U.S. Environmental Protection Agency, Washington, DC.

EPA (2008b). Uses and Emissions of Liquid PFC Heat Transfer Fluids from the Electronics Sector . Office of Air and Radiation Office of Atmospheric Programs, Climate Change Division, U.S. Environmental Protection Agency, Washington, DC. Available at: http://www.epa.gov/semicond uctor-pfc/documents/pfc_heat_tranfer_fluid_emission.pdf.

EPA (2008c). Developing a Reliable Fluorinated Greenhouse Gas (F-GHG) Destruction or Removal Efficiency (DRE) Measurement Method for Electronics Manufacturing: A Cooperative Evaluation with NEC Electronics, Inc. (EPA 430-R10-005). Office of Air and Radiation Office of Atmospheric Programs, Climate Change Division, U.S. Environmental Protection Agency, Washington, DC. Availabl e at: http://www.epa.gov/highgwp/semiconductorpfc/documents/nec_report.pdf 47

.

EPA (2008d). Developing a Reliable Fluorinated Greenhouse Gas (F-GHG) Destruction or Removal Efficiency (DRE) Measurement Method for Electronics Manufacturing: A Cooperative Evaluation with Qimonda (EPA 430-R-08-017). Office of Air and Radiation Office of Atmospheric Programs, Climate Change Division, U.S. Environmental ProtectionAgency, Washington, DC. Available at: http://www.epa.gov/highgwp/semiconductorpfc/documents/qimonda_report.pdf. 47

EPA (2009). Developing a Reliable Fluorinate d Greenhouse Gas (F-GHG) Destruction or Removal Efficiency (DRE) Measurement Method for Electronics Manufactur ing: A Cooperative Evaluation with IBM (EPA 430-R-10-004), Office of Air and Radiation Office of Atmospheric Programs, Climate Change Division, U.S. Environmental Protection Agency,

47 The NEC and Qinonda studies were conceived and conducted over the course of 2006 through 2007, and are referenced as such in t he Electronics Manufacture preamble.Subpart I Technical Support Document

November 2010 28 Washington, DC. Available at: http://www.epa.gov/highgwp/semiconducto r-pfc/documents/ibm_report.pdf.

EPA (2010). Protocol for Measuring Destruction or Removal Efficie ncy (DRE) of Fluorinated Greenhouse Gas Abatement Equipment in Electronics Manufacturing (EPA 430-R-10-003), Office of Air and Radiation Office of Atmospheric Programs, Climate Change Division, U.S. Environmental Prot ection Agency, Washington, DC. Available in EPA docket EPA-HQ-OAR-2009-0927.

Gaitan, M. & Takacs, M. (2008). The state of standards . Solid State Technology, February 2008. Available at: http://www.electroiq.com/index/display/semiconductors-artic le-display/319143/articles/solid-state-technology/volume51/issue-2/departments/mems/the-state-of-standards.html.

International Sematech (2006). Guideline for Characterization of Semiconductor Process Equipment . International Sematech, Technology Transfer # 06124825A-ENG, December 22, 2006. Available in EPA docket EPA-HQ-OAR-2009-
0927.

International Sematech (2001). Guideline for Characterization of Semiconductor Process Equipment . International Sematech, Technology Transfer #01104197A-XFR, 2001. Available in EPA docket EPA-HQ-OAR-2009-0927.

International Sematech (2004). Specification for Definition and Measurement of Equipment Reliability, Availability, and Maintainability. SEMI Standard E10-0304 , March 2004. Available for purchase at: http://www.semi.org/en/index.htm . Contact the EPA Docket Center (EPA docket EPA-HQ-OAR-2009-0927) for more information.

IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T Ngara, and K.Tanabe (eds.). Hayama, Kanagawa, Japan. Available at: http://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volume3/V3_6_Ch6_Electronics_Industry.pdf.

ITRS (2008) International Technology Roadmap for Semiconductors: 2007 Update . January 2008. This and earlier editions and updates are available at <http://public.itrs.net> In formation about the number of interconnect layers for years 1990 – 2010 is contained in Burton and Beizaie, 2001. PE VM is updated using new editions and updates of the ITRS, which are published annually.

Lee et al. (2007). Evaluation Method on Destruction and Re moval Efficiency of Perfluor ocompounds from Semiconductor and Display Manufacture. Bull. Korean Chem. Soc. 28 (8), 1383-1388 (2007). Available at: http://newjournal.kcsnet.or.kr/main/j_se arch/j_download.htm?code=B070824.

Li et al., (2001). Improved Technique for Evaluating Point-of-use Abatement Systems. Semiconductor Fabtech, 14th Edition, June 2001. Available at: http://www.fabtech.org/.

Lyshevshi, S. (2001). MEMS and NEMS System, Devices, and Structures , CRC Press. Available for purchase at: http://www.crcpress.com/ecommerce_product/produ ct_detail.jsf?catno=1262&isbn=0000000000000.

Roedern, B.V. & Ulla l, H.S. (2008). Critical issues for commercialization of thin-film PV technologies . Solid State Technology, February 2008. Available at: http://www. electroiq.com/index/display/semiconductors-articledisplay/319149/articles/solid-state-technology/volume-51/issu e-2/features/thin-film-technology/critical-issues-forcommercialization-of-thin-film-pv-technologies.html.

Semiconductor Equipment and Materials Industry (SEMI) (2008). World Fab Watch

, January 2007 Edition . Available for purchase at: http://www.semi.org/en/index.htm.

VLSI Research, Inc. (2008). Document 327028, V6.12.1— Worldwide Silicon Demand by Wafer Size, by Linewidth and by Device Type. January 2007. Available for purchase at: http://www.vlsiresearch.com.Subpart I Technical Support Document

November 2010 29 

### Appendix A - Default Emission Fa ctors for Threshold Applicability Determination and Etch and
Clean Emission Estimation Methods

Table A-1. Default Emission Factors for Threshold Applicability Determination

Emission Factors EF i Product Type CF 4 C 2 F 6 CHF 3 C 3 F 8 NF 3 SF 6 Semiconductors (kg/m 2 ) 0.90 1.00 0.04 0.05 0.04 0.20

LCD (g/m 2 ) 0.50 NA NA NA 0.90 4.00

MEMS (kg/m 2 ) NA NA NA NA NA 1.02

Notes: NA denotes not appl icable based on currently available information. Source: IPCC, 2006Subpart I Technical Support DocumentNovember 201030Table A-2. Default Emission Factors (1-Uij) for Gas Utilization (Uij) and By-Product Formation Rates (Bijk) for MEMS, LCD, and PV ManufacturingGreenhouse Gases with TAR GWPGreenhouse Gaseswithout TAR GWPNon-GHGsProducing FCBy-products‡Process GasCF4C2F6CHF3CH2F2C3F8c-C4F8NF3RemoteNF3SF6C4F6C5F8C4F8O F2COF2Etch 1-Ui0.7* 0.4* 0.4* 0.06* NA 0.2*NA 0.2 0.2 0.1 0.2 NA NA NACVD 1-Ui0.9 0.6 NA NA 0.4 0.1 0.02 0.2 NA NA 0.1 0.1 NA NAEtch BCF4NA 0.4* 0.07* 0.08* NA 0.2 NA NA NA 0.3* 0.2 NA NA NAEtch BC2F6NA NA NA NA NA 0.2 NA NA NA 0.2* 0.2 NA NA NACVD BCF4NA 0.1 NA NA 0.1 0.1 0.02† 0.1† NA NA 0.1 0.1 0.02† 0.02†CVD BC2F6NA NA NA NA NA NA NA NA NA NA NA NA NA NAMEMSMANUFACTURINGaCVD BC3F8NA NA NA NA NA NA NA NA NA NA NA 0.04 NA NAEtch 1-Ui0.6 NA 0.2 NA NA 0.1 NA NA 0.3 NA NA NA NA NACVD 1-UiNA NA NA NA NA NA 0.03 0.3 0.9 NA NA NA NA NAEtch BCF4NA NA 0.07 NA NA 0.009 NA NA NA NA NA NA NA NAEtch BCHF3NA NA NA NA NA 0.02 NA NA NA NA NA NA NA NAEtch BC2F6NA NA 0.05 NA NA NA NA NA NA NA NA NA NA NACVD BCF4NA NA NA NA NA NA NA NA NA NA NA NA NA NACVD BC2F6NA NA NA NA NA NA NA NA NA NA NA NA NA NALCDMANUFACTURINGCVD BC3F8NA NA NA NA NA NA NA NA NA NA NA NA NA NAEtch 1-Ui0.7 0.4 0.4 NA NA 0.2 NA NA 0.4 NA NA NA NA NACVD 1-UiNA 0.6 NA NA 0.1 0.1 NA 0.3 0.4 NA NA NA NA NAEtch BCF4NA 0.2 NA NA NA 0.1 NA NA NA NA NA NA NA NAEtch BC2F6NA NA NA NA NA 0.1 NA NA NA NA NA NA NA NACVD BCF4NA 0.2 NA NA 0.2 0.1 NA NA NA NA NA NA NA NACVD BC2F6NA NA NA NA NA NA NA NA NA NA NA NA NA NAPVMANUFACTURINGCVD BC3F8NA NA NA NA NA NA NA NA NA NA NA NA NA NANotes: NA denotes not applicable based on currently available information‡ The default emission factors for F2and COF2may be applied to cleaning low-k CVD reactors with ClF3.* Estimate includes multi-gas etch processesaMEMS manufacturing EFs are consistent with the 2006 IPCC Tier 2b EFs for the manufacture of semiconductors.† Estimate reflects presence of low-k, carbide and multi-gas etch processes that maycontain a C-containing FC additiveSource: IPCC, 2006Subpart I Technical Support DocumentNovember 201031Table A-3. Default Emission Factors (1-Uij) for Gas Utilization (Uij) and By-Product Formation Rates (Bijk) for Semiconductor Manufacturing for 150mm and 200 mm Wafer SizesProcess Gas iProcess Type/Sub-typeCF4C2F6CHF3CH2F2C3F8c-C4F8NF3SF6C4F6C5F8C4F8OPlasma Etching1-Ui0.69 0.56 0.38 0.093 NA0.25 0.038 0.20 0.14 NA NABCF4NA 0.23 0.026 0.021 NA0.19 0.0040 NA 0.13 NA NABC2F6NA NA NA NA NA 0.08 NA NA 0.12 NA NABC3F8NA NA NA NA NA NA NA NA NA NA NAChamber CleaningIn situ plasma cleaning1-Ui0.92 0.55 NA NA 0.400.10 0.18 NA NA NA 0.14BCF4NA 0.19 NA NA 0.20 0.11 0.011 NA NA NA 0.13BC2F6NA NA NA NA NA NA NA NA NA NA 0.030BC3F8NA NA NA NA NA NA NA NA NA NA NARemote plasma cleaning1-UiNA NA NA NA NA NA 0.018 NA NA NA NABCF4NA NA NA NA NA NA 0.0047 NA NA NA NABC2F6NA NA NA NA NA NA NA NA NA NA NABC3F8NA NA NA NA NA NA NA NA NA NA NAIn situ thermal cleaning1-UiNA NA NA NA NA NA NA NA NA NA NABCF4NA NA NA NA NA NA NA NA NA NA NABC2F6NA NA NA NA NA NA NA NA NA NA NABC3F8NA NA NA NA NA NA NA NA NA NA NAWafer Cleaning1-Ui0.77 NA NA 0.24 NA NA 0.23 0.20 NA NA NABCF4NA NA NA NA NA NA NA NA NA NA NASubpart I Technical Support DocumentNovember 201032Process Gas iProcess Type/Sub-typeCF4C2F6CHF3CH2F2C3F8c-C4F8NF3SF6C4F6C5F8C4F8OBC2F6NA NA NA NA NA NA NA NA NA NA NABC3F8NA NA NA NA NA NA NA NA NA NA NANotes: NA denotes not applicable based on currently available information.Table A-4. Default Emission Factors (1-Uij) for Gas Utilization (Uij) and By-Product Formation Rates (Bijk) for Semiconductor Manufacturing for 300mm Wafer SizeProcess Gas iProcess Type/Sub-typeCF4C2F6CHF3CH2F2C3F8c-C4F8NF3SF6C4F6C5F8C4F8OPlasma Etching1-Ui0.80 0.80 0.48 0.14 NA0.29 0.32 0.37 0.09 NA NABCF4NA NA 0.0018 0.0011 NA 0.079 NA NA 0.27 NA NABC2F6NA NA 0.0011 NA NA 0.12 NA NA 0.29 NA NABC3F8NA NA NA NA NA NA NA NA NA NA NAChamber CleaningIn situ plasma cleaning1-UiNA NA NA NA NA NA 0.23 NA NA NA NABCF4NA NA NA NA NA NA 0.0046 NA NA NA NABC2F6NA NA NA NA NA NA NA NA NA NA NABC3F8NA NA NA NA NA NA NA NA NA NA NARemote Plasma Cleaning1-UiNA NA NA NA 0.063 NA 0.018 NA NA NA NABCF4NA NA NA NA NA NA 0.040 NA NA NA NABC2F6NA NA NA NA NA NA NA NA NA NA NABC3F8NA NA NA NA NA NA NA NA NA NA NAIn Situ Thermal Cleaning1-UiNA NA NA NA NA NA 0.28 NA NA NA NASubpart I Technical Support DocumentNovember 201033Process Gas iProcess Type/Sub-typeCF4C2F6CHF3CH2F2C3F8c-C4F8NF3SF6C4F6C5F8C4F8OBCF4NA NA NA NA NA NA 0.010 NA NA NA NABC2F6NA NA NA NA NA NA NA NA NA NA NABC3F8NA NA NA NA NA NA NA NA NA NA NAWafer Cleaning1-Ui0.77 NA NA 0.24 NA NA 0.23 0.20 NA NA NABCF4NA NA NA NA NA NA NA NA NA NA NABC2F6NA NA NA NA NA NA NA NA NA NA NABC3F8NA NA NA NA NA NA NA NA NA NA NANotes: NA denotes not applicable based on currently available information.Subpart I Technical Support Document

November 2010 34 

### Appendix B - Development of EPA Published Em ission Factors for the Tier 2c and Tier 2d
Methods

To develop the default emission factors (EFs) for semiconductor manufacturing presented in Tables A-3 and A-4, EPA used industry data provided in cooperation with the Semiconductor Equipment and Materials International (SEMI), which redacted identifying company information prior to sharing the data with EPA. 48 An example of the form in which EPA received data is presented in Figure B-1. All of the data EPA received was compiled in an EF development database. The complete database is presented in Table 5 of the report Draft Emission Factors for Refined Semiconductor Manufacturing Process Categories (EPA-HQ-OAR-2009-0927-0073) (“NODA database”). 49 The EF data in the NODA database, which is identified by process sub-types and wafer technology, includes single- and multi-gas process chemistries. EF information is provided for single and multi-gas emission factors for utilization rates and by-product formation rates. The table denotes the dominant gas, the mass fraction emitted and the by-pro duct formation rates expressed as a mass fraction of the dominant gas. The table also denotes the mass-emitted fractions of the other gases used when multiple gases are employed in either chamber cleaning or f ilm etching emission processes.

Some providers of data identified a broad process type (i.e., chamber cleaning, etching and wafer cleaning) as well as a process sub-type. For example, informa tion pertaining to the chamber cleaning process type was identified by a chamber cleaning process sub-type (in-situ plasma, remote plasma, or in-situ thermal) as well. The NODA database identifies all information by the process sub-types of the Refined Method (s ee section 3.1.6), as the data collected by EPA was originally intended to be used to develop default emission factors for the Refined Method. Although the Refined Method was not included in the final rule, the emission factor data could be used to developed the default factors for the Tier 2c and Tier 2d methods because the information in the database is on a more granular level than is required for these two methods. EFs were developed by wafer technology for the broad etch process type and the broad wafer cleaning process types using all relevant information in the NODA database (e.g., all etch in formation, regardless of the identified sub-type was used to develop the etch EFs). EFs were also developed for the three chamber cleaning process sub-types (in-situ plasma, remote plasma, and in-situ thermal) for each wafer technology . These EFs are presented in Tables A-3 and A-4.

The EFs presented in Tables A-3 and A-4 are simple (unweighted) averages developed employing an approach similar to
that used for the 2006 IPCC Guidelines. Each EF represents an average of the ap propriate values in the NODA database with each entry given equal weight. The exact methods used to develop the EFs are further discussed in the report Draft Emission Factors for Refined Semiconductor Manufacturing Process Categories (EPA-HQ-OAR-2009-0927-0073).



### Measures Taken to Overcome Data Gaps

As evident by the “NA” entries in Tables A-3 and A-4 (NA denotes not applicable based on currently available information) and the information presented in the NODA database , there are still gaps in the EF data that are available to EPA. Using the rationale described below EPA has addressed these gaps.

48 See TECHNICAL SUPPORT DOCUMENT (UPDATED) FOR PR OCESS EMISSIONS FROM ELECTRONICS MANUFACTURE (e.g., SEMICONDUCTORS, LIQUID CRYSTAL DISPLAYS , PHOTOVOLTAICS, AND MICRO-ELECTRO-MECHANICAL SYSTEMS): PROPOSED RULE FOR MANDATO RY REPORTING OF GREENHOUSE GASES (March 22, 2010) and the Subpart I Notice of Data Availability (75 FR 26904) for more inform ation on the data collection process and initiation.

49 EPA initially intended to use the data provided in cooperation with SEMI to develop emission factors for the Refined Method. Therefore the data in the NODA database was originally used to develop draft emission factors for the Refined Method; however, EPA
decided not to include the Refi ned Method in the final rule.Subpart I Technical Support Document

November 2010 35 150 mm

EPA received only one value for fluorinate d GHG usage during device manufacture on 150 mm wafers. In the absence of additional emission data for 150 mm wafers, EPA assumed th at the EFs for 200 mm technol ogies apply for 150 mm as well. EPA based this assumption on the belief that EFs for 150 mm processing technology are closer to 200 mm processing technologies than to 300 mm processing technologies [see Beu (2005)]. Moreover, EPA understands that a portion of the EFs for 200 mm processing in the NODA database were developed on early 200 mm equipment prior to efforts by device and equipment manufacturers to reduce fluor inated GHG usage, which oc curred during the latter half of the 200 mm wafer era. The average draft EFs in Table A-3 re flect emission measurements made in the earlier and later portions of the 200 mm

wafer era. 50 To apply EFs for 300 mm wafer processing equipment to 150 mm might result in reported emissions being understated when EFs for 300 mm are smaller than those for 200 mm [see Beu (2005)]. This concern is supported by comparing the chamber cleanin g EFs for 200 mm and 300 mm technologies. Reports in the 200 mm wafer era indicated that chamber cleaning acco unted for the majority of fluorinated GHG usage.

Wafer Cleaning

300 mm Wafers

EPA received minimal information about emissions resulting from wafer cleaning in the semiconductor industry for 300 mm wafers. In the available patent literature for plasma ba sed bevel cleaning, a process was identified under the wafer cleaning process type that used two gases, CF 4 and SF 6 . [e.g., see Kim et al. (2009)] EPA’s EF database, the NODA database, does not contain gas utilization information for SF 6 for wafer cleaning, or any ch amber cleaning process that may be analogous for wafer cleaning. EPA filled this gap in SF 6 data by using a draft value based on the SF 6 utilization for in situ chamber cleaning provided in the IPCC Good Practice Guidance and Uncertai nty Management in National Greenhouse Gas Inventories (Chapter 3, Table 3.15). (see IPCC, 2000)

150/200 mm Wafers

No information for the wafer cleaning process type was available for 150 mm or 200 mm in the NODA database. As EPA understands, wafer cleaning processes were not used in the 150 mm and early 200 mm eras, but these processes began to phase into the industry in the late 200 mm era and the 300 mm er a (F. Burkeen, et al, 2007). Therefore, to make it feasible for a facility processing 200 mm wafers to estimate emissions from any wafer cleaning activities EPA drew an analogy between the 300 mm and 150/200 mm wafer cleaning EFs.

SF 6 Emission Factor for 150/200 mm Etch

The NODA database does not contain any information for SF 6 for etching for the 150 mm or 200 mm wafer technologies. However, based on the information presented in the 2006 IPCC Guidelines, it is known that SF 6 is used for etching processes for these technologies. To fill this gap in information, for the 150/200mm SF 6 etch EF, EPA used the etch SF 6 EF presented in the 2006 IPCC Guidelines.



### Modifications to the NF 3 

### Emission Factor

EPA learned, through discussions with a major supplier of e quipment, that its experience suggests that the utilization efficiency, U, of NF 3 in contemporary units for cleaning chambers that process 200 mm and 300 mm wafers are similar, despite the latter having higher NF 3 flow rates. RPS units, both 200 mm and 300 mm, carry the same guaranteed utilization efficiency of 95 percent; RPS units emit 5 percent or less of the NF 3 used during chamber cleaning. Achieving similar utilization efficiencies in the two systems is accomplished by increasing the plasma power to the RPS units with higher flow rates. For 200 and 300 mm systems, the manufact urer’s measurement experience indicates that the NF 3 utilization is of the order of 99 percent when operated under manufacturer’s specifications. The manufacturer also posited that utilization efficiencies should exceed 95 percent for t ypical, reasonably maintained RPS units.

50 In using the term “200 mm era” EPA is referring to the period during which th e majority of R&D expenditures by device and equipment manufacturers were dir ected to 200 mm wafers. Toward the end a wafer te chnology era, R&D attention shifted to the nex t generation of wafer technology, 300 mm wafers.Subpart I Technical Support Document

November 2010 36 EPA’s review of the NODA database showed that the mean complement of utilization efficiencies, 〈 (1- U) 〉 or mean EFs, associated with 200 mm and 300 mm wafer processing for NF 3 RPS were 0.0285 ± 0.0390 and 0.0174 ± 0.0285, respectively. Statistically, it is evident that th e population means are equal, and that all the NF 3 emission factor data in EPA’s NODA database may be considered as one population. EPA’s analysis is consiste nt with the manufacturer’s expectations although the mean utilizations for both wafer sizes fall below the tool manufacture’s measurement experience of 99 percent (EF = 0.01) but is also well above the performance expectation of 95 percent utilization (EF = 0.05).

Review of NF 3 RPS emission factors contained in EPA’s NODA database shows values that approach 0.20—80 percent utilization efficiencies, substantially below the expected perfor mance utilization efficiency of 95 percent. Providers of NF 3 utilization data to EPA did not describe the robustness or re presentativeness of the submitted data. EPA viewed in as reasonable to consider the possibility that the higher EFs might be outliers or anomalously high, that they might reflect one or more of four circumstances: (1) poorly measured EFs, (2) poorly maintained systems, (3) older RPS technologies, (4) operation outside manufacturer’s specifications. While the manufacturer agreed such high values could be outliers— especially for values above 0.1 or utilization efficiencies below 90 percent—EPA was uncomfortable with removing such
values without further consideration.

EPA combined the 200 mm and 300 mm data points for NF 3 RPS and posed the question whether the resulting distribution was better described with or without the larger values. For th is analysis EPA assumed the variability in the set of emission factors could be described by a beta distribution, a distribution that (1) accounts for the skewness of the observations and (2) constrains values between zero and one, 0 ≤ (1 – U i ) < s, where s < 1.

EPA’s analysis showed that a reasonable fit (p-value = 0.0037, chi-squared test) was obtained with s = 0.09 and removal of the top four EF values (0.1933, 0.1900, 0.1720 and 0.1120), wh ich correspond to utilization efficiencies between 89 and 81 percent, considerably below the manufacturer’s expected performance of 95 percent. The mean and standard deviation in
emission factor of the reduced dataset was 0.0182 ± 0.0191 (1 standard deviation). A somewhat higher mean emission factor (5 percent) and standard deviation of 0.0191 ± 0.0211 (1 standard deviation) and somewhat poorer fit (p-value = 0.0096, chi-squared) was obtained with s < 0.115 and removal of the top three values.

Consideration of the information gleaned through industry toge ther with EPA’s statistical analysis led EPA to choose the slightly lower mean value fo r the default EF (=0.0182 ± 0.0191 (1 standard deviation) ) for RPS chamber cleaning with NF 3 for both 200 and 300 mm wafer processing systems. After removal of the four highest values, the mean EFs for 200 mm and 300 mm RPS units remained statistically indistinguishable: 0.0204 ± 0.0202 and 0.0141 ± 0.0144, respectively.



### References

Beu (2005), “Reduction of Perfluorocompound (PFC) Emissions: 2005 State-of-the-Technology Report” (Technology
Transfer #05104 693A-Eng), December 2005 . Available at: http://www.epa .gov/highgwp/semiconductorpfc/documents/final_tt_report.pdf.

F. Burkeen, et al (2007), "Visualizing the Wafer's Edge," KLA-Tencor YMS Magazine, Winter 2007. Available in EPA docket (EPA-HQ-OAR-2009-0927) and at: http://208.194.225.108/company/magazine/spring07/YMS_Sp07_Visualizing.pdf.

IPCC (2000), Intergovernmental Panel on Climate Change (IPCC 2000), “IPCC Good Practice Guidance and Uncertainty Management in National Greenhouse Gas Inventories” (Cha pter 3, Table 3.15), 2000. Available at: http://www.ipccnggip.iges.or.jp/public/gp/english/.

IPCC (2006) 2006 IPCC Guidelines for National Greenhouse Gas Inventories . The National Greenhouse Gas Inventories Programme, The Intergovernmental Panel on Climate Change, H.S. Eggleston, L. Buendia, K. Miwa, T Ngara, and K.Tanabe (eds.). Hayama, Kanagawa, Japan. Available at: http://www.ipccnggip.iges.or.jp/public/2006gl/pdf/3_Volume3/V3_6_Ch6_Electronics_Industry.pdf.

Kim et al (2009). Patent 20070068900A1, March 29, 2007 and Kim et al. Patent 20090272402A1, November 5, 2009. Available at: http://www.google.com/patents/about?id=LYCbAAAAEBAJ&dq=20070068900A1 and http://www.google.com/patents/about? id=YJjJAAAAEBAJ&dq =20090272402A1.Subpart I Technical Support DocumentNovember 201037Figure B-1. Data Form Submitted bySemiconductor Device Manufacturers and Equipment Manufacturers to SEMIInformation for Developing EPA’s Refined FLUORINATED GHG Emission Process Categories and Corresponding Emission Factors(one form per process of record)Source/Contact (TBR)1(For SEMI use, information redacted)Date of measurementLocation of study (TBR)(For SEMI use, information redacted)Emission process category andsubcategory (s) of processcategory2Emission Process CategorySubcategory of Process CategoryAlternative Patterning/Etching SubcategoryEquipment (Manufacturername/model number) (TBR)3Letter denotes each reportingentity.(Information redacted, it is sought to facilitate sufficient consideration of equipmentmanufacturer when estimating U.S. shareequipment usage indevice manufacture.)Patterning/etchingsubcategories (Checkpreference and explain each).Specify both film type andetched feature regardless ofpreference.Film EtchFeature EtchExplanation:Specify/describe film type:Specify/describe etched feature:Substrate size (Si wafer)Measurement method/protocol4(Either ISMI Guidelines or equivalent alternative measurement protocol with brief explanation regarding why alternative is consideredequivalent to ISMI Guidelines.)Achieved ISMI Fluorine targetmass balance >90%? Checkanswer.5YESNO(Explain)Corresponding Emission Factorsfor Emission Process CategoriesProcess Gases (i)CF4C2F6C3F8c-C4F8CHF3SF6NF3C4F6C5F8C4F8OCH2F2F2COF2N2OMeasured emissions: 1-Ui6Standard deviation:Subpart I Technical Support DocumentNovember 201038Meas. CF4byproduct, Bip7N/ACF4B standard deviation:N/AMeas. C2F6byproduct, Bip7N/AC2F6B standard deviation:N/AMeas. C3F8byproduct, Bip7N/AC3F8B standard deviation:N/AUnit of measurement (mass):No. of wafers in study(number of wafers measured)CommentsInformation for developing average emission factorsEstimate of U. S. share ofselected process usage category,% (Check answer)10%20%30%40%50%60%70%80%90%Notes:1.TBR denotes To Be Redacted by SEMI.2.Distinguish between four emission process categories: 1.Chamber Cleaning; 2.Wafer Cleaning; 3.Patterning/etching; and 4.Deposition. WithinChamber Cleaningcategorydistinguish between the subcategories remote plasma cleaning and in situ cleaning. WithinWafer Cleaningcategory distinguish between the subcategories ashing and bevel cleaning.WithinDepositioncategory (N2O only) distinguish between the subcategories thermal and PECVD. There are two candidate Patterning/etching categories under consideration:FilmEtchandFeature Etch. The process subcategories under theFilm Etchalternative are: silicon, oxide, nitride and metal. The process subcategories under theFeature Etchalternativeare: Contact, SAC, Gate, Capacitor, Deep Trench, Isolation Trench, Regular Via,Through-silicon via andMetal etch. Select onesubcategory from each of the Film Etch and FeatureEtch categories and enter onto Data Form inthe Subcategory and Alternative Subcategory spaces. Distinguishing between Film Etch and Feature Etch on the Data Form is not necessary.3.SEMI will assign a separate letter for each entity that provides emission factor data.4.Provide a brief explanation that supportsusing an alternative to ISMI Guidelinesfor characterizing process emissions.5.Provide a brief explanation that supportsthe reliability of the reported emission factors despite not achieving the F mass balance target of >90% mass closure.6.Uidenotes gas utilization, i.e., fraction of gas destroyed or transformed during the process step. Many etch recipes use multiplefluorinatedGHG. In those instances, include all ofthose gases and the measured utilization ofeach. In this instance also note the convention adopted for reporting the by-product formation factor, Bipexplained in Note 7 below.7. Bidenotes fraction of gas i transformed into otherfluorinatedGHGs such as CF4formed from C2F6or CHF3, C2F6and C3F8formed from otherfluorinatedGHGs. In cases when aproduct such as CF4is formed in recipes containing multiplefluorinatedGHGs (e.g., CHF3, c-C4F8and C4F6) Bi, by convention, is the ratio of measured mass of CF4formed to massof largest quantity offluorinatedGHG comprising the recipe.Subpart I Technical Support Document

November 2010 39 

### Appendix C – Evaluation of Un certainty Associated with Alt ernative Emission Estimation
Methods

EPA examined estimates of semiconductor facility fluorina ted GHG emissions obtained using alternative emissions estimation methods and one distribution of annual fluorinated GHG gas-usages for a hypothetical facility processing 300- mm substrates that employing nine fluorinated GHGs. The five methods compared in this analysis were the:

(1) IPCC Tier 2b,

(2) Tier 2bM - emission factors modified/updated using the NODA Database,

(3) EPA’s Tier 2c -five fluorinated GHG-using process types/sub-types consisting of three chamber cleaning sub-types, one wafer cleaning ty pe and one aggregated etching type,

(4) EPA’s Refined Method -the same cleaning sub-types as in Tier 2c but the single aggregated etching type is expanded to four film-based sub-types, and

(5) a proxy for EPA’s Tier 2d -the same chamber and wafer cleaning types/sub-types as in Tier 2c but assuming as many groups of similar etching recipes as etching sub-types as there are for the Refined
Method.

For each alternative methodology, EPA compared the similarity between simulated emissions and the magnitudes of the spread in the 95 percent Confidence Interval (CI) of the relative error (RE) for the simulated emissions. This spread is the range in the probable error in emissions (PEE) and is calculate d as the sum of the absolute value of the estimated lower bound of the RE and the corresponding upper bound. Higher PEE estimates mean higher uncertainties. In the absence of measured emissions, similar nominal em issions and PEE estimates are the only available measures of “goodness.”



### Methodologies and Sources of Information

Plant Distribution of Fluorinated GHG Usage

In this analysis one gas usage distribution comprised of nine fluorinated GHGs was used. This assumed plant distribution was based on one sample gas use distribution from a fabrication plant of indeterminate industry representativeness. The nine fluorinated GHGs in this analysis in decreasing usage rank order were: NF 3 , CF 4 , SF 6 , C 2 F 6 , C 4 F 8 , CH 2 F 2 , C 5 F 8 , CHF 3 and C 4 F 6 . NF 3 comprised 63 percent of total [mass basis] used for chamber and wafer cleaning, with 99.99 percent of total
NF 3 used for chamber cleaning. All of the NF 3 used for chamber cleaning was assumed to be used in remote plasma cleaning. CF 4 was used for etching and wafer cleaning [99 percent for etching]. The rest of the gases were used to etch oxide, nitride, silicon, and metal films. (Emissions of HTFs or N 2 O were ignored in this analysis.)

Emission Factors and Relative Errors

The IPCC Tier 2b emission factors (both utilization and by-produc t formation rates) that were used were taken directly from the 2006 IPCC Guidelines. The IPCC p ublished 95 percent CI values for the emission factors were multiplied by two and converted to percent values to obtain relative errors for the IPCC Tier 2b emission factors. Emission factors (EFs) (both utilization and by-product formation ra tes) and REs for all other methods we re developed using data in the NODA database. However, data was sparse for etching sub-types specifically, and the implementation of an analysis required EFs and their REs to be estimated by analogy to other gases in so me instances. In cases where gas usage data was available, but a related EF was not available either in the IPCC or NODA database, EFs, and hence REs, were assigned by analogy based on the identical gas used in another process sub-type for whic h information was available. Th ese analogies are presented in Table C-1 below. For the Tier 2d (proxy) method, because it was not feasible to estimate emissions for “similar recipes” specifically used at the hypothetical fa b due to limited available data, EPA elect ed to estimate emissions for the Tier 2d method by modifying the REs for the four etching film-based sub-types used in the Refined Method analysis. The relative error for each the four etching sub- types for the Tier 2d method wa s assumed to be 20 percent.Subpart I Technical Support Document

November 2010 40 Table C-1. Analogies Made for EFs and REs fo r Various Fluorinated GHGs for the Alternative Methodologies.

Methodology Gas Process Sub-Type An alogous EF Analogous RE Other Notes

EFs for Gas Utilization

CF 4 Metal Etch Average of Silicon Etch, Nitride Etch, and Oxide etch Oxide Etch

CF 4 Nitride Etch -- Oxide Etch

c-C 4 F 8 Nitride Etch Oxide Etch Oxide Etch

SF 6 Silicon Etch -- Average of all available
REs for EFs in database

SF 6 Oxide Etch/ Nitride Etch Silicon Etch Average of all available
REs for EFs in database

C 4 F 6 Nitride Etch Oxide Etch Oxide Etch

CH 2 F 2 Silicon Etch average of Oxide Etch and Nitride
Etch Oxide Etch

CH 2 F 2 Nitride Etch -- Oxide Etch

CHF 3 Metal Etch/ Silicon Etch -- Average of Oxide Etch
and Nitride Etch

NF 3 Ashing -- In-situ Plasma Refined Method

C 5 F 8 Oxide Etch c-C 4 F 8 Oxide Etch c-C 4 F 8 Oxide Etch See note 2.b

SF 6 Etch Silicon Etch Average of all available
REs for EFs in database

Tier 2bM C 5 F 8 Etch c-C 4 F 8 Etch c-C 4 F 8 Etch See note 2.b/ The numbers for C 4 F 8 Oxide Etch was assumed for the larger etch category

SF 6 Etch Silicon Etch 100%

C 5 F 8 Etch 0 0 See note 5 Tier 2c

NF 3 Ashing -- 100%

CF 4 By-Product

C 4 F 6 Nitride Etch Oxide Etch Oxide Etch

CH 2 F 2 Silicon Etch average of oxide and nitride etch average of oxide and
nitride etch

C 5 F 8 Oxide Etch C 4 F 8 Oxide etch C 4 F 8 Oxide etch

CHF 3 Silicon Etch/ Metal Etch average of oxide and nitride etch average of oxide and
nitride etch Refined Method

NF 3 Ashing In-situ plasma In-situ plasma

Tier 2bM C 5 F 8 Etch C 4 F 8 etch C 4 F 8 etch

C 5 F 8 Etch 0 0 See note 5

NF 3 In-situ Thermal -- 200% Tier 2c

NF 3 Ashing 0 0 See note 5

C

2 F 6 By-ProductSubpart I Technical Support Document

November 2010 41 C 4 F 8 Nitride Etch Oxide etch Oxide etch See note 2.b

C 5 F 8 Oxide Etch C 4 F 8 Oxide etch C 4 F 8 Oxide etch

C 4 F 6 Nitride Etch Oxide Etch Oxide Etch Refined Method

CHF 3 Metal Etch/ Nitride Etch/
Silicon Etch Oxide Etch Oxide Etch

Tier 2bM C 5 F 8 Etch C 4 F 8 etch C 4 F 8 etch

Tier 2c C 5 F 8 Etch 0 0 See note 5

Notes:

1) – = Analogy not required 2) Analogies for process categories for each gas were made according to the following overarching steps:

a. If, for a gas, an EF/RE did not exist for a sub-type under a sp ecific process type, but existed for another process sub-type un der the same process type, the EF/RE that existed for that one speci fic sub-type was assumed to be analogous for the sub-type with no existing EF/RE. (i.e., if an EF/RE for CF 4 existed for nitride etch but not oxide etch, the EF/RE for CF 4 for oxide etch was assumed to be analogous to the CF 4 EF/RE for nitride etch.) If an EF or an RE for that gas category was missing, a proxy gas was used as an analogy for these estimates. Of note, Table 5 does not have an y information for gas C 5 F 8 . Hence C 4 F 8 was assumed as a proxy for all associated values.
b. In the case of SF 6 , no such gas analogies could be made, therefore, an average of all REs for the gas distribution was used. 3) Analogies for the overarching proce ss categories of Tier 2c and T i er 2d methods were based on the analogies made for each individual gas and process category for the refined method. 4) Additionally, where no EF informatio n was available but gas utilizatio n t ook place

, t he IPCC Tier 2b EF and RE were used in those
rare instances. 5) For the Tier 2c method only REs were assume d based on analogies, in situations wher e no emission actor existed for a given gas within the database, the related EF fo r calculations was assumed to be 0.Subpart I Technical Support Document

November 2010 42 Type of Emissions Probability Distribution

A beta distribution was assumed for emissions of the gases and their by-products for practical and theoretical reasons. The beta probability distribution cons trains the random variable (EFs in this wo rk) in each trial to values between 0 and 1. Alternatives to the beta distribution—normal, lognormal or gamma—would permit trial EFs that are physically impossible, i.e., EFs that could be negative or greater than one (depending on which of those three distributions were used in a simulation), which would require truncating negative values or values greater than one. The number of EFs in the NODA database for any gas and process type/sub-type was insufficient to test the appropriateness of the beta distribution. Parameters for the beta distribution were estimated using information from the 2006 IPCC Guidelines and using the mean
and REs estimated from th e May 2010 NODA information, as appropriate.

Location and shape parameters of the beta distributions we re estimated for each emissions estimation method using the corresponding means and variances from either IPCC tables (converting the IPCC reported 95 percent CI value to a percentage and multiplying by two to obtain REs for the fl uorinated GHGs) or the NODA database. EFs for all gases utilized were constrained between 0 and 1, but the by-product emissions were constrained between 0 and the highest value for that specific gas and process type available in the NODA database.

Uncertainty Analysis using @RISK

Monte Carlo simulations were performed for each of the five methods using @Ris k software and beta distributions to characterize the variability in EFs. Through @Risk, 10,000 ite rations were completed for each simulation. The results of these trials provided estimates of the mean of simula ted emissions, and the corresponding upper and lower bound confidence intervals (95 percent) in emissions, and, therefore, PEE estimates, for each of the five methods.



### Results

Estimating “Goodness” of Calculated Emissions:

This analysis adopted two measures of goodness: (1) the inter-comparability of nominal emissions for the IPCC Tier 2b, Tier 2bM, Tier 2c, Refined, and Tier 2d methods (i.e., th e similarity of emissions calculated using, for the single distribution of fluorinated GHG usage, the total emissions [MMTCE]), and (2) variability in the corresponding nominal emissions for each method as measured by the 95 percent CI . The PEE is used for comparing the variability in reported emissions among methods, because the PEE—a single number— is more convenient than using two numbers, the lower and upper bound of the 95 percent CI of the RE.

Results in detail

The outcome of an uncertainty analysis such as this one may presume that the simulation for each method employed (a)
robust estimates for emissions factors and reasonable estimat es for the variability in those factors for each gas used and each fluorinated GHG-using process type/s ub-type, and (b) a distribution repres entative of fluorinated GHG usage in semiconductor manufacturing. However, those presumptions don’t hold in this analysis as it relies on a paucity of available EF data and only one fluorinated GHG usage distribution whose representativeness is unknown. Therefore, how much weight should be given to the observations below is affected by the concerns about the scarcity of available EF and gas usage information.

Nominal and simulated mean emissions for the IPCC Tier 2b, Tier 2bM, Tier 2c, Refined, and Tier 2d methods are shown
in Table C-2 below. This table also illu strates the PEE for each methodology. All th e PEE values have been normalized to Tier 2b PEE for ease of comparison.

Table C-2. Comparison of nominal a nd simulated mean emissions (MMTCE) an d normalized estimates of PEE for
five alternative emission estimation methods

Simulated results after 10, 000 iterations with @Risk

Method Nominal emissions (MMTCE) Mean Emissions

(MMTCE) Normalized spread in 95%
CI of RE or PEE

Tier 2b 0.011 0.011 1

Tier 2bM 0.014 0.014 1.72Subpart I Technical Support Document

November 2010 43 Tier 2c 0.014 0.014 1.68

Refined Method 0.014 0.014 1.88

Proxy Tier 2d 0.014 0.014 1.39

As shown in Table C-2, the nominal and simulated emissions are equivalent at up to two significant figures for all the alternative methods evaluated. This supports EPA’s use of a beta distribution to quantify variability in EFs for this uncertainty analysis.

Inter-comparability of Emission Estimates:

The results (to two significant figures) provided in Table C-2 show that total nominal emissions obtained using the IPCC Tier 2b method are understated. All of the emission estimates from the other four methods are the same (up to two significant figures); with emissions being 27 percent higher than the corresponding emissions estimated using IPCC Tier 2b method (0.014 MMTCE for each of the four updated alternatives vs. 0.011 MMTCE for Tier 2b method). Conversely, Tier 2b emissions are understated by approximately 21 percent relative to the methods based on updated EFs.

Variability of Nominal Emissions/PEE:

The methods vary in their respective prob ability distribution spreads around the m ean as shown by the normalized PEEs presented in Table C-2. Results show that the PEEs for the Tier 2bM, Tier 2c, Refined and proxy Tier 2d methods are greater relative to the PEE for the IPCC Tier 2b method. Of the non-IPCC methods evaluated, the PEE for the proxy Tier 2d method is the lowest, but as noted prior it is higher than the PEE for the IPCC Tier 2b method ( see Table C-2). Based on this analysis, the IPCC Tier 2b method appears to produce an understated, but the most precise, estimate with the proxy Tier 2d method being a close second in precision.

It is noteworthy that the higher emissions and variability, calculated for the updated methods compared to the IPCC Tier 2b method for the distribution of gas usage used, appears to be attributable to higher CF 4 by-product formation EFs and REs for the updated methods compared to the IP CC Tier 2b method. For instance, the CF 4 by-product formation EF for NF 3 remote plasma clean for the Tier 2bM is twice as large as the corresponding EF for the IPCC Tier 2b. Similarly, the CF 4 by-product formation RE for the Tier 2b M exceeds the corresponding RE for the IP CC Tier 2b by a factor of 7.2 for NF 3 RPS. It seems that the updated EF info rmation contained in the NODA reflects the increased recent manu facturing trend of using carbon-based low-k dielectrics. This in creased use of C-films would be expected to lead to higher EFs in both etching and chamber cleaning due to reaction of carbon with F-atoms to form CF 4 . Further, the greater REs in EFs developed from the NODA database may be attributable to increase variability in both etching recipes and film C-content that is reflected in the NODA database. Without more information regarding the EF data and gas usages this explanation cannot be explored.



### Findings and Conclusions

The results of comparing the PEEs for all methods are both un expected and expected. On the one hand, these results are unexpected because one anticipates , in principle, that, as the information used to develop EFs improves and as a method’s comminution increases, simulated estimates of PEE would decrease. Therefore, in m oving from the IPCC Tier 2b to the Proxy Tier 2d method, the normalized estimates of PEEs should decrease, corresponding to a reduction in uncertainty. On the other hand, that outcome presumes that each simulation employed (a) robust estimates for emissions factors and
reasonable estimates for the variability in those factors for each gas used and each fluorinated GH G-using technology, and (b) a distribution representative of fl uorinated GHG usage in semiconductor ma nufacturing. Because these presumptions don’t hold—the analysis instead relies on a paucity of available EF data and only one fluorinated GHG usage distribution whose representativeness is unknown—the balance tips toward the unexpected. That there is a reduction in the spread of estimates of PEEs from the Refined Method to the proxy Tier 2d method seems noteworthy (see Table C-2). However, how much weight should be given to this observation is affected by the concerns regarding the paucity of available EF and gas usage information mentioned earlier.

Despite the ambiguity in these results, they do point to two reasons for moving away from the IPCC Tier 2b method: (a)
emissions estimated with the IPCC Tier 2b methods are under stated, and (b) there is a voi d in facility-level, emissionsrelevant information and a need to revise the IPCC Tier 2b EFs. The results of this evaluation also show that moving from the use of a default factor(s) for etch su b-types to the use of recipe-specific meas urements appears to increase certainty in
emission calculations.Subpart I Technical Support Document

November 2010 44 More facility-level, emissions-relevant information would perm it an uncertainty analysis to be performed with more meaningful and robust results. However, additional information about facility-level gas usage and EFs is needed before one can have confidence in facility-level reported emissions. Wh ile using properly weighted default EFs would yield reliable
estimates of total U. S. emissions from semiconductor manufact uring, considerable uncertainty in facility-level emissions
would remain.

Given the lack of available facility-level gas usage and emissi on information, particularly for the etching process type, as made apparent by this analysis, EPA is requiring that larger facilities report EFs for etching technologies and use verified gas apportioning models.Subpart I Technical Support Document

November 2010 45 

### Appendix D - Support for EPA’s Defi nition of Similar Recipe

Accurately tracking fluorinated greenhouse gas (fluorinated GHG) emissions during semiconductor manufacturing is a complex endeavor. Out of as many as seven hundred or so distinctly different manufacturing steps required to simultaneously produce as many as 500 electronic devices or so on a single substrate, which are completed within the course of approximately a month, many of those steps use as many as six fluorinated GHGs, either alone or in various combinations for plasma etching. (Boyd et al., 2009; Linx-consulting, 2010)

Estimating annual facility-level fluorina ted GHG emissions can be simplified by grouping manufacturing steps into process types or sub-types and using emission factors within each type or sub-type Accuracy in a facility’s annual estimate of emissions would be maintained with this approach provided the variability in the factors that govern emissions across each process type or sub-type is sufficiently small and, ideally, random.

For purposes of estimating and repor ting facility-level fluorinated GHG em issions, EPA defines three process types—chamber cleaning, wafer cleaning and etching. The chamber cleaning type is further subdivided into three process sub-types: in situ plasma, remote plasma and in situ thermal. For each sub-type, EPA developed default emission factors—figures for gas utilizati on and by-product formation, as appr opriate—for each gas that all facilities

may use.
EPA provides no process sub-types for (plasma) etching. EPA differentiates, for this process type only, the emissions calculating and reporting requirements for la rge and other semiconductor manufacturing facilities. For other semiconductor facilities, EPA developed a default emissi on factor for each gas that may be used to estimate and to report emissions for plasma etching. For large facilities, EPA requires that, for each gas used, facilities measure and report emission fact ors for each plasma etching recipe, that is not included in a set of similar recipes, as well as to report facility-level emissi ons for each of the recipes. Because th ere may be scores of plasma etching recipes used during device manufacture EPA expects group ing similar recipes will simplify and reduce the burden of emissions reporting with but a rela tively small effect on the overall accuracy of reported facility-level emissions. For recipes and associated gases that meet EPA’s defin ition of similar recipe, a large facility may measure the emission factor(s) for one of those recipes, as well as report, using the measured emission factors, the corresponding emissions associated with gases us ed in those similar recipes.

This appendix provides technical support for EPA’s definitio n of “similar recipe”. The appendix begins with a brief description—a primer—of the physics and chemistry that govern fluorinated GHG-based plasma etching during semiconductor manufacture. This discussion serves two purposes: (1) to identify the experimental parameters that govern current practice of fl uorinated GHG plasma etching, and (2) to bring into clear view the influence that variations in those parameters have on etch efficacy. Following this primer is a summary of the parameters that define plasma-etching practices during semiconductor manufacturing and, therefore, that potentially influence the concomitant fluorinated GHG emissions. The appendix then turns to a review of publicly available studies that investigate fluorinated GHG emissions as functions of th ose plasma-etching parameters. The appendix concludes with a definition for similar recipes, a definition that specifies the parameters as well as allowable ranges in those parameters—an allowable parameter space. EPA expects incr eases or decreases in these parameters within the specified ranges that define this space would result in acceptably small emission increases or decreases.



### Plasma Etching— A Primer

In semiconductor manufacturing, plasma etching practice is predominantly empirical, augmented by rules-of-thumb and heuristics. As Hills and Cook (2000) state, “The co mplexity encountered in actual processing requires much more information than is available experimentally or th at can be derived by even the most complex calculations...A practical plasma etching process involves interacting factors or species production and control in the gas phase, a multitude of chemical pathways inherent to the complexity of the molecules used, many poorly understood
interactions with the complex (and ‘dirty’) wafer surfaces and many device structure specifics...Plasma chemistries are thus chosen by a combination of experience, firs t principles and to some extent empirical ‘lore’.”

A phenomenological discussion is sufficient to establish a relationship between etching, emissions and controllable process parameters. In what follows, only as much of the physics and chemistry as needed is presented: the boundary is chosen in order to frame EPA’s definition of similar recipes.

Plasma etching—specifically reactive ion et ch (RIE), also called dry etch, is most simply defined as “the removal of material from a wafer surface with gase ous reactants to produce gaseous products, which ar e then pumped away andSubpart I Technical Support Document

November 2010 46 appropriately disposed” (Hills and Cook, 2000). The objective of dry etching is to reproducibly produce a pattern into a substrate with certain precision, across a substrate and from one subs trate to the next. RIE takes place in specifically designed reactors, of many designs, into wh ich reactants flow, substrat es are placed, and power is supplied (to sustain the plasma). 51 The scholarly and patent literature show that developing practical plasma etching recipes involves, for a given reactor design, experimentally identifying th e reactor pressure, reactant composition and flow rate, and power that produces suitable etch rates, feature dimension and profile, selectivity, etc. RIE is characterized by two concurring phenomen a: physical sputtering and chemical reaction, which result, to varying degrees, material selectivity 52 and etch anisotropy (directionality).

Figure D-1. RIE Etching showing (a) sputtering, (b) chemic al etching and (c) sputteri ng and chemical etching. Top (dark layer) is mask and lower lay er is material being removed (etched)

Figure D-1 illustrates these two concurring phenomena; it also shows how the image of a mask is reproducibly transferred into the film (substrate). Physical sputtering describes the dislodging of material, which occurs when sufficiently energetic but chemically inert ions hit a su rface and “kick out” atoms or molecular fragments. As the momentum carried by particles transfers energy to surface atoms (which is generally most effective under an angle
of ≈ 60 o measured from vertical), material removal leads to positively inclined sidewalls. Sputtering also erodes the photoresist mask (See Figure D-1a) (Rossnagel, 2000).

Chemical etching results from reactive species created in the plasma, form ed from a mixture of gaseous materials
that breakdown into r eactive components. These reactants form vola tile products upon reacti ng with the substrate material. Reactants are chosen in part for their selectivity to either not react with the mask material or react at a much slower rate than with the underlying substrate. Chemi cal etching, however, is isotropic (multidirectional) and, without counterbalancing effects, resu lts in under-etching and rounded profiles (See Figure D-1 b) (Hills and Cook, 2000).

Balanced physical and chemical material removal leads to ve rtical etch profiles. Additionally, in situ chemistry leads to formation of sidewall passivation layers, which achieves etch directionality. Chemically formed, etch-inhibiting films (e.g., polymer, oxide, etc.) occu r on the sidewalls but not on horizont al surfaces where th ey are continuously removed by ion-bombardment (See Figu re D-1 c) (Hills and Cook, 2000).

Etching reagents include fully fluorinated carbon- or non-carbon-containing compounds (e.g., CF 4 , C 2 F 2 , C 2 F 4 , C 2 F 6 , C 3 F 8 , C 4 F 6 , C 4 F 8 , C 5 F 8 , SF 6 , NF 3 , BF 3 ) and hydrofluorocarbon compounds (e.g., CHF 3 , CH 3 F, CH 2 F 2 , C 2 H 2 F 2 ).

Characterizing Fluorocompound RIE Processes Using the Film SiN

x Example

Plasma etching of Si, SiO 2 , SiN

x films, for example, with fluorocarbon and hydrofluorocabon gases is well studied (Oehrlein,1990; Lehman and Widmer,1978; Booth, 1999; and Standaert, et al., 2004, Lieberman and Lichtenberg, 2005). Argon appears to be a preferred diluent gas. To achieve the proper etch charact eristics (e.g., etch rates,

51 Because of the numerous loss processes that occur during plasma etching, plasmas are not self-sustaining and therefore, to achieve steady-state, require c ontinuous power input, in the form of high fre quency electromagnetic energy. In semiconductor manufacturing, the electromagnetic radiation is in the radio fre quency (RF) spectral region. Fo r simplicity of discussion, the term power is used in this re port rather than RF power.
52 Etch selectivity measur es the differential etching between photoresist ma terial and silicon-based film. The photoresist forms the pattern to be transferred to the substrate via the etching process (Garza et al., 2000).Subpart I Technical Support Document

November 2010 47 verticality, selectivity, uniformity, critical dimens ion (CD) control, to name an important few 53 ) additives such as
O 2 , H 2 or N 2 are common and patent literature points to the use of H 2 O 2 , CO, CO 2 and perhaps N 2 O (Zhu et al., 2005).

While Kushner and co-workers have successfully modeled th e chemical and physical factor s that govern etch rates for relatively simple systems such as C 2 F 6 (Zhang and Kushner 1999, 2000a, 2000b) that success falters with C 4 F 8 (Sankaran, A., A. Vasenkov and M. J. Kushner, 2002). A brief description of the well-studied combination of the
SiN

x -PMMA ( p oly m ethyl m eth a crylate, resist) combination will illustrate this complexity.

In CF 4 or CHF 3 plasma, F atoms and CF

x (x = 1-3) radicals as well as ions, fo rmed by the transfer of the kinetic energy of electrons to reactants, are generated and trans ported to the substrate surface via diffusive processes or accelerated by the electric field of the DC bias applied to the power electrode of the RF plasma. (The DC bias improves directionality but if too high can result in unwa nted increase in substrate temperature, so the DC-bias usually remains fixed; chillers are used to control the substrate temperature.) 54

Higher reactor pressure may in crease or reduce the dissociation (emissions and etch rate) of CF 4 into CF 3 , CF 2 , CF and F. Higher reactor pressure means hi gher reactor gas density and therefor e increased dissociation (but perhaps lower by-product formation depending on the dominant etching reactant). The etch rate, however may drop because the increased rate of polymer (C

x F y ) formation (vide infra). 55 Decreasing pressure leads to a decrease in ion scattering (ion energy is lost through collisions) leading to higher ion bombardment energies, and, in turn, higher physical etching.

Changes in reactant flow rate affect etching rate and emissions depending on reactor conditions. Under very low flow rates, increasing flow increases etching rate and emi ssions because reaction rates are limited by the supply of reactants. In this regime, increasing th e flow rate would increase etching and emissions. At flows above the reactantsupply-limited regime, reaction rates are limited by the reaction time compared to the reactor residence time. Shortening the residence time (by increasing the flow ra te) compared to the reaction time would decrease etching rate and emissions. Increasing the residence time (by de creasing flow rate) would increase etching rate and
emissions.

As previously noted, etching rate is the net of competing physical and chemical phenomena. Gas phase oligomerization of CF

x radical results in large C

x F y molecule formation (Booth, 1999), which forms a fluorocarbon polymer film on all surfaces (Standaert et al., 2004). The ma in etchant of SiN

x is the F atom (Li et al., 1995). Volatile etch products (SiF

x , CNF, NO, N 2 ) are generated and pumped away (See Figure D-2). Formed C

x F y is removed by etching and bombardmen t leading to reformation of CF 4 (or by-product CF 4 formation when the virgin etchant is only CHF 3 ).

53 It will become evident later in this report that fluorina ted GHG emissions have not been a major consideration when characterizing the manufacturability of plasma etching processes.
54 A sufficiently high DC voltage assures net transport of positive ions to the su rface of the substrate.
55 By-product formation and polymer forma tion may be reduced because both are se cond order in reactants resulting in formation rates changing in proportion to the square of reac tant gas densities.Subpart I Technical Support Document

November 2010 48

Figure D-2. Illustration of physical and chemical processes and interactions during CF 4 plasma etching of
SiN

x film

Much of this complex chemistry can be qualitatively explaine d by the F-to-C ratio (F/C), where a larger ratio favors etching and a smaller ratio favors C

x F y formation/deposition (Miyata et al., 1997). The balance between polymer formation and etching also shifts with other process parame ters such as pressure and power, although higher power adversely affects etching selectivity via photoresist rem oval due to increased ion bombardment. In general, it appears that increasing pressure favors C

x F y formation and more intense ion bombardment (power) favors C

x F y formation, and concomitantly, SiN

x etching (Dulak et al., 19 91), albeit with lower selec tivity (vide s upra). Recently, Rabilland et al. (2007) provided additional evidence that supports this mechanism for Si, SiCH, SiO 2 and SiOCH films using pulsed plasma.

Adding O 2 , H 2 or N 2 gases can achieve some fine control of the ch emical aspects of the etching characteristics of fluorocarbon plasmas:

• H 2 extracts fluorine atoms from the plasma via the reaction (H+F → HF),which suppresses SiN

x etching and
C

x F y formation (Oehrlein, 1990)

• O 2 scavenges H and carbon (H+O → OH ad C+xO → CO

x ), which suppresses C

x F y formation and increases F, which, in turn, increases SiN

x etching (Oehrlein, 1990) 56

• CO scavenges F (CO+xF → COF

x ), which enhances polymer formation and suppresses etching (Zhu et al., 2005)

• Argon and N 2 principally cause more intense ion bombardment and a dilution of CF

x radicals, both resulting in
thinner C

x F y layers and therefore enhanced SiNx etching. N 2 is also responsible for promoting the etch rate enhancing the reaction (2N +2 SiN → 2Si +2N 2 ) (Li et al., 1995)

If CHF 3 were used with or instead of CF 4 , the affect of hydrogen on etch rate comes with the etchant, which would lower the F/C ratio relative to a pure CF 4 plasma. If required, the etch rate could be adjusted upward by adding a
small amount of O 2 to the gas composition, which would lower H via the H+O → OH reaction.

56 See also Reid and Hughes (2007) who dem onstrate a similar effect of increasing O 2 flow on plasma etching of carbon doped
ultra-low- k dielectric layers.Subpart I Technical Support Document

November 2010 49 The description of this relatively simple etching chemistry provides a qualitative model for the chemistry for more complex molecules. A principle difference between CF 4 and, say, C 2 F 6 system, is by-product formation: CF 4 is
formed when C 2 F 6 is the etchant. CF 4 formation is postulated to be the result of the branching reaction

C 2 F 6 + e - → C 2 F 5 + F + e -

C 2 F 6 + e - → CF 3 + F + e -

where the latter leads to CF 4 formation by recombination of CF 3 and F. It is the exponential increase in these branching reactions that rapidly compli cates the chemistry of etchants like C 3 F 8 , C 4 F 8 , etc. (Sankaran, Vasanov and Kushner, 2002).

Another essential feature of plasma etching is allowance fo r flow stabilization. Patent literature (see, for example, Hudson and Tietz, 2005) and EPA experience (EPA, 2008) indicates plasma etching processes allow for periods of <1 second to a few seconds to assure pressure and flows are stable and uniform prior to striking plasma. Because there is no destruction of fluorinated GHG during this pe riod, which can represent a co nsequential fraction of total process time and, therefore, a substan tial part of total emissions for plasma-etching recipes when fluorinated GHG destruction is high (plasma on), this flow stabilization time is al so an essential feature of a plasma etch recipe and, in turn, included in EPA’s definition of a similar recipe. EPA has demonstrated that because correcting measured emissions for changing recipe time can be made, only stabilization time and not total etching time is relevant when defining similar recipes.

A Precise Definition for Similar R ecipes: Defining the Parameter Space for the Purpose of Estimating and Reporting Emissions

As illustrated in the plasma etching primer, the parame ters that equipment and electronic device manufacturers manipulate to achieve commercially successful plasma et ching recipes are power, reactor pressure, chemical composition, constituent flow rates and flow stabilization tim e. Anecdotal reports indicate that device manufacturers manipulate these parameters for a variety of reasons and in degrees that are unders tandably proprietary when developing the manufacturing process steps for a specific electronic device. These, then, are the parameters EPA considered in formulating a definition for similar recipes.

EPA unsuccessfully searched pu blicly available literature fo r studies that exam ined the influence of variations inthese process parameters on fluorinated GHG emissions. What emerged were studies on how variations in plasmaetch parameters influence manufacturing benchmarks such as etch rate and etch selectivity as well as dimensional control and uniformity across a surface film of an etch feature. EPA did not identify published studies of fluorinated GHG utilization or fluorinated GHG by-product formation, expressed as functions of plasma etching process variables (vide supra). 57

Precisely defining “similar recipe” for plasma etching presents challenges because of the absence of published studies of fluorinated GHG emissions as functions of the required process parameters (vide supra). EPA met this challenge by recognizing the parallel between plasma etching, which selectively removes portions of a film in order to transfer a pattern to a substrate, and plasma cleanin g, which uniformly removes unwanted film that had been previously and unavoidably deposited on chamber walls. In situ plasma chamber cleaning relies on the same physics and chemistry that produ ces precise features (which was described in the previous section) to remove (etch-away)
undesirable silicon-contai ning films from chemical reactor surfaces fo llowing the chemical deposition of films on
substrates.

The practical parallels between plasma patterning and pl asma cleaning are many. Both are driven by entangled productivity and performance objectives. Manufacturing productivity—substrate throughput—means film etch rate is an important benchmark in both substrate patterning and chamber cleaning; manufacturers relentlessly pursue increasing substrate processing rates. Performance—de vice functionality and yield—means feature and defect control are important benchmarks in both substrate patterning and chamber cleaning. Reactor pressures, chemical

57 This is not an argument for manufactures’ ignoring emissions of fluorinated GHGs with high GWPs wh en developing plasma etch processes. Considerable work has been expended in searching for alternative gases and chemistries, with some success (Johnson et al., 2004). While celebrating th ese successes is not the main purpose of this report, the industry’s increasing ado ption
of CH 2 F 2 , C 4 F 6 and C 5 F 8 , each having lower emissions per unit of input gas (alb eit somewhat offset by C

x H y F

z by-product formation) as well as lower GWPs, has lowered CO 2 e emissions compared to alternatives like, for example, CF 4 , CHF 3 and C 2 F 6 (ISMI, 2005).Subpart I Technical Support Document

November 2010 50 composition, flow rate and powe r affect achieving these obj ectives. While reactor pressure s and flow rates differ in plasma etching and plasma cleaning recipe s, the differences can be explained, in large part, by differences in surface area (substrate area being patterned is much smaller, requiring smaller flows, than reactor surface area being cleaned, requiring higher flows) and reactor design (high density, lower pr essure reactors for patterning vs. low density, higher pressure for chamber cleaning). While plasma etch patternin g seeks anisotropy chamber cleaning seeks isotropy; both can be controlled by the addition of oxygen (higher oxygen decreases polymer formation, which improves the efficacy of chamber cleaning and substrate patterning). 58 Both plasma patterning and chamber cleaning recipes also seek to limit ion bombard ment because in plasma patterning io n bombardment reduces selectivity and increases substrate temperature (vide supra) and in chamber cleaning it incr eases the damage to reactor surfaces.

These parallels between plasma cleaning and plasma patternin g together with considerati on of the basic physics and chemistry that govern plasma cleaning and plasma pattern ing, suggest that studies th at provide information on fluorinated GHG emissions when parameters of in situ plasma chamber cleaning reci pes are varied can inform EPA’s considerations about how fluorinated GHG emissions might change were those same parameters varied in plasma etching recipes.

EPA’s search of the publicly available in situ plasma chamber cleaning literature identified three studies with
sufficient information to estimate the effect that chan ges in recipe parameters have on emissions. These were optimization studies in which the authors identified the cond itions (pressure and flow rate for example) that, for the same cleaning time, resulted in lower emissions and usually lower gas usage. The three studies involved different films and three different recipes: C 2 F 6 /O 2 (Daniels and Cheng, 1998), NF 3 (Bing et al., 2003) and C 3 F 8 with O 2 or N 2 O (Kesari et al., 1999). These fluorinat ed GHGs are also used in plasma etching. Changes in emissions were reported in terms of absolute emissions (e.g., kg carbon equivalent, fluorinated GHG utilization, or both).

C

2 F 6 /O 2 : Daniels and Cheng (1998)

It appears Daniels and Cheng (1998) were the first to report optimizing a popular C 2 F 6 /O 2 chamber cleaning process for fluorinated GHG emissions. Their study sought identifi cation of the conditions that would give the lowest C 2 F 6 emissions for the shortest chamber-cleaning time. Daniels and Cheng reported that Applied Materials (AMAT’s) standard process at the time was 600 sscm of C 2 F6 and O 2 , 4 torr reactor pressure and 1000 watts power. By increasing the reactor pressure to 6 torr (a 33 percent increase) and reducing the C 2 F 6 flow rate to 550 sccm (an 8.3 percent decrease) while keeping the C 2 F 6 :O 2 ratio 1, Daniels and Cheng reported a 35 percent reduction in C 2 F 6 emissions and a 5 percent reduc tion in chamber-cleaning time.

Daniels and Cheng provide data that permits estimation of the changes in C 2 F 6 emissions from separate changes in reactor pressure and C 2 F 6 flow rate. The data given Figure D-3 of this appendix, which is adopted from Daniels and Cheng’s Figure 3, shows that a +10 percent change in pressure—from 4 torr to 4.4 torr—results in a 2.3 percent
reduction in C 2 F 6 emissions. Four torr is chosen because it was th e pressure for AMAT’s (b est known) pr ocess (vide supra). Four torr was also the lowest pressure for which Da niel and Cheng reported emissions (Their studies showed that lower pressures would increase em issions and clean times which was count er to their aim.). The authors, however, do provide data for 5 torr. For a 10 percent reduction in pressure (5 torr to 4.5 torr) C 2 F 6 emissions increased 5 percent.

58 Note also that adding oxygen to in situ plasma chamber cleaning recipes decreases the occurrence of particles that can interfere with waste stream management.Subpart I Technical Support Document

November 2010 51

Figure D-3. C 2 F 6 Emissions vs C 2 F 6 Inlet Flow Rate & Pressure at 1:1 Oxygen:C 2 F 6 Ratio (Extracted from Daniels and Cheng, 1998)

A similar analysis for C 2 F 6 flow rates follows from the authors’ data provided in Figure D-3. For a 10 percent
increase in C 2 F 6 flow (from the flow of 600 sccm for the best known method [BKM] to 660 sscm) Daniels and Cheng observed a 4.8 percent increase in C 2 F 6 emissions while a 10 percent decrease in the BKM flow rate produced a 7.9 decrease in C 2 F 6 emissions. The authors did not vary pow er as the BKM chamber cleaning process called for the highest power setting on the AMAT 5200 DCVD Centura.

Other authors (See Sistern et al., 2004 an d references therein) report proces s optimization studies that result in reducing emissions and ch amber-cleaning times for C 2 F 6 /O 2 process (as well as for C 3 F 8 and C 4 F 8 ). However, those studies do not report experimental details. The summary results reported by Sistern et al. (2004) for C 2 F 6 /O 2 chamber cleaning process are very similar if not identical to those reported by Daniels and Cheng (1998). Sistern et al. (2004) use FTIR and QMS methods for quantifying emissions while Daniels and Cheng (1998) used only QMS.

NF 3 : Bing et al. (2003)

Bing et al. (2003) studied optimization of NF 3 in situ PECVD chamber cleaning. Using a design of experiment methodology, Bing et al. observed NF 3 emissions for a range of operating para meters: chamber/reactor pressure (2 – 4 torr), NF 3 flow rate (200 – 350 sccm), and NF 3 fraction in the diluent gas (11.5 – 14.5 mole-percent). Power was fixed at 950 W. Similar to the work of Daniels and Cheng (1998), Bing et al. (2003) showed that, over this range in process parameters, there’s a trad e-off between cleaning times and NF 3 emissions. Shorter cleaning times are economically beneficial because more eq uipment time is available for wafer processing, which cannot occur during chamber cleaning.

Bing et al. (2003) provide results for both emissions (kgCE) and gas utilization (U). Table D-1summarizes their results. The percentage changes in NF 3 emission are given for a range percent change in each process variable that EPA incorporates in its definition of similar recipe. Examination of the information presented in Table D-1 shows that, in general, a change of ± 10 percent around the process variables that define the BKM results in a corresponding change of 10 percent or less in fluorinated GHG emissions.Subpart I Technical Support Document

November 2010 52

Table D-1. Changes in NF 3 emissions (kgCE) and utilization for vari ous indicated changes in parameters for in situ chamber-cleaning process

Variable

Name Nominal value for BKM, except as noted 1 Change, %, except as
noted Emissions, % change in kgCE, except as noted

+10 +3.6 2
Pressure, torr 3
-10 -4.6 2

+10 -4.6 2

NF 3 , mole% 13

-10 +10.1 2

+22 (Faster clean) 0.91 kgCE 3

NF 3 flow, sccm 300 (Balanced) -17 (Lower emissions) 0.29 kgCE 3

Faster clean 0.79 kgCE 4 (-8.1% from balanced) Utilization,
dimensionless 0.86 (Balanced) Lower emissions 0.94 kgCE 4 (+9.3% from balanced)

Notes:

1 BKM denotes best-known method.

2 Values estimated from Fig. 10 of Bing et al. (2003).

3 Values taken from Table 6 of Bing et al. (2003); 0.91 kgCE repr esents an increase of 69 percent in kgCE compared to 0.54 kgCE, what Bing et al. call the balanced process vs. 0.29 kgCE, which represents a decrease of 46 percent in kgCE compared to balanced process (0.54 kgCE).

4 Values taken from Bing et al. (2 003) Table 6. These values denote NF 3 utilization, which Bing et al. call NF 3 destruction efficiency.

C

3 F 8 /O 2 /N 2 O: Kesari et al. (1999)

Kesari et al. (1999) reported results from studies that examined optimization of in situ C 3 F 8 chamber cleaning processes for several kinds of films. These are the only reported results found for the affect of changing O 2 and N 2 O flow on fluorinated GHG utilization (for two film types, ni tride and oxide). Kesari et al. also provide results of CF 4 formation as a function of O 2 flow when cleaning oxide-coated chambers.

The results from Kesari et al. are summarized in Table D-2. It is evident that, for ± 10 percent change in nominal process flow, the corresponding changes in emissions parameters range from 3.3 to 12.8 percent. Kesari et al. did not offer explanations for why C 3 F 8 utilization and CF 4 formation rates decreased when either N 2 O or O 2 flows were increased or why CF 4 product formation decreased, in the case of oxide film removal, when the O 2 flow was increased. The average change in the nominal emission parameter reported by Kesari et al., disregarding the sign, is 8.3 percent for a ± 10 percent changes in O 2 or N 2 O flow rates.

Table D-2. Affect of ± 10 percent changes in O 2 and N 2 O flow rates on C 3 F 8 utilization and CF 4 by-product formation during nitride and oxide in situ plasma chamber cleaning.

Process Process parameter Emission parameter

Name Nominal value Change, % Name Change, %

Nitride film N 2 O flow rate 400 sscm +10 Gas utilization 1 +6.3Subpart I Technical Support Document

November 2010 53 -10 -12.8

+10 -3.3

-10 Gas utilization 2

+3.3

+10 -12 Oxide film O 2 flow rate 450 sscm

-10 CF 4 formation 3

+12

Note 1. Nominal C 3 F 8 utilization for nitride fi lm chamber clean = 0.47
2. Nominal C 3 F 8 utilization for oxide f ilm chamber clean = 0.60
3. Nominal CF 4 formation per clean = 0.25 grams

Each of these studies indicates that changes in pres sure, flow rate and relative chemical composition of ± 10 percent produces changes in emissions of the order of 10 percent. The results of Bing et al. (2003) and of Daniels and Cheng (1998) also shed light on the magnitude of emissions changes from changes in process parameters greater than 10 percent. Their results point to nonlinear relationship between fluorinated GHG emissions and variations in process parameters. The results of Bing et al. (2003), for example, show that substantial reductions in emissions can result from optimizing chamber-cleaning processes. This suggests EPA’s definition of similar recipes should not permit changes in process parameters beyond 10 percent.



### Summary and Conclusions

EPA’s review of plasma etching practices during semiconductor manufacturing revealed both the complexity of dry etching processes and the parameter space that govern to day’s commercial success and fluorinated GHG emissions. EPA’s review also revealed an absence of publicly ava ilable information about the influence of plasma etching process parameters on fluorinated GHG emissions for commercially efficacious plasma etching recipes. This absence, while restricting the scope of EPA’s review, did no t restrict its ability to develop a practical definition for similar recipes. To overcome this information gap and to identify the parameters for a practical definition of similar recipes, EPA used an analogy between (in situ) plas ma etching and in situ plasma chamber cleaning.

EPA’s review confirmed that what infl uences commercial performance of RIE plasma etching processes is power, DC bias, reactor pressure, chem ical composition and flow rate(s). All of th ese parameters except DC bias influence
fluorinated GHG emissions. 59

EPA’s review of three experimental studies of optimizing in situ plasma chamber cleaning showed that changes of the order of 10 percent in reactor pressure, reactant flow rates and relative chemical composition resulted in observed changes in emissions (including emissions of by-products) and gas utilization of the order of 10 percent or less. All of the studies reviewed suggested that chan ging power would influence emissions but none explicitly presented results. The one study (Liu et al. 2000) that reported measuring the influence on power noted, while not reporting specific measurements, that the optimized reci pe conditions “were observed using similar power...as the original manufacturing recipe.” This result suggests that changing power is of lesser importance than changes in other parameters in improving recipe performance. 60

EPA interprets the results of its review as supporting a defi nition of similar recipe provided that definition does not allow for changes in either the chemi cal composition and allows changes in power, reactor pressure, gaseous flow

59 The DC bias contributes to the removal of material via sputtering, which appears to comprise solid particles rather than gaseous particles. In this mann er fluorinated GHG emissions are no t affected by changing DC bias. In certain inst ances if those particles contain carbon, CF 4 might be formed. However, even if this mode for forming CF 4 were occurring in some instances,
CF 4 emissions would not change except in response to a change in DC bias, which appears not be a prevalent practice.
60 Note also that the largest change in power incorporated into the experimental design of Liu et al. (2008) was 10 percent (from 2500 to 2750 watts), which did not evidently, improve chamber cleaning compared to changes in reactor pressure and C 3 F 8 and
O 2 flow rates.Subpart I Technical Support Document

November 2010 54 rates and relative composition of 10 percent or less. Moreover, that definition would not permit change in time for stabilizing gas flows.

It is also worth noting that this definition also applies to in situ chamber cleaning recipes by virtue of the three studies on in situ chamber cleaning presented here. These three studies showed that changes of the order of 10 percent in reactor pressure, reactant fl ow rates and relative chemical composition resulted in observed changes in emissions (including emissions of by-products) and gas utilization of the order of 10 percent or less.



### References

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Booth (1999). Booth, J. Optical and electrical diagnostics of fluorocarbon etching processes , Plasma Sources Science and Technology 8, pp. 249-57, 1999. Available for purchase at: http://iopscience.iop.org/0963- 0252/8/2/005. Contact the EPA Docket Center (EPA docket EPA-HQ-OAR-2009-0927) for more information.

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