FLAT F ILE GENERATION METHODOLOGY

Version : EPA Base Case v.5.1 4 July

, 201 5

Content

SECTION I: INTRODUCTION

SECTION II: DATA SOURCES AND DESCRIPTIONS

SECTION III: DETAILED DATA PROCESSING

SECTION IV: FLAT FILE LAYOUT Appendix A : Default Values Appendix B: Temporal allocation of IPM emissions to hourly emissions for use in air quality modeling

Attachment: Flat File Inputs2 SECTION I: INTRODUCTION

This document provides the flat file generation methodology for EPA Base Case v.5.1 4

. The methodology takes

EPA Base Case v.5.1 4 using Integrated Planning Model (IPM ® ) run results (parsed outputs) and generates the

formatted flat file that the U.S. Environmental Protection Agency (U. S. EPA) uses as inp ut into air quality modeling framework. Section II provides data descriptions and sources . Section III describes data processing

steps in detail . S ection I V describes the layout of the formatted flat file.

SECTION II: DATA SOURCES AND DESCRIPTIONS

IPM run results that have been disaggregated in to the unit, emission control technology and fuel type are the key input

. The se results include records of fossil

- fired existing and retrofit units, along with committed and new

- build
aggregates. All fossil and biomass fired units are inc luded in the resultant formatted flat file as needed for air quality modeling inputs. Other non fossil plant types that are part of the EPA Base Case v.5.1 4 modeled results (nuclear, hydro, wind, solar PV, solar thermal, geot hermal, landfill gas, non

- fossil waste, municipal solid waste, fuel cell, tires and pumped storage) are not included in the flat file

.

The committed and new

- build aggregates are hereafter referred to as “generic” aggregates. All records contain

the follo wing :

1. Population characteristics including state FIPS codes, county FIPS codes, recognized ORIS codes (<80000) and unit ID s for existing and retrofit units. Generic aggregates have state level information only

. 2. Sulfur dioxide ( SO 2 )

, nitrogen oxides ( NO
x ) , and particulate matter (PM) control information for existing

and retrofit units as well as generic aggregates

. 3. Annual and seasonal heat input (TBtu).

4. Heat content s (MMBtu/ton, k

- gallon, MMcf) and SO 2 and ash contents (lb/MMBtu).

5. Annual and summer NO
x em issions (MTon)

, annual SO 2 emission s (MTon)

, HCL emissions (MTon), and

m ercury emission s (Ton).

Table 1 provides the rest of the input data’s descriptions, sources and file locations. The FlatFile_Inputs spreadsheet is included as an attachment to this documentation. The spreadsheet contains large amount of data including NEEDS v.5.14 plant’s state F IPS code, county FIPS code, county’s most recent 8 hour ozone

or PM2.5 attainment/non

- attainment status, ORIS code, latitude

- longitude coordinates, zip code, Emission Inventory System (EIS) unit

- specific data (unit facility name, facility code, boiler ID, tribal code, reg code, NAICS, longitude, latitude, facility ID, unit ID, rel point ID, process ID, agency facility ID, agency unit ID, agency rel point ID, agency process ID, stack height, stack diameter, stack temperature, stack flow, and stack velocity), filterable PM10 and filterable PM2.5 control efficiencies and sulfur and ash contents by ORIS code.

Table 1. Input Data Descriptions , Sources and Locations

No. Input Description Source Location

1 EIS This file contains Emission Inventory System ( EIS )

unit

- specific data that include u nit facility name, facility code

, boiler ID, tribal code, reg code, NAICS, longitude, latitude, facility ID, unit ID, rel point ID

, process ID, agency facility ID, agency unit ID, agency rel point ID, agency process ID, stack height, stack diameter, stack temperature, stack
flow, and stack velocity

. EPA FlatFile_Input

s .xls

2 GenericUnitSite This file contains all existing plants that serve as sister plants in siting generic units. The data include

NEEDS v.5.1 4 plant ’ s state FIPS code, county FIPS code, county’s most recent 8 hour ozone or PM 2.5 attainment/non

- attainment status, ORIS code

, latitude

- longitude coordinate s , and zip code. EPA FlatFile_Input

s .xls3 No. Input Description Source Location

3 L at L on Default This file contains latitu de

- longitude coordinates by ORIS code, state FIPS code and county FIPS code. EPA FlatFile_Input

s .xls

4 SCC This file contains Source Classification Codes ( SCCs ) by plant type, fuel type , c oal rank, firing and bottom type (for boilers)

. EPA Table 6

5 PlantTypeStackPara

meters This file contains default stack parameters (height, diameter, temperature and velocity) by plant type. EPA Table 7

6 SCCDefault StackPar

ameters This file contains default stack parameters (height, diameter, temperature and velocity) by SCC. EPA Table 8

7 Control Devices This file contains post

- combustion control devices

and their associated control IDs. EPA Table 9

8 SCCDefaultHeatCont

ent This file contains default heat contents by SCC. EPA Table 10

9 SCCEmsFac This file contains emission factors for carbon monoxide (CO), volatile organic compounds (VOC), ammonia (NH 3 ), filterable particulate matter less than or equal to 10 microns ( filterable PM 10 ),

filterable particulate matter less than or equal to 2.5 microns ( filterab le PM 2.5 ) , primary PM 10 and primary

PM 2.5 by SCC. EPA Table 1 1

10 PMSulfurAshContent

Default This file contains default filterable PM 10 and

filterable PM 2.5 control efficiencies and sulfur and ash contents by plant type and fuel type and coal

rank. EPA Table 1 2

11 PMCDEmsFac This file contains PM condensable emission factors by SCC. EPA Table 1 3

12 PMAdjustmentRatio This file contains primary PM 10 and primary PM 2.5 emission factors (EF) by SCC for gas

- fired units (including IGCC)

. EPA Table 1 4

13 PMSulfurAshContent This file contains filterable PM 10 and filterable PM 2.5 control efficiencies and sulfur and ash contents by ORIS code, unit ID, plant type and fuel type. The

filterable PM 10 and filterable PM 2.5 control

efficiencies are based on 2001 da ta. EPA FlatFile_Input

s .xls4 SECTION III: DETAILED DATA PROCESSING

Flow Chart 1 describes general data processing steps. A more detailed description of each step is provided in the

subsections followed

.

Flow Chart 1

. D ata Processing Steps

I. II . Assign existing and retrofit units’ SCCs

, state FIPS c odes, county FIPS codes, and

other EI S unit

- specific data that are required

for construction of the flat file. I . Disaggregate generic aggregates into generic
units, sit e the generic units’ states and counties and assign them SCCs, ORIS codes, facility
IDs, u nit IDs , rel point IDs, and process IDs

.

V . Calculate CO, NO
x , VOC , SO 2 , NH 3 , primary PM 10 , primary PM 2.5 , Mercury (Hg),

and HCl emissions for all records

. III . Assign stack parameters and latitude

longitude/county centroid coordinates for all records.

IV

. Assign post

- combustion control device IDs

for all records.5 Generic unit data are prepared by transforming the generic aggregates into units similar to existing units in terms

of the available data. First, t he g eneric aggregates are disaggregated to create generic units. Second, t he generic units are then sited and given state, count y and county

- centroid based latitude

- longitude coordinates

. Third, the generic units are assigned SCCs , ORIS codes, facility ID s

, unit ID s

, rel point ID s and process ID s

. This process is performed in three steps as described in Flow Chart 2.

Flow Chart 2

. Generic Unit Processing

1. Create g eneric u nits : Generic aggregates are first disaggregated to create generic units. The process entails

two steps: i. T he generic aggregates are first aggregated by state

, plant type and , for coal steam and IGCC

, and

coal rank

. ii. T hey are then s plit into smaller generic units by dividing the aggregated capacity by a reference capacity . T he result is the number of generic units to be created in a given state for each pl ant type and fuel type

. The reference capacity is varied by plant type as shown in T able 2

. Aggregated heat input and emissions are then divided evenly among all generic units created in a given s tate for each plant type.

Table 2

. Generic Unit Reference Capacity

Plant Type Reference Capacity (MW)

Biomass 600

Coal Steam 600
Combined Cycle 250

Combustion Turbine 160

Fossil Waste 0 30

IGCC 550

Oil/Gas Steam 100

2. Site g eneric u nit s : The generic units are then given a state FIPS code, county FIPS code and latitude

longitude /county centroid based on an algorithm that sites generic units in counties within their respective states

. The generic unit siting data file

, GenericUnitSite

, is u sed in this algorithm to assign each generic unit a sister plant that is in a county based on the county’s attainment/non

- attainment status. Within a state the hierarchy for assignment of sister plant s in the order of county code then ORIS code is shown i n Flow Chart 3

. All generic units are sited so that their ORIS codes are unique, and the same ORIS code has the same county, latitude

longitude /county centroid across all runs of the same base case origin. 1. Create generic units

2. Site generic units

3. Assign g eneric u nits SCCs , ORIS codes, facility IDs, u nit IDs , rel point IDs, and process IDs

. I . Disaggregate generic aggregates into generic units, sit e the generic units’ states and counties and assign them SCCs, ORIS codes, facility IDs, u nit IDs , rel point IDs, and process IDs

.6 Flow Chart 3

. Generic Unit Siting Hierarchy

3. Assign g eneric u nits SCCs , ORIS codes, facility IDs

, unit IDs

, rel point IDs and process IDs

. i. SCC assignment is based on unit’s plant type, fuel type and coal rank as shown in T able 3

. i i. Generic unit’s ORIS code consists of a six

- digit number. The units are first sorted by plant type in the order of combined cycle, fossil waste, combusti on turbine, IGCC

, and coal steam. Generic units’ ORIS codes are then assigned. The first digit of the ORIS code represents the unit’s plant type as shown in Table 4. The next three digits are a counter, starting with “000” and incrementing with each gen eric unit created within a given state for each plant type. The last two digits are the state FIPS code. For example, the first combined

- cycle generic unit sited in Arizona, which has a state FIPS code of “04”, has an ORIS code of “700104”.

iii. Generic u nit’s facility ID consists of a concatenation of the word “ORIS” and the unit’s ORIS code. For example, the first combined

- cycle generic unit in Arizona used in the example above has a plant ID of

“ORIS700104”.

iv. Generic unit’s unit ID consists of a conc atenation of a three

- letter unit ID code representing the unit’s plant type as shown in Table 5 and the unit’s state FIPS code. For example, the first combined

- cycle generic unit in Arizona used in the example above has a unit ID of “ ORIS GCC04”.

v. Generic unit’s rel point ID is the same as the unit’s unit ID. For example, the first combined

- cycle generic unit in Arizona in the example above has a point ID of “ ORIS GCC04”.

vi. Generic unit’s process ID is the same as the unit’s facility ID

.

Table 3

. Generic Unit SCC

Plant Type Fuel Type / Coal Rank SCC

Coal Steam Bituminous 10100202

Coal Steam Subbituminous 10100222

Coal Steam Lignite 10100301

Fossil Waste Process Gas 10100701

Biomass Biomass 10100902

Combined Cycle Natural Gas 20100201

Combined Cycle Oil 20100 1 01

Combustion Turbine Natural Gas 20100201

Combustion Turbine Oil 201001 01

IGCC Coal 20100301

IGCC Petroleum Coke 20100301

Oil/Gas Steam Natural Gas 10100601 S ister plants in attainment counties

S ister plants in PM non

- attainment

counties

S ister plants in 8

- hour ozone non

attainment counties7 Table 4

. Generic Unit 1 st Digit ORIS Code

Plant Type 1 st Digit of the ORIS Code

Biomass 3

Coal Steam 9
Combined Cycle 7

Combustion Turbine 8

Fossil Waste 5

IGCC 6

Oil/Gas Steam 4

Table 5

. Generic Unit ID Code

Plant Type Unit ID Code

Biomass GSC

Coal Steam GSC

Combined Cycle GCC

Combustion Turbine GGT

Fossil Waste GFW

IGCC IGC

Oil/Gas Steam GSC

1. Assign existing and retrofit units’ SCCs

. SCC, or Source Classification Code, describ es a generating unit's characteristics. The assignment of SCC for existing and retrofit units is based on a unit’s configuration that includes plant type, fuel type, and, if it’s a boiler, firing and bottom type

. The SCC is an eight

- digit numeric code with specific meaning (starting at the left) in the first, third, and fifth through eighth digits. For the flat
file, t he first digit of the SCC represents the type of unit (boiler [=1] or turbine [=2]). The third digit of the SCC represents the economic sector of the unit (electric power sector=1). And the fifth through eight h digits of the SCC represent the unit's attributes including fuel type and, if a boiler, bottom and firing type. The second

and fourth digits are zero

. Table 6 displays the SCCs.

2. Assign existing and retrofit units’ state FIPS codes, county FIPS codes, facility IDs, rel point IDs and process IDs. The units’ state FIPS codes, county FIPS codes, facility IDs, rel point IDs, and pr ocess IDs are assigned from the EIS unit

- specific data file, EIS. Where the EIS provides no data, default values are used. Appendix A describes the default values in detail.

Table 6. SCC Assignment for Existing and Retrofit Units

Plant Type Boiler / Generator Fuel Type / Coal Rank Firing Bottom SCC

Coal Steam Boiler/Generator Bituminous Wet 10100201

Coal Steam Boiler/Generator Bituminous Vertical Wet 10100201

Coal Steam Boiler/Generator Bituminous Wall Wet 10100201

Coal Steam Boiler/Generator Bituminous Vertical Dry 10100202

Coal Steam Boiler/Generator Bituminous Wall Dry 10100202

Coal Steam Boiler/Generator Bituminous Dry 10100202

Coal Steam Boiler/Generator Bituminous 10100202

Coal Steam Boiler/Generator Bituminous Wall 10100202

II . Assign existing and retrofit units’ SCCs , state FIPS codes, county FIPS codes, and other EI S

unit

- specific data that are required for construction of the flat file.8 Plant Type Boiler / Generator Fuel Type / Coal Rank Firing Bottom SCC

Coal Steam Boiler/Generator Bituminous Vertical 10100202

Coal Steam Bituminous Turbo 10100202

Coal Steam Boiler/Generator Bituminous Cyclone Wet 10100203

Coal Steam Boiler/Generator Bituminous Cyclone Dry 10100203

Coal Steam Boiler/Generator Bituminous Cyclone 10100203

Coal Steam Boiler/Generator Bituminous Stoker/SPR Wet 10100204

Coal Steam Boiler/Generator Bituminous Stoker/SPR 10100204

Coal Steam Boiler/Generator Bituminous Stoker/SPR Dry 10100204

Coal Steam Boiler/Generator Bituminous Tangential Wet 10100211

Coal Steam Boiler/Generator Bituminous Tangential 10100212

Coal Steam Boiler/Generator Bituminous Tangential Dry 10100212

Coal Steam Boiler/Generator Bituminous Cell Wet 10100215

Coal Steam Boiler/Generator Bituminous Cell 10100215

Coal Steam Boiler/Generator Bituminous Cell Dry 10100215

Coal Steam Boiler/Generator Bituminous FBC 10100218

Coal Steam Boiler/Generator Bituminous FBC Wet 10100218

Coal Steam Boiler/Generator Bituminous FBC Dry 10100218

Coal Steam Boiler/Generator Subbituminous Wet 10100221

Coal Steam Boiler/Generator Subbituminous Wall Wet 10100221

Coal Steam Boiler/Generator Subbituminous Vertical Wet 10100221

Coal Steam Boiler/Generator Subbituminous 10100222

Coal Steam Boiler/Generator Subbituminous Dry 10100222

Coal Steam Boiler/Generator Subbituminous Vertical Dry 10100222

Coal Steam Boiler/Generator Subbituminous Wall Dry 10100222

Coal Steam Boiler/Generator Subbituminous Wall 10100222

Coal Steam Boiler/Generator Subbituminous Cyclone Dry 10100223

Coal Steam Boiler/Generator Subbituminous Cyclone Wet 10100223

Coal Steam Boiler/Generator Subbituminous Cyclone 10100223

Coal Steam Boiler/Generator Subbituminous Stoker/SPR 10100224

Coal Steam Boiler/Generator Subbituminous Stoker/SPR Wet 10100224

Coal Steam Boiler/Generator Subbituminous Stoker/SPR Dry 10100224

Coal Steam Boiler/Generator Subbituminous Tangential Wet 10100226

Coal Steam Boiler/Generator Subbituminous Tangential Dry 10100226

Coal Steam Boiler/Generator Subbituminous Cell Wet 10100235

Coal Steam Boiler/Generator Subbituminous Cell Dry 10100235

Coal Steam Boiler/Generator Subbituminous Cell 10100235

Coal Steam Boiler/Generator Subbituminous FBC Dry 10100238

Coal Steam Boiler/Generator Subbituminous FBC Wet 10100238

Coal Steam Boiler/Generator Subbituminous FBC 10100238

Coal Steam Boiler/Generator Lignite Wall Dry 10100301

Coal Steam Boiler/Generator Lignite Wet 10100301

Coal Steam Boiler/Generator Lignite Tangential Wet 10100302

Coal Steam Boiler/Generator Lignite Tangential Dry 101003029 Plant Type Boiler / Generator Fuel Type / Coal Rank Firing Bottom SCC

Coal Steam Boiler/Generator Lignite Cyclone 10100303

Coal Steam Boiler/Generator Lignite Cyclone Wet 10100303

Coal Steam Boiler/Generator Lignite Stoker/SPR Wet 10100306

Coal Steam Boiler/Generator Lignite Stoker/SPR 10100306

Coal Steam Boiler/Generator Lignite Stoker/SPR Dry 10100306

Coal Steam Boiler/Generator Lignite FBC 10100318

Coal Steam Boiler/Generator Lignite FBC Wet 10100318

Coal Steam Boiler/Generator Lignite FBC Dry 10100318

O/G Steam Boiler/Generator Oil 10100401

O/G Steam Boiler/Generator Oil Wall Dry 10100401

O/G Steam Boiler/Generator Oil Tangential 10100404

O/G Steam Orimulsion Wall 10100409

O/G Steam Orimulsion Other 10100409

O/G Steam Boiler/Generator Natural Gas 10100601

O/G Steam Boiler/Generator Natural Gas Wall 10100601

O/G Steam Boiler/Generator Natural Gas Wall Dry 10100601

O/G Steam Natural Gas Wall Wet 10100601

O/G Steam Natural Gas Vertical Dry 10100601

O/G Steam Natural Gas Vertical 10100601

O/G Steam

_ Natural Gas Cell

_ 10100601

O/G Steam Natural Gas Cyclone Dry 10100601

O/G Steam Natural Gas Cyclone Wet 10100601

O/G Steam Natural Gas Cyclone 10100601

O/G Steam Natural Gas Other Dry 10100601

O/G Steam Natural Gas Tangential Dry 10100604

O/G Steam Natural Gas Tangential Wet 10100604

O/G Steam Boiler/Generator Natural Gas Tangential 10100604

Fossil Waste Boiler Process Gas 10100701

Coal Steam Boiler/Generator Petroleum Coke Vertical Dry 10100801

Coal Steam Petroleum Coke Wall 10100801

Coal Steam Boiler/Generator Petroleum Coke 10100801

Coal Steam Boiler/Generator Petroleum Coke FBC Dry 10100818

Coal Steam Boiler/Generator Biomass 10100902

Coal Steam Boiler/Generator Waste Coal 10102001

Coal Steam Boiler/Generator Waste Coal Wall 10102001

Coal Steam Boiler/Generator Waste Coal FBC 10102018

Combined Cycle Generator Oil 20100101

Combustion

Turbine Boiler/Generator Oil 20100101

Combined Cycle Boiler/Generator Natural Gas 20100201

Combined Cycle Natural Gas 2010020110 Plant Type Boiler / Generator Fuel Type / Coal Rank Firing Bottom SCC

Combustion

Turbine Boiler/Generator Natural Gas 20100201

Fossil Waste Generator Process Gas 20100201

IGCC Boiler/Generator 20100301

1. Assign s tack p arameters for all u nits : Existing and retrofit unit’s stack parameters are assigned based on the hierarchy described in Flow Chart 4

. Existing and retrofit units’ stack parameters are first assigned based on a unit’s plant type as shown in Table 7. If Table 7 provides no plant type

- based stack parameters, the units are assigned EIS stack parameters from the EIS. Where th e EIS data file provides no stack parameters, the units are assigned default stack parameters based on a unit’s SCC as shown in

Table 8. Generic units are assigned SCC

- based default stack parameters. Units’ stack flows are assigned from the EIS data file, except for IGCC units which receive default stack flow by plant type as shown in Table 7. Where the EIS data file provides no stack flow data, stack flows are calculated as

follows:



### ) (ft/sec Velocity Stack * 2 (ft) Diameter Stack

* 3.141592 (cft/sec) Flow Stack 2 

###      

=

2. Assign latitude

- longitude coordinates : Latitude

- longitude coordinates are assigned from the EIS data file. If the EIS data file provides no data, latitude

- longitude/county centroid coordinates are assigned based on

a unit’s sister ORIS code from the file “ LatLonDefault. ”

Flow Chart 4. Stac k Parameters Assignment Hierarchy

Table 7

. Plant Type

- Based Stack Parameters
Plant Type Stack Height (ft) Stack Diameter (ft) Stack Temperature (degree F) Stack Velocity (ft/sec) Stack Flow (cft/sec)

IGCC 150 19 340 75.8 21491.48 Plant Type

- Based Stack Parameters

EIS Stack Parameters

SCC

- Based Default Stack Parameters III . Assign stack parameters and latitude

- longitude/county centroid coordinates for all records.11 Table 8. SCC

- Based Default Stack Parameters

SCC Stack Height (ft) Stack

Diameter (ft) Stack Temperature (oF) Stack Velocity (ft/sec)

10100201 603.2 19.8 281.2 076.5

10100202 509.7 14.6 226.0 062.0

10100203 491.6 16.6 278.4 080.5

10100204 225.0 00.6 067.2 002.4

10100211 490.0 17.4 280.0 076.4

10100212 445.6 17.4 275.2 077.6

10100215 509.7 14.6 226.0 062.0

10100218 399.3 10.8 245.6 040.1

10100221 983.0 22.8 350.0 110.0

10100222 468.5 16.0 254.7 065.6

10100223 446.8 15.9 308.0 093.6

10100224 255.5 10.0 251.3 015.3

10100226 495.8 18.9 259.2 091.2

10100235 468.5 16.0 254.7 065.6

10100238 600.0 22.5 315.0 078.0

10100301 427.5 22.3 232.8 074.2

10100302 483.5 21.0 229.4 092.4

10100303 462.0 21.7 271.3 072.5

10100306 300.0 07.2 441.0 067.0

10100318 326.7 12.3 326.7 074.7

10100401 252.9 10.1 258.1 042.6

10100404 322.1 14.0 301.8 062.8

10100409 252.9 10.1 258.1 042.6

10100601 263.9 10.3 236.0 046.9

10100604 308.0 15.2 275.2 066.0

10100701 239.2 09.4 238.0 042.3

10100801 371.3 05.5 122.4 020.4

10100818 399.3 10.8 245.6 040.1

10100902 303.4 03.3 137.7 016.1

10102001 509.7 14.6 226.0 062.0

10102018 399.3 10.8 245.6 040.1

20100101 057.7 09.6 655.8 064.9

20100201 062.0 10.0 585.3 061.3

20100301 150.0 19.0 340.0 075.812 C ontrol I Ds are assigned to reflect all post

- combustion control devices installed at a unit. The control devices can

be installed at either existing or retrofit level, or both. Table 9 lists the control devices and their associated control

IDs.

Table 9 : Post

- Combustion Control Devices

Control ID Description

119 Dry FGD

139 SCR

140 SNCR or other N O
x

141 Wet FGD

206 DSI

207 ACI

Emissions are calculated at three levels: annual, season al and monthly emissions.

1. A nnual emission calculations

i. Annual NO
x , SO 2 , m ercury ( H g) , and HCl emissions (tons) are taken directly from IPM run results

.

ii. Annual CO, VOC and NH 3 emissions (tons) are calculated by multiplying the unit’s fuel use and

uncontrolled emission factor s for CO, VOC and NH 3 as follows:



### = (tons) Emissions Annual
Pollutant



### ton) (lb 2000 f) gallon,MMc (lb/ton,k Factor Emission * f) gallon,MMc (ton,k Use Fuel Annual
Pollutant


### / − −

W here :



### 2000 converts lb to short ton and the pollutants are CO, VOC, and NH 3

. IV

. Assign post

- combustion control device IDs for all records.

V . Calculate CO, NO
x , VOC , SO 2 , NH 3 , primary PM 10 , primary PM 2.5 , Mercury (Hg), and HCl emissions for

all records

.13 

### )

, , ( MMcf gallon k ton Use Fuel Annual

− is calculated from IPM run results

, which are in

MMBtu of annual heat input and converted into physical units of annual fuel use as follows:



### =

− )

, , ( MMcf gallon k ton Use Fuel



### )

, , / ( ) (

MMcf gallon k ton MMBtu Content Heat MMBtu Input Heat

−

Where 

### )

, , / ( MMcf gallon k ton MMBtu Content Heat

− is assigned using EPA Base

Case v.5.1 4 assumptions for coal and petroleum coke units. All other units are assigned

default heat contents based on the unit’s SCC as shown in Table 10

.

Table 10 : SCC

- Based Default Heat Content (MMBtu/ton, K

- gallon, MMcft)

SCC Heat Content

10100401 0152

10100404 0152

10100409 0152

10100601 1024

10100604 1024

10100701 0671

10100902 0012

20100101 0138

20100201 1024



### f) gallon,MMc (lb/ton,k Factor edEmission Uncontroll
Pollutant 

### − is assigned for CO, VOC, NH 3

based on a unit’s SCC as shown in Table 1 1.

Table 1 1: SCC

- Based Emission Factors (lbs/ton, k

- gal, MMcft)

SCC CO

EF VOC

EF NH 3 EF Filterable PM 10 EF Filterable PM 2.5 EF PM Flag 1

10100201 00.50 00.04 00.03 02.60 01.48 A

10100202 00.50 00.06 00.03 02.30 00.60 A

10100203 00.50 00.11 00.03 00.26 00.11 A

10100204 05.00 00.05 00.03 13.20 04.60

10100211 00.50 00.04 00.03 02.60 01.48 A

10100212 00.50 00.06 00.03 02.30 00.60 A

10100215 00.50 00.06 00.03 02.30 00.60 A

10100218 18.00 00.05 00.03 12.40 01.36

10100221 00.50 00.04 00.03 02.60 01.48 A

10100222 00.50 00.06 00.03 02.30 00.60 A

10100223 00.50 00.11 00.03 00.26 00.11 A

10100224 05.00 00.05 00.03 13.20 04.60

10100226 00.50 00.06 00.03 02.30 00.60 A

10100235 00.50 00.06 00.03 02.30 00.60 A14 SCC CO

EF VOC

EF NH 3 EF Filterable PM 10 EF Filterable PM 2.5 EF PM Flag 1

10100238 18.00 00.05 00.03 16.10 04.20

10100301 00.25 00.07 00.03 01.80 00.52 A

10100302 00.60 00.07 00.03 02.30 00.66 A

10100303 00.60 00.07 00.03 00.87 00.37 A

10100306 05.00 00.07 00.03 01.60 00.56 A

10100318 00.15 00.03 00.03 12.00 01.40

10100401 05.00 00.76 00.80 2 3

10100404 05.00 00.76 00.80 2 3

10100409 05.00 00.76 00.80 2 3

10100601 84.00 05.50 03.20 4 4

10100604 24.00 05.50 03.20 4 4

10100701 06.57 00.43 01.20 4 4

10100801 00.60 00.07 00.40 07.90 04.50 A

10100818 18.00 00.05 00.40 12.40 01.36

10100902 06.80 00.19 00.09 05.70 04.90

10102001 00.25 00.07 00.03 01.82 00.52 A

10102018 00.15 00.03 00.03 12.00 01.40

20100101 00.46 00.06 06.62 00.60 00.60

20100201 84.00 02.10 06.56 4 4

20100301 35.00 02.20 06.56 4 4

1 Multiply ash content % (A) by the PM EF numeric value to obtain the EF.

2 Filterable PM 10 EF = 5.9 * (1.12 * S + 0.37), where S=sulfur content %.

3 Filterable PM 2.5 EF = 4.3 * (1.12 * S + 0.37), where S=sulfur content %.

4 There are no EF for these SCC because of uncertainty due to an artifact of the test method used in the past.

PM 10 and PM 2.5 primary are calculated directly from their EF (see Table 1 3 ).

i i i. Annual primary PM 10 and PM 2.5 emissions (tons) are calculated for all but gas

- fired and IGCC units by adding the filterable PM 10 and filterable PM 2.5 emissions to condensable PM emissions

. Filterable PM 10 and PM 2.5 emissions for each unit are based on historical information regarding existing emissions controls and types of fuel burned and ash content of the fuel burned, as well as the projected emission controls (e.g., scrubbers and fabric filters). Condensable PM emissions are based on plant type, sulfur

content of the fuel, and 

### SO 2 /HCl and PM control configurations. Although EPA’s analysis is based on the
best available emission factors, these emission factors do not account for the potential changes in

condensable PM emissions due to the installation and operation of SCRs. The formation o f additional condensable PM (in the form of 

### SO 3 and H 2 SO 4 ) in units with SCRs depends on a number of factors, including coal sulfur content, combustion conditions and characteristics of the catalyst used in the SCR, and is likely to vary widely from unit t o unit. SCRs are generally designed and operated to minimize

increases in condensable PM. This limitation means that condensable PM emissions are potentially

underestimated for units with SCRs. In contrast, it is possible condensable PM emissions are

o verestimated in a case where the unit is combusting a low

- sulfur coal in the presence of a scrubber.15 

### = ) ( tons Emission Annual

10 PM Primary 

# ( ) ) ( ) (

10 

### tons Emission Annual tons Emission Annual

e Condensabl PM PM Filterable 

### +

= ) ( tons Emission Annual

2.5 PM Primary 

# ( ) ) ( ) (

5

. 2 

### tons Emission Annual tons Emission Annual

e Condensabl PM PM Filterable 

### +

Where :



### = ) (

10 

### tons Emission Annual

PM Filterable



###        

− −
) / ( 2000 )

, , / ( * )

, , (

10



### ton lb MMcf gallon k ton lb Factor Emission MMcf gallon k ton Use Fuel

PM Filterable



###        

− 100

1 * 10 PM 

### Efficiency Control Filterable 

# ( ) (%) * Content Ash

= ) (

5

. 2 

### tons Emission Annual

PM Filterable



###        

− −
) / ( 2000 )

, , / ( * )

, , (

5

. 2



### ton lb MMcf gallon k ton lb Factor Emission MMcf gallon k ton Use Fuel

PM Filterable



###        

− 100

1 * 5

. 2 PM 

### Efficiency Control Filterable 

# ( ) (%) * Content Ash

If 

### ) (

5

. 2 

### tons Emission Annual

PM Filterable 

### is greater than 

### ) (

10 

### tons Emission Annual

PM Filterable 

### ,



### ) (

5

. 2 

### tons Emission Annual

PM Filterable 

### is set equal to 

### ) (

10 

### tons Emission Annual

PM Filterable 

### .



### ) / ( 2000 ) / ( * ) (

ton lb MMBtu lb Factor Emission MMBtu Input Heat Annual

e Condensabl PM 

### = ) ( tons Emission Annual

e Condensabl PM16 W here :



### 2000 converts lb to short ton and the pollutants are CO, VOC, and NH 3

.

10 PM 

### Efficiency Control Filterable and

5

. 2 PM 

### Efficiency Control Filterable are assigned

based on a unit’s ORIS code, unit ID, plant type and fuel type from the data file PMSulfurAshContent. Where PMSulfurAshContent provides no data, default values based on a unit’s plant type and fuel type and coal rank as shown in Table 1 2 are used. 1

Table 1 2 : Defaul t PM Control Efficiencies and Sulfur and Ash Contents
Plant Type Fuel Type /

Coal Rank Filterable

PM 10 Control Efficiency (%) Filterable

PM 2.5 Control Efficiency (%) Sulfur

Content (%) Ash

Content (%)

Biomass Biomass 99.2 99.2 1.67 10.8

Coal Steam Bituminous 99.2 99.2 1.67 10.8

Coal Steam Subbituminous 99.2 99.2 0.32 05.6

Coal Steam Lignite 99.2 99.2 0.87 13.9

Coal Steam Petroleum Coke 99.2 99.2 5.30 00.1

Coal Steam Waste Coal 99.2 99.2 2.38 43.7

Coal Steam Biomass 99.2 99.2 1.67 10.8

IGCC Bituminous 1.67 10.8

IGCC Subbituminous 0.32 05.6

IGCC Lignite 0.87 13.9

IGCC Petroleum Coke 5.30 00.1

O/G Steam Oil 99.2 99.2 0.89 00.0

O/G Steam Orimulsion 99.2 99.2 0.89 00.0

Combustion

Turbine Oil 0.11 00.0

Combined Cycle Oil 0.11 00.0



### ) / ( ) / (
2 

### MMBtu lb Content Ash and MMBtu lb Content SO are assigned using EPA Base

Case v .5.1 4 assumptions. The EPA Base Case v.5.1 4 SO 2 and ash contents are in lb/ MMBtu and converted into percentage

- of

- fuel sulfur and ash contents as follows:

i. Sulfur content conversion

If fuel type is coal, waste coal or petroleum coke :



### = (%) Content Sulfur



### 100 * ) / ( 2000 * 2 ) / ( * ) / (
2



### ton lb ton MMBtu Content Heat MMBtu lb Content SO

1 For units with existing ESPs but still not able to meet their MATS filterable PM requirement, unit

- specific filterable PM incremental reductions needed to meet the requirement are incorporated into the units’

10 PM 

### Efficiency Control Filterable and

5

. 2 PM 

### Efficiency Control Filterable . For information on the unit

specific incremental filterable PM reductions needed and incorporated here, see Document for EPA Base Case v.5.14 Using Integrated Planning Model, Chapter 5, Section 5.6.1.17 where 2000 converts lb to short ton.

If fuel type is oil:



### = (%) Content Sulfur



### 100 * ) / ( 7882 * 2 ) / ( * ) / (
2 

### gallon k lb gallon k MMBtu Content Heat MMBtu lb Content SO

− −

where 7882 converts lb to k

- gallon of oil.

If fuel type is fossil waste and the unit uses process gas SCC “101007”:



### = (%) Content Sulfur



### 100 * ) / ( 52794 * 2 ) / ( * ) / (
2 

### MMcf lb MMcf MMBtu Content Heat MMBtu lb Content SO

where 52794 converts lb to MMcf of fossil waste 2

.

If fuel type is fossil waste and the unit uses natural gas SCC "201002":



### = (%) Content Sulfur



### 100 * ) / ( 44000 * 2 ) / ( * ) / (
2 

### MMcf lb MMcf MMBtu Content Heat MMBtu lb Content SO

where 44000 converts lb to MMcf of natural gas.

No sulfur content conversion is performed for natural gas as the sulfur content for natural gas is assumed to be zero.

ii. Ash content conversion for coal



### = (%) Content Ash



### 100 * 2000 ) / ( * ) / ( ton MMBtu Content Heat MMBtu lb Content Ash

where 2 000 is the number of lb per short ton.

I f no sulfur and ash content assumptions from EPA Base Case v.5.1 4 are available, default values based

on a unit’s ORIS code, unit ID, plant type and fuel type from the data file PMSulfurAshContent are used

first ; default values based on plant type and coal rank in Table 1 2 are used second. This hierarchy is

s ummarized in Flow Chart 5

.

2 Fossil waste using process gas SCC is assumed to be a combination of coke

- oven gas and blast

- furnace gas.18 Flow Chart 5

. Sulfur and Ash Contents Assignment Hierarchy



### ) / ( MMBtu lb Factor Emission

e Condensabl PM is assigned for all units based on units’

SCCs and whether they have either a n SO 2 control or PM scrubber installed as shown in

Table 1 3

.

Table 1 3 : SCC

- Based PM Condensable Emission Factors (lbs/MMBtu)

SCC SO 2 Control 1 PM Control 1 PM Condensable EF 2

10100201 Wet Scrubber PM Scrubber 0.0200

10100201 Dry Scrubber PM Scrubber 0.0200

10100202 Wet Scrubber PM Scrubber 0.0200

10100202 Dry Scrubber PM Scrubber 0.0200

10100203 Wet Scrubber PM Scrubber 0.0200

10100203 Dry Scrubber PM Scrubber 0.0200

10100204 0.0400

10100211 Wet Scrubber PM Scrubber 0.0200

10100211 Dry Scrubber PM Scrubber 0.0200

10100212 Wet Scrubber PM Scrubber 0.0200

10100212 Dry Scrubber PM Scrubber 0.0200

10100215 Wet Scrubber PM Scrubber 0.0200

10100215 Dry Scrubber PM Scrubber 0.0200

10100218 0.0100

10100221 Wet Scrubber PM Scrubber 0.0200

10100221 Dry Scrubber PM Scrubber 0.0200

10100222 Wet Scrubber PM Scrubber 0.0200

10100222 Dry Scrubber PM Scrubber 0.0200

10100223 Wet Scrubber PM Scrubber 0.0200

10100223 Dry Scrubber PM Scrubber 0.0200

10100224 0.0400

10100226 Wet Scrubber PM Scrubber 0.0200

10100226 Dry Scrubber PM Scrubber 0.0200

10100235 Wet Scrubber PM Scrubber 0.0200 1. EPA Base Case v.5.14 SO 2 and ash content (lb/MMBtu) assumptions, converted into percentage

- of

- fuel sulfur and ash contents

2. Default percentage

- of

- fuel sulfur and ash contents by ORIS code, unit ID, plant type and fuel type

3. Default percentage

- of

- fuel sulfur and ash contents by plant type and

fuel rank19 SCC SO 2 Control 1 PM Control 1 PM Condensable EF 2

10100235 Dry Scrubber PM Scrubber 0.0200

10100238 0.0100

10100301 Wet Scrubber PM Scrubber 0.0200

10100301 Dry Scrubber PM Scrubber 0.0200

10100302 Wet Scrubber PM Scrubber 0.0200

10100302 Dry Scrubber PM Scrubber 0.0200

10100303 Wet Scrubber PM Scrubber 0.0200

10100303 Dry Scrubber PM Scrubber 0.0200

10100306 0.0400

10100318 0.0100

10100401 0.0100

10100404 0.0100

10100409 0.0100

10100801 0.0100

10100818 0.0100

10100902 0.0170

10102001 Wet Scrubber PM Scrubber 0.0200

10102001 Dry Scrubber PM Scrubber 0.0200

10102018 0.0100

20100101 0.0072

1 For the given SCC, only one of the controls need be present for the EF to be assigned.

2 For SCCs that have non

- blank controls for both SO 2 and PM, then EF = (0.1 * S)

- 0.03,

(where S=sulfur content %), but if the EF is less than 0.01, set it equal to 0.01.

For the SCCs in Table 1 3 that have non

- blank controls for both SO 2 and PM, their PM condensable emission

factor can be calculated using the equation below:



# ( ) 03

. 0 (%) * 1

. 0

− = Content Sulfur Factor Emission e Condensabl PM

If the calculated value is less than the floor of 0.01 lb/ MMBtu, then 0 .01 is assigned as the PM condensable

E mission F actor in place of the calculated value.

Also, u nits hav ing a n SO 2 control are assigned the lower of the PM condensable emission factor from Table 1 3 and the calculated PM condensable emission factor using the above equation.

Primary PM 10 and p rimary PM 2.5 cannot be estimated for gas

- fired units (including IGCCs) using the same methodology as the other fuels sin c e there are no accurate filter able emission factors for them. Thus, their

emission s are estimated di rectly. Primary PM 10 and p rimary PM 2.5 emissi on factors in lb/MMBtu are assigned

based on each unit’s SCC as shown in Table 1 4

.20 Table 1 4 : Primary PM 10 and Primary PM 2.5 Emission Factors for Gas

- Fired and IGCC Units (lb/MMBtu)

SCC Primary PM 10 EF Primary PM 2.5 EF

10100601 0.532 0.440

10100604 0.532 0.440

10100701 0.043 0.035

20100201 0.317 0.195

20100301 11.263 11.263

2

. Season al emission calculations:

Summer is considered to be the 153 days between May 1 and Septem b er 30 inclusive

. Summer NO
x emissions are taken directly from IPM run results. For all other pollutants, summer emissions are calculated by multiplying the annual emissions by the ratio of the summer to annual heat input.



### * ) ( ) ( tons Emissions Annual tons Emissions Summer = 

###        

MMBtu Input Heat Annual MMBtu Input Heat Summer

( ) (

Winter is considered to be the 212 days between October 1 and April 30 inclusive that are not considered to be summer days. Winter emissions are calculated by subtracting the summer emissions from the annual emissions.



### ) ( ) ( tons Emissions Summer tons Emissions Annual (tons) Emissions Winter

− =

3

. Monthly emission calculations:

Summer monthly emissions for are calculated as follows:



### = ) ( tons Emissions Monthly Summer 

### Month in Day of Number tons Emissions Summer

* 153 ) (

Winter monthly emissions are calculated as follows:



### = ) ( tons Emissions Monthly Winter 

### Month in Day of Number tons Emissions Winter

* 212 ) (21 SECTION I V : FLAT FILE LAYOUT

The processed data are then converted into a flat file for U.S. EPA to use in air quality modeling work

. Both

c riteria and HAP emissions are provided in the same file. The pollutants are provided in the following order: CO,

NO
x , VOC, SO 2 , NH 3 , primary PM 10 , primary PM 2.5 , Mercury (Hg), and HCl.

The f ile ’ s naming convention is as follows:

FlatFile _<ipm run alpha

- numeric only>_<year4>_<date created using yyyy mmdd >.txt

where:

year4 = 4

- digit year of the emissions (e.g., 20 30 )

yyyy = 4

- digit year

mm = 2

- digit month number (e.g. 01 through 12)

dd = 2

- digit date number (e.g., 01 through 31)

F or example : ' FlatFile

_ EPA 513

_ BC_ 7c

_ 20 18

_ 201311 08 .txt ’

.

All data fields are comma

- delimited and c haracter data, i ncluding comma s , semi

- colon s

, and space s , are
enclosed in double

- quotes.

The file contains the following h eader line s :

#FORMAT=ff10_POINT

#COUNTRY=US

#YEAR= <year of emissions>
#VALUE_UNITS=TON
#CREATION_DATE= < date created > #CREATOR_NAME=US EPA

- CAMD
#DATA_SET_ID=1,US EPA IPM
#COUNTRY_CD,REGION_CD,TRIBAL_CODE,EIS_FACILITY_ID,EIS_UNIT_ID,EIS_REL_POINT_ID,EIS_PRO
CESS_ID,AGY_FACILITY_ID,AGY_UNIT_ID,AGY_REL_POINT_ID,AGY_PROCESS_ID,SCC,POLL,ANN_VALU
E,ANN_PCT_RED,FACILITY_NAME,ERPTYPE,STKHGT,STKDIAM,STKTEMP,STKFLOW,STKVEL,NAICS,LON

GI TUDE,LATITUDE,LL_DATUM,HORIZ_COLL_MTHD,DESIGN_CAPACITY,DESIGN_CAPACITY_UNITS,REG_
CODES,FAC_SOURCE_TYPE,UNIT_TYPE_CODE,CONTROL_IDS,CONTROL_MEASURES,CURRENT_COST
,CUMULATIVE_COST,PROJECTION_FACTOR,SUBMITTER_FAC_ID,CALC_METHOD,DATA_SET_ID,FACIL_
CATEGORY_CODE,O RIS_FACILITY_CODE,ORIS_BOILER_ID,IPM_YN,CALC_YEAR,DATE_UPDATED,FUG_
HEIGHT,FUG_WIDTH_YDIM,FUG_LENGTH_XDIM,FUG_ANGLE,ZIPCODE,ANNUAL_AVG_HOURS_PER_YE
AR,JAN_VALUE,FEB_VALUE,MAR_VALUE,APR_VALUE,MAY_VALUE,JUN_VALUE,JUL_VALUE,AUG_VALU
E,SEP_VALUE,OCT_VALUE,NOV_VAL UE,DEC_VALUE,JAN_PCTRED,FEB_PCTRED,MAR_PCTRED,APR_P
CTRED,MAY_PCTRED,JUN_PCTRED,JUL_PCTRED,AUG_PCTRED,SEP_PCTRED,OCT_PCTRED,NOV_PCT
RED,DEC_PCTRED,COMMENT

The last header line contains comma

- delimited field names identifying the data contained in each data field

.22 Appendix A

Default Values

Field Name Defa u lt Value

COUNTRY_CD 

### N/A

REGION_CD 

### N/A

TRIBAL_CODE 

### N/A

EIS_FACILITY_ID "ORIS" followed by the ORIS_FACILITY_CODE. For example,

ORIS55177.

EIS_UNIT_ID "ORIS" followed by the ORIS_BOILER_ID. For example, ORISST1.

EIS_REL_POINT_ID "ORIS" followed by the ORIS_BOILER_ID. That is, the same as the

unit ID default value.

EIS_PROCESS_ID Use the same value as in the [IPM Y/N] field. That is, the NEEDS UniqueID.

AGY_FACILITY_ID Blank

AGY_UNIT_ID Blank

AGY_REL_POINT_ID Blank

AGY_PROCESS_ID Blank

SCC N/A

POLL N/A

ANN_VALUE N/A

ANN_PCT_RED Blank

FACILITY_NAME NEEDS Plant Name

ERPTYPE Blank

STKHGT SCC

- based default stack parameters from

SCCDefaultStackParameters file.

STKDIAM SCC

- based default stack parameters from

SCCDefaultStackParameters file.

STKTEMP SCC

- based default stack parameters from

SCCDefaultStackParameters file.

STKFLOW SCC

- based default stack parameters from

SCCDefaultStackParameters file.

STKVEL SCC

- based default stack parameters from

SCCDefaultStackParameters file.

NAICS Blank

LONGITUDE County

- centroid based longitude by ORIS code, state FIPS code and country FIPS code from LatLonDefault file.

LATITUDE County

- centroid based longitude by ORIS code, state FIPS code and country FIPS code from LatLonDefault file.

LL_DATUM Blank

HORIZ_COLL_MTHD Blank

DESIGN_CAPACITY N/A

DESIGN_CAPACITY_UNITS N/A

REG_CODES Blank

FAC_SOURCE_TYPE "125"

UNIT_TYPE_CODE "100" for Boiler, "120" for Turbine, "140" for combined cycle (boiler/gas turbine).23 Field Name Defa u lt Value

CONTROL_IDS N/A

CONTROL_MEASURES Blank

CURRENT_COST Blank

CUMULATIVE_COST Blank

PROJECTION_FACTOR Blank

SUBMITTER_ID N/A

CALC_METHOD N/A

DATA_SET_ID N/A

FACIL_CATEGORY_CODE N/A

ORIS_FACILITY_CODE NEEDS ORIS Code

ORIS_BOILER_ID NEEDS Unit ID

IPM_YN N/A

INV_YEAR N/A

DATE_UPDATED N/A

FUG_HEIGHT Blank

FUG_WIDTH_YDIM Blank

FUG_LENGTH_XDIM Blank

FUG_ANGLE Blank

ZIPCODE N/A

ANNUAL_AVG_HOURS_PER_YEAR N/A

JAN_VALUE N/A

FEB_VALUE N/A

MAR_VALUE N/A

APR_VALUE N/A

MAY_VALUE N/A

JUN_VALUE N/A

JUL_VALUE N/A

AUG_VALUE N/A

SEP_VALUE N/A

OCT_VALUE N/A

NOV_VALUE N/A

DEC_VALUE N/A

JAN_PCTRED Blank

FEB_PCTRED Blank

MAR_PCTRED Blank

APR_PCTRED Blank

MAY_PCTRED Blank

JUN_PCTRED Blank

JUL_PCTRED Blank

AUG_PCTRED Blank

SEP_PCTRED Blank24 Field Name Defa u lt Value

OCT_PCTRED Blank

NOV_PCTRED Blank

DEC_PCTRED Blank

COMMENT Blank25 Appendix B Temporal A llocation of IPM Projected Seasonal E missions to H ourly E missions for U se in A ir Q uality

M odeling

IPM provides u nit

- level emission projections of average winter (representing October through April) and average summer (representing May through September) values. To use these data in an air quality model, the unit

- level

data must fi rst be converted to into hourly values through a process called “temporal allocation”.

The goal of the temporal allocation process is to reflect the variability in the unit

- level emissions that can impact air quality over seasonal, daily, or hourly time s cales, in a manner compatible with incorporating future

- year emission projections into future

- year air quality modeling. The temporal allocation process is applied to the

seasonal emiss ion projections obtained from an IPM modeling scenario. IPM represents two seasons: summer ( May through September ) and winter (October through April)

. IPM unit

- level parsed files contain seasonal and

annual totals of SO 2 , NO X , CO 2 , Hg

, and HCl emissions ( computed directly within IPM ), while PM 2.5 , PM 10 , VOC,

NH 3 , and CO emissions are calculated using a post

- processing tool 3 based on each unit’s projected fuel use and configuration , coupled with pollutant

- specific emission factors. 4 W hen calculating PM emissions , the p ost

processing tool utilizes specific data assu mptions such as the ash and sulfur content of the coal projected to be

used at the unit

. The tool creates a Flat File (in a comma

- separated value or .csv file format) that provides the starting point for developing emission inputs to an air quality model.

The result ing Flat File contains all of the endogenous ly

- determined and post

- calculated unit

- level emissions combined with stack parameters ( i.e., stack location and other characteristics consistent with information found in

the National Emissions Invento ry (NEI)). A cross reference is used to map the units in NEEDS to the stack parameter and facility, unit, release point, and process identifiers used in the N ational Emissions Inventory (N EI )

. The cross reference also maps sources to the hourly Continuous Emissions Monitoring System (CEMS) data that

is used to temporally allocate the emissions in the base year air quality modeling . This cross reference has been updated for the v5.14 platform through collaboration with EPA, regional planning organizations, a nd states and is

also used to determine which emission s sources in the NEI sources have future year emissions predicted by IPM. Emissions from point sources for which emissions are not predicted by IPM are carried forward into the future year modeling pla tform using other projection methods. Therefore, if the NEI and IPM sources are not properly
matched, double

- counting could result because the future year emissions output from IPM in the future year are treated as a full replacement for the base year emis sions, although only for the emissions processes estimated by

IPM

.

In order to support the temporal allocation process and other requirements of modeling point sources , the Flat File output from the IPM postprocessor specifies annual and monthly emissions for each stack; however, since IPM projections are only modeled for two seasons comprising multiple months each, monthly emissions cannot be precisely specified in the Flat File. Instead, the monthly values in the Flat File ou tput from the postprocessor are computed by multiplying the average summer day and average winter day emissions predicted by IPM by the number of days in the respective month. In summary, th e monthly emission values shown in the Flat File are not

intended to represent an actual month

- to

- month emission pattern; instead, they are interim values that have translated IPM’s seasonal projections into month

- level data that serve as a starting point for the temporal allocation process.

The monthly emissions with in the Flat File undergo a multi

- step temporal allocation process to yield the hourly

emission values at each unit, as is needed for air quality modeling : summer/ winter value to month, month to day, and day to hour

. For sources not matched to unit

- specific CEMS data, t he first two steps are done outside of SMOKE and the third step to get to hourly values is done by SMOKE using daily the emissions files created from the first two steps. For each of these three temporal allocation steps, NO x and SO 2 CEM S d ata are used to

allocate NO
x and SO 2 emissions, while CEM S heat input data are used to allocate all other pollutants. The approach defined here gives priority to temporalization based on the base year CEMS data to the maximum extent possible.

3 Documentation of this tool can be found at www.epa.gov/powersectormodeling

4 For more information on EPA emission factors see http://www.epa.gov/ttnchie1/ap42/26 Prior to u sing the 2011 CEMS data to develop monthly, daily, and hourly profiles, the CEMS data was processed through a tool that found data quality flags that indicated the data were measured. These situations can cause erroneously high values in the CEMS data. I f the data were not measured, and it was found to be more the 3 times the annual mean, the data were replaced with annual mean values. These adjusted CEMS data were used to compute the monthly, daily, and hourly profiles described above (see example in Fig ure B

- 1).

For u nits in NEEDS that are matched to units in the National Emission Inventory (NEI)

, and for which CEMS data

are avai lable, the emissions are tempora lized based on the CEMS data for that unit and pollutant. For units that

are not matched to the NEI or for which CEMS data are not available, the allocation of the IPM seasonal emissions to months is done using average fuel

- specific season

- to

- month factors generated for each of the 64 IPM regions shown in Figure B

- 2 . These factors are based on a single year of CEMS data for the modeling base year associated with the air quality modeling analysis being performed, such as 2011. Note that IPM uses load data (reflecting the shape of demand) corresponding to the load in each IPM region that occurred in the base year of the air quality modeling analysis, such as 2011. The fuels used for creating the profiles for a region are coal, natural gas, and other

, where the other fuels used include oil and wood and vary by region . Separate profiles are computed for NO
x , SO 2 , and heat input. An overall composite profile across all fuels is also computed and can be

used in the event that a region has too few units of a fuel type to make a reasonable average profile, or in the case when a unit changes fuels between the base and future year and there were previously no units with that fuel in the region containing the unit

.

T he monthly emission values in the Flat File are first reallocated across the months in that season to align the

month

- to

- month emission pattern at each stack with historic seasonal emission patterns. 5 While this reallocation affects the monthly pattern of each unit ’s future

- year seasonal emissions, the seasonal totals are held equal to the IPM projection for that unit and season . Second, t he reallocated monthly emission values at each stack are disaggregated down to the daily level consistent with historic daily emission patterns in the given month at the given stack using separate profiles for NO
x , SO 2 , and heat input. This process helps t o capture the influence of meteorological episodes that cause electricity demand to vary from day

- to

- day, as well as weekday

- weekend effects that change demand during the course of a given week. Third, this data set of emission values for each day of the y ear at each unit is input into SMOKE, which uses temporal profiles to disaggregate the daily values into specific values for each hour of the year

.

For units without or not matched to CEMS data, or for which the CEMS data are found to be unsuit able f or use in the future year

, emissions are allocated from month to day using IPM

- region and fuel

- specific average month

- to

day factors based on CEM S data from the base year of the air quality modeling analysis. These instances include units that did not oper ate in the base year or for which it may not have been possible to match the unit in NEEDS with a specific unit in the NEI. EPA uses average emission profiles for some units with CEMS data in the base

year when one of the following cases is true : (1) units are projected to have substantially increased emissions in the future year compared to its emissions in the base (historic) year 6 ; (2) CEMS data are only available for a limited number of hours in that base year; (3) units change fuels in the future year; (4) the unit is new in the future year; or (5 ) units experienced atypical conditions during the base year, such as lengthy downtimes for

maintenance or installation of controls. The temporal profiles that map emissions from days to hours are computed bas ed on the region and fuel

- specific seasonal (i.e., winter and summer) average day

- to

- hour factors derived from the CEMS data for those fuels and regions using only heat input data for that season

. Only heat inpt

is used because it is the variable that is t he most complete in the CEMS data. SMOKE uses the se profiles to

allocate the daily emissions data to hours.

The emissions from units for which unit

- specific profiles are not deemed appropriate, and for units in the IPM outputs that are not specifically matched to units in the base year, are temporally allocated to hours reflecting

5 For example, the total emissions for a unit in May would not typically be the same as the total emissions for the same unit in July, even though May and July are both in th e summer season and the number of days in those months is the same. This is because the weather changes over the course of each season, and thus the operating behavior of a specific unit can also vary throughout each season. Therefore, part of the temporal allocation process is intended to create month

- specific emissions totals that reflect this intra

- seasonal variation in unit operation and associated emissions.

6 In such instances, EPA does not use that unit’s CEMS data for temporal allocation in order to avoid assigning large increases in emissions over short time periods in the unit’s hourly emission profile.27 patterns typical of the region in which the unit is located. Analysis of CEMS data for units in each of the 64 IPM regions revealed that there were differences in the temporal patterns of historic emission data that correlate with fuel type (e.g., coal, gas, and other), time of year, pollutant, season (i.e. winter versus summer) and region of the country. The correlation of the temporal pattern with fuel type is explained by the relationship of units’ operating practices with the fuel burned. For example, coal units take longer to ramp up and ramp down than natural gas units, and some oil units are used only when electricity demand cannot otherwise be met. Geographically, the

pat terns were less dependent on state location than they were on IPM regional location. For temporal allocation of
emissions at these units, Figure B

- 3 provides an example of daily coal, gas, and composite profiles in one IPM region

. EPA developed seasonal av erage emission profiles, each derived from base year CEMS data for each season across all units sharing both IPM region and fuel type. 7 Figure B

- 4 provides an example of seasonal profiles that allocate daily emissions to hours in one IPM region. These aver age day to hour temporal profiles were also used for sources during seasons of the year for which there were no CEMS data available , but for which IPM predicted emissions in that season

. This situation can occur for multiple reasons, including how the

CEMS was run at each source in the base year.

For units that do have CEMS data in the base year and are matched to units in the IPM output, the base year

CEMS data are scaled so that their seasonal emissions match the IPM

- projected totals . In particular, the fraction of the unit’s seasonal emissions in the base year is computed for each hour of the season, and then applied to the seasonal emissions in the future year. This is accomplished outside of SMOKE by creating data in the same

forma t as CEMS data for NOx, SO2, and heat input. Any pollutants other than NOX and SO2 are temporalized within SMOKE using heat input as a surrogate. Distinct factors are used for the fuels coal, natural gas, and

“other”

. This procedure yields future

- year hou rly data that have the same temporal pattern as the base year CEMS data while matching future

- year seasonal total emissions for each stack to IPM’s future

- year projections (see example in Figure B

- 5)

.

In cases when the emissions for a particular unit are projected to be substantially higher in the future year than in the base year, the proportional scaling method to match the emission patterns in the base year described above can yield emissions for a unit that are much higher than the historic maximum em issions for that unit. To address

this issue for the 2017 scenario, the maximum measured emissions of NO
x and SO 2 in the period of 2011

- 2014 were computed. The temporalized emissions were then evaluated at each hour to determine whether they were

above thi s cumulative maximum. The amount of “excess emissions” over the maximum was then computed. For
units for which the “excess emissions” could be reallocated to other hours, those emissions were distributed evenly to hours that were below the maximum. Those h ourly emissions were then reevaluated against the maximum, and the procedure of reallocating the excess emissions to other hours was repeated until all of the

hours had emissions below the maximum , whenever possible (see example in Figure B

- 6 )

.

Using the above approach, it was not always possible to reallocate excess emissions to hours below the historic maximum, such as when the total seasonal emissions of NOx or SO2 for a unit divided by the number of hours of operation are greater than the 2011

- 2014 ma ximum emissions level. For these units, the regional fuel

- specific average profile was applied to all pollutants, including heat input, for that season (see example in Figure B

- 7 ) . An exception to this is if the fuel for that unit is not gas or coal. In that case, the composite (non

- fuel

- specific) profile was used for that unit. This is because many sources that used “other” fuel profiles had very irregular shapes due to a small number of sources in the region , and the allocated emissions frequently still exceeded the 2011

- 2014 maximum. Note that it was not possible for SMOKE to use regional profiles for some pollutants and adjusted CEMS data for other pollutants for the same unit / season, therefore all pollutants are assigned to regional profiles

when re gional profiles are needed . Also note that for some units, some hours still exceed the 2011

- 2014 annual maximum for the unit even after regional profiles were applied (see example in Figure B

- 8 )

.

7 EPA also uses a n overall composite profile across all fuels for each IPM region in instances where a unit is projected to burn a fuel for which E PA cannot construct an average emission profile (because there were no other

units in that IPM region whose historic CEMS data represent emissions from burning th at fuel )

.28 Figure B

- 1. Removal of Unmeasured Spikes in CEMS Data29 Figure B

- 2 . EPA Base Case v.5.1 4 IPM Regions (64 in all)

Figure B

- 3. Average NOx Daily Profiles by Fuel and Composite in West Texas Region (July)30 Figure B

- 4 . Example of Summer vs. Winter Hourly Profiles in Virginia Region

Figure B

- 5 . Future Year Emissions Follow Pattern of Base Year Emissions31 Figure B

- 6 . Excess Emissions Apportioned to Hours Less than Maximum

Figure B

- 7 . Adjustment to Hours Less than Maximum not Possible, Regional Profile Applied32 Figure B

- 8 . Regional Profi le Applied, but Exceeds Maximum in Some Hours