California Environmental Protection Agency 

Air Resources Board

Air Quality Impacts of the Use of Ethanol

 in California Reformulated Gasoline

Appendix B

Photochemical Modeling

December 1999
B-ii

Table of Contents

B-1. Introduction........................................................................................................... 1

B-2. Photochemical Model Description........................................................................ 1

B-2.1. Urban Airshed Model...................................................................................... 2

B-2.2. Flexible Chemical Mechanism Version of the Urban Airshed Model............ 2

B-2.3. SAPRC97 Chemical Mechanism.................................................................... 3

B-2.4. Computer......................................................................................................... 4

B-3. Model Input Description....................................................................................... 6

B-3.1. Episode and Domain....................................................................................... 6

B-3.2. Basic Input Files............................................................................................. 6

B-3.3. Region Top and Boundary Conditions........................................................... 7

B-3.4. Initial Conditions............................................................................................ 9

B-3.5. Point and Area Sources................................................................................. 10

B-3.6. Air Quality Monitoring Sites........................................................................ 10

B-4. Results................................................................................................................. 11

B-4.1. Domain Maximum 1-Hour-Average Concentrations ................................... 11

B-4.2. Domain Maximum 8-Hour-Average Concentrations ................................... 29

B-4.3. Domain Maximum 24-Hour-Average Concentrations ................................. 29

B-5. Sensitivity Simulations........................................................................................ 30

B-5.1. Increasing Motor Vehicle Hydrocarbon and CO Emissions......................... 30

B-5.2. Potential Impact of the Chlorine Radical Reaction With Ethanol................ 31

B-5.3. Updated Rate Constants................................................................................ 33

B-5.4. Revised Boundary Conditions ...................................................................... 33

B-5.5. Sensitivity Results......................................................................................... 34

B-6. Model Performance............................................................................................. 35

B-6.1. Model Performance Statistics....................................................................... 35

B-6.2. Ozone, CO, NO, and NO2 ............................................................................ 36

B-6.3. PAN .............................................................................................................. 43

B-6.4. Acetaldehyde, Benzene, 1,3-Butadiene, and Formaldehyde ........................ 46

B-7. Ozone, PAN, and PPN Formation Potentials...................................................... 48

B-7.1. Description of Formation Potentials............................................................. 48
B-iii

B-7.2. Model Description and Inputs....................................................................... 49

B-7.3. Results........................................................................................................... 53

B-7.4. Other Study of PAN Formation Potentials................................................... 66

B-8. References........................................................................................................... 67

Attachment B1 – Listing of SAPRC97 Chemical Mechanism................................... 70

Attachment B2 – Listing of Reactions of Isoprene (Condensed 1-Product)............... 77

Attachment B3 – Listing of Explicit Reaction Mechanisms for Other VOCs............ 78

List of Tables

Table 2.1 List of Hydrocarbon Species Treated Explicitly in SAPRC97.......................... 4

Table 3.1 List of the Meteorological and Terrain Files for the SCAQS

August 26-28, 1987 Episode ............................................................................. 7

Table 3.2 Scenarios Considered for the Photochemical Modeling.................................... 7

Table 3.3 Baseline Boundary Concentration (ppb)............................................................ 8

Table 3.4 Region Top Concentrations (ppb)...................................................................... 9

Table 3.5 Initial Species Concentrations (ppb)................................................................ 10

Table 3.6 Sites in the Modeling Domain Used to Study the Impact of

Each of the Scenarios Studied......................................................................... 11

Table 4.1 Domain Maximum 1-Hour-Average Concentrations for Each

Scenario........................................................................................................... 12

Table 4.2 Domain Maximum 8-Hour-Average Concentrations for Each

Scenario........................................................................................................... 29

Table 4.3 Domain Maximum 24-Hour-Average Concentrations For Each

Scenario........................................................................................................... 30

Table 5.1 Sensitivity Scenarios........................................................................................ 31

Table 5.2 Boundary and Top Concentrations Used in the Sensitivity

Simulations (ppb)............................................................................................ 33

Table 5.3 Domain Maximum 1-Hour-Average Concentrations for

Sensitivity Simulations.................................................................................... 34

Table 6.1 UAM-FCM with SAPRC97 Model Performance Evaluation.......................... 36

Table 6.2 UAM-FCM with CB4 Model Performance Evaluation................................... 37
B-iv

Table 6.3 Observed and Predicted Maximum 1-Hour-Average PAN

Concentrations for August 28, 1987 ............................................................... 43

Table 6.4 Measured and Predicted 3-Hour-Average Concentrations for

Selected VOCs on August 28, 1987 (ppb)...................................................... 47

Table 7.1 PAN and PPN Equilibrium Reaction Rate Constants....................................... 50

Table 7.2 Meteorological Inputsa..................................................................................... 50

Table 7.3 Initial Concentrations for South Coast Air Basin Scenarios

(ppm)............................................................................................................... 51

Table 7.4 Initial Concentrations for Brazil Scenarios (ppm)........................................... 52

Table 7.5 Contribution From Individual VOCs to Total Ozone Formation*

(ppm)............................................................................................................... 60

Table 7.6 Contribution From Individual VOCs to Ozone Formation*

(ppm)............................................................................................................... 61

Table 7.7 Contribution From Individual VOCs to PAN Formation* (ppm) .................... 62

Table 7.8 Contribution From Individual VOCs to PAN Formation* (ppm) .................... 63

Table 7.9 Contribution From Individual VOCs to PPN Formationa,b (ppm)................... 64

Table 7.10 Contribution From Individual VOCs to PPN Formationa,b

(ppm)............................................................................................................... 65

Table 7.11 Relative Contribution of Lumped VOC Species to PAN

Formationa....................................................................................................... 66

List of Figures

Figure 2.1 Modeling Domain............................................................................................. 5

Figure 4.1 Time Series for Ozone, NO2, and NO at Anaheim for 1997 and

2003 Scenarios................................................................................................ 14

Figure 4.2 Time Series for Ozone, NO2, and NO at Burbank for 1997 and

2003 Scenarios................................................................................................ 15

Figure 4.3 Time Series for Ozone, NO2, and NO at Los Angeles for 1997

and 2003 Scenarios.......................................................................................... 16

Figure 4.4 Time Series for Ozone, NO2, and NO at Riverside for 1997

and 2003 Scenarios.......................................................................................... 17

Figure 4.5 Time Series for Ozone, NO2, and NO at Grid with Domain

Maximum for 1997 and 2003 Scenarios......................................................... 18
B-v

Figure 4.6 Time Series for MTBE, Ethanol, and CO at Anaheim for 2003

Scenarios......................................................................................................... 19

Figure 4.7 Time Serie s for MTBE, Ethanol, and CO at Burbank for 2003

Scenarios......................................................................................................... 20

Figure 4.8 Time Series for MTBE, Ethanol, and CO at Los Angeles for

2003 Scenarios................................................................................................ 21

Figure 4.9 Time Series for MTBE, Ethanol, and CO at Riverside for 2003

Scenarios......................................................................................................... 22

Figure 4.10 Time Series for MTBE, Ethanol, and CO at Grid with

Domain Maximum for 2003 Scenarios........................................................... 23

Figure 4.11 Time Series for PAN, PPN, and Nitric Acid at Anaheim for

1997 and 2003 Scenarios................................................................................. 24

Figure 4.12 Time Series for PAN, PPN, and Nitric Acid at Burbank for

1997 and 2003 Scenarios................................................................................. 25

Figure 4.13 Time Series for PAN, PPN, and Nitric Acid at Los Angeles

for 1997 and 2003 Scenarios........................................................................... 26

Figure 4.14 Time Series for PAN, PPN, and Nitric Acid at Riverside for

1997 and 2003 Scenarios................................................................................. 27

Figure 4.15 Time Series for PAN, PPN, and Nitric Acid at Grid with

Domain Maximum for 1997 and 2003 Scenarios........................................... 28

Figure 6.1 Comparison of Predicted Ozone, NO, and NO2 by SAPRC97

and CB-IV Against Ambient Data at Anaheim (1987 SCAQS)..................... 38

Figure 6.2 Comparison of Predicted Ozone, NO, and NO2 by SAPRC97

and CB-IV Against Ambient Data at Burbank (1987 SCAQS)...................... 39

Figure 6.3 Comparison of Predicted Ozone, NO, and NO2 by SAPRC97

and CB-IV Against Ambient Data at Los Angeles

(1987 SCAQS)................................................................................................ 40

Figure 6.4 Comparison of Predicted Ozone, NO, and NO2 by SAPRC97

and CB-IV Against Ambient Data at Riverside (1987 SCAQS) .................... 41

Figure 6.5 Comparison of Predicted Ozone, NO, and NO2 by SAPRC97

and CB-IV at the Domain Maximum.............................................................. 42

Figure 6.6 Comparison of Observed and Predicted PAN at Anaheim,

Azusa, and Burbank ........................................................................................ 44

Figure 6.7 Comparison of Observed and Predicted PAN at Claremont,

Los Angeles, and Riverside............................................................................. 45

Figure 7.1 Ozone Formation Potentials From Individual VOCs..................................... 54

Figure 7.2 Ozone Formation Potentials From Individual VOCs

(continued)...................................................................................................... 55
B-vi

Figure 7.3 PAN Formation Potentials From Individual VOCs........................................ 56

Figure 7.4 PAN Formation Potentials From Individual VOCs (continued) .................... 57

Figure 7.5 PPN Formation Potentials From Individual VOCs........................................ 58

Figure 7.6 PPN Formation Potentials From Individual VOCs (continued)..................... 59
B-1

B-1. Introduction

This appendix describes the air quality simulations performed in support of the

analysis of the potential impact on air quality caused by the phase-out of gasoline

containing methyl tertiary-butyl ether (MTBE) and replacement by ethanol-based or nonoxygenated fuels. It is important to bear in mind that the model results for this study are

being used in a relative, rather than absolute sense. That is, the model was used to

estimate the change from 1997 MTBE gasoline to ethanol-containing and nonoxygenated gasolines in 2003, rather than to predict absolute values in 2003. The

estimated changes were then used to adjust the base year (1997) air quality measurements

to future (2003) concentrations, as described in Appendix C. The modeling community

is in general agreement that models are best used in a relative sense.

In the sections that follow a brief description of the air quality model is presented

together with the photochemical mechanism chosen. A description of the input files

necessary to run each of the scenarios considered is presented, together with a summary

of the results. A discussion of sensitivity simulations and model performance is included.

An analysis of the sensitivity of ozone, PAN, and PPN under a wide variety of conditions

was conducted with a box model.

B-2. Photochemical Model Description

Photochemical air quality modeling is a primary tool for understanding the complex

interrelationships among pollutants emitted and transported in a given area.

Photochemical air quality models are computer models that represent the state-of–thescience understanding of how ozone and other secondary pollutants are formed and the

relationship to the primary pollutants emitted by different source categories. They have

been used to assess the effectiveness of air pollution control strategies to achieve the air

quality standards. The Flexible Chemical Mechanism Version of the Urban Airshed

Model (UAM-FCM) is an air quality model that has been used by ARB since 1995.

The UAM-FCM is an adaptation of the Urban Airshed Model (UAM) to provide

flexibility in incorporating different Carbon Bond IV or SAPRC-type photochemical

mechanisms into the UAM (Kumar et al., 1995). The UAM has been the primary air

quality regulatory model for ozone control strategy development. However, it has a hardcoded a version of the Carbon Bond IV photochemical mechanism, together with a

unique algorithm to solve the set of differential equations representing the chemical

transformations that is accurate, robust and fast. The algorithm was designed to take

maximum advantage of the Carbon Bond IV features. The treatment of photolytic

reactions in the UAM is also unique. All values for the photolytic reaction rates are hardcoded, and depend on the value of the NO2 photolytic reaction rate. The hard-coded

approach in the UAM makes it very difficult to study recent and more updated

mechanisms, such as those developed by Dr. W.P.L. Carter at the University of

Riverside. Any change or update in the Carbon Bond IV mechanism, photolytic rates, or

the implementation of a different chemical mechanism requires changes to the UAM
B-2

code that need to be done by hand. However, the UAM-FCM can read a text file version

of a mechanism and create program subroutines that are readily integrated with the model

(Kumar et al., 1995). Below we briefly describe the main aspects of the UAM and the

UAM-FCM.

B-2.1. Urban Airshed Model

Morris and Meyers (1990) provide a detailed description of the UAM. Only a brief

summary is provided here. The UAM is a gridded 3-dimensional air quality model that

can simulate the atmospheric physical and chemical processes that cause air pollution.

The basic advection-diffusion equation is:

( ) ( ) ( )

( ) ( ) ( )

z

C

K

y z

C

K

x y

C

K

z x

wC

y

vC

x

uC

t

C i

V

i

H

i

H

i i i i

∂

∂

∂

∂

+

∂

∂

∂

∂

+

∂

∂

∂

∂

=

∂

∂

+

∂

∂

+

∂

∂

+

∂

∂

+ Ri + Si + Li(B-1)

The first term on the left-hand side of Equation (1) represents the time-varying

concentration of pollutant i, and the last three terms on the left-hand side of Equation (1)

represent advection. The first three terms on the right-hand side of Equation (1) represent

turbulent diffusion, Ri are chemical reaction processes, Si are emission source processes,

and Li correspond to losses by deposition. The other terms in Equation (1) are the

horizontal and vertical wind speed components -- u, v, and w -- and the horizontal and

vertical diffusivity coefficients, KH and KV . Equation (1) is solved for each pollutant and

grid cell at each time step in the simulation. As designed, the UAM has hard-coded a

version of the Carbon Bond IV (CB4) chemical mechanism. The CB4 version

implemented in the UAM was last updated in 1993 by adding radical-radical interactions.

The hard-coded approach to the atmospheric chemical mechanism used in the UAM

prevents the implementation of newer and more up-to-date chemical mechanisms.

B-2.2. Flexible Chemical Mechanism Version of the Urban Airshed

Model

The UAM-FCM was developed under contract for ARB (Kumar et al., 1995). The

UAM-FCM has a software package (the FCM) that reads a text file describing the

photochemical mechanism, and creates a set of mechanism-specific programs that are

then integrated into the UAM. The FCM allows the user to incorporate reaction-specific

photolytic rates, by providing a file for each photolytic reaction, with data on crosssection and quantum yield for each wavelength of interest. The UAM-FCM has a

generalized technique to solve the set of differential equations that is not mechanism

specific, but is accurate and robust. The current version of the UAM-FCM can handle up

to 220 chemical reactions (including up to 20 photolytic reactions), and up to 140

chemical species.
B-3

B-2.3. SAPRC97 Chemical Mechanism

Carter (1993, 1997) developed the atmospheric chemical mechanism designated as

SAPRC97 (version D), which is readily processed by the UAM-FCM software. To save

computing time in solving the set of differential equations that represent the reaction

mechanism, only a small number of hydrocarbon species are treated explicitly in this

mechanism. In the SAPRC series of mechanisms, hydrocarbons are grouped together

using the lumped-molecule approach. In this approach the reactions of many alkanes,

alkenes, and aromatic species that are present in the emission inventory are represented

by lumped reaction mechanisms (Carter, 1990). The computer software calculates the

kinetic rates and product yield parameters for the lumped species that best represent the

unique hydrocarbon mixture in the emission inventory (Carter, 1988; Carter 1990). For

this study the one-product mechanism is used to represent the reactions of isoprene

(Carter, 1996). In addition, explicit reaction mechanisms (as opposed to a lumped

representation) for several compounds of interest (such as benzene, 1,3-butadiene,

ethanol, and methyl tertiary-butyl ether) were added to the original version of the

SAPRC97. It was also desired to distinguish between acetaldehyde and formaldehyde

formed as by-products of photochemical reactions (secondary), from those emitted

directly from sources (primary). The explicit reactions for the additional species were

obtained from Dr. Carter’s ftp site (ftp://cert.ucr.edu/pub/carter/mech/saprc97).

A complete listing of this photochemical mechanism is provided in the Attachment B1. The list of hydrocarbon species that are treated explicitly is given in Table 2.1. Note

that in the SAPRC97 chemical mechanism, PPN is used to lump peroxypropionyl nitrate

and higher molecular weight acyl peroxy nitrates. Thus, modeled PPN cannot be

compared directly with measured PPN. In addition to the species listed in Table 2.1, the

photochemical mechanism includes a large number of species that are generated by the

oxidation of hydrocarbons, as well as a set of chemical reactions that represents the

inorganic reactions that take place in air. The mechanism used in our simulations has a

total of 99 species and 204 reactions, of which 20 are photolytic. Of the 99 species, 29

are treated as steady state, 4 species are held constant, and hourly average concentrations

are generated by the UAM-FCM for the other 66 species.
B-4

Table 2.1 List of Hydrocarbon Species Treated Explicitly in SAPRC97

Name Symbol

Formaldehyde (secondary) HCHO

Formaldehyde (primary) FORM

Acetaldehyde (secondary) CCHO

Acetaldehyde (primary) ALD

Acetone ACET

Methyl ethyl ketone MEK

Peroxyacetyl nitrate PAN

Peroxypropionyl nitrate and higher molecular weight

acyl peroxy nitrates

PPN

Methane CH4

Ethene ETHE

Isoprene ISOP

Benzene C6H6

1,3-Butadiene BUTD

p-Dichlorobenzene PDCB

Perchloroethylene PERC

Dichloromethylene DICM

Ethanol ETOH

Methyl tertiary-butyl ether MTBE

Glyoxal GLY

Methyl Glyoxal MGLY

Benzaldehyde BALD

Cresols CRES

Phenols PHEN

B-2.4. Computer

The executable UAM-FCM files were prepared and compiled according to the

recommended procedure by Kumar et al. (1995). The emission inventory corresponding

to each year and case under study were used to calculate the reaction rates and product

yields of the lumped species. All simulations were run on a Unix workstation. The time

to run a 24-hour episode simulation was about 2 hours and twenty minutes.
B-5

Figure 2.1 Modeling Domain
B-6

B-3. Model Input Description

B-3.1. Episode and Domain

The UAM-FCM was applied to a three-day summer ozone episode in the South

Coast, the August 26-28, 1987 Southern California Air Quality Study (SCAQS) episode

(Lawson, 1990). The SCAQS domain has been gridded into 65 x 40 x 5 cells. Each

horizontal square cell is 5 x 5 km2, with varying vertical height. The origin of the domain

is at (275, 3670) in UTM coordinates (Zone 11). The domain is shown in Figure 2.1. It

includes the counties of Los Angeles, Orange, and Kern, and portions of Riverside, San

Diego, San Bernardino, and Ventura counties.

The August 26-28, 1987 SCAQS episode corresponds to an episode with very high

observed ozone concentrations. We believe that the meteorological conditions of the

episode represent close to worst-case conditions conducive to high pollutant

concentrations. The SCAQS domain also contains a large fraction of the population in

the State. Therefore, this episode and domain also represent worst-case conditions for

exposure analysis of photochemically generated pollutants (e.g., ozone, NO2,

acetaldehyde, formaldehyde, PAN and PPN). For these reasons we believe that modeling

of this single episode is sufficient for our study. Therefore, the meteorology of the

August 26-28, 1987 SCAQS episode will be used in conjunction with the VOC and NOx

emissions appropriate for the year 1997, and 2003 scenarios described in Table 3.2.

Worst-case conditions for directly emitted pollutants (e.g., CO, benzene, 1,3-butadiene,

ethanol, and MTBE) are more readily inferred from air quality measurement (see

Appendix C).

B-3.2. Basic Input Files

The UAM-FCM requires 13 input files that provide information on the initial and

boundary conditions of the domain, temperature, wind direction, wind speed, terrain,

photolytic rates, reaction rate constants, and product yields, and emissions from area and

point sources. Mobile sources and biogenic emissions are included in the area source

file. The files used in our simulations, (except for the initial and boundary conditions,

and area and point source emissions) were prepared by the South Coast Air Quality

Management District for the 1994 State Implementation Plan (SCAQMD, 1994). The

same diffusion break, region top, metscalars, terrain, temperature, and meteorological

input files were used in all simulations, since these characterize the meteorological

conditions for the episode and terrain. Table 3.1 provides a description of these files.

Other files, such as initial and boundary conditions, point sources and area emissions

were created for each specific simulation.
B-7

Table 3.1 List of the Meteorological and Terrain Files for the SCAQS

August 26-28, 1987 Episode

Input File Identification Description

ms238d11.b, ms239d11.b, ms240d11.b Metscalar file

sim238bl, sim239bl, sim240bl Control file

df238d11.b Diffusion break file

tm238d11.b, tm239d11.b, tm240d11.b Temperature file

rt238d11.b Region top file

tr238d11.b Terrain file

wd238d11.b, wd239d11.b, wd240d11.b Wind file

B-3.3. Region Top and Boundary Conditions

The region top and boundary conditions (together with the point and area sources) are

specific to each of the different scenarios considered in this modeling study. The

scenarios considered include the years 1997 and 2003 with different types of gasoline.

These scenarios are listed in Table 3.2.

Table 3.2 Scenarios Considered for the Photochemical Modeling

Scenario Description of Motor Vehicle Fuel Used

1997 MTBE Current MTBE-based California Phase 2 Reformulated Gasoline (CaRFG)

2003 MTBE Year 2003 MTBE-based CaRFG

2003 Et2.0% Year 2003 Ethanol-based fully complying fuel (with oxygen content of 2.0 wt%)

2003 Et3.5% Year 2003 Ethanol-based fully complying fuel (with oxygen content of 3.5 wt%)

2003 NonOxy Year 2003 Non-oxygenated fully complying fuel

The region top and boundary condition files describe the air quality at the boundaries

of the domain under study. These two files specify hourly ambient levels of each of the

species in the SAPRC mechanism. For these simulations the region top and boundary

conditions were treated as constant for all species throughout the episode. Region top

concentrations were essentially the same as those used for the boundary conditions.

Table 3.3 and Table 3.4 show the pollutant concentrations used for the boundary and

region top, respectively.
B-8

Table 3.3 Baseline Boundary Concentration (ppb)

Species 1997 MTBE 2003 MTBE 2003 Et2.0% 2003 Et3.5% 2003 NonOxy

O3 40.0 40.0 40.0 40.0 40.0

NO 0.9095 0.8285 0.8285 0.8285 0.8285

NO2 1.6832 1.4 1.4 1.4 1.4

N2O5 1.0 1.0 1.0 1.0 1.0

HONO 0.08371 0.06913 0.06913 0.06913 0.06913

CO 200.0 200.0 200.0 200.0 200.0

CO2 1000.0 1000.0 1000.0 1000.0 1000.0

CCHO 0.5 0.53 0.53 0.53 0.53

HCHO 0.5 0.5 0.5 0.5 0.5

RCHO 0.98 0.98 0.98 0.98 0.98

ETHE 0.829 0.7626 0.7626 0.7626 0.7626

CH4 1720.0 1720.0 1720.0 1720.0 1720.0

ALK1 0.49 0.49 0.49 0.49 0.49

ALK2 1.01 1.01 1.01 1.01 1.01

ARO1 0.4273 0.3962 0.3962 0.3962 0.3962

ARO2 0.14507 0.13538 0.13538 0.13538 0.13538

OLE1 0.7048 0.69056 0.69056 0.69056 0.69056

OLE2 0.01 0.01 0.01 0.01 0.01

C6H6 0.08 0.08 0.08 0.08 0.08

NO3 1.0 1.0 1.0 1.0 1.0

HO2 0.1 0.1 0.1 0.1 0.1

MTBE 0.1 0.1 0.01 0.01 0.01

ETOH 0.01 0.01 0.3 0.41 0.01

All other species 0.01 0.01 0.01 0.01 0.01
B-9

Table 3.4 Region Top Concentrations (ppb)

Species 1997 MTBE 2003 MTBE 2003 Et2.0% 2003 Et3.5% 2003 NonOxy

O3 40.0 40.0 40.0 40.0 40.0

NO 0.9095 0.8285 0.8285 0.8285 0.8285

NO2 1.6832 1.4 1.4 1.4 1.4

N2O5 1.0 1.0 1.0 1.0 1.0

HONO 0.08371 0.06913 0.06913 0.06913 0.06913

CO 200.0 200.0 200.0 200.0 200.0

CO2 1000.0 1000.0 1000.0 1000.0 1000.0

CCHO 0.5 0.53 0.53 0.53 0.53

HCHO 0.5 0.5 0.5 0.5 0.5

RCHO 0.98 0.98 0.98 0.98 0.98

ETHE 0.829 0.7626 0.7626 0.7626 0.7626

CH4 1720.0 1720.0 1720.0 1720.0 1720.0

ALK1 0.49 0.49 0.49 0.49 0.49

ALK2 1.0 1.0 1.0 1.0 1.0

ARO1 0.4218 0.3912 0.3912 0.3912 0.3912

ARO2 0.14507 0.13538 0.13538 0.13538 0.13538

OLE1 0.7048 0.69056 0.69056 0.69056 0.69056

OLE2 0.01 0. 01 0.01 0. 01 0. 01

C6H6 0.08 0. 08 0. 08 0. 08 0. 08

NO3 1.0 1.0 1.0 1.0 1.0

HO2 0.1 0.1 0.1 0.1 0.1

MTBE 0.1 0.1 0.01 0.01 0.01

ETOH 0.01 0.01 0.3 0.41 0.01

All other species 0.01 0.01 0.01 0.01 0.01

B-3.4. Initial Conditions

All simulations were started with the same initial conditions given in Table 3.5.

Because of this, only the results of the last simulation day, August 28, are used in the

analysis. The results of the last simulation day, based on our past experience, are

insensitive to the initial conditions.
B-10

Table 3.5 Initial Species Concentrations (ppb)

Species Concentration

O3 70.0

NO 1.0

NO2 2.0

HNO3 0.1

HONO 0.1

CO 200.0

CO2 0.1

H2O2 0.1

CCHO 1.1

HCHO 5.8

RCHO 0.98

ETHE 1.4

CH4 1720.0

ALK1 0.49

ALK2 1.01

ARO1 0.7

ARO2 0.23

OLE1 0.83

OLE2 0.23

OLE3 0.00

C6H6 0.16

All other species 0.01

B-3.5. Point and Area Sources

Point source emission and area source emission files were prepared for each specific

scenario studied. The preparation of each file is discussed in Appendix A.

B-3.6. Air Quality Monitoring Sites

Table 3.6 lists the 20 air quality monitoring sites in the South Coast modeling domain

used to analyze the results of each different scenario studied. In addition to these sites,

the domain maximum was also used. Table 3.6 shows the site locations in the domain.
B-11

Table 3.6 Sites in the Modeling Domain Used to Study the Impact of Each of the

Scenarios Studied

Site Name Id

Anaheim ANAH

Azusa AZUS

Burbank BURK

Los Angeles North Main CELA

Costa Mesa - Mesa Verde Drive COMV

Hawthorne HAWT

La Habra LABH

North Long Beach LGBH

Lynwood LYNN

Pasadena - S. Wilson Avenue PASA

Pico Rivera PICO

Pomona POMA

Reseda RESE

Riverside - Rubidoux RIVR

Riverside - Magnolia RIVM

Santa Clarita - County Fire Station SCFE

San Bernardino - 4th Street SNB4

El Toro TORO

Upland UPLA

West Los Angeles - VA Hospital WSLA

B-4. Results

As indicated above, only the results of the third day of the episode simulated

(August 28) were used in the analysis to avoid dependence on the initial conditions.

B-4.1. Domain Maximum 1-Hour-Average Concentrations

Table 4.1 shows the domain maximum concentration of the pollutants of interest for

each scenario simulated. As shown in Table 4.1, the domain maximum ozone decreases

(6 - 8%) from 1997 to 2003 because of reductions in overall emissions. CO shows a

more significant decrease (25 - 35%). Nitric acid and ethanol both decrease by up to 9%.

The maximum 1-hour-average ethanol concentration is dominated by a non-motor

vehicle emission source. Although total ethanol emissions increase from 1997 to the
B-12

2003 ethanol-containing fuel scenarios, emissions from a single stationary source (which

dominates the magnitude of the maximum ethanol concentration) have decreased. In

general the predicted concentrations do not show a large change from 1997 to 2003 for

most of the pollutants, except for NO, NO2, CO, benzene, ethanol, and nitric acid.

Maximum ozone concentrations among the year 2003 simulations are very similar,

within 1-2%. CO concentration is higher for the NonOxy scenario among the 2003

simulations, and is lowest for the Et3.5% scenario.

Table 4.1 Domain Maximum 1-Hour-Average Concentrations for Each Scenario

Domain Maximum 1-Hour-Average Concentration (ppb)

Simulation O3 NO NO2 CO Formald

ehyde

Acetald

ehyde

C6H6 BUTD MTBE ETOH PAN PPN HNO3

1997 MTBE 235.9 214.3 105.3 3,023.6 22.7 9.2 3.4 3.0 6.1 45.6 4.4 1.4 57.7

2003 MTBE 222.2 190.7 97.2 2,189.1 23.0 8.7 1.9 3.0 3.9 41.4 4.2 1.4 52.3

2003 Et2.0% 220.2 190.6 97.0 2,189.1 22.7 8.8 1.9 3.0 0.0 42.3 4.1 1.4 52.3

2003 Et3.5% 221.0 190.6 97.1 2,083.3 22.9 8.9 2.0 3.0 0.0 42.8 4.2 1.4 52.2

2003 NonOxy 220.4 190.6 97.0 2,262.6 22.7 8.8 1.9 3.0 0.0 41.4 4.0 1.4 52.4

a Formaldehyde and acetaldehyde refer to total concentrations from primary emissions and secondary

formation, C6H6 is benzene, BUTD is 1,3-butadiene, MTBE is methyl tertiary-butyl ether, ETOH is ethanol,

PAN is peroxyacetyl nitrate, PPN represents peroxypropionyl nitrate and higher molecular weight acyl

peroxy nitrates, and HNO3 is nitric acid.

The model predicts a domain maximum 1-hour PAN concentration of 4.2 ppb and

4.1 ppb for the 2003 MTBE, and 2003 Et2.0% scenarios, respectively. The differences in

predicted PAN concentrations for each scenario are due to differences in the emissions of

various VOCs with higher PAN formation potentials than ethanol. From Table 4.9 in

Appendix A, it is clear that the 2003 Et2.0% scenario has higher ethanol emissions than

the 2003 MTBE. However, the 2003 MTBE has higher emissions of alkanes, aromatics,

and olefins compared to the 2003 Et2.0%. Figure 7.3 and Figure 7.4 in later in the

appendix suggest that the lumped species ALK2, ARO2, OLE1, OLE2, and OLE3 can

have (depending on the environmental conditions) higher PAN formation potentials than

ethanol. Another factor is that although ethanol emissions are higher in the 2003 Et2.0%

scenario, they only represent 8% of the nonmethane VOC emissions. For comparison,

ALK2, ARO2, OLE1, OLE2, and OLE3 comprise about 31% of the nonmethane VOC

emissions in 2003 Et2.0%. Hence, PAN formation is primarily governed by the

differences in alkane, aromatic, and olefinic emissions between scenarios, rather than the

emissions of ethanol.

Figure 4.1 through Figure 4.5 show hourly the 1997 and 2003 scenarios for ozone,

NO, and NO2, at Anaheim (ANAH), Burbank (BURK), downtown Los Angeles (CELA),

Riverside-Rubidoux (RIVR), and at the grid cell with the domain maximum (GMX). The

time plots clearly show that the 1997 and 2003 scenarios have very similar predicted
B-13

ozone concentrations during the last day of the simulation. There are significant

differences in predicted NO2 concentrations between 1997 and 2003, as expected. All

2003 scenarios have the essentially the same predicted NO and NO2 hourly

concentrations.

Figure 4.6 through Figure 4.10 show ethanol, MTBE, and CO time series plots for

Anaheim, Burbank, downtown Los Angeles, Riverside-Rubidoux, and at the grid with the

domain maximum. The plots are only for the 2003 scenarios (Et2.0%, Et3.5%, NonOxy,

and MTBE). As expected, the 2003 Et3.5% scenario has highest predicted ethanol

concentrations, while the 2003 MTBE is the only scenario with significant MTBE hourly

concentrations among all the 2003 scenarios.

Figure 4.11 through Figure 4.15 show time series plots of hourly PAN (and higher

molecular weight acyl peroxy nitrates), and nitric acid concentrations for the 1997 and

2003 scenarios, at Anaheim, Burbank, downtown Los Angeles, Riverside-Rubidoux, and

at the domain maximum. Predicted PAN, PPN, and nitric acid concentrations are the

same for all 2003 scenarios. Both PAN and PPN show a large maximum on the second

day of the episode that has significantly decreased by the third day of the episode

simulated.

From Figure 4.1 through Figure 4.5, it is clear that although hydrocarbon and NOX

emissions decreased from 1997 to 2003, the reduction did not significantly impact the O3,

NO, and NO2 levels predicted by the photochemical mechanism. This is confirmed by

the small impact on the predicted maximum ozone concentrations. In addition, the NOXto-hydrocarbon ratio may not have significantly changed from 1997 to 2003, which may

explain the essentially similar PAN, PPN (and higher molecular weight acyl peroxy

nitrates), and nitric acid predicted concentrations for these years (see Figure 4.11 through

Figure 4.15).
B-14

Figure 4.1 Time Series for Ozone, NO2, and NO at Anaheim for 1997 and 2003

Scenarios
B-15

Figure 4.2 Time Series for Ozone, NO2, and NO at Burbank for 1997 and 2003

Scenarios
B-16

Figure 4.3 Time Series for Ozone, NO2, and NO at Los Angeles for 1997 and

2003 Scenarios
B-17

Figure 4.4 Time Series for Ozone, NO2, and NO at Riverside for 1997 and 2003

Scenarios
B-18

Figure 4.5 Time Series for Ozone, NO2, and NO at Grid with Domain Maximum

for 1997 and 2003 Scenarios
B-19

Figure 4.6 Time Series for MTBE, Ethanol, and CO at Anaheim for 2003

Scenarios
B-20

Figure 4.7 Time Series for MTBE, Ethanol, and CO at Burbank for 2003

Scenarios
B-21

Figure 4.8 Time Series for MTBE, Ethanol, and CO at Los Angeles for 2003

Scenarios
B-22

Figure 4.9 Time Series for MTBE, Ethanol, and CO at Riverside for 2003

Scenarios
B-23

Figure 4.10 Time Series for MTBE, Ethanol, and CO at Grid with Domain

Maximum for 2003 Scenarios
B-24

Figure 4.11 Time Series for PAN, PPN, and Nitric Acid at Anaheim for 1997

and 2003 Scenarios
B-25

Figure 4.12 Time Series for PAN, PPN, and Nitric Acid at Burbank for 1997

and 2003 Scenarios
B-26

Figure 4.13 Time Series for PAN, PPN, and Nitric Acid at Los Angeles for 1997

and 2003 Scenarios
B-27

Figure 4.14 Time Series for PAN, PPN, and Nitric Acid at Riverside for 1997

and 2003 Scenarios
B-28

Figure 4.15 Time Series for PAN, PPN, and Nitric Acid at Grid with Domain

Maximum for 1997 and 2003 Scenarios
B-29

B-4.2. Domain Maximum 8-Hour-Average Concentrations

Table 4.2 shows domain maximum 8-hour-average concentrations for selected

pollutants. As shown, the 8-hour-average ozone concentration decreases by up to 5%

from 1997 to 2003. CO is reduced by up to 32% for the Et3.5% scenario. Similarly, the

8-hour benzene concentration is reduced by 37% between 1997 and 2003. The 8-houraverage formaldehyde is reduced by 4%, but the 8-hour-average acetaldehyde decreases

by up to 13% from 1997. The 8-hour nitric acid predicted concentration is seen to

decrease by 5% from 1997 to 2003, while 8-hour PPN and BUTD are essentially

unchanged. PAN and ethanol 8-hour-average concentrations decrease by up to 9% from

1997 baseline. As discussed in SectionB-4.1, the predicted ethanol concentrations are

dominated by non-motor vehicle sources, which may explain the predicted decrease in

ethanol 8-hour-average concentrations

Table 4.2 Domain Maximum 8-Hour-Average Concentrations for Each Scenario

Domain Maximum 8-Hour-Average Concentrationa (ppb)

Simulation O3 NO NO2 CO Formald

ehyde

Acetald

ehyde

C6H6 BUTD MTBE ETOH PAN PPN HNO3

1997 MTBE 187.3 150.3 86.4 2,432 16.8 7.7 2.46 2.08 4.1 40.9 3.25 0.99 47.9

2003 MTBE 177.9 133.4 75.0 1,816 16.3 6.7 1.60 2.05 2.7 37.2 2.98 0.94 45.6

2003 Et2.0% 178.0 133.2 74.9 1,816 16.1 6.8 1.59 2.05 0.0 38.0 2.98 0.94 45.5

2003 Et3.5% 178.1 133.2 74.9 1,741 16.2 6.8 1.61 2.05 0.0 38.5 3.01 0.94 45.5

2003 NonOxy 178.3 133.2 75.0 1,872 16.1 6.8 1.56 2.05 0.0 37.2 2.96 0.95 45.6

a Formaldehyde and acetaldehyde refer to total concentrations from primary emissions and secondary

formation, C6H6 is benzene, BUTD is 1,3-butadiene, MTBE is methyl tertiary-butyl ether, ETOH is ethanol,

PAN is peroxyacetyl nitrate, PPN represents peroxypropionyl nitrate and higher molecular weight acyl

peroxy nitrates, and HNO3 is nitric acid.

B-4.3. Domain Maximum 24-Hour-Average Concentrations

Table 4.3 shows maximum 24-hour-average concentrations in the domain for

selected pollutants. As shown, the 24-hour-average ozone concentration decreases by up

to 4% from 1997 to 2003. CO is reduced by up to 29% for the 2003 Et3.5% scenario.

Similarly, the 24-hour benzene concentration is reduced by almost 37% between 1997

and 2003. The 24-hour-average formaldehyde is reduced by up to 16%, but the 24-houraverage acetaldehyde is unchanged. The 24-hour nitric acid concentration is seen to

decrease by 12% from 1997 to 2003, while PPN decreases by 2% for the 2003 Et3.5%,

increases by 3% for the 2003 NonOxy, and is unchanged for the 2003 MTBE ands 2003

Et2.0%. The impact on 24-hour PAN concentration is also modest, with a decrease of up

to 6% for the 2003 NonOxy scenario. The 24-hour-average ethanol concentration is

reduced up to 9% for the 2003 NonOxy case. As discussed in SectionB-4.1, the
B-30

predicted ethanol concentrations are dominated by non-motor vehicle sources, which may

explain the predicted decrease in ethanol 24-hour-average concentrations.

Table 4.3 Domain Maximum 24-Hour-Average Concentrations For Each

Scenario

Domain Maximum 24-Hour-Average Concentrationa (ppb)

Simulation O3 NO NO2 CO Formald

ehyde

Acetald

ehyde

C6H6 BUTD MTBE ETOH PAN PPN HNO3

1997 MTBE 148.0 66.2 72.8 1,614 11.35 6.2 1.72 0.88 2.63 19.05 2.12 0.58 36.73

2003 MTBE 142.7 57.8 60.7 1,252 9.90 6.2 1.10 0.88 1.67 17.35 2.03 0.58 32.41

2003 Et2.0% 142.7 57.7 60.4 1,252 9.57 6.2 1.09 0.87 0.00 17.89 2.02 0.58 32.28

2003 Et3.5% 142.8 57.7 60.5 1,206 9.78 6.2 1.10 0.88 0.00 18.14 2.06 0.58 32.27

2003 NonOxy 142.9 57.7 60.5 1,286 9.49 6.2 1.06 0.87 0.00 17.36 2.00 0.60 32.28

a Formaldehyde and acetaldehyde refer to total concentrations from primary emissions and secondary

formation, C6H6 is benzene, BUTD is 1,3-butadiene, MTBE is methyl tertiary-butyl ether, ETOH is ethanol,

PAN is peroxyacetyl nitrate, PPN represents peroxypropionyl nitrate and higher molecular weight acyl

peroxy nitrates, and HNO3 is nitric acid.

B-5. Sensitivity Simulations

Sensitivity analysis is an evaluation of the model response to variations in one or

more of the model inputs. The sensitivity simulations performed in our study represent

the cumulative effect of 1) use of EMFAC2000 instead of EMFAC7G, 2) consideration

of chlorine radical chemistry, 3) use of updated rate constants for the reactions of

hydroxyl radical with ethanol and MTBE, and 4) revised boundary conditions. The

sensitivity simulations considered for this study are listed in Table 5.1, and a brief

description of the each of the effects considered in the sensitivity simulations is provided

below.

B-5.1. Increasing Motor Vehicle Hydrocarbon and CO Emissions

The on-road motor vehicle emissions were increased to evaluate the potential impact

of using EMFAC2000 (ARB, 1999) instead of EMFAC7G. EMFAC2000 was not

available at the time of this study, but emissions from motor vehicles increase

substantially with EMFAC2000. A large increase in hydrocarbon emissions will change

the NOX-to-hydrocarbon ratio and potentially impact the radical flux. This may increase

the photochemical oxidation of ethanol and lead to increase acetaldehyde and PAN

impacts. For this purpose, hydrocarbon emissions were multiplied by a factor of three to

place an upper-limit to the impact of using EMFAC2000, which at one time proposed

multiplication factors of 2.34 and 1.84 for the 2000 on-road motor vehicle emission
B-31

inventory in the South Coast Air Basin for hydrocarbons and NOX, respectively. The

factor of three is also consistent with an independent fuel-based inventory for the South

Coast Air Basin in 1997 which proposes a multiplication factor of 3.5±0.6 for on-road

motor vehicle hydrocarbon emissions of stabilized exhaust (Singer and Harley, 2000).

The Singer and Harley (2000) fuel-based inventory is for stabilized exhaust emissions

and does not include cold start or evaporative emissions, so it is not necessarily

inconsistent with draft versions of EMFAC2000. We also have some concerns with

Singer and Harley's methodology (primarily lack of freeway measurements where

gm/gallon emission rates are likely to be lower) and view it as an upper-bound estimate.

The motor vehicle CO emissions were also increased by a factor of three to represent the

impact of using EMFAC2000, which proposes a significant (a factor of about three)

increase of motor vehicle CO emissions.

Table 5.1 Sensitivity Scenarios

Scenario Description

1997 MTBE Sens Increased on-road motor vehicle ROG and motor vehicle CO by factor

of 3 for the 1997 MTBE fuel, added of chlorine + ethanol reaction,

updated OH radical rate constant for OH + ethanol, and OH + MTBE,

and used revised boundary conditions

2003 MTBE Sens Increased on-road motor vehicle ROG and motor vehicle CO by factor

of 3 for the 2003 MTBE fuel, added of chlorine + ethanol reaction,

updated OH radical rate constant for OH + ethanol, and OH + MTBE,

and used revised boundary conditions

2003 Et2.0% Sens Increased on-road motor vehicle ROG and motor vehicle CO by factor

of 3 for the 2003 Et2.0% fuel, added of chlorine + ethanol reaction,

updated OH radical rate constant for OH + ethanol, and OH + MTBE,

and used revised boundary conditions

2003 Et3.5% Sens Increased on-road motor vehicle ROG and motor vehicle CO by factor

of 3 for the 2003 Et3.5% fuel, added of chlorine + ethanol reaction,

updated OH radical rate constant for OH + ethanol, and OH + MTBE,

and used revised boundary conditions

2003 NonOxy Sens Increased on-road motor vehicle ROG and motor vehicle CO by factor

of 3 for the 2003 NonOxy fuel, added of chlorine + ethanol reaction,

updated OH radical rate constant for OH + ethanol, and OH + MTBE,

and used revised boundary conditions

B-5.2. Potential Impact of the Chlorine Radical Reaction With Ethanol

In addition to the increase in on-road motor vehicle emissions described above,

the chemical mechanism used was modified in response to concerns on the impact of

including chlorine radical reactions in the atmospheric chemical mechanism (FinlaysonPitts, 1999). Reactions of chlorine radical with hydrocarbons are not part of SAPRC97

mechanism used in our study (see Attachment B1).
B-32

The chlorine (Cl) radical behaves similarly to the hydroxyl radical on its reaction

with hydrocarbons. Cl radicals can be generated during daylight through photolysis of

Cl2 present in the air (Spicer et al., 1998; Seinfeld and Pandis, 1998). Other sources of Cl

radical are sea salt interaction with nitrogen oxides, and the hydroxyl radical reaction

with the gaseous HCl produced by the acidification of sea salt with sulfuric acid or nitric

acid (Fantechi et al., 1998, and references cited therein). The Cl radical is known to have

a key role on the reactions that cause stratospheric ozone depletion (Seinfeld and Pandis,

1998). In addition, it has been recognized that it can also play a role in the tropospheric

oxidation of hydrocarbons near coastal areas (Finlayson-Pitts, 1999; de Haan et al., 1999;

Hov, 1985). Other reactive halogenated species, such as bromine and iodide, can also

play a role in the tropospheric ozone budget in some areas (Platt et al., 1999; Stutz et al.,

1999), but are not believed to be of relevance to the South Coast Air Basin.

A proper treatment of the Cl radical reactions in an atmospheric chemical

mechanism should include reactions of Cl radical with all hydrocarbons, including

methane, 1,3-butadiene, isoprene, MTBE, ethanol, benzene, and their reaction products

(for example, see Fantechi et al., 1998), including reactions with other inorganic species.

However, there are significant uncertainties in the reliability of models on chlorine

chemistry, because there are limited smog chamber data to test mechanisms for chlorine

radical reactions (Carter, 1999a). Hence, the addition of Cl radical reactions will require

a revision of the atmospheric chemical mechanism, which is outside the scope of this

study. A way to address, the potential impact of adding Cl radical reactions is to focus on

its effect on ethanol. We added a Cl radical reaction with ethanol, assuming the same

lumped products as with the OH reaction with ethanol in the SAPRC97 chemical

mechanism (see Attachment B3), and using a constant reaction rate of

9.4×1011 cm3molecule-1s

-1 (Finlayson-Pitts, 1999):

ETOH + CL = #.1 RO2-R + #.9 HO2 + #.156 HCHO + #.922 CCHO + #.1 RO2

The above reaction is a coarse approximation, since the reaction products and

product yields could be very different from the real reaction (for example, HCl is not

included as a byproduct of the Cl radical reaction with ethanol). Two additional

assumptions were made to place an upper-limit on the potential effect of including the Cl

radical reaction with ethanol. First, the reaction was not restricted to daylight hours only;

and, second, we assumed a constant Cl radical concentration of 1x104 atoms per cm3

(Finlayson-Pitts, 1999; Fantechi et al., 1998) throughout the domain. The impact of

adding the above reaction is to greatly increase the oxidation of ethanol and lead to

increased acetaldehyde and PAN impacts. It is expected that the maximum impact will

be for the 2003 Et3.5% scenario, because of the higher ethanol emission rates in the

inventory, relative to the other scenarios.
B-33

B-5.3. Updated Rate Constants

In response to comments received (Atkinson, 1999a), we also revised, for the

sensitivity simulations, the rate constants used in our chemical mechanism so that the

OH + ETOH reaction will have a rate constant given by

k=5.56×1013(T/300)2exp(532/T) cm3molecule-1s

-1, and the OH + MTBE reaction the rate

constant was updated to be k=5.89×10-13(T/300)2exp(483/T) cm3molecule-1s

-1 (Atkinson,

1999b). These changes increased the OH + ethanol rate constant by only 0.03%, and the

OH + MTBE rate constant by 3.8%, with respect to the values originally used (see

Attachment B.3). The use of the revised kinetic rate constants will increase slightly the

photochemical oxidation of ethanol and MTBE.

B-5.4. Revised Boundary Conditions

In response to comments received (Atkinson, 1999a), we also revised the HONO,

N2O5, and NO3 concentrations used in the boundaries and top concentration when

performing the sensitivity simulations. The revised concentrations are shown in

Table 5.2. The HONO boundary and top concentrations used in the sensitivity

simulations are larger by a factor of 9 for the 1997 MTBE sens, and by a factor of 8 for

the 2003 scenarios than those used in the baseline simulations (see Table 3.3 and

Table 3.4). The N2O5 and NO3 concentrations used in the boundaries and top

concentration are lower by a factor of three for the 1997 MTBE sens, and by a factor of

50 for the 2003 scenarios than those used in the baseline simulations (see Table 3.3 and

Table 3.4). The reason for using higher N2O5 and NO3 in the boundaries and top

concentrations for the 1997 MTBE sens was dictated by the model’s ability to resolve the

set of non-linear simultaneous equations represented by the chemical reactions. Use of

lower N2O5 and NO3 concentrations in the 1997 MTBE sens scenario will cause the

model to not to converge on a solution due to very stiff conditions. We do not believe

that the different N2O5 and NO3 boundary and top concentrations used for the 1997 and

2003 sensitivity scenarios will affect any of the conclusions derived from the results of

these simulations.

Table 5.2 Boundary and Top Concentrations Used in the Sensitivity Simulations

(ppb)

Sensitivity Simulation HONO N2O5 NO3

1997 MTBE Sens 0.784 0.307 0.307

2003 MTBE Sens 0.660 0.020 0.020

2003 Et2.0% Sens 0.660 0.020 0.020

2003 Et3.5% Sens 0.660 0.020 0.020

2003 NonOxy Sens 0.660 0.020 0.020
B-34

B-5.5. Sensitivity Results

The predicted domain maximum 1–hour-average concentrations from the sensitivity

simulations are given in Table 5.3. The results in Table 5.3 reflect the factor of three

increase in on-road motor vehicle hydrocarbon and CO emissions, the use of revised rate

constants for the OH + ethanol and OH + MTBE reactions, the effect of the Cl + ethanol

reaction, and the revised top concentrations and boundaries, as described above. By

comparing Table 4.1 and Table 5.3, it is clear that the predicted domain maximum 1-

hour-average concentrations increased significantly for many species when the motor

vehicle hydrocarbon emissions were increased by a factor of three. Ethanol, 1,3-

butadiene, and nitric acid are notable exceptions. As discussed in SectionB-4.1, the

maximum 1-hour-average ethanol concentration is dominated by a non-motor vehicle

emission source. The 1,3-butadiene domain maximum 1-hour concentration occurs at

0400 over the same location in Ventura County (upwind from the Los Angeles urban

area) for all the sensitivity scenarios. At this hour, only nighttime reactions of 1,3-

butadiene with NO3 radical and O3 are important. Assuming a nighttime O3 concentration

of 100 ppb, and a NO3 radical concentration of 0.02 ppb, the NO3 radical reaction is a

factor of 3 faster than the O3 reaction. The lack of sensitivity of 1,3-butadiene domain

maximum 1-hour concentration to hydrocarbon emission increases is then presumably

due to a local source. Nitric acid is formed by reaction of NO2 with the hydroxyl radical.

Hydroxyl radical concentrations increase as ozone increases, so nitric acid concentrations

appear to be limited by NOX emissions for this summertime episode, especially for the

2003 scenarios.

Table 5.3 Domain Maximum 1-Hour-Average Concentrations for Sensitivity

Simulations

Domain Maximum 1-Hour-Average Concentration (ppb)

Simulation O3 NO NO2 CO Formald

ehyde

Acetald

ehyde

C6H6 BUTD MTBE ETOH PAN PPN HNO3

1997 MTBE

Sens

425 214 120 7,448 37.4 19.1 9.1 3.1 16.5 45.2 18.1 5.7 69.8

2003 MTBE

Sens

331 191 97 4,982 26.2 13.4 4.7 3.1 9.9 41.1 11.4 3.7 54.4

2003 Et2.0%

Sens

318 191 97 4,982 24.8 13.7 4.6 3.1 0.0 43.1 10.9 3.7 54.2

2003 Et3.5%

Sens

323 191 97 4,670 25.6 14.7 4.7 3.1 0.0 44.2 11.7 3.6 54.1

2003 NonOxy

Sens

317 191 97 5,193 24.6 13.3 4.3 3.1 0.0 41.1 10.4 3.8 54.4

a Formaldehyde and acetaldehyde refer to total concentrations from primary emissions and secondary

formation, C6H6 is benzene, BUTD is 1,3-butadiene, PAN is peroxyacetyl nitrate, PPN represents

peroxypropionyl nitrate and higher molecular weight acyl peroxy nitrates, and HNO3 is nitric acid
B-35

The 1997 MTBE sensitivity scenario shows a larger increase in maximum

concentrations for many species than the 2003 sensitivity scenarios. For example, the

predicted maximum 1-hour-average ozone concentration increases by a factor of 1.8 from

the 1997 MTBE base case to the 1997 MTBE sensitivity simulation, whereas it only

increases by an average factor of 1.46 for the 2003 scenarios. Acetaldehyde increases by

a factor of 2.1 in 1997 when motor vehicle hydrocarbon emissions are tripled, but it only

increases by a factor of 1.51 for the 2003 NonOxy scenario. Similarly, formaldehyde

increases by factor of 1.65 for the 1997 MTBE scenario, but only a factor of 1.08 for the

2003 NonOxy scenario. This difference also occurs for benzene, PAN, and PPN.

Presumably, these differences are because the motor vehicle emissions are a larger

fraction of the total inventory in 1997 as compared to 2003 (42% of ROG in 1997 versus

30% in 2003).

The major finding is that the predicted maximum 1-hour-average concentrations for

acetaldehyde and PAN from the ethanol-containing gasoline (Et3.5%) are now 1.4 ppb

and 1.3 ppb, respectively, greater than the maximum predicted for the non-oxygenated

gasoline (NonOxy). These acetaldehyde and PAN impacts from the ethanol-containing

gasoline represent an upper limit because the factor of three increase in all on-road

hydrocarbon emissions is larger than expected from EMFAC2000 when it becomes final

and the ozone episode modeled here is an extreme ozone event.

B-6. Model Performance

A performance evaluation is the process of establishing that the air quality model is

adequately reproducing the chemical and physical processes that generate ozone and

other pollutants. One aspect of model performance includes the sensitivity simulations

described in SectionB-5. In this section we test the model’s ability to reproduce

measured air quality data. For this purpose, an area and point emission inventory was

prepared for a 1987 baseline simulation. Differences and ratios of observed and

simulated maximum concentrations were calculated for each day of the August 26-28,

1987 episode in the SCAQS domain. Historical model performance evaluations have

focused on ozone, and to a lesser extent, NO2. Results are presented for other pollutants

under study, including CO, NO, PAN, acetaldehyde, benzene, 1,3-butadiene, and

formaldehyde. Although nitric acid data is available from the 1987 SCAQS field

program, UAM-FCM does consider the thermodynamic equilibrium of nitric acid with

ammonia and ammonium nitrate. We were also unable to conduct a model performance

evaluation for ethanol, MTBE, or PPN, as there are no air quality measurements available

for these pollutants for the 1987 episode.

B-6.1. Model Performance Statistics

Several statistical measures were used (ARB, 1992), including the Mean Absolute

Gross Error (MAGE):
B-36

∑

−

=

N

C C

MAGE s o

| |

(B-2)

where N is the number of observations, Cs is the simulated concentration and Co is the

observed concentration.

Mean Absolute Normalized Gross Error (MANGE):

∑

−

=

o

s o

C

C C

N

MANGE 1 | |(B-3)

Mean Bias (MBIAS):

∑

−

=

N

C C

MBIAS s o(B-4)

Normalized Mean Bias (NBIAS):

∑

−

=

o

s o

C

C C

N

NBIAS 1(B-5)

and the Unpaired Peak Estimation Accuracy (UPEA):

max

max max

o

s o

C

C C

UPEA

−

= (B-6)

Where Cs

max is the maximum estimated 1-hour concentration at any site in the

domain, and Co

max is the maximum observed 1-hour concentration at any site in the

domain.

B-6.2. Ozone, CO, NO, and NO2

The average statistics for all sites in the domain are given in Table 6.1 for August 28,

1987 (the last day of the 3-day simulation). The UAM-FCM SAPRC97 tends to overpredict maximum ozone by only 4%. The predicted maximum NO2 is within 10% of the

observed maximum, but the model significantly under-predicts maximum CO and NO, as

is typical for grid-based predictions of directly emitted compounds.

Table 6.1 UAM-FCM with SAPRC97 Model Performance Evaluation

O3

a COb NOc NO2d

UPEA (%) 4 -21 -56 7

MBIAS (ppb) 28 -142 -49 -14

MAGE (ppb) 38 771 51 31

NBIAS (%) 32 7 -71 -14

MANGE (%) 38 48 76 60

a Only ozone concentrations over 61 ppb were used.

b Only CO concentrations over 201 ppb were used.

c Only NO concentrations over 21 ppb were used.

d Only NO2 concentrations over 11 ppb were used.
B-37

Although the UAM has been widely applied to a number of episodes (see for

example, Morris and Meyers, 1990), the UAM-FCM, on the other hand, has had limited

application since its development in 1995. Therefore it was considered appropriate to

examine the model performance of the UAM-FCM when using a different chemical

mechanism, such as the Carbon-Bond IV (CB-IV).

The CB-IV chemical mechanism uses the lumped structure approach to represent the

atmospheric oxidation of hydrocarbons in ambient air (Gery et al., 1989). Carbon-bond

surrogates are used to represent the chemistry of the three most common type of carbon

bonds (single: PAR, double: OLE, and the CHO- group: ALD2), and two molecular

surrogates represent the chemistry of aromatic compounds (monoalkylbenzenes: TOL

based on toluene; dialkylbenzenes and trialkylbenzenes: XYL based on m-xylene).

Ethene, isoprene, ethanol, methanol, formaldehyde, methylglyoxal, glyoxal, and PAN are

treated explicitly.

Carbon-Bond IV (version 6.21) was implemented into the UAM-FCM. We speciated

area and point source emission files, together with initial and boundary conditions for the

August 26-28, 1987, for the CB-IV mechanism. Table 6.2 summarizes the performance

of the UAM-FCM with CBIV. Compared to the performance of the SAPRC97

mechanism in Table 6.1, CB-IV tends to under-predict maximum ozone concentration by

11% on the last day of the episode. However, both SAPRC97 and CB-IV have similar

average performance for CO, NO, and NO2. Overall, the UAM-FCM has similar model

performance with either SAPRC97 or CB-IV. Figure 6.1 through Figure 6.5 show a

comparison of ozone, NO and NO2, as predicted by SAPRC97 and CB-IV (together with

the measured concentrations), for Anaheim, Burbank, Downtown Los Angeles, and

Riverside. Figure 6.5 shows a comparison of ozone, NO, and NO2, as predicted by

SAPRC97 and CB-IV, for the cell with the maximum pollutant concentration in the

domain (no measured data are shown, since there is no monitoring station at this

location).

Table 6.2 UAM-FCM with CB4 Model Performance Evaluation

O3

a COb NOc NO2d

UPEA (%) -11 -23 -42 0

MBIAS (ppb) -1 -251 -38 -13

MAGE (ppb) 27 771 45 28

NBIAS (%) 5 0 -50 -12

MANGE (%) 24 46 67 56

a Only ozone concentrations over 61 ppb were used.

b Only CO concentrations over 201 ppb were used.

c Only NO concentrations over 21 ppb were used.

d Only NO2 concentrations over 11 ppb were used.
B-38

Figure 6.1 Comparison of Predicted Ozone, NO, and NO2 by SAPRC97 and CBIV Against Ambient Data at Anaheim (1987 SCAQS)
B-39

Figure 6.2 Comparison of Predicted Ozone, NO, and NO2 by SAPRC97 and CBIV Against Ambient Data at Burbank (1987 SCAQS)
B-40

Figure 6.3 Comparison of Predicted Ozone, NO, and NO2 by SAPRC97 and CBIV Against Ambient Data at Los Angeles (1987 SCAQS)
B-41

Figure 6.4 Comparison of Predicted Ozone, NO, and NO2 by SAPRC97 and CBIV Against Ambient Data at Riverside (1987 SCAQS)
B-42

Figure 6.5 Comparison of Predicted Ozone, NO, and NO2 by SAPRC97 and CBIV at the Domain Maximum
B-43

B-6.3. PAN

PAN measurements are available at six sites in the SCAQS domain during

August 27-28, 1987. Comparisons of hourly PAN concentrations against observations

for each site are shown in Figure 6.6 and Figure 6.7. These figures show that, on the last

day of the episode, the model underpredicts PAN concentrations at Burbank, Los

Angeles, and, especially, at Claremont and Riverside. However, the model overestimates

PAN at Anaheim. Table 6.3 shows the maximum observed and predicted 1-hour-average

PAN concentrations. PAN concentrations are sensitive to local variations in the NO to

NO2 ratio and temperature, microscale features that cannot be simulated by gridded

models like UAM-FCM.

Table 6.3 Observed and Predicted Maximum 1-Hour-Average PAN

Concentrations for August 28, 1987

Site Observed (ppb) Predicted (ppb)

Anaheim 1.1 5.0

Azusa 12 8.0

Burbank 12 6.6

Claremont 30 6.1

Los Angeles 10 6.0

Riverside 13 5.2
B-44

Figure 6.6 Comparison of Observed and Predicted PAN at Anaheim, Azusa,

and Burbank

Observed and Predicted PAN at Anaheim 

(August 27-28, 1987)

0

1

2

3

4

5

6

048

121620

048

121620

ppb

Obs Sim

Observed and Predicted PAN at Azusa

 (August 27-28, 1987)

0

5

10

15

048

121620

048

121620

ppb

Obs Sim

Observed and Predicted PAN at Burbank

(August 27-28, 1987)

0

5

10

15

048

121620

048

121620

ppb

Obs Sim
B-45

Figure 6.7 Comparison of Observed and Predicted PAN at Claremont, Los

Angeles, and Riverside

Observed and Predicted PAN at Claremont

(August 27-28, 1987)

0

5

10

15

20

25

30

35

048

121620

048

121620

ppb

Obs Sim

Observed and Predicted PAN at Los Angeles 

(August 27-28, 1987)

0

5

10

15

048

121620

048

121620

ppb

Obs Sim

Observed and Predicted PAN at Riverside 

(August 27-28, 1987)

0

5

10

15

048

121620

048

121620

ppb

Obs Sim
B-46

B-6.4. Acetaldehyde, Benzene, 1,3-Butadiene, and Formaldehyde

As an additional evaluation of the air quality model performance, we compare in

Table 6.4 the predicted and measured 3-hour-average concentrations for benzene, 1,3-

butadiene, total formaldehyde, and total acetaldehyde. Note that concentrations in

Table 6.4 are expressed in ppb, and not in ppbC. There are large discrepancies for all

species and times between predicted and observed 3-hour-average concentrations at the

Los Angeles and Riverside sites. For the other sites, the air quality model predicts a

value comparable to that measured. For example, at start time of 0600, the model

predicts good agreement with measured data at Anaheim and Hawthorne (for benzene

and acetaldehyde), at Long Beach (all species), and Burbank (acetaldehyde). However,

when averaging of all the values for a start time of 0600, the model overpredicts for

benzene and 1,3-butadiene, and underpredicts the aldehydes. The comparison between

model and measurements does not significantly improve later in the day (start time of

1100). However, on average there is better agreement between model predictions and

measured data in the late morning (start time of 1100). Overall, the predicted results for

acetaldehyde and formaldehyde are in rough agreement with the measurements, while the

model severely under-predicts benzene and 1,3-butadiene concentrations. The

instantaneous mixing of emissions into a large grid cell by UAM-FCM is a reasonable

approximation for secondary pollutants like ozone, NO2, acetaldehyde, and

formaldehyde, but not for directly emitted pollutants such as benzene and 1,3-butadiene.
B-47

Table 6.4 Measured and Predicted 3-Hour-Average Concentrations for Selected

VOCs on August 28, 1987 (ppb)

Site Start Benzene 1,3-Butadiene Formaldehyde Acetaldehyde

Hour Measured Predicted Measured Predicted Measured Predicted Measured Predicted

Anaheim 600 1.8 2.1 0.3 0.2 6.8 9.8 4.7 4.9

Anaheim 1100 2.6 1.7 0.3 0.0 19.0 11.0 17.0 6.1

Azusa 600 6.0 3.0 1.1 0.3 8.7 17.0 5.8 8.4

Azusa 1100 5.1 2.4 0.1 0.0 19.0 17.0 17.0 10.0

Burbank 600 8.9 1.5 1.5 0.1 8.1 13.0 5.3 5.3

Burbank 1100 6.3 2.9 0.3 0.1 17.0 20.0 16.0 12.0

Los Angeles 600 38.0 4.6 2.1 0.8 7.8 15.0 3.5 7.9

Los Angeles 1100 5.9 4.3 0.2 0.1 10.0 26.0 9.9 17.0

Hawthorne 600 1.2 1.6 0.1 0.2 3.0 6.4 3.1 3.6

Hawthorne 1100 0.6 1.6 0.1 0.1 4.9 7.7 4.1 4.7

Long Beach 600 5.0 3.8 0.5 0.6 11.0 10.0 5.5 5.5

Long Beach 1100 2.8 3.4 0.1 0.1 14.0 16.0 13.0 12.0

Riverside 600 5.9 2.6 0.7 0.1 8.5 18.0 5.7 9.1

Riverside 1100 2.5 0.7 0.1 0.0 13.0 6.8 13.0 3.2

Average (600) 9.5 2.8 0.9 0.3 7.7 13.0 4.8 6.4

Average (1100) 3.7 2.4 0.2 0.1 14.0 15.0 13.0 9.2

Average (600 & 1100) 6.6 2.6 0.5 0.2 11.0 14.0 8.8 7.8
B-48

B-7. Ozone, PAN, and PPN Formation Potentials

In addition to the 3-dimensional airshed model simulations, we also investigated the

ozone, PAN, and PPN (which includes higher molecular weight acyl peroxy nitrates)

formation potentials for each of the explicit VOCs and lumped species in the SAPRC97

chemical mechanism. This was used to explain the lack of sensitivity of PAN formation

to the ethanol content of the gasoline observed in SectionB-4.

B-7.1. Description of Formation Potentials

The formation of secondary pollutants in an airshed is a complex process, which

involves a series of photochemical reactions driven by the sunlight. It has been

recognized that individual organic compounds can contribute differently to the creation

of secondary air pollutants in atmosphere. Over decades, a variety of scales of VOC

formation potential have been devised to quantify the degree to which different organic

compounds affect formation of a given pollutant, such as ozone. More generally, the

potential of a given organic compound in atmospheric chemistry refers to the reactivity of

that compound to promote formation of products. Among these scales, the incremental

reactivity developed by Carter and Atkinson (1989) is the simplest method of calculating

the potential of an organic compound to form ozone or any other pollutant.

Given a VOCi, its ozone incremental reactivity is defined as the ratio of the ozone

concentration change to a small perturbation of the VOCi:

Ozone formation potential = 











Δ

+ Δ −

Δ →

i

i i i

VOC VOC

O VOC VOC O VOC

i

( ) ( )

lim 3 3

0

(B-7)

where O3(VOCi + ΔVOCi) and O3(VOCi) are the ozone concentrations of the perturbed

case and base case of VOCi, respectively. Yang et al. (1995) show that ozone formation

potential can be estimated as the local sensitivity of the predicted ozone concentration to

the initial concentrations of each organic compound in a mixture.

Similarly, the PAN formation potential of a given organic compound, VOCi, in a

mixture or airshed can be calculated by:

PAN formation potential = 











Δ

+ Δ −

Δ →

i

i i i

VOC VOC

PAN VOC VOC PAN VOC

i

( ) ( )

lim

0

(B-8)

where PAN(VOCi + ΔVOCi) and PAN(VOCi) are the PAN concentrations of the

perturbed case and base case of VOCi, respectively. The equation, in essence, is a local

sensitivity of PAN to the concentration change of an organic compound and can be

computed by the partial differentiation of PAN with respect to VOCi. The PAN

sensitivity coefficient, i.e.,

VOCi

PAN

∂

∂
B-49

is interpreted as the amount of PAN formed per unit amount of VOCi changed in the

mixture and has units of ppm-PAN/ppm-VOC or ppm-PAN/ppm-C. As mentioned

above, the PAN formation potential was estimated as the local sensitivity of the predicted

ozone concentration to the initial concentrations of each organic compound in a mixture

(Yang et al. (1995).

The total formation potential for ozone, PAN, and PPN (which includes higher

molecular weight acyl peroxy nitrates) can be calculated by using a first-order

approximation:

Total PAN formation potential = i

i i

VOC

VOC

PAN Δ















∂

∂

∑ (B-9)

B-7.2. Model Description and Inputs

The scenario for the ozone, PAN, and PPN (and includes higher molecular weight

acyl peroxy nitrates) formation potential calculations is adopted from the average

condition of 39 cities across the U.S. designed by Carter (1994) for ozone incremental

reactivity. Pollutant formation potential scales are time varying over the 10-hour

simulation. The results presented here are the formation potentials of ozone, PAN, and

PPN (and includes higher molecular weight acyl peroxy nitrates) estimated at 1800 where

the maximum ozone occurs in the simulation period, because the time satisfies the

condition of maximum incremental reactivity scale (Yang et al., 1995).

We implemented the SAPRC97 chemical mechanism -- as described in

Attachment B1 -- in a box model to evaluate the ozone, PAN, and PPN (and includes

higher molecular weight acyl peroxy nitrates) formation potential of selected individual

VOCs and lumped VOC categories. Table 7.1 gives the PAN and PPN (and includes

higher molecular weight acyl peroxy nitrates) reactions, together with the value of their

corresponding kinetic parameters (as used in the box model). Table 7.2 provides the

default meteorological inputs for the box-model simulations. Table 7.3 gives the initial

conditions for several episodes in the South Coast Air Basin, and Table 7.4 has the initial

conditions for episodes representative of two large cities in Brazil.
B-50

Table 7.1 PAN and PPN Equilibrium Reaction Rate Constants

Reactions

CCO-O2 + NO2 =

PANa

PANa = CCO-O2 +

NO2 + RCO3

C2CO-O2 + NO2 =

PPNb

PPNb = C2CO-O2 +

NO2 + RCO3

Kinetic

Parameters

Ao = 2.57x10-28

Eo = 0.0

Bo = -7.1

Ai = 12.0x10-12

Ei = 0.0

Bi = -0.9

F = 0.3

N = 1.0

Ao = 4.9x10-3

Eo = 23.972

Bo = 0.0

Ai = 4.0x1016

Ei = 27.079

Bi = 0.0

F = 0.3

N = 1.0

A = 8.4x10-12

E = 0.0

B = 0.0

A = 1.6x1017

E = 27.966

B = 0.0

K(298oK) 3.3x104 ppm-1min-1 3.9x10-2 min-1 1.2x104 ppm-1min-1 4.1x10-2 min-1

Note: All kinetic parameters in cm-molecules-sec units. PPN represents peroxypropionyl nitrate and higher

molecular weight acyl peroxy nitrates (see Attachment B1).

a

 rate constant expression given by k = [k0*M/(1+(K0*M/K1))]*FZ , with Z = 1/[ 1+log10(k0*M/k1)/N2 ].

Where, k0 = A0*[(T/TREF)

B0]*exp(-E0/RT), and, k1 = A1*[(T/TREF)B1]*exp(-E1/RT)

b

 rate constant expression given by k = A(T/T REF)

B

exp(-E/RT), where k and A are in cm-molecule-s units, T

is temperature in oK, R=0.0019872 kcal mol-1 oK , and E is in kcal mol-1

Table 7.2 Meteorological Inputsa

Time Temperature (oK) Mixing Height (m) Zenith Angle (degrees) b

 800 295.5 292.9 71.6

 900 297.7 595.7 59.5

1000 299.9 998.5 47.5

1100 301.8 1201 35.9

1200 303.3 1503 25.9

1300 304.5 1610 20.1

1400 305.6 1716 22.1

1500 305.8 1823 30.4

1600 306.1 1823.1 41.3

1700 305.9 1823.2 53.1

1800 305.1 1823.3 65.2

a Adopted from the average scenario of 39 cities, Carter (1994).

b Evaluated at the latitude of 36.22o

 and the solar declination of 16.5 o (Los Angeles)
B-51

Table 7.3 Initial Concentrations for South Coast Air Basin Scenarios (ppm)

Initial Concentrations

South

Coastb

1968

Los

Angeles c

1968

LARPPd

1973

Los

Angeles

8/28/87a

SCAQS

8/28/87a

Los

Angeles

12/3/87a

Claremontf

9/8/93

Azusae

8/6/97

Azusae

10/4/97

Azusae

8/22/97

O3 0.01 0.01 0.01 0.0067 0.01 0.01 0.04 0.02 0.0043 0.001

NO 0.24 0.341 0.034 0.1 0.04 0.19 0.18 0.031 0.05 0.141

NO2 0.049 0.069 0.007 0.05 0.05 0.06 0.12 0.104 0.065 0.072

CO 10.3 10.3 1.91 5.4 2.0 6.64 4.0 2.64 2.53 3.1

Methane 3.3 3.3 2.01 2.62 2.6 3.44 2.6 2.82 2.58 2.6

Ethene 0.065 0.076 - 0.0526 0.027 0.036 0.018 0.028 0.026 0.0301

Formaldehyde 0.005 0.005 0.01 0.008 0.005 0.011 - 0.011 0.0074 0.0003

Acetaldehyde 0.005 0.005 0.005 0.0035 0.005 0.0067 - 0.006 0.0028 0.0009

Acetone - - - 0.057 - 0.0083 - 0.016 0.0075 0.0007

MEK - - - 0.0008 - 0.0032 - 0.005 0.001 0.0003

Benzene - - - 0.038 0.0078 0.011 0.0029 - 0.013 0.0025

Isoprene - - - 0.00082 - 0.0005 - 0.0009 0.00082 0.0041

Ethanol - - - - - - - - - -

MTBE - - - - - - - - - -

1,3 Butadiene - 0.0028 - - - - 0.0003 - - 0.00018

Dichloromethane - - - 0.001 - 0.014 0.0004 0.0005 - -

ALK1 (lumped alkanes,

kOH<1.0x104 ppm-1min-1)

0.37 0.455 0.286 0.506 0.18 0.245 0.081 0.373 0.24 0.078

ALK2 (lumped alkanes,

kOH31.0x104 ppm-1min-1)

0.038 0.039 0.021 0.18 0.018 0.014 0.0094 0.13 0.083 0.014

ARO1 (lumped aromatics,

kOH<2.0x104 ppm

-1min-1)

0.033 0.06 0.024 0.206 0.06 0.034 0.0068 0.083 0.068 0.011

ARO2 (lumped aromatics) 0.044 0.081 0.02 0.11 0.081 0.019 0.0058 0.089 0.051 0.007

OLE1 (lumped terminal

alkenes, kOH32.0x104 ppm1min-1)

0.016 0.036 0.023 0.094 0.036 0.108 0.004 0.023 0.075 0.0076

OLE2 (lumped internal

alkenes)

- 0.02 0.017 0.0098 0.02 0.005 0.0022 0.019 0.01 0.0026

OLE3 (terpenes) - - - - - - 0.00017 - - 0.0041

ROG/NOX 8.3 8.3 3.1 44 13.3 6.8 1.6 30.8 25.1 3.05

aLawson, 1990 dCalvert, 1976

bLonemann, 1968 eMcCauley, 1999

cKopczynski, 1968 fPasek, 1999

Note: Other constant concentrations are included in the simulation runs, i.e., CO2, O2, Air, and H2.
B-52

Table 7.4 Initial Concentrations for Brazil Scenarios (ppm)

Initial Concentrations

Porto Alegre, Brazil

1998a

Avenida Brazil,

Rio de Janeiro 1999b

O3 0.01 0.01

NO 0.143 0.22

NO2 0.029 0.045

CO 3.34 5.1

Methane 1.70 1.90

Ethene 0.036 0.056

Formaldehyde 0.0124 0.0097

Acetaldehyde 0.014 0.0102

Acetone - -

MEK - -

Benzene 0.038 0.068

Isoprene 0.0042 -

Ethanol 0.012 0.0485

MTBE 0.066 -

1,3 Butadiene 0.062 0.012

Dichloromethane - -

ALK1 (lumped alkanes,

kOH<1.0x104 ppm-1min-1)

0.315 1.03

ALK2 (lumped alkanes,

kOH31.0x104 ppm-1min-1)

0.2 0.57

ARO1 (lumped aromatics,

kOH<2.0x104 ppm-1min-1)

0.12 0.245

ARO2 (lumped aromatic) 0.22 0.515

OLE1 (lumped terminal alkenes,

kOH32.0x104 ppm-1 min-1)

0.061 0.075

OLE2 (lumped internal alkenes) 0.10 0.164

OLE3 (terpenes) - -

ROG/NOX 44.5 67.0

a Grosjean et al. (1998)

b Grosjean (1999)

Note: Other constant concentrations are included in the simulation runs, i.e., CO2, O2, Air, and H2.
B-53

B-7.3. Results

Figure 7.1 and Figure 7.2 present the individual ozone formation potentials for the twelve

cases described in Table 7.3 and Table 7.4. Note that all box model simulations were conducted

with all VOC and NOX inputs as initial conditions, i.e., no emissions over the simulation time

period. This is a reasonable approach for a Lagrangian model that simulates an air parcel as it

travels over a region, but will likely underestimate the contribution from fast-reacting species in

comparison to more slowly reacting compounds (e.g., alkanes, ethanol). The ranking has a

general consistency with relatively high ozone formation potentials for ethene, 1,3-butadiene,

formaldehyde, acetaldehyde, isoprene, ARO2, and the three lumped olefin classes. However, the

ozone formation potential for ARO1 is negative for some of the cases. Previous studies have

shown that aromatic compounds could have negative ozone reactivity under some high-VOC

loading conditions (Carter, 1994; Khan et al., 1998).

For PAN production, 1,3-butadiene, acetaldehyde, isoprene, ARO2, and the three lumped

olefin classes have relatively high formation potential compared to other compounds, as shown

in Figure 7.3 and Figure 7.4. As with ozone, the ARO1 class was found to have negative

formation potential for some cases. For the ten explicit VOC compounds in the figures, the rank

of PAN formation potentials estimated here has general agreement with a recent study by

Derwent et al. (1998). Figure 7.5 and Figure 7.6 show that 1,3-butadiene, isoprene, and the three

lumped olefin classes have higher PPN (including higher molecular weight acyl peroxy nitrates)

formation potentials. For most simulated cases, ARO1 and ARO2 have negative potential for

PPN (and higher molecular weight acyl peroxy nitrates) production.

The total ozone formation potentials for the ten explicit VOCs are given in Table 7.5 and

Table 7.6. The total PAN formation potentials are provided in Table 7.7 and Table 7.8, and the

total PPN formation potentials are shown in Table 7.9 and Table 7.10. Note that the missing

values in Table 7.5 to Table 7.10 denote compounds that were not included in the initial

conditions and, hence, do not have calculated formation potentials. For the Los Angeles cases in

the last 1960s and early 1970s, the lumped alkane class ALK1 is the main contributor to ozone,

PAN, and PPN (and higher molecular weight acyl peroxy nitrates) concentrations. The lumped

aromatic class ARO2 also contributes significantly for these historical cases. For the more

recent cases in the 1980s and 1990s, ALK1 remains a large contributor, but the role of ARO2

diminishes and the contribution of the lumped olefin classes increase. This shift most likely

reflects the effects of a decreasing aromatic content in gasoline and diesel fuel.

In the two Brazilian cases, ALK1 is the major contributor to ozone, and ARO2, OLE1, and

OLE2 dominate PAN concentrations. OLE2 is the major contributor to PPN (and higher

molecular weight acyl peroxy nitrates). Even though ethanol and acetaldehyde concentrations

are relatively high, they are not the major contributors to PAN. Thus, the box model simulations

are consistent with the results from the three-dimensional airshed model that ethanol substitution

scenarios will not necessarily lead to a substantial in increase in PAN concentrations.
B-54

Figure 7.1 Ozone Formation Potentials From Individual VOCs

-1

0

1

2

3

4

5

6

Ethene

Benzene

Ethanol

MTBE

1,3 Butadiene

MEK

Acetone

Formaldehyde

Acetaldehyde

Isoprene

ALK1ALK2

ARO1ARO2

OLE1OLE2OLE3

Ozone forming potential (ppm O3/ppm VOC)

South Coast, 1968

L.A., 1968

L.A., LARPP, 1973

L.A., 8/28/87

SCAQS, 8/28/87

L.A., 12/3/87
B-55

Figure 7.2 Ozone Formation Potentials From Individual VOCs (continued)

-2

0

2

4

6

8

10

12

14

16

Ethene

Benzene

Ethanol

MTBE

1,3 Butadiene

MEK

Acetone

Formaldehyde

Acetaldehyde

Isoprene

ALK1ALK2

ARO1ARO2

OLE1OLE2OLE3

Ozone forming potential (ppm O3/ppm VOC)

Claremont, 9/8/93

Azusa, 8/6/97

Azusa, 10/4/97

Azusa, 8/22/97

Porto Alegre, Brazil, 1998

Avenida Brazil, Rio de Janeiro, 1999
B-56

Figure 7.3 PAN Formation Potentials From Individual VOCs

-0.05

0

0.05

0.1

0.15

0.2

Ethene

Benzene

Ethanol

MTBE

1,3 Butadiene

MEK

Acetone

Formaldehyde

Acetaldehyde

Isoprene

ALK1ALK2

ARO1ARO2

OLE1OLE2OLE3

PAN forming potential (ppm PAN/ppm VOC)

South Coast, 1968

L.A., 1968

L.A., LARPP, 1973

L.A., 8/28/87

SCAQS, 8/28/87

L.A., 12/3/87
B-57

Figure 7.4 PAN Formation Potentials From Individual VOCs (continued)

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

Ethene

Benzene

Ethanol

MTBE

1,3 Butadiene

MEK

Acetone

Formaldehyde

Acetaldehyde

Isoprene

ALK1ALK2

ARO1ARO2

OLE1OLE2OLE3

PAN forming potential (ppm PAN/ppm VOC)

Claremont, 9/8/93

Azusa, 8/6/97

Azusa, 10/4/97

Azusa, 8/22/97

Porto Alegre, Brazil, 1998

Avenida Brazil, Rio de Janeiro, 1999
B-58

Figure 7.5 PPN Formation Potentials From Individual VOCs

-0.03

-0.02

-0.01

0

0.01

0.02

0.03

0.04

0.05

0.06

Ethene

Benzene

Ethanol

MTBE

1,3 Butadiene

MEK

Acetone

Formaldehyde

Acetaldehyde

Isoprene

ALK1ALK2

ARO1ARO2

OLE1OLE2OLE3

PPN forming potential (ppm PPN/ppm VOC)

South Coast, 1968

L.A., 1968

L.A., LARPP, 1973

L.A., 8/28/87

SCAQS, 8/28/87

L.A., 12/3/87
B-59

Figure 7.6 PPN Formation Potentials From Individual VOCs (continued)

-0.015

-0.01

-0.005

0

0.005

0.01

0.015

0.02

0.025

Ethene

Benzene

Ethanol

MTBE

1,3 Butadiene

MEK

Acetone

Formaldehyde

Acetaldehyde

Isoprene

ALK1ALK2

ARO1ARO2

OLE1OLE2OLE3

PPN forming potential (ppm PPN/ppm VOC)

Claremont, 9/8/93

Azusa, 8/6/97

Azusa, 10/4/97

Azusa, 8/22/97

Porto Alegre, Brazil, 1998

Avenida Brazil, Rio de Janeiro, 1999
B-60

Table 7.5 Contribution From Individual VOCs to Total Ozone Formation* (ppm)

VOCs South

Coastb

1968

Los

Angeles c

1968

Los

Angeles

LARPPd

1973

Los

Angeles

8/28/87a

SCAQS

8/28/87a

Los

Angeles

12/3/87a

Claremontf

9/8/93

Azusae

8/6/97

Los

Angeles e

10/4/97

Los

Angeles e

8/22/97

Ethene 0.09953 0.07193 0.00520 0.03515 0.05048 0.01409 0.00636 0.00939 0.08674

Benzene 0.00043 0.00205 0.00197 0.00049 0.00042 0.00168

Ethanol

MTBE

1,3-Butadiene 0.00592 0.00124 0.00186

MEK 0.00004 0.00163 0.00043 0.00010 0.00040

Acetone 0.00004 0.00101 0.00023 0.00014 0.00032

Formaldehyde 0.00569 0.00214 0.00100 -0.00081 0.00290 0.00916 -0.00008 0.00007 0.00113

Acetaldehyde 0.00793 0.00503 0.00362 0.00135 0.00816 0.01019 0.00404 0.00179 0.00414

Isoprene 0.00023 0.00144 0.00044 0.00062 0.03009

ALK1 0.23994 0.22601 0.03184 0.03925 0.12619 0.17033 0.01895 0.04533 0.03887 0.07233

ALK2 0.04231 0.03239 -0.00820 0.00027 0.02027 0.01738 0.00584 0.00011 0.00084 0.02891

ARO1 0.01625 -0.04142 -0.01254 -0.05754 0.00915 0.00557 0.00628 -0.04218 -0.04161 0.04027

ARO2 0.21484 0.12599 -0.00205 -0.04482 0.06570 0.07153 0.02865 -0.04196 -0.01717 0.11135

OLE1 0.04005 0.05394 0.01191 0.01022 0.01559 0.24770 0.00917 0.00613 0.03381 0.04902

OLE2 0.03445 0.00150 -0.00713 0.01561 0.01034 -0.01380 -0.00258 0.02715

OLE3 0.00046 0.01989

*

TOFP = ( )( )

o

i

i

∑ OFPi VOC

a

 Lawson, 1990 bLonemann, 1968 cKopczynski, 1968

dCalvert, 1976 eMcCauley, 1999 fPasek, 1999
B-61

Table 7.6 Contribution From Individual VOCs to Ozone Formation* (ppm)

VOCs

Porto Alegre, Brazil

1998a

Avenida Brazil, Rio

de Janeiro

1999b

Ethene 0.00178 -0.00276

Benzene 0.00042 0.00016

Ethanol 0.00009 0.00035

MTBE 0.00050

1,3-Butadiene 0.00080 0.00130

MEK

Acetone

Formaldehyde -0.00057 -0.00049

Acetaldehyde 0.00385 0.00203

Isoprene -0.00026

ALK1 0.01700 0.03412

ALK2 -0.00676 0.01356

ARO1 -0.02446 -0.02267

ARO2 -0.08406 -0.12305

OLE1 -0.00190 -0.00541

OLE2 -0.02467 0.00484

OLE3

*

TOFP = ( )( )

o

i

i

∑ OFPi VOC

a Grosjean et al. (1998)

b Grosjean (1999)
B-62

Table 7.7 Contribution From Individual VOCs to PAN Formation* (ppm)

VOCs

South

Coastb

1968

Los

Angeles c

1968

Los

Angeles

LARPPd

1973

Los Angeles

8/28/87a

SCAQS

8/28/87a

Los Angeles

12/3/87a

Claremontf

9/8/93

Azusae

8/6/97

Los

Angeles e

10/4/97

Los

Angeles e

8/22/97

Ethene 0.00263 0.00295 0.00001 0.00048 0.00139 0.00002 0.00006 0.00013 0.00050

Benzene -0.00009 -0.00003 -0.00007 < 1E-05 -0.00008 0.00001

Ethanol

MTBE

1,3-Butadiene 0.00051 < 1E-05 0.00001

MEK 0.00001 0.00019 0.00008 0.00002 < 1E-05

Acetone 0.00002 0.00010 0.00006 0.00003 < 1E-05

Formaldehyde 0.00001 0.00001 -0.00004 -0.00004 -0.00010 -0.00002 -0.00003 < 1E-05

Acetaldehyde 0.00046 0.00055 0.00016 0.00018 0.00021 0.00061 0.00037 0.00015 0.00003

Isoprene 0.00000 0.00003 0.00007 0.00003 0.00004 0.00019

ALK1 0.01394 0.01687 0.00011 -0.00129 0.00430 0.01113 0.00003 -0.00041 0.00044 0.00050

ALK2 0.00305 0.00308 -0.00021 -0.00291 0.00096 0.00142 0.00001 -0.00168 -0.00036 0.00020

ARO1 0.00065 -0.00136 -0.00016 -0.00081 0.00017 0.00043 0.00002 -0.00125 -0.00124 0.00028

ARO2 0.00415 0.00701 0.00034 0.00359 0.00060 0.00127 0.00008 0.00179 0.00089 0.00064

OLE1 0.00178 0.00444 0.00052 0.00229 0.00036 0.01166 0.00002 0.00068 0.00267 0.00031

OLE2 0.00319 0.00048 0.00023 0.00059 0.00002 0.00048 0.00029 0.00016

OLE3 < 1E-05 0.00012

aLawson, 1990, bLonemann, 1968, cKopczynski, 1968, dCalvert, 1976, eMcCauley, 1999, fPasek, 1999

* TPANFP= ( )( )

o

i

i

∑ PANFPi VOC
B-63

Table 7.8 Contribution From Individual VOCs to PAN Formation* (ppm)

VOCs

Porto Alegre, Brazil

1998a

Avenida Brazil,

 Rio de Janeiro

1999b

Ethene -0.00004 -0.00006

Benzene -0.00011 -0.00009

Ethanol 0.00009 0.00012

MTBE -0.00003

1,3-Butadiene 0.00018 0.00014

MEK

Acetone

Formaldehyde -0.00002 -0.00001

Acetaldehyde 0.00077 0.00047

Isoprene 0.00012

ALK1 -0.00151 -0.00419

ALK2 -0.00471 -0.01112

ARO1 -0.00048 0.00002

ARO2 0.00726 0.01781

OLE1 0.00149 0.00177

OLE2 0.00505 0.00911

OLE3

a Grosjean et al., 1998

b Grosjean, 1999

* TPANFP= ( )( )

o

i

i

∑ PANFPi VOC
B-64

Table 7.9 Contribution From Individual VOCs to PPN Formationa,b (ppm)

VOCs Los

Angeles

8/28/87c

SCAQS

8/28/87c

Los

Angeles

12/3/87c

Azusag

8/6/97

Los

Angelesg

10/4/97

Los

Angelesg

8/22/97

Claremonth

9/8/93

South

Coastd

1968

Los

Angeles e

1968

Los

Angeles

LARPPf

1973

Ethene 0.00004 0.00003 -0.00008 0.00003 0.00003 < 1E-05 -0.00006 -0.00005 0.00011

Benzene -0.00003 -0.00001 -0.00003 < 1E-05 -0.00002 < 1E-05

Ethanol

MTBE

1,3 Butadiene 0.00015 < 1E-05 < 1E-05

MEK 0.00004 0.00001 < 1E-05 < 1E-05

Acetone > -1E-05 > -1E-05 > -1E-05 < 1E-05

Formaldehyde -0.00004 -0.00002 -0.00001 -0.00002 -0.00006 -0.00001 -0.00001 < 1E-05

Acetaldehyde 0.00002 0.00003 0.00002 0.00001 0.00004 0.00004 0.00004 0.00002 < 1E-05

Isoprene < 1E-05 0.00001 < 1E-05 < 1E-05 0.00004

ALK1 0.00506 0.00608 0.00013 -0.00004 0.00132 0.00380 0.00001 0.00003 0.00035 0.00014

ALK2 0.00156 0.00160 0.00001 0.00015 0.00034 0.00062 < 1E-05 0.00024 0.00049 0.00007

ARO1 -0.00061 -0.00177 -0.00014 -0.00108 -0.00009 -0.00044 < 1E-05 -0.00088 -0.00078 0.00005

ARO2 -0.00103 -0.00138 -0.00002 -0.00038 -0.00004 -0.00022 0.00001 -0.00051 -0.00025 0.00013

OLE1 0.00019 0.00053 0.00005 0.00015 0.00006 0.00139 < 1E-05 0.00004 0.00023 0.00007

OLE2 0.00032 0.00004 < 1E-05 0.00004 < 1E-05 -0.00003 -0.00001 0.00003

OLE3 < 1E-05 0.00003

bNote that PPN represents peroxypropionyl nitrate and higher molecular weight acyl peroxy nitrates

cLawson, 1990, dLonemann, 1968 eKopczynski, 1968, fCalvert, 1976, gMcCauley, 1999, hPasek, 1999

a TPPNFP = ( )( )

o

i

i

∑ PPNFPi VOC .
B-65

Table 7.10 Contribution From Individual VOCs to PPN Formationa,b (ppm)

VOCs

Porto Alegre,

Brazil

1998c

Avenida Brazil,

Rio de Janeiro

1999d

Ethene -0.00008 -0.00005

Benzene -0.00003 -0.00002

Ethanol -0.00002 -0.00004

MTBE -0.00001

1,3-Butadiene 0.00013 0.00023

MEK

Acetone

Formaldehyde > -1E-05 < 1E-05

Acetaldehyde 0.00001 0.00001

Isoprene < 1E-05

ALK1 -0.00009 -0.00045

ALK2 0.00019 -0.00044

ARO1 -0.00065 -0.00058

ARO2 -0.00128 -0.00193

OLE1 0.00004 0.00019

OLE2 0.00035 0.00107

OLE3

a

TPPNFP = ( )( )

o

i

i

∑ PPNFPi VOC

b

Note that PPN represents peroxypropionyl nitrate and higher molecular weight. acyl peroxy nitrates

c

Grosjean et al. (1998)

d

Grosjean (1999)

Individual reactivities or forming potentials from the results show a variation in

estimated values across different scenarios, because a VOC reactivity is dependent upon

local ambient conditions, such as VOC/NOx ratios noted in previous studies (Carter,

1989; Derwent and Jenkin, 1991). A relative scale to each base mixture reactivity may

significantly eliminate the variation of individual reactivities over different ambient

conditions. However, pursuing a robust regulatory reactivity or forming potential scale is

beyond the scope of this study.
B-66

B-7.4. Other Study of PAN Formation Potentials

The PAN formation potential results in Table 7.7 and Table 7.8 are in agreement with

the results obtained by Bowman and Seinfeld (1994) for the relative contribution of

lumped VOC species to PAN formation. From Table 7.11, ALK1, ALK2, ARO2, and

OLE1 have large contributions to PAN formation, while acetaldehyde has a low

contribution to PAN formation.

Table 7.11 Relative Contribution of Lumped VOC Species to PAN Formationa

Species Descriptionb

Initial

Concentrationd

(ppbC)

Contribution

to PANd

(%)

CO Carbon monoxide 1,500 -

CH4 Methane 1,700 -

HCHO Formaldehyde 8 -

CCHO Acetaldehyde 5 2.6

RCHO Higher molecular weight aldehydes 2 0.5

MEK Higher molecular weight ketones 16 1.4

ALK1 Low molecular weight alkanes 353 18.6

ALK2 Higher molecular weight alkanes 236 13.5

ARO1 Benzene and toluene 147 9.4

ARO2 Higher molecular weight aromatics (mostly xylenes) 108 15.2

ETHE Ethylene 75 6.8

OLE1 Low molecular weight, less reactive alkenes 60 14.9

OLE2 Low molecular weight, more reactive alkenes 29 8.9

OLE3 Biogenic compounds (isoprene + terpenes) 62 8.3

a Adapted from Bowman and Seinfeld (1994)

b SAPRC90 (Carter, 1990)

c Using 1987 SCAQS emission inventory as input data

d At VOC/NOX = 8.2 ppbC/ppb
B-67

B-8. References

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Modeling,” April (http://www.arb.ca.gov/ccaqs/models/models.htm).

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Estimation Model - Technical Support Document,” November

(http://www.arb.ca.gov/msei/pubs/tsd.zip).

Atkinson, R. (1999a) Letter to Bart Croes, November 23.

Atkinson, R. (1999b) Communication to Bart Croes, November 30.

Bowman, F.M. and J.H. Seinfeld (1994) “Ozone Productivity of Atmospheric Organics,”

Journal of Geophysical Research, 99: 5309-5324.

Calvert, J.G (1976) “Hydrocarbon Involvement in Photochemical Smog Formation,”

Environmental Science & Technology, 10: 256-262.

Carter, W.P.L (1988) “Appendix C: Documentation for the SAPRC Atmospheric

Photochemical Mechanism Preparation and Emissions Processing Programs for

Implementation in Airshed Models,” Final Report for Air Resources Board. Contract

No. A5-122-32, October.

Carter, W.P.L and R. Atkinson (1989) “Computer Modeling Studies of Incremental

Hydrocarbon Reactivity,” Environmental Science & Technology, 23: 864-880.

Carter, W.P.L. (1990) “A Detailed Mechanism for the Gas-Phase Atmospheric Reactions

of Organic Compounds,” Atmospheric Environment, 24A: 481-518.

Carter, W.P.L, D. Luo, I.L. Malkina, and J.A. Pierce (1993) "An Experimental and

Modeling Study of the Photochemical Ozone Reactivity of Acetone," Final Report for

Chemical Manufacturers Association Contract No. KET-ACE-CRC.

Carter, W.P.L. (1994) “Development of Ozone Reactivity Scales for Organic Gases,”

Journal of the Air & Waste Management Association, 44: 881-899.

Carter, W.P.L. (1995) “Computer Modeling of Environmental Chamber Studies of

Maximum Incremental Reactivities of Volatile Organic Compounds,” Atmospheric

Environment, 29: 2513-2527.

Carter, W.P.L. (1996) “Condensed Atmospheric Photooxidation Mechanisms for

Isoprene,” Atmospheric Environment, 30: 4275-4290.

Carter, W.P.L., D Luo, and I.L. Malkina (1997) “Environmental Chamber Studies for

Development of an Updated Photochemical Mechanism for VOC Reactivity

Assessment,” Final Report for California Air Resources Board Contract 92-345,

Coordinating Research Council Project M-9, and National Renewable Energy

Laboratory Contract ZF-2-12252-07, November 26.

Carter, W.P.L (1999a), Personal Communication, Riverside, CA.
B-68

Carter, W.P.L (1999b) “Documentation of the SAPRC-99 Chemical Mechanism for VOC

Reactivity Assessment,” Draft Report to the California Air Resources Board,

September 13.

De Haan, et al. (1999), Int. Rev. Phys. Chem. 18, 343

Derwent, R.G., Jenkin, M.E. (1991) “Hydrocarbons and the Long-Range Transport of

Ozone and PAN Across Europe, Atmospheric Environment, 25A: 1661-1678.

Derwent, R.G., M.E. Jenkin, S.M. Saunders, and M.J. Pilling (1998) “Photochemical

Ozone Creation Potentials for Organic Compounds in Northwest Europe Calculated

with A Master Chemical Mechanism,” Atmospheric Environment, 32: 2429-2441.

Fantechi, G., N.R. Jensen, O. Saastad, J. Hjorth, and J. Peeters (1998) “Reactions of Cl

Atoms With Selected VOC: Kinetics, Products and Mechanisms,” Journal of

Atmospheric Chemistry, 31: 247-267.

Finlayson-Pitts, B.J. and J.N. Pitts, Jr. (1986) “Atmospheric Chemistry: Fundamentals

and Experimental Techniques,” A Wiley-Interscience Publication, John Wiley &

Sons, New York.

Finlyson-Pitts, B.J. (1999), Comments on Draft Report: Air Quality Impacts of the Use of

Ethanol in California Reformulated Gasoline, December 6 Letter to Bart Croes,

CARB.

Gery, M., G.Z. Whitten, J.P. Killus, and M.C. Dodge (1990) “A Photochemical Kinetics

Mechanism for Urban and Regional Scale Computer Modeling,” Journal of

Geophysical Research, 94: 12,925-12,956.

Grosjean, E., D. Grosjean, and R.A. Rasmussen (1998) “Ambient Concentrations,

Sources, Emission Rates and Photochemical Reactivity of C2-C10 Hydrocarbons in

Porto Alegre, Brazil,” Environmental Science & Technology, 32: 2061-2069.

Grosjean, D. (1999) Personal Communication, Ventura, CA.

Hov, Ö. (1985), The Effects of Chlorine on the Formation of Photochemical Oxidants in

Southern Telemark, Norway. Atmospheric Environment 19: 471.

Khan, M., Y.J. Yang, and A.G. Russell (1999), “Photochemical Reactivities of Common

Solvents: Comparisons between Urban and Regional Domains,” Atmospheric

Environment, 33: 1085-1092.

Kopczynski, S.L., W.A. Lonneman, F.D. Sutterfield, and P.E. Darley (1972)

“Photochemistry of Atmospheric Samples in Los Angeles,” Environmental Science &

Technology, 6: 342-347.

Kumar, N., F.W. Lurmann, and W.P.L. Carter (1995) “Development of the Flexible

Chemical Mechanism Version of the Urban Airshed Model,” Final Report STI94470-1508-FR. prepared for the California Air Resources Board, August.

Kumar, N., F.W. Lurmann, and W.P.L Carter (1996) “Assessment of Effects of Chemical

Uncertainty on Airshed Model Results,” Final Report for California Air Resources

Board Contract No. 93-716, Statewide Air Pollution Research Center, Riverside,

California, June 13.
B-69

Lawson, D.R. (1990) “The Southern California Air Quality Study,” Journal of the Air &

Waste Management Association 40: 156-165.

Lonnemann, W.A., S.L. Kopczynski, P.E. Darley and F.D. Sutterfield (1974)

“Hydrocarbon Composition of Urban Air Pollution,” Environmental Science &

Technology, 8: 229-234.

McCauley, E. (1999) Personal Communication, Sacramento, CA.

Morris, R.E. and T.C. Myers (1990) “User’s Guide for the Urban Airshed Model,

Volume I: Users Manual for UAM (CB-IV)” Systems Applications, Inc., EPA-450/4-

90-007A, June.

Pasek, R. (1999) Personal Communication, Sacramento, CA.

Platt, U. and G. Moortgat (1999) “Heterogeneous and Homogeneous Chemistry of

Reactive Halogen Compounds in the Lower Troposphere.” Journal of Atmospheric

Chemistry, 34: 1-8.

SCAQMD (South Coast Air Quality Management District) (1994) “1994 Air Quality

Management Plan,” September.

Singer, B.C. and R.A. Harley (2000) “A Fuel-Based Inventory of Motor Vehicle Exhaust

Emissions in the Los Angeles Area During Summer 1997,” Atmospheric

Environment, in press.

Stutz, J., K. Hebestreit, B. Alicke, and U. Platt (1999) “Chemistry of Halogen Oxides in

the Troposphere: Comparison of Model Calculations with Recent Field Data.”

Journal of Atmospheric Chemistry, 34: 65-85.

Whitten, G.Z., H. Hogo, and J.P. Killus (1980) “The Carbon-Bond Mechanism: A

Condensed Kinetic Mechanism for Photochemical Smog,” Environmental Science &

Technology, 14: 690-700.

Yang, Y.J., W.R. Stockwell, and J.B. Milford (1995) “Uncertainty in Incremental

Reactivities of Volatile Organic Compounds,” Environmental Science & Technology,

29: 1336-1345.
B-70

Attachment B1 – Listing of SAPRC97 Chemical Mechanism

This attachment provides a listing of the SAPRC97 mechanism. Separate listings are

provided for the isoprene reaction mechanism and for other species treated explicitly in

Attachments B2 and B3, respectively. Interpretation of reactions rates constants can be

found in Kumar et al. (1996). Note that this chemical mechanism contains explicit gasphase reactions for some organic compounds, such as formaldehyde, acetaldehyde,

ethylene, and PAN. However, the PPN model species represents higher acyl peroxy

nitrates (e.g., CH3-CH2-CH2-CH2-CO-OO-NO2), but not alkyl peroxy nitrates such as

CH3-CH2-CH2-CH2-OO-NO2. The latter are not represented in the model because of

their rapid back-decomposition to reactants at ambient temperatures. PPN does not

represent the aromatic acyl peroxy nitrates that are represented by the PBZN model

species (Carter, 1990 and 1999a). In the newest version of update to the mechanism,

SAPRC99, Carter (1999b) uses PAN2 instead of PPN.

A summary of the reaction rate constants used in the mechanism is provided for the

benefit of the reader. The default rate parameter, k, input in the mechanism is:

Label) A, E, B ; reaction list

Where

k = A(T/TREF)

B

exp(-E/RT) (B1-1)

Where A is the Arrhenius pre-exponential factor in cm3molecule-1sec-1, TREF is a

reference temperature (300 K), B is a constant, E is activation energy in kcal/mole, and R

is the ideal gas constant in kcal mole-1K

-1 (Kumar et al., 1995). For those reaction rate

constants that are temperature and pressure dependent, the Troe falloff expression is used.

The default input parameters for the falloff rates constant are:

Label) FALLOFF ; reaction list

A0, E0, B0

A1, E1, B1

F, N

The falloff expression is

k = [k0*M/(1+(K0*M/K1))]*FZ (B1-2)

with

Z = 1/[ 1+log10(k0*M/k1)/N2 ] (B1-3)

Where

k0 = A0*[(T/TREF)

B0]*exp(-E0/RT) (B1-4)

k1 = A1*[(T/TREF)

B1]*exp(-E1/RT) (B1-5)

Here, k0 is the low-pressure limiting rate constant, and A0 its value at 300 K, k1 is the

high-pressure limiting rate constant, with A1 its value at 300 K. For second-order
B-71

reactions, the units of k0, k1, A0, and A1 are in cm3 molecule-1sec-1, while for first-order

reaction the units are in sec-1. F is the broadening factor of the falloff curve, M is the

total pressure fixed at 1.0 x106 ppm. The constants E0 and E1 are activation energies in

kcal mole-1 oK

-1, and B0, B1, and N are constants for each reaction (Finlayson-Pitts,

1986; Kumar et al., 1995; Carter, 1990). Finally, photolytic reactions are indicated by

the PF= label.

1) PF=NO2 ;NO2 + HV = NO + O

2) 6.0E-34, 0.0, -2.3 ;O + O2 + M = O3 + M

3A) 6.5E-12, -0.238 ;O + NO2 = NO + O2

!

3B) FALLOFF ;O + NO2 = NO3 + M

9.0E-32 0.0 -2.0

2.2E-11 0.0 0.0

0.6 1.0

!

4) 2.00E-12, 2.782 ;O3 + NO = NO2 + O2

5) 1.400E-13, 4.968 ;O3 + NO2 = O2 + NO3

 6) 1.7E-11, -0.298 ;NO + NO3 = #2 NO2

7) 3.300E-39, -1.05 ;NO + NO + O2 = #2 NO2

!

 8) FALLOFF ;NO2 + NO3 = N2O5

2.2E-30 0.0 -4.3

1.5E-12 0.0 -0.5

0.6 1.0

!

9) 9.09E+26, 22.26 ;N2O5 + #RCON8 = NO2 + NO3

10) 1.0E-21 0.0 ;N2O5 + H2O = #2 HNO3

11) 2.5E-14, 2.44 ;NO2 + NO3 = NO + NO2 + O2

12A) PF=NO3NO ;NO3 + HV = NO + O2

12B) PF=NO3NO2 ;NO3 + HV = NO2 + O

13A) PF=O3O3P ;O3 + HV = O + O2

13B) PF=O3O1D ;O3 + HV = O*1D2 + O2

14) 2.2E-10, 0.0 ;O*1D2 + H2O = #2 HO

15) 1.919E-11, -0.251 ;O*1D2 + M = O + M

!

16) FALLOFF ;HO + NO = HONO

7.0E-31 0.0 -2.6

1.5E-11 0.0 -0.5

0.6 1.0

!

 17) PF=HONO ;HONO + HV = HO + NO

!

 18) FALLOFF ;HO + NO2 = HNO3

2.6E-30 0.0 -3.2

2.4E-11 0.0 -1.3

0.6 1.0

!

 19) 6.45E-15, -1.652 ;HO + HNO3 = H2O + NO3 ! 1 ATM ONLY.

21) 2.4E-13, 0.0 ;HO + CO = HO2 + CO2 !1 ATM ONLY

22) 1.600E-12, 1.87 ;HO + O3 = HO2 + O2

 23) 3.700E-12, -0.48 ;HO2 + NO = HO + NO2

!

24) FALLOFF ;HO2 + NO2 = HNO4
B-72

1.8E-31 0.0 -3.2

4.7E-12 0.0 -1.4

0.6 1.0

!

25) 4.76E+26, 21.66 ;HNO4 + #RCON24 = HO2 + NO2

 27) 1.3E-12, -0.755 ;HNO4 + HO = H2O + NO2 + O2

 28) 1.100E-14, 0.994 ;HO2 + O3 = HO + #2 O2

 29A) 2.2E-13, -1.23 ;HO2 + HO2 = H2O2 + O2

 29B) 1.9E-33, -1.95 ;HO2 + HO2 + M = H2O2 + O2

 29C) 3.1E-34, -5.60 ;HO2 + HO2 + H2O = H2O2 + O2 + H2O

!29D) 2.7E-54, -6.32 ;HO2 + HO2 + M + H2O = H2O2 + O2 +H2O

 29D) 6.6E-35, -6.32 ;HO2 + HO2 + H2O = H2O2 + O2 + H2O !(1 ATM ONLY)

 30A) 2.2E-13, -1.23 ;NO3 + HO2 = HNO3 + O2

 30B) 1.9E-33, -1.95 ;NO3 + HO2 + M = HNO3 + O2

 30C) 3.1E-34, -5.60 ;NO3 + HO2 + H2O = HNO3 + O2 + H2O

 30D) 6.6E-35, -6.32 ;NO3 + HO2 + H2O = HNO3 + O2 + H2O

31) PF=H2O2 ;H2O2 + HV = #2 HO

32) 3.300E-12, 0.397 ;H2O2 + HO = HO2 + H2O

33) 4.60E-11, -0.457 ;HO + HO2 = H2O + O2

B1) 4.200E-12, -0.360 ;RO2 + NO = NO

!

B2) FALLOFF ;RCO3 + NO = NO

5.65E-28 0.0 -7.1

2.64E-11 0.0 -0.9

0.27 1.0

!

B4) FALLOFF ;RCO3 + NO2 = NO2

2.57E-28 0.0 -7.1

12.0E-12 0.0 -0.9

0.30 1.0

!

B5) 3.40E-13, -1.590 ;RO2 + HO2 = HO2

B6) 3.40E-13, -1.590 ;RCO3 + HO2 = HO2

B8) 1.0E-15 ;RO2 + RO2 =

B9) 1.86E-12, -1.053 ;RO2 + RCO3 =

B10) 2.8E-12, -1.053 ;RCO3 + RCO3 =

B11) SAMEK B1 ;RO2-R + NO = NO2 + HO2

B12) SAMEK B5 ;RO2-R + HO2 = XOOH

B13) SAMEK B8 ;RO2-R + RO2 = RO2 + #.5 HO2

B14) SAMEK B9 ;RO2-R + RCO3 = RCO3 + #.5 HO2

B19) SAMEK B1 ;RO2-N + NO = RNO3

B20) SAMEK B5 ;RO2-N + HO2 = XOOH + MEK + #1.5 XC

B21) SAMEK B8 ;RO2-N + RO2 = RO2 + #.5 HO2 + MEK + #1.5 XC

B22) SAMEK B9 ;RO2-N + RCO3 = RCO3 + #.5 HO2 + MEK + #1.5 XC

B15) SAMEK B1 ;R2O2 + NO = NO2

B16) SAMEK B5 ;R2O2 + HO2 =

B17) SAMEK B8 ;R2O2 + RO2 = RO2

B18) SAMEK B9 ;R2O2 + RCO3 = RCO3

B23) SAMEK B1 ;RO2-XN + NO = XN

B24) SAMEK B5 ;RO2-XN + HO2 = XOOH

B25) SAMEK B8 ;RO2-XN + RO2 = RO2 + #.5 HO2

B26) SAMEK B9 ;RO2-XN + RCO3 = RCO3 + HO2

G2) SAMEK B1 ;RO2-NP + NO = NPHE

G3) SAMEK B5 ;RO2-NP + HO2 = XOOH + #6 XC

G4) SAMEK B8 ;RO2-NP + RO2 = RO2 + #.5 HO2 + #6 XC

G5) SAMEK B9 ;RO2-NP + RCO3 = RCO3 + HO2 + #6 XC
B-73

B7) PF=CO2H ;XOOH + HV = HO2 + HO

B7A) 1.18E-12, -0.254 ;HO + XOOH = HO

B7B) 1.79E-12, -0.435 ;HO + XOOH = RO2-R + RO2

C1) PF=HCHONEWR ;HCHO + HV = #2 HO2 + CO

C2) PF=HCHONEWM ;HCHO + HV = H2 + CO

C3) 1.125E-12 -1.288 2.0 ;HCHO + HO = HO2 + CO + H2O

C4) 9.7E-15, -1.242 ;HCHO + HO2 = HOCOO

C4A) 2.4E+12, 13.91 ;HOCOO = HO2 + HCHO

C4B) SAMEK B1 ;HOCOO + NO = XC + NO2 + HO2

C9) 2.8E-12, 5.00 ;HCHO + NO3 = HNO3 + HO2 + CO

C10) 5.55E-12, -0.618 ;CCHO + HO = CCO-O2 + H2O + RCO3

C11A) PF=CCHOR ;CCHO + HV = CO + HO2 + HCHO + RO2-R + RO2

C12) 1.4E-12, 3.696 ;CCHO + NO3 = HNO3 + CCO-O2 + RCO3

C25) 8.5E-12 -0.50 ;RCHO + HO = C2CO-O2 + RCO3

C26) PF=RCHO ;RCHO + HV = CCHO + RO2-R + RO2 + CO + HO2

C27) 1.4E-12, 3.696 ;NO3 + RCHO = HNO3 + C2CO-O2 + RCO3

C38) 4.81E-13 0.457 2.0 ;ACET + HO = R2O2 + HCHO + CCO-O2 + RCO3 + RO2

C39) PF=ACET-93C ;ACET + HV = CCO-O2 + HCHO + RO2-R + RCO3 + RO2

C44) 2.92E-13 -0.823 2.0 ;MEK + HO = H2O + #.5 "CCHO + HCHO + CCO-O2 + &

C2CO-O2 " + RCO3 + #1.5 "R2O2 + RO2 "

C57) PF=KETONE ;MEK + HV + #0.1 = CCO-O2 + CCHO + RO2-R + RCO3 &

+ RO2

C95) 2.191E-11, 1.408 ;RNO3 + HO = NO2 + #.155 MEK + #1.05 RCHO + &

 #.48 CCHO + #.16 HCHO + #.11 XC + #1.39 "R2O2 + RO2 "

C13) SAMEK B2 ;CCO-O2 + NO = CO2 + NO2 + HCHO + RO2-R + RO2

C14) SAMEK B4 ;CCO-O2 + NO2 = PAN

C15) SAMEK B6 ;CCO-O2 + HO2 = XOOH + CO2 + HCHO

C16) SAMEK B9 ;CCO-O2 + RO2 = RO2 + #.5 HO2 + CO2 + HCHO

C17) SAMEK B10 ;CCO-O2 + RCO3 = RCO3 + HO2 + CO2 + HCHO

!

 C18) FALLOFF ;PAN = CCO-O2 + NO2 + RCO3

4.90E-03 23.972 0.0

4.00E+16 27.079 0.0

0.30 1.00

!

C28) SAMEK B2 ;C2CO-O2 + NO = CCHO + RO2-R + CO2 + NO2 + RO2

C29) 8.4E-12 0.0 0.0 ;C2CO-O2 + NO2 = PPN

C30) SAMEK B6 ;C2CO-O2 + HO2 = XOOH + CCHO + CO2

C31) SAMEK B9 ;C2CO-O2 + RO2 = RO2 + #.5 HO2 + CCHO + CO2

C32) SAMEK B10 ;C2CO-O2 + RCO3 = RCO3 + HO2 + CCHO + CO2

C33) 1.6E+17, 27.966 ;PPN = C2CO-O2 + NO2 + RCO3

TBON) 2.4E-11 ;C2(C)-O + NO2 = RNO3 + #-2 XC

TBOD) 7.5E+14, 16.2 ;C2(C)-O = ACET + HCHO + RO2-R + RO2

C58A) PF=GLYOXAL1 ;GLY + HV = #.8 HO2 + #.45 HCHO + #1.55 CO

C58B) PF=GLYOXAL2 ;GLY + HV + #0.029 = #.13 HCHO + #1.87 CO

 C59) 1.14E-11 ;GLY + HO = #.6 HO2 + #1.2 CO + #.4 "HCOCO-O2 + &

RCO3 "

 C60) SAMEK C12 ;GLY + NO3 = HNO3 + #.6 HO2 + #1.2 CO + &

 #.4 "HCOCO-O2 + RCO3 "

 C62) SAMEK B2 ;HCOCO-O2 + NO = NO2 + CO2 + CO + HO2

 C63) SAMEK B4 ;HCOCO-O2 + NO2 = GPAN

 C64) SAMEK C18 ;GPAN = HCOCO-O2 + NO2 + RCO3

 C65) SAMEK B6 ;HCOCO-O2 + HO2 = XOOH + CO2 + CO

 C66) SAMEK B9 ;HCOCO-O2 + RO2 = RO2 + #.5 HO2 + CO2 + CO

 C67) SAMEK B10 ;HCOCO-O2 + RCO3 = RCO3 + HO2 + CO2 + CO

C68A) PF=MEGLYOX1 ;MGLY + HV = HO2 + CO + CCO-O2 + RCO3
B-74

C68B) PF=MEGLYOX2 ;MGLY + HV + #.107 = HO2 + CO + CCO-O2 + RCO3

C69) 1.72E-11 ;MGLY + HO = CO + CCO-O2 + RCO3

C70) SAMEK C12 ;MGLY + NO3 = HNO3 + CO + CCO-O2 + RCO3

G46) 2.63E-11 ;HO + PHEN = #.15 RO2-NP + #.85 RO2-R + #.2 GLY + &

#4.7 XC + RO2

G51) 3.6E-12 ;NO3 + PHEN = HNO3 + BZ-O

G52) 4.2E-11 ;HO + CRES = #.15 RO2-NP + #.85 RO2-R + #.2 MGLY + &

 #5.5 XC + RO2

G57) 2.1E-11 ;NO3 + CRES = HNO3 + BZ-O + XC

G30) 1.29E-11 ;BALD + HO = BZ-CO-O2 + RCO3

G31) PF=BZCHO ;BALD + HV + #.05 = #7 XC

G32) 1.4E-12, 3.747 ;BALD + NO3 = HNO3 + BZ-CO-O2

G33) SAMEK B2 ;BZ-CO-O2 + NO = BZ-O + CO2 + NO2 + R2O2 + RO2

G34) 8.4E-12 0.0 0.0 ;BZ-CO-O2 + NO2 = PBZN

G36) SAMEK B6 ;BZ-CO-O2 + HO2 = XOOH + CO2 + PHEN

G37) SAMEK B9 ;BZ-CO-O2 + RO2 = RO2 + #.5 HO2 + CO2 + PHEN

G38) SAMEK B10 ;BZ-CO-O2 + RCO3 = RCO3 + HO2 + CO2 + PHEN

G35) 1.6E+15, 25.90 ;PBZN = BZ-CO-O2 + NO2 + RCO3

G43) 1.3E-11, -0.596 ;BZ-O + NO2 = NPHE

G44) SAMEK B5 ;BZ-O + HO2 = PHEN

G45) 1.0E-3 ;BZ-O = PHEN

G58) 3.6E-12 ;NPHE + NO3 = HNO3 + BZ(NO2)-O

G59) SAMEK G43 ;BZ(NO2)-O + NO2 = #2 XN + #6 XC ! DINITROPHENOL

G60) SAMEK B5 ;BZ(NO2)-O + HO2 = NPHE

G61) SAMEK G45 ;BZ(NO2)-O = NPHE

G7) 1.14E-11 ;HO + AFG1 = HCOCO-O2 + RCO3

G8) PF=ACROLEIN ;AFG1 + HV + #0.077 = HO2 + HCOCO-O2 + RCO3

U2OH) 1.72E-11 ;HO + AFG2 = C2CO-O2 + RCO3

U2HV) PF=ACROLEIN ;AFG2 + HV = HO2 + CO + CCO-O2 + RCO3

RCH4) 6.255E-13 2.548 2.0 ;CH4 + HO = HCHO + RO2-R + RO2

RZ1) 1.0 ;(HCHO2) = #.7 HCOOH + #.12 "HO + HO2 + CO" + &

 #.18 "H2 + CO2"

RZ2) 1.0 ;(CCHO2) = #.25 CCOOH + #.15 "CH4 + CO2" + #.6 HO + &

 #.3 "CCO-O2 + RCO3 " + #.3 "RO2-R + HCHO + CO + &

 RO2 "

RZ3) 1.0 ;(RCHO2) = #.25 CCOOH + #.15 CO2 + #.6 HO + &

#.3 "C2CO-O2 + RCO3 " + #.3 "RO2-R + CCHO + CO + &

 RO2 " + #.55 XC

RZ4) 1.0 ;(C(C)CO2) = HO + R2O2 + HCHO + CCO-O2 + RCO3 + RO2

RZ5) 1.0 ;(C(R)CO2) = HO + CCO-O2 + CCHO + R2O2 + RCO3 + RO2

RZ6) 1.0 ;(CYCCO2) = #.3 "HO + C2CO-O2 + R2O2 + RCO3 + &

 RO2 " + #.3 RCHO + #4.2 XC

RZ7) 1.0 ;(BZCHO2) = #.5 "BZ-O + R2O2 + CO + HO "

ETOH) 1.960E-12 -0.870 ;ETHE + HO = RO2-R + RO2 + #1.56 HCHO + #.22 CCHO

ETO3) 9.140E-15 5.127 ;ETHE + O3 = HCHO + (HCHO2)

ETN3) 5.430E-12 6.043 ;ETHE + NO3 = R2O2 + RO2 + #2 HCHO + NO2

ETOA) 1.040E-11 1.574 ;ETHE + O = RO2-R + HO2 + RO2 + HCHO + CO

A1OH) ;HO + ALK1 = #A1OHRR RO2-R + #A1OHNR RO2-N + &

 #A1OHXN RO2-XN + #A1OHNP RO2-NP + #A1OHRH HO2 + &

 #A1OHR2 R2O2 + #A1OHRS RO2 + #A1OHA1 HCHO + &

 #A1OHA2 CCHO + #A1OHA3 RCHO + #A1OHK3 ACET + &

 #A1OHK4 MEK + #A1OHCO CO + #A1OHC2 CO2 + &

 #A1OHPH PHEN + #A1OHCR CRES + #A1OHBZ BALD + &

 #A1OHGL GLY + #A1OHMG MGLY + #A1OHU1 AFG1 + &

 #A1OHU2 AFG2 + #A1OHTB C2(C)-O + #A1OHQ1 CCO-O2 + &
B-75

 #A1OHQ2 C2CO-O2 + #A1OHQS RCO3 + #A1OHXC XC

!

A2OH) ;HO + ALK2 = #A2OHRR RO2-R + #A2OHNR RO2-N + &

 #A2OHXN RO2-XN + #A2OHNP RO2-NP + #A2OHRH HO2 + &

 #A2OHR2 R2O2 + #A2OHRS RO2 + #A2OHA1 HCHO + &

 #A2OHA2 CCHO + #A2OHA3 RCHO + #A2OHK3 ACET + &

 #A2OHK4 MEK + #A2OHCO CO + #A2OHC2 CO2 + &

 #A2OHPH PHEN + #A2OHCR CRES + #A2OHBZ BALD + &

 #A2OHGL GLY + #A2OHMG MGLY + #A2OHU1 AFG1 + &

#A2OHU2 AFG2 + #A2OHTB C2(C)-O + #A2OHQ1 CCO-O2 + &

 #A2OHQ2 C2CO-O2 + #A2OHQS RCO3 + #A2OHXC XC

!

B1OH) ;HO + ARO1 = #B1OHRR RO2-R + #B1OHNR RO2-N + &

 #B1OHXN RO2-XN + #B1OHNP RO2-NP + #B1OHRH HO2 + &

 #B1OHR2 R2O2 + #B1OHRS RO2 + #B1OHA1 HCHO + &

 #B1OHA2 CCHO + #B1OHA3 RCHO + #B1OHK3 ACET + &

 #B1OHK4 MEK + #B1OHCO CO + #B1OHC2 CO2 + &

 #B1OHPH PHEN + #B1OHCR CRES + #B1OHBZ BALD + &

 #B1OHGL GLY + #B1OHMG MGLY + #B1OHU1 AFG1 + &

 #B1OHU2 AFG2 + #B1OHTB C2(C)-O + #B1OHQ1 CCO-O2 + &

 #B1OHQ2 C2CO-O2 + #B1OHQS RCO3 + #B1OHXC XC

!

B2OH) ;HO + ARO2 = #B2OHRR RO2-R + #B2OHNR RO2-N + &

 #B2OHXN RO2-XN + #B2OHNP RO2-NP + #B2OHRH HO2 + &

 #B2OHR2 R2O2 + #B2OHRS RO2 + #B2OHA1 HCHO + &

 #B2OHA2 CCHO + #B2OHA3 RCHO + #B2OHK3 ACET + &

 #B2OHK4 MEK + #B2OHCO CO + #B2OHC2 CO2 + &

 #B2OHPH PHEN + #B2OHCR CRES + #B2OHBZ BALD + &

 #B2OHGL GLY + #B2OHMG MGLY + #B2OHU1 AFG1 + &

 #B2OHU2 AFG2 + #B2OHTB C2(C)-O + #B2OHQ1 CCO-O2 + &

 #B2OHQ2 C2CO-O2 + #B2OHQS RCO3 + #B2OHXC XC

!

O1OH) ;OLE1 + HO = #O1OHRR RO2-R + #O1OHRN RO2-N + &

 #O1OHRS RO2 + #O1OHA1 HCHO + #O1OHA2 CCHO + &

 #O1OHA3 RCHO + #O1OHK3 ACET + #O1OHK4 MEK + &

 #O1OHBZ BALD + #O1OHXC XC

!

O1O3) ;OLE1 + O3 = #O1O3A1 HCHO + #O1O3A2 CCHO + &

 #O1O3A3 RCHO + #O1O3K3 ACET + #O1O3K4 MEK + &

 #O1O3BZ BALD + #O1O3Z1 (HCHO2) + #O1O3Z2 (CCHO2) + &

 #O1O3Z3 (RCHO2) + #O1O3Z4 (C(C)CO2) + &

 #O1O3Z5 (C(R)CO2) + #O1O3Z6 (CYCCO2) + &

 #O1O3Z8 (BZCHO2) + #O1O3OH HO + #O1O3RR RO2-R + &

 #O1O3RN RO2-N + #O1O3XN RO2-XN + #O1O3NP RO2-NP + &

 #O1O3RH HO2 + #O1O3R2 R2O2 + #O1O3RS RO2 + &

 #O1O3Q1 CCO-O2 + #O1O3Q2 C2CO-O2 + #O1O3QS RCO3 + &

 #O1O3XC XC

!

O1OA) ;OLE1 + O = #O1OARR RO2-R + #O1OARH HO2 + &

 #O1OARS RO2 + #O1OAA1 HCHO + #O1OAA3 RCHO + &

 #O1OAK4 MEK + #O1OACO CO + #O1OAXC XC

!

O1N3) ;OLE1 + NO3 = #O1N3N2 NO2 + #O1N3N3 HNO3 + &

 #O1N3RH HO2 + #O1N3RR RO2-R + #O1N3RN RO2-N + &

 #O1N3R2 R2O2 + #O1N3RS RO2 + #O1N3A1 HCHO + &

 #O1N3A2 CCHO + #O1N3A3 RCHO + #O1N3K3 ACET + &
B-76

 #O1N3K4 MEK + #O1N3BZ BALD + #O1N3XC XC

!

O2OH) ;OLE2 + HO = #O2OHRR RO2-R + #O2OHRN RO2-N + &

 #O2OHRS RO2 + #O2OHA1 HCHO + #O2OHA2 CCHO + &

 #O2OHA3 RCHO + #O2OHK3 ACET + #O2OHK4 M EK + &

 #O2OHBZ BALD + #O2OHXC XC

!

O2O3) ;OLE2 + O3 = #O2O3A1 HCHO + #O2O3A2 CCHO + &

 #O2O3A3 RCHO + #O2O3K3 ACET + #O2O3K4 MEK + &

 #O2O3BZ BALD + #O2O3Z1 (HCHO2) + #O2O3Z2 (CCHO2) + &

 #O2O3Z3 (RCHO2) + #O2O3Z4 (C(C)CO2) + &

 #O2O3Z5 (C(R)CO2) + #O2O3Z6 (CYCCO2) + &

 #O2O3Z8 (BZCHO2) + #O2O3OH HO + #O2O3RR RO2-R + &

 #O2O3RN RO2-N + #O2O3XN RO2-XN + #O2O3NP RO2-NP + &

 #O2O3RH HO2 + #O2O3R2 R2O2 + #O2O3RS RO2 + &

 #O2O3Q1 CCO-O2 + #O2O3Q2 C2CO-O2 + #O2O3QS RCO3 + &

 #O2O3XC XC

!

O2OA) ;OLE2 + O = #O2OARR RO2-R + #O2OARH HO2 + &

 #O2OARS RO2 + #O2OAA1 HCHO + #O2OAA3 RCHO + &

 #O2OAK4 MEK + #O2OACO CO + #O2OAXC XC

!

O2N3) ;OLE2 + NO3 = #O2N3N2 NO2 + #O2N3N3 HNO3 + &

 #O2N3RH HO2 + #O2N3RR RO2-R + #O2N3RN RO2-N + &

 #O2N3R2 R2O2 + #O2N3RS RO2 + #O2N3A1 HCHO + &

 #O2N3A2 CCHO + #O2N3A3 RCHO + #O2N3K3 ACET + &

 #O2N3K4 MEK + #O2N3BZ BALD + #O2N3XC XC

!

O3OH) ;OLE3 + HO = #O3OHRR RO2-R + #O3OHRN RO2-N + &

 #O3OHRS RO2 + #O3OHA1 HCHO + #O3OHA2 CCHO + &

 #O3OHA3 RCHO + #O3OHK3 ACET + #O3OHK4 MEK + &

 #O3OHBZ BALD + #O3OHXC XC

!

O3O3) ;OLE3 + O3 = #O3O3A1 HCHO + #O3O3A2 CCHO + &

 #O3O3A3 RCHO + #O3O3K3 ACET + #O3O3K4 MEK + &

 #O3O3BZ BALD + #O3O3Z1 (HCHO2) + #O3O3Z2 (CCHO2) + &

 #O3O3Z3 (RCHO2) + #O3O3Z4 (C(C)CO2) + &

 #O3O3Z5 (C(R)CO2) + #O3O3Z6 (CYCCO2) + &

 #O3O3Z8 (BZCHO2) + #O3O3OH HO + #O3O3RR RO2-R + &

 #O3O3RN RO2-N + #O3O3XN RO2-XN + #O3O3NP RO2-NP + &

 #O3O3RH HO2 + #O3O3R2 R2O2 + #O3O3RS RO2 + &

 #O3O3Q1 CCO-O2 + #O3O3Q2 C2CO-O2 + #O3O3QS RCO3 + &

 #O3O3XC XC

!

O3OA) ;OLE3 + O = #O3OARR RO2-R + #O3OARH HO2 + &

 #O3OARS RO2 + #O3OAA1 HCHO + #O3OAA3 RCHO + &

 #O3OAK4 MEK + #O3OACO CO + #O3OAXC XC

!

O3N3) ;OLE3 + NO3 = #O3N3N2 NO2 + #O3N3N3 HNO3 + &

 #O3N3RH HO2 + #O3N3RR RO2-R + #O3N3RN RO2-N + &

 #O3N3R2 R2O2 + #O3N3RS RO2 + #O3N3A1 HCHO + &

 #O3N3A2 CCHO + #O3N3A3 RCHO + #O3N3K3 ACET + &

 #O3N3K4 MEK + #O3N3BZ BALD + #O3N3XC XC

!

! END OF FILE
B-77

Attachment B2 – Listing of Reactions of Isoprene

(Condensed 1-Product)

ISOH) 2.54E-11 -0.81 ;ISOP + HO = #.088 RO2N + #.912 RO2R + &

 #.629 HCHO + #.912 ISPD + #.079 R2O2 + &

 #1.079 RO2

! #1.079 RO2 + #.283 XC

ISO3) 7.86E-15 3.80 ;ISOP + O3 = #.4 HCHO + #.6 ISPD + #.55 BHCHO2 + &

 #.2 CC3O2 + #.2 CC3HO2

! #.2 CC3O2 + #.2 CC3HO2 + #.05 XC

ISOA) 3.60E-11 ;ISOP + O = #.75 ISPD + #.25 "C3O3 + &

 RCO3 + #2 HCHO + RO2R + RO2"

!ISOA) 3.60E-11 ;ISOP + O = #.75 "ISPD + XC "+ #.25 "C3O3 + &

! RCO3 + #2 HCHO + RO2R + RO2"

ISN3) 3.03E-12 0.89 ;ISOP + NO3 = #.8 "RCHO + RNO3 + RO2R " + &

 #.2 "ISPD + R2O2 + NO2" + RO2

! #.2 "ISPD + R2O2 + NO2" + RO2 + #-2.2 XC

ISN2) 1.50E-19 ;ISOP + NO2 = #.8 "RCHO + RNO3 + RO2R " + &

 #.2 "ISPD + R2O2 + NO" + RO2

! #.2 "ISPD + R2O2 + NO" + RO2 + #-2.2 XC

!

IPOH) 3.36E-11 ;ISPD + HO = #.293 CO + #.252 CCHO + #.126 HCHO + &

 #.041 GLY + #.021 RCHO + #.168 MGLY + #.314 MEK + &

 #.503 RO2R + #.21 CCO3 + #.288 C3O3 + &

 #.21 R2O2 + #.713 RO2 + #.498 RCO3

! #.21 R2O2 + #.713 RO2 + #.498 RCO3 + #-.112 XC

IPO3) 7.11E-18 ;ISPD + O3 = #.02 CCHO + #.04 HCHO + #.01 GLY + &

 #.84 MGLY + #.09 MEK + #.66 BHCHO2 + &

 #.09 HCOCHO2 + #.18 HOCCHO2 + #.06 C2O2CHO + &

 #.01 COHC2O2

! #.01 COHC2O2 + #-.39 XC

IPHV) PF=ACROLEIN ;ISPD + HV + #.0036 = #.333 CO + #.067 CCHO + &

 #.9 HCHO + #.033 MEK + #.333 HO2 + #.7 RO2R + &

 #.267 CCO3 + #.7 C3O3 + #.7 RO2 + &

 #.967 RCO3

! #.967 RCO3 + #-.133 XC

IPN3) 1.0E-15 ;ISPD + NO3 = #.643 CO + #.282 HCHO + #.85 RNO3 + &

 #.357 RCHO + #.925 HO2 + #.075 C3O3 + &

 #.075 R2O2 + #.925 RO2 + #.075 RCO3 + #.075 HNO3

! #.075 R2O2 + #.925 RO2 + #.075 RCO3 + #.075 HNO3 + &

! #-2.471 XC

ISZ1) 1.0 ;CC3O2 = HO + R2O2 + HCHO + C3O3 + RO2 + &

 RCO3

ISZ2) 1.0 ;CC3HO2 = #.75 RCHO + #.25 ISPD

!ISZ2) 1.0 ;CC3HO2 = #.75 RCHO + #.25 ISPD + #.5 XC

MAZ1) 1.0 ;C2O2CHO = HO + R2O2 + HCHO + HC2O4 + RO2 + &

 RCO3

M1Z1) 1.0 ;HOCCHO2 = #.6 HO + #.3 "CCO3 + RCO3" + &

 #.3 "RO2R + HCHO + CO + RO2"

! #.3 "RO2R + HCHO + CO + RO2" + #.8 XC
B-78

M2Z1) 1.0 ;HCOCHO2 = #.12 "HO2 + #2 CO + HO" + &

 #.51 HCHO

!M2Z1) 1.0 ;HCOCHO2 = #.12 "HO2 + #2 CO + HO" + #.74 XC + &

! #.51 "CO2 + HCHO"

M2Z2) 1.0 ;COHC2O2 = HO + MGLY + HO2 + R2O2 + RO2

 ! END OF FILE

Attachment B3 – Listing of Explicit Reaction Mechanisms for

Other VOCs

OH001) 2.500E-12 0.397 0.000 ;C6H6 + HO = #.236 PHEN + #.207 GLY &

 + #1.44 AFG1 + #.764 RO2-R + #.236 HO2 &

 + #1.29 XC + #.764 RO2

!

OH033) 1.480E-11 -0.890 0.000 ;BUTD + HO = RO2-R + RO2 + HCHO + RCHO

!

O3033) 1.340E-14 4.537 0.000 ;BUTD + O3 = #.6 HCHO + RCHO + #-1.2 XC &

 + #.4 (HCHO2) + #.6 (CCHO2)

!

N3033) 1.000E-13 0.000 0.000 ;BUTD + NO3 = R2O2 + RO2 + HCHO + RCHO &

 + NO2

!

OA033) 2.100E-11 0.000 0.000 ;BUTD + O = #.4 HO2 + #.5 RCHO + #.5 MEK &

 + #.5 XC

!

OH018) 3.840E-13 0.000 0.000 ;PDCB + HO = #.236 PHEN + #.207 GLY &

 + #1.44 AFG1 + #.764 RO2-R + #.236 HO2 &

 + #1.29 XC + #.764 RO2

OH152) 9.640E-12 2.403 0.000 ;PERC + HO = RO2-R + CCHO + RO2

!

OH086) 6.14E-18 1.987 2.000 ;DICM + HO = RO2-R + HCHO + RO2

!

AS1) 6.14E-25 ; AS = AS

CR1) 6.14E-25 ; CRVI = CRVI

!

 C1) PF=HCHONEWR ;FORM + HV = #2 HO2 + CO

 C2) PF=HCHONEWM ;FORM + HV = H2 + CO

 C3) 1.125E-12 -1.288 2.0 ;FORM + HO = HO2 + CO + H2O

 C4) 9.7E-15, -1.242 ;FORM + HO2 = HOCOO

 C9) 2.8E-12, 5.00 ;FORM + NO3 = HNO3 + HO2 + CO

!

 C10) 5.55E-12, -0.618 ;ALD + HO = CCO-O2 + H2O + RCO3

 C11A) PF=CCHOR ;ALD + HV = CO + HO2 + HCHO + RO2-R + RO2

 C12) 1.4E-12, 3.696 ;ALD + NO3 = HNO3 + CCO-O2 + RCO3

!

OH091) 5.560E-13 -1.057 2.000 ;ETOH + HO = #.1 RO2-R + #.9 HO2 &

 + #.156 HCHO + #.922 CCHO + #.1 RO2

!

OH108) 6.129E-13 -0.914 2.000 ;MTBE + HO = #.02 RO2-N + #.98 RO2-R &
B-79

 + #.37 R2O2 + #.39 HCHO + #.41 MEK + #2.87 XC &

 + #1.37 RO2

! END OF FILE