This paper explores the practical and cost-effective approaches and techniques to address the environmental impact assessment for air emissions based on the typical chemical use and emission characteristics for semiconductor processes.

1. Modeling Software for EHS Professionals
Applying Appropriate Techniques in
Environmental Impact Assessment for Air
Emissions from Semiconductor Facilities
Prepared By:
Weiping Dai
Sue Sung
Curtis DeVore
BREEZE SOFTWARE 12700
Park Central Drive
Suite 2100
Dallas, TX 75251
+1 (972) 661-8881
breeze-software.com

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Applying Appropriate Techniques in Environmental Impact Assessment
for Air Emissions from Semiconductor Facilities
Weiping Dai, Sue Sung, Curtis DeVore
Trinity Consultants
12801 N. Central Expressway, Suite 1200, Dallas, Texas 75243, U.S.
wdai@trinityconsultants.com
Abstract
Emissions of toxic chemicals from semiconductor
facilities into the ambient air must be carefully evaluated to
ensure protection of human health and the environment. The
emission profile from semiconductor operations is unique in
many aspects. Numerous organic and inorganic chemicals
with different physical and chemical properties (e.g., toxicity,
reactivity, and corrosivity) may be involved in semiconductor
processes and emitted into the atmosphere from stack and
fugitive sources. Moreover, the type and usage of chemicals
may change frequently with the change of processes and
products. As such, assessing the environmental impacts
(health, safety, and welfare) for air emissions from
semiconductor processes requires unique approaches and
techniques in order to provide adequate environmental, health,
and safety protection while obtaining the flexibility required
by the process operations. This paper explores the practical
and cost-effective approaches and techniques to address the
environmental impact assessment for air emissions based on
the typical chemical use and emission characteristics for
semiconductor processes. A multi-tiered approach utilizing
both screening and refined dispersion modeling techniques
will be discussed along with case studies to demonstrate the
practices in the United States (U.S.). Special treatment and
consideration of emissions, source parameters, and chemical
properties (e.g., toxicity) are also studied based on typical air
emission characteristics for semiconductor processes.
Overall, the approaches and techniques discussed in the paper
will demonstrate the best practices in the U.S. to achieve the
objective of protecting the human health and welfare in both
short-term and long-term periods while obtaining the
flexibility in chemical use required by semiconductor
processes.
Introduction
Processes and fabrication technologies in the
semiconductor industry have evolved dramatically since the
first integrated circuit was fabricated in the early 1960s. The
size of silicon wafers has steadily increased. The complexity
of the integrated circuits and the number of transistors in one
chip have kept being pushed toward or even beyond the once-
recognized limits. [1] With the advancement of semiconductor
fabrication technologies, the release of chemicals from
semiconductor processes into the ambient air and other media
poses significant challenges in providing timely and effective
solutions to assess, mitigate, and manage the potential
impacts. Assessing the environmental impacts (health, safety,
and welfare) for air toxics emissions from semiconductor
processes requires unique approaches and techniques in order
to ensure adequate environmental, health, and safety
protection while obtaining the flexibility required by the
process operations.
Air Toxics Emission Profile
A semiconductor process can typically be broken down
into five major steps: design; crystal preparation; wafer
fabrication; final layering and cleaning; and assembly. Each
step may involve various chemicals for processing and
cleaning purposes. The chemicals utilized in semiconductor
processes can be categorized into several groups: inorganic
compounds (e.g., ammonia, hydrochloric acid, and
hydrofluoric acid), volatile organic compounds (VOCs, e.g.,
methanol, trichloroethylene, and toluene) and exempt VOCs
(e.g., acetone, chlorodifluoromethane, and tetrafluoroethane).
The exempt VOCs are a list of compounds that are explicitly
exempted from regulation in the U.S. as VOCs due to their
negligible photochemical reactivity and thus do not contribute
appreciably to ground-level ozone formation. Typical air
toxics emissions from semiconductor processes are shown in
Table 1. [2]
Table 1. Typical Air Toxics Emissions
from Semiconductor Processes
Process Air Emissions
Crystal Preparation Acid fumes, VOCs, and
dopant gases
Wafer Fabrication VOCs and dopant gases
Final Layering and
Cleaning
Acid fumes and VOCs
Assembly VOCs
In the U.S., industrial facilities (including semiconductor
facilities) meeting certain criteria are required by regulations
to report the emissions and transfers of a list of regulated toxic
chemicals to the U.S. Environmental Protection Agency (U.S.
EPA). The reported data are stored in the Toxic Release
Inventory (TRI) database. Table 2 documents the major air
emissions (greater than 1 ton per year) of toxic chemicals
reported by the electronics/computer facilities (including
semiconductor facilities) in 2001. Although the data is not
exclusive for semiconductor facilities, the chemical profile
and relative emissions are representative for semiconductor
facilities.
Overall, chemical use and associated emissions from
semiconductor processes include the following characteristics:
first, a large number of chemicals are used in various steps of

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Quantify Air Toxics Emissions
and Release Conditions
Model Transport and Dispersion
of Air Emissions
Determine Maximum Ground-
level Concentrations or Risk
Conc. or Risk
Acceptable?
Assessment
Completed
Yes
No
Reduce
Conc.
Or Risk
a process; second, the use of specific chemicals depends on
the products and process techniques involved and thus may
change frequently; third, new chemicals may be used as new
products or processes are evolved.
Table 2. 2001 Air Toxics Emissions (Tons per Year)
Reported by Electronics/Computer Facilities in the U.S.
Chemical Fugitive Stack Total
AMMONIA 114.7 150.0 264.7
GLYCOL ETHERS 31.7 67.1 98.8
TOLUENE 19.3 53.8 73.1
METHANOL 18.5 52.4 70.9
TRICHLOROETHYLENE 12.4 57.7 70.1
N-METHYL-2-PYRROLIDONE 11.2 49.2 60.4
HYDROGEN FLUORIDE 1.9 53.1 55.0
TETRACHLOROETHYLENE 7.4 45.8 53.2
DICHLOROMETHANE 2.8 47.6 50.4
NITRIC ACID 5.3 44.8 50.1
N,N-DIMETHYLFORMAMIDE 20.3 29.6 49.9
HYDROCHLORIC ACID 1.9 41.6 43.5
METHYL ETHYL KETONE 7.3 35.2 42.5
SULFURIC ACID 5.5 20.9 26.4
XYLENE (MIXED ISOMERS) 6.4 19.2 25.6
OZONE 0.0 24.7 24.7
STYRENE 1.3 18.9 20.2
METHYL ISOBUTYL KETONE 7.2 11.2 18.4
ETHYLENE GLYCOL 3.3 14.2 17.5
2-METHOXYETHANOL 1.9 5.1 7.0
CHLORINE 0.1 5.8 5.9
COPPER COMPOUNDS 1.9 3.0 4.9
CHLOROBENZENE 0.0 4.2 4.2
FORMALDEHYDE 1.3 2.7 4.0
ETHYLBENZENE 0.4 2.3 2.7
LEAD COMPOUNDS 0.0 2.1 2.1
ZINC COMPOUNDS 0.3 1.8 2.1
1,1-DICHLORO-1-FLUOROETHANE 1.9 0.0 1.9
BARIUM COMPOUNDS 0.5 0.9 1.4
CYANIDE COMPOUNDS 0.0 1.3 1.3
1,2-DICHLOROBENZENE 0.1 1.1 1.2
COPPER 0.3 0.8 1.1
Impact Assessment for Air Emissions
The air emissions of chemicals involved in the
semiconductor processes must be addressed to ensure there
are no potential adverse impacts on human health, safety, or
other environmental welfare due to both short-term and long-
term exposures. Oftentimes, such emission activities are
subject to regulatory requirements to evaluate the potential
environmental impacts and establish allowable emission
limits. Potential impacts due to air toxics emissions are
typically evaluated through steps shown in Figure 1.
Figure 1. Typical Steps in Impact Assessment
due to Air Toxics Emissions
As shown in Figure 1, the potential impacts due to the air
toxics emissions could be evaluated with the modeled ground-
level concentrations or the health risk derived from the
modeled concentrations and the exposure pathways. Both
approaches have been utilized in the U.S. and an impact
analysis is typically only performed for offsite receptors. For
example, the State of Texas implements a Health Effects
Evaluation program by establishing short-term (1- hour for
most of the chemicals) and long-term (annual) threshold
concentrations called “Effects Screening Levels” (ESLs) for
each air toxic based on its toxicity and other
physical/chemical properties. The ESLs are set to prevent
acute and chronic health effects and nuisance effects (e.g.,
odor) on the general population as well as the environmental
welfare (e.g., vegetative damage and corrosion) but are not
considered as air quality standards. [3] For each chemical of
interest, the modeled maximum ground-level concentrations
in the modeling domain or at receptors of interest (e.g.,
residential areas, schools, and hospitals) are compared with
the corresponding ESLs to determine whether the impacts are
acceptable. In the State of California, the Health Risk
Assessment (HRA) approach is adopted in the Air Toxics
“Hot Spots” program. Health risks (e.g., cancer risk and non-
cancer acute/chronic hazards) due to multi-pathway exposures
(e.g., inhalation, ingestion, dermal exposure) are quantified
based on modeled ground-level concentrations or deposition
fluxes for all regulated toxic chemicals emitted from a
stationary source (e.g., a semiconductor facility). The
calculated risks are compared against the risk thresholds (e.g.,
one per one million cancer risk for 70-year exposure)

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established by the Air Quality Management Districts
(AQMDs) for potential further requirements (e.g., public
notification and risk reduction). [4] Regardless whether the
concentration or risk approach is used, the techniques for
quantifying air toxics emissions and simulating the
atmospheric dispersion should be similar. In this paper, the
case study will be based on the Texas ESL concentration
approach.
Dispersion Model Selection
Air dispersion models are used to simulate the transport
and dispersion of plumes containing the air toxics emitted
from various sources (e.g., air toxics emissions from
semiconductor facilities). There are many dispersion models
in the public domain that were developed or sponsored by the
U.S. EPA and other agencies. In the U.S., common
dispersion models used in the near-field (less than 50 km from
the emission sources) air quality impact analyses for
emissions from industrial activities include SCREEN3,
ISCST3, ISC-PRIME, and AERMOD.
SCREEN3 is a Gaussian model to predict potential
impacts for a single emission source based on a set of
conservative screening procedures developed by the U.S.
EPA. SCREEN3 utilizes a single meteorological condition or
an array of combinations of various meteorological
conditions. [5] ISCST3 (Industrial Source Complex Short
Term Version 3) is a Gaussian dispersion model. It has been
the U.S. EPA preferred model for various regulatory
applications for more than two decades. It can be used to
perform a dispersion modeling analysis for multiple emission
sources in simple or complex terrains. Other model options
such as stack-tip downwash, building downwash, calm wind
processing, dry/wet deposition, and chemical decay are also
available. [6] ISC-PRIME is a special version of ISCST3
with the Plume RIse Model Enhancements (PRIME) Module.
The PRIME module incorporates two fundamental features
associated with building downwash: the enhanced plume
dispersion coefficients due to the turbulent wake, and the
reduced plume rise caused by a combination of the
descending streamlines in the lee of the building and the
increased entrainment in the wake. ISC-PRIME is preferred
when building downwash effects are expected to be
significant. Moreover, ISC-PRIME can calculate the ambient
air concentrations for receptors inside the downwash cavity
region while ISCST3 cannot perform such an evaluation. [7]
AERMOD is the new generation dispersion model designed
to replace ISCST3 in the near future as the U.S. EPA
preferred model. It reflects the state-of-science of the
planetary boundary layer theories in the regulatory dispersion
model. The current available version of AERMOD also
incorporates the PRIME module for better handling of
building downwash effects. [8]
Selecting an appropriate dispersion model for an impact
assessment is critical to correctly model the plume behavior in
the atmosphere and thus render representative predicted
concentrations. The selection of a dispersion model for a
specific application is typically the outcome of considering
many relevant factors: the scientific merits of the model under
certain circumstances, the related regulatory requirements, the
emission source conditions, and other characteristics in the
modeling domain (e.g., terrain, land use, and other
geophysical features). For example, since the AERMOD
model is not yet the official U.S. EPA preferred model, its
application to fulfill certain regulatory requirements has been
based on a case-by-case justification and vary from state to
state. For impact assessments of air toxics emissions, ISCST3
is still the workhorse while ISC-PRIME is better suited when
building downwash effects on the plume dispersion are
significant. The air toxics emissions from semiconductor
facilities typically occur through relatively short vent stacks
located on the rooftop of the fabrication building. The
building downwash effects are often expected to be
significant and oftentimes there are offsite receptors located in
the cavity region. Therefore, while most of the dispersion
models could be used for air emissions impact assessments,
ISC-PRIME could be a more appropriate dispersion model for
emissions from semiconductor facilities.
Multi-Tiered Modeling Approach
As discussed previously, there are typically a large
number of chemicals emitted from a semiconductor facility
into the atmosphere. Performing a modeling analysis for
emissions of each individual chemical would be time-
consuming and inefficient. On the contrary, a multi-tiered
modeling approach is effective and appropriate to ensure the
assessment will be protective of the health, safety, and welfare
while streamlining the analysis process. In this approach, 3
tiers, each one with a higher degree of refinement than the
previous, could be used in assessing the potential impacts of
the air toxics emissions. Only chemicals whose potential
impacts do not pass at the current tier will go to the next tier
for further analyses. In general, this multi-tiered approach
could apply to the impact assessments utilizing either the
concentration-based approach or the risk-based approach. In
fact, the same or similar techniques discussed in this paper
have been utilized in the Texas State Health Effects
Evaluation. [9]
Tier 1 Analysis – Conservative Screening Evaluation
The purpose of the Tier 1 analysis is to screen out the air
toxics that have acceptable impacts even with conservative
assumptions. It is a conservative screening step used to
reduce the number of air toxics that may require individual
refined modeling analysis (Tier 2). In the Tier 1 analysis, one
generic dispersion model run including all emission sources to
be evaluated is set up with a unit emission rate (e.g., one
pound per hour or one gram per second) for each source. This
generic model run will generate the ground-level
concentrations of applicable averaging periods (e.g., short-
term or long-term) for each source, individually, at all
modeled receptors. The modeled concentration averaging
periods in the Tier 1 analysis could be any averaging periods
that are available in the dispersion model and match the
averaging periods associated with the corresponding threshold
values. Note that the emission rates used in the analysis
should also reflect the corresponding averaging periods (e.g.,
annual emission rates for long-term impact evaluation and
short-term emission rates for short-term impact evaluation).

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However, different averaging periods may be required for
different chemicals. For example, while most of the short-
term ESLs for the Texas Health Effects Evaluation are based
on a 1-hour average, some chemicals have short-term
averaging periods other than 1-hour (e.g., 3-hour average for
hydrogen fluoride). To simplify the analysis, the Tier 1
generic run could be set up only for the 1-hour average and
the modeled hourly concentrations will be converted to other
averaging periods by utilizing the screening conversion
factors established by the U.S. EPA. For example, the hourly
concentration can be converted to an annual concentration by
multiplying by a conversion factor of 0.08. [5]
The potential maximum impact of a chemical emitted from
an individual source will be the product of the modeled
maximum concentration (in terms of “airborne concentration
per unit emission rate”) generated from the generic model run
for that source multiplied by the emission rate (in the same
unit as the unit emission rate used in the generic model run)
for that chemical emitted from the corresponding source. The
sum of the maximum potential impact (regardless of the time
and location associated with the impact) for each chemical
from all modeled sources is then compared to the
corresponding threshold concentration (e.g., the short-term
ESL). The Tier 1 analysis is a conservative procedure since
the maximum impact from all sources modeled concurrently
cannot be more than the sum of the maximum impact for each
source modeled separately. Therefore, if the total maximum
impact for a chemical obtained from the Tier 1 analysis is less
than the corresponding threshold value, it can be concluded
that the worst potential impact due to the modeled emissions
of that chemical will be smaller than the threshold value and
thus no further analysis would be required for that chemical.
Typically, the Tier 1 analysis will provide satisfactory results
for most of the air toxics emitted from a semiconductor
fabrication facility.
Overall, there are many advantages of performing the Tier
1 analysis. First, the Tier 1 analysis requires only one generic
model run and thus reduces the burden and cost of performing
a dispersion modeling analysis for each chemical. Second,
since the generic run uses a unit emission rate for each
emission source, any update to the emission rates will not
require re-modeling. Third, a spreadsheet tool can be
developed to manage the information of the emission sources,
emission rates, Tier 1 modeled concentrations, and toxicity
threshold values. This spreadsheet tool can also be used to
quickly evaluate the potential impacts due to emission
changes for both existing and new chemicals without
performing a new dispersion modeling analysis.
Tier 2 Analysis – Refined Modeling Evaluation
For chemicals whose potential impacts in the Tier 1
analysis are higher than their threshold values, a Tier 2
analysis is performed with a refined modeling approach. In a
Tier 2 analysis, at least one dispersion model run will be
required for each chemical (sometimes it is necessary to
perform different model runs with different emission rates for
different averaging periods). Each dispersion model run will
use the emission rates for all sources emitting the chemical of
interest. With such an approach, the modeled ground-level
concentration for the modeled period at each receptor will
reflect the contribution from each source corresponding to its
emission rate of that chemical and the plume dispersion
associated with the meteorological conditions. Therefore, for
a chemical emitted by multiple emission sources, the Tier 2
analysis will account for the temporal and spatial contribution
of each source during its plume dispersion and thus will be
expected to generate a maximum concentration that should be
less than that obtained in the Tier 1 analysis. If a Tier 2
analysis produces the maximum impact for emissions of a
chemical that is less than the applicable threshold value, no
further analysis will be necessary for that chemical.
Otherwise, a Tier 3 analysis to develop case-by-case
justifications shall be performed.
Tier 3 Analysis – Case-by-Case Considerations
For chemicals whose potential impacts in the Tier 2
analysis are higher than their threshold values, case-by-case
considerations could be developed to justify whether an
emission reduction is necessary or how such a reduction
should be prioritized. The following typical aspects should be
considered:
• The magnitude of the maximum impact compared to
the applicable threshold value.
• The frequency of occurrences exceeding the applicable
threshold value.
• The locations and extent of the potential exceedances.
(e.g., residential area, industrial/commercial area, or
unpopulated area).
• The margin of safety considered when the applicable
threshold values were developed.
• The extremity of certain meteorological conditions that
cause the potential exceedances.
Source Grouping Technique
Source grouping is a technique to evaluate the collective
impacts of a number of emission sources by grouping them
together. There are two ways for emission sources to be
grouped: (1) Grouping with a representative emission stack: a
group of stacks that are located relatively close to each other
and possess similar stack characteristics and emission profiles
are represented with one conservative stack. (2) Grouping
within a dispersion model run. Details of both grouping
methods are discussed below.
Representative Stack Grouping
The technique to identify a representative emission stack
for a group of emission sources is described in a U.S. EPA
guidance document. [5] The same technique is also
recognized in the Texas Health Effects Evaluation. [9] The
sources to be grouped should satisfy the following criteria:
• The sources emit one or more common chemicals.
• The sources should have similar stack parameters (i.e.,
stack diameter, stack height and elevation, volumetric
flow rate or exit velocity, and exit temperature).
• The sources should be located close to each other (e.g.,
within about 100 meters distance)

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Deviations from the above criteria (e.g., greater than 20%
difference for certain stack parameters) may result in
unrepresentative modeling concentrations. The representative
stack (i.e., worst-case stack) for the merged sources could be
determined with the “M-method”:
Q
TVh
M ss ⋅⋅
=
Where: M = merged stack parameter which accounts for
the relative influence of stack height, plume rise, and emission
rate on concentrations; hs = physical stack height in meters; V
= stack gas flow rate in cubic meters per second; Ts = stack
gas exit temperature in Kelvin; and Q = pollutant emission
rate in grams per second. In the grouping procedure, an “M”
value will be calculated for each source in a group of emission
sources. The stack that has the lowest “M” value is used as a
"representative" stack whose parameters would be used in the
modeling analysis. The emission rate of an emitted chemical
for the merged group should be the total emission rate of that
chemical from all emission sources in the group. For
emission sources with the same “M” value, source locations
relative to the property line or receptors of interest should be
taken into account to determine the representative stack that
would produce conservative modeling results.
Grouping within the Model Run
With this grouping technique, a number of individual
emission sources satisfying the same criteria as discussed for
the representative stack grouping technique are grouped
together in a dispersion model run to report their collective
impacts from the modeling analysis. Each individual source
is present in the model run with its own modeling parameters
(e.g., location, emission rate, stack parameters, and building
downwash dimensions) before the grouping. This technique
makes use of the “source group” option implemented in the
ISCST3, ISC-PRIME, or AERMOD dispersion models.
Utilization of the Grouping Techniques
Utilizing the grouping techniques discussed above can
provide several benefits. First, source grouping can provide
the flexibility in allocating emissions within the same group of
emission sources. In the U.S., air emission sources are
typically subject to the regulatory emission limits established
through emissions quantification and consideration of
operating characteristics (e.g., throughput) and pattern (e.g.,
continuous operation vs. batch operation). Since the
modeling concentrations based on the source grouping are
expected to be conservatively representative, the regulatory
agency with the authority to review and approve the allowable
emissions in a permit application would tend to accept the
approach of assigning one emission limit for a merged stack
group (rather than an emission limit for each individual stack).
This would result in the flexibility to change emission rates at
stacks within the group so long as the total emission rate for
the group is not exceeded. Second, grouping with a
representative source stack can reduce the number of sources
to be included in the dispersion modeling analysis and thus
simplify the processing of modeling input files and output
results.
For semiconductor fabrication facilities, there are typically
multiple emission sources located as a cluster of stacks on the
fabrication building rooftop with similar release
characteristics and emission profiles - for example, inorganics
emissions from scrubber stacks for the oxidation process,
etching, photoresist stripping, doping, layering (epitaxial
growth, sputtering, or chemical vapor deposition), and wet
chemical stations; and organics emissions from thermal
oxidizer stacks for solvent stations in coating application,
cleaning, photoresist exposure and development, doping,
layering, and tool/fab wipe cleaning.
Flexibility in Chemical Changes
Semiconductor fabrication involves many chemicals for
processing and cleaning purposes. As products and processes
change, the usage amount of existing chemicals may need to
be increased or new chemicals may need to be used. As such,
it is critical for semiconductor facilities to gain the flexibility
in chemical changes through the utilization of conservative
assumptions or techniques in the course of evaluating the
potential impacts. More importantly, it is desirable to obtain
such flexibility without the need to amend the existing permit
or obtain approval from the regulatory agency. In Texas,
several ratio tests (with certain exceptions) are recognized by
the regulatory agency to obtain the flexibility in chemical
changes for industrial processes such as semiconductor
fabrication. [10] Several change scenarios and related ratio
tests are discussed below. In essence, the emission changes
due to the chemical changes in processes must be evaluated
for the affected emission sources to demonstrate no potential
adverse impacts. Further impact analysis may be required if
the changes cannot pass the applicable tests.
Substitution of a Single Chemical
The facility can substitute a single chemical with another
if the following ratio test is satisfied:
1
1
2
2
ESL
ER
ESL
ER
≤
Where: ER2 = emission rate of the new chemical; ESL2 =
toxic threshold value of the new chemical; ER1 = emission
rate of the existing chemical to be substituted; ESL1 = toxic
threshold value of the existing chemical to be substituted.
Substitution of Multiple Chemicals
The facility can substitute multiple chemicals if the
following ratio test is satisfied:
n
n
a
a
n
n
a
a
ESL
ER
ESL
ER
ESL
ER
ESL
ER
1
1
1
1
2
2
2
2
...... ++≤++
Where: ER2a through ER2n = emission rates of the new
chemicals; ESL2a through ESL2n = toxic threshold values of
the new chemicals; ER1a through ER1n = emission rates of the
existing chemicals to be substituted; ESL1a through ESL1n =
toxic threshold values of the existing chemicals to be
substituted.

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Increases of Chemical Usage
When the usage of an existing chemical in the facility is
increased and thus the emission of that chemical is increased
subsequently, the facility is typically required to obtain
authorization from the regulatory agency before such change
can be made. The following test could be performed to
determine if further impact analysis (e.g., site-wide impact
analysis) is necessary:
totalinc
inc
ER
ESL
ER
GLC
≤
max,
Where GLCmax,inc = maximum impact due to the emission
increase; ERinc = emission increase; ESL = toxic threshold
value associated with the chemical of interest; ERtotal = total
site-wide emission of the chemical of interest (including
ERinc). This test is to determine if the total impacts after the
change could potentially be acceptable by assuming that the
new emissions disperse in a similar manner as the existing
emissions.
No Adverse Impact due to Chemical Substitution
Regulatory agencies would expect that no adverse impact
would result due to chemical substitution if the following test
is satisfied:
newnew ESLGLCER ≤⋅ max
Where: ERnew = emission rate of the new chemical;
GLCmax = maximum impact per unit emission rate; ESLnew =
toxic threshold value of the new chemical. Note that this test
should be performed for all applicable averaging periods
associated with the chemical. As discussed in the Tier 1
analysis, this test can be performed with the developed
screening spreadsheet without performing a new modeling
analysis.
Case Study
The following case study is developed based on the 1993
air emissions reported in the TRI database by semiconductor
manufacturing facilities (SIC 3674). Air emissions of various
toxic chemicals were reported as fugitive or point (stack)
emissions. For simplification purposes, in this case study, all
air emissions are assumed to be emitted from point sources
continuously. The TRI data was converted to “pounds per
hour per facility” based on the “pounds per year” and
“number of reported facilities” in the TRI database. Table 3
presents the 1993 air emissions for the reported 25 toxic
chemicals that were included in this case study. These
emissions are assumed to be for a fictional semiconductor
facility with one fabrication building (200-m length × 200-m
width × 20-m height) in an urban area of Austin, Texas. The
emission stacks are located on the roof of the fab building.
Organics emissions are equally distributed to five organics
stacks and inorganics emissions are equally distributed to five
inorganics stacks. All emission stacks are assumed to have
the following parameter values: 1.5-m stack diameter, 1-m
height above the building rooftop, 5 m/s exit velocity, and 20
°C exit temperature. The layout of the fab building and the
emission sources is illustrated in Figure 2.
Table 3. 1993 Air Toxics Emissions Reported by
Semiconductor Facilities in the U.S.
Chemical No. of
Reported
Facilities
Total
Emissions
(tons/yr)
Emission per
Facility
(lbs/yr/fac.)
1,2-Dichlorobenzene 2 24.7 2.820
Methyl Ethyl Ketone 6 64.8 2.466
Toluene 3 29.4 2.237
Acetone 53 506.0 2.180
Tetrachloroethylene 4 27.8 1.587
Trichloroethylene 3 18.0 1.370
Freon 113 10 57.3 1.308
Xylene (Mixed Isomers) 25 131.3 1.199
1,1,1-Trichloroethane 8 42.0 1.199
Methanol 16 83.3 1.189
Glycol Ethers 27 127.1 1.075
Methyl Isobutyl Ketone 2 5.0 0.571
1,2,4-Trichlorobenzene 2 3.3 0.377
Phenol 3 1.4 0.107
Ethylbenzene 2 0.7 0.080
Ethylene Glycol 16 5.5 0.079
P-Xylene 1 0.2 0.046
N-Butyl Alcohol 1 0.1 0.023
Ammonia 42 72.2 0.392
Hydrochloric Acid 78 38.8 0.113
Nitric Acid 57 26.5 0.106
Hydrogen Fluoride 71 30.2 0.097
Sulfuric Acid 125 50.9 0.093
Phosphoric Acid 69 14.9 0.049
Ammonium Sulfate 3 0.1 0.008
* 1 ton = 2,000 pounds (lbs)
Figure 2. Layout of Fab Building and Emission Sources
North
Property Line
FAB Building
Organics Stacks
Inorganics Stacks

8. SEMICON®
China 2005
©SEMI 2005
Since the facility is located in Texas, it may be subject to
the Texas Health Effects Evaluation. In this case study, the
ISC-PRIME air dispersion model is used to perform the
analysis using the multi-tiered approach. A receptor grid
consisting of 100-meter spaced receptors is placed along the
facility property line and the surrounding area up to 2
kilometers from the property line on each direction to ensure
the capturing of the maximum impact. One-year of
meteorological data was modeled and the associated wind
rose plot is shown in Figure 3. A wind rose plot illustrates the
frequency of ranges of wind speed at an array of wind
directions. The wind direction represents the direction from
which the wind is blowing. A wind rose plot is useful to
evaluate the prevailing wind speed and direction that affect
the plume dispersion. Results and findings of the impact
analysis for the case study are discussed in the following
sections.
Figure 3. Wind Rose Plot for the Meteorological
Data Used in the Modeling Analysis
Results and Discussions of Tier 1 Analysis
In the Tier 1 analysis of this case study, each stack source
was modeled with a unit emission rate of 1 lb/hr. No source
grouping was applied to the analysis. The generic model run
was set up to generate hourly concentrations and a conversion
factor of 0.08 was used to convert the hourly concentration to
the annual concentration in order to evaluate the long-term
impacts.
The Tier 1 analysis results are documented in Table 4 for
the short-term impacts and in Table 5 for the long-term (i.e.,
annual) impacts. The Tier 1 results show that the impacts of
all chemicals (except hydrochloric acid) do not exceed the
corresponding ESLs. The long-term impact of hydrochloric
acid is above the applicable ESL and thus a Tier 2 analysis is
required for this chemical. Hydrochloric acid is generally
regarded as a chemical that requires refined evaluation
techniques.
Table 4. Tier 1 Analysis Results for Short-term Impact
Chemical Tier 1
Impact
(µg/m3
)
Short-term
ESL
(µg/m3
)
Impact Less
Than ESL?
(Yes/No)
1,2-Dichlorobenzene 31.4 600 Yes
Methyl Ethyl Ketone 27.4 3900 Yes
Toluene 24.9 1880 Yes
Acetone 24.2 5900 Yes
Tetrachloroethylene 17.6 340 Yes
Trichloroethylene 15.2 1350 Yes
Freon 113 14.5 38000 Yes
Xylene (Mixed Isomers) 13.3 3700 Yes
1,1,1-Trichloroethane 13.3 10800 Yes
Methanol 13.2 2620 Yes
Glycol Ethers 12.0 600 Yes
Methyl Isobutyl Ketone 6.4 2050 Yes
1,2,4-Trichlorobenzene 4.2 400 Yes
Phenol 1.2 150 Yes
Ethylbenzene 0.9 2000 Yes
Ethylene Glycol 0.9 260 Yes
P-Xylene 0.5 2080 Yes
N-Butyl Alcohol 0.3 610 Yes
Ammonia 4.8 170 Yes
Hydrochloric Acid 1.4 75 Yes
Nitric Acid 1.3 50 Yes
Hydrogen Fluoride 1.2 5 Yes
Sulfuric Acid 1.1 50 Yes
Phosphoric Acid 0.6 10 Yes
Ammonium Sulfate 0.1 50 Yes
Table 5. Tier 1 Analysis Results for Long-term Impact
Chemical Tier 1
Impact
(µg/m3
)
Long-term
ESL
(µg/m3
)
Impact Less
Than ESL?
(Yes/No)
1,2-Dichlorobenzene 2.51 60 Yes
Methyl Ethyl Ketone 2.19 390 Yes
Toluene 1.99 188 Yes
Acetone 1.94 590 Yes
Tetrachloroethylene 1.41 34 Yes
Trichloroethylene 1.22 135 Yes
Freon 113 1.16 3800 Yes
Xylene (Mixed Isomers) 1.07 370 Yes
1,1,1-Trichloroethane 1.07 1080 Yes
Methanol 1.06 262 Yes
Glycol Ethers 0.96 60 Yes
Methyl Isobutyl Ketone 0.51 205 Yes
1,2,4-Trichlorobenzene 0.34 40 Yes
Phenol 0.10 15 Yes
Ethylbenzene 0.07 200 Yes
Ethylene Glycol 0.07 26 Yes
P-Xylene 0.04 208 Yes
N-Butyl Alcohol 0.02 61 Yes
Ammonia 0.38 17 Yes
Hydrochloric Acid 0.11 0.1 No
Nitric Acid 0.10 5 Yes
Hydrogen Fluoride 0.10 0.5 Yes
Sulfuric Acid NA NA NA
Phosphoric Acid 0.05 1 Yes
Ammonium Sulfate 0.01 5 Yes

9. SEMICON®
China 2005
©SEMI 2005
This case study clearly demonstrates the benefits of the
Tier 1 analysis. Instead of performing dispersion modeling
analysis for each chemical (25 model runs in this case), the
Tier 1 screening analysis with one generic model run can
dramatically reduce the number of chemicals required for
further analysis (only one chemical in this case).
Results and Discussions of Tier 2 Analysis
A refined dispersion modeling analysis was performed for
hydrochloric acid to evaluate its long-term impact. In this
case study, the hydrochloric acid emission rate for each source
was used in the refined model run. The Tier 2 modeling
results show that the maximum annual impact is 0.08 µg/m3
,
which is less than the annual ESL of 0.1 µg/m3
. Therefore, no
Tier 3 analysis is necessary for this case study. The
concentration contour plot showing the hydrochloric acid
impact is presented in Figure 4. Comparing the contour plot
with the wind rose plot shows that the high impact area is
consistent with the prevailing wind direction.
Figure 4. Contour Plot of Hydrochloric Acid Annual Impact
Evaluation of Source Grouping Effects
In this case study, the source grouping effects for the Tier
1 analysis are evaluated with 1,2-Dichlorobenzene (emitted
from the organic stacks) as an example. Table 6 presents the
potential impacts with or without applying the source
grouping techniques.
Table 6. Evaluation of Source Grouping Effects
Scenario Short-term Impact (µg/m3
)
Without Source Grouping 31.4
Grouping with Representative Stack 33.7
Grouping within the Model Run 25.7
As expected, grouping with a representative stack (i.e.,
worst-case stack) produces the highest impact. Applying such
a technique is generally acceptable to regulatory agencies. It
is interesting to note that grouping similar sources (e.g.,
organics stacks in this case study) within the model run
produces a lower impact than the scenario without applying
the grouping technique (as in the Tier 1 analysis of the case
study). This is because the Tier 1 analysis reflects the
conservative result (i.e., maximum concentration) for each
modeled source or source group. Without grouping, such
conservatism in the Tier 1 analysis comes from each
individual source. However, with grouping, the conservatism
in the Tier 1 analysis only comes from each source group,
whose maximum impact cannot be greater than the sum of the
maximum impact (regardless of time and location) for each
individual source in the group. Therefore, prudence should be
taken when utilizing the grouping within a model run
technique in the Tier 1 analysis. This technique should be
acceptable (with reasonable conservatism) when each source
in the group is expected to have similar impact. Otherwise,
such grouping technique may distort the potential impacts for
certain stacks in the group under certain circumstances.
Conclusions
Semiconductor fabrication processes may potentially emit
a large number of toxic chemicals into the ambient air, which
need to be evaluated to protect public health and welfare and
the environment. Utilizing a multi-tiered approach is
demonstrated to be effective in performing the impact
assessment for the air toxics emissions from semiconductor
facilities. Such an approach could significantly reduce the
initial level of effort for the impact assessment. Moreover, the
results from the Tier 1 analysis can be incorporated into a
useful tool to evaluate future emission changes without
performing a new dispersion modeling analysis.
Moreover, semiconductor operations typically require the
flexibility to change the chemical usage due to the frequent
changes in processes and products. Applying the grouping
techniques and applicable ratio tests discussed in this paper
can help to gain the desired flexibility in chemical changes
and emission limits while ensuring the protection of human
health, safety, and welfare.
References
[1] R. C. Jaeger, “Introduction to Microelectronic
Fabrication (2nd
Edition)”, 2002, Prentice Hall.
[2] U.S. EPA, “Profile of the Electronics and Computer
Industry”, EPA/310-R-95-002, September 1995.
[3] Z. M. Post, M. E. Honeycutt, J. T. McCoy, L. C.
Carlisle, and J. M. Wiersema, “Letter to the Editor: Texas
Effects Screening Levels Based on Sound Science”, J.
Clean Technol., Environ. Toxicol., & Occup. Med., Vol 7,
No. 1, 1998, pp 107 – 111.
[4] Office of Environmental Health Hazard Assessment,
Caifornia Environmental Protection Agency, “Air Toxics
Hot Spots Program Guidance Manual for Preparation of
Health Risk Assessment”, August 2003.

10. SEMICON®
China 2005
©SEMI 2005
[5] U.S. EPA, “Screening Procedures for Estimating the
Air Quality Impact of Stationary Sources (Revised)”,
EPA-454/R-92-019, October 1992.
[6] U.S. EPA, “User’s Guide for the Industrial Source
Complex (ISC3) Dispersion Models, Volume 1 – User
Instruction”, EPA-454/B-95-003a, September 1995.
[7] Electric Power Research Institute, “Addendum to
ISC3 User’s Guide: The Prime Plume Rise and Building
Downwash Model”, November 1997.
[8] A. J. Cimorelli et al, “AERMOD: Description of
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002d, October 31, 2002.
[9] Texas Commission on Environmental Quality, “Air
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February 1999.
[10] Texas Commission on Environmental Quality,
“Modeling and Effects Review Applicability: How to
Determine the Scope of Modeling and Effects Review for
Air Permits”, RG-324, October 2001.