FINAL 2007 AQMP 

APPENDIX V 

MODELING AND ATTAINMENT DEMONSTRATIONS 

JUNE, 2007 
SOUTH COAST AIR QUALITY MANAGEMENT DISTRICT 

GOVERNING BOARD 

Chairman: WILLIAM A. BURKE, Ed.D. 

Speaker of the Assembly Appointee 

Vice Chairman: S. ROY WILSON, Ed.D. 

Supervisor, Fourth District 

Riverside County Representative 

MEMBERS:

MICHAEL D. ANTONOVICH 

Supervisor, Fifth District 

Los Angeles County Representative 

BILL CAMPBELL 

Supervisor, Third District 

Orange County Representative 

JANE W. CARNEY 

Senate Rules Committee Appointee 

RONALD O. LOVERIDGE 

Mayor, City of Riverside Cities 

Representative, Riverside County 

GARY OVITT 

Supervisor, Fourth District 

San Bernardino County Representative 

JAN PERRY 

Councilmember, City of Los Angeles 

Cities Representative, Los Angeles County, Western Region 

MIGUEL A. PULIDO 

Mayor, City of Santa Ana 

Cities Representative, Orange County 

TONIA REYES URANGA 

Councilmember, City of Long Beach 

Cities Representative, Los Angeles County, Eastern Region 

VACANT 

Governor’s Appointee 

DENNIS YATES 

Mayor, City of Chino 

Cities Representative, San Bernardino County 

EXECUTIVE OFFICER:

BARRY R. WALLERSTEIN, D.Env. 

. 
i 

CONTRIBUTORS

Elaine Chang, DrPH 

Deputy Executive Officer 

Planning, Rule Development and Area Sources 

Laki Tisopulos, Ph.D., P.E. 

Assistant Deputy Executive Officer 

Planning, Rule Development and Area Sources 

Joseph Cassmassi 

Planning & Rules Manager 

Planning, Rule Development and Area Sources 

Kevin Durkee Chris Nelson 

Mark Bassett Zorik Pirveysian 

Kathy Hsiao Jill Whynot 

Bong-Mann Kim Susan Yan 

Satoru Mitsutomi Zhang, Xinqiu 

Production

Faye Thomas 

Donna Vernon 

CALIFORNIA AIR RESOURCES BOARD

Linda Murchison 

Division Chief 

Technical Support Division 

John DaMassa 

Branch Chief 

Kurt Karperos 

Branch Chief 

Bruce Jackson Sylvia Oey 

LucilleVan Ommering 
Table of Contents 

i 

Table of Contents 

CHAPTER 1 Modeling Overview 

Introduction........................................................................................................... V-1-1

Attainment Designation and Control Strategy........................................... V-1-1

Model Selection ......................................................................................... V-1-2

Modeling Methodology ........................................................................................ V-1-4

Design Values and Relative Response Factors (RRF) .............................. V-1-4

PM2.5......................................................................................................... V-1-6

Annual PM2.5 Modeling Approach ............................................... V-1-7

Episodic 24-Hr Average PM2.5 Modeling Approach.................... V-1-8

PM10.......................................................................................................... V-1-9

Ozone .........................................................................................................V-1-10

Modeling Approach........................................................................ V-1-10

Application of RRF’s...................................................................... V-1-12

Uncertainties Associated with the Technical Analysis......................................... V-1-12

Demographic and Growth Projections....................................................... V-1-13

Input Elements to Air Quality Models....................................................... V-1-13

Ambient Air Quality Monitoring Data ...................................................... V-1-13

Meteorological Measurements................................................................... V-1-13

Emissions Inventory .................................................................................. V-1-14

Air Quality Models .................................................................................... V-1-14

Are There Any Safeguards Against Uncertainties?................................... V-1-14

Document Organization ........................................................................................ V-1-15

CHAPTER 2 The Federal PM2.5 Attainment Demonstration Plan 

Introduction........................................................................................................... V-2-1

PM2.5 Data: MATES-III and FRM.......................................................... V-2-2

MATES-III Monitoring .................................................................. V-2-2

MATES-III Speciated Data ............................................................ V-2-3

FRM PM2.5 .................................................................................... V-2-10

Sandwich and Speciated Monitored Attainment (SMAT).................................... V-2-12

Sandwich.................................................................................................... V-2-12

SMAT ........................................................................................................V-2-15

CAMx and MM5 Overview.................................................................................. V-2-15

Modeling Domain ...................................................................................... V-2-15 

Boundary, Top Conditions......................................................................... V-2-16 
Final 2003 AQMP Appendix V 

ii 

MM5 Simulations ...................................................................................... V-2-18 

Emissions Inventory.............................................................................................. V-2-19

Paved Road Dust Emissions Uncertainties................................................ V-2-22

PM2.5 Split Profiles and Ammonia Inventory Adjustments..................... V-2-23

Base-Year Annual Simulations............................................................................. V-2-24

PM2.5 Component Species Performance Evaluation for the 

MATES-III Sites................................................................................. V-2-25

Annual Average SSI Mass Performance Evaluation................................. V-2-47 

Base Year Model Performance Stress Test Evaluation ............................. V-2-47 

Future Air Quality................................................................................................. V-2-48

SMAT Annual PM2.5 Attainment Demonstration.................................... V-2-52

2015 CAMx Grid-Cell Evaluation............................................................. V-2-54

SMAT 24-Hour PM2.5 Attainment Demonstration .................................. V-2-54 

Weight of Evidence............................................................................................... V-2-59 

Air Quality Trends ..................................................................................... V-2-59

Emissions Trends....................................................................................... V-2-60

Mobile Source Emissions and VMT.......................................................... V-2-62

CHAPTER 3 The Federal 24-Hour PM10 Attainment 

Demonstration Plan and Visibility Assessment 

Introduction........................................................................................................... V-3-1

Modeling Methodology ........................................................................................ V-3-1

Future Year Air QUality ....................................................................................... V-3-2

PM10 24-hour Attainment Demonstration ................................................ V-3-2

PM10 Annual Analysis.............................................................................. V-3-2

Visibility................................................................................................................ V-3-4

Background................................................................................................ V-3-4

Visibility Modeling.................................................................................... V-3-4

Prior Visibility Modeling Results.............................................................. V-3-5

Predicted Future Air Quality...................................................................... V-3-6

Future Visibility Projections...................................................................... V-3-6

Future Light Extinction Budgets at Riverside ................................ V-3-8
Table of Contents 

iii 

CHAPTER 4 Revision to the 2003 Ozone Attainment 

Demonstration Plan 

Introduction........................................................................................................... V-4-1 

Model Selection ......................................................................................... V-4-2 

Modeling Approach ................................................................................... V-4-3 

Federal 8-Hour Ozone Standard Requirements......................................... V-4-4 

California Requirements and Population Exposure................................... V-4-6 

Emissions Summary.............................................................................................. V-4-8 

Introduction................................................................................................ V-4-8 

Historical Baseline Emissions ................................................................... V-4-9 

Future Controlled Emissions ..................................................................... V-4-10 

Episode Selection.................................................................................................. V-4-11 

Conceptual Model of an 8-Hour Ozone Episode....................................... V-4-12 

Statistical Episode Characterization and Ranking.....................................V-4-14 

Model Input Preparation ............................................................................ V-4-15 

Boundary and Top Air Quality Concentrations.........................................V-4-17 

Future Boundary, Top and Initial Air Quality Conditions ........................V-4-18 

Meteorological Models ..............................................................................V-4-19 

Base-Year Perfomance Evaluation ....................................................................... V-4-24 

Statistical Evaluation ................................................................................. V-4-25 

Graphical Evaluation ................................................................................. V-4-32 

Effect of Emissions Uncertainties.............................................................. V-4-44 

Ozone Air Quality Projections.............................................................................. V-4-45 

Graphical Distribution ...............................................................................V-4-47 

Projection of 2018 Air Quality in the Coachella Valley ........................... V-4-51 

Sensitivity Studies: Model Performance and CEQA............................................V-4-52 

Weight of Evidence............................................................................................... V-4-54 

CHAPTER 5 Summary and Conclusions 

Comparison to State and Federal Standards ......................................................... V-5-1 

Basin Emissions Carrying Capacity (Emissions Budget)..................................... V-5-1 

REFERENCES 
CHAPTER 1 

MODELING OVERVIEW 

Introduction 

Modeling Methodology 

Uncertainties Associated with the Technical Analysis 

Document Organization 
Chapter 1 Modeling Overview 

INTRODUCTION 

This appendix to the Final 2007 AQMP provides the details of the modeling attainment 

demonstrations presented in Chapter V of the main document. The federal Clean Air 

Act (CAA) sets forth specific criteria to use air quality simulation modeling techniques 

to estimate future air quality in areas that do not meet the air quality standards. This 

Final 2007 AQMP provides future year attainment demonstrations for two new 

pollutants: 8-hour average ozone and both annual and 24-hour average PM2.5. 

The South Coast Air Basin (Basin) is currently designated nonattainment for PM2.5, 

ozone (8-hours), PM10 (24-hours) and carbon monoxide. On February 24, 2006, CARB 

forwarded the District’s request to U.S. EPA to redesignate the Basin attainment for 

carbon monoxide. Air quality monitoring data measured from 2001 through 2005 

indicated that the standard had been achieved and currently continues to be met. Future 

year projections of CO provided in the 2003 AQMP and projections from CARB’s 

EMFAC2002 emissions model were used to support the redesignation request and 

provide the basis for a CO maintenance plan for the Basin. EPA’s final approval of the 

redesignation request is currently pending. 

Similarly, on October 17, 2006, the Federal Register codified EPA’s decision revoking 

the annual PM10 standard. The action left the 24-hour average PM10 standard in place. 

The Basin has not experienced any violations of 24-hour average PM10 standard except 

during a few special events. The District has yet to seek redesignation to attainment for 

PM10 however it will pursue such a request in the near future. Regardless, the Final 

2007 AQMP will provide an updated attainment demonstration for 24-hour average 

PM10 to serve as the basis for a future maintenance plan. 

The 2003 modeling attainment demonstrations served as an update of the 1997 AQMP 

ozone, PM10 and carbon monoxide plans for the South Coast Air Basin and other 

portions of the Southeast Desert Modified Nonattainment Area that are under the 

District’s jurisdiction and were submitted as part of the California SIP. The Final 2007 

AQMP provides attainment demonstrations for 8-hour ozone and PM2.5 and provides 

similar linkage to the 2003 1-hour ozone and PM10 attainment demonstrations. This 

plan reflects the updated emissions baseline and future year estimates, new technical 

information and enhanced air quality modeling techniques and episodes. 

Attainment Designation and Control Strategy 

The Basin is currently designated nonattainment for PM2.5, and severe-17 

nonattainment for ozone. The District will request that U.S. EPA accept a voluntary 

reclassification for the Basin from “Severe-17” to “Extreme” nonattainmnet through the 

Governing Board’s adoption of this Final AQMP and resolution. This action will enable 

V - 1- 1 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

the use of long-term measures in the control strategy and extend the attainment date to 

June 15, 2024. In addition, the District will request that U.S. EPA accept a voluntary 

reclassification for the Coachella Valley portion of the Salton Sea Air Basin from 

“Serious” to “Severe-15” nonattainmnet to extend the attainment date to June 15, 2018. 

PM2.5 and ozone, are linked to common precursor emissions. The District’s goal is to 

develop an integrated control strategy which: 1) ensures that ambient air quality 

standards for all criteria pollutants are met by the established deadlines in the federal 

Clean Air Act (CAA); and 2) achieves an expeditious rate of reduction towards the state 

air quality standards. The overall control strategy is designed so that efforts to achieve 

the standard for one criteria pollutant do not cause unnecessary deterioration of another. 

A two-step modeling process has been conducted for the 2007 AQMP. First, future year 

annual and 24-hour average PM2.5 is simulated to demonstrate attainment by 2015. The 

future year 8-hour average ozone emissions control strategy then builds upon the PM2.5 

strategy to demonstrate attainment of the federal standard in the downwind Coachella 

Valley by 2018 and the Basin by 2024. This two-step approach is described in Chapter 

4 of the main document and the control measures are extensively discussed in 

Appendices IVA, IVB and IVC. The two-step approach is also consistent with the 

approach used in the 2003 AQMP to first demonstrate attainment in 2006 of the PM10 

standard and subsequent attainment of the 1-hour average ozone standard in 2010. 

Model Selection 

During the development of the 2003 Plan, the District convened a panel of seven experts 

to independently review the regional air quality modeling conducted for ozone and 

PM10. The focus of the panel’s review was to provide guidance in the selection of an 

appropriate meteorological-air quality dispersion platform for the attainment analysis. 

At that time, District and CARB modeling staff were evaluating three potential models 

for application using SAPRC99 chemistry: California Photochemical Grid Model 

(CALGRID) [Yamartino, et. Al, 1989], the Comprehensive Air Quality Model with 

Extensions (CAMx) [Environ, 2002], and the Urban Airshed Model (UAM) [EPA, 

1990]. The performance of the three models varied with only UAM displaying the 

capacity to closely recreate the peak 1-hour average ozone concentrations observed for 

the August 5, 1997 meteorological episode. The performance of the CAMx and 

CALGRID simulations was similar and although they under-predicted peak 

concentrations, model output provided a better characterization of the spatial distribution 

of ozone in the Basin. 

In general, the recommendations of the panel members supported the use of the UAM 

modeling platform for the 2003 attainment demonstrations, primarily based upon the 

District staff’s familiarity with the model and that goal of recreating the regional peak 

ozone concentrations was critical. They also recommended that a relative reduction 

V- 1 - 2 
Chapter 1 Modeling Overview 

approach be applied to the performance of CAMx and CALGRID to see if future year 

emissions reductions would be consistent with the UAM projected rates of reduction. 

Most important, the consensus of the panel was for the District to move from UAM to 

the more current state-of-the-art dispersion platforms and chemistry modules. Among 

the recommended candidates were the Community Multiscale Air Quality Model 

(CMAQ) [USEPA, 1999] and CAMx both coupled with SAPRC99 chemistry and the 

prognostic Pennsylania State University / National Center for Atmospheric Research 

Mesoscale Model Version 5 (MM5) [Grell,et. al., 1994]. Both CAMx and CMAQ can 

simulate ozone and PM2.5 concentrations together in a “one-atmosphere” approach and 

in response to the expert panel recommendations, District and CARB staff has selected 

CAMx as the primary regional dispersion modeling platform for the attainment 

demonstrations. 

Table V-1-1 provides a summary comparison of the modeling technology used in the 

2003 and Final 2007 AQMP’s. 

TABLE V-1-1 

Comparison of Modeling Methodologies used in the 2003 and Final 2007 AQMP 

Mechanism Ozone PM2.5 

 2003 AQMP Final 2007 

AQMP 

2003 AQMP Final 2007 

AQMP 

Dispersion 

Platform 

UAM-IV CAMx UAM-IV CAMx 

Chemistry SAPRC99 SAPRC99 AERO-LT/ 

CB-IV 

PMCAMx 

“One 

Atmosphere” 

Meteorology CALMET/ 

Hybrid 

MM5/FDDA Diagnostic 

Wind Model 

MM5 

Mobile 

Emissions 

EMFAC2002 EMFAC2007 EMFAC2002 EMFAC2007 

Boundary EPA “Clean”/ 

SCOS97 

WRAP-CAMxGEOCHEM Modified EPA 

“Clean” 

WRAP-CAMxGEOCHEM 

The following sections provide a brief overview of the PM2.5, PM10 and ozone 

modeling methodologies. Wherever possible, the Draft Modeling Protocol will be used 

V - 1- 3 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

as a reference document to avoid duplicating presentation material. Draft Modeling 

Protocol is included in this Appendix as Attachment 1. 

MODELING METHODOLOGY 

Design Values and Relative Response Factors (RRF) 

The Final 2007 AQMP modeling approach to demonstrate attainment of the air quality 

standard relies heavily on the use of design values and relative response factors (RRF, 

previously referred as relative reduction factors) to translate regional modeling 

simulation output to the form of the air quality standard. Both ozone and PM2.5 have 

standards that require three consecutive years of monitored data, averaged by a designed 

form, to assess compliance. In the case of ozone, compliance to the standard is 

determined from a three year average of the 4th highest daily ozone 8-hour average 

concentration. The PM2.5 annual design value is determined from quarterly average 

PM2.5 concentrations, averaged by year, for a three year period. For the 24-hour 

average PM2.5 design value, the 98th percentile daily concentration sampled from a year 

is selected and then averaged for a three year period. The complexity of the design 

values does not lend itself to a direct attainment demonstration that relies on explicit air 

quality model simulation predictions of future air quality based on one or several 

meteorological episodes. 

Design Value Selection 

EPA guidance recommends the use of multiple year averages of design values, where 

appropriate, to dampen the effects of single year anomalies to the air quality trend due to 

factors such as adverse or extremely favorable meteorology or radical change in the local 

emissions profile. For Basin 8-hour average ozone, the trend of the design values, each 

calculated using 3-years of data (depited in Figure V-1-1a.) is relative unchanged 

between 2001 and 2005. Given this configuration, a three-year weighted average of the 

design values is representative of the design value centered around 2002, the preferred 

year for the baseline inventory development and is used in the ozone attainment 

demonstration. 

The trend in the Basin PM2.5 design values (also calculated using 3-years of data) from 

2001 through 2005 (Figure 5-1b) is significantly different from ozone, depicting a sharp 

reduction in concentration over the period. The design value for 2001 is 30.1 μg/m3 

while the 2005 design value (based on data from 2003, 2004 and 2005) is 22.6 μg/m3. 

V- 1 - 4 
Chapter 1 Modeling Overview 

110

115

120

125

130

135

Ozone Concentration (ppb)

2001 2002 2003 2004 2005

FIGURE V-1-1a 

South Coast Air Basin 8-Hour Ozone Design Values 

(Each value represents the 3-year average of the 4th highest ozone concentration) 

20

22

24

26

28

30

32

2001 2002 2003 2004 2005

PM2.5 Concentration (ug/m3)

FIGURE V-1-1b 

South Coast Air Basin Annual PM2.5 Design Values 

(Each value represents the 3-year average of the highest annual average PM2.5 concentration) 

The reduction of seven and one half micrograms per cubic meter occurred for the same 

meteorology as the ozone design trend. Similar reductions can be observed in the 

component contributions of nitrate and sulfate in the PM10 FRM data over the same 

period. Since the trend in PM2.5 is steadily moving in the direction of air quality 

improvement, it is more reasonable to use a representative design value that is not locked 

in a multiple year average that overly reflects data that are not consistent with the current 

air quality trend. The 2005 design value includes the speciated data (monitored in 2005) 

that is used in the attainment demonstration. Furthermore, if the preliminary 2006 

PM2.5 data are included in the analysis, the 2006 PM2.5 design would value 20.7 μg/m3

. 

The revise weighted design value centered around 2005 (including data from 2003 

V - 1- 5 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

through 2006) would be 22.7 μg/m3, essentially the same value as the 2005 design of 

22.6 μg/m3

. To reflect the ambient trend of PM2.5 and preserve data consistency, the 

PM2.5 attainment demonstration is based on the 2005 design value. 

Relative Response Factors and Future Year Design Values 

To bridge the gap between air quality model output evaluation and applicability to the 

health based air quality standards, EPA guidance (EPA, 2006) has proposed the use of 

relative response factors. The RRF is simply a ratio of future year predicted air quality 

with the control strategy fully implemented to the simulated air quality in the base year. 

The attainment demonstration consists of multiplying the non-dimensional RFF to the 

base year design value to predict the future year design value. Thus, the simulated 

improvement in air quality, based on one or more meteorological episodes, is translated 

as a metric that directly determines compliance in the form of the standard. EquationsV1 and V-2 summarize the calculation. 

Eq. V-1. 

RRFi = Future-Year Model Predictioni / Base-Year Model Predictioni 

 where i is the pollutant or species 

Eq V-2. 

 Attainment Demonstration 

= Σ RRFi X Design Valuei ≤ Air Quality Standard 

 

 

The modeling analyses described above use the RRF and design value approach to 

demonstrate future year attainment of the standards. 

PM2.5 

The Final 2007 AQMP employs CAMx using the “one atmosphere” approach comprised 

of the CB-IV gas phased chemistry and a static two-mode particle size aerosol module as 

the particulate modeling platform. The analysis follows EPA’s recommended speciated 

modeling attainment test (SMAT), whereby model simulations for the base and futureyear controlled emissions are used to generate RRFs at selected sites where monioting 

data is available for individual species. The site and species specific RRFs are 

calculated on a quarterly basis and then applied to quarterly desing values to determine 

attainment. The procedure is significant departure from the 2003 AQMP where a direct 

V- 1 - 6 
Chapter 1 Modeling Overview 

deterministic approach was used to directly calculate future year PM2.5 from model 

output. 

In the 2003 AQMP the UAMAERO-LT model was used to simulate annual average 

Basin concentrations of PM2.5 and PM10. UAMAERO-LT model was a simplified 

version of the UAM-AERO model. The detailed thermodynamic routine (ISOROPIA) 

of the UAM-AERO model was replaced with the parameterized inorganic gas/aerosol 

partitioning module. The secondary organic aerosol formation scheme was replaced 

with a condensed version of the Carnegie Melon University (CMU) secondary organic 

aerosol module. The CMU module treats organic products as semi-volatile species and 

employs an equilibrium approach to the gas/aerosol partitioning of these species. In 

addition, the detailed particle-sizing scheme used in the UAM-AERO model was also 

replaced by an observation-based, two size (fine and coarse) particle-sizing scheme for 

secondary aerosols. UAMAERO-LT utilized a full Carbon Bond IV gas-phase chemical 

mechanism to simulate the formation of particulate nitrate, sulfate, ammonium, organic 

carbon, elemental carbon and other primary particles. By implementing the fine and 

coarse particle-sizing scheme for secondary aerosols, the 2003 AQMP was able to 

provide a first look at future year PM2.5 and the initial required emissions reductions 

that would be needed to attain the proposed federal standard. 

The preliminary PM2.5 modeling approach crafted for the 2007 AQMP was to move the 

empirical AERO-LT chemistry from the UAM to CAMx to take advantage of the 

advanced dispersion platform. Parallel testing was conducted to evaluate the 

CAMx/AERO-LT performance against CAMx using the “one atmosphere” approach 

comprised of the the CB-IV chemistry and a static two-mode particle size aerosol 

module. The results of the analysis indicated that the two model/chemistry packages 

were performing similarly and that the speed of simulating an annual average using 

CAMx “one atmosphere” was approximately equal to that of the AERO-LT 

combination. As a consequence, the PM2.5 modeling approach shifted to the use of the 

CAMx “one atmosphere” as the primary tool. 

Annual PM2.5 Modeling Approach

In the Final 2007 AQMP, CAMx annual average PM2.5 modeling simulations were 

generated for 2005, 2014 and 2020 baseline emissions and 2014 and 2020 controlled 

emsissions scenarios. The 2005 CAMx simulation was conducted using baseline 

monthly temperature and humidity corrected emissions, for a weekday, Saturday and 

Sunday activity profile. Seasonal boundary conditions were extracted from the Western 

Regional Air Partnership (WRAP) regional modeling simulations (initialized from 

global air quality model output) in support of the Regional Haze Rule demonstrations. 

The simulations were driven by MM5 meteorological fields; five day-simulations with a 

one day “ramp-up” period using NCEP model inintialzation. 

V - 1- 7 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

CAMx simulations used the same region (5 km squared grid, 280 easting and 3650 

northing, 65 by 40 grid cells) as that used for the 2003 UAMAERO-LT analyses. The 

vertical structure was increased to 11 layers (compared with the 5-layer analysis of 

UAMAERO-LT), but less than the 19 layers used for the MM5 simulations in an effort 

to conserve computational resources. MM5 was used to generate the meteorological 

profile for each day in 2005. The MM5 simulations were generated for the larger 

SCOS97 modeling domain employing a 5 km square grid and fit to the smaller PM2.5 

grid. The MM5 simulations were initialized from NCEP analyses and run for 5-day 

increments without the four-dimensional-data-assimilation (FDDA) option. 

Speciated PM2.5 data measured from the District’s Multiple Air Toxic Evaluation 

Program (MATES-III) during 2005 provided the characterization for evaluation and 

validation of the CAMx annual and episodic demonstrations. A brief summary of the 

MATES-III field program and a detailed description of the data is provided in Chapter 2. 

Model performance was evaluated against monitored particulate PM2.5 air quality data 

for six species (ammonium, nitrates, sulfates, organic carbon, elemental carbon, and 

primary) and total particulate mass. Annual data from eight MATES-III monitoring 

sites, including Los Angeles, Anaheim, Wilmington, Long Beach, Compton, Burbank, 

Rubidoux, and Fontana, were used in the validation. The future year attainment 

demonstration was analyzed for 2014 controlled emissions, thus enabling an annual 

demonstration based on a control strategy that would be fully implemented by January 1, 

2015. 

Future year PM2.5 air quality (2014 and 2020) was determined using site and species 

specific RRF’s applied to 2005 PM2.5 design values per EPA guidance documents. The 

quarterly RRF’s were calculated from the controlled 2014 simulation and the 2005 

baseline simulation. The design values were determined from the federal reference 

method Size Selective Inlet (SSI) High-Vol PM2.5 data measured at the District’s air 

monitoring network from 2003-2005. The SSI PM2.5 design values were calculated by 

quarter then apportioned by species based on the distribution observed in the MATES-III 

data. 

Episodic 24-Hr Average PM2.5 Modeling Approach

Per PM2.5 guidance, two options are provided to determine RRFs for the future year 24-

hour average PM2.5 attainment demonstration. The first option uses episodic modeling 

with day-specific emissions for representative meteorological episodes to calculate RRFs 

and apply the RRF to the design value. The second approach proposed by EPA relies on 

an average response to implementation of emissions control for the top 25 percentile of 

days in each quarter of the annual model simulation. 

The maximum 24-hour PM2.5 design value (based on 2003-2005 data) for the Basin 

(64.8 μg/m3

) meets the current federal standard. Of great interest is how will the 24-

V- 1 - 8 
Chapter 1 Modeling Overview 

hour PM2.5 concentration fair compared to the new standard of 35 μg/m3 when that 

standard become effective in 2010. On the basis of our initial simulations and analysis, 

the District staff feels that the future design calculation based on the top 25 percentile 

day, quarterly is more conservative than the episodic modeling. AQMD recommends 

the use of the 25 percentile approach. 

 Episodic Simulations 

The first approach to determine future year 24-hour maximum or 98th percentile PM2.5 

impacts relied on the simulation of one or more representative peak PM2.5 epsiodes 

where observed concentrations exceed 65 μg/m3

. The peak PM2.5 24-hour average 

concentration observed in the Basin during the 2005 MATES-III monitoring program 

(110 μg/m3 at Rubidoux) occurred on October 22, 2005. Episode specific emissions for 

the peak and preceding days were temperature and humidity corrected and MM5/FDDA 

simulations were generated to provide the meteorological imput. 

 Quarterly Top 25 Percentile 

For this approach, the 2005 observational data are sorted by quarter of year and further 

into the top 25 percent of days in each quarter. PM2.5 RRFs are calculated on a 

quarterly basis from the future and base year annual simulations for only those days in 

the top 25 percentile per quarter. The quarterly RRFs for the “top 25 percent days” are 

then applied to the quarterly 24-hour average PM2.5 design values to develop quarterly 

future year design values which are later aggregated into an annual 24-hour future year 

design value to assess attainment. (The measured quarterly 24-hour average PM2.5 

design values were comprised of the 98th percentile data in each quarter for the years 

2003, 2004 and 2005). Several variations of the episodic and quarterly top 25 percentile 

future year calculations were conducted and are presented and discussed in Chapter 2. 

PM10 

As previously discussed, on September 21, 2006 the U.S. EPA administrator signed the 

final documents that eliminated the existing annual PM10 standard. The action retained 

24-hour PM10 standard at its existing concentration of 150 μg/m3

. The form of the 24-

hour PM10 standard allows for one violation of the standard annually. The Basin 

currently meets the 24-hour average federal standard however, no petition to EPA to redesignate the Basin as attainment status has been submitted. (The only days that exceed 

the standard are associated with high wind natural events or exceptional events due to 

wildfires). 

For this analysis, the annual second maximum concentration is used for the attainment 

demonstration (given the standard allows for one violation annually). RiversideRubidoux has been the PM10 24-hour design site in nine of the past ten years when high 

V - 1- 9 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

wind days have been excluded from the analysis. The 2005 design value at Rubidoux is 

86 percent of the federal standard. The standard attainment demonstration is conducted 

to assure that the Basin will continue to be in compliance in future years. 

As a conservative analysis, only emissions reductions associated with the PM2.5 portion 

of the 24-hour PM10 concentration are assumed to be impacted by future year emission 

controls. Future year predictions of maximum and second maximum 24-hour average 

PM10 are calculated using the site specific annual average PM2.5 RRFs applied only to 

the PM2.5 portion of the PM10 design concentration. The average PM2.5 RRFs 

calculated from the eight sites, for 2005 to 2014, are applied to the fine portion of the 24-

hour PM10 distribution for sites other than the MATES-III, which do not have the 

PM2.5 speciation. The coarse portion of the PM10 is assumed to be held constant in this 

analysis. The predicted reductions to the fine portion are then added to the coarse to 

estimate a 2015 second maximum PM10 24-hour average concentration. 

OZONE 

The CAA requires that ozone nonattainment areas designated as serious and above use a 

photochemical grid model to demonstrate attainment. CAMx was selected as the 

modeling tool used in the Final 2007 AQMP ozone modeling attainment demonstration. 

CAMx is an urban scale, three-dimensional, grid-type, numerical simulation model. For 

the Final 2007 AQMP, CAMx has been coupled with SAPRC99 gaseous chemistry for 

the ozone attainment demonstration. Although CAMx was not used as the primary 

modeling tool, CAMx simulations provided supporting documentation for the 2003 

AQMP ozone attainment demonstration. In addition, as prevouly discussed, CAMx is 

one of the modeling platforms recommended by the peer review. 

Modeling Approach

CAMx simulations were conducted using a Lambert Confromal projection over the 5 km 

squared grid SCOS97 modeling domain. The modeling analyses were run using 16 

vertical layers up to 5000 m above ground level. 

CAMx simulations were generated for six meteorological episodes including one period 

in 2004, four periods in 2005 and one in 1997. Table V-1-2 provides a comparison for 

the meteorological episodes evaluated in the current and preceding attainment 

demonstrations. The August 1997 SCOS97 meteorological episode was retained for this 

analysis to provide a bridge from the 2003 AQMP attainment demonstration. The five 

episodes observed in 2004 and 2005 occurred during MATES-III, a period of enhanced 

air quality monitoring in the Basin. Supporting MATES-III, the District operated three 

radar wind profilers in the Basin, with radio acoustic sounding systems and also 

enhanced its Photochemical Assessment Monitoring Stations (PAMS) programs. 

V- 1 - 10 
Chapter 1 Modeling Overview 

Additional profiler data was obtained from operating sites in Ventura and San Diego 

Counties. 

TABLE V-1-2 

Comparison of Ozone Meteorological Epsiodes used in the 2003 and Final 2007 

AQMPs 

2003 AQMP Final 2007 AQMP 

August 4-7, 1997 August 4-7, 1997 

 August 4-8 , 2004 

 May 17-24, 2005 

 July 14-19, 2005 

 August 2-9, 2005 

 August 25-29, 2005 

Selection of episodes from 2004 and 2005 was also made to avoid the fuel commingling 

associated with the Phase III California Fuel Reformulation where the primary 

oxygenate was changed from MTBE to ethanol. Commingling of ethanol and nonethanol based fuels leads to enhanced evaporative VOC emissions and thus more ozone. 

Quantification of the amount of commingling taking place on a daily or episodic basis 

was nearly impossible. Implementation of the fuel switch from MTBE to ethanol took 

place in California during 2003 and was assumed to be completed by December 31, 

2003. Selecting meteorological episodes post 2003 reduced the uncertainty associated 

with the estimation of the VOC emissions inventory due to commingling. 

The meteorological fields used for the CAMx ozone simulations were generated using 

MM5 with the FDDA option. The meteorological fields were developed using a 

Lambert Conformal grid adapted for the the SCOS97 modeling domain. MM5 was 

simulated using 34 vertical layers and simulations were initialized using the NCEP 

global weather forecast model analysis. The MM5 fields were post-processed to layeraveraged winds to the levels defined for the CAMx simulations and to adjust coordinates 

to the UTM system. 

Day-specific point, mobile and area emissions inventories were generated for each 

meteorological episode. Mobile source emissions were temperature corrected by grid 

V - 1- 11 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

using a VMT weighted scheme. County-wide area source emissions were temperature 

corrected and gridded using the spatial emissions surrogate profiles developed for the 

2003 AQMP. A more detailed description of the meteorological episode selection, 

meteorological modeling and validation and the episodic emissions inventory 

development is presented in Chapert 4. 

Application of RRF’s

Unlike the regional ozone modeling conducted for the 2003 AQMP that based the 

attainment demonstration on the direct results of a future year simulations, the procedure 

for determining future year attainment of the 8-hour ozone standard for the Final 2007 

AQMP relies on the use of site specific RRF’s determined from a series of simulations 

for the 2002 and 2023 controlled emissions. The basic procedure is outlined earlier in 

this chapter. The ozone attainment demonstration is anchored by the 2002 base-year 

emissions. The meteorological episodes are first validated based on model performance 

using day-specific emissions for each base-case (e.g. 1997, 2004 or 2005). The suites of 

validated episodes are then simulated using the 2023 controlled and 2002 emissions to 

determine a site specific average set of RRFs. The site specific RRF is applied to the 

2002 design value to determine whether attainment has been satisfied. 

A minimum of 5-episode days are recommended to determine the site specific RRF. 

The evaluation requires that the model performance for the day is within specific 

performance goals including observation with 25 percent of the station design value, 

absolute prediction accuracy within 25 percent and that a minimum observed 

concentration at each site 85 ppb or greater. If a site did not meet the 5-day threshold, 

either the average of the RRFs for all Basin sites or the calculated RRF from the 19 days 

simulated was applied to estimate the future design value. In this situation, the lesser 

reduction value (i.e., higher ratio of 2003 ozone divided by 2002 ozone) was used as the 

representative RRF for future year design calculation. Per EPA modeling guidance, 

since the CAMx regional modeling is based on a 5 km squared grid, the ozone 

performance evaluation and peak RRF calculation is based on a comparison of the 

observed concentration and the predicted concentration within a 15 km radius of the grid 

hosting the observation. (Data are evaluated for a 7 X 7 grid area). 

UNCERTAINTIES ASSOCIATED WITH THE TECHNICAL ANALYSIS 

As with any plan update there are uncertainties associated with the technical analysis. 

The following paragraphs describe the primary contributors to such uncertainties as well 

as some of the safeguards buildt in to the air quality planning process to manage and 

control such uncertainties. 

V- 1 - 12 
Chapter 1 Modeling Overview 

Demographic and Growth Projections 

Uncertainties exist in the demographic and growth projections for the future base years. 

As projections are made to longer periods (i.e., over ten or more years), the uncertainty 

of the projections become greater. Examples of activities that may contribute to these 

types of uncertainties include the rate and the type of new sources locating in the Basin 

and their geographic distribution, future year residential construction, military base reuse 

and their air quality impact, and economic prosperity. 

Input Elements to Air Quality Models

In addition to the above, there are also uncertainties in the technical information 

gathered for the air quality analysis. There are three major input elements associated 

with any air quality modeling analysis: ambient air quality monitoring data; 

meteorological measurements; and emissions inventory. All three input elements have 

various levels of uncertainties impacting the technical analysis. 

Ambient Air Quality Monitoring Data 

Generally, ambient air quality measurements are within plus or minus half of a unit of 

measurement (e.g., for ozone usually reported in units of part-per-billion (ppb) would be 

accurate to within ± 5 ppb). Due to this uncertainty, the Basin’s 8-hour attainment status 

based on ambient monitoring data would be achieved if all ozone monitors reported 

ozone concentration levels less than or equal to 84 ppb. Similar uncertainty is observed 

in particulate data measurements and labroratory analysis. For example, PM2.5 is 

comprised of six primary constituents (NH4+

, NO3, SO4-, OC, EC and crustal), as well 

as bonded water and total mass. Each of the primary species has individual uncertainty 

associated with the laboratory analysis procedure used to analyze concentration, the type 

of filter media to collect the sample and the total mass can be affected by minor changes 

in the volumetric flow that fall within the approved instrument calibration range. As a 

consequence, the sum of the total species may not add up to or may exceed the filter 

measured mass. 

Meteorological Measurements 

Air Quality models have to rely on reliable meteorological input data to accurately 

simulate future ambient concentration levels. There are uncertainties associated with 

meteorological model input parameters, such as initializations from National Weather 

Service global and hemispheric simulations, or satellite estimates of ground level 

temperature and moisture. Direct measurements of instantaneous wind speeds and 

directions at varying levels above ground require averaging to hourly values before they 

V - 1- 13 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

can be assimilated into the numerical analyses. Layer averaging of model ouput reduces 

the sensitivity of the model to changing patterns in the vertical structure. 

Emissions Inventory 

As discussed in Chapter 3 of the main document, large uncertainties in the mobile source 

emissions inventory estimates have been observed as evident with the latest 

EMFAC2007 release. On-road mobile source emission estimates have increased with 

each new EMFAC release. On-road mobile source emissions have inherent uncertainties 

also with the current methodologies used to estimate vehicle activity such as vehicle 

miles traveled, the impacts of fuel additives such as ethanol and day-of-week diurnal 

profiles of traffic volume. Stationary (or point) source emission estimates have less 

associated uncertainties compared to area source emission estimates. Major stationary 

sources report emissions annually whereas area source emissions are, in general, 

estimated based on production or usage information. Area source emissions including 

paved road dust and fugitive dust have significant uncertainties in the estimation of 

particulate (PM2.5) emissions due to the methodologies used for estimation, temporal 

loading and weather impacts. 

Air Quality Models 

The air quality models used for ozone and particulate air quality analysis are state-ofthe-art, complex 3-dimensional models that utilize 3-dimensional meteorological 

models, complex chemical mechanisms that accurately simulate ambient reactions of 

pollutants and sophisticated numerical methods to solve complex mathematical 

equations that lead to the prediction of ambient air quality concentrations. While air 

quality models progressively became more sophisticated in employing improved 

chemical reaction modules that more accurately simulate the complex ambient chemical 

reaction mechanisms of the various pollutants, such improved modules are still based on 

limited experimental data which carry associated uncertainties. In order to predict 

ambient air quality concentrations, air quality models rely on the application of 

sophisticated numerical methods to solve complex mathematical equations that govern 

the highly complex physical and chemical processes that also have associated 

uncertainties. 

Are There Any Safeguards Against Uncertainties? 

Yes. While completely eliminating uncertainties is an impossible task, there are a 

number of features and practices build-into the air quality planning process that manage 

and control such uncertainties and preserve the integrity of an air quality management 

plan. 

V- 1 - 14 
Chapter 1 Modeling Overview 

The concerns regarding uncertainties in the technical analysis are reduced with future 

AQMP revisions. Each AQMP revision employs the best available technical 

information available. Under state law, the AQMP revision process is a dynamic 

process with revisions occurring every three years. The AQMP revision represents a 

“snapshot in time” providing the progress achieved since the previous AQMP revision 

and efforts still needed in order to attain air quality standards. 

Under the federal Clean Air Act, a state implementation plan (SIP) is prepared for each 

criteria pollutant. The SIP is not updated on a routine basis under the federal Clean Air 

Act. However, the federal Clean Air Act recognizes that uncertainties do exist and 

provides a safeguard if a nonattainment area does not meet an applicable milestone or 

attain federal air quality standards by their applicable dates. Contingency (or backstop) 

measures are required in the AQMP and must be developed into regulations such that 

they will take effect if a nonattainment area does not meet an applicable milestone or 

attainment date. In addition, federal sanctions may be imposed until an area meets 

applicable milestone targets. 

In September 2006, U.S. EPA released an updated guidance document on the use of 

modeled results to demonstrate attainment of the federal ozone, PM2.5 and regional haze 

air quality standards. The guidance document recognized that there will be uncertainties 

with the modeling analysis and recommends supplemental analysis or weight of 

evidence discussion that corroborates the modeling attainment analysis where attainment 

is likely despite the modeled results which may be inconclusive. Table V-1-3, is taken 

directly from the modeling guidance document to illustrate the value of supplemental 

analyses. Where possible, the U.S. EPA recommends that at least one “mid-course” 

review of air quality, emissions and modeled data be conducted. A second review, 

shortly before the attainment date, should be conducted also. Statistical trend analyses 

can also provide support for assessing the likelihood for future year attainment. Such 

actions will occur in the South Coast Air Quality Management District. 

DOCUMENT ORGANIZATION 

This document provides the federal attainment demonstrations for PM2.5, PM10 and 

ozone. Chapter 2 provides the PM2.5 attainment demonstration to meet the 2015 

attainment date. The discussion includes future year (2015 and 2021) particulate 

impacts for both PM2.5. Chapter 3 provides an update to the 24-hour average PM10 

attainment demonstration and a brief discussion on the impacts of the control strategy to 

regional visibility. Chapter 4 presents the ozone attainment demonstration based on the 

CAMx modeling analyses. The ozone analysis includes a characterization of the 

episodic, base-year modeling performance, and future year attainment for the control 

strategy. As with the particulate analyses, a series of alternative emissions simulations 

are presented to test the sensitivity of the proposed control strategy. Weight of evidence 

V - 1- 15 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

discussions for ozone and PM2.5 will be incorporated in Chapters 2 and 4 respectively 

in the final document. Chapter 5 presents the summary comparing predicted air quality 

to the state and federal standards and the projected 20145 PM2.5 and 2024 8-hour ozone 

carrying capacities. Table V 1-4 lists the Attachments to this document. 

TABLE V-1-3 

Guidelines for Weight of Evidence Determinations (U.S. EPA, 2006) 

Results of Modeled Attainment Test Supplemental Analyses 

Ozone Annual PM2.5 24-Hour PM2.5 

Future Design 

Value < 82 ppb, 

all monitoring sites 

Future Design 

Value < 14.5 μg/m3

, 

all monitoring sites 

Future Design 

Value < 62 μg/m3

, 

all monitoring sites 

Basic supplemental 

analyses should be 

completed to confirm the 

outcome of the modeled 

attainment test 

Future Design 

Value 82 - 87 ppb, 

at one or more 

sites/grid cells 

Future Design 

Value 14.5 – 15.5 

μg/m3

, at one or 

more sites/grid cells 

Future Design 

Value 62 – 67 

μg/m3

, at one or 

more sites/grid cells 

A weight of evidence 

demonstration should be 

conducted to determine if 

aggregate supplemental 

analyses support the 

modeled attainment test 

Future Design 

Value > 87 ppb, 

at one or more 

sites/grid cells 

Future Design 

Value > 15.5 

μg/m3

, at one or 

more sites/grid cells 

Future Design 

Value > 67 μg/m3

, 

at one or more 

sites/grid cells 

More qualitative results 

are less likely to support a 

conclusion differing from 

the outcome of the 

modeled attainment test. 

V- 1 - 16 
Chapter 1 Modeling Overview 

TABLE V-1-4 

Attachments 

Number Description 

References 

Attachment-1 PM2.5 Annual and 24-Hour Attainment Calculations 

Attachment-2 Model Performance Statistics 

Attachment-3 Draft Modeling Protocol 

Attachment-4 Critiques of the Expert Reviewers 

Attachment-5 CEPA Source Level Emissions Reduction Summary for 

2014: Annual Average Inventory 

Attachment-6 CEPA Source Level Emissions Reduction Summary for 

2017: Annual Average Inventory 

Attachment-7 CEPA Source Level Emissions Reduction Summary for 

2017: Planning Inventory 

Attachment-8 CEPA Source Level Emissions Reduction Summary for 

2023: Annual Average Inventory 

Attachment-9 CEPA Source Level Emissions Reduction Summary for 

2023: Planning Inventory 

V - 1- 17 
CHAPTER 2 

THE FEDERAL PM2.5 ATTAINMENT 

DEMONSTRATION PLAN 

Introduction 

PM2.5 Data: MATES-III and FRM 

Sandwich and Speciated Monitored Attainment (SMAT) 

CAMx and MM5 Overview 

Emissions Inventory 

 Base-Year Annual Simulations 

Future Air Quality 

Weight of Evidence 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 1

INTRODUCTION 

As outlined in Chapter 1 of this document, the CAMx “one atmosphere” gas-aerosol 

modeling system was used to develop the regional PM2.5 attainment demonstration 

for the Final 2007 AQMP. The departure from the Urban Airshed Model with Linear 

Chemistry (UAM/LC) [Kumar, et al, 1995] modeling system was made to take 

advantage of CAMx’s better-more mass consistent dispersion platform, integrated 

gas phase (CB-IV) and aerosol chemistry (two size partitioned) and readily 

incorporated numerical prognostic meteorological model data. 

EPA guidance on PM modeling for attainment demonstrations requires the use of a 

regional dispersion model in combination with relative response factors. The 

speciated modeling attainment test (SMAT) relies on the use of modeled 

performance of individual particulate species in the base year and future year 

controlled scenarios to produce relative response factors to be applied to design year 

data. The CAMx output provides comprehensive characterization of the six key 

segments of the PM2.5 distribution (NH4+, NO3, SO4, organic carbon (OC), 

elemental carbon (EC), crustal, as well as nitric acid and the standard chemical mix 

associated with ozone production (O3, NO, NO2, CO, aldehydes, and VOC). 

Particulate data measured in 2005 as part of the Multiple Air Toxics III (MATES-III) 

program provided the speciation of the PM2.5 samples. The MATES-III monitoring 

program began in April 2004 and continued through March of 2006. The data used 

for the attainment demonstration was measured from January 1, 2005 through 

December 31, 2005, in the middle of the MATES-III program. Problems observed in 

data typically associated with the start-up of a field program and ensuing initial 

laboratory analysis were minimized over the 8-months of lead sampling prior to 

2005. All MATES-III measured data was subjected to extensive quality assurance 

procedures following the protocol outlined by EPA criteria. A comprehensive 

analysis of the MATES-III sampling program is expected to be issued in the Spring 

of 2007. 

The speciated PM2.5 sampled by the MATES-III program were a unique data set, 

separate from the data acquired through the standard Federal Reference Method 

(FRM) PM2.5 sampling network. Total mass sampled in parallel (MATES-III and 

FRM) using side-by-side samplers are not expected to match directly. As such, 

EPA’s “Sandwich” methodology was used in this demonstration to fit the MATESIII data by species to the annual FRM mass. The process calculates organic carbon 

as the sum of the total filter mass minus the mass of the remaining species and 

estimations of bonded water and filter contamination (“blank”). Bonded water and 

filter contamination are inferred in the FRM PM2.5 data samples and their inclusion 

in the analysis provides for a more direct comparison to the FRM determined 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 2 

regional design values. The Sandwich methodology is discussed later in conjunction 

with the SMAT. 

The PM2.5 attainment demonstration is twofold to address the annual and 24-hour 

portions of the standard. The initial sections of this chapter address the MATES- III 

program and data, the District FRM PM2.5 sampling network, the SMAT and 

Sandwich data analyses, the CAMx modeling setup and briefly the modeling 

emissions inventory. The following sections of this chapter provide the annual 

PM2.5 attainment demonstration and supporting weight of evidence analyses then 

lastly, the episodic PM2.5 24-hour standard attainment demonstration. 

PM2.5 Data: MATES-III and FRM 

MATES-III Monitoring 

MATES-III is the second follow up to the original MATES toxics analysis that took 

place in the later 1980’s. MATES-II was comprised of an extensive field monitoring 

campaign and laboratory analysis, emissions inventory development and regional 

toxics modeling. The MATES-II sampling generated speciated PM10 from the TEP2000 monitoring network using the PTEP samplers (described in the 2003 AQMP, 

Appendix V). A comprehensive discussion of the MATES-II program is provided in 

the MATES-II final report and appendices. 

MATES-III PM2.5 samples were collected upon a 47mm quartz and Teflon filters 

simultaneously within the same particulate sampler for a 24-hour duration using a 

size selective sampler (SSI) in accordance to the method based on EPA’s Federal 

Reference Method 40CFR50 (Draft MATES-III Protocol, 2004). Samples were 

taken every third day basis. Teflon filters were used for the analysis of total 

particulate mass, ions and metals. The PM2.5 quartz filter was used for the analysis 

of organic and elemental carbon using the IMPROVE or NIOSH method. The 

District also operates co-located speciated air sampling system (SASS) monitors for 

the carbon measurement at two sites (Central Los Angeles and Riverside-Rubidoux) 

as part of EPA’s STN sampling network. Only the IMPROVE carbon data are 

incorporated in the attainment demonstration. 

The MATES-III sampling network was comprised of eight monitoring sites at 

locations used in the MATES-II study. At least one site is situated in each of the four 

counties in the Basin with the bulk of the monitoring in Los Angeles. The locations 

of the monitoring stations were chosen to bridge the MATES-II and MATES-III 

exposure analysis but also to address environmental justice issues associated with 

goods movement and exposure to mobile source emissions. The sites are listed in 

Table V-2-1. 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 3 

TABLE V-2-1 

MATES-III Monitoring Network 

Site Address County 

Anaheim 1010 S. Harbor Blvd. Orange 

Burbank 228 W. Palm Ave. Los Angeles 

Compton 720 N. Bullis Ave. Los Angeles 

Fontana 14360 Arrow Highway San Bernardino 

Long Beach 3648 N. Long Beach Blvd. Los Angeles 

Los Angeles 1630 N. Main St. Los Angeles 

Rubidoux 5888 Mission Blvd Riverside 

Wilmington 900 E. Lomita Blvd Los Angeles 

MATES-III Speciated Data 

 Annual Data 

Figure V-2-1 provides the PM2.5 mass distribution for the 2005 MATES-III data. 

The data reflects the unadjusted direct measurements of the key PM2.5 species at 

each station. A category called “Others” which is included in the data is defined as 

the net difference between the sum of the species mass and the total mass weighed on 

the filter. Field measurements and lab analyses each have uncertainty and precisions 

bounds. As identified by EPA, the greatest uncertainty in species mass lies with the 

measurement and analysis of organic carbon. The uncertainty associated with the 

organic carbon mass is treated through an adjustment that is discussed as part of the 

“Sandwich Method”. 

The highest PM2.5 mass is measured at Burbank, Fontana and Rubidoux and the 

lowest at Anaheim. Figure V-2-1 provides the speciation of the adjusted 2005 

MATES-III data including ammonium, nitrates, sulfates, organic carbon (OC), 

elemental carbon (EC), sodium, chloride, and metals including aluminum, iron, 

silicon, titanium, nickel, and lead among others. Table V-2-2 provides the 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 4 

concentrations of the PM2.5 species observed in the MATES-III data while Table V2-3 provides the percentage of total mass for the major component species . 

2005 MATES-III Annual PM2.5

-10

-5

0

5

10

15

20

25

30

Anaheim

Burbank

Compton

Fontana

Long Beach

Los Angeles

Rubidoux

Wilmington

Mass (ug/m3)

Others

Na & Cl

Metals

EC

OC

SO4 ion

NO3 ion

NH4 ion

FIGURE V-2-1 

MATES-III 2005 Annual Distribution of PM2.5 Species (μg/m3) 

TABLE V-2-2 

MATES-III 2005 Annual PM2.5 Species Concentrations (μg/m3) 

Location NH4 NO3 SO4 OC EC Metals Na & Cl Others MASS 

Anaheim 1.90 4.09 3.30 6.03 1.43 2.54 0.73 -3.04 16.97 

Burbank 2.43 5.49 3.38 8.44 2.09 2.94 0.55 -3.47 21.83 

Compton 2.07 4.18 3.74 6.99 1.84 2.80 0.72 -3.60 18.73 

Fontana 2.52 6.43 3.15 8.01 2.14 2.88 0.55 -4.53 21.14 

Long Beach 2.11 3.87 4.17 6.71 1.52 2.98 0.85 -4.59 17.61 

Los Angeles 2.27 5.09 3.43 7.58 1.95 2.55 0.59 -5.42 18.04 

Rubidoux 2.73 7.31 3.05 6.88 1.69 2.52 0.61 -3.38 21.41 

Wilmington 1.90 3.34 4.47 6.66 2.12 3.26 0.88 -4.15 18.47 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 5 

TABLE V-2-3 

MATES-III Annual Percentage 2005 PM2.5 Species Contribution 

Location NH4 NO3 SO4 OC EC Metals Na & Cl 

Anaheim 9.5 20.4 16.5 30.1 7.1 12.7 3.6 

Burbank 9.6 21.7 13.4 33.3 8.2 11.6 2.2 

Compton 9.3 18.7 16.7 31.3 8.2 12.5 3.2 

Fontana 9.8 25.0 12.3 31.2 8.3 11.2 2.1 

Long Beach 9.5 17.4 18.8 30.2 6.8 13.4 3.8 

Los Angeles 9.7 21.7 14.6 32.3 8.3 10.9 2.5 

Rubidoux 11.0 29.5 12.3 27.8 6.8 10.2 2.4 

Wilmington 8.4 14.8 19.8 29.4 9.3 14.4 3.9 

In general, the organic carbon mass accounts for approximately 30 percent of the 

total mass (adjusted for the negative contribution of the other category) at each 

station. Ammonium, sulfate and nitrates account for an approximate 45 percent of 

the total mass at each location. Rubidoux and Fontana are the most heavily impacted 

by nitrates. Sulfate is highest in the near coastal or ports of Los Angeles/Long Beach 

areas, particularly Wilmington and Long Beach. EC and metals measurements were 

highest at Wimington accounting for almost 24 percent of the mass when combined. 

All sites observed measurable concentrations of sodium and chloride ions reflecting 

the influence of the marine air as it is transported inland. 

Quarterly Data 

Figures V-2-2a –V-3-2h depict the 2005 MATES-III PM2.5 data by component 

species at each monitoring sites sorted by quarter. Table V-2-4 provides the 

quarterly design values for each site. PM2.5 concentrations are highest in either 

Quarter-3 or Quarter-4 at each site. The lowest concentrations are observed in the 

second quarter (with the exceptions of Rubidoux and Fontana). The contribution of 

the individual species varies by quarter as well. Sulfate is highest in Quarter-3 while 

nitrate are highest in Quarter-4 and to some extent Quarter-1. The species 

concentrations reflects the seasonal weather patterns where the higher values of 

sulfate typically occur under strong-elevated inversions and sea breeze transport 

inland, conditions that are prevalent in the Basin in late spring and summer. Nitrate 

chemistry is very dependent on the availability of water vapor and as a result 

Quarter-4, with the high humidity and frequent nocturnal inversions enhance regional 

formation. Organic carbon and elemental carbon values are also highest in Quarter-4 

due to the poor dispersion from weak winds and low level inversions. Quarter-2 

tends to have the lowest concentrations due to spring storms and favorable 

dispersion. 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 6 

2005 Anaheim Quarterly MATES-III PM2.5

-5

0

5

10

15

20

25

30

Q1 Q2 Q3 Q4

Mass (ug/m3)

Others

Na & Cl

Metals

EC

OC

SO4 ion

NO3 ion

NH4 ion

FIGURE V-2-2a 

2005 Quarterly Distribution of PM2.5 Species at Anaheim (μg/m3) 

2005 Burbank Quarterly MATES-III PM2.5

-5

0

5

10

15

20

25

30

35

Q1 Q2 Q3 Q4

Mass (ug/m3)

Others

Na & Cl

Metals

EC

OC

SO4 ion

NO3 ion

NH4 ion

FIGURE V-2-2b 

2005 Quarterly Distribution of PM2.5 Species at Burbank (μg/m3) 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 7 

2005 Compton Quarterly MATES-III PM2.5

-5

0

5

10

15

20

25

30

Q1 Q2 Q3 Q4

Mass (ug/m3)

Others

Na & Cl

Metals

EC

OC

SO4 ion

NO3 ion

NH4 ion

FIGURE V-2-2c 

2005 Quarterly Distribution of PM2.5 Species at Compton (μg/m3) 

2005 Fontana Quarterly MATES-III PM2.5

-5

0

5

10

15

20

25

30

35

Q1 Q2 Q3 Q4

Mass (ug/m3)

Others

Na & Cl

Metals

EC

OC

SO4 ion

NO3 ion

NH4 ion

FIGURE V-2-2d 

2005 Quarterly Distribution of PM2.5 Species at Fontana (μg/m3) 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 8 

2005 Long Beach Quarterly MATES-III PM2.5

-5

0

5

10

15

20

25

30

Q1 Q2 Q3 Q4

Mass (ug/m3)

Others

Na & Cl

Metals

EC

OC

SO4 ion

NO3 ion

NH4 ion

FIGURE V-2-2e 

2005 Quarterly Distribution of PM2.5 Species at Long Beach (μg/m3) 

2005 Los Angeles Quarterly MATES-III PM2.5

-5

0

5

10

15

20

25

30

35

Q1 Q2 Q3 Q4

Mass (ug/m3)

Others

Na & Cl

Metals

EC

OC

SO4 ion

NO3 ion

NH4 ion

FIGURE V-2-2f 

2005 Quarterly Distribution of PM2.5 Species at Los Angeles (μg/m3) 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 9 

2005 Rubidoux Quarterly MATES-III PM2.5

-5

0

5

10

15

20

25

30

35

Q1 Q2 Q3 Q4

Mass (ug/m3)

Others

Na & Cl

Metals

EC

OC

SO4 ion

NO3 ion

NH4 ion

FIGURE V-2-2g 

2005 Quarterly Distribution of PM2.5 Species at Rubidoux (μg/m3) 

2005 Wilmington Quarterly MATES-III PM2.5

-5

0

5

10

15

20

25

30

Q1 Q2 Q3 Q4

Mass (ug/m3)

Others

Na & Cl

Metals

EC

OC

SO4 ion

NO3 ion

NH4 ion

FIGURE V-2-2h 

2005 Quarterly Distribution of PM2.5 Species at Wilmington (μg/m3) 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 10 

TABLE V-2-4 

FRM Annual and Quarterly PM2.5 Design Concentrations (2003-2005) 

 at MATES-III Monitoring Sites (μg/m3) 

Location Quarter-1 Quarter-2 Quarter-3 Quarter-4 Annual 

Anaheim 17.6 12.4 15.4 20.0 16.4 

Burbank 18.7 15.2 20.7 20.3 18.7 

Compton 16.7 13.3 18.2 21.8 17.5 

Fontana 18.7 19.2 20.2 23.2 20.3 

Los Angeles 19.7 16.3 20.2 22.2 19.6 

Long Beach 18.0 12.7 15.7 22.9 17.3 

Rubidoux 21.2 21.9 22.6 24.9 22.7 

Wilmington 12.7 10.9 15.7 19.6 14.7 

On average, the annual MATES-III data are consistent with the annual design values. 

The quarterly MATES-III data compares well with the quarterly FRM data with the 

exceptions of Rubidoux and Fontana which exhibited higher Quarter-3 mass. 

FRM PM2.5 

The AQMD measures PM2.5 using the federal reference method Size Selective Inlet 

(SSI) High-Vol method at 16 air monitoring sites in the Basin. The FRM PM2.5 data 

are used in this analysis to expand the future year predictions to the entire Basin and 

to corroborate the attainment demonstration at the grid level. Figure V-2-3 depicts 

the isopleths of 2005 annual PM2.5 from the FRM sites in the Basin. Table V-2-5 

provides the quarterly and annual design values for the remaining FRM sites not used 

as monitoring locations for MATES-III. (Note: design values for the sites used for 

the MATES-III networks are listed in Table V-2-4 above). 

The FRM data depicted in Figure V-2-3 clearly delineates the extent of the PM2.5 

problem in the Basin. PM2.5 is essentially a combustion generated pollutant and 

with the volume of traffic flow, numbers of sources (both point and area) located in 

the region, concentrations exceed the annual federal standard (15 μg/m3) throughout 

the Basin. The area with the highest annual concentration includes southwest San 

Bernardino and Northwest Riverside Counties. These areas have design values 

exceeding 20 μg/m3 and encompass both the Fontana and Rubidoux air monitoring 

stations. It is important to note that the areas with the highest concentrations are 

directly downwind of a major ammonia source area associated with dairies and 

poultry farming. These industries are rapidly moving from the Basin and are 

expected to contribute significantly less to particulate formation in future years. 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 11 

TABLE V-2-5 

FRM Annual and Quarterly PM2.5 Design Concentrations (2003-2005) 

at the Remaining Basin PM2.5 Monitoring Sites (μg/m3) 

Location Quarter-1 Quarter-2 Quarter-3 Quarter-4 Annual 

Azusa 16.2 15.9 21.1 19.6 18.2 

Big Bear 12.8 8.0 7.7 14.7 10.8 

Lynwood 19.3 14.6 18.3 22.9 18.8 

Mission Viejo 12.0 10.2 12.7 12.9 11.9 

Ontario 21.0 17.9 20.5 25.3 21.2 

Pasadena 15.5 14.6 18.6 18.5 16.8 

Reseda 14.3 13.4 15.9 17.8 15.4 

Riverside Magnolia 18.9 19.8 20.6 22.5 20.5 

San Bernardino 18.2 20.3 21.6 21.8 20.5 

FIGURE V-2-3 

2005 South Coast Air Basin Annual PM2.5 (μg/m3) 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 12 

SANDWICH AND SPECIATED MONITORED ATTAINMENT (SMAT) 

Sandwich 

The “sandwich” method (Frank, 2006) calculates the PM2.5 organic carbon mass 

from the difference between the total mass of the particulate sample and the other 

component species. As previously described, there is uncertainty associated with the 

monitoring and analytical methods used to develop the particulate profile. While 

nitrate filter mass loss is expected, the analytical technique to determine the 

concentrations of the remaining species is well established. Confidence is high in 

determining the concentrations of the other ions (sulfates, ammonium, sodium and 

chloride) and the measurements of directly emitted elemental and crustal 

components. Primary and secondary organic compounds express greater monitoring 

and analytical variability and the sandwich method proposes to minimize this 

uncertainty. 

In the unadjusted 2005 MATES-III data, the “others” is just the difference between 

the measured component species mass and the total mass of the filter. In the 2003 

AQMP, annual PM10 attainment demonstration the speciated particulate data used 

the measurements of ammonium, sulfate, nitrate, organic carbon and elemental 

carbon directly. The difference between the total filter mass and the sum of the five 

components was categorized as the “others.” The others included the crustal [metals] 

components, sea salts and accounted for any particle bonded water, filter blank 

contamination and uncertainties in the data monitoring or laboratory analysis. 

The sandwich method for PM2.5 (described by Equation V-2-1) accounts for the 

calculation of bonded water adds a filter blank contamination term and substitutes 

organic carbon as the “others” compontent to be estimated from the mass difference. 

Eq. V-2-1. 

OC = PM2.5 – (NH4 + NO3 + SO4 + EC + bonded H2O + blank + crustal [metals]). 

The sandwich method estimates ammonium (if not directly measured) and uses a 

either a linear or polynomial empirical equation to approximate the mass of bonded 

water in the sample. The polynomial equation is an empirically derived 

approximation of the thermodynamic Aerosol Inorganic Model (AIM) (Clegg, 1998) 

that uses the concentrations of NH4, NO3 and SO4 to estimate bonded water. The 

alternate linear equation also approximates bonded water assuming that the water 

content bonded to ammonium nitrate is equivalent to 12 percent of the mass and that 

the water bonded to ammonium sulfate is approximately equal to 26 percent of that 

mass. Comparisons of the calculated bonded water using the two algorithms were 

close and for the PM2.5 attainment demonstration, the primary method used to 

calculate water was the polynomial approach. 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 13 

The sandwich also incorporates a filter blank contamination estimation of 0.5 μg/m3 

into the calculation. AQMD procedures require the use of forceps to handle filter 

media to avoid mass contamination. However, some mass inevitably does impact the 

filter prior to exposure mostly due to the conditioned air mass in the sequential 

sampler as the filter is being queued for monitoring. The AQMD staff has discussed 

the filter bank issue with EPA and after reviewing monitoring and laboratory 

procedures as well as measurement of the blanks has determined that the 0.5 μg/m3

value for the bank is an appropriate average for the Basin. 

The sandwich methodology does not exclude the use of directly measured 

ammonium or organic carbon. Estimates of ammonium calculated using a empirical 

relationships (0.29 X nitrate and 0.375 X sulfate) closely matched the measured 

ammonium. As a consequence, the directly measured ammonium is used in the Final 

2007 PM2.5 attainment demonstration analysis. Second, measurements of PM2.5 

OC were analyzed using the same technique as for the previous 2003 AQMP PM10 

analysis (although different filter media). The data were trend adjusted, based on 

emissions reductions observed over recent years and further adjusted to estimate the 

carbon fraction. The carbon fraction factor can range in the Basin from 1.2 to 1.8 

depending upon the location of the station relative to source areas. For the 2007 

AQMP a carbon factor of 1.3 was applied to the OC data measured at the eight sites. 

The Sandwich methodology was applied to the MATES-III data for each station. 

The MATES-III data were aggregated in to quarterly averages, and the organic 

carbon portion was calculated directly. If a quarterly value of organic carbon was 

calculated to be a negative number, the average of the non-negative quarterly average 

concentrations at that site were substituted for the negative value. To maintain mass 

consistency, an adjustment to the total quarterly mass was made totaling the sum of 

the substituted average organic carbon concentration and the absolute value of the 

negative calculation of organic carbon resulting from the Sandwich methodology. 

Bonded water was calculated using the AIM model and a 0.5 μg/m3

 blank was added. 

The Sandwich modified MATES-III quarterly data were then apportioned to the 

quarterly design values at each (MATES-III) monitoring site (subtracting the blank 

before scaling then adding the blank back to the total mass) prior to the SMAT. 

Table V-2-6 provides the quarterly design values for each of the eight MATES-III 

sites with the Sandwich derived species distribution. 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 14 

TABLE V-2-6 

MATES-III/Sandwich Apportioned 2005 Quarterly Design Values 

Quarter NH4 NO3 SO4 OC EC Water Crustal/Metals Blank Mass 

Anaheim 

1 1.49 4.95 2.20 3.25 1.59 2.00 1.57 0.50 17.57 

2 1.04 2.63 3.16 0.75 0.65 1.95 1.72 0.50 12.40 

3 1.60 2.71 4.47 1.74 0.72 1.62 2.00 0.50 15.37 

4 2.64 5.34 2.45 2.69 2.39 1.80 2.19 0.50 20.00 

Burbank 

1 1.54 4.90 1.77 5.16 1.74 1.62 1.48 0.50 18.70 

2 1.48 3.63 2.94 1.97 1.02 1.53 2.10 0.50 15.17 

3 2.45 4.34 4.54 3.10 1.25 2.20 2.27 0.50 20.67 

4 3.06 6.90 2.42 3.80 3.21 2.32 2.09 0.50 24.30 

Compton 

1 1.42 4.33 2.47 4.80 2.13 1.86 1.81 0.50 19.30 

2 1.30 3.11 3.78 0.68 0.90 2.16 2.16 0.50 14.60 

3 2.17 3.15 5.34 2.28 0.82 2.07 1.94 0.50 18.27 

4 2.76 5.63 2.69 3.60 3.23 2.03 2.44 0.50 22.87 

Fontana 

1 1.89 6.22 1.82 2.95 1.84 1.94 1.58 0.50 18.73 

2 2.24 5.93 3.30 1.63 1.46 1.94 2.16 0.50 19.17 

3 2.10 4.83 4.27 1.37 1.88 2.00 3.24 0.50 20.20 

4 3.53 8.29 2.40 0.55 2.51 2.72 2.67 0.50 23.17 

Long Beach 

1 1.37 4.19 2.55 3.74 1.83 1.92 1.88 0.50 17.97 

2 1.25 2.45 3.72 0.40 0.70 1.67 1.98 0.50 12.67 

3 1.95 2.53 4.75 1.26 0.87 1.73 2.08 0.50 15.67 

4 3.29 5.86 4.31 1.42 2.50 2.53 2.49 0.50 22.90 

Los Angeles 

1 1.78 6.25 2.44 2.54 1.98 2.55 1.69 0.50 19.73 

2 1.58 4.07 3.74 0.73 1.32 2.16 2.22 0.50 16.33 

3 2.95 4.52 5.11 0.98 1.45 2.47 2.22 0.50 20.20 

4 3.17 7.06 2.92 0.52 3.25 2.59 2.23 0.50 22.23 

Rubidoux 

1 1.79 6.51 1.93 4.18 2.00 2.44 1.81 0.50 21.17 

2 3.00 8.25 3.18 1.39 1.18 2.23 2.15 0.50 21.87 

3 2.94 7.29 4.30 1.62 1.17 2.27 2.50 0.50 22.60 

4 3.47 8.44 2.65 1.53 2.61 3.04 2.64 0.50 24.87 

Wilmington 

1 1.27 3.49 2.91 3.43 2.44 1.84 2.08 0.50 17.97 

2 1.13 2.02 3.84 0.38 0.92 1.74 2.14 0.50 12.67 

3 1.73 1.95 5.12 1.34 1.15 1.73 2.16 0.50 15.67 

4 2.62 5.02 3.88 2.47 3.37 2.27 2.79 0.50 22.90 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 15 

SMAT 

The federal guidance for developing a PM2.5 attainment test differs from past in that 

the attainment demonstration does not directly rely on explicit model output. The 

attainment test in the new guidance requires the use of the RRFs determined from the 

modeling, applied to the current design values to create future design values. The 

speciated modeling attainment test outlined in the guidance document further 

requires the development of species dependent RRFs from the base and future year 

modeling simulations. The guidance tests the model response for the major species 

simulated. The analysis requires that the Sandwich speciated design value data and 

RRFs be assessed by the quarter of the year then recompiled into an annual future 

year demonstration. 

Note: in the SMAT, the blank is constant and the future year bonded water is 

calculated as a function of the predicted ammonium, nitrate, and sulfate 

concentrations. The net amount of future year bonded water is expected to decrease 

as a function of the control strategy implementation. 

CAMX AND MM5 OVERVIEW 

As discussed in Chapter 1, CAMx and MM5 were selected as the dispersion platform 

and meteorological model respectively for the PM2.5 attainment demonstration. The 

following sections briefly describe the modeling domain, meteorological interface 

and the boundary conditions applied in the analysis. The prescriptions for the MM5 

domain initialization and coupling with the modeling domain are addressed in the 

Draft 2007 Modeling Protocol. Similar setup procedures for the CAMx simulations 

can be found in the Protocol document. 

Modeling Domain 

The CAMx modeling domain was defined by 2600 5 km squared grid cells a 

Universal Transverse Mercator (UTM) projection beginning at 275 easting through 

3670 northing using a 65 by 40 grid cell structure. This is same grid specification 

that was used for the 2003 UAMAERO-LT analyses. Figure V-2-4 depicts the 

modeling domain. 

The PM2.5 domain extends approximately 80 km offshore to the west of the middle 

Basin. The domain captures the international shipping routes that extend parallel to 

the coast (northwest and southeast) and due west from the port areas. The northern 

boundary of the domain extends to Santa Barbara County and Kern County while the 

southern boundary resides primarily in Northern San Diego County. The desert 

portions of Riverside, San Bernardino and Imperial counties define the eastern 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 16 

boundary of the modeling domain. The modeling domain is smaller than both the 

ozone modeling and MM5 domain. 

The vertical structure for the CAMx modeling was increased to 8 layers of varying 

depth (compared with the 5-layer analysis of UAMAERO-LT) but less than the 19 

layers used for the MM5 simulations in effort to conserve computational resources. 

The top of the modeling domain was set at 5,000 m. 

FIGURE V-2-4 

PM2.5 Modeling Domain 

Boundary, Top Conditions 

One of the more difficult tasks of the modeling analysis was to determine a method 

to define the boundary and top conditions for the PM2.5 simulations. Three options 

were considered for the analysis: (1) assume clean conditions, (2) use the ozone 

modeling to generate concentration files at the PM2.5 grid boundary, or (3) use 

hemispheric or global chemistry model output to specify the boundaries. Option-3 

with minor adjustments was selected for the attainment demonstration. 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 17 

The Western Regional Air Partnership (WRAP) has been simulating hemispheric 

particulates with a focus on the western U.S. as part of the Regional Haze Rule 

demonstration using CAMx on a coarse grid extending into the Pacific Ocean. 

Model output from the WRAP analysis for model year 2002 was extracted and 

converted to develop hourly boundary conditions for the PM2.5 modeling analyses. 

For this analysis it is assumed that little uncertainty is introduced into the modeling 

using the 2002 boundary data. The WRAP modeling used CB-IV gaseous chemistry 

as does the Final 2007 AQMP PM2.5 CAMx modeling. The WRAP modeling was 

conducted on a Lambert Conformal grid and therefore specification of the boundary 

conditions required remapping to the UTM coordinate system. Additional vertical 

layer averaging and remapping to the PM2.5 grid assumed that the concentration is 

uniform across each vertical layer. 

The boundary and top concentration input files for the PM model were created on a 

month by month basis. The files were derived by averaging the WRAP simulation 

concentrations at each boundary point, vertical layer for each hour of the day over the 

course of a month. The values of the various boundary species were averaged over 

the entire top of the modeling domain for every hour in a month to create the top 

concentration files. The CAMx top concentration file only uses one concentration 

value for the top of the model for the entire simulation. Table V-2-7 provides the 

representative results for February and August. 

Initial PM2.5 performance with the WRAP boundary conditions suggested that SOx 

concentrations along the western boundary in the shipping lanes were too low. A 

minimum concentration of 5 ppb SO2 was set for the southern boundary extending 

westward from the San Diego coast to approximately 20 km offshore after which the 

concentration was phased to a value less than 1 ppb at the extreme southwest corner 

of the modeling domain. A similar adjustment was made along the north-south 

boundary with SO2 being set at 5 ppb from the coast of Santa Barbara south to 

approximately 15 km offshore, again being reduced to less than 1 ppb at the 

southwest corner of the domain. 

Future Boundary, Top and Initial Air Quality Conditions 

For the future year scenarios, the boundary, region top and ambient air quality 

concentrations were adjusted to reflect projected emissions reductions from the 2005 

base-year. 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 18 

MM5 Simulations 

MM5 was used to generate the meteorological profile for each day in 2005. The 

MM5 simulations were generated for the larger SCOS97 modeling domain 

employing a 5 km square grid and fit to the smaller PM2.5 grid. The MM5 

simulations were initialized from NCEP analyses and run for 5-day increments 

without the option for four dimensional data assimilation (FDDA). For the annual 

PM2.5 modeling, the ramp-up period for the MM5 simulations was approximately 

one-half day. The total simulation time of 5 1⁄2 days allowed for an overlap from run 

to run and provided consistency in the meteorological profile. The reader is directed 

to the Draft 2007 Modeling Protocol where the developments of the MM5 

meteorological simulations are discussed at length. 

TABLE V-2-7 

Top Concentration Files for the PM Runs Derived from the WRAP simulation for February and 

August (ppb gaseous species, ng/m3 aerosol species). 

 Only species with non-zero values are shown. 

Species February August Species February August 

NO 0 0.01 SOA2F 0.53 13.32

NO2 0.02 0.03 SOA3F 0.53 13.32

O3 64.03 49.51 SOA4F 5.95 346.45

OLE 0 0.01 SOA5F 0.53 13.32

PAR 2.55 5.26 POMF 27.68 352.93

TOL 0 0.01 ECF 10.5 72.45

FORM 0.2 0.53 OTRF 4.58 175.45

ALD2 0.02 0.12 NH4C 0.03 0.17

ETH 0 0.03 NO3C 0.02 0.25

PAN 0.15 0.23 SO4C 0.12 0.25

CO 95.36 92.85 SOA1C 0 0.01

H2O2 0.92 3.07 SOA2C 0 0.01

HNO3 0.22 0.28 SOA3C 0 0.01

SO2 0.02 0.04 SOA4C 0.01 0.38

NH4F 31.77 161.54 SOA5C 0 0.01

NO3F 15.75 234.54 POMC 0.03 0.39

SO4F 109.71 237.17 ECC 0.01 0.08

SOA1F 0.53 13.32 OTRC 154.08 346.99

MM5 produced wind speed and direction components (u,v,w), temperature, 

humidity, insolation, and cloud cover data that were input to CAMx. Output from 

the MM5 simulations were layer averaged to the CAMx vertical structure. Vertical 

stability was estimated using the CMAQ-dispersion scheme option and the vertical 

diffusivity minimum value was set at 1.0 m2

/sec. Figures V-2-5 through V-2-8 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 19 

characterize the MM5 surface layer wind fields for morning (1000 PST) and 

afternoon (1400 PST) for January 15, 2005 and July 15, 2005. 

EMISSIONS INVENTORY 

Table V-2-8 provides the baseline 2005, 2014 and 2020 and controlled 2014 and 

2020 modeling emissions inventories used in the attainment demonstration. CAMx 

model is based on the annual average inventory, with adjustments made for weekly 

and monthly variations. A brief characterization of the annual day emissions used for 

the modeling analysis follows. An extensive discussion of the overall emissions 

inventory is summarized in the Final 2007 AQMP Appendix III. 

TABLE V-2-8 

Annual Average Day Emissions Inventory (tons/day) 

Year VOC NOx SOx Diesel Geol PM2.5 

(a) Baseline 

2005 740 1029 62 22 25 106 

2014 528 654 43 12 27 102 

2020 499 525 50 7 28 103 

(b) Controlled 

2014 469 454 19 6 27 87 

2020 398 293 20 3 28 87 

PM2.5 modeling emissions were developed as monthly profiles corrected for 

temperature and humidity. For each month, where applicable, point, area and offroad mobile sources were adjusted to a day-of-week through-put profile consisting of 

a Monday-Friday, Saturday and Sunday schedule. On-road mobile sources were also 

adjusted by the same day-of-week schedule and overlaid with average diurnal 

profiles that represent weekday and weekend defined traffic patterns. The on-road 

mobile source emission data incorporate month specific ambient temperature and 

humidity input. Monthly biogenic emissions inventories (not listed in Table V-2-8) 

were developed by the CARB. 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 20 

FIGURE V-2-5 

MM5 Surface Layer Winds: January 15, 2005, 1000 PST 

FIGURE V-2-6 

MM5 Surface Layer Winds: January 15, 2005, 1400 PST 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 21 

FIGURE V-2-7 

MM5 Surface Layer Winds: January 15, 2005, 1400 PST 

FIGURE V-2-8 

MM5 Surface Layer Winds: January 15, 2005, 1400 PST 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 22 

Paved Road Dust Emissions Uncertainties 

Uncertainties can be estimated for all sources of emission: point, mobile, and area. 

With regard to PM2.5 and PM10 prediction, quantification, spatial allocation and 

apportionment of dust sources is magnified. Paved road dust accounted for the 

largest percentage of the primary emissions category. The paved road dust emissions 

are calculated based on the number of rain days in the year, VMT and silt loading. 

The 2005 paved road dust estimated emissions were impacted by each of these 

factors. 

Rain Days 

Precipitation summaries were reviewed to determine the dates on which measurable 

rainfall (0.01 inches or more in the South Coast Drainage Division) fell in the Basin 

during 2005. A total of 85 days met this criterion in the Basin for 2005. Table V-2-9 

lists the dates meeting this criterion. This data was used adjust monthly entrained 

paved road dust emissions by the rain-factor prescribed in EPA AP-42 (Fifth Edition, 

Volume 1) 13.2.1--Paved Roads. 

TABLE V-2-9 

2005 Rain Days in the Basin: 

Days Recording Measurable Precipitation of at least 0.01 Inches of Rain 

Month Dates 

January 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 24, 26, 27, 28 

February 6, 8, 10,11,12, 13, 17, 18, 19, 20, 21, 22, 23, 24, 25 

March 2, 3, 4, 6, 8, 10, 11, 12, 18, 19, 20, 21, 22, 23, 24, 28 

April 4, 22, 23, 24, 28 

May 5, 6, 9 

June 2, 3 

August 15 

September 3, 5, 19, 20, 21 

October 11, 15, 16, 17, 18, 19, 24, 25, 27, 28, 29 30 

November 9, 10, 11, 25 

December 2, 3, 9, 14, 24, 26, 28, 31 

VMT Capping 

In addition, the paved road dust emissions are a function of VMT. In the 1997 and 

2003 AQMP, paved road dust emissions were adjusted to reflect a cap on emissions 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 23 

growth for high VMT road types in future years. Base year emissions were not 

capped at a given VMT level. The future year adjustment assumed that the silt 

loading would be depleted by the entrainment from the traffic volume. Increasing the 

traffic volume beyond a set point would not increase dust entrainment because the 

silt would be essentially depleted. The Final 2007 AQMP continued this adjustment 

of capping paved road dust on freeways in future years, allowing growth only 

associated with the construction of new lanes or additional miles of freeway. 

 Differential Silt Loading 

A third adjustment was made to the paved road dust emissions to attempt to account 

for the differential silt loading content observed in the densely populated urban 

portions of Los Angeles and Orange Counties and the developing communities in the 

east Basin. Analysis of the preliminary modeling indicated the paved road dust may 

be overestimated by a factor of two in Los Angeles and Orange Counties where the 

traffic volume is greatest and the majority of streets have curbs, gutters and are 

regularly swept. A uniform silt loading factor is used in the CARB model for the 

entire Basin that doesn’t account for differences in land use. Corresponding field 

studies conducted in Sacramento (2000) and Riverside (Fitz, 1998) indicated a wide 

range of silt loading exists to arterials, collectors and local streets that departs from 

the silt loading estimates provided in CARB’s emissions model. 

In addition, examination of the MATES-III data indicates that the crustal-metals 

portion of the PM2.5 distribution is essential constant across the basin. This infers 

that although the paved road dust emissions contribution should be uniform and that 

west Basin VMT contributions are offset by higher silt loading in the east Basin. An 

adjustment was made to the paved road dust emissions to normalize the total basin 

loading by county; lowering Los Angeles by 55 percent, raising Orange County by 

20 percent and doubling the emissions in Riverside and San Bernardino. No net 

change in the Basin total paved road dust occurred. The adjustment was made for 

base and future years by growing the county totals and redistributing the emissions 

using the normalization. 

PM2.5 Split Profiles and Ammonia Inventory Adjustments

Revisions to the particulate emissions split files were made to account for new 

processes and AQMD rule development and implementation. For the Final 2007 

AQMP, a cooking PM2.5 split profile was added and the profiles for residual oil 

burning and distillated oil burning were updated. 

Revisions were made to the spatial distribution and emissions categories defining the 

ammonia inventory. In general, the total ammonia in the inventory did not change 

significantly from the 2003 AQMP inventory with emissions nominally exceeding 

100 tons per day. The contributions of the soils, on-road mobile and livestock 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 24 

categories however did change significantly placing a higher contribution to mobile 

emissions at the expense of soils. Livestock emissions were halved as a result of the 

review and estimation methodology modifications. Table V-2-10 summarizes the 

changes made to the three main ammonia emissions categories. 

Future year (2014) mobile source ammonia emissions are projected to be reduced by 

45 percent from 2005 levels due to fleet turnover. 

TABLE V-2-10 

Comparison of Ammonia Soil, Mobile Source, and Lives Stock Emissions 

Category 2003 AQMP (TPD) Final 2007 AQMP (TPD) 

Soil 34.2 1.42 

On-road Mobile 9.47 36.12 

Live stock 60.37 25.67 

BASE-YEAR ANNUAL SIMULATIONS 

CAMx was simulated for 2005 using the monthly adjusted base-year annual average 

day emissions and the meteorological and air quality data inputs outlined in the 

preceding section. EPA guidance focuses model performance to the ability to predict 

the PM2.5 component species and the total mass. No specific criteria thresholds of 

performance are recommended in EPA’s modeling guidance document. This is 

important since the model is used in a relative response fashion compared to the 

ozone and PM10 analyses in previous AQMPs. 

Performance is evaluated by examining key statistics and graphical presentations of 

differences between model predicted concentrations and observations. The statistics 

examine model bias and error while graphical presentations of error, model 

prediction as a time series and concentration scatter plots round out the prescribed 

methods of model performance evaluation. 

A nearest cell average of predicted concentrations is typically used when comparing 

individual grid concentrations to station measurements, because of possible spatial 

misalignments of the predicted concentration fields. The CAMx modeling results are 

presented based on a nearest nine-grid-cell average basis. Performance evaluations at 

each station are based on this average concentration. 

Finally, model performance is assessed using every third day predications that line up 

with the observations. Statistics and graphical presentations are not included where 

observational data is missing. 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 25 

PM2.5 Component Species Performance Evaluation for the MATES-III Sites

The CAMx 2005 base-year annual average predicted PM2.5 and observations for the 

six component species and total mass at the MATES-III sites are presented in Table 

V-2-11a through V-2-11g. Also presented in the tables are estimates of bias and 

error for each component at each monitoring site. 

Figure V-2-9 provides a “soccer goal” graphical presentation of error for model 

performance. Figure V-2-10a through Figure V-2-10h presents the time series of 

model predicted vs. observations for each component at the MATES-III monitoring 

sites. Figure V-2-11a through Figure V-2-11h presents the scatter-plots of prediction 

accuracy for each component at the MATES-III monitoring sites. Figure V-2-12 

provides the CAMx predicted 2005 spatial distribution of the component species and 

total mass. 

In general, nitrate and ammonium tend to be over predicted by an average 2 μg/m3

 or 

less at most sites. Ammonium model performance at Rubidoux and Fontana are 

approximately within 35 percent of observations and within 20 percent or less for 

nitrate. On average, sulfate is nominally under-predicted however; OC and EC are 

well simulated at all stations. Model performance for the crustal-others category 

indicates an average over-prediction of about 1 μg/m3

 or 25 percent above 

observations. Overall, the prediction of total mass reflects the model performance for 

ammonium, nitrate and the others with a tendency for over-prediction at about an 

average level of 4 μg/m3

 or approximately 20 percent above observations. 

TABLE V-2-11a 

CAMx 2005 Base Year Ammonium Model Predictions (μg/m3

) 

Locations Mean 

Observed 

Mean 

Predicted Mean Bias Mean Error 

Normalized 

Mean Bias 

Normalized 

Mean Error 

 

All Stations 2.60 4.19 1.59 2.32 0.61 0.90 

Anaheim 2.23 3.71 1.48 2.00 0.66 0.90 

Burbank 2.77 3.38 0.61 1.79 0.22 0.65 

Compton 2.32 4.65 2.33 2.68 1.00 1.16 

Fontana 2.95 3.97 1.02 2.29 0.34 0.78 

N Long Beach 2.33 4.15 1.82 2.42 0.78 1.04 

Los Angeles 2.76 4.60 1.83 2.40 0.66 0.87 

Rubidoux 3.20 4.74 1.54 2.34 0.48 0.73 

Wilmington 2.13 3.89 1.77 2.41 0.83 1.13 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 26 

TABLE V-2-11b 

CAMx 2005 Base Year Nitrate Model Predictions (μg/m3

) 

Locations Mean 

Observed 

Mean 

Predicted Mean Bias Mean Error 

Normalized 

Mean Bias 

Normalized 

Mean Error 

 

All Stations 5.35 7.67 2.31 3.98 0.43 0.74 

Anaheim 4.55 7.10 2.55 3.50 0.56 0.77 

Burbank 5.85 6.49 0.64 3.44 0.11 0.59 

Compton 4.46 7.93 3.47 4.12 0.78 0.92 

Fontana 6.76 7.65 0.90 4.38 0.13 0.65 

N Long Beach 4.04 6.52 2.48 3.38 0.61 0.84 

Los Angeles 5.81 8.86 3.05 4.39 0.52 0.76 

Rubidoux 7.67 9.68 2.01 4.81 0.26 0.63 

Wilmington 3.37 5.51 2.14 2.87 0.63 0.85 

TABLE V-2-11c 

CAMx 2005 Base Year Sulfate Model Predictions (μg/m3

) 

Locations Mean 

Observed 

Mean 

Predicted Mean Bias Mean Error 

Normalized 

Mean Bias 

Normalized 

Mean Error 

 

All Stations 3.73 3.29 -0.44 2.03 -0.12 0.55 

Anaheim 3.55 2.75 -0.80 1.77 -0.23 0.50 

Burbank 3.63 2.21 -1.42 1.92 -0.39 0.53 

Compton 3.96 4.09 0.13 2.53 0.03 0.64 

Fontana 3.27 2.61 -0.66 1.63 -0.20 0.50 

N Long Beach 4.36 4.34 -0.02 2.18 0.00 0.50 

Los Angeles 3.78 3.17 -0.61 1.94 -0.16 0.51 

Rubidoux 3.11 2.65 -0.46 1.59 -0.15 0.51 

Wilmington 4.70 4.90 0.20 2.97 0.04 0.63 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 27 

TABLE V-2-11d 

CAMx 2005 Base Year Organic Carbon Model Predictions (μg/m3

) 

Locations Mean 

Observed 

Mean 

Predicted Mean Bias Mean Error 

Normalized 

Mean Bias 

Normalized 

Mean Error 

 

All Stations 4.71 4.83 0.12 1.81 0.03 0.38 

Anaheim 4.15 4.87 0.71 1.57 0.17 0.38 

Burbank 4.73 4.10 -0.63 1.57 -0.13 0.33 

Compton 4.20 5.65 1.44 1.80 0.34 0.43 

Fontana 4.75 3.98 -0.77 1.71 -0.16 0.36 

N Long Beach 4.19 4.88 0.69 1.81 0.17 0.43 

Los Angeles 4.75 6.03 1.28 1.81 0.27 0.38 

Rubidoux 3.99 4.41 0.42 1.34 0.10 0.33 

Wilmington 4.35 4.38 0.03 1.55 0.01 0.36 

TABLE V-2-11e 

CAMx 2005 Base Year Elemental Carbon Model Predictions (μg/m3

) 

Locations Mean 

Observed 

Mean 

Predicted Mean Bias Mean Error 

Normalized 

Mean Bias 

Normalized 

Mean Error 

 

All Stations 1.87 1.66 -0.21 0.82 -0.11 0.44 

Anaheim 1.43 1.36 -0.08 0.66 -0.05 0.46 

Burbank 2.08 1.25 -0.83 1.00 -0.40 0.48 

Compton 1.79 2.04 0.24 0.78 0.13 0.44 

Fontana 2.17 1.33 -0.84 1.02 -0.39 0.47 

N Long Beach 1.44 2.22 0.78 0.91 0.54 0.63 

Los Angeles 1.97 1.94 -0.02 0.68 -0.01 0.34 

Rubidoux 1.71 1.17 -0.54 0.76 -0.32 0.44 

Wilmington 2.07 1.93 -0.14 0.80 -0.07 0.39 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 28 

TABLE V-2-11f 

CAMx 2005 Base Year Crustal-Others Model Predictions (μg/m3

) 

Locations Mean 

Observed 

Mean 

Predicted Mean Bias Mean Error 

Normalized 

Mean Bias 

Normalized 

Mean Error 

 

All Stations 3.62 4.73 1.11 2.87 0.31 0.79 

Anaheim 3.49 4.82 1.33 2.59 0.38 0.74 

Burbank 4.79 3.12 -1.67 2.83 -0.35 0.59 

Compton 3.59 5.23 1.65 3.07 0.46 0.86 

Fontana 3.15 4.25 1.10 2.22 0.35 0.70 

N Long Beach 3.40 5.77 2.36 3.36 0.69 0.99 

Los Angeles 3.47 4.82 1.35 2.87 0.39 0.83 

Rubidoux 3.55 4.78 1.22 2.45 0.34 0.69 

Wilmington 3.72 5.46 1.75 3.73 0.47 1.00 

TABLE V-2-11g 

CAMx 2005 Base Year Total Mass Model Predictions (μg/m3

) 

Locations Mean 

Observed 

Mean 

Predicted Mean Bias Mean Error 

Normalized 

Mean Bias 

Normalized 

Mean Error 

 

All Stations 19.62 26.14 6.52 10.49 0.33 0.53 

Anaheim 17.63 24.45 6.81 8.84 0.39 0.50 

Burbank 21.94 20.72 -1.22 8.76 -0.06 0.40 

Compton 18.83 29.22 10.39 12.24 0.55 0.65 

Fontana 21.44 23.42 1.98 9.29 0.09 0.43 

N Long Beach 17.43 27.84 10.41 11.22 0.60 0.64 

Los Angeles 19.15 29.38 10.23 12.47 0.53 0.65 

Rubidoux 21.85 27.05 5.21 10.32 0.24 0.47 

Wilmington 18.35 25.33 6.98 10.02 0.38 0.55 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 29 

FIGURE V-2-9 

CAMx 2005 Base Year Soccer Plots of Annual Average Error at the MATES-III Sites NME 

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Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 30 

FIGURE V-2-10a 

CAMx 2005 Base Year Time Series: Predicted vs. Observed at Anaheim 

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Chapter 2 Federal PM2.5 Attainment 

V - 2- 31 

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FIGURE V-2-10b 

CAMx 2005 Base Year Time Series: Predicted vs. Observed at Burbank 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 32 

FIGURE V-2-10c 

CAMx 2005 Base Year Time Series: Predicted vs. Observed at Compton 

 ug/m3 

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Chapter 2 Federal PM2.5 Attainment 

V - 2- 33 

FIGURE V-2-10d 

CAMx 2005 Base Year Time Series: Predicted vs. Observed at Fontana 

 ug/m3 

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Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 34 

FIGURE V-2-10e 

CAMx 2005 Base Year Time Series: Predicted vs. Observed at Long Beach 

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Chapter 2 Federal PM2.5 Attainment 

V - 2- 35 

FIGURE V-2-10f 

CAMx 2005 Base Year Time Series: Predicted vs. Observed at Los Angeles 

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Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 36 

FIGURE V-2-10g 

CAMx 2005 Base Year Time Series: Predicted vs. Observed at Rubidoux 

 ug/m3 

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Chapter 2 Federal PM2.5 Attainment 

V - 2- 37 

FIGURE V-2-10h 

CAMx 2005 Base Year Time Series: Predicted vs. Observed at Wilmington 

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Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 38 

FIGURE V-2-11a 

CAMx 2005 Base Year Bivariate Plots: Predicted vs. Observed at Anaheim 

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Chapter 2 Federal PM2.5 Attainment 

V - 2- 39 

FIGURE V-2-11b 

CAMx 2005 Base Year Bivariate Plots: Predicted vs. Observed at Burbank 

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Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 40 

FIGURE V-2-11c 

CAMx 2005 Base Year Bivariate Plots: Predicted vs. Observed at Compton 

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Chapter 2 Federal PM2.5 Attainment 

V - 2- 41 

FIGURE V-2-11d 

CAMx 2005 Base Year Bivariate Plots: Predicted vs. Observed at Fontana 

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Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 42 

FIGURE V-2-11e 

CAMx 2005 Base Year Bivariate Plots: Predicted vs. Observed at Long Beach 

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Chapter 2 Federal PM2.5 Attainment 

V - 2- 43 

FIGURE V-2-11f 

CAMx 2005 Base Year Bivariate Plots: Predicted vs. Observed at Los Angeles 

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Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 44 

FIGURE V-2-11g 

CAMx 2005 Base Year Bivariate Plots: Predicted vs. Observed at Rubidoux 

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0

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10

15

20

25

30

35

40

45

50

55

60

0 5 10 15 20 25 30 35 40 45 50 55 60

Predicted 

Observed 

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30 35 40

Predicted 

Observed 

0

2

4

6

8

10

12

14

16

18

20

0 2 4 6 8 10 12 14 16 18 20

Predicted 

Observed 

0

2

4

6

8

10

12

14

16

18

20

0 2 4 6 8 10 12 14 16 18 20

Predicted 

Observed 

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30 35 40

Predicted 

Observed 

0

10

20

30

40

50

60

70

80

90

100

110

120

0 10 20 30 40 50 60 70 80 90 100 110 120
Chapter 2 Federal PM2.5 Attainment 

V - 2- 45 

FIGURE V-2-11h 

CAMx 2005 Base Year Bivariate Plots: Predicted vs. Observed at Wilmington 

Predicted 

Observed 

0

2

4

6

8

10

12

14

16

18

20

0 2 4 6 8 10 12 14 16 18 20

Predicted 

Observed 

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30 35 40

Predicted 

Observed 

0

2

4

6

8

10

12

14

16

18

20

0 2 4 6 8 10 12 14 16 18 20

Predicted 

Observed 

0

2

4

6

8

10

12

14

16

18

20

0 2 4 6 8 10 12 14 16 18 20

Predicted 

Observed 

0

2

4

6

8

10

12

14

16

18

20

0 2 4 6 8 10 12 14 16 18 20

Predicted 

Observed 

0

5

10

15

20

25

30

35

40

0 5 10 15 20 25 30 35 40

Predicted 

Observed 

0

10

20

30

40

50

60

70

80

0 10 20 30 40 50 60 70 80
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 46 

FIGURE V-2-12 

CAMx 2005 Base Year Spatial Distribution of the Predicted PM2.5 Components and 

Total Mass 

1

1

1

1

1

2

2

2

2

3 3

3

4

4

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

1

1

1

1

1

1

2 2

2

2

2

3

3

3

3

4

4

4

5

5

5

6

6

West 

6

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

1

1

1

1

1 1

1 1

2

2

2

2

2

3

4

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

1

1

1

1 1

1

1 1

1

1

1 1

1

2

2

2

2

2

2

3

3

3

4 4 4

5

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

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0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

.5

.5

.5

.5 .5

.5

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1.0

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1.0

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West 

South 

3675

3700

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

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3775

3800

3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

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3775

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3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

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3775

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3825

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0

10

20

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40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

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3775

3800

3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

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3825

3850

0

10

20

30

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

3850

0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

1

1

1

1

1

1

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2 2

2 3

3

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4 4

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West 

South 

3675

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

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3775

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3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

3800

3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

3800

3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

3800

3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

3750

3775

3800

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0

10

20

30

40

275300325350375400425450475500525550575600

0 10 20 30 40 50 60

9 9

9

9

9

12

12

12

12

15

15

15

18

18

18

21

21

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24 24

West 

South 

3675

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

3700

3725

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3775

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3825

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3775

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0

10

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3775

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0

10

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3775

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0

10

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

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275300325350375400425450475500525550575600

0 10 20 30 40 50 60

West 

South 

3675

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3725

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3775

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0

10

20

30

40

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Chapter 2 Federal PM2.5 Attainment 

V - 2- 47 

Annual Average SSI Mass Performance Evaluation 

Table V-2-12 presents the CAMx predicted annual average PM2.5 and observed 

annual average mass at the District's PM2.5 FRM monitoring network and at FRM 

sites in neighboring air basins included in the modeling domain. The goal of this 

analysis is to demonstrate that the model is consistent in the simulation of PM2.5 at 

the key sites and across the modeling domain. 

In general, the 2005 base year simulations over-predict observed PM2.5 

measurements by the FRM methodology. The over prediction is greatest in the 

western Basin, in particular metropolitan Los Angeles County. Over prediction in 

the San Gabriel Valley and eastern Basin is within 60 percent of observations (with 

the exception of Big Bear Lake which is significantly under-predicted. Southern 

Orange County, Ventura County and the northern desert stations are reasonably well 

simulated. It is important to remember that the attainment demonstration is based on 

a relative response factor and not direct future year simulations. 

TABLE V-2-12 

CAMx Predicted and FRM Observed 2005 Base-Year Annual Average PM2.5

Location Predicted Annual Average 

Concentration (μg/m3

) 

Observed Annual Average 

Concentration (μg/m3) 

Percentage 

Prediction Error 

Azusa 20.4 17.0 20.0 

Big Bear 2.3 12.1 -81.7 

Lynwood 30.4 17.5 73.7 

Mission Viejo 16.8 10.7 57.0 

Ontario 30.3 18.8 61.2 

Pasadena 21.4 15.1 41.7 

Reseda 17.2 13.9 23.7 

Riverside Magnolia 26.7 18.0 48.3 

San Bernardino 28.2 17.0 65.9 

Lancaster-AV 6.8 8.9 -23.6 

Victorville-MD 13.5 9.4 43.6 

El Rio-SCCAB 12.0 10.6 13.2 

Piru-SCCAB 7.1 9.3 -23.7 

Simi Valley-SCCAB 8.9 11.2 -20.5 

Thousand Oaks-SCCAB 11.2 10.5 6.7 

Base-Year Model Performance Stress Test Evaluation 

EPA’s modeling guidance as well as the Draft Modeling Protocol outline a series of 

basic stress tests that can be applied to the base case simulation to determine the level 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 48 

of sensitivity of model performance key parameters defining the simulations. These 

stress tests include modifying the boundary conditions, introducing gross changes in 

the meteorological and emissions profiles. The goal for these analyses is to see if any 

one factor is unduly biasing model performance and in doing so jeopardizing the 

validity of the analysis. 

Table V-2-13 summarizes the suite of performance stress tests applied to the CAMx 

PM2.5 simulations. Gross testing of the meteorological model performance was not 

attempted for the PM2.5 analyses. Graphical and statistical evaluation of the MM5 

simulations were reviewed for the particulate analyses and are discussed in greater 

detail in the Chapter 4 for the episodic the ozone modeling evaluation. In general, 

The PM2.5 model output responded in an expected manner to the changes in 

simulation and emissions profiles outline in the stress tests. 

FUTURE AIR QUALITY 

Under the federal Clean Air Act, the Basin must comply with the federal PM2.5 air 

quality standards by April, 2010 [Section 172(a)(2)(A)]. An extension of up-to five 

years could be granted if attainment cannot be demonstrated and several other 

conditions are satisfied. A simulation of 2010 annual average PM2.5 was conducted 

to substantiate the severity of the PM2.5 problem in the Basin. The simulation used 

the projected emissions for 2009 which included all existing and adopted control 

measures that will be implemented prior to 2010. The resulting 2010 future-year 

design value (17.9 μg/m3

) failed to meet the federal standard. As a consequence and 

as indicated in Chapter 1, the District is formally requesting U.S. EPA to grant the 

five-year extension based upon the severity of the problem and the modeled 

attainment demonstration that clearly indicates that significant reductions in daily 

emissions of PM2.5, NOx, VOC and SOx are required to meet the 2015 attainment 

date. 

Figure V-2-13 depicts future annual average PM2.5 air quality projections based on 

the SMAT at the eight PM2.5 monitoring sites having comprehensive particulate 

species characterization compared to federal and state annual PM2.5 standards, 

respectively. Shown in the figure are the estimated baseline conditions for 2005 

along with projections for 2015, and 2021 with control measures in place. All sites 

will attain the federal annual standard by the year 2015. None of the sites will meet 

the state annual PM2.5 standard (12 μg/m3

) by 2015. Implementation of the 8-hour 

ozone control strategy will continue to lower annual PM2.5 concentrations. 

The Basin currently meets the 24-hour PM2.5 federal standard (65 μg/m3

) although a 

request for re-designation has not been forwarded to EPA. The SMAT applied to 

episodic PM2.5 with emission controls shows that the Basin will maintain its 

attainment of the 24-hour average federal PM2.5 standard in 2015. However, as 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 49 

shown in Figure V-2-15, the Final 2007 AQMP does not achieve the revised 24-hour 

PM2.5 standard (35 μg/m3

) by 2015 or 2021. Additional controls are needed. 

California does not have a separate 24-hour PM2.5 standard. 

TABLE V-2-13 

Annual PM2.5 Model Performance Stress Tests 

Stress Test Methodology Simulated Impact 

Boundary conditions only: no 

biogenic or anthropogenic emissions 

Annual average concentration range 2-5 μg/m3

Boundary conditions and biogenic 

emissions: no anthropogenic 

emissions 

Annual average concentration range 2-5 μg/m3

Boundary conditions and 

anthropogenic emissions: no 

biogenic emissions 

Annual average concentration range 10-30 μg/m3

No NOx emissions in LA and 

Orange Counties or offshore 

Annual average concentration range 10-22 μg/m3

. 

Westside lower 10-19 μg/m3

 but indicates sea 

breeze dispersion and transport.

No NOx emissions in San 

Bernardino and Riverside Counties 

Annual average concentration range 10-28 μg/m3. 

East Basin 5 μg/m3

 lower but indicates sea breeze 

dispersion and transport. 

Gross VOC emissions reductions 40, 

60 & 80 % 

Net 1-2 % reduction in PM2.5 concentration for 

20% VOC emissions reduction. 

Gross NOx emissions reductions 40, 

60 & 80 % 

Net 5-10 % reduction in PM2.5 concentration for 

20% NOx emissions reduction. 

Halving NO & NO2 concentrations 

in boundaries 

Reduction of approximately about 1 μg/m3

EPA Clean SO2 Boundary 10 ppb to 

WRAP 1 ppb 

Reduction of approximately 5 μg/m3

 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 50 

PM2.5 Annual Average Design

0.0

5.0

10.0

15.0

20.0

25.0

Los Angeles

Burbank

Fontana

Anaheim

Compton

Rubidoux

N. Long Beach

Wilmington

ug/m3

2005 Design 2015 Controlled Design 2024 Controlled Design

FIGURE V-2-13 

Annual Average PM2.5 DesignConcentrations: 

2005, 2015 Controlled, and 2024 Controlled 

PM2.5 24-Hour Average Design

0

10

20

30

40

50

60

70

Los Angeles

Burbank

Fontana

Anaheim

Compton

Rubidoux

N. Long Beach

Wilmington

ug/m3

2005 Design 2015 Controlled Design 2024 Controlled Design

FIGURE V-2-14 

Maximum 24-Hour Average PM2.5 DesignConcentrations: 

2005 Baseline, 2015 Controlled, and 2024 Controlled 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 51 

Future-year PM2.5 air quality is projected using the procedures and assumptions 

previously described. Emissions for the 2005 and 2014 baseline and controlled 

scenarios are listed in Table V-2-8. Future year PM2.5 air quality was determined 

using site and species specific relative response factors applied to 2005 PM2.5 design 

values per EPA guidance documents. 

The future year PM2.5 discussion follows the order of the previous analysis on base 

year model performance evaluation. Future year PM2.5 attainment is presented for: 

(1) the MATES-III sites, (2) the annual average for total mass at the FRM PM2.5 

sites, and (3) a weight of evidence the 2015 gridded simulation "hot-spot" grid 

analysis. 

For the purpose of the Basin attainment demonstration, analyses of predicted PM2.5 

outside the District jurisdiction are not presented in this draft analysis. 

Control Strategy Choices 

PM2.5 has five major precursors that contribute to the development of the aerosol 

including ammonia, NOx, SOx, VOC, and directly emitted PM2.5. Various 

combinations of reductions in these pollutants could all provide a path to clean air. 

The attainment strategy presented in this Final 2007 AQMP relies on the maximum 

extent possible reductions of SOx, direct PM2.5, followed by VOC and NOx. As 

discussed in Chapter 4 of the Final 2007 AQMP, the proposed strategy focuses on the 

reductions of SOx and primary PM2.5 through cleaner marine fuels and extensive 

diesel trap retrofits respectively. 

It is useful to weigh the value of the per ton precursor emissions to microgram 

reductions of PM2.5. The formation of PM2.5 is non-linear and as such individual 

precursors contribute differently to the overall mass. The CAMx simulations provide 

a relative rate of reduction per ton of emissions reduced based on complex aerosol 

chemistry. For PM2.5, the simulations determine that VOC emissions reductions 

have the lowest return in terms of micrograms reduced per ton reduction. NOx 

reductions are approximately three times more effective in lowering PM2.5 

concentrations but not as effective as sulfate and direct PM2.5 emissions reductions. 

Table V-2-14 summarizes the relative importance of precursor emissions reductions 

to the analysis. 

The District’s proposed control strategy maximizes reductions of direct PM2.5 and 

SOx to the extent possible due to their effectiveness as well as the likelihood 

schedule of implementation within the next seven years. Substantial additional VOC 

and NOx emissions reductions are also required for attainment. However the 

strategy, nonetheless attempts to maximize the potential PM2.5 concentration 

reduction per identified ton precursor emissions reduction. The mix of the four 

primary precursor’s emissions reductions targeted for the PM2.5 focused approach 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 52 

are listed in the Controlled Emissions Projection Algorithm (CEPA) output attached 

at the end of this document. 

SMAT Annual PM2.5 Attainment Demonstration 

As previously outlined, the SMAT is conducted on a quarterly basis using the CAMx 

model output for the six species from the 2005 base-year and the 2014 controlled 

emissions. Quarterly RRFs determined from the modeling are applied to the 

MATES-III/Sandwich modified quarterly design value component species. Bonded 

water is calculated from the concentrations of ammonium, nitrate and sulfate using 

the AIM polynomial regression equation. Bonded water is not directly reduced by an 

RRF but is recalculated after applying the RRFs to the ammonium, sulfate and 

nitrate. Finally, the blank is added to the mass. 

Tables V-2-15a through V-2-15c provide the 2014 baseline PM2.5 air quality at the 

eight key sites, the predicted PM2.5 based on the CARB emissions reduction plan 

and the estimation of the 2015 controlled annual average PM2.5 adding the District’s 

emissions reduction overlay to the CARB plan. 

Without implementing any additional controls, PM2.5 concentrations at the key sites 

will not meet the federal standard by 2015. Regional concentrations of PM2.5 will 

be lower with implementation of the CARB plan however the maximum predicted 

PM2.5 concentration, will continue to exceed the federal standard by approximately 

four (4) percent. With implementation of the District overlay to the CARB plan, all 

stations will meet the federal standard of 15.0 μg/m3

. The PM2.5 annual attainment 

demonstration calculations using the SMAT and RRFs are provided in Tables V-A1a through V-A-1h in Attachment A. 

TABLE V-2-14 

Relative Contributions of Precursor Emissions Reductions to Simulated 

Controlled Future-Year PM2.5 Concentrations 

Precursor 

(TPD) 

PM2.5 Component (μg/m3) Standardized 

Contribution to 

Mass 

VOC Organic Carbon Factor of 1 

NOx Nitrate Factor of 3 

PM2.5 Elemental Carbon & Others Factor of 5 

SOx Sulfate Factor of 10 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 53 

TABLE V-2-15a 

2014 Predicted Baseline PM2.5 

Location NH4 NO3 SO4 OC EC Metals/ Water Blank PM2.5 

 Others Mass 

Anaheim 1.4 3.3 2.5 2.0 1.3 2.0 1.5 0.5 14.5 

Burbank 1.8 4.1 2.4 3.2 1.7 2.1 1.6 0.5 17.4 

Compton 1.6 3.6 2.9 2.5 1.6 2.0 1.7 0.5 16.5 

Fontana 1.9 4.8 2.5 1.6 1.9 2.6 1.7 0.5 17.6 

Los Angeles 2.0 4.8 2.9 1.1 1.9 2.1 2.1 0.5 17.3 

Long Beach 1.6 3.3 3.0 1.5 1.3 1.9 1.6 0.5 14.6 

Rubidoux 2.1 5.6 2.4 2.1 1.7 2.2 1.9 0.5 18.5 

Wilmington 1.4 2.7 3.0 1.5 1.7 1.9 1.5 0.5 14.2 

TABLE V-2-15b 

2014 Predicted PM2.5 with CARB Measures 

Location NH4 NO3 SO4 OC EC Metals/ Water Blank PM2.5 

 Others Mass 

Anaheim 1.2 2.9 2.0 1.7 1.2 1.9 1.3 0.5 12.6 

Burbank 1.6 3.7 1.9 2.9 1.6 2.0 1.4 0.5 15.5 

Compton 1.5 3.4 2.3 2.2 1.5 1.9 1.5 0.5 14.7 

Fontana 1.6 4.0 2.0 1.4 1.8 2.5 1.4 0.5 15.2 

Los Angeles 1.8 4.4 2.3 0.9 1.7 2.1 1.8 0.5 15.4 

Long Beach 1.4 3.1 2.3 1.3 1.2 1.7 1.4 0.5 12.9 

Rubidoux 1.7 4.5 1.9 1.9 1.6 2.1 1.5 0.5 15.7 

Wilmington 1.2 2.5 2.2 1.4 1.4 1.7 1.3 0.5 12.1 

TABLE V-2-15c 

2014 Predicted PM2.5 with CARB Measures and District Overlay 

Location NH4 NO3 SO4 OC EC Metals/ Water Blank PM2.5 

 Others Mass 

Anaheim 1.2 2.7 1.9 1.7 1.1 1.9 1.2 0.5 12.3 

Burbank 1.5 3.5 1.9 2.8 1.5 2.0 1.3 0.5 14.9 

Compton 1.4 3.4 2.2 2.2 1.4 1.9 1.5 0.5 14.5 

Fontana 1.5 3.7 2.0 1.4 1.7 2.5 1.4 0.5 14.7 

Los Angeles 1.7 4.2 2.2 0.9 1.6 2.0 1.7 0.5 14.9 

Long Beach 1.4 3.0 2.3 1.3 1.2 1.7 1.4 0.5 12.7 

Rubidoux 1.6 4.1 1.9 1.8 1.5 2.1 1.4 0.5 15.0 

Wilmington 1.1 2.4 2.2 1.3 1.4 1.6 1.2 0.5 11.8 
Chapter 2 Federal PM2.5 Attainment 

V - 2-54 

2015 CAMx Grid-Cell Evaluation

Figure V-2-15 presents the grid cell extrapolated of 2005 PM2.5 annual design 

values. Only grid cells over the federal standard are darkened. Extrapolation was 

based on distance weighted interpolation scheme using design values from sites 

inside and outside the Basin to enhance the spatial representation. The pattern 

depicted by the grid cell design display closely matches the pattern of annual average 

PM2.5 presented in Figure V-2-3. 

Using a similar interpolation scheme, the relative percentage contributions of the six 

component species at the eight MATES-III sites was extrapolated to each cell in the 

basin. Predicted 2015 PM2.5 concentrations at the grid cell level (without using 

multi-cell averaging) was estimated each grid cell by multiplying the speciated RRFs 

from the CAMx simulations by the relative percentage concentrations of the six 

components contributing to the grid cell mass and the interpolated grid cell design 

value. Figure V-2-16 presents the 2015 baseline distribution. PM2.5 levels will be 

reduced regionally with implementing additional control measure however, almost 60 

percent of the population of the Basin will continue to breathe air quality above the 

federal standard. With the Final 2007 AQMP control strategy in place no cells in the 

Basin will be above the federal standard. 

SMAT 24-Hour PM2.5 Attainment Demonstration 

As previously stated, the 2005 Basin maximum design value (64.8 μg/m3) meets the 

federal 24-hour average PM2.5 standard of 65 μg/m3. The SMAT for the 24-hour 

standard is presented to assure that the PM2.5 episodic levels continue to lower and 

that the Basin continues to meet the standard in 2015 and beyond. Six methods are 

applied to the Sandwich modified MATES-III quarterly design values and episodic 

PM2.5 data to quantify future year PM2.5 reductions. All of the tests summarized in 

Table V-2-15 demonstrate continued attainment of the 24-hour average PM2.5 

standard in 2015. 

The six versions of the 24-hour PM2.5 SMAT include: 

• CAMx derived RRFs (2005-2014) for the annual average PM2.5 attainment 

demonstration are applied to the three-year average PM2.5 design values; 

• the quarterly based SMAT prescribed in the EPA guidance document that uses 

the CAMx quarterly RRF’s from the top 25 percentile applied to the quarterly 

24-hour design values for each year in the three year period 2003-2005; 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 55 

FIGURE V- 2-15 

2005 Grid-Cell Extrapolated Design Values > 15.0 μg/m3 

FIGURE V- 2-16 

2015 Baseline Grid-Cell Extrapolated Predicted Design Values (μg/m3 ) 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 56 

• a version of the quarterly based SMAT prescribed in the EPA guidance 

document that uses the CAMx quarterly RRF’s from the annual average 

PM2.5 attainment demonstration applied to the quarterly 24-hour design 

values for each year in the three year period 2003-2005; 

• a modified version of the second option that applies the quarterly RRFs from 

the top 25 percentile to the top three quarterly episodic 2005 PM2.5 

measurements; 

• the expected response of the peak episode PM2.5 [October 22, 2005, 110 

μg/m3] to episodic specific RRFs is applied to the 3-year average Basin 

maximum design value, and 

• the expected response of the peak episode PM2.5 to the annual average RRFs 

is applied to the 3-year average Basin maximum design value. 

Table V-2-16 summarizes the different methods for calculating the 2015 24-hour 

PM2.5 design value. 

The first test simply assumes that the RRFs calculated for the annual average attainment 

demonstration can be directly applied to the 24-hour PM2.5 design values to estimate the 

2015 reduction in PM2.5 due to implementation of the control strategy. The second test 

is more conservative and follows the example specified in the EPA guidance document. 

The quarterly RRFs determined for the top 25 percent of the quarterly distributions are 

applied to the component based design values for the period 2003 through 2015 to 

recreate a design value. The third test recreates the second test but uses the quarterly 

RRFs derived from the annual PM2.5 analysis. 

The fourth analysis focuses on the top three episodic days in each quarter of 2005 to 

establish both the percentage contributions of the components to the sample mass and an 

average quarterly top-three distribution for an episodic period. The quarterly RRFs 

determined for the top-25 percentile analysis are applied to the top-three quarterly 

measurements to determine a quarterly mass reduction percentage. The quarterly 

percentage reduction is then applied to the quarterly 2005 design to estimate a 2015 

quarterly concentration. 

The fifth and sixth analyses apply the day specific and annual average RRFs to the 

component species observed on October 22, 2005, the day having the highest measured 

PM2.5 at a majority of sites in the Basin. These two analyses, like the third, produce a 

percentage reduction that is applied to the 2005 design to estimate 2015 attainment 

The PM2.5 24-hour attainment demonstration calculations using the SMAT and RRFs are 

provided in Attachment A. Table V-A-2 provides the annual average RRF applied to the 

24-hour annual design value. Tables V-A-3a through V-A-3h present the EPA 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 57 

recommended attainment test. Tables V-A-4a through V-A-4h presents the modified 

EPA test using the quarterly RRFs from the annual attainment demonstration as an 

alternate reduction rate. Tables V-A-5a through V-A-5h present the application of the 

quarterly top-25 percentile RRFs to the 2005 quarterly top-three episodic measurements. 

Tables V-A-6a through V-A-6h provide the applications of the episodic model derived 

RRFs to the peak episodes and the application of the annual RRFs to the peak episodes 
Chapter 2 Federa

V - 2-58 

TABLE V-2-16 

Summary of Methodologies to Calculate 2015 24-Hour Average Design Value (μg/m3)

Location Annual RRF to Design 

Quarterly Top 

25 Percentile 

RRF to 

Quarterly 

Design

Quarterly 

RRF from 

Annual 

to Quarterly 

Design

Quarterly Top 

25 Percentile 

RRF to 

Quarterly 

Top-3 Ratio to 

Design 

Peak Day 

RRF to Peak 

Day 

Annual R

to Peak D

Anaheim 35.7 42.8 

41.8 

38.5 34.6 34.1 

Burbank 40.5 47.7 

46.7 

44.1 43.8 39.4 

Compton 39.5 56.6 

46.3 

54.3 37.5 40.9 

Fontana 40.0 45.0 

46.7 

41.2 36.8 33.0 

Long Beach 32.4 41.9 

39.1 

37.3 31.2 33.3 

Los Angeles 46.1 55.1 

50.7 

47.8 50.3 46.4 

Rubidoux 42.8 46.9 

49.3 

47.1 38.6 37.4 

Wilmington 30.3 39.5 

36.1 

35.8 30.3 28.8 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 59 

WEIGHT OF EVIDENCE 

Table V-1-3 in Chapter 1 summarizes the additional information requirements 

needed to support the modeling attainment demonstrations based upon the projected 

future year concentration. Specifically, “A weight of evidence demonstration should 

be conducted to determine if aggregate supplemental analyses support the modeled 

attainment test.” The “weight of evidence” supporting information for the current 

PM2.5 attainment demonstration includes an analyses of the PM2.5 air quality trend, 

trends in population exposure, emissions trends, and adjustments to the mobile 

source emissions VMT distributions. While the weight of evidence discussion is 

focused towards supporting the attainment demonstration, it is important to be 

unbiased and present both sides of the argument “for” and “against” acceptance of 

the analysis. In the case of the PM2.5, it is equally important to remember the 

magnitude of the problem requires an extraordinary commitment to implementation 

of the control strategy. Positive trend data in either air quality or emissions 

reductions should be viewed as encouraging but not taken solely as the remedy to the 

air quality problem. 

Air Quality Trends 

Probably the most convincing argument that the Basin will attain the Federal 

Standard for PM2.5 in 2015 is the ongoing trend of ambient PM2.5 concentrations. 

Figure V-2-17 depicts the trend of annual average PM2.5 concentrations at key 

monitoring stations in each of the four counties of the Basin. The trend clearly 

depicts a steady rate of improving PM2.5 air quality, regardless of locations in the 

Basin. This trend line also supports the argument for selecting 2005 as the design 

year to anchor the PM2.5 attainment demonstration due to the rapid change in air 

quality. The 4-station average PM2.5 has improved by more than 36 percent from 

1999 through 2006 for an approximate 4.5 percent annual improvement rate. 

It is dangerous, however, to directly extrapolate the improvement rate. For example, 

over the last 10 years, the first five years of data would have suggested vast 

improvement for the following five year period. But, the trend flattened to little to no 

improvement. Redistribution of population and industrial growth in the east Basin is 

expected to continue to increase over the next 10 years. This shift in demographics is 

expected to slow the east basin trend of improving air quality. Also, with the 

expected tripling of goods movement through the Ports of Los Angeles and Long 

Beach, emissions from heavy duty truck and rail traffic is expected to increase 

accordingly. Regardless, while the trend is encouraging, the rate of improvement 

will slow and possibly turn around if no further emissions reductions are made. 

Implementation of the control strategy proposals of the Ports, CARB through their 

AQMP commitment and the District’s total program is expected to ensure that PM2.5 

levels will continue to improve regionally. 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 60 

 

10

15

20

25

30

35

1999 2000 2001 2002 2003 2004 2005 2006

Annual Average ug/m3

Los Angeles Anaheim Rubidoux Fontana

FIGURE V-2-17 

Trend of Annual Average PM2.5 in the South Coast Air Basin (1999-2006) 

Emissions Trends 

Figures V-2-18 and V-2-19 depict the baseline trends of the PM2.5 precursor 

emissions from 2002 through 2023. The VOC and NOx emissions a trend lines up 

nicely against the PM2.5 air quality trend for the 2002 to 2005 period. Four and two 

percent reductions of VOC and NOx emissions respectively are consistent with 

improving air quality trend. However increases in directly emitted particulate and 

SOx suggests an offset to the other precursor emissions benefits over the 2002 – 2005 

period. Introduction of a 15 ppm sulfur fuel in California in 2006 is not depicted in 

the 2005 bar but in reality, the region may have experienced an early phase in of the 

lower sulfur fuel. Clearly the baseline trend in sulfur emissions is lower over the 

next six year before undergoing a moderate increase in 2014. 

Figure V-2-20 show the impact of the emissions control strategy. Significant 

additional reductions beyond baseline are demonstrated through 2020. With the 

control strategy implemented in 2014, the Basin will experience reductions in 

emissions from 2005 of: 36.6 percent for VOC, 57.5 percent for NOx, 69.4 percent 

for SOx, and 13.7 percent for directly emitted PM2.5. Translated over the nine seven 

years needed to implement annual percent reductions are expected to be consistent 

with those observed between 2002 and 2005. The confirms that implementations of 

the control strategy on top of a decreasing baseline will move the air quality trend in 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 61 

the direction of improving PM2.5 concentrations and attainment of the federal 

standard. 

0

200

400

600

800

1000

1200

2002 2005 2008 2011 2014 2017 2020 2023

Tons Per Day

VOC NOX

FIGURE V-2-18 

Trend of Baseline VOC and NOx Emissions (TPD) in the South Coast Air Basin 

0

20

40

60

80

100

120

2002 2005 2008 2011 2014 2017 2020 2023

Tons Per Day

SOX PM2.5

FIGURE V-2-19 

Trend of Baseline SOx and PM2.5 Emissions (TPD) in the South Coast Air Basin 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 62 

0

100

200

300

400

500

600

700

2014 2014

Controlled 

2020 2020

Controlled

Tons Per Day

VOC NOX SOX PM2.5

FIGURE V-2-20 

Comparison of Baseline and Controlled Emissions (TPD) in the South Coast Air Basin 

Mobile Source Emissions and VMT 

The emissions inventory used for the October 2006 / Draft 2007 AQMP relied on an 

interim inventory and a working draft version of EMFAC 2007 that CARB provided 

to AQMD staff to begin the analysis for the Draft 2007 AQMP. Several major 

improvements to the EMFAC and off-road models were in progress at the time. 

CARB staff released the official EMFAC2007 and OFFROAD emissions model on 

November 1, 2006 and provided subsequent additional external adjustment factors to 

incorporate additional changes viewed necessary to the mobile source inventories. 

Significant changes occurred to VOC and NOx on-road mobile source emissions. A 

decrease in VOC emissions was made due to the modification in number of pending 

vehicle registrations assumed in the EMFAC model. “Pending vehicles” are those in 

the DMV data base that are not fully processed for administrative reasons. In prior 

EMFAC models, pending vehicles were not included which might have contributed 

to previous underestimation of VOC emissions in the inventory. In developing the 

working draft of EMFAC2007 for the Draft 2007 AQMP, CARB staff assumed all 

pending registrations were on the road, and incorporated these vehicles in the vehicle 

population analysis. However, with the official release of EMFAC2007, CARB staff 

revised its assumption based on further evaluation of the pending registration and 

concluded that only 25 percent of the total pending vehicles were actually being 

driven. The change in assumption resulted in a 95 tons/day decrease in VOCs for 

2005 with minor impact on the NOx emissions. This is due to the fact that the 

pending vehicles have a greater impact on evaporative emissions (i.e., VOC) than 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 63 

pending vehicles have a greater impact on evaporative emissions (i.e., VOC) than 

tailpipe exhaust emissions since total vehicle miles traveled (VMT) were presumably 

already captured by the EMFAC model. 

The impact of the significant change in the VOC inventory is most apparent in the 

performance of the CAMx base year ozone simulations. VOC emissions are a 

critical component of the PM2.5 inventory however as depicted in Table V-2-14 the 

reduction of VOC emissions had a smaller impact compared with other precursors. 

The net change in the inventory for 2005 NOx emissions was an increase of about 10 

TPD based on EMFAC2007 derived VMT profile. 

Differing Estimates of VMT on Future Year PM2.5 

Historically, VMT is calculated through several approaches. One approach, used by 

metropolitan planning organizations such as SCAG, uses complex simulation models 

to spatially estimate VMT based on origin-destination surveys. The approach used 

by CARB is based on Department of Motor Vehicle (DMV) vehicle registrations and 

Bureau of Automotive Repair (BAR) odometer readings collected through the Smog 

Check program. 

Under state and federal law, transportation agencies develop VMT information for 

transportation planning and conformity purposes. Under federal law, the Highway 

Performance Monitoring System (HPMS) estimates of VMT are to be considered the 

primary measure of VMT “within the portion of the nonattainment area” [40 CFR 

93.122(b)(3)]. In addition, “For areas with network-based travel models, a factor (or 

factors) may be developed to reconcile and calibrate the network-based travel model 

estimates of VMT in the base year of its validation to the HPMS estimates for the 

same period. These factors may then be applied to model estimates of future VMT. 

Locally developed count-based programs and other departures from these procedures 

are permitted subject to the interagency consultation procedures of § 93.105(c)(1)(i).” 

SCAG provided VMT estimates for calendar years 2000, 2002, 2005, 2010, 2015, 

2020, and 2030 to CARB and AQMD for the development of the 2007 AQMP 

revision. SCAG’s estimates are based on information developed for the 2004 RTP. 

The South Coast Air Basin VMT totals are used for planning purposes and the 

spatially disaggregated VMT is used for air quality modeling purposes. CARB 

compares SCAG’s VMT estimates with their VMT estimates based on the DMV and 

BAR registration data and attempts to reconcile with SCAG’s estimates using vehicle 

population data and mileage accrual rate. 

In the prior EMFAC models, CARB’s VMT estimates generally agreed with SCAG’s 

estimates. For the latest EMFAC 2007, CARB took DMV and BAR data from 2000 

to 2005 to develop new VMT estimates for 2000, 2002, and 2005. When CARB 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 2- 64 

VMT data are in close agreement with SCAG's except for 2005. AQMD staff 

examination of the EMFAC VMT indicates that for 2005 the difference in CARB’s 

VMT estimates and SCAG’s is on the order of 10 percent for light- and medium-duty 

vehicles (or 30 million more VMT per day) and 20 percent for heavy duty vehicles 

(or about 5 million more VMT per day). CARB staff indicated that they believe that 

the differences are within the uncertainties of estimating VMT. 

Figure V-2-21 illustrates the difference between the current EMFAC on-road mobile 

sources VMT assumption compared to SCAG’s projections. The difference between 

the two estimation methodologies is portrayed as the 2005 “blip” in the diagram.

FIGURE V-2-21 

EMFAC2007 vs. SCAG’s Project of Basin On-Road VMT 

The AQMD retained two technical experts in the area of transportation analysis to 

review the VMT estimates for 2005. The consultants reviewed CARB’s assumptions 

and to the extent possible some of the DMV and BAR data used to produce the 2005 

VMT estimates. They concluded that there is no independent evidence to support a 

decline in VMT between 2005 and 2010, and recommended conducting sensitivity 

analysis in the near-term (given the need to develop an AQMP Revision) to 

determine the magnitude of the differences. 

300

320

340

360

380

400

420

440

460

480

2000 2005 2010 2015 2020 2025

Adjusted EMFAC 2007 

SCAG Projections 

EMFAC 2007 
Chapter 2 Federal PM2.5 Attainment 

V - 2- 65 

Impact to Projections of Future Year PM2.5 

CAMx was simulated for PM2.5 using the SCAG estimate of VMT which resulted in 

a reduction of 10 TPD fewer tons of 2005 base-year NOx emissions. A rough 

estimate of this impact was between 0.08 and 0.10 μg/m3

 less PM2.5 produced in 

2005, the anchor year for the RRF calculation. (Less PM2.5 produced through the 

2005 simulation affects the slope of the RRF and will require additional emissions 

reductions in future years). Estimation of the impact of using SCAG’s VMT profile 

to 2015 PM2.5 is roughly place the need for about 10 additional tons of NOx 

reductions in 2014 or its equivalent reduction in either SOx, directly emitted PM2.5 

or VOC. Using SCAG’s VMT profile as the basis for 2005 mobile source NOx 

provided a conservative choice that confirmed the direction of tonnage of emissions 

reductions needed to meet the federal standard with confidence. 

In light of uncertainty in VMT projections, the District staff recommended to retain 

the mobile source emissions estimates made from EMFAC2007 for the planning 

inventory. However, for modeling purposes, the gridded mobile source emissions 

were based on the SCAG 2005 projection of VMT. 
CHAPTER 3 

THE FEDERAL 24-HOUR PM10 ATTAINMENT 

DEMONSTRATION PLAN AND VISIBILITY 

ASSESSMENT 

Introduction 

Modeling Methodology 

Future Year Air Quality 

Visibility 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 3- 1 

INTRODUCTION 

As discussed, in the main document, on September 21, 2006 the U.S. EPA 

administrator signed the final documents that eliminated the existing annual PM10 

standard. The action retained 24-hour PM10 standard at its existing concentration of 

150 μg/m3

. The form of the 24-hour PM10 standard allows for one violation of the 

standard annually. The Basin currently meets the 24-hour average federal standard. 

(The only days that exceed the standard are associated with high wind natural events 

or exceptional events due to wildfires). 

For this analysis, the annual second maximum concentration is used for the 

attainment demonstration (given the standard allows for one violation annually). 

Riverside Rubidoux has been the PM10 24-hour design site in nine of the past ten 

years when high wind days have been excluded from the analysis. The 2005 design 

value at Rubidoux is 86 percent of the federal standard. The standard attainment 

demonstration is conducted to assure that the Basin will continue to be in compliance 

in future years. 

MODELING METHODOLOGY 

As a conservative analysis, only emissions reductions associated with the PM2.5 

portion of the 24-hour PM10 concentration are assumed to be impacted by future 

year emission controls. Co-located PM10 and PM2.5 measurements (monitored on 

the same days) were used to determine the site specific average percentage 

contribution of PM2.5 to the PM10 annual and second annual maximum 

concentrations. 

Future year predictions of maximum and second maximum 24-hour average PM2.5 

were determined using the site specific annual PM2.5 RRFs calculated for 2005 and 

2014. The annual PM2.5 RRF encumbers total mass rather than individual 

component species. The site specific RRF was applied to the PM2.5 portion of the 

PM10. The PM10-2.5 “coarse” portion remains constant in the analysis. 

The RRFs for the six of the eight MATES-III sites, calculated from the annual PM2.5 

attainment demonstration, for 2005 to 2014, are applied directly to the fine portion of 

the 24-hour PM10 distribution measured at that location. The Compton RRF was 

applied to the Lynwood PM10 (since the monitoring stations are closely located). 

The average RRF determined from all eight MATES-III sites was used to estimated 

the reductions of the PM2.5 portion of the PM10 mass at the remaining PM10 sites in 

the Basin. The predicted reductions to the fine portion are then added to the coarse to 

estimate a 2015 second maximum PM10 24-hour average design concentration. 
 Chapter 3 Federal 24-Hour PM10 Attainment Plan and Visibility Assessment

V -3- 2 

FUTURE YEAR AIR QUALITY 

PM10 24-hour attainment Demonstration 

Table V-3-1 summarizes the PM10 24-hour attainment demonstration. All sites meet 

the federal PM10 standard of 150 μg/m3

 in 2015. The predicted 2nd highest 

maximum concentrations for 2015 is located at Rubidoux and values approximately 

74 percent of the federal standard. Only five of the sixteen locations are expected to 

meet the more restive state standard of 50 μg/m3

 by 2015. Rubidoux is predicted to 

exceed the state standard by 122 percent in 2015. 

PM10 Annual Analysis 

The Final 2007 AQMP does not provide an updated regional attainment 

demonstration to show compliance to the revoked annual PM10 standard (50 μg/m3

). 

At the writing of this document, it is expected that the 2006 design value for 

Rubidoux will continue to nominally exceed the revoked federal standard but will 

continue to exceed the California PM10 standard of 20 μg/m3

. Despite EPA’s 

decision revoking the PM10 annual standard, the District will continue to work 

towards meeting its former attainment target in the effort to protect public health, 

demonstrate progress towards attaining the state PM10 annual standard and assist in 

compliance of the federal 24-hour PM10 standard. 

As part of the 2003 AQMP, the District proposed a comprehensive program to 

examine the local emissions profile and potential for mitigation actions that could be 

taken to bring PM10 concentrations at Rubidoux within the annual standard by 2006. 

A survey of the local emissions was conducted and as a result two District rules 

(1186 and 1174) targeting emissions from aggregate operations and bag houses have 

been strengthened in the efforts to reduce impacts to the Rubidoux community. In 

addition, the District has increased compliance measures in the area and staff is 

working with the Riverside County Redevelopment agencies to expedite installation 

of paved curbs and gutters to eliminate sources of fugitive dust emissions. The Final 

2007 AQMP control measure BCM-02 PM Emissions Hot Spots continues this 

concept of addressing localized PM impacts. 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 3- 3 

TABLE V-3-1 

24-Hour Average Maximum and Average 2nd Maximum Basin PM10:

2003-2005 Baseline Design and 2015 Controlled 

Average 

Maximum 

Average 2nd

Maximum 

Location 

Mass 

(μg/m3) 

PM2.5/PM10 

Ratio 

Est. 

2.5 

Mass 

(μg/m3) 

Est. 

Coarse 

Mass 

(μg/m3) 

Mass 

(μg/m3)

PM2.5/PM10 

Ratio 

Est. 

2.5 

Mass 

(μg/m3) 

Est. 

Coarse 

Mass 

(μg/m3) 

24-Hour Average 

PM2.5 

RRF 

201

Estim

Aver

Maxim

(μg/m

Azusa 93 0.51 47.6 45.4 79 0.54 42.3 36.7 0.75 Burbank 82 0.51 42.0 40.0 73 0.69 50.2 22.8 0.79 Long Beach 96 0.73 69.8 26.2 63 0.78 48.9 14.1 0.73 Los Angeles 74 0.75 55.7 18.3 69 0.80 54.9 14.1 0.76 Santa Clarita 60 0.56 33.6 26.4 54 0.54 29.2 24.8 0.75 Hawthorne 53 0.56 29.7 23.3 61 0.54 32.9 28.1 0.75 Anaheim 78 0.50 38.8 39.2 67 0.49 33.1 33.9 0.74 Mission Viejo 51 0.69 35.4 15.6 44 0.33 14.7 29.3 0.74 Rubidoux 141 0.60 84.4 56.6 129 0.42 54.3 74.7 0.66 Perris 102 0.56 57.1 44.9 88 0.54 47.5 40.5 0.75 Banning Airport 79 0.56 44.2 34.8 55 0.54 29.7 25.3 0.75 Crestline 49 0.56 27.4 21.6 47 0.54 25.4 21.6 0.75 Fontana 105 0.29 30.6 74.4 96 0.36 34.2 61.8 0.73 San Bernardino 96 0.58 55.5 40.5 85 0.44 37.8 47.2 0.75 Redlands 80 0.56 44.8 35.2 70 0.54 37.8 32.2 0.75 Ontario 90 0.44 40.0 50.0 77 0.65 50.1 26.9 0.75 
 Chapter 3 Federal 24-Hour PM10 Attainment Plan and Visibility Assessment

V -3- 4 

VISIBILITY 

Background 

In July 1999, U.S. EPA adopted the federal Regional Haze Regulations [40 CFR Part 

51] to address Section 169A of the CAA which set forth a national goal for future 

visibility with specific focus to remedy any visibility impairments to Class I areas 

nationwide. States are required to provide to EPA emissions reduction strategies to 

improve visibility in all mandatory Class I national parks and wilderness areas. In 

response to the requirements of the regulations, California joined the Western 

Regional Air Partnership (WRAP), a multi-agency organization that is coordinating 

implementation of the regional haze rules. States with PM2.5 non-attainment areas 

are require to submit “haze plans” to EPA within 3-years following PM2.5 

designation and develop future year (2018) inventories of emissions that lead to 

visibility reduction. The ARB has assumed the responsibility for the plan and 

inventory development requirements for the state. 

The emissions reductions needed to attain the PM2.5 standard in the Basin will 

directly contribute to improved future year visibility. California continues to 

maintain a state standard for visibility structured to reduce aerosol particles (8-hour 

average) that contribute to an extinction coefficient value of 0.23 per kilometer (or 10 

miles of visual range) when relative humidity is less than 70 percent. The previous 

form of the standard assessed the number of days when visual range was less than 10 

miles for the same humidity consideration. Visibility is among the strongest 

indicators to air quality and its value is paramount. As such, future year visibility is 

used in the socioeconomic evaluation of the AQMP to estimate monetary benefits 

that arise from improved visual range through the implementation of the plan. 

Future-year visibility in the Basin is projected empirically using the results derived 

from a regression analysis of visibility with air quality measurements. The regression 

data set consisted of aerosol composition data collected during a special monitoring 

program conducted concurrently with visibility data collection (prevailing visibility 

observations from airports and visibility measurements from District monitoring 

stations). A full description of the visibility analysis is given in Technical Report V-C 

of the 1994 AQMP. 

Visibility Modeling 

To establish the most reasonable control strategy to meet the visibility standard in the 

future, a relationship between visibility and concentrations of visibility reducing 

particles must be established. This, in turn, requires visibility modeling techniques to 

identify sources of visibility reducing particles and to quantify their impacts. 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 3- 5 

The total atmospheric light extinction can be broken down into four basic 

components: scattering of light by particles, absorption of light by particles, 

absorption of light by gases, and scattering of light by gases (Rayleigh scattering). In 

general, total light extinction is dominated by scattering of light due to particles, with 

light absorption by particles being second in importance. The components other than 

scattering of light by particles have been well-characterized by theory or from 

previous studies. Therefore, light extinction by particle scattering is normally 

estimated either by visibility modeling or by direct measurement. 

Multiple linear regression is a statistical tool commonly used for characterizing the 

relationship between visibility and ambient air quality of the visibility reducing 

particles. When atmospheric light extinction due to particle scattering is regressed on 

concentrations of visibility reducing particles, the regression coefficients represent 

the extinction efficiency due to particle scattering (extinction per unit concentration) 

for each air pollutant species. 

Multiple linear regression was employed in the 1991 AQMP to develop empirical 

predictive equations. Empirical visibility model developed in the 1991 AQMP for 

Riverside were utilized in the current AQMP analysis to estimate future visibilities 

with new future-year (2015, and 2021) organic carbon concentrations, sulfate, and 

nitrate concentrations which were obtained from the CAMx simulations. Details of 

the statistical analysis used to develop the empirical predictive equations can be 

found in Technical Report V-G of the 1991 AQMP. 

Prior Visibility Modeling Results 

In the 1991 AQMP, the regression analysis resulted in several sets of extinction 

efficiencies for light scattering by particles for Riverside (Rubidoux station) and four 

additional measurement locations. (Since Rubidoux is the limiting PM2.5 station in 

the Basin it is considered to be the representative site for expected minimum Basin 

visual range estimation.) Combining extinction efficiencies for light scattering by 

particles with the empirical expressions for the other light extinction component 

produces a series of empirical predictive equations. Empirical predictive equations 

relate light extinction to concentrations of visibility reducing air pollutants and have 

the following form: 

bext = Summation ( bi

. Ci

 )+ bRAY

where bi

 = extinction efficiency for ith species 

 (10-4 m-1/μg/m3

 or 10-4 m-1/pphm) 

 Ci

 = mean concentration for ith species (μg/m3 or pphm) 
 Chapter 3 Federal 24-Hour PM10 Attainment Plan and Visibility Assessment

V -3- 6 

 bRAY = extinction due to Rayleigh scattering in the Basin (10-4

m-1) 

Table V-3-2 is a summary of the 1991 AQMP results, showing the extinction 

efficiency, bi

, for Riverside. (The extinction efficiency, bi, for the other locations 

analyzed in the 1994 AQMP can be found in 1994 AQMP, Technical Report V-C). 

A baseline light extinction budget was determined for each empirical predictive 

equation using the mean measured values of the air quality components for the 

baseline year 2005. The light extinction budget for Riverside during the baseline 

emission year is summarized in Table V-3-3. These show the percent contribution to 

total extinction from each component for each equation. At Riverside light scattering 

by particles accounts for up to 86 percent of the total light extinction with secondary 

nitrate and carbon particles being dominant. 

Predicted Future Air Quality 

Future air quality levels are needed to estimate future visual air quality. The 

concentrations of sulfate, nitrate, organic carbon and elemental for future years 2015, 

and 2021 are taken from the results of the CAMx modeling analysis. Future 

concentrations of NO2 are estimated from the mean annual concentrations measured 

using linear rollback of NOx emissions. Natural background concentrations for each 

of these are assumed to be negligible for this analysis. Estimated future baseline and 

controlled levels for all pollutant species that affect visibility are shown in Table V3-4. 

Future Visibility Projections 

Tables V-3-5 and V-3-6 compare the predicted future visibility with the current 

levels based on measurements. The results for the baseline emission scenario (no 

further emission controls) are shown in Table V-3-5 and the results for the controlled 

emission scenarios are shown in Table V-3-6. Each table shows the predicted annual 

average light extinction coefficients compared to the total light extinction coefficient 

derived from 1986 measurements and the mean visual range estimated from the 

measured and predicted extinction coefficients. Figure V-3-1 illustrates the 

improvement in visibility in terms of the annual visual range for both emission 

control scenarios. 

The results of the visibility analysis for Rubidoux illustrated in Figure V-3-1 indicate 

that with future year reductions of PM2.5 from implementation of all proposed 

emission controls for 2015, the annual average visibility would improve from about 

10 miles (calculated for 2005) to over 20 miles at Rubidoux. Visual range in 2021 is 

estimated Visibility at all other Basin sites is expected to equal or exceed the 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 3- 7 

Rubidoux visual range. Visual range is expected to double from 2005 due to 

reductions of secondary PM2.5 (by more than one third), direct PM2.5 emissions 

including diesel soot and lower nitrogen dioxide concentrations as a result of 2007 

AQMP controls. 

TABLE V-3-2 

Riverside Extinction Efficiencies, bi

, Defining Alternate Sets of Empirical Predictive 

Equations for Light Extinction 

Visibility-Reducing Alternate Equations1

Species Units 1 2 3 4 

Riverside 

 SULF (10-4 m-1/μg/m3) b1 

 NITR (10-4 m-1/μg/m3) b2 0.070 0.075 

 IONS (10-4 m-1/μg/m3

) b3 0.055 0.058 

 OC (10-4 m-1/μg/m3) b4 0.104 0.089 

 CRBN (10-4 m-1/μg/m3) b5 0.062 0.053 

 EC (10-4 m-1/μg/m3

) b6 0.119 0.119 0.119 0.119 

 NO2 (10-4 m-1/pphm) b7 0.033 0.033 0.033 0.033 

 molecules (10-4 m-1) bRAY 0.114 0.114 0.114 0.114 

TABLE V-3-3 

Current Light Extinction Budgets for Each Alternate Empirical 

Predictive Equation at Each Measurement Location 

(in percent of total light extinction) 

 Alt ______________b sp ______________ 

Location Eq. SULF NITR IONS OC CRBN b

ap

b

ag

bRAY

Riverside 1 0 0 74 11 0 7 3 6 

 2 0 72 0 13 0 7 3 6 

 3 0 0 75 0 11 6 3 5 

 4 0 73 0 0 13 6 2 5 

bsp – backscattering from particulates 

bap– absorption from particulates 

bag – absorption from gases

 

1

 Alternate equations in the set of empirical predictive equations defined for each measurement location. 
 Chapter 3 Federal 24-Hour PM10 Attainment Plan and Visibility Assessment

V -3- 8 

TABLE V-3-4 

Riverside Air Quality Levels for the Years 2005 and 2015 Future Baseline and 

Controlled 

Component Units Baseline Controlled 

2015 

 SULF

1 μg/m3

3.96 3.07 

 NITR

1 μg/m3

9.30 6.63 

 IONS μg/m3 13.27 9.71 

 OC

2 μg/m3

0.26 0.23 

 EC

2 μg/m3

1.73 1.52 

 CRBN μg/m3 2.07 1.82 

 NO2

2 pphm 1.10 0.75 

2020 

 SULF

1 μg/m3

4.24 3.22 

 NITR

1 μg/m3

7.77 4.74 

 IONS μg/m3 12.01 7.96 

 OC

2 μg/m3

0.23 0.25 

 EC

2 μg/m3

1.77 1.53 

 CRBN μg/m3 2.07 1.85 

 NO2

2

 pphm 0.88 0.49 

The predicted future visibilities are consistent with the observed annual average 

visual range in areas influenced by marine air (with the attendant marine haze). 

Without significant air pollution sources, median mid-day visibilities along the 

California coast are generally less than 25 miles (Trijonis, 1980). 

Future Light Extinction Budgets at Riverside

Table V-3-7 compares the baseline and future projected light extinction budgets 

determined from one of the alternate empirical equations for each location to 

illustrate changes in the importance of each pollutant component to overall light 

extinction. These changes result from alterations in the future pollutant mix and in 

the spatial distribution of sources. 
Final 2007 AQMP Appendix V: Modeling and Attainment Demonstrations 

V - 3- 9 

0

5

10

15

20

25

30

2005 2014 2020

Visual Range (Miles)

Baseline Controlled

FIGURE V-3-1 

Annual Average Daytime Visibility Projections at Rubidoux in Miles 

TABLE V-3-5 

Projected Future Visibility, Baseline without Future Controls 

Year Alt. Eq.1 Total Light Extinction 

Coefficient (10-4 m-1) 

Calculated Visual 

Range (miles) 

Baseline 1.7 11.0 

2014 1 1.109 16.8 

 2 1.035 18.0 

 3 1.235 15.1 

 4 1.182 15.8 

2020 1 1.035 18.0 

 2 0.921 20.2 

 3 1.160 16.1 

 4 1.065 17.5 

 

1

 Alternate equations in the set of predictive empirical equations defined for each measurement 

location. 
 Chapter 3 Federal 24-Hour PM10 Attainment Plan and Visibility Assessment

V -3- 10 

TABLE V-3-6 

Projected Future Visibility, With Controls 

Year Alt. Eq. Total Light Extinction 

Coefficient (10-4 m-1) 

Calculated Visual 

Range (miles) 

2014 1 0.874 21.3 

 2 0.808 23.1 

 3 0.979 19.0 

 4 0.930 20.0 

2020 1 0.772 24.1 

 2 0.670 27.8 

 3 0.872 21.4 

 4 0.783 23.8 

TABLE V-3-7 

Comparison of Baseline and Future Projected Light Extinction 

Budgets for Riverside (% contribution) 

Component Baseline Controlled 

2005 2014 2020 2014 2020 

 NITR 66 63 59 57 50 

 OC 15 3 3 3 4 

 EC 9 20 23 22 27 

 NO2 3 4 2 3 2 

 RAY. 7 11 12 14 17 

The light extinction budget for Riverside changes nominally for the future baseline 

emission cases except for the following: (1) nitrate remains the major contributor but 

its contribution decreases; and (2) elemental carbon contributions increase from the 

base year then remain constant through 2021. 

The projected light extinction budgets for the years 2015 and 2021 with the 

controlled emission scenarios continues to show reduced impacts of nitrates to 

visibility but the relative contribution due to elemental carbon increases. 
CHAPTER 4 

REVISION TO THE 2003 OZONE ATTAINMENT 

DEMONSTRATION PLAN 

Introduction 

Modeling Approaches 

Emissions Summary 

Episode Selection 

Base-Year Performance Evaluation 

Ozone Air Quality Projections 

Sensitivity Studies 

Weight of Evidence 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-1

INTRODUCTION 

The Final 2007 AQMP Ozone Attainment Demonstration Plan to meet the federal 8-

hour average standard (84 ppb) is presented in this chapter. The Basin is currently 

designated severe-17 nonattainment for ozone. As mentioned in Chapter 1 of the main 

document, the submittal of the 2003 California Ozone SIP served as the 1-hour ozone 

attainment demonstration for the South Coast Air Basin and those portions of the 

Southeast Desert Modified Nonattainment Area which are under the District’s 

jurisdiction. The attainment demonstrations provided in this Final Plan address the 

current 8-hour federal ozone standard and reflect the updated emissions baseline 

estimates, new technical information, enhanced air quality modeling techniques, and the 

control strategy provided in Chapter 4 of the main document and Appendices IV-A 

through IV-C. 

The modeling Attainment Demonstration serves as a revision to the 1997 and 2003 

ozone Attainment Demonstration Plans (Ozone Plan) submitted to EPA as part of the 

California State Implementation Plan (SIP). The ozone modeling attainment 

demonstration relies on the CAMx modeling system with the SAPRC99 chemical 

mechanism and six modeling episodes. The structure of the standard and the use of 

RRFs differentiate this ozone modeling attainment demonstration from past endeavors. 

The standard is based on the 4th highest annual 8-hour measured ozone concentration 

averaged over a three year period. The variability of meteorological episodes that can 

generate ozone concentrations equivalent to 4th highest in a three year period does not 

lend to a direct deterministic simulated attainment demonstration. As such, EPA’s 

modeling guidance recommends the use of RRFs determined from several simulated 

ozone episodes to assess future year standard attainment. This analysis uses six 

meteorological episodes to draw a representative sample of days when the 8-hour ozone 

standard was exceeded at the set of Basin stations with design values requiring 

attainment demonstrations. 

The meteorological episodes span three years: 2004 and 2005 when the MATES-III 

monitoring program was in effect and primary modeling episode used in the 2003 

AQMP, August 5-6, 1997, which occurred during the 1997 Southern California Ozone 

Study (SCOS97). The 2004 and 2005 episodes occurring during the MATES-III 

sampling program integrate data from the network of radar wind and temperature 

profiles distributed throughout Southern California. In addition, advances in satellite 

data acquisition used in meteorological model initialization since SCOS97 and readily 

available global model output have shifted the focus of regional meteorological 

modeling from diagnostic/objective analysis towards 4-dimensional data assimilation in 

prognostic modeling. Equally important, the 2004-2005 episodes occurred in the post 

California Phase III reformulation period and represent the current VOC emissions 

profile. The 1997 episode is one of several meteorological episodes that were 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-2

intensively monitored through the SCOS97 field program and was included in the 

analysis to provide continuity between the Final 2007 AQMP and 2003 Ozone Plans. 

The base year for the ozone modeling demonstration and emissions inventory 

characterization is 2002. 

This chapter draws heavily from the Draft Modeling Protocol and provides the 

background for the development of the components that contribute to the ozone 

modeling attainment demonstration. (Where necessary, the discussion will refer to the 

Draft Modeling Protocol to avoid duplication). Included are discussions of the modeling 

tools selected for the demonstration, federal and state air quality standard requirements, 

and base and future year emissions. The selection and characterization of 

meteorological episodes and preparation of the ozone simulation model input is provided 

in detail. The analysis also provides the base year model validation and supporting 

statistical and graphical documentation. 

Ozone air quality is projected using CAMx for the following future years: 2017 (for 

impacts to the Coachella Valley portion of the Salton Sea Air Basin), and 2024 (to 

demonstrate attainment of the federal ozone standard in the South Coast Air Basin). 

Additional analyses provide characterization of future year air quality for alternative 

emissions control strategies. 

Model Selection 

The CAA requires that ozone nonattainment areas designated as serious and above use a 

photochemical grid model to demonstrate attainment. During the development of the 

2003 Plan, the District convened a panel of seven experts to independently review the 

regional air quality modeling conducted for ozone and PM10. The consensus of the 

panel was for the District to move to the more current state-of-the-art dispersion 

platforms and chemistry modules. EPA (CRF 51, Appendix W) does not recommend a 

specific modeling dispersion platform or chemistry package to be used in an ozone 

attainment demonstration but provides guidance in the selection process. The 

comprehensive reviews of the peers are provided as attachments to the 2003 AQMP, 

Appendix V and a summary of the panel recommendations is presented in Chapter 1 of 

the 2003 AQMP. 

The model selected for the Final 2007 AQMP attainment demonstrations is the 

Comprehensive Air Quality Model with Extensions (CAMx), version 4.4 [Environ, 

2006], using SAPRC99 chemistry (Carter, 2000). Moreover, this model and chemistry 

package is consistent with the previous advice of the outside peer reviewers. CAMx is a 

state-of-the-art air quality model that can simulate ozone and PM2.5 concentrations 

together in a “one-atmosphere” approach for the attainment demonstrations. CAMx is 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-3

designed to integrate the output from both prognostic and diagnostic meteorological 

models. 

The meteorological modeling platform selected for the modeling attainment 

demonstrations is the mesoscale meteorological model MM5. MM5 is a hydrostatic 

model system that can be run as a prognostic meteorological model or run in a historical 

mode with the option for 4-dimensional data assimilation. MM5 is widely used through 

the country by governmental agencies (the National Weather Service NWS), EPA, the 

military, and numerous state and local air quality agencies) as well as most if not all 

universities supporting a meteorology program. The MM5 layer structure, portability for 

including different mixing and cloud parameterization schemes and grid specification 

makes the model the ideal choice to couple with CAMx. One desirable aspect of the 

CAMx-MM5 system is mass consistency. The Draft Modeling Protocol provides and 

extended discussion on MM5 and the CAMx dispersion modeling platforms. 

Modeling Approach 

The Final 2007 AQMP modeling approach for the 8-hour average federal standard 

attainment demonstration involves a series of steps which incorporate the simulations of 

multiple air quality episodes for three emissions scenarios to develop a set of site 

specific RRFs to be applied to the Basin design values. The sequence of the modeling 

approach first relies on determining the base-year episode simulation performance using 

day specific base-year emissions inventories in 2004 or 2005. Sub regional and site 

specific performance statistics a for the Basin (and downwind receptor sites) are 

evaluated to determine (1) if the simulation is reasonably recreating the sub-regional 

observed ozone patterns and (2) if the simulation is able to produce concentrations of 

ozone within an acceptable concentration range. Station and day specific simulations 

that meet both criterions are used to develop the RFFs. (A more detailed discussion of 

the criterion is presented in the model performance evaluation section of this Appendix). 

The second phase of the analysis involves simulating the meteorological episodes for 

two additional day-specific emissions scenarios: 2002, the base year for the RRF 

calculation and, 2023 with emissions control measures fully implemented. (Note: For 

the Coachella Valley portion of the Salton Sea Air Basin (SSAB), the future year 

simulation is based on the controlled 2017 day-specific inventory.) Simulated 

concentrations for the base year and future year controlled emissions scenario are 

generated to establish site specific RRFs. 

The final phase is the attainment demonstration where the site specific RRFs are applied 

to the 2002 weighted station design values to determine the future year design 

concentrations. 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-4

Table V-4-1 provides the weighted 2002 design values for the Basin. Table V-4-2 

provides the 2002 design values for the Coachella Valley-SSAB air monitoring stations 

and downwind transport stations in the SCCAB and MDAB. EPA guidance 

recommends the use of a 5-year weighted design values to minimize the impacts of year 

to-year variations in weather and short term emissions trends. In Tables V-4-1 and V-4-

2, the sites exceeding the 8-hour federal standard are delineated through bold lettering. 

These stations are the focus of the analysis. 

Federal 8-Hour Ozone Standard Requirements 

Air quality modeling is required by both the federal Clean Air Act (CAA) and the 

California Clean Air Act (CCAA). Section 182(b)(1)(A) of CAA requires that moderate 

and above ozone nonattainment areas must reduce volatile organic compounds (VOC) 

and oxides of nitrogen (NOx) emissions sufficiently to attain the national ambient air 

quality standard for ozone and an attainment demonstration must be performed using 

photochemical grid modeling. According to Section 181(a)(1) of the CAA, ozone 

nonattainment areas are classified and given an attainment deadline based on their 

design values. Within the jurisdiction of the District are the South Coast Air Basin 

(Basin) and the Coachella Valley of the Salton Sea Air Basin (see Figure V-4-1). The 

District is seeking voluntary redesignations for the Basin and Coachella Valley. The 

Basin is requesting to move from a “severe-17” ozone nonattainment area to “extreme” 

nonattainment area to make available long term control measures and to extend the 

attainment date to June 15, 2024. The attainment demonstration for the Basin is the 

primary subject of this chapter. The Coachella valley is also seeking to be reclassified as 

“severe-15” nonattainment for ozone and therefore extend its attainment deadline to June 

15, 2018. 

The modeling domain used in the photochemical modeling analysis, also shown in 

Figure V-4-1, encompasses the entire Basin, Ventura County, Antelope Valley 

(AVAQMD), San Diego County, the Coachella Valley, and portions of the Mojave 

Desert Air Quality Management District (MDAQMD) and Imperial County. Ventura 

County, the Antelope Valley and Mojave Desert are classified as "moderate" (attainment 

year: 2010). These areas experience pollutant transport from the Basin, and at times are 

an upwind source of pollution. San Diego County is classified as “basic” with an 

attainment year of 2009 and Imperial County is classified as “marginal” with an 

attainment year of (2007). 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-5

TABLE V-4-1 

8-Hour Average South Coast Air Basin Weighted Design Values 

City 2002 

Design 

2003 

Design 

2004 

Design 

Weighted 

Design 

Value 

 

Azusa 102 101 98 100 

Burbank 92 91 92 91 

Long Beach 62 61 64 62 

Reseda 94 107 110 103 

Pomona 89 96 101 95 

Lynwood 51 53 57 54 

Pico Rivera 80 79 78 79 

Los Angeles 79 78 79 79 

Pasadena 96 95 96 96 

Santa Clarita 113 127 125 124 

West Los Angeles 69 73 77 73 

Hawthorne 68 70 63 67 

Glendora 111 114 109 111 

Anaheim 70 72 79 72 

La Habra 76 75 75 75 

Costa Mesa 67 71 73 70 

Mission Viejo 79 83 87 84 

Rubidioux 108 113 113 111 

Perris 113 115 106 111 

Lake Elsinore 104 109 106 106 

Banning Airport 110 119 117 115 

Upland 111 110 107 111 

Crestline 129 131 128 129 

Fontana 112 123 119 118 

San Bernardino 115 119 113 115 

Redlands 120 128 124 124 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-6

TABLE V-4-2 

8-Hour Average Weighted Design Values: Salton Sea Air Basin (SSAB), Mojave Desert 

Air Basin (MDAB) and the South Central Coast Air Basin (SCCAB) 

City 2002 

Design 

2003 

Design 

2004 

Design 

Weighted 

Design 

Value 

 

SSAB 

Palm Springs 107 111 106 106 

Indio 95 99 99 95 

 

MDAB 

Lancaster 71 82 100 84 

Phelan 103 106 105 105 

Twenty-nine 

Palms 

88 86 86 87 

Hesperia 106 106 107 106 

Joshua Tree 94 99 106 100 

Barstow 87 88 87 87 

Trona 80 83 86 83 

Victorville 97 100 98 98 

 

SCCAB 

Ojai 95 95 94 95 

El Rio 66 66 66 66 

Piru 73 90 88 84 

Simi 97 95 92 95 

Thousand Oaks 81 83 84 83 

Emma Woods 69 71 69 70 

California Requirements and Population Exposure 

The CCAA requires the District to demonstrate reasonable progress towards achieving 

state ambient air quality standards in the Basin. To date, the Basin has not met the 

California 1-hour ozone standard (90 ppb). Yet, ambient ozone air quality has greatly 

improved. The CCAA requires per-capita exposure reductions for the years 1994, 1997, 

and 2000, as compared to a 1986-88 base period. Overall per-capita exposure to 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-7

ambient ozone must be reduced in accordance with the following schedule: 25 percent 

by 1994, 40 percent by 1997, and 50 percent by 2000. 

Reductions are to be calculated based on per-capita exposure and the severity of 

exceedances. For the Basin, this provision is applicable to ozone [H&S Code 40920(c)]. 

The definition of exposure is the number of persons exposed to a specific pollutant 

concentration level above the state standard times the number of hours exposed. The 

per-capita exposure is the population exposure (units of pphm-persons-hours) divided by 

the total population. While this requirement has already been met in previous AQMPs 

(Appendix V, 2003 AQMP), the exposure demonstration is extended through 2005 in 

the Final 2007 AQMP for consistency. 

The Regional Human Exposure (REHEX) model is used to estimate per-capita exposure 

reduction. It considers population mobility; time spent indoors, outdoors and in transit; 

exposure by age classification; and activity pattern by season and weekday/weekend. 

An analysis using the REHEX model indicates that the CCAA Amendments exposure 

reduction targets have been achieved for ozone with a margin of safety. Figure V-4-2 

summarizes the results and compares exposure reductions to the targets. 

.

San Luis

Obispo Co.

Santa

Barbara Co.

Kern Co.

Ventura

Co.

Orange

 Co.

Imperial

Co.

Los

Angeles Co.

Riverside Co.

San Diego

Co.

San

Bernardino

Co.

Northern Mexico

FIGURE V-4-1 

Southern California Modeling Domain Used in the Ozone Attainment Demonstration 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-8

0%

20%

40%

60%

80%

100%

120%

1997 2000 2005

Year

Percent Reduction

CCA Requirements REHEX

FIGURE V-4-2 

CAAA Population Exposure Assessment: Percent Reductions in Annual Average PerCapita Exposure to Ozone 

EMISSIONS SUMMARY 

Introduction 

There are specific emission inventories developed for the photochemical modeling. The 

summer planning emission inventories developed for the historical years (1997, 2004 

and 2005) and future planning years (baseline and controlled) are described in Appendix 

III. Baseline modeling inventories for the historical years (1997, 2004 and 2005) and the 

future years (2009, 2017, and 2023) are discussed next. Two emission projections are 

needed for each of the modeled future years. The first is the projected emissions 

assuming no further emission controls. These projections are commonly referred to as 

“baseline emissions” (e.g., 2023 baseline emissions), and reflect the emissions resulting 

from increases in population and vehicle miles traveled (VMT), as well as the 

implementation of all adopted rules and regulations up through 2005. The second 

emission projections reflect the implementation of the Final 2007 AQMP control 

Air Quality

Improvement 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-9

measures on the future baseline emissions. For a detailed description of the Final 2007 

AQMP control measures, the reader is referred to the main volume and Appendix IV. 

The July 2005 historical year emissions are summarized as representative ozone 

episodes used for attainment demonstration. This is followed by a discussion of the 

future-year (July 2005 episode) emission inventory, assuming implementation of 

proposed control measures, are presented. Appendix III contains emission summary 

reports by source category for the historical base year, future baseline, and future 

controlled scenarios used in this modeling analysis. Attachments 5, 6 and 7 of this 

appendix contain the Controlled Emission Projection Algorithm (CEPA) emissions 

summary report by source category for the future (2014, 2017 and 2023) controlled 

scenarios for the annual average inventory. 

It should be noted that the inventories reported here may be slightly different than those 

reported in the Final 2007 AQMP and Appendix III, since the inventories used for 

modeling reflect day-specific conditions. Day specific point, mobile and area emissions 

inventories were generated for each meteorological episode. Mobile source emissions 

were temperature corrected by grid using a VMT weighted scheme. County-wide area 

source emissions were temperature corrected and gridded using the spatial emissions 

surrogate profiles developed for the 2003 AQMP. 

Historical Baseline Emissions 

Historical baseline emissions of oxides of nitrogen (NOx) and volatile organic gases 

(VOC) and carbon monoxide (CO) are summarized in Table V-4-3 for the July 2005 

meteorological episode. The day-specific July 2005 episode emissions inventory is 

representative of the remaining meteorological episodes. Variations in the temperature 

and humidity profiles among the episode days and between episodes contribute to 

variations in the weekday emissions totals of less than 50 tons/day or 5 percent. The 

summaries of biogenic, on-road mobile and total antropogenic emissions for the July 

2005 are reported for the Basin and the modeling region. 

Emissions for the July episode span the weekend where significant reductions in on-road 

NOx and increases in VOC from off road activities occur. Based on CALTRANS data, 

NOx emissions from heavy-duty vehicles are reduced by more than 60 percent on 

Saturdays with further reductions occurring on Sundays. Increases in off-road mobile 

source activities (e.g. pleasure craft and recreational vehicles) account for the bulk of the 

VOC increase on both Saturdays and Sundays. 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-10

Future Controlled Emissions 

The control factors developed from CEPA were applied to the future base year emissions 

to calculate the controlled emission inventories. The future-year baseline emission 

inventories estimation reflect the emissions resulting from increases in population and 

vehicle miles traveled (VMT), as well as the implementation of all rules and regulations 

adopted as of December 31, 2005. VOC and NOx baseline emissions decrease from the 

historical base year through the year 2023. This decreasing trend in emissions reflects 

the implementation of current state and local air quality rules and regulations. 

TABLE V-4-3 

South Coast Air Basin July 2005 Historical Episode Emissions (tons/day) 

 Date Emission Category 2005

 CO NOX VOC 

Thursday 14-Jul-05 Biogenic 233 

 On-Road 2870 466 368 

 Total Anthropogenic 3911 895 825 

Friday 15-Jul-05 Biogenic 200 

 On-Road 2823 451 350 

 Total Anthropogenic 3864 880 807 

Saturday 16-Jul-05 Biogenic 209 

 On-Road 2286 314 314 

 Total Anthropogenic 4397 706 925 

Sunday 17-Jul-05 Biogenic 224 

 On-Road 2177 280 309 

 Total Anthropogenic 4286 670 895 

Monday 18-Jul-05 Biogenic 245 

 On-Road 2715 433 350 

 Total Anthropogenic 3756 862 806 

Tuesday 19-Jul-05 Biogenic 245 

 On-Road 2905 445 372 

 Total Anthropogenic 3946 873 829 

Base year 2002, 2017, and 2023 and future-year controlled emissions, estimated from 

the baseline emissions using the CEPA control factors for the simulations, are given in 

Table V-4-4. 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-11

TABLE V-4-4 

2002, 2017, 2023 Base Year and 2023 Future Year Controlled Emissions Scenarios (TPD)

Year Scenario VOC NOx CO 

2002 Baseline 1030 1090 5525 

2017 Baseline 509 581 2368 

2017 Controlled 444 380 2283 

2023 Baseline 496 515 2058 

2023 Controlled without 

Long- Term Measures 

402 317 2058 

2023 Controlled with LongTerm Measures 420 114 1966 

EPISODE SELECTION 

The 2003 AQMP benefited from the intensive monitoring conducted under the Southern 

California Ozone Study where the August 4-7, 1997 episode was the cornerstone of the 

modeling analysis. The requirements for multiple episode days at individual stations 

pose a different challenge for the Final 2007 AQMP. 

Five additional meteorological episodes with regionally observed higher ozone 

concentrations were added to the 2003 AQMP modeling episode. The five episodes 

observed in 2004 and 2005 occurred during MATES-III, a period of enhanced air quality 

monitoring in the Basin. Supporting MATES-III, the District operated three radar wind 

profilers in the Basin, with radio acoustic sounders. Additional profiler data was 

obtained from operating sites in Ventura and San Diego Counties. Table V-4-5 lists the 

complement of meteorological episodes used in the ozone attainment demonstration. 

Selection of episodes from 2004 and 2005 was also made to avoid the commingling 

associated with the Phase III California Fuel Reformulation where the primary 

oxygenate was changed from MTBE to ethanol. Commingling of ethanol and nonethanol based fuels leads to enhanced evaporative VOC emissions and thus more ozone. 

Quantification of the amount of commingling taking place on a daily or episodic basis 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-12

was nearly impossible. Implementation of the fuel switch from MTBE to ethanol took 

place in California during 2003 and was assumed to be completed by December 31, 

2003. Selecting meteorological episodes for the post 2003 emissions reduced the 

uncertainty associated with the estimation of the VOC emissions inventory due to 

commingling. 

Conceptual Model of an 8-Hour Ozone Episode 

Several field studies (SCAQS, [1987], and SCOS97, [1998]) and previous AQMPs have 

described at length the development of an ozone episode in the Basin. The focus of 

many of these analyses was to simulate the observed 1-hour maximum concentration in 

the modeling domain. Cassmassi (1998) used Classification and Regression Tree 

analysis (CART) to determine whether the conceptual model for a 1-hour ozone episode 

differed from the meteorological profile characterizing an 8-hour average ozone episode 

in the Basin. The results of the analysis indicated that the peak 1-hour episodes were a 

subset of the 8-hour episodes and the meteorological profiles contributing to both 

scenarios were nearly identical. As such, the development of the 8-hour conceptual 

model for the Basin and the methodology to select and characterize episodes relies on 

the basic models constructed to describe the Basin 1-hour ozone episode. 

The Draft Modeling Protocol provides an extended discussion of the meteorological and 

air quality profile of four of the five 2004 and 2005 episodes, in addition to the August 

1997 episode, selected for evaluation in the ozone attainment demonstration. The 

August 2-9, 2005 meteorological episode was selected as a replacement for the June 

2004 episode after the release of the Draft Modeling Protocol. In general, elevated 

concentrations of ozone (both 1- and 8-hour average) occur under a west coast or Four 

Corners ridge of high pressure aloft. Typically, the 500 mb pressure surface heights 

above mean sea level (msl) exceed 5880 m and generate a strong low level subsidence 

inversion (10o

 C in strength or higher). The surface pressure gradient (i.e. wind forcing) 

typically is less than 5 mb between the coast and the desert (approximately 200 km in 

distance) and days often begin with a deck of morning coastal stratus that extends into 

the near valleys then burns off in the late morning hours. The more severe episodes tend 

to have neutral to slightly off shore pressure gradient forcing and clear skies. 

Each of the 2004 and 2005 meteorological episodes selected for the ozone attainment 

demonstration fit this model. Figure V-4-3 illustrates the 500 mb upper air structure 

over the west coast during the July 2005 meteorological episode. Figure V-4-4 provides 

the 1200 UTC (4:00 am PST) temperature profile for July 16, 2005. 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-13

FIGURE V-4-3 

500 mb Upper Air Structure: July 2005 Meteorological Episode 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-14

FIGURE V-4-4 

1200 UTC Upper Air Sounding at Miramar MCAS (San Diego, CA) July 16, 2005 

Statistical Episode Characterization and Ranking 

CAMx simulations were generated for six meteorological episodes including two 

periods in 2004, three periods in 2005 and one in 1997. Table V-4-5 characterizes the 

selected episodes two ways: first by an assessment of the meteorological profile using a 

statistical model to rank the episodes based on meteorological stagnation potential and 

second by comparing observed maximum ozone concentrations to the annual design 

values. 

The meteorological classification is based on an empirical analysis presented in the 2003 

AQMP which provides both a stagnation severity rank (1 being the highest) and the 

percentile the meteorological episode had in a 22-year distribution. The observed 

maximum 8-hour average concentrations on each episode day, and the average of the 8-
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-15

hour maximum concentrations observed for each multi-day episode are also provided for 

comparison to the annual 4th highest 8-hour average ozone value observed in the year 

that the episode takes place. 

Briefly, the selected episode days mostly rank in the 95th percentile or higher for 

meteorological stagnation potential. The episode average of the 8-hour maximum 

concentrations is within 5 ppb of the annual 4th highest 8-hour observed concentration 

for four of the six simulation periods. 

Model Input Preparation 

The procedures for CAMx input file preparation are presented in this section. Unlike 

previous AQMPs which relied on the use of UAM for the attainment demonstration, 

CAMX is designed to marry seamlessly with the MM5 model output. The 

meteorological modeling domain, NCEP initializations and vertical dispersion schemes 

are evaluated in the modeling are provided in the Modeling Protocol Document. 

Statistical meteorological model evaluation was conducted using METSTAT software 

package (Environ, Inc., 2005) and by Aerospace Corporation (McAtee, et al., 2006). 

Data evaluation compared MM5 predictions vs. observational data at selected 

meteorological monitoring sites from the SCAQMD, NWS, FAA, CIMIS and other air 

quality agencies networks. A summary of the meteorological model performance was 

presented at the 2006 National Air Quality Conference in San Antonio, Texas. The 

meteorological modeling was also presented to and critiqued by AQMP Scientific, 

Technical, Modeling and Peer Review (STMPR) Advisory group monthly meetings 

from December 2005 through September, 2006. 

As previously stated, the CAMx ozone simulations were run on a 5 km squared grid 

using a Lambert Conformal projection of the SCOS97 modeling domain depicted in 

Figure V-4-1. The modeling analyses were run using 16 vertical layers up to 5000 m 

above ground level. The eastern extent of the domain is approximately 100 miles 

offshore of the Basin. The large domain was chosen to minimize uncertainties in the 

upwind boundary conditions. 

The meteorological fields used for the CAMx ozone simulations were generated using 

MM5 with the FDDA option. The meteorological fields were developed using a 

Lambert Conformal grid that roughly overlaid the SCOS97 modeling domain. MM5 

was simulated using 34 vertical layers and simulations were initialized using NCEP 

global weather forecast model analysis. The MM5 fields were post processed to layer 

averaged winds to the levels defined for the CAMx simulations and to adjust coordinates 

to the UTM system. 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-16

TABLE V-4-5 

Ozone Meteorological Episodes Used for the Ozone Attainment Demonstration 

Ranking Applied to Historical 22-Year Period (1981-2002) 

Episode Stagnation 

Severity 

Rank 

Percentile 8-Hour 

Maximum 

Ozone 

(ppb) 

Episode 

Average 

8-Hour 

Maximum 

Ozone 

(ppb) 

Annual 4th Highest 

Observed 

8-Hour Maximum 

Ozone /Station 

(ppb) 

8/4/1997 570 93 110 

8/5/1997 198 98 124 

8/6/1997 203 97 130 

8/7/1997 515 95 130 

124 127 

San Bernardino 

8/7/2004 331 96 127 

8/8/2004 144 98 122 

125 116 

Crestline 

5/21/2005 389 95 112 

5/22/2005 50 99 145 

129 

7/15/2005 265 96 143 

7/16/2005 22 99 141 

7/17/2005 15 99 141 

7/18/2005 73 99 127 

7/19/2005 567 93 110 

132 

8/4/2005 270 97 108 

8/5/2005 399 95 110 

8/6/2005 288 96 119 

8/7/2005 341 96 114 

113 

8/27/2005 160 98 130 

8/28/2005 138 98 121 

126 

125 

Crestline 

Selected objective-hybrid MM5 wind fields were evaluated in the development of the 

modeling episodes to test transport to the northern portion of Los Angeles Country and 

Santa Clarita. The hybrid approach was not used in the ozone attainment demonstration. 

Table V-4-6 summarizes some of the critical components of the air quality modeling 

system. Of the components listed, treatment of the boundary conditions is the subject of 

discussion in the following section. 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-17

TABLE V-4-6 

Air Quality Modeling System Configuration 

Component Source 

Initial Conditions/Boundary Conditions Extracted from WRAP Regional Haze Modeling 

output 

Meteorological Fields MM5/FDDA with NCEP initialization 

Eta PBL – Mellor-Yamada scheme as used in 

the Eta model, Janjic (1990, MWR) and Janjic (1994, 

MWR). It predicts TKE and has local vertical mixing. 

 

Horizontal Advection Solver Piecewise Parabolic Method (PPM) of Colella and 

Woodward (1984), high order accuracy and little 

numerical diffusion 

Vertical Mixing/Diffusivity MM5 CAMx Option OB70 w/Kv Patch. Minimum 

vertical diffusivity set at 1 m2

/sec. 

Chemistry (SAPRC99) CAMx Version 4.4 Beta. Version modified to treat 

ETOH, MTBE and MBUT explicitly (Environ, 

2006) 

Chemistry Solver Chemical Mechanism Compiler (CMC), fast highly 

efficient solver based on an “adaptive-hybrid” 

approach compared to the standard chemistry solver 

for the CB-IV mechanism 

SAPRC99 Mechanism ID=5 The fixed parameter version of the SAPRC99 

mechanism (Carter, 2000). 211 reactions and 74 

species (56 state gasses and 18 radicals) 

Dry Deposition of Gases Resistance model developed by Wesely (1989) 

Boundary and Top Air Quality Concentrations 

The boundary concentrations can have a marked impact on RRFs for the South Coast 

Air Basin. In the Draft 2007 AQMP (released in October 2006) boundary conditions for 

the ozone simulations were extracted from the annual WRAP Regional Haze modeling 

conducted for the model year 2002 (Tonneson 2005). This modeling was conducted 

using CB4 chemical mechanism. There are some uncertainties on conversion from CB4 

to SAPRC species. In addition, the converted SAPRC99 species profile did not reflect 

emissions inventory SAPRC99 species composition. The WRAP modeling results 

included occasional high levels of VOC and NOX that may not represent existing 

boundary concentrations. 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-18

For the Final 2007 AQMP, the ozone simulations were conducted using the EPA default 

boundary concentration profile USEPA (1991). Uncertainties identified in the episodic 

diurnal profiles for the ozone simulations were sufficiently large enough to warrant a 

return to the boundary conditions used in the 2003 AQMP ozone attainment 

demonstration. This profile is commonly referred to as the “EPA-Clean” boundary. The 

boundary conditions were adjusted to match the ROG SAPRC profile. 

Table V-4-7 summarizes the boundary conditions used for all simulations. All 

concentrations were constant horizontally and, except for NO2, constant vertically. For 

each profile, the sum of VOC concentrations is approximately 22 ppbC. For each 

simulation, the domain top boundary concentrations were the same as the lateral 

boundaries, with the exception that the top ozone concentration was 60 ppb. 

The initial concentrations for the all episodes were set using the air quality data from the 

District and neighboring district’s air monitoring stations. 

TABLE V-4-7

Boundary Profile Concentrations (ppb) for the SCOS Modeling Domain. 

SAPRC99 Species (ppb) SAPRC99 Species (ppb) 

HCHO 0.930 ARO1 0.210 

CCHO 0.530 ARO2 0.070 

RCHO 0.250 OLE1 0.180 

ISOP 0.020 OLE2 e-13 

MEOH 0.100 

ETOH 0.050 O3 40.0 

ETHE 0.180 CO 200. 

ALK1 2.500 

ALK2 2.300 NO 0.100 

ALK3 0.930 NO2 (surf) 2.000 

ALK4 e-13 NO2 (aloft) 0.100 

ALK5 e-13 

Future Boundary, Top and Initial Air Quality Conditions 

For the future year scenarios, the boundary, region top and ambient air quality 

concentrations were rolled back based on the percentage reduction in emissions from 

2002 base year to the projected emissions levels for future year of the simulation (2017, 

or 2023).
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-19

The future year the top ozone concentrations were reduced to 45 ppb. The lateral 

boundary concentrations were not rolled back since the boundary concentrations used 

base year is considered to be clean. 

Meteorological Models 

The MM5 meteorological model using 4-dimensional data assimilation (4DDA) was the 

primary tool used to develop the meteorological fields. The Modeling Protocol provides 

characterization of the nested MM5 modeling domains, the layer structure and 

initialization assumptions. Three-dimensional wind, temperature and mixing height 

fields were extracted from the MM5 simulations and post processed using CALMET to 

layer average variables to the CAMx structure. Vertical mixing was calculated using the 

ETA planetary boundary layer (PBL) scheme and a minimum value of vertical 

diffusivity was set at 1.0 m2

/sec. 

The MM5 data fields were extensively analyzed using the METSAT software. Figure 

V-4-5 illustrates the extent of surface meteorological measurements in southern 

California, and the data used in the meteorological model evaluation were derived from 

a subset of the total archive. The summary performance statistics for the July 2005 

episode are presented in Table V-4-8 and Figures V-5-6 through V-4-8. (The 

performance of MM5 for the July 2005 episode was characteristic of that of the 

remaining five episodes). 

As previously stated, an assessment of the meteorological model performance was 

presented at EPA’s 2006 National Air Quality Conference and periodically during the 

development of the ozone modeling episodes at the STMPR Advisory group. The data 

has also been provided to the independent Peer Reviewers, and their evaluation is 

pending. 

150 250 350 450 550 650

UTM Easting

3600

3700

3800

3900

UTM Northing

FIGURE V-4-5 

Locations of Surface Monitoring Used in Preparation of Meteorological Fields
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-20

TABLE V-4-8 

METSTAT Statistical Evaluation of MM5-4DDA for the July 2005 Episode: 

AQMD Air Monitoring Stations 

Variable Statistric Units 7/14 7/15 7/16 7/17 7/18 7/19 

Wind Speed Mean OBS (m/s) 1.62 1.7 1.78 1.93 1.72 1.76 

Wind Speed Mean PRD (m/s) 1.85 1.78 1.76 1.89 1.84 1.91 

Wind Speed Bias (m/s) 0.23 0.04 -0.01 -0.03 0.13 0.15 

Wind Speed Gross Error (m/s) 0.96 0.88 0.89 0.91 0.83 1 

Wind Speed RMSE (m/s) 1.27 1.18 1.12 1.17 1.08 1.37 

Wind Speed Sys RMSE (m/s) 0.82 0.75 0.78 0.75 0.69 0.96 

Wind Speed Unsys RMSE (m/s) 0.96 0.91 0.81 0.9 0.83 0.97 

Wind Speed IOA 0.68 0.72 0.75 0.81 0.79 0.68 

Wind Direction Mean OBS (deg) 227.83 220.61 235.33 252.18 237.75 209.55 

Wind Direction Mean PRD (deg) 240.19 226.58 232.84 241.36 247.27 221.05 

Wind Direction Bias (deg) 8.76 4.48 7.5 4.85 17.25 11.71 

Wind Direction Gross Error (deg) 53.93 48.06 45.51 46.29 50.39 56.66 

Temperature Mean OBS (K) 300.38 298.73 298.88 299.53 300.25 301.27 

Temperature Mean PRD (K) 299.98 298.66 298.53 298.63 299.4 299.75 

Temperature Bias (K) -0.06 0.23 0.06 -0.58 -0.46 -1.21 

Temperature Gross Error (K) 2.59 2.37 2.22 2.59 2.62 2.6 

Temperature RMSE (K) 3.37 3.29 3.25 3.76 3.93 3.55 

Temperature Sys RMSE (K) 2.37 1.84 2.21 2.63 2.58 2.5 

Temperature Unsys RMSE (K) 2.4 2.73 2.39 2.68 2.96 2.51 

Temperature IOA 0.92 0.92 0.93 0.92 0.91 0.91 

Humdity Mean OBS (g/kg) 11.5 12.2 12.31 12.19 12.92 13.91 

Humdity Mean PRD (g/kg) 11.74 12.55 12.48 12.47 12.53 13.2 

Humdity Bias (g/kg) -0.17 0.39 0.19 0.34 -0.42 -0.74 

Humdity Gross Error (g/kg) 2.69 2.14 1.91 1.97 1.87 1.96 

Humdity RMSE (g/kg) 3.57 3.04 2.72 2.85 2.64 2.83 

Humdity Sys RMSE (g/kg) 2.05 2.42 1.99 2.57 1.63 1.98 

Humdity Unsys RMSE (g/kg) 2.93 1.83 1.85 1.24 2.07 2.03 

Humdity IOA 0.58 0.5 0.56 0.45 0.52 0.52 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-21

Observed/Predicted Windspeed

1.4

1.5

1.6

1.7

1.8

1.9

2

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

m/s

Wind Spd Mean OBS Wind Spd Mean PRD

Bias/Gross Error Windspeed

-0.2

0

0.2

0.4

0.6

0.8

1

1.2

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

m/s

Wind Spd Bias Wind Spd Gross Error

RMSE Windspeed

0

0.5

1

1.5

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

m/s

Wind Spd RMSE Wind Spd Sys RMSE Wind Spd Unsys RMSE

IOA Windspeed

0

0.2

0.4

0.6

0.8

1

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

Wind Spd IOA

Observed/Predicted Wind Direction

0

6 0

12 0

18 0

240

300

360

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

deg

Wind Dir Mean OBS Wind Dir Mean PRD

Bias/Gross Error Wind Direction

-90

-60

-30

0

3 0

6 0

9 0

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

deg

Wind Dir Bias Wind Dir Gross Error

Figure V-4-6 

METSAT Evaluation of MM5 Winds vs. AQMD Station Data: July 2005 Episode 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-22

Observed/Predicted Temperature

297

297.5

298

298.5

299

299.5

300

300.5

301

3 0 1.5

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

K

Temprt r Mean OBS Temprt r Mean PRD

Bias/Gross Error Temperature

- 1.5

- 1

-0.5

0

0.5

1

1.5

2

2.5

3

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

K

Temprt r Bias Temprt r Gross Error

RMSE Temperature

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

K

Temprt r RMSE Temprt r Sys RMSE Temprt r Unsys RMSE

IOA Temperature

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

Temprt r IOA

Figure V-4-7 

METSAT Evaluation of MM5 Temperature vs. AQMD Station Data: July 2005 Episode 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-23

Observed/Predicted Humidity

0

2

4

6

8

10

12

14

16

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

g/kg

Humdit y Mean OBS Humdit y Mean PRD

Bias/Gross Error Humidity

- 1

-0.5

0

0.5

1

1.5

2

2.5

3

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

g/kg

Humdit y Bias Humdit y Gross Error

RMSE Humidity

0

0.5

1

1.5

2

2.5

3

3.5

4

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

g/kg

Humdit y RMSE Humdit y Sys RMSE Humdit y Unsys RMSE

IOA Humidity

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

 7/ 14 7/ 15 7/ 16 7/ 17 7/ 18 7/ 19 

Humdit y IOA

Figure V-4-8 

METSAT Evaluation of MM5 Winds vs. AQMD Station Data: July 2005 Episode 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-24

BASE-YEAR PERFOMANCE EVALUATION 

For the CAMx performance evaluation the modeling domain is separated into nine subregions or zones. Figure V-4-9 depicts the sub-regional zones used for base-year 

simulation performance. The different zones present unique air quality profiles. In 

previous ozone modeling attainment demonstrations using a smaller modeling domain, 

the number and size of the zones was different. Seven zones represented the Basin and 

portions of Ventura County, the Mojave Desert and the Coachella Valley. 

For the current analysis the Basin is represented by three of the zones: Zone 3 – the San 

Fernando Valley, Zone 4 – the Eastern San Gabriel, Riverside and San Bernardino 

Valleys, and Zone 5 – the Los Angeles and Orange County emissions source areas. Of 

the four areas, Zone 4 represents the Basin maximum ozone concentrations and the 

primary downwind impact zone. As such, the priority in evaluating model performance 

is focus on Zone 4. 

 

FIGURE V-4-9 

Performance Evaluation Zones 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-25

Statistical Evaluation 

The statistics used to evaluate 1-hour average CAMx ozone performance do not change 

from previous AQMPs and include the following: 

Statistic for O3 Criteria (%) Comparison Basis

Normalized Gross Bias ≤ ±15 Paired in space and time 

Normalized Gross Error ≤ 35 Paired in space (+2 grid 

cells) and time 

Peak Prediction Accuracy ≤ ± 20 Unpaired in space and time 

The same statistics are applied to the 8-hour average ozone. 

The base-year 1- and 8-hour average regional model performance for the August 2004, 

May 2005, July 2005, August 2005 (2-episodes) and August 1997 episodes for Zones 3, 

4, and 5 are presented in Tables V-4-9 to V-4-14. Base-year performance statistics for 

Zones 2, 8 and 9 for the downwind areas are provided in the Attachment B performance 

summary evaluation tables. Performance statistics are presented for observed 

concentrations of 60 ppb or greater. Data for 1 and 8-hour average ozone concentrations 

for the sub regional peak concentrations are provide in the tables. Base-year station 

statistics for all of the ozone episodes are presented in Attachment B. 

Performance statistics for the ozone precursors, nitrogen dioxide, nitric oxide and carbon 

monoxide will be provided separately. 

The CAMx ozone simulations generally met the 1-hour average unpaired peak model 

performance goal in all three zones on most days. Nearly all stations in zone 4 met the 

unpaired peak and normalized error goals with performance in zones 3 and 5 lagging, 

particularly for the May 2005 episode. In general, the bias tends to be negative 

indicating that model performance tended to under predict ozone concentrations. 

Overall, the 8-hour average evaluation was slightly better. 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-26

TABLE V-4-9 

CAMx Sub-Region-3 1-Hour Average Ozone Performance Statistics 

Ozone Threshold (60 PPB) August 2004 May 2005 July 2005Date 8/7 8/8 5/21 5/22 7/15 7/16 7/17 7/18 Julian Date 220 221 141 142 196 197 198 199 Ratio of Predicted Sub-Regional Peak to Peak Observed 

1.15 1.09 0.97 0.68 1.40 0.85 0.95 0.70 

Ratio of Unpaired Station Peaks 0.84 0.80 0.67 0.54 1.24 0.72 0.74 0.50 Normalized Systematic Bias (%) -20 -12 -32 -46 9 -3 -16 -36 Normalized Gross Error (%) 23 17 32 46 14 17 23 36 Ozone Threshold (60 PPB) August 2005 August 2005 AugusDate 8/4 8/5 8/6 8/7 8/27 8/28 8/4 8/5 Julian Date 216 217 218 219 239 240 216 217 Ratio of Predicted Sub-Regional Peak to Peak Observed 

0.80 0.92 0.92 0.94 0.87 0.84 1.04 0.91 

Ratio of Unpaired Station Peaks 0.72 0.89 0.91 0.91 0.74 0.67 0.86 0.78 Normalized Systematic Bias (%) -5 -2 4 9 -26 -42 -11 -12 Normalized Gross Error (%) 16 17 21 23 32 42 17 30 
Chapter 4 Revision to the 2003 Ozone Attainmen

V-4-27

TABLE V-4-10 

CAMx Sub-Region-4 1-Hour Average Ozone Performance Statistics 

Ozone Threshold (60 PPB) August 2004 May 2005 July 2005Date 8/7 8/8 5/21 5/22 7/15 7/16 7/17 7/18 Julian Date 220 221 141 142 196 197 198 199 Ratio of Predicted Sub-Regional Peak to Peak Observed 

0.85 1.12 0.90 0.94 0.98 0.94 0.96 1.06 

Ratio of Unpaired Station Peaks 0.82 1.07 0.80 0.92 0.88 0.85 0.92 0.97 Normalized Systematic Bias (%) -13 3 -16 -25 7 -3 2 -8 Normalized Gross Error (%) 15 16 21 29 20 20 16 18 Ozone Threshold (60 PPB) August 2005 August 2005 AugusDate 8/4 8/5 8/6 8/7 8/27 8/28 8/4 8/5 Julian Date 216 217 218 219 239 240 216 217 Ratio of Predicted Sub-Regional Peak to Peak Observed 

1.02 1.01 1.04 1.04 0.56 0.74 1.04 0.79 

Ratio of Unpaired Station Peaks 0.98 1.00 1.00 1.04 0.58 0.69 0.99 0.74 Normalized Systematic Bias (%) 5 3 -9 -4 -29 -28 -6 -4 Normalized Gross Error (%) 17 24 20 20 34 33 19 17 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-28

TABLE V-4-11 

CAMx Sub-Region-5 1-Hour Average Ozone Performance Statistics 

Ozone Threshold (60 PPB) August 2004 May 2005 July 2005Date 8/7 8/8 5/21 5/22 7/15 7/16 7/17 7/18 Julian Date 220 221 141 142 196 197 198 199 Ratio of Predicted Sub-Regional Peak to Peak Observed 

1.14 1.43 0.94 0.96 1.68 2.01 1.41 ----- 

Ratio of Unpaired Station Peaks 1.02 1.21 0.87 0.80 0.78 1.20 1.12 ----- Normalized Systematic Bias (%) -10 -8 -32 -33 -33 15 17 ----- Normalized Gross Error (%) 15 16 36 34 33 15 21 ----- Ozone Threshold (60 PPB) August 2005 August 2005 AugusDate 8/4 8/5 8/6 8/7 8/27 8/28 8/4 8/5 Julian Date 216 217 218 219 239 240 216 217 Ratio of Predicted Sub-Regional Peak to Peak Observed 

138 1.72 1.66 1.64 1.06 0.83 1.12 1.16 

Ratio of Unpaired Station Peaks 1.55 1.48 1.59 1.28 0.83 0.71 0.81 0.84 Normalized Systematic Bias (%) -2 48 56 35 -21 -24 -20 -20 Normalized Gross Error (%) 17 48 59 35 23 26 22 27 
Chapter 4 Revision to the 2003 Ozone Attainmen

V-4-29

TABLE V-4-12 

CAMx Sub-Region-3 8-Hour Average Ozone Performance Statistics 

Ozone Threshold (60 PPB) August 2004 May 2005 July 2005Date 8/7 8/8 5/21 5/22 7/15 7/16 7/17 7/18 Julian Date 220 221 141 142 196 197 198 199 Ratio of Predicted Sub-Regional Peak to Peak Observed 

1.11 1.04 0.95 0.76 1.35 0.88 0.87 0.82 

Ratio of Unpaired Station Peaks 0.79 0.76 0.66 0.57 1.15 0.75 0.66 0.58 Normalized Systematic Bias (%) -12 -9 -30 -43 11 0 -7 -27 Normalized Gross Error (%) 13 11 30 43 11 12 18 27 Ozone Threshold (60 PPB) August 2005 August 2005 AugusDate 8/4 8/5 8/6 8/7 8/27 8/28 8/4 8/5 Julian Date 216 217 218 219 239 240 216 217 Ratio of Predicted Sub-Regional Peak to Peak Observed 

0.93 0.91 0.91 1.02 1.01 0.74 1.07 1.15 

Ratio of Unpaired Station Peaks 0.77 0.83 0.86 0.96 0.92 0.65 0.96 1.07 Normalized Systematic Bias (%) -9 -7 8 15 -17 -36 2 11 Normalized Gross Error (%) 13 10 21 27 17 36 5 21 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-30

TABLE V-4-13 

CAMx Sub-Region-4 8-Hour Average Ozone Performance Statistics 

Ozone Threshold (60 PPB) August 2004 May 2005 July 2005Date 8/7 8/8 5/21 5/22 7/15 7/16 7/17 7/18 Julian Date 220 221 141 142 196 197 198 199 Ratio of Predicted Sub-Regional Peak to Peak Observed 

0.89 1.10 0.84 0.80 0.90 0.97 1.03 1.10 

Ratio of Unpaired Station Peaks 0.84 1.06 0.77 0.77 0.79 0.88 0.99 0.97 Normalized Systematic Bias (%) -10 7 -13 -18 13 -2 2 -4 Normalized Gross Error (%) 10 8 19 22 20 14 8 7 Ozone Threshold (60 PPB) August 2005 August 2005 AugusDate 8/4 8/5 8/6 8/7 8/27 8/28 8/4 8/5 Julian Date 216 217 218 219 239 240 216 217 Ratio of Predicted Sub-Regional Peak to Peak Observed 

0.99 1.02 0.95 0.96 0.70 0.77 1.10 1.09 

Ratio of Unpaired Station Peaks 0.94 1.00 0.91 0.96 0.63 0.76 1.03 1.00 Normalized Systematic Bias (%) 10 8 -2 -2 -27 -22 4 2 Normalized Gross Error (%) 16 17 13 13 31 29 11 6 
Chapter 4 Revision to the 2003 Ozone Attainmen

V-4-31

TABLE V-4-14 

CAMx Sub-Region-5 8-Hour Average Ozone Performance Statistics 

Ozone Threshold (60 PPB) August 2004 May 2005 July 2005Date 8/7 8/8 5/21 5/22 7/15 7/16 7/17 7/18 Julian Date 220 221 141 142 196 197 198 199 Ratio of Predicted Sub-Regional Peak to Peak Observed 

1.21 1.43 1.05 0.99 1.61 - - - 1.49 - - - 

Ratio of Unpaired Station Peaks 0.93 1.06 0.88 0.71 0.83 - - - 1.18 - - - Normalized Systematic Bias (%) -10 -4 -22 -31 -17 - - - 22 - - - Normalized Gross Error (%) 13 11 24 31 17 - - - 22 - - - Ozone Threshold (60 PPB) August 2005 August 2005 AugusDate 8/4 8/5 8/6 8/7 8/27 8/28 8/4 8/5 Julian Date 216 217 218 219 239 240 216 217 Ratio of Predicted Sub-Regional Peak to Peak Observed 

1.45 - - - 1.61 1.56 1.30 1.01 1.46 1.29 

Ratio of Unpaired Station Peaks 0.90 - - - 1.56 1.33 0.79 0.78 1.01 .86 Normalized Systematic Bias (%) -15 - - - 44 29 -25 -29 -12 -2 Normalized Gross Error (%) 15 - - - 44 29 25 29 12 9 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-32

Graphical Evaluation 

Figures V-4-10 through V-4-14 show the tile plots of predicted maximum ozone for the 

each day of the July 15-19, 2005 ozone simulations. Figure V-4-15 provides the 

cumulative scatter plot of CAMx predicted vs. observed 1-hour average ozone for the 

July 14-18 subset of the 2005 episode. Figures V-4-16a through V-4-16h show the 

station diurnal plots of predicted and observed ozone. Similar tile plots of predicted 

maximum ozone, diurnal plots and scatter plots of performance for the remaining 

episodes are provided as attachments to this appendix. 

FIGURE V-4-10 

CAMx Simulated Maximum 1-Hour Average Ozone, July 15, 2005 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-33

FIGURE V-4-11 

CAMx Simulated Maximum 1-Hour Average Ozone, July 16, 2005 

FIGURE V-4-12 

CAMx Simulated Maximum 1-Hour Average Ozone, July 17, 2005 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-34

FIGURE V-4-13 

CAMx Simulated Maximum 1-Hour Average Ozone, July 18, 2005 

FIGURE V-4-14 

CAMx Simulated Maximum 1-Hour Average Ozone, July 19, 2005 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-35

Scatter Plot of Predicted vs. Observed Concentrations

July 15-19

y = 0.8683x + 5.9521

R2

 = 0.7522

0

20

40

60

80

100

120

140

0 20 40 60 80 100 120 140

Observed [ppb]

Predicted [ppb]

FIGURE V-4-15 

CAMx Predicted vs. Observed 8-Hour Average Ozone Concentrations: July 14-18, 2005 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-36

3176: Anaheim 7.422 421.646

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

60: Azusa 6.981 456.113

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

4164: Banning Airport 104.459 433.527

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

69: Burbank -27.848 461.308

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

FIGURE V-4-16a 

CAMx Simulated 8-Hour Average Ozone (Solid Line) Vs. Observed (Squares): 

July, 2005 Ozone Meteorological Episode 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-37

87: Los Angeles -22.302 445.563

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

5181: Crestline 66.383 468.606

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

3195: Costa Mesa 6.780 405.599

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

4158: Elsinore 60.525 405.907

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

FIGURE V-4-16b 

CAMx Simulated 8-Hour Average Ozone (Solid Line) Vs. Observed (Squares): 

July, 2005 Ozone Meteorological Episode 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-38

5197: Fontana 46.811 453.081

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

591: Glendora 13.487 457.010

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

4157: Indio Jackson 162.217 411.293

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

3177: La Habra 4.359 432.978

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

FIGURE V-4-16c 

CAMx Simulated 8-Hour Average Ozone (Solid Line) Vs. Observed (Squares): 

July, 2005 Ozone Meteorological Episode 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-39

820: LAXH -36.352 433.685

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

72: Long Beach -17.171 421.904

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

84: Lynwood -19.237 432.753

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

5212: Mira Loma 42.938 438.915

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

FIGURE V-4-16d 

CAMx Simulated 8-Hour Average Ozone (Solid Line) Vs. Observed (Squares): 

July, 2005 Ozone Meteorological Episode 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-40

3812: Mission Viejo 29.671 400.791

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

88: Pasadena -11.205 457.021

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

4149: Perris 69.051 417.376

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

85: Pico Rivera -5.273 442.860

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Predicted

FIGURE V-4-16e 

CAMx Simulated 8-Hour Average Ozone (Solid Line) Vs. Observed (Squares): 

July, 2005 Ozone Meteorological Episode 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-41

4137: Palm Springs 132.826 423.133

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

75: Pomona 22.547 448.620

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

5204: Redlands 76.256 448.189

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

74: Reseda -48.000 463.105

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

FIGURE V-4-16f 

CAMx Simulated 8-Hour Average Ozone (Solid Line) Vs. Observed (Squares): 

July, 2005 Ozone Meteorological Episode 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-42

4144: Rubidoux 52.093 442.557

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

90: Santa Clarita -48.140 483.357

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

5203: San Bernardino 65.874 453.300

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

5175: Upland 31.687 452.125

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

FIGURE V-4-16g 

CAMx Simulated 8-Hour Average Ozone (Solid Line) Vs. Observed (Squares): 

July, 2005 Ozone Meteorological Episode 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-43

91: West Los Angeles -34.796 447.031

0

20

40

60

80

100

120

140

 7/ 15/ 5 7/ 16/ 5 7/ 17/ 5 7/ 18/ 5 7/ 19/ 5

Date

O3 [ppb]

M inimum to M aximum Range Observed Predicted

FIGURE V-4-16h 

CAMx Simulated 8-Hour Average Ozone (Solid Line) Vs. Observed (Squares): 

July, 2005 Ozone Meteorological Episode 

The diurnal plots illustrate a range of model predictions based on a 7 X 7 grid analysis. 

In the diagram, and in the later attainment demonstration, the peak prediction in the 49 

grid cell array is compared to the station observation. 

The July episode spans a weekend (July 16th and 17th) over the course of the 5 day 

meteorological episode. Weekend inventories have become increasingly more reliable 

but have not yet reached the level of certainty of the weekday emissions profiles. 

Overall, heavy duty truck traffic decreases by about 60 percent in the Basin on Saturday, 

compared to Friday, and an additional 10-15 percent on Sundays. NOx emissions are 

greatly reduced along the primary transportation corridors. Unfortunately, at this time, 

there is no weekend trip model is available to accurately simulate the reduced usage of 

trucks on weekends and the residual impact on the movement and speeds of passenger 

cars and light duty vehicles. Hence, the simulation uncertainty is most pronounced 

during the weekends. Weekday simulations provide a more accurate characterization of 

the observed ozone trends. 

On July 16th and 17th, the peaks are nominally under predicted and tend to lag the 

observed concentrations in the San Bernardino Valley and mountain areas. Performance 

in the Riverside area is split, where Rubidoux is generally under predicted but Lake 

Elsinore and Perris are well simulated. The simulation tends to under predicted 

observations in the eastern San Gabriel Valley but is reasonable in the coastalmetropolitan areas. The San Fernando Valley sites of Burbank and Reseda are well 

simulated with a tendency for over prediction. Santa Clarita however is significantly 

under predicted on these days. 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-44

Effect of Emissions Uncertainties 

The Final 2007 AQMP emissions inventory built upon the effort undertaken in the 2003 

AQMP to provide updates to the mobile and day specific point and biogenic inventories 

used in the modeling attainment demonstrations. Aircraft and airport operations were 

thoroughly reviewed and inventoried. Shipping transits into the Ports of Los Angeles 

and Long Beach were carefully logged and shipping lane transits up and down the coast 

were logged for the major vessels. The episode specific biogenic emissions inventory 

under went significant modification. The areas source emissions distribution continued 

to rely on the emissions surrogates used in the 2003 AQMP to distribute emissions. 

As previously discussed in Chapter 2 the revisions to ARB's on-road emissions program 

EMFAC2007 and the update of the Off-Road companion model had a significant impact 

on the emissions inventory and resulting model simulations. The net impact of 

EMFAC2007 was to raise the absolute tonnage of NOx and VOC in the mobile source 

emissions inventory over the 2003 AQMP projected 2002 inventory. The Basin 2002 

base-year mobile source inventory totals for VOC and NOx increased from 559 and 968 

TPD in the 2003 AQMP to 710 and 1001 TPD for the current effort. While VOC 

emissions rose 27 percent, NOx emissions only rose by a 3 percent margin. Many of the 

comments regarding the episode development in simulating previous episodes was that 

there existed significantly more NOx relative to the amount of VOC in the domain. The 

enhancement to the inventories have led to more accurate inventory estimates, however, 

the ratio of VOC to NOx remains in favor of ozone titration in the coastal emissions 

region. 

Several additional factors resulting from the use of the EMFAC2007 and Direct 

Transportation Impact Model (DTIM4) to generate grid level mobile source emissions 

may have altered the VOC to NOx ratio in the Basin. First, there exist differences 

between the two models in the numbers of trips and lengths of trips inferred by the 

regional transportation model output. More numerous starts and stops lead to greater 

VOC emissions from vehicle use and standing evaporative loss. Similarly, speed 

impacts NOx emissions, especially from heavy-duty vehicles. Differences exist between 

the emissions models in how the heavy-duty vehicle speed factors are assigned. 

Significant movement was made to resolve differences in the projections of truck travel, 

most notably the redistribution of a percentage of the fleet to the eastern Basin and 

second, out of the Basin to the northern and eastern air Basins. The redistribution of 

truck travel is one of the contributing factor to the nominal increase in NOx as opposed 

to previous inventory updates. 

The impact of ethanol as an additive in the fuel has lead to increased VOC emissions due 

to increase vapor permeation in the fuel and exhaust of passenger vehicles. While 

progress has been made to capture the impact of the VOC evaporative emissions, there 

continues to exist uncertainty to the total daily tonnage and in particular the response on 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-45

exceedingly hot days when evaporation can become an exponential function of 

temperature. VOC emissions on hot days, which are synonymous with higher ozone 

days may be under represented and the net impact to model performance would be for 

under prediction of the total amount of ozone formed in the Basin. 

Comments on the episode selection were directed at the exclusion of 2003 as a source 

for potential simulations days. The summer of 2003 was exceptionally hot with 

numerous days exceeding the 100o

F temperature in the inland valleys. Given the 

uncertainty associated with vapor permeation, coupled with fuel commingling, it was 

decided to avoid selecting days on which significant uncertainty in the emissions 

occurred. 

Other areas of the inventory uncertainty may have impacted model performance 

including the assignment of surrogates used to distribute emissions through the Basin, 

and the sub-county distribution of vehicles by age. Several sensitivity simulations were 

conducted using emissions factors generated by EMFAC2002 during the 2003 AQMP 

and were regenerated for this analysis using a grid level characterization of the passenger 

vehicle age with each county. The analysis was designed to attempt to place older, high 

emitting vehicles in the general areas where they operate. There are drawbacks to this 

assumption in that the average trip distance in the Basin exceeds one grid length and can 

easily transverse a county line. The sensitivity analyses were encouraging and 

preliminary results improved the ozone simulation model performance in some critical 

areas (most notably, Santa Clarita). 

Similar types of sensitivity analyses were conducted to test the extent of reduced truck 

travel (lower NOx) in the Basin on weekends and the movement, storage and usage of 

pleasure craft on weekends and weekdays. The impacts of these prospective inventory 

modifications varied by hour of day and location in the Basin. 

The biogenic inventory is also subject to uncertainties due to the critical roll daily 

temperature and humidity has in the estimation of the emissions. This is clearly evident 

in the day-to-day variation in total emissions over the five multi-day episodes, and in the 

difference in the estimated emissions between spring and mid summer. Added to the 

diurnal and seasonal variation has been the rapid die off of the forests in the East Basin 

due to an infestation of the Bark Beetle. Estimates of tree death by acre continue to 

increase creating a moving target for emissions estimation. Finally, the several episodes 

take place in August and it is difficult to assess cumulative stress on the biomass as the 

season progresses and what impact did the stress have on daily emissions. 

OZONE AIR QUALITY PROJECTIONS 

CAMx simulations were conducted for the year base emission scenarios (2017 and 

2023), and future year controlled scenarios (2017, and 2023). As discussed earlier, the 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-46

ozone attainment demonstration relies on the use of site specific RRFs being applied to 

the 2002 weighted design values. The RRFs are determined from the future year 

controlled and the 2002 base year simulations. 

Future year 8-hour ozone attainment demonstrations are required for those sites with 

design values that exceed 84 ppb. As such, the current demonstrations are focused on 16 

locations in the Basin. The initial screening for station days to be included in the 

attainment demonstration included the following criteria: (1) having an observed 

concentration equaling or exceeding 85 ppb and (2) a simulation predicted base year 

(1997, 2004 or 2005) concentration over 60 ppb. Additional criteria were added to the 

selection process as the simulations were evaluated. 

A minimum of 5-episode days are recommended to determine the site specific RRF. 

The evaluation requires that the model performance for the day is within specific 

performance goals. The final criteria used to select an episode station day for the RRF 

calculation included: (1) the base-year observed concentration lie with 25 percent of the 

station design value, (2) the absolute prediction accuracy (predicted minus observed in 

the base- year) is within 25 percent and (3) that a minimum base-year observed 

concentration at each site used in the analysis 85 ppb or greater. A maximum of 19 

episode days were evaluated for inclusion in the RRF calculation. If a site did not meet 

the 5-episode day threshold, the smaller reduction determined from either the average of 

the RRFs for all Basin sites or the 19 day average RRF from that site, regardless of 

model performance, was applied to estimate the future design value at that station. 

Since the CAMx simulations are run on a 5 km grid, the maximum 8-hour average 

concentration from the 49 grid cells representing the monitoring site are used to generate 

the simulated concentration at the monitor. 

The results of the attainment demonstration for 2023 are presented in Table V-4-15. 

Table V-16 provides the CAMx 2023 future year day specific model simulation results. 

The analysis indicates that the federal 8-hour ozone standard would be attained in 2024 

at the key stations with the controlled emissions implemented to the 2023 inventory. 

The controlled carrying capacity (420 TPD of VOC and 114 TPD of NOx) consists of 

both short-term and long-term control measures. The CEPA output summarizing the 

control strategy implementation and emissions reductions is provided as Attachment 7. 

With controls in place, it is expected that all stations in the Basin will meet the federal 8-

hour ozone standard. The east Basin stations of Crestline and Fontana are projected to 

have the highest 8-hour controlled design values. Both sites are downwind receptors 

along the primary wind transport route that moves precursor emissions and developing 

ozone eastward during by the daily sea breeze. Future year projections of ozone along 

the northerly transport route through the San Fernando Valley indicate that the ozone 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-47

design value in the Santa Clarita Valley will be approximately 13 percent below the 

standard. 

It is important to reiterate that the form of the ozone standard allows for at least 3-days 

to have 8-hour average concentrations that exceed 80 ppb in any year. So, although the 

demonstration satisfies the criteria for attainment, areas of the Basin are likely to 

experience occasional higher ozone days (greater than 80 ppb) under severe 

meteorological conditions. 

Equally important, is the rate of progress specified by the timing of the new standard. 

The 2003 AQMP 1-hour ozone demonstration set a 2010 attainment carrying capacity 

of 330 TPD of VOC and 540 TPD of NOx. Sensitivity simulations were conducted to 

assess progress towards attaining the revoked 1-hour ozone standard for a current 2010 

baseline emissions estimate. The results indicated that the currently predicted 1-hour 

average ozone concentrations for 2010 are expected to be approximately 20 percent 

above the revoked 1-hour federal standard assuming full implementation of all available 

control measures. 

Graphical Distribution 

The spatial distribution of ozone design values for the 2002 base year is shown in Figure 

V-4-17. The distribution was generated using GIS mapping of the station based ozone 

design values overlaid onto the modeling grid while applying a distance weighted 

interpolation scheme to expand the prediction. Future year ozone air quality projections 

for 2024 with and without implementation of all control measures are presented in 

Figures V-4-18 and V-4-19. The predicted ozone concentration will be significantly 

reduced in the future years in all parts of the Basin with the implementation of proposed 

control measures in the South Coast Air Basin. 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-48

TABLE V-4-15 

2024 Projected Basin 8-Hour Ozone Design Values 

Site 2002 2002 2023 No. 2024 

 Weighted Baseline Controlled Valid Controlled 

Design 

(PPB) 

Simulation 

(PPB) 

Average 

(PPB) Days RRF 

Design 

(PPB) 

(a) Criteria 

Azusa 101.0 108.1 66.3 < 5 0.661 69 

Banning 

Airport 115.0 119.0 69.4 11 0.588 68 

Burbank 92.0 103.8 77.0 < 5 0.661 63 

Crestline 128.7 123.0 78.5 8 0.644 83 

Elsinore 107.0 110.5 63.3 9 0.575 62 

Fontana 117.7 108.1 73.6 11 0.685 81 

Glendora 112.0 106.6 73.8 5 0.706 79 

Pasadena 96.0 99.0 73.4 < 5 0.661 73 

Perris 112.0 107.3 75.4 < 5 0.661 79* 

Pomona 96.0 101.7 77.9 8 0.779 75 

Redlands 125.0 116.5 75.2 13 0.649 81 

Reseda 104.0 105.3 66.2 7 0.632 66 

Rubidoux 111.0 111.4 76.0 12 0.688 76 

Santa Clarita 122.0 109.8 66.4 10 0.610 74 

San Bernardino 116.0 115.0 75.6 14 0.660 77 

Upland 110.0 107.3 75.8 8 0.713 78 

Avg. ≥ 5 Days 0.661 

 

(b) All Days 

Azusa 101.0 96.6 71.6 19 0.788 80* 

Burbank 92.0 97.5 73.8 19 0.756 70* 

Pasadena 96.0 97.8 75.7 19 0.774 74* 

Perris 112.0 111.7 66.2 15 0.592 66 

* The higher future year design value determined from either the average RRF from the criteria (0.661) or 

from the RRF calculated from all simulation days (only 15 were evaluated for Perris). 

 
Chapter 4 Revision to the 2003 Ozone Attainmen

V-4-49

TABLE V-4-16 

CAMx 2023 Controlled Simulation 

Station CAMx 2023 Controlled Simulation  2004 2005 19

220 221 142 196 197 198 199 200 216 217 218 219 240 216 217 

Azusa 66.3 Banning 78.6 78.4 70.8 69.8 73.5 76.8 75.8 58.2 52.8 70.7 Burbank 77 Crestline 88 82.4 79.9 84 82.9 82.6 58 Elsinore 70 71.3 70.1 67.9 66.8 56.2 59.7 53.4 Fontana 85.2 80.2 78.9 81.3 84 65.6 62.6 61.3 61.7 73 76.2 Glendora 87.6 80.3 68.9 65.6 66.8 Indio 59 51.5 52.9 Pasadena 77.9 68.9 Perris 75.4 Palm Springs 62.5 64.9 58.9 50.1 58.4 59.7 56.5 65.7 Pomona 83.7 77.8 82.5 87.4 83.9 67 66.5 74 Redlands 88 83.1 82.4 84 82.9 84.8 64.2 63.5 56.9 73 74.9 73.4 Reseda 63.7 72.3 64.3 65.1 59.4 74.2 64.5 Rubidoux 88 82.7 82.4 83.2 82.9 84.8 63.5 61.5 60.7 73 73.4 76.2 Santa Clarita 63.7 63.8 72.3 64.3 65.1 59.4 74.2 60.5 58.1 San Bernardino 88 83.1 82.4 79.9 84 82.9 84.8 64.2 63.5 61.3 58.7 73 74.9 75.3 Upland 83.5 77.6 78.5 82.7 80.9 61.9 64.5 76.2 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-50

FIGURE V-4-17 

2002 Baseline 8-Hour Ozone Design Concentrations (ppb) 

FIGURE V-4-18 

Model-Predicted 2024 Baseline 8-Hour Ozone Design Concentrations (ppb) 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-51

FIGURE V-4-19 

Model-Predicted 2024 Controlled 8-Hour Ozone Design Concentrations (ppb) 

Projection of 2018 Air Quality in the Coachella Valley 

One major component of the Final 2007 AQMP modeling attainment demonstration 

addresses the issue of transport of ozone and precursor pollutants into the Coachella 

Valley. The Coachella Valley has a 2013 attainment date. After the initial simulations 

using the 2012 controlled emissions inventory, it was determined that additional time 

would be required to meet the standard, despite implementation of the upwind control 

strategy. (The projected 2013 ozone design value for the Coachella Valley using the 

2012 controlled emissions inventory was 88 ppb). As a consequence, the District is 

seeking a voluntary redesignation of the Coachella valley’s ozone attainment status from 

“serious” to “severe-15.” This action will provide additional time, out to 2018, to attain 

the federal 8-hour standard. 

CAMx simulations were also generated for the suite of episode days using the 2017 

baseline and controlled inventories. Emission reductions through 2017 are expected to 

take place through exiting established control measures and reductions in mobile source 

emissions as projected by EMFAC2007 and through the CARB control strategy with the 

District overlay. 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-52

Table V-4-17 provides the 2017 ozone attainment demonstration for the Coachella 

Valley. Again, RRFs are determined from CAMx simulations using the 2002 baseline 

and 2017 controlled emissions. Each site used at least 5 simulation days to generate the 

RRFs. The attainment demonstration shows that both Indio and Palm Springs will meet 

the federal standard. 

TABLE V-4-17 

2017 Projected Coachella Valley 8-Hour Ozone Design Values 

Site 2002 2002 2017 2024 

 Weighted Baseline Controlled Controlled 

Design 

(PPB) 

Simulation 

(PPB) 

Average 

(PPB) 

No. 

Valid 

Days RRF 

Design 

(PPB) 

Palm Springs 105.7 99.9 75.9 9 0.767 81.1 

Indio Jackson 95.0 84.0 66.2 5 0.791 75.2 

TABLE V-4-18 

CAMx 2017 Coachella Valley Controlled 8-Hour Average Ozone Simulation (PPB) 

Station CAMx 2017 Simulation Days 

 2004 2005 1997 

 220 221 142 196 197 198 199 239 218 

Palm Springs 80.2 82.6 76.5 73.6 84.6 82.3 79.7 67.6 56.2 

Indio Jackson 73.2 66.3 71.7 63 56.8 

SENSITIVITY STUDIES: MODEL PERFORMANCE AND CEQA 

A set of CAMx sensitivity simulations were generated to test, model performance and 

evaluate alternate emissions scenarios for CEQA determination. The stress tests 

conducted for the PM2.5 modeling analysis were also applied to the ozone simulations 

where emissions motor vehicle emissions were doubled, the model was run solely with 

biogenic emissions and the top ozone boundary condition was modified. The results of 

the simulations suggested a better fit of the data when VOC emissions were increase 

throughout the Basin bringing them in line with the ambient VOC/NOx ratio measured 

through the PAMS network. Reducing the top concentration (top boundary of the model 

simulation) resulted in a reduction of surface ozone ranging several ppb, but with no 

specific trend in time of day. 
Chapter 4 Revision to the 2003 Ozone Attainment Demonstration Plan 

V-4-53

Table V-4-19 lists the emissions for the 2023 baseline, plan and CEQA alternative ozone 

simulations conducted. Three CEQA ozone simulations were conducted: (Alt-1) Heavy 

VOC and heavy NOx, (Alt-2) Extensive VOC reductions and little NOx, and the 2003 

AQMP (No-Project). The results of the simulations indicated that only the first scenario 

could result in attainment of the ozone standard. (See Figure V-4-20). The Heavy VOC 

scenario does not demonstrate attainment because of the influence of biogenic 

emissions. The No-plan scenario did not meet the standard because of the lack of 

emissions reductions. 

TABLE V-4-19 

CEQA Simulations Modeling Emissions 

Ozone-2023 

 VOC NOX CO 

Baseline 496 506 2142 

Plan 420 117 2049 

Alt-1 200 160 1965 

Alt-2 100 250 1965 

No-Project 283 373 2100 

0

20

40

60

80

100

120

2007 AQMP No-Project Alternative 1

Ozone Concentration (ppb)

FIGURE V-4-20 

CEQA 2023 Ozone Simulation Results 
Final 2007AQMP Appendix V: Modeling and Attainment Demonstrations 

V-4-54

WEIGHT OF EVIDENCE 

The 2007 AQMP will rely on the use of long term measures to ensure attainment of the 

federal 8-hour ozone standard. Several sensitivity runs were conducted to address 

questions pertaining the mobile source emissions inventory, and VMT. 

With the revisions to the mobile source inventory (from an earlier version of 

EMFAC2007), the ozone model performance decreased slightly, although it was still 

within the acceptable criteria. However, lower base year emissions (i.e., 2002 

emissions) and a significant alteration in the VOC-to-NOx ratio (due to pending vehicle 

adjustments described earlier) lead to a lower carrying capacity for ozone attainment. 

This means greater reductions are needed to meet the 8-hour ozone standard by 2023. 

AQMD staff has retained outside consultants to perform peer review on AQMD's 

modeling work. Their initial feedback suggested that VOC emissions in 2002 might 

have been underestimated. In light of the earlier discussion on VMT projections and 

peer review comments on the VOC inventory, a series of sensitivity analyses were 

performed to test potential policy implications. The VMT sensitivity modeling runs 

included: 1) adjusting CARB VMT estimates for 2005 to match with SCAG’s; 2) 

readjusting CARB’s VMT estimates for 2002, 2014, and 2020 anchoring off its 2005 

VMT in accordance with the growth rates provided by SCAG. The results indicate that 

the 2005 VMT “blip” helps reduce the need for additional NOx reductions by 10 tpd by 

2014. However, should CARB’s 2005 VMT be accurate 30 TPD of additional NOx 

reductions would be required for 8-hour ozone attainment. 

Several additional simulations were conducted by adjusting the VOC emissions in 2002 

to attempt to equilibrate with the ambient VOC/NOx ratio. The net results of these 

analyses were to generate more ozone in 2002 and as a consequence increase the slope 

of the RRF’s. Regardless, all of the adjustments to the 2002 inventory did not negate the 

need for long term measures and additional NOx controls. 

In conclusion with the uncertainties that have been previously discussed in the 

inventory, the attainment demonstration for 2024 projects a maximum future year design 

value of 83 ppb which provides an additional measure of confidence that the strategy, as 

designed will meet the federal ozone standard. 
CHAPTER 5 

SUMMARY AND CONCLUSIONS 

Comparison to State and Federal Standards 

Basin Emissions Carrying Capacity (Emissions Budget) 
Chapter 5 Summary and Conclusions

V-5-1 

COMPARISON TO STATE AND FEDERAL STANDARDS 

Figure V-5-1 shows the 2002 observed and model-predicted regional peak 

concentrations for the three nonattainment criteria pollutants, as percentages of the most 

stringent federal standard, for the years 2010, 2015, and 2024 (with and without further 

emission controls). Figure V-5-2 shows similar information related to the most stringent 

California state standards. Note: the revoked federal 1-hour standard comparison has 

been included for reference. The 2010 baseline 1-hour average ozone concentrations are 

projected to exceed the revoked standard. 

Table V-5-1 summarizes the expected year for attainment of the various federal and state 

standards for the four pollutants analyzed. As shown, the Basin will be in compliance 

with federal standards by the year 2024. The Basin will require additional time beyond 

2024 to meet the state ozone, PM2.5 and PM10 standards. 

BASIN EMISSIONS CARRYING CAPACITY (EMISSIONS BUDGET) 

The District is required to separately identify the emission reductions and corresponding 

type and degree of implementation measures required to meet federal and state ambient 

air quality standards. Section 40463(b) of the California State Health and Safety Code 

specifies that, with the active participation of the Southern California Association of 

Governments, a South Coast Air Basin emission carrying capacity for each state and 

federal ambient air quality standard shall be established by the South Coast District 

Board for each formal review of the Plan and shall be updated to reflect new data and 

modeling results. 

A carrying capacity is defined as the maximum level of emissions that enable the 

attainment and maintenance of an ambient air quality standard for a pollutant. Emission 

carrying capacity for state standards shall not be a part of the State Implementation Plan 

requirements of the Clean Air Act for the South Coast Air Basin. Emission carrying 

capacity as defined in the Health and Safety Code is an overly simplistic measure of the 

Basin-wide allowable emission levels for specific ambient air quality standards. It is 

highly dependent on the spatial and temporal pattern of the emissions. Because of the 

multi-component nature of PM2.5, the carrying capacity for the contributing emissions 

can vary significantly and like ozone it is a non-linear function among their precursors. 

The federal Clean Air Act requires that plans contain an emissions budget that represents 

the remaining emissions levels that achieve the applicable attainment deadline. Based 

on the modeling results, a set of carrying capacities can be defined corresponding to 

federal and state ambient air quality standards for annual PM2.5 and 8-hour ozone. 

VOC and oxides of nitrogen are used for ozone. PM2.5 additionally requires reductions 

of sulfur oxides and directly emitted PM2.5. Table V-5-2 shows the emissions carrying 

capacities for the Basin to meet federal air quality standards. These estimates are based 

on emission patterns estimated for each of the federal attainment years: 2015 for PM2.5 

and 2021 for ozone. 
Final 2007 AQMP Appendix V Modeling Attainment Demonstrations 

5 - 2

0

20

40

60

80

100

120

140

160

180

200

1-Hour

Ozone

8-Hour

Ozone

Annual

PM2.5

24-Hour

PM2.5

24-Hour

PM10

Percent of Standard

2002 Baseline 2010 Controlled

2015 Controlled 2024 controlled

FIGURE V-5-1 

Projection of Future Air Quality in the Basin in Comparison 

with the Most Stringent Federal Standards. 

0

50

100

150

200

250

300

1-Hour

Ozone

8-Hour

Ozone

Annual

PM2.5

24-

Hour

PM2.5

Annual

PM10

24-

Hour

PM10

Percent of Standard

2002 Baseline 2015 Controlled 2024 controlled

FIGURE V-5-2 

Projection of Future Air Quality in the Basin in Comparison with 

Most Stringent California State Standards 
Chapter 5 Summary and Conclusions

V-5-3 

TABLE V-5-1 

Expected Year of Compliance with State and Federal 

Standards for the Four Criteria Pollutants 

 Concentration Expected 

Pollutant Standard Level Compliance Year 

Ozone NAAQS 8-hours 84 ppb 2024 

 CAAQS 1-hour 90 ppb beyond 2024 

 CAAQS 8-hours 70 ppb beyond 2024 

 

PM2.5 NAAQS Annual 15 ug/m3 2015 

 NAAQS 24-hours 65 ug/m3 2005 

 NAAQS 24-hours* 35 ug/m3 2005 

 CAAQS Annual 12 ug/m3 beyond 2024 

PM10 NAAQS 24-hours 150 ug/m3 2000 

 CAAQS 24-hours 50 ug/m3 beyond 2024 

 CAAQS Annual 20 ug/m3 beyond 2024 

CO** NAAQS 1-hour 35 ppm 1990 

 NAAQS 8-hours 9 ppm 2002 

 CAAQS 8-hours 9 ppm 2002 

NO2 NAAQS Annual 0.0534 ppm 1995 

 CAAQS Annual 0.030 ppm Beyond 2005 

 CAAQS 24-hours 18 ppm 2003 

 * EPA adopted the new 24-Hour PM2.5 standard in September 2006. The current SIP 

requirements address the 65 ug/m3

 standard in place in 2005 when national area attainment 

designations were adopted. 

** On May 11, 2007, U.S. EPA redesignated the South Coast Air Basin as attainment for 

Carbon Monoxide 
Final 2007 AQMP Appendix V Modeling Attainment Demonstrations 

V-5-4

TABLE V-5-2 

Emissions Carrying Capacity Estimations for the South Coast Air Basin (tons/day) 

based on the Planning Inventory 

a) PM2.5 Attainment Strategy to meet NAAQS (2015) 

VOC NOx SOx PM2.5

 

469 454 19 87 

b) Ozone Attainment Strategy to meet NAAQS (2024) 

VOC NOx CO 

 

420 114 2039 
References 

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Attachment-1 

PM2.5 Annual and 24-Hour Attainment Calculations 
TABLE V-A-1a 

Predicted 2015 PM2.5 at Anaheim Using the Speciated Modeling Attainment Test 

RRF (CAMx 2015/CAMx 2005)  NH4 NO3 SO4 OC EC OTR Q1 0.70 0.70 0.71 0.80 0.86 1.03 Q2 0.61 0.59 0.62 0.85 0.86 1.02 Q3 0.63 0.65 0.58 0.82 0.85 1.00 Q4 0.73 0.75 0.67 0.80 0.86 1.02 2005 Design Modified by MATES-III with Sandwich  NH4 NO3 SO4 OC EC OTR Water Blank Filter  Mass Q1 1.49 4.95 2.20 3.25 1.59 1.57 2.00 0.50 17.5Q2 1.04 2.63 3.16 0.75 0.65 1.72 1.95 0.50 12.4Q3 1.60 2.71 4.47 1.74 0.72 2.00 1.62 0.50 15.3Q4 2.64 5.34 2.45 2.69 2.39 2.19 1.80 0.50 20.0Annual 1.69 3.91 3.07 2.11 1.34 1.87 1.84 0.50 16.32015 Controlled PM2.5  NH4 NO3 SO4 OC EC OTR Water Blank SubtotaQ1 1.04 3.47 1.56 2.60 1.37 1.62 1.43 0.50 13.5Q2 0.63 1.55 1.96 0.64 0.56 1.75 1.19 0.50 8.7Q3 1.01 1.76 2.59 1.43 0.61 2.00 0.95 0.50 10.8Q4 1.93 4.01 1.64 2.15 2.06 2.23 2.01 0.50 16.5Annual 1.15 2.70 1.94 1.70 1.15 1.90 1.40 0.50 12.4
TABLE V- A-1b 

Predicted 2015 PM2.5 at Burbank Using the Speciated Modeling Attainment Test 

RRF (CAMx 2015/CAMx 2005)  NH4 NO3 SO4 OC EC OTR Q1 0.70 0.69 0.72 0.80 0.85 1.01 Q2 0.63 0.62 0.62 0.83 0.83 1.00 Q3 0.64 0.65 0.60 0.81 0.83 0.97 Q4 0.76 0.77 0.71 0.81 0.84 1.01 2005 Design Modified by MATES-III with Sandwich  NH4 NO3 SO4 OC EC OTR Water Blank Filter  Mass Q1 1.54 4.90 1.77 5.16 1.74 1.48 1.62 0.50 18.7Q2 1.48 3.63 2.94 1.97 1.02 2.10 1.53 0.50 15.1Q3 2.45 4.34 4.54 3.10 1.25 2.27 2.20 0.50 20.6Q4 3.06 6.90 2.42 3.80 3.21 2.09 2.32 0.50 24.3Annual 2.13 4.94 2.92 3.51 1.81 1.99 1.92 0.50 19.72015 Controlled PM2.5  NH4 NO3 SO4 OC EC OTR Water Blank SubtotaQ1 1.08 3.38 1.27 4.13 1.48 1.49 1.10 0.50 14.4Q2 0.93 2.25 1.82 1.64 0.85 2.10 0.92 0.50 11.0Q3 1.57 2.82 2.72 2.51 1.04 2.20 1.36 0.50 14.7Q4 2.33 5.31 1.72 3.08 2.70 2.11 1.73 0.50 19.4Annual 1.48 3.44 1.88 2.84 1.51 1.98 1.28 0.50 14.9
TABLE V- A-1c 

Predicted 2015 PM2.5 at Compton Using the Speciated Modeling Attainment Test 

RRF (CAMx 2015/CAMx 2005)  NH4 NO3 SO4 OC EC OTR Q1 0.78 0.86 0.62 0.76 0.81 0.94 Q2 0.70 0.75 0.63 0.80 0.81 0.91 Q3 0.71 0.80 0.60 0.78 0.81 0.89 Q4 0.78 0.86 0.63 0.76 0.80 0.93 2005 Design Modified by MATES-III with Sandwich  NH4 NO3 SO4 OC EC OTR Water Blank Filter  Mass Q1 1.42 4.33 2.47 4.80 2.13 1.81 1.86 0.50 19.3Q2 1.30 3.11 3.78 0.68 0.90 2.16 2.16 0.50 14.6Q3 2.17 3.15 5.34 2.28 0.82 1.94 2.07 0.50 18.2Q4 2.76 5.63 2.69 3.60 3.23 2.44 2.03 0.50 22.8Annual 1.91 4.06 3.57 2.84 1.77 2.09 2.03 0.50 18.72015 Controlled PM2.5  NH4 NO3 SO4 OC EC OTR Water Blank SubtotaQ1 1.11 3.72 1.53 3.65 1.73 1.70 1.42 0.50 15.3Q2 0.91 2.33 2.38 0.54 0.73 1.97 1.41 0.50 10.7Q3 1.54 2.52 3.20 1.78 0.66 1.73 1.38 0.50 13.3Q4 2.15 4.84 1.69 2.74 2.58 2.27 1.62 0.50 18.4Annual 1.43 3.35 2.20 2.18 1.43 1.92 1.46 0.50 14.4
TABLE V- A-1d 

Predicted 2015 PM2.5 at Fontana Using the Speciated Modeling Attainment Test 

RRF (CAMx 2015/CAMx 2005)  NH4 NO3 SO4 OC EC OTR Q1 0.65 0.63 0.77 0.87 0.91 1.06 Q2 0.53 0.50 0.61 0.84 0.89 1.05 Q3 0.53 0.49 0.64 0.83 0.88 1.03 Q4 0.69 0.68 0.73 0.86 0.90 1.06 2005 Design Modified by MATES-III with Sandwich  NH4 NO3 SO4 OC EC OTR Water Blank Filter  Mass Q1 1.89 6.22 1.82 2.95 1.84 1.58 1.94 0.50 18.7Q2 2.24 5.93 3.30 1.63 1.46 2.16 1.94 0.50 19.1Q3 2.10 4.83 4.27 1.37 1.88 3.24 2.00 0.50 20.2Q4 3.53 8.29 2.40 0.55 2.51 2.67 2.72 0.50 23.1Annual 2.44 6.32 2.95 1.63 1.92 2.41 2.15 0.50 20.32015 Controlled PM2.5  NH4 NO3 SO4 OC EC OTR Water Blank SubtotaQ1 1.23 3.92 1.40 2.57 1.67 1.67 1.28 0.50 14.2Q2 1.19 2.97 2.01 1.37 1.30 2.27 1.05 0.50 12.6Q3 1.11 2.37 2.73 1.14 1.65 3.34 1.23 0.50 14.0Q4 2.44 5.64 1.75 0.47 2.26 2.83 2.22 0.50 18.1Annual 1.49 3.72 1.97 1.39 1.72 2.53 1.45 0.50 14.7
TABLE V- A-1e 

Predicted 2015 PM2.5 at Long Beach Using the Speciated Modeling Attainment Tes

RRF (CAMx 2015/CAMx 2005)  NH4 NO3 SO4 OC EC OTR Q1 0.75 0.81 0.62 0.73 0.79 0.84 Q2 0.68 0.72 0.6 0.74 0.77 0.79 Q3 0.68 0.77 0.57 0.72 0.76 0.76 Q4 0.75 0.85 0.61 0.73 0.78 0.83 2005 Design Modified by MATES-III with Sandwich  NH4 NO3 SO4 OC EC OTR Water Blank Filter  Mass Q1 1.37 4.19 2.55 3.74 1.83 1.88 1.92 0.50 17.9Q2 1.25 2.45 3.72 0.40 0.70 1.98 1.67 0.50 12.6Q3 1.95 2.53 4.75 1.26 0.87 2.08 1.73 0.50 15.6Q4 3.29 5.86 4.31 1.42 2.50 2.49 2.53 0.50 22.9Annual 1.97 3.76 3.83 1.71 1.48 2.11 1.96 0.50 17.32015 Controlled PM2.5  NH4 NO3 SO4 OC EC OTR Water Blank SubtotaQ1 1.03 3.39 1.58 2.73 1.45 1.44 1.49 0.50 13.6Q2 0.85 1.76 2.23 0.30 0.54 0.99 1.09 0.50 8.2Q3 1.33 1.95 2.71 0.91 0.66 1.14 1.19 0.50 10.3Q4 2.47 4.98 2.63 1.04 1.95 1.84 1.88 0.50 17.2Annual 1.42 3.02 2.29 1.24 1.15 1.35 1.41 0.50 12.3
TABLE V- A-1f 

Predicted 2015 PM2.5 at Los Angeles Using the Speciated Modeling Attainment Tes

RRF (CAMx 2015/CAMx 2005)  NH4 NO3 SO4 OC EC OTR Q1 0.74 0.76 0.69 0.76 0.81 0.99 Q2 0.67 0.69 0.62 0.79 0.81 0.98 Q3 0.69 0.74 0.59 0.78 0.80 0.96 Q4 0.78 0.82 0.67 0.77 0.81 0.99 2005 Design Modified by MATES-III with Sandwich  NH4 NO3 SO4 OC EC OTR Water Blank Filter  Mass Q1 1.78 6.25 2.44 2.54 1.98 1.69 2.55 0.50 19.7Q2 1.58 4.07 3.74 0.73 1.32 2.22 2.16 0.50 16.3Q3 2.95 4.52 5.11 0.98 1.45 2.22 2.47 0.50 20.2Q4 3.17 7.06 2.92 0.52 3.25 2.23 2.59 0.50 22.2Annual 2.37 5.48 3.55 1.19 2.00 2.09 2.44 0.50 19.62015 Controlled PM2.5  NH4 NO3 SO4 OC EC OTR Water Blank SubtotaQ1 1.32 4.75 1.68 1.93 1.60 1.67 1.90 0.50 15.3Q2 1.06 2.81 2.32 0.58 1.07 2.18 1.38 0.50 11.8Q3 2.04 3.34 3.01 0.76 1.16 2.13 1.58 0.50 14.5Q4 2.47 5.79 1.96 0.40 2.63 2.21 2.03 0.50 17.9Annual 1.72 4.17 2.24 0.92 1.62 2.05 1.72 0.50 14.9
TABLE V- A-1g 

Predicted 2015 PM2.5 at Rubidoux Using the Speciated Modeling Attainment Test 

RRF (CAMx 2015/CAMx 2005)  NH4 NO3 SO4 OC EC OTR Q1 0.63 0.61 0.72 0.86 0.89 0.94 Q2 0.49 0.46 0.58 0.81 0.87 0.90 Q3 0.48 0.45 0.59 0.80 0.85 0.90 Q4 0.66 0.65 0.69 0.85 0.89 0.94 2005 Design Modified by MATES-III with Sandwich  NH4 NO3 SO4 OC EC OTR Water Blank Filter  Mass Q1 1.79 6.51 1.93 4.18 2.00 1.81 2.44 0.50 21.1Q2 3.00 8.25 3.18 1.39 1.18 2.15 2.23 0.50 21.8Q3 2.94 7.29 4.30 1.62 1.17 2.50 2.27 0.50 22.6Q4 3.47 8.44 2.65 1.53 2.61 2.64 3.04 0.50 24.8Annual 2.80 7.62 3.02 2.18 1.74 2.28 2.50 0.50 22.62015 Controlled PM2.5  NH4 NO3 SO4 OC EC OTR Water Blank SubtotaQ1 1.13 3.97 1.39 3.59 1.78 1.70 1.52 0.50 15.5Q2 1.47 3.80 1.84 1.13 1.03 1.94 1.09 0.50 12.7Q3 1.41 3.28 2.54 1.30 0.99 2.25 1.19 0.50 13.4Q4 2.29 5.49 1.83 1.30 2.32 2.48 1.96 0.50 18.1Annual 1.57 4.13 1.90 1.83 1.53 2.09 1.44 0.50 15.0
TABLE V- A-1h 

Predicted 2015 PM2.5 at Wilmington Using the Speciated Modeling Attainment Tes

RRF (CAMx 2015/CAMx 2005)  NH4 NO3 SO4 OC EC OTR Q1 0.69 0.78 0.56 0.68 0.72 0.74 Q2 0.66 0.72 0.56 0.69 0.69 0.70 Q3 0.64 0.75 0.54 0.68 0.68 0.67 Q4 0.71 0.81 0.57 0.68 0.71 0.74 2005 Design Modified by MATES-III with Sandwich  NH4 NO3 SO4 OC EC OTR Water Blank Filter  Mass Q1 1.27 3.49 2.91 3.43 2.44 2.08 1.84 0.50 17.9Q2 1.13 2.02 3.84 0.38 0.92 2.14 1.74 0.50 12.6Q3 1.73 1.95 5.12 1.34 1.15 2.16 1.73 0.50 15.6Q4 2.62 5.02 3.88 2.47 3.37 2.79 2.27 0.50 22.9Annual 1.69 3.12 3.94 1.91 1.97 2.29 1.90 0.50 17.32015 Controlled PM2.5  NH4 NO3 SO4 OC EC OTR Water Blank SubtotaQ1 0.88 2.72 1.63 2.33 1.76 1.54 1.24 0.50 12.6Q2 0.75 1.45 2.15 0.26 0.63 1.50 0.93 0.50 8.1Q3 1.11 1.46 2.76 0.91 0.78 1.45 0.99 0.50 9.9Q4 1.86 4.07 2.21 1.68 2.39 2.06 1.63 0.50 16.4Annual 1.15 2.43 2.19 1.30 1.39 1.64 1.20 0.50 11.7
TABLE V- A-2 

Summary of Methodologies to Calculate 2015 24-Hour Average Design Value (μg/m3) 

Location 24-Hour Average Design Annual RRF to Design 

Anaheim 47.0 33.4 

Burbank 53.3 37.8 

Compton (Using Lynwood) 51.3 37.4 

Fontana 54.8 40.6 

Long Beach 44.6 30.8 

Los Angeles 60.7 43.1 

Rubidoux 64.8 42.8 

Wilmington (Using Long Beach) 44.6 26.6 
TABLE V-A-3a 

Anaheim 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.09 0.36 0.17 0.19 0.09 0.09 

Q2 0.09 0.29 0.36 0.06 0.05 0.14 

Q3 0.11 0.18 0.41 0.12 0.05 0.13 

Q4 0.14 0.32 0.17 0.14 0.12 0.11 

 

Design Q1 Q2 Q3 Q4 

2003 51.8 46.3 27.6 47.3 

2004 48.2 30.5 46.8 49.9 

2005 41.8 27.6 42.9 43.8 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.78 0.78 0.80 0.81 0.78 1.00 

Q2 0.67 0.68 0.83 0.72 0.80 0.90 

Q3 0.73 0.78 0.57 0.80 0.83 1.00 

Q4 0.72 0.74 0.67 0.84 0.89 1.03 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.6 12.3 5.6 11.3 4.1 9.7 5.6 

2004 3.3 11.4 5.2 10.5 3.8 9.1 5.2 

2005 2.9 9.9 4.5 9.1 3.3 7.8 4.5 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.6 14.5 7.0 8.0 3.6 4.7 4.4 0.5 46.4 

2004 3.4 13.5 6.6 7.4 3.4 4.3 4.1 0.5 43.2 

2005 2.9 11.7 5.7 6.4 2.9 3.8 3.5 0.5 37.5 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 2.7 8.2 9.2 11.5 2.3 5.0 6.4 

2004 1.8 5.4 6.0 7.5 1.5 3.3 4.2 

2005 1.6 4.9 5.4 6.8 1.4 3.0 3.8 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.8 9.1 13.8 2.0 1.9 5.8 5.8 0.5 41.7 

2004 1.8 6.0 9.1 1.3 1.2 3.8 3.8 0.5 27.6 

2005 1.7 5.4 8.2 1.2 1.1 3.5 3.4 0.5 25.1 

 

 
Q3 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.0 4.6 7.0 4.3 1.1 4.6 2.2 

2004 5.1 7.9 12.0 7.4 1.9 7.9 3.7 

2005 4.7 7.2 11.0 6.8 1.7 7.2 3.4 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.2 3.9 6.5 2.6 1.1 3.6 2.7 0.5 23.2 

2004 3.8 6.6 10.9 4.5 1.9 6.1 4.7 0.5 38.9 

2005 3.4 6.0 10.0 4.1 1.8 5.6 4.3 0.5 35.7 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.1 11.2 5.6 10.3 4.7 4.7 4.2 

2004 5.4 11.9 5.9 10.9 4.9 4.9 4.4 

2005 4.8 10.4 5.2 9.5 4.3 4.3 3.9 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.8 11.2 5.4 5.6 5.1 5.4 3.6 0.5 41.4 

2004 5.0 11.8 5.7 5.9 5.3 5.7 3.8 0.5 43.7 

2005 4.4 10.4 5.0 5.2 4.7 5.0 3.3 0.5 38.4 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 46.4 41.7 23.2 41.4 46.4 

2004 43.2 27.6 38.9 43.7 43.7 

2005 37.5 25.1 35.7 38.4 38.4 42.8 
TABLE V-A-3b 

Burbank 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.08 0.32 0.13 0.28 0.10 0.08 

Q2 0.10 0.28 0.27 0.13 0.07 0.14 

Q3 0.12 0.24 0.31 0.15 0.06 0.11 

Q4 0.13 0.35 0.14 0.16 0.13 0.09 

 

Design Q1 Q2 Q3 Q4 

2003 54.1 45.2 51.6 50.3 

2004 37.8 41.6 51.5 60.1 

2005 50.6 34.8 49.3 42.6 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.79 0.82 0.69 0.74 0.75 1.00 

Q2 0.67 0.73 0.57 0.76 0.80 1.00 

Q3 0.71 0.95 0.35 0.67 0.83 0.94 

Q4 0.79 0.85 0.62 0.78 0.83 1.00 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.3 13.4 5.4 11.3 4.8 9.6 4.8 

2004 3.0 9.3 3.7 7.8 3.4 6.7 3.4 

2005 4.0 12.5 5.0 10.5 4.5 9.0 4.5 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.4 14.2 4.9 11.2 4.1 4.3 3.6 0.5 46.2 

2004 2.4 9.9 3.4 7.8 2.8 3.0 2.5 0.5 32.4 

2005 3.2 13.3 4.5 10.5 3.8 4.0 3.4 0.5 43.2 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.0 10.3 8.0 10.7 3.1 4.0 4.5 

2004 3.7 9.5 7.4 9.9 2.9 3.7 4.1 

2005 3.1 7.9 6.2 8.2 2.4 3.1 3.4 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.0 9.2 7.0 4.5 2.5 6.3 3.6 0.5 36.7 

2004 2.8 8.5 6.4 4.1 2.3 5.8 3.4 0.5 33.8 

2005 2.3 7.1 5.4 3.4 1.9 4.9 2.8 0.5 28.4 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 6.1 10.7 11.2 8.7 3.1 5.1 5.6 

2004 6.1 10.7 11.2 8.7 3.1 5.1 5.6 

2005 5.9 10.2 10.7 8.3 2.9 4.9 5.4 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.4 11.8 5.6 5.2 2.6 5.3 3.7 0.5 39.0 

2004 4.4 11.7 5.6 5.2 2.6 5.3 3.7 0.5 39.0 

2005 4.2 11.2 5.3 5.0 2.5 5.1 3.5 0.5 37.3 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.5 13.4 4.0 12.0 6.0 4.5 4.5 

2004 6.6 16.1 4.8 14.3 7.2 5.4 5.4 

2005 4.6 11.4 3.4 10.1 5.1 3.8 3.8 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 5.2 15.0 4.4 6.3 5.4 4.5 3.8 0.5 45.0 

2004 6.2 17.9 5.2 7.5 6.5 5.4 4.5 0.5 53.7 

2005 4.4 12.7 3.7 5.3 4.6 3.8 3.2 0.5 38.2 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 46.2 36.7 39.0 45.0 46.2 

2004 32.4 33.8 39.0 53.7 53.7 

2005 43.2 28.4 37.3 38.2 43.2 47.7 
TABLE V-A-3c 

Compton/Lynwood 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.08 0.28 0.18 0.26 0.11 0.10 

Q2 0.09 0.28 0.36 0.05 0.06 0.15 

Q3 0.12 0.19 0.41 0.13 0.05 0.11 

Q4 0.12 0.30 0.16 0.16 0.14 0.11 

 

Design Q1 Q2 Q3 Q4 

2003 45.3 44.7 45.5 52.5 

2004 44.8 38.2 36.3 52.4 

2005 41.0 31.8 51.7 53.0 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.77 0.97 0.27 0.82 0.91 1.17 

Q2 0.85 0.48 2.22 0.60 0.57 0.68 

Q3 0.81 0.96 0.62 0.74 0.75 0.90 

Q4 0.76 0.87 0.54 0.80 0.82 0.93 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 2.7 9.4 5.4 10.3 4.5 8.5 4.5 

2004 2.7 9.3 5.3 10.2 4.4 8.4 4.4 

2005 2.4 8.5 4.9 9.3 4.1 7.7 4.1 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.6 12.4 2.2 9.5 4.7 5.1 2.5 0.5 39.5 

2004 2.6 12.3 2.2 9.4 4.6 5.0 2.5 0.5 39.0 

2005 2.4 11.2 2.0 8.6 4.2 4.6 2.3 0.5 35.8 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.5 8.4 9.7 9.7 2.7 4.9 4.9 

2004 3.0 7.2 8.3 8.3 2.3 4.1 4.1 

2005 2.5 5.9 6.9 6.9 1.9 3.4 3.4 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.5 6.0 36.1 1.3 1.6 4.7 12.4 0.5 66.1 

2004 3.0 5.1 30.9 1.1 1.4 4.0 10.6 0.5 56.5 

2005 2.5 4.2 25.7 0.9 1.2 3.3 8.8 0.5 47.2 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.0 7.7 12.2 6.3 1.8 6.8 5.0 

2004 3.9 6.1 9.7 5.0 1.4 5.4 3.9 

2005 5.6 8.7 13.8 7.2 2.0 7.7 5.6 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.5 8.1 11.5 4.3 1.6 4.5 5.1 0.5 40.1 

2004 3.6 6.5 9.2 3.4 1.3 3.6 4.1 0.5 32.1 

2005 5.1 9.2 13.1 4.9 1.8 5.1 5.8 0.5 45.5 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.2 13.0 4.7 11.4 6.2 5.7 4.7 

2004 5.2 13.0 4.7 11.4 6.2 5.7 4.7 

2005 5.3 13.1 4.7 11.6 6.3 5.8 4.7 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.9 13.7 4.6 6.8 6.2 5.3 3.7 0.5 45.7 

2004 4.9 13.7 4.6 6.7 6.2 5.3 3.7 0.5 45.6 

2005 5.0 13.8 4.7 6.8 6.3 5.4 3.7 0.5 46.1 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 39.5 66.1 40.1 45.7 66.1 

2004 39.0 56.5 32.1 45.6 56.5 

2005 35.8 47.2 45.5 46.1 47.2 56.6 
TABLE V-A-3d 

Fontana 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.10 0.41 0.14 0.16 0.10 0.09 

Q2 0.12 0.36 0.24 0.09 0.08 0.12 

Q3 0.11 0.27 0.29 0.07 0.10 0.16 

Q4 0.16 0.45 0.14 0.02 0.11 0.12 

 0.10 0.41 0.14 0.16 0.10 0.09 

 

Design Q1 Q2 Q3 Q4 

2003 53.6 48.8 46.6 55.7 

2004 62.6 45.5 49.9 48.5 

2005 48.2 43.7 38.4 43.0 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.66 0.65 0.67 0.80 1.00 1.00 

Q2 0.56 0.67 0.37 1.25 1.33 1.25 

Q3 0.56 0.58 0.58 0.79 1.00 1.06 

Q4 0.63 0.66 0.56 0.84 0.86 1.00 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.2 14.9 4.2 10.6 4.8 9.6 4.2 

2004 5.0 17.4 5.0 12.4 5.6 11.2 5.0 

2005 3.8 13.4 3.8 9.5 4.3 8.6 3.8 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.7 14.4 4.9 6.9 5.4 4.6 3.7 0.5 44.1 

2004 4.3 16.8 5.7 8.1 6.3 5.4 4.3 0.5 51.4 

2005 3.3 12.9 4.4 6.2 4.9 4.2 3.3 0.5 39.7 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.8 12.6 7.2 10.1 3.9 5.8 4.3 

2004 4.5 11.7 6.8 9.5 3.6 5.4 4.1 

2005 4.3 11.2 6.5 9.1 3.5 5.2 3.9 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.3 11.7 4.3 5.3 5.1 7.1 3.2 0.5 40.4 

2004 3.1 10.9 4.0 5.0 4.7 6.6 2.9 0.5 37.7 

2005 2.9 10.5 3.9 4.8 4.5 6.3 2.8 0.5 36.3 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.1 9.7 8.3 8.3 3.7 8.3 3.7 

2004 4.4 10.4 8.9 8.9 4.0 8.9 4.0 

2005 3.4 8.0 6.8 6.8 3.0 6.8 3.0 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.8 7.3 8.0 2.6 4.4 8.1 3.7 0.5 37.3 

2004 3.0 7.8 8.5 2.7 4.8 8.7 4.0 0.5 39.9 

2005 2.3 6.0 6.6 2.1 3.7 6.7 3.0 0.5 30.9 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 7.7 17.7 4.4 9.4 5.5 5.5 5.0 

2004 6.7 15.4 3.8 8.2 4.8 4.8 4.3 

2005 6.0 13.6 3.4 7.2 4.3 4.3 3.8 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 5.5 16.5 4.5 1.1 5.3 6.6 4.0 0.5 43.9 

2004 4.8 14.3 3.9 1.0 4.6 5.7 3.5 0.5 38.3 

2005 4.2 12.7 3.5 0.9 4.1 5.1 3.1 0.5 34.0 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 44.1 40.4 37.3 43.9 44.1 

2004 51.4 37.7 39.9 38.3 51.4 

2005 39.7 36.3 30.9 34.0 39.7 45.0 
TABLE V-A-3e 

Long Beach 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.08 0.30 0.20 0.21 0.10 0.11 

Q2 0.10 0.23 0.41 0.03 0.06 0.16 

Q3 0.13 0.17 0.43 0.08 0.06 0.14 

Q4 0.15 0.31 0.26 0.06 0.11 0.11 

 

Design Q1 Q2 Q3 Q4 

2003 46.5 42.9 36.9 47.4 

2004 45.8 32.9 34.6 45.9 

2005 37.3 27.7 46.1 43.2 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR Water 

Q1 0.81 0.82 0.75 0.79 0.87 0.89 0.81 

Q2 0.71 0.93 0.62 0.67 0.75 0.75 0.71 

Q3 0.70 0.95 0.58 0.68 0.75 0.77 0.70 

Q4 0.77 0.75 0.83 0.89 0.83 0.84 0.77 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 2.8 10.1 5.1 10.1 3.7 9.2 5.1 

2004 2.7 10.0 5.0 10.0 3.6 9.1 5.0 

2005 2.2 8.1 4.0 8.1 2.9 7.4 4.0 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.0 11.3 6.9 7.9 4.2 4.5 3.9 0.5 42.1 

2004 2.9 11.2 6.8 7.7 4.2 4.4 3.8 0.5 41.5 

2005 2.4 9.1 5.5 6.3 3.4 3.6 3.1 0.5 33.9 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.0 6.8 9.8 9.8 2.5 5.5 5.5 

2004 2.3 5.2 7.5 7.5 1.9 4.2 4.2 

2005 1.9 4.4 6.3 6.3 1.6 3.5 3.5 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 1.7 3.9 5.2 7.6 1.9 4.4 2.8 0.5 28.1 

2004 1.3 3.0 4.0 5.8 1.5 3.4 2.1 0.5 21.6 

2005 1.1 2.5 3.4 4.9 1.2 2.8 1.8 0.5 18.2 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.4 5.8 9.8 5.8 1.8 5.5 3.6 

2004 4.1 5.5 9.2 5.5 1.7 5.1 3.4 

2005 5.5 7.3 12.3 7.3 2.3 6.8 4.6 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.3 5.9 9.1 2.1 1.6 3.9 4.0 0.5 30.4 

2004 3.1 5.6 8.5 2.0 1.5 3.7 3.7 0.5 28.5 

2005 4.1 7.4 11.4 2.6 2.0 4.9 4.9 0.5 37.8 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 6.1 10.8 6.1 9.8 4.7 5.6 3.8 

2004 5.9 10.4 5.9 9.5 4.5 5.4 3.6 

2005 5.6 9.8 5.6 9.0 4.3 5.1 3.4 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 5.4 10.9 10.3 2.7 4.4 4.4 5.2 0.5 43.7 

2004 5.2 10.5 10.0 2.6 4.3 4.3 5.0 0.5 42.3 

2005 4.9 9.9 9.4 2.4 4.0 4.0 4.7 0.5 39.8 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 42.1 36.8 30.4 43.7 43.7 

2004 41.5 28.3 28.5 42.3 42.3 

2005 33.9 23.9 37.8 39.8 39.8 41.9 
TABLE V-A-3f 

Los Angeles 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.09 0.41 0.17 0.13 0.10 0.09 

Q2 0.10 0.31 0.32 0.05 0.08 0.14 

Q3 0.15 0.26 0.35 0.05 0.07 0.11 

Q4 0.15 0.40 0.18 0.02 0.15 0.10 

 

Design Q1 Q2 Q3 Q4 

2003 53.6 55.1 51.0 55.3 

2004 49.7 44.0 55.9 61.3 

2005 53.5 38.2 36.8 52.0 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.69 0.57 1.22 1.05 1.29 1.28 

Q2 0.76 0.83 0.55 0.78 0.83 0.94 

Q3 0.77 0.89 0.6 0.76 0.78 0.96 

Q4 0.84 0.87 0.7 0.79 0.82 1 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.7 13.3 5.3 11.2 4.8 9.0 5.8 

2004 3.4 12.3 4.9 10.3 4.4 8.4 5.4 

2005 3.7 13.3 5.3 11.1 4.8 9.0 5.8 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.4 12.6 11.3 7.4 7.1 6.0 5.4 0.5 53.8 

2004 3.2 11.7 10.4 6.9 6.6 5.6 5.0 0.5 49.9 

2005 3.4 12.6 11.2 7.4 7.1 6.0 5.4 0.5 53.7 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.4 10.9 10.4 14.2 3.8 4.9 6.0 

2004 3.5 8.7 8.3 11.3 3.0 3.9 4.8 

2005 3.0 7.5 7.2 9.8 2.6 3.4 4.1 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.2 14.1 9.7 2.0 3.8 7.3 5.2 0.5 46.8 

2004 3.3 11.3 7.8 1.6 3.0 5.8 4.2 0.5 37.5 

2005 2.9 9.8 6.7 1.4 2.6 5.0 3.6 0.5 32.6 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 6.6 9.6 10.6 8.6 3.0 7.6 5.1 

2004 7.2 10.5 11.6 9.4 3.3 8.3 5.5 

2005 4.7 6.9 7.6 6.2 2.2 5.4 3.6 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 5.9 11.9 10.8 1.9 2.9 5.5 5.5 0.5 44.9 

2004 6.4 13.0 11.8 2.1 3.2 6.0 6.0 0.5 49.2 

2005 4.2 8.6 7.8 1.4 2.1 4.0 4.0 0.5 32.6 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 6.0 14.2 4.9 13.2 6.6 4.9 4.9 

2004 6.7 15.8 5.5 14.6 7.3 5.5 5.5 

2005 5.7 13.4 4.6 12.4 6.2 4.6 4.6 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 6.8 19.1 7.1 1.0 6.8 5.7 5.3 0.5 52.2 

2004 7.5 21.1 7.8 1.2 7.5 6.3 5.9 0.5 57.8 

2005 6.4 17.9 6.6 1.0 6.4 5.3 5.0 0.5 49.1 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 53.8 46.8 44.9 52.2 53.8 

2004 49.9 37.5 49.2 57.8 57.8 

2005 53.7 32.6 32.6 49.1 53.7 55.1 
TABLE V-A-3g 

Rubidoux 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.09 0.32 0.09 0.20 0.10 0.09 

Q2 0.14 0.39 0.15 0.07 0.06 0.10 

Q3 0.13 0.33 0.20 0.07 0.05 0.11 

Q4 0.14 0.35 0.11 0.06 0.11 0.11 

 

Design Q1 Q2 Q3 Q4 

2003 72.9 61.6 60.5 66.0 

2004 59.5 60.5 55.3 76.6 

2005 56.6 55.8 47.0 49.5 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.69 0.66 0.70 0.80 0.86 0.91 

Q2 0.56 0.58 0.42 0.81 1.00 1.06 

Q3 0.52 0.52 0.50 0.79 0.80 0.89 

Q4 0.54 0.56 0.50 0.79 0.80 0.89 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.1 18.8 5.8 15.2 6.5 14.5 7.2 

2004 4.1 15.3 4.7 12.4 5.3 11.8 5.9 

2005 3.9 14.6 4.5 11.8 5.0 11.2 5.6 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.5 15.2 4.7 11.7 6.3 6.0 3.8 0.5 52.7 

2004 3.7 12.4 3.9 9.5 5.1 4.9 3.1 0.5 43.1 

2005 3.5 11.8 3.7 9.1 4.9 4.6 3.0 0.5 41.0 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 7.3 19.6 7.9 11.0 3.1 4.9 7.3 

2004 7.2 19.2 7.8 10.8 3.0 4.8 7.2 

2005 6.6 17.7 7.2 10.0 2.8 4.4 6.6 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.8 13.8 3.9 3.5 3.7 6.5 3.4 0.5 40.1 

2004 4.7 13.5 3.8 3.4 3.6 6.4 3.4 0.5 39.4 

2005 4.4 12.5 3.5 3.2 3.3 5.9 3.1 0.5 36.4 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 8.4 16.8 9.0 8.4 2.4 8.4 6.6 

2004 7.7 15.3 8.2 7.7 2.2 7.7 6.0 

2005 6.5 13.0 7.0 6.5 1.9 6.5 5.1 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.1 10.4 5.9 3.3 2.4 5.9 3.6 0.5 36.1 

2004 3.7 9.5 5.4 3.1 2.2 5.4 3.3 0.5 33.1 

2005 3.2 8.1 4.6 2.6 1.9 4.6 2.8 0.5 28.2 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 9.2 18.3 4.6 14.4 7.2 7.2 4.6 

2004 10.7 21.3 5.3 16.7 8.4 8.4 5.3 

2005 6.9 13.7 3.4 10.8 5.4 5.4 3.4 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 5.0 12.8 3.6 3.1 5.8 6.5 3.3 0.5 40.5 

2004 5.8 14.8 4.2 3.6 6.7 7.5 3.8 0.5 47.0 

2005 3.7 9.6 2.7 2.3 4.4 4.8 2.4 0.5 30.5 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 52.7 40.1 36.1 40.5 52.7 

2004 43.1 39.4 33.1 47.0 47.0 

2005 41.0 36.4 28.2 30.5 41.0 46.9 
TABLE V-A-3h 

Wilmington 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.07 0.25 0.23 0.20 0.14 0.12 

Q2 0.09 0.20 0.43 0.03 0.08 0.18 

Q3 0.11 0.12 0.46 0.09 0.08 0.14 

Q4 0.12 0.26 0.24 0.11 0.15 0.12 

 

Design Q1 Q2 Q3 Q4 

2003 46.5 42.9 36.9 47.4 

2004 45.8 32.9 34.6 45.9 

2005 37.3 27.7 46.1 43.2 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.74 0.78 0.67 0.77 0.71 0.78 

Q2 0.50 1.46 0.24 0.70 0.67 0.76 

Q3 0.60 1.00 0.47 0.65 0.57 0.68 

Q4 0.74 1.02 0.56 0.69 0.75 0.78 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.4 11.4 10.5 9.1 6.5 5.5 5.1 

2004 3.3 11.2 10.4 9.0 6.4 5.5 5.0 

2005 2.7 9.2 8.4 7.3 5.2 4.4 4.1 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.5 8.9 7.0 7.0 4.6 4.3 3.6 0.5 38.5 

2004 2.5 8.8 6.9 6.9 4.5 4.3 3.5 0.5 37.9 

2005 2.0 7.1 5.7 5.6 3.7 3.5 2.9 0.5 31.0 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.0 8.4 18.4 1.3 3.2 7.5 7.2 

2004 3.1 6.5 14.1 1.0 2.5 5.8 5.5 

2005 2.6 5.4 11.9 0.9 2.1 4.9 4.7 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.0 12.3 4.4 0.9 2.2 5.7 3.1 0.5 31.1 

2004 1.5 9.4 3.4 0.7 1.7 4.4 2.4 0.5 24.0 

2005 1.3 7.9 2.8 0.6 1.4 3.7 2.0 0.5 20.3 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.2 4.5 16.9 3.3 2.8 5.3 6.3 

2004 3.9 4.2 15.9 3.1 2.6 4.9 5.9 

2005 5.3 5.6 21.1 4.1 3.5 6.6 7.9 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.5 4.5 7.9 2.1 1.6 3.6 3.3 0.5 26.1 

2004 2.4 4.2 7.5 2.0 1.5 3.4 3.1 0.5 24.5 

2005 3.2 5.6 9.9 2.6 2.0 4.5 4.2 0.5 32.5 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.5 12.5 11.1 5.2 7.1 5.9 5.6 

2004 5.4 12.1 10.8 5.1 6.9 5.7 5.5 

2005 5.1 11.4 10.2 4.8 6.5 5.4 5.1 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.1 12.7 6.2 3.6 5.3 4.6 4.0 0.5 41.1 

2004 4.0 12.3 6.0 3.5 5.2 4.5 3.8 0.5 39.8 

2005 3.7 11.6 5.7 3.3 4.9 4.2 3.6 0.5 37.5 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 38.5 31.1 26.1 41.1 41.1 

2004 37.9 24.0 24.5 39.8 39.8 

2005 31.0 20.3 32.5 37.5 37.5 39.5 
TABLE V-A-4a 

Alternate Anaheim 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.09 0.36 0.17 0.19 0.09 0.09 

Q2 0.09 0.29 0.36 0.06 0.05 0.14 

Q3 0.11 0.18 0.41 0.12 0.05 0.13 

Q4 0.14 0.32 0.17 0.14 0.12 0.11 

 

Design Q1 Q2 Q3 Q4 

2003 51.8 46.3 27.6 47.3 

2004 48.2 30.5 46.8 49.9 

2005 41.8 27.6 42.9 43.8 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.70 0.70 0.71 0.80 0.86 1.03 

Q2 0.61 0.59 0.62 0.85 0.86 1.02 

Q3 0.63 0.65 0.58 0.82 0.85 1.00 

Q4 0.73 0.75 0.67 0.80 0.86 1.02 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.6 12.3 5.6 11.3 4.1 9.7 5.6 

2004 3.3 11.4 5.2 10.5 3.8 9.1 5.2 

2005 2.9 9.9 4.5 9.1 3.3 7.8 4.5 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.3 13.1 6.3 7.9 4.0 4.8 3.9 0.5 43.7 

2004 3.0 12.1 5.8 7.3 3.7 4.5 3.6 0.5 40.7 

2005 2.6 10.5 5.0 6.4 3.2 3.9 3.2 0.5 35.3 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 2.7 8.2 9.2 11.5 2.3 5.0 6.4 

2004 1.8 5.4 6.0 7.5 1.5 3.3 4.2 

2005 1.6 4.9 5.4 6.8 1.4 3.0 3.8 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.5 7.9 10.3 2.4 2.0 6.6 4.5 0.5 36.7 

2004 1.7 5.2 6.8 1.6 1.3 4.4 3.0 0.5 24.4 

2005 1.5 4.7 6.2 1.4 1.2 3.9 2.7 0.5 22.1 

 

 
Q3 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.0 4.6 7.0 4.3 1.1 4.6 2.2 

2004 5.1 7.9 12.0 7.4 1.9 7.9 3.7 

2005 4.7 7.2 11.0 6.8 1.7 7.2 3.4 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 1.9 3.2 6.6 2.7 1.2 3.6 2.7 0.5 22.4 

2004 3.2 5.5 11.1 4.6 2.0 6.1 4.5 0.5 37.6 

2005 3.0 5.0 10.2 4.2 1.8 5.6 4.1 0.5 34.5 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.1 11.2 5.6 10.3 4.7 4.7 4.2 

2004 5.4 11.9 5.9 10.9 4.9 4.9 4.4 

2005 4.8 10.4 5.2 9.5 4.3 4.3 3.9 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.8 11.4 5.4 5.3 4.9 5.3 3.6 0.5 41.2 

2004 5.1 12.0 5.7 5.6 5.1 5.6 3.8 0.5 43.4 

2005 4.5 10.5 5.0 4.9 4.5 4.9 3.4 0.5 38.2 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 43.7 36.7 22.4 41.2 43.7 

2004 40.7 24.4 37.6 43.4 43.4 

2005 35.3 22.1 34.5 38.2 38.2 41.8 
TABLE V-A-4b 

Alternate Burbank 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.08 0.32 0.13 0.28 0.10 0.08 

Q2 0.10 0.28 0.27 0.13 0.07 0.14 

Q3 0.12 0.24 0.31 0.15 0.06 0.11 

Q4 0.13 0.35 0.14 0.16 0.13 0.09 

 

Design Q1 Q2 Q3 Q4 

2003 54.1 45.2 51.6 50.3 

2004 37.8 41.6 51.5 60.1 

2005 50.6 34.8 49.3 42.6 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.70 0.69 0.72 0.80 0.85 1.01 

Q2 0.63 0.62 0.62 0.83 0.83 1.00 

Q3 0.64 0.65 0.60 0.81 0.83 0.97 

Q4 0.76 0.77 0.71 0.81 0.84 1.01 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.3 13.4 5.4 11.3 4.8 9.6 4.8 

2004 3.0 9.3 3.7 7.8 3.4 6.7 3.4 

2005 4.0 12.5 5.0 10.5 4.5 9.0 4.5 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.0 11.9 5.1 12.1 4.6 4.4 3.4 0.5 45.0 

2004 2.1 8.3 3.5 8.5 3.2 3.1 2.4 0.5 31.6 

2005 2.8 11.2 4.7 11.3 4.3 4.1 3.2 0.5 42.1 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.0 10.3 8.0 10.7 3.1 4.0 4.5 

2004 3.7 9.5 7.4 9.9 2.9 3.7 4.1 

2005 3.1 7.9 6.2 8.2 2.4 3.1 3.4 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.8 7.8 7.6 4.9 2.6 6.3 3.6 0.5 36.2 

2004 2.6 7.2 7.0 4.5 2.4 5.8 3.4 0.5 33.4 

2005 2.2 6.0 5.8 3.8 2.0 4.9 2.8 0.5 28.0 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 6.1 10.7 11.2 8.7 3.1 5.1 5.6 

2004 6.1 10.7 11.2 8.7 3.1 5.1 5.6 

2005 5.9 10.2 10.7 8.3 2.9 4.9 5.4 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.0 8.0 9.6 6.3 2.6 5.5 4.4 0.5 40.9 

2004 4.0 8.0 9.6 6.3 2.6 5.5 4.4 0.5 40.8 

2005 3.8 7.7 9.2 6.0 2.5 5.3 4.2 0.5 39.1 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.5 13.4 4.0 12.0 6.0 4.5 4.5 

2004 6.6 16.1 4.8 14.3 7.2 5.4 5.4 

2005 4.6 11.4 3.4 10.1 5.1 3.8 3.8 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 5.0 13.6 5.0 6.5 5.5 4.6 3.8 0.5 44.4 

2004 5.9 16.2 6.0 7.8 6.6 5.5 4.5 0.5 52.9 

2005 4.2 11.5 4.2 5.5 4.7 3.9 3.2 0.5 37.7 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 45.0 36.2 40.9 44.4 45.0 

2004 31.6 33.4 40.8 52.9 52.9 

2005 42.1 28.0 39.1 37.7 42.1 46.7 
TABLE V-A-4c 

Alternate Compton/Lynwood 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.08 0.28 0.18 0.26 0.11 0.10 

Q2 0.09 0.28 0.36 0.05 0.06 0.15 

Q3 0.12 0.19 0.41 0.13 0.05 0.11 

Q4 0.12 0.30 0.16 0.16 0.14 0.11 

 

Design Q1 Q2 Q3 Q4 

2003 45.3 44.7 45.5 52.5 

2004 44.8 38.2 36.3 52.4 

2005 41.0 31.8 51.7 53.0 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.78 0.86 0.62 0.76 0.81 0.94 

Q2 0.70 0.75 0.63 0.80 0.81 0.91 

Q3 0.71 0.80 0.60 0.78 0.81 0.89 

Q4 0.78 0.86 0.63 0.76 0.80 0.93 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 2.7 9.4 5.4 10.3 4.5 8.5 4.5 

2004 2.7 9.3 5.3 10.2 4.4 8.4 4.4 

2005 2.4 8.5 4.9 9.3 4.1 7.7 4.1 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.7 11.0 5.0 8.8 4.2 4.1 3.2 0.5 39.4 

2004 2.6 10.9 5.0 8.7 4.1 4.1 3.2 0.5 39.0 

2005 2.4 10.0 4.5 8.0 3.8 3.7 2.9 0.5 35.7 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.5 8.4 9.7 9.7 2.7 4.9 4.9 

2004 3.0 7.2 8.3 8.3 2.3 4.1 4.1 

2005 2.5 5.9 6.9 6.9 1.9 3.4 3.4 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.9 9.3 10.2 1.7 2.3 6.2 4.7 0.5 37.9 

2004 2.5 8.0 8.8 1.5 2.0 5.3 4.0 0.5 32.4 

2005 2.1 6.6 7.3 1.2 1.6 4.4 3.3 0.5 27.1 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.0 7.7 12.2 6.3 1.8 6.8 5.0 

2004 3.9 6.1 9.7 5.0 1.4 5.4 3.9 

2005 5.6 8.7 13.8 7.2 2.0 7.7 5.6 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.9 6.8 11.1 4.6 1.7 4.4 4.8 0.5 37.8 

2004 3.1 5.4 8.9 3.6 1.4 3.5 3.8 0.5 30.3 

2005 4.5 7.7 12.7 5.2 1.9 5.0 5.4 0.5 42.9 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.2 13.0 4.7 11.4 6.2 5.7 4.7 

2004 5.2 13.0 4.7 11.4 6.2 5.7 4.7 

2005 5.3 13.1 4.7 11.6 6.3 5.8 4.7 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 5.1 13.5 5.4 6.4 6.1 5.3 3.9 0.5 46.2 

2004 5.0 13.5 5.4 6.4 6.1 5.3 3.9 0.5 46.1 

2005 5.1 13.6 5.5 6.5 6.1 5.4 4.0 0.5 46.6 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 39.4 37.9 37.8 46.2 46.2 

2004 39.0 32.4 30.3 46.1 46.1 

2005 35.7 27.1 42.9 46.6 46.6 46.3 
TABLE V-A-4d 

Alternate Fontana 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.10 0.41 0.14 0.16 0.10 0.09 

Q2 0.12 0.36 0.24 0.09 0.08 0.12 

Q3 0.11 0.27 0.29 0.07 0.10 0.16 

Q4 0.16 0.45 0.14 0.02 0.11 0.12 

 0.10 0.41 0.14 0.16 0.10 0.09 

 

Design Q1 Q2 Q3 Q4 

2003 53.6 48.8 46.6 55.7 

2004 62.6 45.5 49.9 48.5 

2005 48.2 43.7 38.4 43.0 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.65 0.63 0.77 0.87 0.91 1.06 

Q2 0.53 0.50 0.61 0.84 0.89 1.05 

Q3 0.53 0.49 0.64 0.83 0.88 1.03 

Q4 0.69 0.68 0.73 0.86 0.90 1.06 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.2 14.9 4.2 10.6 4.8 9.6 4.2 

2004 5.0 17.4 5.0 12.4 5.6 11.2 5.0 

2005 3.8 13.4 3.8 9.5 4.3 8.6 3.8 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.6 13.9 5.6 7.5 4.9 4.9 3.9 0.5 44.9 

2004 4.2 16.2 6.5 8.8 5.7 5.8 4.5 0.5 52.3 

2005 3.2 12.5 5.0 6.8 4.4 4.4 3.5 0.5 40.4 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.8 12.6 7.2 10.1 3.9 5.8 4.3 

2004 4.5 11.7 6.8 9.5 3.6 5.4 4.1 

2005 4.3 11.2 6.5 9.1 3.5 5.2 3.9 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.1 8.7 7.1 3.6 3.4 5.9 3.7 0.5 36.0 

2004 2.9 8.2 6.7 3.3 3.2 5.5 3.4 0.5 33.6 

2005 2.8 7.8 6.4 3.2 3.0 5.3 3.3 0.5 32.3 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.1 9.7 8.3 8.3 3.7 8.3 3.7 

2004 4.4 10.4 8.9 8.9 4.0 8.9 4.0 

2005 3.4 8.0 6.8 6.8 3.0 6.8 3.0 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.6 6.1 8.8 2.7 3.9 7.9 3.8 0.5 36.3 

2004 2.8 6.6 9.4 2.9 4.2 8.5 4.1 0.5 38.9 

2005 2.2 5.1 7.2 2.2 3.2 6.5 3.1 0.5 30.0 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 7.7 17.7 4.4 9.4 5.5 5.5 5.0 

2004 6.7 15.4 3.8 8.2 4.8 4.8 4.3 

2005 6.0 13.6 3.4 7.2 4.3 4.3 3.8 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 6.0 17.0 5.8 1.2 5.6 7.0 4.6 0.5 47.5 

2004 5.2 14.8 5.1 1.0 4.8 6.1 4.0 0.5 41.5 

2005 4.6 13.1 4.5 0.9 4.3 5.4 3.5 0.5 36.8 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 44.9 36.0 36.3 47.5 47.5 

2004 52.3 33.6 38.9 41.5 52.3 

2005 40.4 32.3 30.0 36.8 40.4 46.7 
TABLE V-A-4e 

Alternate Long Beach 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.08 0.30 0.20 0.21 0.10 0.11 

Q2 0.10 0.23 0.41 0.03 0.06 0.16 

Q3 0.13 0.17 0.43 0.08 0.06 0.14 

Q4 0.15 0.31 0.26 0.06 0.11 0.11 

 

Design Q1 Q2 Q3 Q4 

2003 46.5 42.9 36.9 47.4 

2004 45.8 32.9 34.6 45.9 

2005 37.3 27.7 46.1 43.2 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR Water 

Q1 0.75 0.81 0.62 0.73 0.79 0.84 0.75 

Q2 0.68 0.72 0.6 0.74 0.77 0.79 0.68 

Q3 0.68 0.77 0.57 0.72 0.76 0.76 0.68 

Q4 0.75 0.85 0.61 0.73 0.78 0.83 0.75 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 2.8 10.1 5.1 10.1 3.7 9.2 5.1 

2004 2.7 10.0 5.0 10.0 3.6 9.1 5.0 

2005 2.2 8.1 4.0 8.1 2.9 7.4 4.0 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.7 11.2 5.7 7.3 3.8 4.2 3.5 0.5 38.9 

2004 2.7 11.0 5.6 7.2 3.8 4.1 3.4 0.5 38.4 

2005 2.2 9.0 4.6 5.8 3.1 3.4 2.8 0.5 31.3 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.0 6.8 9.8 9.8 2.5 5.5 5.5 

2004 2.3 5.2 7.5 7.5 1.9 4.2 4.2 

2005 1.9 4.4 6.3 6.3 1.6 3.5 3.5 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.0 7.1 10.7 1.0 1.9 5.5 4.5 0.5 34.3 

2004 2.3 5.4 8.2 0.8 1.5 4.2 3.5 0.5 26.4 

2005 1.9 4.6 6.9 0.7 1.2 3.6 2.9 0.5 22.3 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.4 5.8 9.8 5.8 1.8 5.5 3.6 

2004 4.1 5.5 9.2 5.5 1.7 5.1 3.4 

2005 5.5 7.3 12.3 7.3 2.3 6.8 4.6 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.2 4.8 8.9 2.2 1.6 3.8 3.8 0.5 28.9 

2004 3.0 4.5 8.4 2.1 1.5 3.6 3.5 0.5 27.1 

2005 4.0 6.0 11.2 2.8 2.0 4.8 4.7 0.5 36.0 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 6.1 10.8 6.1 9.8 4.7 5.6 3.8 

2004 5.9 10.4 5.9 9.5 4.5 5.4 3.6 

2005 5.6 9.8 5.6 9.0 4.3 5.1 3.4 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 5.2 12.3 7.6 2.2 4.1 4.4 4.5 0.5 40.8 

2004 5.1 11.9 7.3 2.1 4.0 4.2 4.3 0.5 39.5 

2005 4.8 11.2 6.9 2.0 3.8 4.0 4.1 0.5 37.2 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 38.9 34.3 28.9 40.8 40.8 

2004 38.4 26.4 27.1 39.5 39.5 

2005 31.3 22.3 36.0 37.2 37.2 39.1 
TABLE V-A-4f 

Alternate Los Angeles 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.09 0.41 0.17 0.13 0.10 0.09 

Q2 0.10 0.31 0.32 0.05 0.08 0.14 

Q3 0.15 0.26 0.35 0.05 0.07 0.11 

Q4 0.15 0.40 0.18 0.02 0.15 0.10 

 

Design Q1 Q2 Q3 Q4 

2003 53.6 55.1 51.0 55.3 

2004 49.7 44.0 55.9 61.3 

2005 53.5 38.2 36.8 52.0 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.74 0.76 0.69 0.76 0.81 0.99 

Q2 0.67 0.69 0.62 0.79 0.81 0.98 

Q3 0.69 0.74 0.59 0.78 0.80 0.96 

Q4 0.78 0.82 0.67 0.77 0.81 0.99 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.7 13.3 5.3 11.2 4.8 9.0 5.8 

2004 3.4 12.3 4.9 10.3 4.4 8.4 5.4 

2005 3.7 13.3 5.3 11.1 4.8 9.0 5.8 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.7 16.8 6.4 5.4 4.5 4.7 4.4 0.5 46.3 

2004 3.4 15.6 5.9 5.0 4.1 4.3 4.1 0.5 43.0 

2005 3.7 16.8 6.4 5.4 4.5 4.7 4.4 0.5 46.2 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.4 10.9 10.4 14.2 3.8 4.9 6.0 

2004 3.5 8.7 8.3 11.3 3.0 3.9 4.8 

2005 3.0 7.5 7.2 9.8 2.6 3.4 4.1 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.7 11.8 11.0 2.0 3.7 7.6 5.3 0.5 45.5 

2004 2.9 9.4 8.7 1.6 3.0 6.0 4.2 0.5 36.4 

2005 2.6 8.1 7.6 1.4 2.6 5.3 3.7 0.5 31.7 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 6.6 9.6 10.6 8.6 3.0 7.6 5.1 

2004 7.2 10.5 11.6 9.4 3.3 8.3 5.5 

2005 4.7 6.9 7.6 6.2 2.2 5.4 3.6 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 5.3 9.9 10.6 2.0 3.0 5.5 5.1 0.5 41.9 

2004 5.8 10.8 11.6 2.2 3.3 6.0 5.6 0.5 45.9 

2005 3.8 7.1 7.6 1.4 2.2 4.0 3.7 0.5 30.4 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 6.0 14.2 4.9 13.2 6.6 4.9 4.9 

2004 6.7 15.8 5.5 14.6 7.3 5.5 5.5 

2005 5.7 13.4 4.6 12.4 6.2 4.6 4.6 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 6.3 18.0 6.8 1.0 6.7 5.6 5.0 0.5 49.9 

2004 7.0 19.9 7.5 1.1 7.4 6.2 5.6 0.5 55.2 

2005 5.9 16.9 6.4 1.0 6.3 5.3 4.7 0.5 46.9 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 46.3 45.5 41.9 49.9 49.9 

2004 43.0 36.4 45.9 55.2 55.2 

2005 46.2 31.7 30.4 46.9 46.9 50.7 
TABLE V-A-4g 

Alternate Rubidoux 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.09 0.32 0.09 0.20 0.10 0.09 

Q2 0.14 0.39 0.15 0.07 0.06 0.10 

Q3 0.13 0.33 0.20 0.07 0.05 0.11 

Q4 0.14 0.35 0.11 0.06 0.11 0.11 

 

Design Q1 Q2 Q3 Q4 

2003 72.9 61.6 60.5 66.0 

2004 59.5 60.5 55.3 76.6 

2005 56.6 55.8 47.0 49.5 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.63 0.61 0.72 0.86 0.89 0.94 

Q2 0.49 0.46 0.58 0.81 0.87 0.90 

Q3 0.48 0.45 0.59 0.80 0.85 0.90 

Q4 0.66 0.65 0.69 0.85 0.89 0.94 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.1 18.8 5.8 15.2 6.5 14.5 7.2 

2004 4.1 15.3 4.7 12.4 5.3 11.8 5.9 

2005 3.9 14.6 4.5 11.8 5.0 11.2 5.6 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.1 14.0 4.9 12.5 6.5 6.2 3.7 0.5 52.4 

2004 3.4 11.4 4.0 10.2 5.3 5.0 3.0 0.5 42.9 

2005 3.2 10.9 3.8 9.7 5.0 4.8 2.9 0.5 40.8 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 7.3 19.6 7.9 11.0 3.1 4.9 7.3 

2004 7.2 19.2 7.8 10.8 3.0 4.8 7.2 

2005 6.6 17.7 7.2 10.0 2.8 4.4 6.6 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 4.2 10.9 5.3 3.5 3.2 5.5 3.5 0.5 36.7 

2004 4.2 10.7 5.2 3.4 3.2 5.4 3.4 0.5 36.1 

2005 3.8 9.9 4.8 3.2 2.9 5.0 3.2 0.5 33.3 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 8.4 16.8 9.0 8.4 2.4 8.4 6.6 

2004 7.7 15.3 8.2 7.7 2.2 7.7 6.0 

2005 6.5 13.0 7.0 6.5 1.9 6.5 5.1 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.8 9.0 7.0 3.4 2.6 6.0 3.7 0.5 35.9 

2004 3.5 8.2 6.4 3.1 2.4 5.5 3.4 0.5 32.8 

2005 2.9 7.0 5.4 2.6 2.0 4.7 2.9 0.5 28.0 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 9.2 18.3 4.6 14.4 7.2 7.2 4.6 

2004 10.7 21.3 5.3 16.7 8.4 8.4 5.3 

2005 6.9 13.7 3.4 10.8 5.4 5.4 3.4 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 6.1 14.8 5.0 3.4 6.5 6.8 4.1 0.5 47.1 

2004 7.1 17.2 5.8 3.9 7.5 7.9 4.7 0.5 54.6 

2005 4.6 11.1 3.7 2.5 4.8 5.1 3.0 0.5 35.5 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 52.4 36.7 35.9 47.1 52.4 

2004 42.9 36.1 32.8 54.6 54.6 

2005 40.8 33.3 28.0 35.5 40.8 49.3 
TABLE V-A-4h 

Alternate Wilmington 24-Hour 2015 Design Value Estimation 

 

Split NH4 NO3 SO4 OC EC OTR 

Q1 0.07 0.25 0.23 0.20 0.14 0.12 

Q2 0.09 0.20 0.43 0.03 0.08 0.18 

Q3 0.11 0.12 0.46 0.09 0.08 0.14 

Q4 0.12 0.26 0.24 0.11 0.15 0.12 

 

Design Q1 Q2 Q3 Q4 

2003 46.5 42.9 36.9 47.4 

2004 45.8 32.9 34.6 45.9 

2005 37.3 27.7 46.1 43.2 

 

Top-25 

Percentile 

RRF NH4 NO3 SO4 OC EC OTR 

Q1 0.69 0.78 0.56 0.68 0.72 0.74 

Q2 0.66 0.72 0.56 0.69 0.69 0.70 

Q3 0.64 0.75 0.54 0.68 0.68 0.67 

Q4 0.71 0.81 0.57 0.68 0.71 0.74 

 

Q1 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 3.4 11.4 10.5 9.1 6.5 5.5 5.1 

2004 3.3 11.2 10.4 9.0 6.4 5.5 5.0 

2005 2.7 9.2 8.4 7.3 5.2 4.4 4.1 

 

Q1 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.3 8.9 5.9 6.2 4.7 4.1 3.2 0.5 35.8 

2004 2.3 8.8 5.8 6.1 4.6 4.0 3.1 0.5 35.3 

2005 1.9 7.1 4.7 5.0 3.8 3.3 2.6 0.5 28.8 

 

Q2 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.0 8.4 18.4 1.3 3.2 7.5 7.2 

2004 3.1 6.5 14.1 1.0 2.5 5.8 5.5 

2005 2.6 5.4 11.9 0.9 2.1 4.9 4.7 

 

Q2 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.6 6.1 10.3 0.9 2.2 5.3 4.3 0.5 32.2 

2004 2.0 4.6 7.9 0.7 1.7 4.0 3.3 0.5 24.8 

2005 1.7 3.9 6.6 0.6 1.4 3.4 2.7 0.5 21.0 

 

Q3 Components 
Year NH4 NO3 SO4 OC EC OTR Water 

2003 4.2 4.5 16.9 3.3 2.8 5.3 6.3 

2004 3.9 4.2 15.9 3.1 2.6 4.9 5.9 

2005 5.3 5.6 21.1 4.1 3.5 6.6 7.9 

 

Q3 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 2.7 3.4 9.1 2.2 1.9 3.5 3.6 0.5 26.9 

2004 2.5 3.2 8.6 2.1 1.8 3.3 3.4 0.5 25.3 

2005 3.4 4.2 11.4 2.8 2.4 4.4 4.5 0.5 33.5 

 

Q4 Components 

Year NH4 NO3 SO4 OC EC OTR Water 

2003 5.5 12.5 11.1 5.2 7.1 5.9 5.6 

2004 5.4 12.1 10.8 5.1 6.9 5.7 5.5 

2005 5.1 11.4 10.2 4.8 6.5 5.4 5.1 

 

Q4 2015 Estimates 

Year NH4 NO3 SO4 OC EC OTR Water Blank Mass

2003 3.9 10.1 6.4 3.6 5.1 4.4 3.7 0.5 37.6 

2004 3.8 9.8 6.2 3.4 4.9 4.2 3.6 0.5 36.4 

2005 3.6 9.2 5.8 3.2 4.6 4.0 3.3 0.5 34.3 

 

Weighted 2015 Design Value 

Year Q1 Q2 Q3 Q4 Max FDV 

2003 35.8 32.2 26.9 37.6 37.6 

2004 35.3 24.8 25.3 36.4 36.4 

2005 28.8 21.0 33.5 34.3 34.3 36.1 
TABLE V-A-5a 

2015 Estimated Reduction Ratios to be Applied Anaheim 24-Hour PM2.5 Design 

RRF NH4 NO3 SO4 OC EC OTR

Q1 0.78 0.78 0.80 0.81 0.78 1.00 Q2 0.67 0.68 0.83 0.72 0.80 0.90 Q3 0.73 0.78 0.57 0.80 0.83 1.00 Q4 0.72 0.74 0.67 0.84 0.89 1.03 

 0.78 0.78 0.80 0.81 0.78 1.00 

Q1 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass 

22-Jan-05 8.5 21.8 7.1 12 3.1 3.9 5.9 0.5 62.3 

11-Mar-05 7.3 17.2 6 6.2 1.3 3.3 4.8 0.5 46.1 

25-Jan-05 4.5 11.8 4.1 6.8 2.2 3 3.3 0.5 35.7 

Average 48.0 

Q1 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

22-Jan-05 6.6 17.0 5.7 9.7 2.4 3.9 4.6 0.5 50.5 

11-Mar-05 5.7 13.4 4.8 5.0 1.0 3.3 3.8 0.5 37.5 

25-Jan-05 3.5 9.2 3.3 5.5 1.7 3.0 2.6 0.5 29.3 

Average 39.1 

Q2 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass 

25-May-05 4.5 5.0 9.4 5.3 0.9 1.7 4.1 0.5 30.8 

30-Jun-05 3.7 5.2 9.2 5.2 0.8 1.3 4.1 0.5 29.4 

22-May-05 2.2 4.8 5.8 6.5 0.9 1.9 2.8 0.5 24.9 

Average 24.8

Q2 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

25-May-05 3.0 3.4 7.8 3.8 0.7 1.5 3.2 0.5 24.0 

30-Jun-05 2.5 3.5 7.6 3.7 0.6 1.2 3.1 0.5 22.8 

22-May-05 1.5 3.3 4.8 4.7 0.7 1.7 2.1 0.5 19.2 

Average 22.0 
Q3 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass 

4-Sep-05 6.5 6.0 2.9 8.5 1.0 2.5 2.0 0.5 29.3 

22-Sep-05 4.6 5.7 5.6 6.9 2.2 2.3 2.9 0.5 30.1 

1-Sep-05 3.8 4.8 6.5 5.8 0.9 3.4 3.1 0.5 28.3 

Average 29.2 

Q3 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

4-Sep-05 4.7 4.7 1.7 6.8 0.8 2.5 1.6 0.5 23.4 

22-Sep-05 3.4 4.4 3.2 5.5 1.8 2.3 1.9 0.5 23.1 

1-Sep-05 2.8 3.7 3.7 4.6 0.7 3.4 1.9 0.5 21.4 

Average 22.6 

Q4 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass 

4-Sep-05 9.8 17.4 8.9 8.1 1.7 2.1 5.9 0.5 53.9 

22-Sep-05 8.6 19.9 4.6 10.8 2 2.5 4.7 0.5 53.1 

1-Sep-05 6 12.6 3.8 9.9 4.2 2.7 3.3 0.5 42.6 

Average 49.9 

Q4 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

4-Sep-05 7.1 12.9 6.0 6.8 1.5 2.2 4.3 0.5 41.1 

22-Sep-05 6.2 14.7 3.1 9.1 1.8 2.6 3.5 0.5 41.4 

1-Sep-05 4.3 9.3 2.5 8.3 3.7 2.8 2.4 0.5 34.0 

Average 38.8 

Design Q1 Q2 Q3 Q4

2003 51.8 46.3 27.6 47.3 2004 48.2 30.5 46.8 49.9 2005 41.8 27.6 42.9 43.8 

Top-3 

Ratio 0.81 0.78 0.77 0.78 

Predicted 2014

2003 42.2 35.9 21.4 36.8 42.2 2004 39.2 23.7 36.2 38.9 39.2 2005 34.0 21.4 33.2 34.1 34.1 38.5 
TABLE V-A-5b 

2015 Estimated Reduction Ratios to be Applied Burbank 24-Hour PM2.5 Design 

RRF NH4 NO3 SO4 OC EC OTR Water

Q1 0.79 0.82 0.69 0.74 0.75 1.00 0.79 Q2 0.67 0.73 0.57 0.76 0.80 1.00 0.67 Q3 0.71 0.95 0.35 0.67 0.83 0.94 0.71 Q4 0.79 0.85 0.62 0.78 0.83 1.00 0.79 

Q1 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

11-Mar-05 11.4 28.9 9.0 12.2 3.7 3.8 7.7 0.5 76.8 

22-Jan-05 6.9 19.7 3.8 14.0 3.9 3.8 4.4 0.5 56.4 

8-Mar-05 8.4 20.7 7.8 7.7 2.2 4.1 6.0 0.5 57.0 

Average 63.4 

Q1 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

11-Mar-05 9.0 23.7 6.2 9.0 2.8 3.8 5.9 0.5 60.9 

22-Jan-05 5.5 16.2 2.6 10.4 2.9 3.8 3.4 0.5 45.2 

8-Mar-05 6.6 17.0 5.4 5.7 1.7 4.1 4.5 0.5 45.5 

Average 50.5 0

Q2 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

25-May-05 6.5 10.8 10.2 7.9 1.7 1.7 5.3 0.5 44.2 

4-May-05 5.7 9.8 7.7 7.0 1.5 1.7 4.3 0.5 37.7 

16-Apr-05 1.2 5.3 3.0 11.3 1.9 1.6 1.9 0.5 26.3 

Average 36.1 

Q2 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

25-May-05 4.4 7.9 5.8 6.0 1.4 1.7 3.3 0.5 30.9 

4-May-05 3.8 7.2 4.4 5.3 1.2 1.7 2.7 0.5 26.8 

16-Apr-05 0.8 3.9 1.7 8.6 1.5 1.6 1.1 0.5 19.7 

Average 25.8 

0
Q3 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

3-Jul-05 5.2 7.5 9.7 10.6 0.8 3.3 4.6 0.5 41.7 9-Jul-05 3.9 6.1 8.5 7.1 1.0 2.1 4.0 0.5 32.7 

19-Sep-05 7.6 9.6 8.4 9.3 1.9 2.2 4.5 0.5 43.5 

Average 39.3 

Q3 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

3-Jul-05 3.7 7.1 3.4 7.1 0.7 3.1 2.4 0.5 27.9 9-Jul-05 2.8 5.8 3.0 4.8 0.8 2.0 2.0 0.5 21.6 

19-Sep-05 5.4 9.1 2.9 6.2 1.6 2.1 2.7 0.5 30.5 

Average 26.7 0

Q4 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

6-Nov-05 10.0 25.2 3.9 15.4 3.1 2.1 5.3 0.5 65.0 

22-Oct-05 11.0 27.2 8.7 6.7 1.9 2.1 7.3 0.5 65.0 

12-Dec-05 4.9 13.2 1.9 15.2 5.8 2.4 2.7 0.5 46.0 

Average 58.7 

Q4 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

6-Nov-05 7.9 21.4 2.4 12.0 2.6 2.1 4.3 0.5 53.2 

22-Oct-05 8.7 23.1 5.4 5.2 1.6 2.1 5.5 0.5 52.1 

12-Dec-05 3.9 11.2 1.2 11.9 4.8 2.4 2.2 0.5 38.0 

Average 47.8 0

Design Q1 Q2 Q3 Q4

2003 54.1 45.2 51.6 50.3 2004 37.8 41.6 51.5 60.1 2005 50.6 34.8 49.3 42.6 

Top-3 

Ratio 0.80 0.71 0.68 0.81 

Predicted 2014

2003 43.1 32.3 35.0 41.0 43.1 2004 30.1 29.7 34.9 48.9 48.9 2005 40.3 24.9 33.4 34.7 40.3 44.1 
TABLE V-A-5c 

2015 Estimated Reduction Ratios to be Applied to Compton 24-Hour PM2.5 Design 

RRF NH4 NO3 SO4 OC EC OTR Water

Q1 0.77 0.97 0.27 0.82 0.91 1.17 0.77 Q2 0.85 0.48 2.22 0.60 0.57 0.68 0.85 Q3 0.81 0.96 0.62 0.74 0.75 0.90 0.81 Q4 0.76 0.87 0.54 0.80 0.82 0.93 0.76 

Q1 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

22-Jan-05 8.5 21.8 7.1 12.0 3.1 3.9 5.9 0.5 62.3 

11-Mar-05 7.3 17.2 6.0 6.2 1.3 3.3 4.8 0.5 46.1 

25-Jan-05 4.5 11.8 4.1 6.8 2.2 3.0 3.3 0.5 35.7 

Average 48.0 

Q1 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

22-Jan-05 6.5 21.1 1.9 9.8 2.8 4.6 3.9 0.5 51.3 

11-Mar-05 5.6 16.7 1.6 5.1 1.2 3.9 3.2 0.5 37.7 

25-Jan-05 3.5 11.4 1.1 5.6 2.0 3.5 2.1 0.5 29.7 

Average 39.6 0

Q2 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

25-May-05 4.5 5.0 9.4 5.3 0.9 1.7 4.1 0.5 30.8 

30-Jun-05 3.7 5.2 9.2 5.2 0.8 1.3 4.1 0.5 29.4 

22-May-05 2.2 4.8 5.8 6.5 0.9 1.9 2.8 0.5 24.9 

Average 24.8

Q2 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

25-May-05 3.8 2.4 20.9 3.2 0.5 1.2 7.3 0.5 39.7 

30-Jun-05 3.1 2.5 20.4 3.1 0.5 0.9 7.1 0.5 38.1 

22-May-05 1.9 2.3 12.9 3.9 0.5 1.3 4.5 0.5 27.8 

Average 35.2 1
Q3 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

4-Sep-05 6.5 6.0 2.9 8.5 1.0 2.5 2.0 0.5 29.3 

22-Sep-05 4.6 5.7 5.6 6.9 2.2 2.3 2.9 0.5 30.1 

1-Sep-05 3.8 4.8 6.5 5.8 0.9 3.4 3.1 0.5 28.3 

Average 29.2 

Q3 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

4-Sep-05 5.3 5.8 1.8 6.3 0.8 2.3 1.9 0.5 24.5 

22-Sep-05 3.7 5.5 3.5 5.1 1.7 2.1 2.2 0.5 24.2 

1-Sep-05 3.1 4.6 4.0 4.3 0.7 3.1 2.2 0.5 22.4 

Average 23.7 0

Q4 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

22-Oct-05 9.8 17.4 8.9 8.1 1.7 2.1 5.9 0.5 53.9 

6-Nov-05 8.6 19.9 4.6 10.8 2.0 2.5 4.7 0.5 53.1 

15-Dec-05 6.0 12.6 3.8 9.9 4.2 2.7 3.3 0.5 42.6 

Average 49.9 

Q4 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

22-Oct-05 7.4 15.1 4.8 6.5 1.4 2.0 4.2 0.5 41.9 

6-Nov-05 6.5 17.3 2.5 8.6 1.6 2.3 3.6 0.5 43.1 

15-Dec-05 4.6 11.0 2.1 7.9 3.4 2.5 2.5 0.5 34.5 

Average 39.8 0

Design Q1 Q2 Q3 Q4

2003 45.3 44.7 45.5 52.5 2004 44.8 38.2 36.3 52.4 2005 41 31.8 51.7 53 

Top-3 

Ratio 0.82 1.42 0.81 0.80 

Predicted 2014

2003 37.4 63.4 36.9 41.9 63.4 2004 36.9 54.2 29.5 41.8 54.2 2005 33.8 45.1 42.0 42.3 45.1 54.3 
TABLE V-A-5d 

2015 Estimated Reduction Ratios to be Applied Fontana 24-Hour PM2.5 Design 

RRF NH4 NO3 SO4 OC EC OTR Water

Q1 0.66 0.65 0.67 0.80 1.00 1.00 0.66 Q2 0.56 0.67 0.37 1.25 1.33 1.25 0.56 Q3 0.56 0.58 0.58 0.79 1.00 1.06 0.56 Q4 0.63 0.66 0.56 0.84 0.86 1.00 0.63 

Q1 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

11-Mar-05 7.2 20.0 5.3 14.3 7.1 3.3 5.0 0.5 62.2 

8-Mar-05 6.5 16.1 4.6 14.2 4.3 3.6 4.1 0.5 53.6 

22-Jan-05 5.9 18.8 1.8 15.8 2.9 3.3 3.5 0.5 51.9 

Average 55.9 

Q1 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

11-Mar-05 4.8 13.0 3.6 11.4 7.1 3.3 3.2 0.5 46.9 

8-Mar-05 4.3 10.5 3.1 11.4 4.3 3.6 2.7 0.5 40.3 

22-Jan-05 3.9 12.2 1.2 12.6 2.9 3.3 2.3 0.5 39.0 

Average 42.1 0

Q2 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

25-May-05 5.2 10.7 8.3 10.1 2.6 2.4 4.6 0.5 44.0 

15-Jun-05 7.4 17.9 6.1 7.7 1.6 2.5 4.9 0.5 48.1 

28-May-05 7.7 13.9 6.3 7.2 1.4 2.6 4.4 0.5 43.5 

Average 45.2 

Q2 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

25-May-05 2.9 7.2 3.1 12.6 3.5 3.0 2.2 0.5 34.9 

15-Jun-05 4.1 12.0 2.3 9.6 2.1 3.1 2.6 0.5 36.4 

28-May-05 4.3 9.3 2.3 9.0 1.9 3.3 2.4 0.5 32.9 

Average 34.7 0
Q3 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

18-Jul-05 3.7 3.7 8.9 12.5 3.7 4.0 3.7 0.5 40.2 

1-Sep-05 3.6 5.5 5.5 9.7 3.0 5.3 2.8 0.5 35.3 

29-Aug-05 3.4 3.7 5.3 12.1 3.7 5.1 2.5 0.5 35.7 

Average 37.1 

Q3 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

18-Jul-05 2.1 2.1 5.2 9.9 3.7 4.2 2.1 0.5 29.8 

1-Sep-05 2.0 3.2 3.2 7.7 3.0 5.6 1.6 0.5 26.8 

29-Aug-05 1.9 2.1 3.1 9.6 3.7 5.4 1.4 0.5 27.7 

Average 28.1 0

Q4 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

22-Oct-05 22.0 52.8 11.0 10.5 3.5 3.3 12.1 0.5 115.2 

6-Nov-05 9.9 26.4 3.4 11.8 3.2 2.4 5.3 0.5 62.4 

27-Dec-05 7.1 18.0 0.3 10.6 3.9 2.9 2.9 0.5 45.7 

Average 74.4 

Q4 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

22-Oct-05 13.9 34.8 6.2 8.8 3.0 3.3 7.8 0.5 78.3 

6-Nov-05 6.2 17.4 1.9 9.9 2.8 2.4 3.4 0.5 44.6 

27-Dec-05 4.5 11.9 0.2 8.9 3.4 2.9 2.0 0.5 34.2 

Average 52.3 0

Design Q1 Q2 Q3 Q4

2003 53.6 48.8 46.6 55.7 2004 62.6 45.5 49.9 48.5 2005 48.2 43.7 38.4 43 

Top-3 

Ratio 0.75 0.77 0.76 0.70 

Predicted 2014

2003 40.3 37.5 35.3 39.2 40.3 2004 47.1 35.0 37.8 34.1 47.1 2005 36.3 33.6 29.1 30.3 36.3 41.2 
TABLE V-A-5e 

2015 Estimated Reduction Ratios to be Applied to Long Beach 24-Hour PM2.5 Design 

RRF NH4 NO3 SO4 OC EC OTR Water

Q1 0.81 0.82 0.75 0.79 0.87 0.89 0.81 Q2 0.71 0.93 0.62 0.67 0.75 0.75 0.71 Q3 0.70 0.95 0.58 0.68 0.75 0.77 0.70 Q4 0.77 0.75 0.83 0.89 0.83 0.84 0.77 

Q1 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

22-Jan-05 8.2 18.6 7.9 8.7 2.2 4.3 5.7 0.5 55.5 

1-Jan-05 0.3 1.9 2.0 18.8 6.0 4.5 1.0 0.5 34.5 

11-Mar-05 5.8 11.6 6.9 11.2 1.2 3.8 4.3 0.5 44.8 

Average 44.9 

Q1 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

22-Jan-05 6.6 15.3 5.9 6.9 1.9 3.8 4.5 0.5 45.4 

1-Jan-05 0.2 1.6 1.5 14.9 5.2 4.0 0.7 0.5 28.6 

11-Mar-05 4.7 9.5 5.2 8.8 1.0 3.4 3.3 0.5 36.5 

Average 36.8 0

Q2 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

25-May-05 4.6 5.4 11.1 5.4 1.1 1.8 4.8 0.5 34.2 

30-Jun-05 5.0 4.4 11.0 4.4 1.0 1.5 4.6 0.5 32.0 

22-May-05 2.5 3.6 7.7 12.6 0.9 1.8 3.3 0.5 32.4 

Average 32.9

Q2 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

25-May-05 3.3 5.0 6.9 3.6 0.8 1.4 3.1 0.5 24.6 

30-Jun-05 3.6 4.1 6.8 2.9 0.8 1.1 3.0 0.5 22.8 

22-May-05 1.8 3.3 4.8 8.4 0.7 1.4 2.1 0.5 23.0 

Average 23.5 0
Q3 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

22-Sep-05 6.2 8.5 0.3 8.7 2.9 6.0 1.4 0.5 34.0 

11-Aug-05 3.4 6.5 14.3 4.4 1.4 7.1 6.1 0.5 43.1 

25-Sep-05 5.6 9.1 0.3 6.2 1.3 6.0 1.5 0.5 30.0 

Average 35.7 

Q3 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

22-Sep-05 4.3 8.1 0.2 5.9 2.2 4.6 1.5 0.5 27.3 

11-Aug-05 2.4 6.2 8.3 3.0 1.1 5.5 3.6 0.5 30.5 

25-Sep-05 3.9 8.6 0.2 4.2 1.0 4.6 1.6 0.5 24.6 

Average 27.5 0

Q4 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

6-Nov-05 8.5 18.1 5.5 11.1 3.9 2.7 4.8 0.5 54.5 

22-Oct-05 9.7 15.6 10.0 6.1 1.7 2.3 6.0 0.5 51.3 

24-Dec-05 4.1 8.7 4.4 9.3 2.4 2.5 2.9 0.5 34.4 

Average 46.7 

Q4 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

6-Nov-05 6.5 13.6 4.6 9.9 3.2 2.3 3.8 0.5 44.4 

22-Oct-05 7.5 11.7 8.3 5.4 1.4 1.9 4.9 0.5 41.6 

24-Dec-05 3.2 6.5 3.7 8.3 2.0 2.1 2.3 0.5 28.5 

Average 38.2 0

Design Q1 Q2 Q3 Q4

2003 46.5 42.9 36.9 47.4 2004 45.8 32.9 34.6 45.9 2005 37.3 27.7 46.1 43.2 

Top-3 

Ratio 

0.82 0.71 0.77 0.82 

Predicted 2014

2003 38.1 30.6 28.4 38.8 38.8 2004 37.6 23.5 26.6 37.5 37.6 2005 30.6 19.8 35.5 35.3 35.5 37.3 
TABLE V-A-5f 

2015 Estimated Reduction Ratios to be Applied to Los Angeles 24-Hour PM2.5 Design 

RRF NH4 NO3 SO4 OC EC OTR Water

Q1 0.69 0.57 1.22 1.05 1.29 1.28 0.69 Q2 0.76 0.83 0.55 0.78 0.83 0.94 0.76 Q3 0.77 0.89 0.60 0.76 0.78 0.96 0.77 Q4 0.84 0.87 0.70 0.79 0.82 1.00 0.84 

Q1 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

11-Mar-05 11.8 30.3 10.5 11.5 3.4 3.7 8.4 0.5 79.6 

22-Jan-05 7.2 20.6 4.5 13.3 4.0 3.5 4.8 0.5 57.9 

8-Mar-05 2.4 19.6 4.3 8.0 2.1 2.8 4.6 0.5 43.9 

Average 60.5 

Q1 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

11-Mar-05 8.1 17.3 12.8 12.1 4.4 4.7 7.1 0.5 67.0 

22-Jan-05 5.0 11.7 5.5 14.0 5.2 4.5 3.7 0.5 50.0 

8-Mar-05 1.7 11.2 5.2 8.4 2.7 3.6 3.2 0.5 36.4 

Average 51.1 0

Q2 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

25-May-05 5.8 8.8 11.6 8.1 1.5 2.5 5.5 0.5 43.9 

30-Jun-05 5.0 8.8 8.2 7.1 1.7 2.4 4.3 0.5 37.4 

22-May-05 2.4 5.9 6.3 12.5 1.6 2.9 3.2 0.5 34.9 

Average 38.7 

Q2 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

25-May-05 4.4 7.3 6.4 6.3 1.2 2.4 3.4 0.5 31.9 

30-Jun-05 3.8 7.3 4.5 5.5 1.4 2.3 2.7 0.5 28.1 

22-May-05 1.8 4.9 3.5 9.8 1.3 2.7 1.9 0.5 26.4 

Average 28.8 0
Q3 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

5-Aug-05 7.9 15.8 18.3 11.2 4.2 5.7 9.0 0.5 72.2 

3-Jul-05 5.9 6.7 10.6 7.2 1.0 4.3 4.8 0.5 40.6 

19-Sep-05 8.0 10.5 9.0 13.6 1.8 4.2 4.9 0.5 51.9 

Average 54.9 

Q3 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

5-Aug-05 6.1 14.1 11.0 8.5 3.3 5.5 5.8 0.5 54.7 

3-Jul-05 4.5 6.0 6.4 5.5 0.8 4.1 3.2 0.5 31.0 

19-Sep-05 6.2 9.3 5.4 10.3 1.4 4.0 3.5 0.5 40.7 

Average 42.2 0

Q4 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

22-Oct-05 12.5 26.3 9.2 7.6 1.9 2.6 7.4 0.5 67.5 

6-Nov-05 9.8 25.8 4.4 12.2 2.9 2.5 5.6 0.5 63.1 

24-Nov-05 4.7 13.7 3.0 12.0 5.2 2.6 3.2 0.5 44.3 

Average 58.3 

Q4 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

22-Oct-05 10.5 22.9 6.4 6.0 1.6 2.6 6.0 0.5 56.5 

6-Nov-05 8.2 22.4 3.1 9.6 2.4 2.5 4.6 0.5 53.4 

24-Nov-05 3.9 11.9 2.1 9.5 4.3 2.6 2.6 0.5 37.4 

Average 49.1 0

Design Q1 Q2 Q3 Q4

2003 53.6 55.1 51 55.3 2004 49.7 44 55.9 61.3 2005 53.5 38.2 36.8 52 

Top-3 

Ratio 0.85 0.74 0.77 0.84 

Predicted 2014

2003 45.3 41.0 39.2 46.6 46.6 2004 42.0 32.7 42.9 51.6 51.6 2005 45.2 28.4 28.3 43.8 45.2 47.8 
TABLE V-A-5g 

2015 Estimated Reduction Ratios to be Applied to Rubidoux 24-Hour PM2.5 Design 

RRF NH4 NO3 SO4 OC EC OTR Water

Q1 0.69 0.66 0.70 0.80 0.86 0.91 0.69 Q2 0.56 0.58 0.42 0.81 1.00 1.06 0.56 Q3 0.52 0.52 0.50 0.79 0.80 0.89 0.52 Q4 0.54 0.56 0.50 0.79 0.80 0.89 0.54 

Q1 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

11-Mar-05 0.0 16.7 3.2 13.9 3.4 3.1 3.7 0.5 44.1 

22-Jan-05 5.4 17.3 2.0 10.6 3.9 2.9 3.4 0.5 45.5 

8-Mar-05 5.8 16.2 4.4 8.2 3.2 3.7 4.1 0.5 45.5 

Average 45.0 

Q1 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

11-Mar-05 3.8 11.0 2.2 11.1 2.9 2.8 2.5 0.5 36.9 

22-Jan-05 3.7 11.4 1.4 8.5 3.4 2.6 2.3 0.5 33.8 

8-Mar-05 4.0 10.7 3.1 6.6 2.8 3.4 2.7 0.5 33.7 

Average 34.8 0

Q2 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

15-Jun-05 9.4 17.1 5.4 5.9 1.1 1.5 4.6 0.5 44.8 

25-May-05 7.1 16.5 7.5 8.1 1.6 1.8 5.2 0.5 47.8 

16-Apr-05 5.4 17.6 3.3 7.1 1.3 1.7 3.9 0.5 40.1 

Average 44.2 

Q2 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

15-Jun-05 5.3 9.9 2.3 4.8 1.1 1.6 2.5 0.5 27.9 

25-May-05 4.0 9.6 3.2 6.6 1.6 1.9 2.6 0.5 29.9 

16-Apr-05 3.0 10.2 1.4 5.8 1.3 1.8 2.0 0.5 26.0 

Average 27.9 0
Q3 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

6-Jul-05 4.1 10.6 5.4 14.1 2.1 3.3 3.6 0.5 43.2 

14-Aug-05 4.0 13.0 6.7 5.3 0.9 3.6 4.4 0.5 37.9 

3-Jul-05 5.4 11.6 6.7 7.2 1.0 3.3 4.2 0.5 39.4 

Average 40.2 

Q3 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

6-Jul-05 2.1 5.5 2.7 11.1 1.7 2.9 1.8 0.5 28.4 

14-Aug-05 2.1 6.8 3.4 4.2 0.7 3.2 2.1 0.5 22.9 

3-Jul-05 2.8 6.0 3.4 5.7 0.8 2.9 2.1 0.5 24.2 

Average 25.2 0

Q4 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

22-Oct-05 20.6 55.6 21.1 10.9 3.5 2.7 16.1 0.5 130.5 

6-Nov-05 10.2 26.1 3.5 15.8 3.1 2.3 5.3 0.5 66.4 

12-Nov-05 7.6 20.5 2.7 9.9 2.8 2.4 4.1 0.5 50.1 

Average 82.3 

Q4 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

22-Oct-05 11.1 31.1 10.6 8.6 2.8 2.4 8.4 0.5 75.5 

6-Nov-05 5.5 14.6 1.8 12.5 2.5 2.0 3.0 0.5 42.3 

12-Nov-05 4.1 11.5 1.4 7.8 2.2 2.1 2.3 0.5 31.9 

 49.9 0

Design Q1 Q2 Q3 Q4

2003 72.9 61.6 60.5 66 2004 59.5 60.5 55.3 76.6 2005 56.6 55.8 47 49.5 

Top-3 

Ratio 0.74 0.62 0.62 0.60 

Predicted 2014

2003 53.6 38.3 37.6 39.8 53.6 2004 43.7 37.6 34.4 46.2 46.2 2005 41.6 34.7 29.2 29.9 41.6 47.1 
TABLE V-2A-5h 

2015 Estimated Reduction Ratios to be Applied to Wilmington 24-Hour PM2.5 Design 

RRF NH4 NO3 SO4 OC EC OTR Water

Q1 0.74 0.78 0.67 0.77 0.71 0.78 0.74 Q2 0.50 1.46 0.24 0.70 0.67 0.76 0.50 Q3 0.60 1.00 0.47 0.65 0.57 0.68 0.60 Q4 0.74 1.02 0.56 0.69 0.75 0.78 0.74 

Q1 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

22-Jan-05 8.7 18.7 9.6 9.5 3.4 4.5 6.3 0.5 60.8 

1-Jan-05 0.2 1.9 2 15.8 4.9 4.6 1 0.5 30.4 

13-Jan-05 1.6 6.3 2.6 12.5 5.7 5.2 1.9 0.5 35.7 

Average 42.3 

Q1 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

22-Jan-05 6.4 14.6 6.4 7.3 2.4 3.5 4.5 0.5 45.7 

1-Jan-05 0.1 1.5 1.3 12.2 3.5 3.6 0.6 0.5 23.3 

13-Jan-05 1.2 4.9 1.7 9.6 4.0 4.1 1.3 0.5 27.3 

Average 32.1 0

Q2 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

30-Jun-05 4.6 2.6 11.1 4.3 1.2 1.5 4.4 0.5 29.6 

25-May-05 4.6 4 11.4 6 1.1 1.7 4.7 0.5 33.5 22-May-05 2.5 2 10.4 4.3 1 1.8 4 0.5 26.1 

Average 29.7 

Q2 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

30-Jun-05 2.3 3.8 2.7 3.0 0.8 1.1 1.6 0.5 15.8 

25-May-05 2.3 5.8 2.7 4.2 0.7 1.3 1.8 0.5 19.4 22-May-05 1.3 2.9 2.5 3.0 0.7 1.4 1.3 0.5 13.5 

Average 16.2 0
Q3 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

21-Jul-05 1.6 3.2 9 4.6 1.9 2.4 3.7 0.5 26.3 12-Jul-05 7 3.4 16.4 5.3 1.8 2.2 6.4 0.5 42.5 

22-Sep-05 5.4 9.3 0.3 7.4 3.8 5.3 1.5 0.5 33 

Average 33.9 

Q3 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

21-Jul-05 1.0 3.2 4.2 3.0 1.1 1.6 1.8 0.5 16.4 12-Jul-05 4.2 3.4 7.7 3.4 1.0 1.5 3.3 0.5 25.1 

22-Sep-05 3.2 9.3 0.1 4.8 2.2 3.6 1.5 0.5 25.3 

Average 22.3 0

Q4 Observed Components NH4+ NO3- SO4= OC EC OTR Water Blank Mass R

24-Nov-05 3.4 11.9 5.3 12.7 3.1 3 3.7 0.5 43.1 

22-Oct-05 7.3 14 14.7 5.5 1.7 2.3 7.4 0.5 52.8 

6-Nov-05 7.3 14.2 5.1 15.1 2.9 2.8 4 0.5 51.5 

Average 49.1 

Q4 2015 Estimates NH4+ NO3- SO4= OC EC OTR Water Blank Mass

24-Nov-05 2.5 12.1 3.0 8.8 2.3 2.3 2.7 0.5 34.2 

22-Oct-05 5.4 14.3 8.2 3.8 1.3 1.8 4.9 0.5 40.2 

6-Nov-05 5.4 14.5 2.9 10.4 2.2 2.2 3.3 0.5 41.3 

Average 38.6 0

Design Q1 Q2 Q3 Q4

2003 46.5 42.9 36.9 47.4 Design lgbh2004 45.8 32.9 34.6 45.9 2005 37.3 27.7 46.1 43.2 

Top-3 Ratio 0.76 0.55 0.66 0.79 

Predicted 2014

2003 35.3 23.4 24.2 37.2 37.2 2004 34.8 18.0 22.7 36.1 36.1 2005 28.3 15.1 30.3 33.9 33.9 35.8 
TABLE V-A-6a 

2015 Episode Day Estimated Reduction Ratios to be Applied Anaheim 24-Hour PM2.5 Desi

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

RRF 22-Oct-05 0.736 0.842 0.549 0.838 0.866 0.985 

Observed 

22-Oct-05 9.8 17.4 8.9 8.1 1.7 2.1 5.9 0.5 53.9 

2015 Predicted 

22-Oct-05 7.2 14.7 4.9 6.8 1.5 2.1 4.2 0.5 41.7 0

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

Average 4-Q RRF 0.73 0.75 0.72 0.79 0.83 0.98 

Observed 

22-Oct-05 9.8 17.4 8.9 8.1 1.7 2.1 5.9 0.5 53.9 

2015 Predicted 

22-Oct-05 7.1 13.0 6.4 6.4 1.4 2.1 4.4 0.5 41.2 0

Episode Day Using Ratio Design Future Design 

RRF 22-Oct-05 0.74 47 34.6 

Episode Day Using Ratio Design Future Design 

Average 4-Q RRF 0.73 47 34.1 
TABLE V-A-6b 

2015 Episode Day Estimated Reduction Ratios to be Applied Burbank 24-Hour PM2.5 Desig

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

RRF 22-Oct-05 0.822 0.888 0.588 0.856 0.859 0.972 

Observed 

22-Oct-05 11 27.2 8.7 6.7 1.9 2.1 7.3 0.5 65 

2015 Predicted 

22-Oct-05 9.0 24.2 5.1 5.7 1.6 2.0 5.6 0.5 53.8 0

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

Average 4-Q RRF 0.74 0.84 0.56 0.74 0.80 0.99 

Observed 

22-Oct-05 11 27.2 8.7 6.7 1.9 2.1 7.3 0.5 65 

2015 Predicted 

22-Oct-05 8.1 22.8 4.9 4.9 1.5 2.1 5.2 0.5 50.0 0

Episode Day Using Ratio Design Future Design 

RRF 22-Oct-05 0.82 53.3 43.8 

Episode Day Using Ratio Design Future Design 

Average 4-Q RRF 0.74 53.3 39.4 
TABLE V-A-6c 

2015 Episode Day Estimated Reduction Ratios to be Applied to Compton 24-Hour PM2.5 Des

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

RRF 22-Oct-05 0.731 0.822 0.601 0.809 0.823 0.866 

Observed 

22-Oct-05 9.8 17.4 8.9 8.1 1.7 2.1 5.9 0.5 53.9 

2015 Predicted 

22-Oct-05 7.2 14.3 5.3 6.6 1.4 1.8 4.2 0.5 41.3 0

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

Average 4-Q RRF 0.80 0.82 0.91 0.74 0.76 0.92 

Observed 

22-Oct-05 9.8 17.4 8.9 8.1 1.7 2.1 5.9 0.5 53.9 

2015 Predicted 

22-Oct-05 7.8 14.3 8.1 6.0 1.3 1.9 5.2 0.5 45.1 0

Episode Day Using Ratio Design Future Design 

RRF 22-Oct-05 0.73 51.3 37.5 

Episode Day Using Ratio Design Future Design 

Average 4-Q RRF 0.80 51.3 40.9 
TABLE V-A-6d 

2015 Episode Day Estimated Reduction Ratios to be Applied Fontana 24-Hour PM2.5 Desig

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

RRF 22-Oct-05 0.672 0.703 0.59 0.844 0.886 1.003 

Observed 

22-Oct-05 22 52.8 11 10.5 3.5 3.3 12.1 0.5 115.2 

2015 Predicted 

22-Oct-05 14.8 37.1 6.5 8.9 3.1 3.3 8.3 0.5 82.4 0

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

Average 4-Q RRF 0.60 0.64 0.55 0.92 1.05 1.08 

Observed 

22-Oct-05 22 52.8 11 10.5 3.5 3.3 12.1 0.5 115.2 

2015 Predicted 

22-Oct-05 13.3 33.8 6.0 9.7 3.7 3.6 7.5 0.5 77.9 0

Episode Day Using Ratio Design Future Design 

RRF 22-Oct-05 0.67 54.8 36.8 

Episode Day Using Ratio Design Future Design 

Average 4-Q RRF 0.60 54.8 33.0 
TABLE V-A-6e 

2015 Episode Day Estimated Reduction Ratios to be Applied to Long Beach 24-Hour PM2.5 D

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

RRF 22-Oct-05 0.76 0.82 0.67 0.78 0.90 0.7 

Observed 

22-Oct-05 9.7 15.6 10.0 6.1 1.7 2.3 6.0 0.5 51.3 

2015 Predicted 

22-Oct-05 7.3 12.8 6.7 4.7 1.5 1.6 4.4 0.5 39.5 0

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

Average 4-Q RRF 0.562 0.571 0.565 0.816 0.829 1.011 0.573 

Observed 

22-Oct-05 9.7 15.6 10.0 6.1 1.7 2.3 6.0 0.5 51.3 

2015 Predicted 

22-Oct-05 5.4 8.9 5.6 4.9 1.4 2.3 3.4 0.5 32.6 0

Episode Day Using Ratio Design Future Design 

RRF 22-Oct-05 0.70 44.6 31.2 

Episode Day Using Ratio Design Future Design 

Average 4-Q RRF 0.75 44.6 33.3 
TABLE V-A-6f 

2015 Episode Day Estimated Reduction Ratios to be Applied to Los Angeles 24-Hour PM2.5 D

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

RRF 22-Oct-05 0.82 0.87 0.67 0.84 0.93 0.93 

Observed 

22-Oct-05 12.5 26.3 9.2 7.6 1.9 2.6 7.4 0.5 67.5 

2015 Predicted 

22-Oct-05 10.3 22.9 6.2 6.4 1.7 2.4 5.7 0.5 56.1 0

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

Average 4-Q RRF 0.562 0.571 0.565 0.816 0.829 1.011 0.573 

Observed 

22-Oct-05 12.5 26.3 9.2 7.6 1.9 2.6 7.4 0.5 67.5 

2015 Predicted 

22-Oct-05 7.0 15.0 5.2 6.2 1.5 2.7 4.2 0.5 42.3 0

Episode Day Using Ratio Design Future Design 

RRF 22-Oct-05 0.83 60.7 50.3 

Episode Day Using Ratio Design Future Design 

Average 4-Q RRF 0.77 60.7 46.4 
 TABLE V-A-6g 

2015 Episode Day Estimated Reduction Ratios to be Applied to Rubidoux 24-Hour PM2.5 De

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

RRF 22-Oct-05 0.61 0.60 0.61 0.82 0.93 0.83 

Observed 

22-Oct-05 20.6 55.6 21.1 10.9 3.5 2.7 16.1 0.5 130.5 

2015 Predicted 

22-Oct-05 12.6 33.3 12.8 9.0 3.3 2.2 9.8 0.5 83.0 0

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

Average 4-Q RRF 0.562 0.571 0.565 0.816 0.829 1.011 0.573 

Observed 

22-Oct-05 20.6 55.6 21.1 10.9 3.5 2.7 16.1 0.5 130.5 

2015 Predicted 

22-Oct-05 11.6 31.7 11.9 8.9 2.9 2.7 9.2 0.5 79.0 0

Episode Day Using Ratio Design Future Design 

RRF 22-Oct-05 0.60 64.8 38.6 

Episode Day Using Ratio Design Future Design 

Average 4-Q RRF 0.58 64.8 37.4 
TABLE V-A-6h 

2015 Episode Day Estimated Reduction Ratios to be Applied to Wilmington 24-Hour PM2.5 D

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

RRF 22-Oct-05 0.7 0.8 0.7 0.8 0.8 0.6 

Observed 

22-Oct-05 7.3 14 14.7 5.5 1.7 2.3 7.4 0.5 52.8 

2015 Predicted 

22-Oct-05 5.4 11.2 9.5 4.1 1.4 1.4 5.1 0.5 38.2 0

Episode Day Using NH4 NO3 SO4 OC EC OTR Water Blank Mass R

Average 4-Q RRF 0.6 0.6 0.6 0.8 0.8 1 0.6 

Observed 

22-Oct-05 7.3 14 14.7 5.5 1.7 2.3 7.4 0.5 52.8 

2015 Predicted 

22-Oct-05 4.1 8 8.3 4.5 1.4 2.4 4.2 0.5 32.8 0

Episode Day Using Ratio Design Future Design 

RRF 22-Oct-05 0.68 44.6 30.3 

Design 

lgbh 

Episode Day Using Ratio Design Future Design 

Average 4-Q RRF 0.65 44.6 28.8 

Design 

lgbh 
ATTACHMENT-2 

Model Performance Statistics 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubRegional Descriptions  SubRegion 003 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0069 Burbank 53 48 -27.848 461.308  0088 Pasadena 56 47 -11.205 457.021  0074 Reseda 49 48 -48.000 463.105  0090 Santa Clarita 49 52 -48.140 483.357  SubRegion 004 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0060 Azusa 60 47 6.981 456.113  4164 Banning Airport 79 42 104.459 433.527  5181 Crestline 72 49 66.383 468.606  4158 Elsinore 71 37 60.525 405.907  5197 Fontana 68 46 46.811 453.081  0591 Glendora 61 47 13.487 457.010  5212 Mira Loma 67 43 42.938 438.915  4149 Perris 72 39 69.051 417.376  0075 Pomona 63 45 22.598 448.610  5204 Redlands 74 45 76.256 448.189  4144 Rubidoux 69 44 52.093 442.557  5203 San Bernardino 72 46 65.874 453.299  5175 Upland 65 46 31.687 452.125  SubRegion 005 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  3176 Anaheim 60 40 7.422 421.645  0087 Los Angeles 54 45 -22.302 445.563  3195 Costa Mesa 60 37 6.793 405.626  3177 La Habra 59 42 4.359 432.978  0820 LAXH 51 42 -36.352 433.685  0072 Long Beach 55 40 -17.171 421.903  0084 Lynwood 55 42 -19.237 432.753  3812 Mission Viejo 64 36 29.671 400.791  0085 Pico Rivera 57 44 -5.273 442.860  0091 West Los Angeles 52 45 -34.796 447.031  SubRegion 009 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  4157 Indio Jackson 91 38 162.217 411.293  4137 Palm Springs 85 40 132.826 423.133 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 214 (08/02) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 23 12.3 15 9.1 15 0 0.74 -0.9 1.3 - Subregional Peak: 9.4 15 0 0.77 (at cell 50 x  0069 Burbank 2 6.9 15 7.6 15 0 1.11 0.1 0.1 - 0088 Pasadena 5 6.6 15 7.0 13 -2 1.06 0.1 0.1 - 0074 Reseda 5 9.1 15 8.6 15 0 0.94 0.0 0.1 - 0090 Santa Clarita 11 12.3 15 9.1 15 0 0.74 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 214 (08/02) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 81 11.4 15 9.9 16 1 0.87 -0.2 1.3 - Subregional Peak: 10.2 16 1 0.89 (at cell 74 x  0060 Azusa 1 6.1 15 7.5 15 0 1.23 0.2 0.2 - 4164 Banning Airport 10 11.4 15 7.6 17 2 0.66 -0.2 0.2 - 5181 Crestline 15 9.3 17 8.7 17 0 0.94 -0.2 0.2 - 4158 Elsinore 7 9.4 14 6.8 16 2 0.73 -0.3 0.3 - 5197 Fontana 5 8.2 15 9.3 15 0 1.14 0.1 0.1 - 0591 Glendora 2 7.0 15 8.7 15 0 1.24 0.2 0.2 - 5212 Mira Loma 7 8.4 14 9.4 14 0 1.11 0.1 0.1 - 4149 Perris 7 7.9 13 8.8 16 3 1.11 0.1 0.2 - 0075 Pomona 2 7.4 14 9.2 14 0 1.24 0.2 0.2 - 5204 Redlands 8 8.5 15 9.9 16 1 1.17 0.1 0.1 - 4144 Rubidoux 7 8.4 15 9.6 15 0 1.14 0.1 0.1 - 5203 San Bernardino 6 8.4 16 9.5 16 0 1.13 0.1 0.1 - 5175 Upland 4 8.4 15 9.5 15 0 1.13 0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 214 (08/02) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 4 7.4 20 4.0 20 0 0.54 -3.1 3.1 - Subregional Peak: 8.0 17 -3 1.09 (at cell 81 x  4157 Indio Jackson 2 6.3 21 3.3 22 1 0.52 -0.5 0.5 - 4137 Palm Springs 2 7.4 20 4.0 20 0 0.54 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 215 (08/03) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 20 9.9 15 9.2 14 -1 0.93 0.2 0.9  Subregional Peak: 9.6 15 0 0.97 (at cell 52 x  0069 Burbank 2 6.7 13 8.5 14 1 1.27 0.2 0.2  0088 Pasadena 4 7.2 14 8.1 15 1 1.12 0.1 0.1  0074 Reseda 6 7.6 13 8.5 16 3 1.12 0.1 0.1  0090 Santa Clarita 8 9.9 15 9.2 14 -1 0.93 -0.1 0.1 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 215 (08/03) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 84 9.9 16 10.4 15 -1 1.05 0.8 1.2  Subregional Peak: 10.5 15 -1 1.06 (at cell 73 x  0060 Azusa 3 7.4 15 8.6 15 0 1.16 0.2 0.2  4164 Banning Airport 9 9.9 16 8.8 17 1 0.89 -0.2 0.2  5181 Crestline 12 9.6 15 10.0 16 1 1.04 0.0 0.1  4158 Elsinore 8 8.0 14 8.5 17 3 1.06 0.0 0.1  5197 Fontana 6 8.0 14 9.2 15 1 1.15 0.2 0.2  0591 Glendora 4 8.0 15 9.2 15 0 1.14 0.2 0.2  5212 Mira Loma 7 8.4 14 9.7 15 1 1.15 0.1 0.1  4149 Perris 6 8.5 14 9.3 16 2 1.10 0.1 0.2  0075 Pomona 4 7.2 14 9.0 15 1 1.25 0.3 0.3  5204 Redlands 6 8.7 14 10.3 16 2 1.18 0.2 0.2  4144 Rubidoux 7 8.5 14 10.0 15 1 1.18 0.2 0.2  5203 San Bernardino 7 9.3 14 10.4 15 1 1.12 0.2 0.2  5175 Upland 5 7.1 13 9.2 15 2 1.29 0.2 0.2  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 215 (08/03) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 5 6.6 19 6.4 13 -6 0.97 -1.7 1.8 - Subregional Peak: 9.8 14 -5 1.48 (at cell 67 x  3176 Anaheim 1 6.1 13 6.4 13 0 1.05 0.0 0.0 - 0820 LAXH 2 6.6 19 4.5 18 -1 0.68 -0.4 0.4 - 0091 West Los Angeles 2 6.6 18 5.1 17 -1 0.78 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 215 (08/03) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 5 8.7 19 5.7 18 -1 0.66 -2.2 2.2 - Subregional Peak: 8.9 19 0 1.02 (at cell 82 x  4157 Indio Jackson 1 6.1 21 3.9 21 0 0.63 -0.4 0.4 - 4137 Palm Springs 4 8.7 19 5.7 18 -1 0.66 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 216 (08/04) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 27 14.1 14 10.1 14 0 0.72 -0.7 1.5 - Subregional Peak: 11.2 16 2 0.80 (at cell 53 x  0069 Burbank 3 7.7 13 10.1 14 1 1.31 0.3 0.3 - 0088 Pasadena 7 8.4 14 9.5 15 1 1.13 0.0 0.1 - 0074 Reseda 8 10.3 14 9.7 15 1 0.95 -0.1 0.1 - 0090 Santa Clarita 9 14.1 14 9.5 16 2 0.68 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 216 (08/04) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 99 11.8 15 11.6 16 1 0.98 0.3 1.3  Subregional Peak: 12.0 15 0 1.02 (at cell 70 x  0060 Azusa 5 9.1 14 9.4 15 1 1.03 0.2 0.2  4164 Banning Airport 13 10.8 16 9.1 17 1 0.84 -0.2 0.2  5181 Crestline 12 11.8 15 10.2 16 1 0.87 -0.2 0.2  4158 Elsinore 9 10.5 16 10.1 17 1 0.96 0.1 0.1  5197 Fontana 7 9.4 14 10.9 15 1 1.16 0.1 0.1  0591 Glendora 6 10.2 15 10.0 14 -1 0.98 0.1 0.1  5212 Mira Loma 8 9.4 13 11.4 14 1 1.22 0.1 0.2  4149 Perris 6 9.1 14 11.6 16 2 1.28 0.2 0.2  0075 Pomona 5 9.0 14 10.2 13 -1 1.13 0.2 0.2  5204 Redlands 7 9.9 15 11.1 16 1 1.12 0.2 0.2  4144 Rubidoux 7 9.7 13 11.5 15 2 1.19 0.2 0.2  5203 San Bernardino 8 10.3 14 10.8 15 1 1.05 0.1 0.1  5175 Upland 6 9.1 16 10.9 14 -2 1.20 0.1 0.2  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 216 (08/04) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 24 7.2 16 10.0 13 -3 1.38 -0.2 1.1 - Subregional Peak: 11.1 14 -2 1.55 (at cell 65 x  3176 Anaheim 4 7.0 12 7.2 12 0 1.03 0.0 0.1 - 0087 Los Angeles 4 6.7 15 7.3 14 -1 1.08 0.0 0.1 - 3177 La Habra 1 6.5 13 6.5 13 0 1.00 0.0 0.0 - 0820 LAXH 7 7.2 16 6.2 12 -4 0.86 -0.2 0.2 - 3812 Mission Viejo 2 6.4 13 10.0 13 0 1.56 0.6 0.6 - 0091 West Los Angeles 6 7.1 16 7.9 13 -3 1.12 0.0 0.1 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 216 (08/04) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 9 8.7 11 7.0 12 1 0.80 -1.1 1.4 - Subregional Peak: 9.8 18 7 1.13 (at cell 82 x  4157 Indio Jackson 2 6.3 12 7.0 12 0 1.11 0.1 0.1 - 4137 Palm Springs 7 8.7 11 5.7 9 -2 0.66 -0.2 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 217 (08/05) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 23 12.3 13 10.9 15 2 0.89 -0.5 1.5 - Subregional Peak: 11.4 16 3 0.92 (at cell 50 x  0069 Burbank 3 7.3 14 8.6 15 1 1.18 0.2 0.2 - 0088 Pasadena 3 6.6 14 8.4 14 0 1.28 0.2 0.2 - 0074 Reseda 7 11.1 13 10.6 14 1 0.95 0.0 0.1 - 0090 Santa Clarita 10 12.3 13 10.9 15 2 0.89 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 217 (08/05) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 91 11.9 15 11.9 16 1 1.00 0.0 1.9  Subregional Peak: 12.0 16 1 1.01 (at cell 69 x  0060 Azusa 1 7.4 13 9.8 13 0 1.32 0.3 0.3  4164 Banning Airport 12 11.8 16 6.0 17 1 0.51 -0.4 0.4  5181 Crestline 9 11.9 15 9.6 17 2 0.81 -0.1 0.2  4158 Elsinore 9 8.8 11 9.3 17 6 1.06 0.0 0.2  5197 Fontana 7 10.8 15 11.3 16 1 1.05 0.1 0.2  0591 Glendora 5 7.9 13 11.6 15 2 1.47 0.5 0.5  5212 Mira Loma 7 10.2 14 11.6 15 1 1.14 0.2 0.2  4149 Perris 7 10.1 14 10.9 17 3 1.07 0.1 0.3  0075 Pomona 4 8.8 14 11.8 15 1 1.34 0.4 0.4  5204 Redlands 9 11.2 14 10.3 17 3 0.92 0.0 0.2  4144 Rubidoux 7 10.5 14 11.9 16 2 1.13 0.2 0.2  5203 San Bernardino 9 11.2 14 10.5 16 2 0.94 0.0 0.2  5175 Upland 5 10.1 15 11.7 15 0 1.15 0.1 0.2  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 217 (08/05) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 1 6.3 12 9.3 12 0 1.48 3.0 3.0  Subregional Peak: 10.9 14 2 1.72 (at cell 63 x  3812 Mission Viejo 1 6.3 12 9.3 12 0 1.48 0.5 0.5 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 217 (08/05) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 18 11.2 19 5.4 19 0 0.48 -3.1 3.1 - Subregional Peak: 7.6 19 0 0.68 (at cell 82 x  4157 Indio Jackson 5 7.4 21 5.1 11 -10 0.69 -0.3 0.3 - 4137 Palm Springs 13 11.2 19 5.4 19 0 0.48 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 218 (08/06) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 37 14.3 13 13.1 15 2 0.91 0.1 1.9  Subregional Peak: 13.2 15 2 0.92 (at cell 53 x  0069 Burbank 7 8.8 14 13.1 15 1 1.49 0.3 0.3  0088 Pasadena 8 9.9 15 12.6 16 1 1.27 0.2 0.2  0074 Reseda 9 11.0 12 10.2 15 3 0.93 0.1 0.1  0090 Santa Clarita 13 14.3 13 9.8 15 2 0.68 -0.2 0.2 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 218 (08/06) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 111 12.7 14 12.7 16 2 1.00 -0.9 1.8 - Subregional Peak: 13.2 16 2 1.04 (at cell 61 x  0060 Azusa 7 9.7 15 12.0 16 1 1.24 0.2 0.2 - 4164 Banning Airport 6 8.2 12 4.7 11 -1 0.58 -0.4 0.4 - 5181 Crestline 14 11.9 17 7.9 19 2 0.67 -0.3 0.3 - 4158 Elsinore 11 9.6 17 8.6 18 1 0.89 -0.1 0.2 - 5197 Fontana 9 12.7 14 10.4 17 3 0.82 -0.2 0.2 - 0591 Glendora 8 11.3 13 11.7 17 4 1.04 0.0 0.2 - 5212 Mira Loma 9 11.8 16 12.4 16 0 1.05 0.0 0.1 - 4149 Perris 4 9.1 12 5.6 13 1 0.62 -0.3 0.3 - 0075 Pomona 8 11.0 16 12.7 16 0 1.15 0.1 0.1 - 5204 Redlands 9 8.3 13 9.5 18 5 1.15 0.0 0.2 - 4144 Rubidoux 8 11.5 16 12.0 17 1 1.04 0.0 0.2 - 5203 San Bernardino 9 11.5 13 9.0 18 5 0.78 -0.1 0.1 - 5175 Upland 9 12.2 15 11.7 17 2 0.96 -0.1 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 218 (08/06) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 23 7.9 15 12.5 15 0 1.59 3.7 3.9  Subregional Peak: 13.1 15 0 1.66 (at cell 59 x  3176 Anaheim 6 6.9 13 11.7 13 0 1.70 0.7 0.7  0087 Los Angeles 7 7.2 14 11.5 14 0 1.60 0.3 0.4  3177 La Habra 3 6.6 14 12.5 15 1 1.90 0.9 0.9  0084 Lynwood 1 6.1 13 11.0 13 0 1.80 0.8 0.8 1 3812 Mission Viejo 6 7.9 15 12.0 15 0 1.52 0.6 0.6 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 218 (08/06) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 10 7.0 11 5.1 11 0 0.73 -1.9 1.9 - Subregional Peak: 7.8 19 8 1.11 (at cell 82 x  4157 Indio Jackson 5 7.0 11 5.1 11 0 0.73 -0.3 0.3 - 4137 Palm Springs 5 7.0 10 4.6 9 -1 0.66 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 219 (08/07) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 29 13.9 13 12.6 14 1 0.91 0.5 2.1  Subregional Peak: 13.1 14 1 0.94 (at cell 53 x  0069 Burbank 5 10.0 12 12.6 13 1 1.26 0.3 0.3  0088 Pasadena 7 10.3 12 12.6 14 2 1.23 0.3 0.3  0074 Reseda 7 9.6 12 9.7 14 2 1.01 0.1 0.2  0090 Santa Clarita 10 13.9 13 9.3 15 2 0.67 -0.2 0.2 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 219 (08/07) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 125 13.4 13 13.9 15 2 1.04 -0.6 1.9 - Subregional Peak: 14.0 15 2 1.04 (at cell 60 x  0060 Azusa 6 11.5 13 13.9 15 2 1.21 0.2 0.3 - 4164 Banning Airport 15 11.0 15 8.7 18 3 0.79 -0.2 0.2 - 5181 Crestline 14 12.9 13 10.3 18 5 0.80 -0.2 0.3 - 4158 Elsinore 10 10.6 11 7.7 16 5 0.73 -0.2 0.3 - 5197 Fontana 8 12.1 15 12.2 16 1 1.01 -0.1 0.2 - 0591 Glendora 8 13.4 13 13.9 15 2 1.04 0.2 0.3 - 5212 Mira Loma 11 11.7 14 12.1 15 1 1.04 0.0 0.1 - 4149 Perris 6 7.9 14 8.3 15 1 1.05 0.0 0.1 - 0075 Pomona 8 12.5 13 12.9 16 3 1.03 0.1 0.2 - 5204 Redlands 11 11.6 13 11.6 17 4 1.00 -0.1 0.1 - 4144 Rubidoux 10 11.4 14 12.0 16 2 1.05 0.0 0.1 - 5203 San Bernardino 10 13.3 15 11.7 17 2 0.88 -0.1 0.2 - 5175 Upland 8 12.3 14 13.2 16 2 1.07 0.1 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 219 (08/07) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 20 8.1 15 10.4 15 0 1.28 2.4 2.4  Subregional Peak: 13.3 14 -1 1.64 (at cell 58 x  3176 Anaheim 6 7.3 12 9.5 13 1 1.30 0.3 0.3  0087 Los Angeles 4 6.6 12 9.9 12 0 1.50 0.4 0.4  3177 La Habra 4 6.4 12 10.4 15 3 1.63 0.5 0.5  0072 Long Beach 1 6.1 12 7.5 12 0 1.23 0.2 0.2  3812 Mission Viejo 5 8.1 15 10.2 12 -3 1.26 0.3 0.3 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 219 (08/07) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 18 10.0 18 5.6 10 -8 0.56 -2.6 2.6 - Subregional Peak: 9.1 20 2 0.91 (at cell 82 x  4157 Indio Jackson 3 7.7 21 4.9 16 -5 0.63 -0.4 0.4 - 4137 Palm Springs 15 10.0 18 5.6 10 -8 0.56 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 220 (08/08) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 22 11.2 14 11.4 14 0 1.01 1.5 1.9  Subregional Peak: 13.5 15 1 1.20 (at cell 52 x  0069 Burbank 5 7.9 13 11.2 14 1 1.41 0.4 0.4  0088 Pasadena 4 8.3 13 11.4 14 1 1.37 0.5 0.5  0074 Reseda 5 10.5 13 9.2 12 -1 0.87 0.0 0.1  0090 Santa Clarita 8 11.2 14 10.4 13 -1 0.93 0.1 0.1 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 220 (08/08) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 88 10.2 14 13.0 15 1 1.28 2.1 2.3  Subregional Peak: 13.5 16 2 1.32 (at cell 59 x  0060 Azusa 4 8.4 13 12.7 15 2 1.51 0.6 0.6  4164 Banning Airport 7 7.7 11 6.3 10 -1 0.82 -0.1 0.1  5181 Crestline 17 9.4 17 10.7 18 1 1.14 0.1 0.2  4158 Elsinore 8 8.2 15 8.8 17 2 1.07 0.0 0.1  5197 Fontana 5 9.4 15 12.7 16 1 1.35 0.5 0.5  0591 Glendora 5 9.9 14 12.8 15 1 1.29 0.5 0.5  5212 Mira Loma 9 10.2 14 12.6 15 1 1.24 0.2 0.2  4149 Perris 5 8.1 17 10.5 17 0 1.30 0.3 0.3  0075 Pomona 6 9.9 14 12.9 14 0 1.30 0.5 0.5  5204 Redlands 5 7.7 16 11.5 17 1 1.50 0.4 0.4  4144 Rubidoux 6 10.1 14 12.6 16 2 1.25 0.2 0.3  5203 San Bernardino 6 9.6 15 11.7 16 1 1.22 0.5 0.5  5175 Upland 5 9.5 14 13.0 15 1 1.37 0.4 0.4  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 220 (08/08) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 15 8.0 16 10.5 14 -2 1.31 1.2 1.9  Subregional Peak: 11.8 14 -2 1.48 (at cell 58 x  3176 Anaheim 5 8.0 16 8.3 14 -2 1.04 0.0 0.2  0087 Los Angeles 2 6.4 15 7.8 14 -1 1.22 0.1 0.1  3177 La Habra 2 6.5 12 9.0 12 0 1.38 0.4 0.4  3812 Mission Viejo 3 7.5 13 10.5 14 1 1.40 0.6 0.6  0091 West Los Angeles 3 6.7 14 8.1 13 -1 1.20 0.1 0.1 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 220 (08/08) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 5 6.8 13 6.3 13 0 0.92 -0.7 0.7 - Subregional Peak: 8.0 11 -2 1.17 (at cell 105 x  4137 Palm Springs 5 6.8 13 6.3 13 0 0.92 -0.1 0.1 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 221 (08/09) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 7 7.2 13 9.8 13 0 1.36 2.4 2.4  Subregional Peak: 12.2 15 2 1.69 (at cell 51 x  0069 Burbank 3 7.2 13 9.8 14 1 1.36 0.3 0.3  0088 Pasadena 3 6.3 13 9.0 14 1 1.42 0.4 0.4  0074 Reseda 1 6.3 13 9.8 13 0 1.55 0.6 0.6 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 221 (08/09) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 81 11.8 13 13.0 15 2 1.10 2.0 2.5  Subregional Peak: 13.2 15 2 1.12 (at cell 74 x  0060 Azusa 2 6.5 14 10.4 13 -1 1.60 0.6 0.6 1 4164 Banning Airport 9 9.0 12 10.8 16 4 1.20 0.0 0.1  5181 Crestline 13 11.8 13 12.6 16 3 1.07 0.0 0.2  4158 Elsinore 6 7.4 13 9.2 16 3 1.25 0.3 0.3  5197 Fontana 6 8.5 12 12.0 15 3 1.42 0.4 0.4  0591 Glendora 3 7.7 14 11.0 14 0 1.43 0.4 0.4  5212 Mira Loma 8 9.0 12 11.9 14 2 1.33 0.4 0.4  4149 Perris 4 9.3 14 11.6 16 2 1.24 0.3 0.3  0075 Pomona 5 7.4 13 11.3 14 1 1.53 0.5 0.5  5204 Redlands 6 10.8 13 13.0 15 2 1.20 0.4 0.4  4144 Rubidoux 7 9.5 12 12.4 15 3 1.30 0.4 0.4  5203 San Bernardino 6 10.5 13 12.8 15 2 1.22 0.4 0.4  5175 Upland 6 8.1 14 11.9 14 0 1.47 0.5 0.5  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 221 (08/09) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 4 7.1 13 10.6 13 0 1.50 2.8 2.8  Subregional Peak: 11.9 15 2 1.68 (at cell 67 x  3176 Anaheim 2 6.1 13 7.9 15 2 1.30 0.3 0.3  3812 Mission Viejo 2 7.1 13 10.6 13 0 1.50 0.6 0.6 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 221 (08/09) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean NSite Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 5 7.3 12 7.2 11 -1 0.99 -0.5 0.9 - Subregional Peak: 11.1 17 5 1.51 (at cell 81 x  4137 Palm Springs 5 7.3 12 7.2 11 -1 0.99 -0.1 0.1 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubRegional Descriptions  SubRegion 003 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0069 Burbank 53 48 -27.848 461.308  0088 Pasadena 56 47 -11.205 457.021  0074 Reseda 49 48 -48.000 463.105  0090 Santa Clarita 49 52 -48.140 483.357  SubRegion 004 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0060 Azusa 60 47 6.981 456.113  4164 Banning Airport 79 42 104.459 433.527  5181 Crestline 72 49 66.383 468.606  4158 Elsinore 71 37 60.525 405.907  5197 Fontana 68 46 46.811 453.081  0591 Glendora 61 47 13.487 457.010  5212 Mira Loma 67 43 42.938 438.915  4149 Perris 72 39 69.051 417.376  0075 Pomona 63 45 22.598 448.610  5204 Redlands 74 45 76.256 448.189  4144 Rubidoux 69 44 52.093 442.557  5203 San Bernardino 72 46 65.874 453.299  5175 Upland 65 46 31.687 452.125  SubRegion 005 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  3176 Anaheim 60 40 7.422 421.645  0087 Los Angeles 54 45 -22.302 445.563  3195 Costa Mesa 60 37 6.793 405.626  3177 La Habra 59 42 4.359 432.978  0820 LAXH 51 42 -36.352 433.685  0072 Long Beach 55 40 -17.171 421.903  0084 Lynwood 55 42 -19.237 432.753  3812 Mission Viejo 64 36 29.671 400.791  0085 Pico Rivera 57 44 -5.273 442.860  0091 West Los Angeles 52 45 -34.796 447.031  SubRegion 009 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  4157 Indio Jackson 91 38 162.217 411.293  4137 Palm Springs 85 40 132.826 423.133 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 214 (08/02) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 2 9.4 10 7.5 11 1 0.79 -0.9 1.1 - Subregional Peak: 7.9 11 1 0.84 (at 51 x 54) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 214 (08/02) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 10 8.9 13 8.1 11 -2 0.91 0.0 1.0  Subregional Peak: 8.3 11 -2 0.93 (at 74 x 44) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 215 (08/03) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 2 8.8 10 7.9 10 0 0.90 0.1 1.0  Subregional Peak: 8.3 11 1 0.94 (at 51 x 53) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 215 (08/03) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 11 8.5 13 9.0 14 1 1.05 0.9 1.1  Subregional Peak: 9.0 11 -2 1.06 (at 72 x 44) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 215 (08/03) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 1 6.3 15 5.9 9 -6 0.93 -0.4 0.4 - Subregional Peak: 7.8 17 2 1.23 (at 82 x 41) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 216 (08/04) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 3 10.8 10 8.3 10 0 0.77 -1.0 1.2 - Subregional Peak: 10.0 14 4 0.93 (at 53 x 51) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 216 (08/04) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 10.1 12 9.6 10 -2 0.94 0.7 1.3  Subregional Peak: 10.0 10 -2 0.99 (at 70 x 41) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 216 (08/04) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 2 6.7 10 6.1 10 0 0.90 -1.0 1.0 - Subregional Peak: 9.7 10 0 1.45 (at 67 x 36) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 216 (08/04) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 1 7.0 9 6.0 12 3 0.85 -1.0 1.0 - Subregional Peak: 7.8 15 6 1.12 (at 82 x 41) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 217 (08/05) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 2 11.0 10 9.1 11 1 0.83 -0.8 1.0 - Subregional Peak: 9.9 15 5 0.91 (at 53 x 51) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 217 (08/05) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 12 9.9 12 9.9 11 -1 1.00 0.5 1.3  Subregional Peak: 10.1 11 -1 1.02 (at 70 x 43) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 217 (08/05) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 7.9 13 5.0 9 -4 0.63 -2.1 2.1 - Subregional Peak: 6.0 16 3 0.76 (at 82 x 41) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 218 (08/06) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 11.8 10 10.2 11 1 0.86 0.4 1.9  Subregional Peak: 10.7 13 3 0.91 (at 53 x 49) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 218 (08/06) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 11.0 11 10.0 11 0 0.91 -0.3 1.1 - Subregional Peak: 10.5 11 0 0.95 (at 62 x 43) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 218 (08/06) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 2 6.6 11 10.3 10 -1 1.56 2.9 2.9  Subregional Peak: 10.7 10 -1 1.61 (at 62 x 41) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 218 (08/06) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 6.3 8 5.0 9 1 0.79 -1.4 1.4 - Subregional Peak: 6.6 18 10 1.04 (at 82 x 41) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 219 (08/07) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 11.0 10 10.6 10 0 0.96 1.0 2.3  Subregional Peak: 11.2 11 1 1.02 (at 54 x 49) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 219 (08/07) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 11.4 10 11.0 10 0 0.96 -0.3 1.3 - Subregional Peak: 11.0 10 0 0.96 (at 61 x 47) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 219 (08/07) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 2 6.7 10 8.9 9 -1 1.33 1.9 1.9  Subregional Peak: 10.5 10 0 1.56 (at 58 x 46) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 219 (08/07) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 7.7 14 5.3 7 -7 0.69 -1.8 1.8 - Subregional Peak: 8.1 17 3 1.05 (at 82 x 41) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 220 (08/08) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 8.5 9 9.5 10 1 1.12 1.8 1.8  Subregional Peak: 12.0 13 4 1.41 (at 58 x 49) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 220 (08/08) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 8.5 10 11.1 10 0 1.30 2.7 2.8  Subregional Peak: 12.1 13 3 1.42 (at 59 x 49) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 220 (08/08) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 1 6.5 11 6.8 9 -2 1.05 0.3 0.3  Subregional Peak: 9.9 11 0 1.53 (at 65 x 39) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 220 (08/08) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 1 6.0 10 6.3 8 -2 1.04 0.2 0.2  Subregional Peak: 7.7 21 11 1.27 (at 82 x 41) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 221 (08/09) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 11 10.8 9 11.3 10 1 1.05 2.5 2.6  Subregional Peak: 11.4 10 1 1.06 (at 74 x 45) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0000 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 214  Unpaired Subregional Maximum of 9.3 at Cell 82 x 10 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 214 215 216 217 218 Avg. 214 215 216 217 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0001 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 214  Unpaired Subregional Maximum of 6.5 at Cell 27 x 54 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 214 215 216 217 218 Avg. 214 215 216 217 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0002 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 214  Unpaired Subregional Maximum of 8.6 at Cell 49 x 52 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 214 215 216 217 218 Avg. 214 215 216 217 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0003 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 214  Unpaired Subregional Maximum of 9.6 at Cell 54 x 50 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 214 215 216 217 218 Avg. 214 215 216 217 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 0069 Burbank 7.3 5.1 5.4 5.9 5.4 7.7 8.1 6.1 6.9 7.6 7.0 0088 Pasadena 7.5 5.6 5.8 7.0 5.3 8.6 8.1 6.1 6.4 7.3 7.1 0074 Reseda 7.9 6.7 6.6 9.1 8.8 8.6 8.4 6.9 7.7 8.3 9.0 0090 Santa Clarita 10.2 9.4 8.8 10.8 11.0 11.8 8.5 7.5 7.9 8.2 9.1  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0004 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 214  Unpaired Subregional Maximum of 9.6 at Cell 69 x 43 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 214 215 216 217 218 Avg. 214 215 216 217 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 0060 Azusa 7.5 4.9 5.6 6.7 5.2 8.4 8.8 6.6 7.0 8.0 8.6 4164 Banning Airport 8.3 8.9 8.3 9.3 9.0 6.7 7.0 6.5 7.0 7.3 5.6 5181 Crestline 9.8 8.8 8.5 10.1 9.9 10.5 8.8 8.0 9.0 8.4 8.8 4158 Elsinore 7.7 7.6 7.2 8.1 7.6 7.9 7.6 6.1 7.6 9.0 7.5 5197 Fontana 8.1 6.6 6.7 7.9 8.2 11.0 9.0 7.4 8.1 8.6 8.7 0591 Glendora 7.7 5.7 6.1 7.7 6.3 9.6 9.1 7.0 7.4 8.5 9.0 5212 Mira Loma 8.4 7.2 7.3 8.0 8.4 10.2 9.4 7.8 8.2 9.1 9.7 4149 Perris 6.8 6.7 6.9 7.6 7.7 6.1 8.5 7.2 7.9 9.6 8.3 0075 Pomona 7.5 5.5 5.7 6.7 6.4 9.1 9.0 6.9 7.2 8.0 8.8 5204 Redlands 8.0 7.3 7.3 8.0 9.1 7.3 9.2 8.1 8.8 9.2 8.8 4144 Rubidoux 8.3 7.3 7.4 7.8 8.4 9.8 9.5 7.9 8.6 9.4 9.9 5203 San Bernardino 8.5 7.1 7.4 8.4 9.4 8.9 9.2 7.8 8.8 8.9 9.1 5175 Upland 7.6 6.1 6.1 7.2 7.3 10.3 9.1 7.3 7.6 8.5 8.8 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0005 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 214  Unpaired Subregional Maximum of 9.3 at Cell 66 x 42 -- Nearest Site: 52 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 214 215 216 217 218 Avg. 214 215 216 217 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 3176 Anaheim 6.5 4.9 5.1 5.8 5.2 5.9 7.2 5.9 5.8 5.9 7.6 0087 Los Angeles 6.3 4.5 4.7 5.6 3.7 6.3 6.2 4.9 5.3 5.5 5.5 0820 LAXH 6.5 4.8 5.5 6.5 4.1 4.7 5.7 4.8 5.3 5.1 5.4 3812 Mission Viejo 6.7 4.5 4.5 5.0 4.8 6.6 8.5 6.7 7.1 8.3 8.5 0091 West Los Angeles 6.7 4.9 5.9 6.7 4.3 5.3 6.6 5.3 5.8 6.1 6.2  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0006 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 214  Unpaired Subregional Maximum of 9.4 at Cell 80 x 18 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 214 215 216 217 218 Avg. 214 215 216 217 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0007 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 214  Unpaired Subregional Maximum of 6.5 at Cell 40 x 66 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 214 215 216 217 218 Avg. 214 215 216 217 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0008 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 214  Unpaired Subregional Maximum of 7.4 at Cell 70 x 58 -- Nearest Site: 51
 - - - - - Observed - - - - - - - - - - Simulated - - 

Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 214 215 216 217 218 Avg. 214 215 216 217 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0009 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 214  Unpaired Subregional Maximum of 7.7 at Cell 91 x 41 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 214 215 216 217 218 Avg. 214 215 216 217 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 4157 Indio Jackson 6.2 4.4 4.6 5.8 6.1 6.3 5.5 4.6 5.3 6.6 5.0 4137 Palm Springs 6.9 6.0 6.3 7.0 7.9 6.2 5.5 4.5 5.9 6.0 4.8 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubRegional Descriptions  SubRegion 003 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0069 Burbank 53 48 -27.848 461.308  0088 Pasadena 56 47 -11.205 457.021  0074 Reseda 49 48 -48.000 463.105  0090 Santa Clarita 49 52 -48.140 483.357  SubRegion 004 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0060 Azusa 60 47 6.981 456.113  4164 Banning Airport 79 42 104.459 433.527  5181 Crestline 72 49 66.383 468.606  4158 Elsinore 71 37 60.525 405.907  5197 Fontana 68 46 46.811 453.081  0591 Glendora 61 47 13.487 457.010  5212 Mira Loma 67 43 42.938 438.915  4149 Perris 72 39 69.051 417.376  0075 Pomona 63 45 22.598 448.610  5204 Redlands 74 45 76.256 448.189  4144 Rubidoux 69 44 52.093 442.557  5203 San Bernardino 72 46 65.874 453.299  5175 Upland 65 46 31.687 452.125  SubRegion 005 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  3176 Anaheim 60 40 7.422 421.645  0087 Los Angeles 54 45 -22.302 445.563  3195 Costa Mesa 60 37 6.793 405.626  3177 La Habra 59 42 4.359 432.978  0820 LAXH 51 42 -36.352 433.685  0072 Long Beach 55 40 -17.171 421.903  0084 Lynwood 55 42 -19.237 432.753  3812 Mission Viejo 64 36 29.671 400.791  0085 Pico Rivera 57 44 -5.273 442.860  0091 West Los Angeles 52 45 -34.796 447.031  SubRegion 009 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  4157 Indio Jackson 91 38 162.217 411.293  4137 Palm Springs 85 40 132.826 423.133 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 217 (08/04) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 22 9.9 15 6.7 13 -2 0.68 -2.0 2.0 - Subregional Peak: 8.5 15 0 0.86 (at cell 53 x  0069 Burbank 4 7.2 14 5.9 13 -1 0.82 -0.2 0.2 - 0088 Pasadena 4 7.1 14 5.2 14 0 0.73 -0.3 0.3 - 0074 Reseda 7 8.0 16 6.4 12 -4 0.80 -0.3 0.3 - 0090 Santa Clarita 7 9.9 15 6.7 13 -2 0.68 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 217 (08/04) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 86 12.0 14 7.9 15 1 0.66 -3.2 3.2 - Subregional Peak: 8.8 15 1 0.73 (at cell 79 x  0060 Azusa 3 7.4 15 5.3 14 -1 0.72 -0.3 0.3 -1 4164 Banning Airport 13 12.0 14 7.9 15 1 0.66 -0.5 0.5 - 5181 Crestline 15 10.9 15 6.2 13 -2 0.57 -0.4 0.4 - 4158 Elsinore 7 11.1 15 7.9 14 -1 0.71 -0.3 0.3 - 5197 Fontana 5 8.1 13 5.0 13 0 0.62 -0.4 0.4 - 0591 Glendora 4 8.3 15 5.5 14 -1 0.66 -0.3 0.3 - 4149 Perris 9 10.2 15 7.2 13 -2 0.71 -0.3 0.3 - 0075 Pomona 4 6.5 15 5.2 15 0 0.80 -0.3 0.3 - 5204 Redlands 7 10.0 16 7.0 13 -3 0.70 -0.4 0.4 - 4144 Rubidoux 9 9.1 14 6.1 11 -3 0.67 -0.4 0.4 - 5203 San Bernardino 5 9.1 15 6.6 13 -2 0.72 -0.4 0.4 - 5175 Upland 5 7.5 16 5.1 15 -1 0.68 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 217 (08/04) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 14 8.0 13 6.5 13 0 0.82 -2.2 2.3 - Subregional Peak: 8.0 14 1 1.00 (at cell 68 x  3176 Anaheim 6 8.0 13 4.7 14 1 0.58 -0.5 0.5 - 0820 LAXH 2 7.0 12 4.9 12 0 0.70 -0.3 0.3 - 3812 Mission Viejo 4 6.6 15 6.5 13 -2 0.99 0.0 0.1 - 0085 Pico Rivera 2 6.7 14 5.0 13 -1 0.74 -0.2 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 217 (08/04) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 12 10.9 18 6.3 17 -1 0.58 -2.2 2.2 - Subregional Peak: 12.6 13 -5 1.16 (at cell 106 x  4157 Indio Jackson 2 6.7 11 5.8 11 0 0.87 -0.2 0.2 - 4137 Palm Springs 10 10.9 18 6.3 17 -1 0.58 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 218 (08/05) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 29 11.0 15 8.9 13 -2 0.81 -2.8 2.8 - Subregional Peak: 10.8 15 0 0.98 (at cell 52 x  0069 Burbank 5 8.6 14 6.6 14 0 0.77 -0.4 0.4 - 0088 Pasadena 6 8.3 14 6.3 13 -1 0.76 -0.4 0.4 - 0074 Reseda 10 9.6 14 7.9 14 0 0.82 -0.4 0.4 - 0090 Santa Clarita 8 11.0 15 8.9 13 -2 0.81 -0.2 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 218 (08/05) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 98 11.2 14 11.0 14 0 0.98 -2.1 2.6 - Subregional Peak: 11.7 14 0 1.04 (at cell 77 x  0060 Azusa 5 7.9 13 6.8 14 1 0.86 -0.2 0.2 - 4164 Banning Airport 10 9.7 13 11.0 14 1 1.14 -0.1 0.2 - 5181 Crestline 14 10.6 15 7.7 13 -2 0.73 -0.4 0.4 - 4158 Elsinore 7 8.7 12 10.1 15 3 1.16 0.2 0.2 - 5197 Fontana 6 9.3 15 5.6 12 -3 0.60 -0.4 0.4 - 0591 Glendora 6 8.5 14 7.3 15 1 0.86 -0.2 0.2 - 5212 Mira Loma 7 10.0 11 6.1 13 2 0.61 -0.4 0.4 - 4149 Perris 9 10.7 15 9.2 13 -2 0.86 0.0 0.1 - 0075 Pomona 6 8.7 14 6.1 16 2 0.70 -0.3 0.3 - 5204 Redlands 9 11.2 14 9.4 13 -1 0.84 -0.4 0.4 - 4144 Rubidoux 7 9.9 12 7.9 11 -1 0.80 -0.3 0.4 - 5203 San Bernardino 6 9.6 15 8.2 13 -2 0.86 -0.4 0.4 - 5175 Upland 6 8.7 15 6.1 16 1 0.70 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 218 (08/05) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 52 8.7 16 7.6 13 -3 0.87 -3.0 3.1 - Subregional Peak: 10.0 14 -2 1.15 (at cell 68 x  3176 Anaheim 7 7.6 11 5.2 15 4 0.68 -0.5 0.5 - 0087 Los Angeles 6 7.0 15 5.4 12 -3 0.77 -0.5 0.5 - 3195 Costa Mesa 2 6.3 3 1.4 3 0 0.23 -0.8 0.8 -1 3177 La Habra 5 6.9 12 5.2 15 3 0.76 -0.4 0.4 - 0820 LAXH 15 8.7 16 5.8 12 -4 0.67 -0.6 0.6 - 0084 Lynwood 2 6.2 13 5.8 13 0 0.94 -0.2 0.2 -1 3812 Mission Viejo 3 6.7 12 7.6 13 1 1.13 0.1 0.1 - 0085 Pico Rivera 4 7.3 13 6.5 14 1 0.90 -0.2 0.2 - 0091 West Los Angeles 8 8.6 16 5.8 13 -3 0.68 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 218 (08/05) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 18 8.1 18 8.8 15 -3 1.08 -0.8 1.4 - Subregional Peak: 12.6 13 -5 1.56 (at cell 107 x  4157 Indio Jackson 8 7.3 10 7.3 11 1 1.00 -0.2 0.3 - 4137 Palm Springs 10 8.1 18 8.8 15 -3 1.08 0.0 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 219 (08/06) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 37 10.0 14 9.8 13 -1 0.98 -1.9 2.0 - Subregional Peak: 12.3 15 1 1.23 (at cell 55 x  0069 Burbank 7 8.7 13 8.6 13 0 0.99 -0.2 0.2 - 0088 Pasadena 8 9.8 14 7.8 14 0 0.79 -0.3 0.3 - 0074 Reseda 11 8.6 15 9.0 12 -3 1.05 -0.2 0.3 - 0090 Santa Clarita 11 10.0 14 9.8 13 -1 0.98 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 219 (08/06) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 97 10.7 16 11.9 14 -2 1.11 0.2 1.6  Subregional Peak: 12.8 14 -2 1.20 (at cell 71 x  0060 Azusa 2 8.8 14 8.3 14 0 0.94 0.0 0.1  4164 Banning Airport 12 8.1 16 11.5 15 -1 1.42 0.0 0.2  5181 Crestline 18 10.7 16 9.0 15 -1 0.84 -0.2 0.2  4158 Elsinore 7 8.5 14 11.9 14 0 1.40 0.3 0.4  5197 Fontana 7 8.7 14 10.4 13 -1 1.20 0.1 0.3  0591 Glendora 5 9.6 15 8.6 14 -1 0.89 -0.1 0.1  5212 Mira Loma 8 9.2 13 10.5 12 -1 1.15 0.0 0.2  4149 Perris 3 8.3 16 10.1 15 -1 1.21 0.2 0.2  0075 Pomona 5 7.5 16 8.7 14 -2 1.16 0.1 0.2  5204 Redlands 8 10.7 15 11.0 15 0 1.03 0.1 0.2  4144 Rubidoux 10 10.1 14 11.0 13 -1 1.09 0.0 0.2  5203 San Bernardino 6 9.8 15 10.5 14 -1 1.07 0.2 0.2  5175 Upland 6 7.9 14 9.3 14 0 1.17 0.1 0.2 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 219 (08/06) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 49 9.0 13 8.9 14 1 0.99 -1.7 1.9 - Subregional Peak: 9.5 15 2 1.06 (at cell 68 x  3176 Anaheim 8 8.4 14 5.7 13 -1 0.68 -0.4 0.4 - 0087 Los Angeles 3 8.0 16 5.3 11 -5 0.66 -0.4 0.4 - 3195 Costa Mesa 4 6.9 11 7.9 13 2 1.14 0.0 0.2 - 3177 La Habra 6 6.9 14 7.2 14 0 1.04 -0.1 0.1 - 0820 LAXH 8 8.2 14 5.4 14 0 0.66 -0.4 0.4 - 0084 Lynwood 3 6.9 12 6.1 12 0 0.88 -0.1 0.1 - 3812 Mission Viejo 5 8.7 13 8.9 14 1 1.02 0.0 0.1 - 0085 Pico Rivera 5 9.0 13 7.4 13 0 0.82 -0.2 0.2 - 0091 West Los Angeles 7 8.6 15 6.4 12 -3 0.75 -0.2 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 219 (08/06) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 27 8.1 12 8.3 15 3 1.03 -0.5 0.9 - Subregional Peak: 11.6 15 3 1.43 (at cell 81 x  4157 Indio Jackson 14 8.1 12 8.3 15 3 1.03 -0.1 0.1 - 4137 Palm Springs 13 8.1 19 7.8 14 -5 0.96 0.0 0.1 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 220 (08/07) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 36 12.8 14 10.8 12 -2 0.84 -1.6 1.9 - Subregional Peak: 14.7 15 1 1.15 (at cell 55 x  0069 Burbank 7 9.1 13 10.7 13 0 1.18 0.0 0.1 - 0088 Pasadena 8 9.2 14 9.8 13 -1 1.06 -0.2 0.2 - 0074 Reseda 11 10.8 13 10.8 12 -1 1.00 -0.2 0.3 - 0090 Santa Clarita 10 12.8 14 8.6 13 -1 0.67 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 220 (08/07) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 134 15.6 16 12.7 15 -1 0.82 -1.3 1.5 - Subregional Peak: 13.3 16 0 0.85 (at cell 61 x  0060 Azusa 7 10.2 13 10.2 14 1 1.00 -0.1 0.2 - 4164 Banning Airport 15 15.6 16 11.5 16 0 0.74 -0.1 0.2 - 5181 Crestline 18 13.8 16 11.2 15 -1 0.81 -0.2 0.2 - 4158 Elsinore 11 10.6 15 12.4 14 -1 1.17 -0.1 0.2 - 5197 Fontana 9 12.3 14 10.8 14 0 0.88 -0.1 0.1 - 0591 Glendora 7 11.5 13 10.6 15 2 0.92 -0.1 0.2 - 5212 Mira Loma 10 11.8 13 10.5 12 -1 0.89 -0.1 0.1 - 4149 Perris 11 12.1 14 10.8 14 0 0.90 -0.1 0.1 - 0075 Pomona 7 11.6 14 11.0 15 1 0.95 -0.1 0.1 - 5204 Redlands 12 14.8 15 12.7 15 0 0.86 -0.2 0.2 - 4144 Rubidoux 10 12.7 13 11.3 13 0 0.89 -0.1 0.1 - 5203 San Bernardino 9 13.7 15 12.4 14 -1 0.90 -0.1 0.2 - 5175 Upland 8 11.8 14 10.8 15 1 0.92 -0.1 0.1 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 220 (08/07) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 27 9.3 14 9.5 14 0 1.02 -0.8 1.2 - Subregional Peak: 10.6 15 1 1.14 (at cell 68 x  3176 Anaheim 6 8.4 13 8.1 13 0 0.97 -0.2 0.2 - 0087 Los Angeles 4 9.3 14 7.0 12 -2 0.75 -0.2 0.2 - 3177 La Habra 4 7.9 14 8.8 14 0 1.11 0.1 0.1 - 0084 Lynwood 1 6.1 12 6.8 12 0 1.12 0.1 0.1 - 3812 Mission Viejo 7 9.2 16 9.5 14 -2 1.04 -0.1 0.1 - 0085 Pico Rivera 5 8.6 13 8.8 13 0 1.02 -0.1 0.1 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 220 (08/07) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 23 11.3 18 9.4 13 -5 0.84 -1.6 2.5 - Subregional Peak: 10.7 15 -3 0.95 (at cell 82 x  4157 Indio Jackson 11 10.8 20 9.4 13 -7 0.87 -0.1 0.3 - 4137 Palm Springs 12 11.3 18 8.7 16 -2 0.77 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 221 (08/08) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 32 13.6 14 10.8 12 -2 0.80 -1.3 1.7 - Subregional Peak: 14.9 14 0 1.09 (at cell 53 x  0069 Burbank 7 10.0 13 10.2 12 -1 1.02 0.1 0.1 - 0088 Pasadena 7 9.8 14 9.7 13 -1 0.99 0.0 0.1 - 0074 Reseda 8 10.4 12 10.8 12 0 1.04 -0.1 0.1 - 0090 Santa Clarita 10 13.6 14 8.2 12 -2 0.60 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 221 (08/08) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 132 13.6 15 14.6 14 -1 1.07 0.3 1.4  Subregional Peak: 15.2 14 -1 1.12 (at cell 71 x  0060 Azusa 6 9.8 13 10.0 13 0 1.02 0.0 0.0  4164 Banning Airport 15 12.2 14 13.1 16 2 1.07 -0.1 0.2  5181 Crestline 15 11.0 15 12.9 14 -1 1.17 0.1 0.3  4158 Elsinore 13 12.2 14 14.4 14 0 1.18 0.0 0.2  5197 Fontana 8 10.8 14 12.8 14 0 1.19 0.2 0.2  0591 Glendora 6 10.9 13 10.8 14 1 0.99 0.0 0.1  5212 Mira Loma 9 11.4 14 11.8 12 -2 1.03 0.0 0.1  4149 Perris 13 10.0 12 13.2 14 2 1.32 0.1 0.2  0075 Pomona 7 11.9 13 11.2 14 1 0.94 0.0 0.1  5204 Redlands 13 13.6 15 14.6 14 -1 1.07 -0.1 0.2  4144 Rubidoux 10 12.0 14 13.1 13 -1 1.09 0.1 0.2  5203 San Bernardino 9 13.6 15 14.3 14 -1 1.05 0.1 0.2  5175 Upland 8 11.2 14 12.0 14 0 1.07 0.1 0.1 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 221 (08/08) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 25 8.4 14 10.1 13 -1 1.21 -0.6 1.2 - Subregional Peak: 12.0 12 -2 1.43 (at cell 68 x  3176 Anaheim 7 8.4 14 6.9 13 -1 0.82 -0.3 0.3 - 0087 Los Angeles 3 7.4 13 6.0 12 -1 0.81 -0.2 0.2 - 3177 La Habra 5 8.2 14 8.2 13 -1 1.00 0.0 0.1 - 3812 Mission Viejo 6 8.2 14 10.1 13 -1 1.23 0.1 0.1 - 0085 Pico Rivera 4 7.7 12 7.6 12 0 0.99 0.0 0.0 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 221 (08/08) 2004  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 43 11.0 16 8.9 16 0 0.81 -1.9 2.2 - Subregional Peak: 12.2 16 0 1.11 (at cell 82 x  4157 Indio Jackson 22 9.4 19 8.0 16 -3 0.85 -0.3 0.3 - 4137 Palm Springs 21 11.0 16 8.9 16 0 0.81 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubRegional Descriptions  SubRegion 003 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0069 Burbank 53 48 -27.848 461.308  0088 Pasadena 56 47 -11.205 457.021  0074 Reseda 49 48 -48.000 463.105  0090 Santa Clarita 49 52 -48.140 483.357  SubRegion 004 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0060 Azusa 60 47 6.981 456.113  4164 Banning Airport 79 42 104.459 433.527  5181 Crestline 72 49 66.383 468.606  4158 Elsinore 71 37 60.525 405.907  5197 Fontana 68 46 46.811 453.081  0591 Glendora 61 47 13.487 457.010  5212 Mira Loma 67 43 42.938 438.915  4149 Perris 72 39 69.051 417.376  0075 Pomona 63 45 22.598 448.610  5204 Redlands 74 45 76.256 448.189  4144 Rubidoux 69 44 52.093 442.557  5203 San Bernardino 72 46 65.874 453.299  5175 Upland 65 46 31.687 452.125  SubRegion 005 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  3176 Anaheim 60 40 7.422 421.645  0087 Los Angeles 54 45 -22.302 445.563  3195 Costa Mesa 60 37 6.793 405.626  3177 La Habra 59 42 4.359 432.978  0820 LAXH 51 42 -36.352 433.685  0072 Long Beach 55 40 -17.171 421.903  0084 Lynwood 55 42 -19.237 432.753  3812 Mission Viejo 64 36 29.671 400.791  0085 Pico Rivera 57 44 -5.273 442.860  0091 West Los Angeles 52 45 -34.796 447.031  SubRegion 009 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  4157 Indio Jackson 91 38 162.217 411.293  4137 Palm Springs 85 40 132.826 423.133 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 217 (08/04) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 2 7.8 11 5.7 10 -1 0.72 -2.0 2.0 - Subregional Peak: 6.6 11 0 0.85 (at 52 x 55) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 217 (08/04) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 10 11.1 11 6.7 10 -1 0.60 -2.9 2.9 - Subregional Peak: 7.1 11 0 0.64 (at 72 x 36) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 217 (08/04) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 1 6.9 9 3.5 10 1 0.51 -3.4 3.4 - Subregional Peak: 6.8 10 1 0.98 (at 68 x 37) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 217 (08/04) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 1 7.4 12 6.3 10 -2 0.85 -1.1 1.1 - Subregional Peak: 10.4 10 -2 1.41 (at 106 x 12) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 218 (08/05) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 9.0 11 7.0 10 -1 0.78 -2.1 2.1 - Subregional Peak: 8.3 11 0 0.92 (at 53 x 55) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 218 (08/05) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 9.9 11 9.0 10 -1 0.91 -1.8 2.0 - Subregional Peak: 9.2 10 -1 0.92 (at 71 x 37) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 218 (08/05) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 6 8.0 11 5.1 10 -1 0.64 -2.4 2.4 - Subregional Peak: 8.5 10 -1 1.07 (at 68 x 37) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 218 (08/05) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 7.4 12 7.8 10 -2 1.05 0.8 0.8  Subregional Peak: 9.2 9 -3 1.23 (at 107 x 12) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 219 (08/06) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 8.9 10 7.4 9 -1 0.83 -1.4 1.4 - Subregional Peak: 9.2 11 1 1.04 (at 55 x 53) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 219 (08/06) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 11 9.4 14 9.9 10 -4 1.06 0.7 1.1  Subregional Peak: 10.6 10 -4 1.13 (at 76 x 44) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 219 (08/06) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 6 7.7 9 6.8 10 1 0.88 -1.6 1.6 - Subregional Peak: 8.6 10 1 1.12 (at 68 x 37) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 219 (08/06) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 7.7 10 7.7 10 0 1.01 0.2 0.2  Subregional Peak: 8.9 11 1 1.16 (at 81 x 44) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 220 (08/07) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 10.3 10 8.1 10 0 0.79 -1.1 1.2 - Subregional Peak: 11.5 13 3 1.11 (at 59 x 50) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 220 (08/07) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 12.4 15 10.4 10 -5 0.84 -1.1 1.1 - Subregional Peak: 11.1 10 -5 0.89 (at 76 x 44) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 220 (08/07) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 5 7.6 11 7.1 10 -1 0.93 -0.7 0.9 - Subregional Peak: 9.1 10 -1 1.21 (at 68 x 37) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 220 (08/07) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 9.1 17 8.4 10 -7 0.92 -1.1 1.1 - Subregional Peak: 9.7 11 -6 1.06 (at 81 x 43) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 221 (08/08) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 11.3 10 8.6 9 -1 0.76 -1.1 1.2 - Subregional Peak: 11.9 11 1 1.04 (at 59 x 50) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 221 (08/08) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 12.2 11 12.9 10 -1 1.06 0.7 0.8  Subregional Peak: 13.4 10 -1 1.10 (at 74 x 46) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 221 (08/08) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 3 7.1 10 7.6 10 0 1.06 -0.3 0.8 - Subregional Peak: 10.2 9 -1 1.43 (at 68 x 37) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 221 (08/08) 2004 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 9.9 13 7.8 11 -2 0.79 -1.3 1.3 - Subregional Peak: 10.7 11 -2 1.08 (at 81 x 43) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0000 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 217  Unpaired Subregional Maximum of 9.4 at Cell 83 x 8 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 217 218 219 220 221 Avg. 217 218 219 220 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0001 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 217  Unpaired Subregional Maximum of -99.0 at Cell -9 x -9 -- Nearest Site: 08 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 217 218 219 220 221 Avg. 217 218 219 220 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0002 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 217  Unpaired Subregional Maximum of 7.3 at Cell 49 x 52 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 217 218 219 220 221 Avg. 217 218 219 220 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0003 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 217  Unpaired Subregional Maximum of 9.5 at Cell 53 x 52 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 217 218 219 220 221 Avg. 217 218 219 220 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 0069 Burbank 7.7 6.0 7.3 7.8 7.7 7.9 6.5 4.6 5.4 6.5 8.0 0088 Pasadena 7.7 5.9 7.3 8.0 8.0 7.7 5.8 3.8 4.7 5.8 7.0 0074 Reseda 8.3 7.2 8.5 8.0 8.7 8.9 7.2 5.4 6.6 7.4 8.1 0090 Santa Clarita 9.5 7.8 9.0 8.9 10.3 11.3 6.9 5.7 7.0 7.4 7.2 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0004 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 217  Unpaired Subregional Maximum of 10.7 at Cell 76 x 44 -- Nearest Site: 52 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 217 218 219 220 221 Avg. 217 218 219 220 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 0060 Azusa 7.5 5.5 6.7 5.5 8.2 7.6 6.1 4.1 5.2 6.4 7.1 4164 Banning Airport 10.0 11.1 9.1 7.3 11.2 11.4 9.1 6.5 8.7 8.7 10.2 5181 Crestline 10.2 9.6 9.9 9.4 12.4 9.7 8.0 5.3 6.2 7.6 9.4 4158 Elsinore 9.1 10.3 7.3 7.3 10.1 10.9 9.5 6.7 9.0 9.9 10.0 5197 Fontana 8.2 6.8 7.9 7.3 10.0 9.3 7.7 4.6 5.3 8.2 9.4 0591 Glendora 7.5 6.1 7.1 7.3 8.8 8.3 6.7 4.4 5.5 7.0 7.9 5212 Mira Loma 9.2 0.5 8.5 7.8 10.4 10.0 7.5 4.6 5.7 7.9 9.1 4149 Perris 9.4 9.1 8.7 5.9 10.4 9.4 8.9 6.1 8.5 9.2 9.6 0075 Pomona 8.0 5.6 7.2 6.3 9.0 9.3 6.8 4.2 4.7 7.4 8.5 5204 Redlands 9.9 8.4 9.0 8.1 12.0 12.2 8.9 5.5 6.7 9.2 10.4 4144 Rubidoux 9.3 8.3 8.4 8.2 11.2 10.7 8.1 5.0 6.2 8.4 9.7 5203 San Bernardino 9.1 7.1 8.6 7.3 11.0 11.4 8.5 5.2 6.0 8.6 9.9 5175 Upland 7.7 6.1 7.1 6.8 9.5 9.2 7.1 4.4 4.9 7.9 8.8  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0005 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 217  Unpaired Subregional Maximum of 9.7 at Cell 69 x 38 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 217 218 219 220 221 Avg. 217 218 219 220 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 3176 Anaheim 7.0 6.9 6.6 7.6 6.8 7.1 4.7 3.5 4.2 4.6 5.6 0087 Los Angeles 6.7 4.8 6.6 4.2 6.7 5.7 4.6 3.3 4.2 5.0 5.4 3177 La Habra 6.2 4.8 6.1 6.3 6.1 6.5 5.2 3.4 3.7 5.8 6.5 0820 LAXH 7.8 5.6 8.0 7.7 5.2 5.3 4.7 4.5 5.1 4.8 4.8 3812 Mission Viejo 7.2 5.9 5.6 7.0 7.6 7.0 6.7 5.6 6.4 6.8 7.1 0085 Pico Rivera 6.6 4.8 6.1 6.7 7.0 5.9 5.2 3.6 4.5 5.7 6.0 0091 West Los Angeles 7.5 4.9 7.7 7.2 5.2 5.1 5.3 4.4 5.0 5.3 6.0 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0006 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 217  Unpaired Subregional Maximum of 9.1 at Cell 80 x 24 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 217 218 219 220 221 Avg. 217 218 219 220 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0007 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 217  Unpaired Subregional Maximum of 6.2 at Cell 50 x 70 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 217 218 219 220 221 Avg. 217 218 219 220 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0008 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 217  Unpaired Subregional Maximum of 7.5 at Cell 78 x 56 -- Nearest Site: 51 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 217 218 219 220 221 Avg. 217 218 219 220 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0009 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 217  Unpaired Subregional Maximum of 9.0 at Cell 84 x 43 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 217 218 219 220 221 Avg. 217 218 219 220 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 4157 Indio Jackson 7.6 5.7 6.2 7.7 8.9 7.8 7.5 6.2 7.6 7.7 8.4 4137 Palm Springs 8.2 7.4 7.4 7.1 9.1 9.9 7.2 6.3 7.8 7.4 7.4 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubRegional Descriptions  SubRegion 003 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0069 Burbank 53 48 -27.848 461.308  0088 Pasadena 56 47 -11.205 457.021  0074 Reseda 49 48 -48.000 463.105  0090 Santa Clarita 49 52 -48.140 483.357  SubRegion 004 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0060 Azusa 60 47 6.981 456.113  4164 Banning Airport 79 42 104.459 433.527  5181 Crestline 72 49 66.383 468.606  4158 Elsinore 71 37 60.525 405.907  5197 Fontana 68 46 46.811 453.081  0591 Glendora 61 47 13.487 457.010  5212 Mira Loma 67 43 42.938 438.915  4149 Perris 72 39 69.051 417.376  0075 Pomona 63 45 22.598 448.610  5204 Redlands 74 45 76.256 448.189  4144 Rubidoux 69 44 52.093 442.557  5203 San Bernardino 72 46 65.874 453.299  5175 Upland 65 46 31.687 452.125  SubRegion 005 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  3176 Anaheim 60 40 7.422 421.645  0087 Los Angeles 54 45 -22.302 445.563  3195 Costa Mesa 60 37 6.793 405.626  3177 La Habra 59 42 4.359 432.978  0820 LAXH 51 42 -36.352 433.685  0072 Long Beach 55 40 -17.171 421.903  0084 Lynwood 55 42 -19.237 432.753  3812 Mission Viejo 64 36 29.671 400.791  0085 Pico Rivera 57 44 -5.273 442.860  0091 West Los Angeles 52 45 -34.796 447.031  SubRegion 009 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  4157 Indio Jackson 91 38 162.217 411.293  4137 Palm Springs 85 40 132.826 423.133 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 237 (08/25) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 5 8.1 15 7.4 14 -1 0.91 -0.7 1.0 - Subregional Peak: 9.8 14 -1 1.21 (at cell 49 x  0088 Pasadena 1 7.5 13 6.4 13 0 0.85 -0.2 0.2 - 0074 Reseda 1 6.7 16 7.0 16 0 1.04 0.0 0.0 - 0090 Santa Clarita 3 8.1 15 7.4 14 -1 0.91 -0.1 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 237 (08/25) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 35 8.6 15 8.7 15 0 1.01 -1.2 1.6 - Subregional Peak: 9.3 14 -1 1.08 (at cell 72 x  0060 Azusa 2 6.9 14 6.5 14 0 0.94 -0.1 0.1 - 4164 Banning Airport 5 8.0 16 6.2 15 -1 0.78 -0.4 0.4 - 5181 Crestline 3 7.7 17 7.2 16 -1 0.94 -0.1 0.1 - 4158 Elsinore 2 6.8 14 6.2 14 0 0.91 -0.1 0.1 - 5197 Fontana 2 7.8 15 6.3 15 0 0.81 -0.3 0.3 - 0591 Glendora 1 6.9 14 6.2 14 0 0.90 -0.1 0.1 - 5212 Mira Loma 5 8.6 15 8.2 14 -1 0.96 -0.1 0.3 - 0075 Pomona 2 7.3 14 5.3 15 1 0.73 -0.3 0.3 - 5204 Redlands 3 7.1 17 6.4 16 -1 0.91 -0.1 0.1 - 4144 Rubidoux 4 8.0 16 8.7 15 -1 1.08 -0.1 0.2 - 5203 San Bernardino 4 7.4 16 6.6 15 -1 0.89 -0.2 0.2 - 5175 Upland 2 8.0 15 5.7 14 -1 0.72 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 237 (08/25) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 29 10.9 14 6.5 14 0 0.60 -2.7 2.7 - Subregional Peak: 8.2 13 -1 0.75 (at cell 68 x  3176 Anaheim 3 6.6 16 4.0 14 -2 0.61 -0.4 0.4 - 0087 Los Angeles 3 7.2 15 4.8 12 -3 0.67 -0.4 0.4 - 3195 Costa Mesa 5 8.0 13 6.5 14 1 0.81 -0.3 0.3 - 0820 LAXH 7 8.0 12 5.6 12 0 0.70 -0.3 0.3 - 0072 Long Beach 4 7.2 15 5.7 13 -2 0.80 -0.3 0.3 - 0091 West Los Angeles 7 10.9 14 5.9 13 -1 0.55 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 237 (08/25) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 4 7.2 17 4.3 17 0 0.60 -2.9 2.9 - Subregional Peak: 7.9 13 -4 1.10 (at cell 108 x  4137 Palm Springs 4 7.2 17 4.3 17 0 0.60 -0.4 0.4 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 238 (08/26) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 16 8.8 13 7.3 14 1 0.83 -1.6 1.6 - Subregional Peak: 8.9 15 2 1.01 (at cell 55 x  0069 Burbank 5 8.0 15 7.3 14 -1 0.92 -0.2 0.2 - 0088 Pasadena 6 8.2 14 6.6 14 0 0.80 -0.3 0.3 - 0074 Reseda 3 8.8 13 6.2 11 -2 0.71 -0.2 0.2 - 0090 Santa Clarita 2 7.0 12 6.1 13 1 0.88 -0.1 0.1 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 238 (08/26) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 77 10.4 15 11.0 15 0 1.06 -1.8 2.3 - Subregional Peak: 11.9 15 0 1.15 (at cell 78 x  0060 Azusa 5 7.9 14 7.1 15 1 0.89 -0.2 0.2 - 4164 Banning Airport 9 9.4 16 11.0 15 -1 1.17 0.0 0.3 - 5181 Crestline 10 8.1 16 6.7 13 -3 0.82 -0.3 0.3 - 4158 Elsinore 7 10.0 14 7.8 12 -2 0.78 -0.1 0.2 - 5197 Fontana 5 9.1 16 5.9 16 0 0.65 -0.3 0.3 - 0591 Glendora 7 9.1 14 7.5 15 1 0.82 -0.3 0.3 - 5212 Mira Loma 6 10.3 14 5.9 16 2 0.58 -0.4 0.4 - 4149 Perris 1 7.1 14 8.3 14 0 1.17 0.2 0.2 -1 0075 Pomona 5 9.6 15 7.6 15 0 0.79 -0.2 0.2 - 5204 Redlands 5 9.0 16 9.3 14 -2 1.03 -0.3 0.3 - 4144 Rubidoux 6 10.4 15 6.4 13 -2 0.62 -0.2 0.2 - 5203 San Bernardino 6 8.9 15 7.3 13 -2 0.82 -0.3 0.4 - 5175 Upland 5 9.6 16 7.0 16 0 0.73 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 238 (08/26) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 36 9.4 15 7.0 14 -1 0.74 -2.8 2.8 - Subregional Peak: 8.5 16 1 0.90 (at cell 68 x  3176 Anaheim 7 8.2 15 5.0 14 -1 0.61 -0.5 0.5 - 0087 Los Angeles 4 8.0 16 4.9 14 -2 0.62 -0.6 0.6 - 3195 Costa Mesa 3 7.6 16 6.0 14 -2 0.79 -0.3 0.3 - 3177 La Habra 2 6.8 15 6.0 15 0 0.88 -0.3 0.3 - 0820 LAXH 2 6.9 15 4.7 15 0 0.68 -0.3 0.3 - 0072 Long Beach 3 6.8 14 5.0 13 -1 0.74 -0.3 0.3 - 0084 Lynwood 2 6.9 14 5.4 13 -1 0.78 -0.2 0.2 - 3812 Mission Viejo 7 8.3 16 7.0 14 -2 0.84 -0.3 0.3 - 0091 West Los Angeles 6 9.4 15 5.5 13 -2 0.58 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 238 (08/26) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 12 10.2 17 6.5 16 -1 0.63 -2.4 2.4 - Subregional Peak: 10.8 15 -2 1.05 (at cell 81 x  4157 Indio Jackson 2 7.1 19 4.0 19 0 0.57 -0.5 0.5 - 4137 Palm Springs 10 10.2 17 6.5 16 -1 0.63 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 239 (08/27) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 21 12.2 13 9.1 14 1 0.74 -2.3 2.7 - Subregional Peak: 10.6 14 1 0.87 (at cell 52 x  0069 Burbank 6 10.3 12 9.1 14 2 0.88 -0.1 0.2 - 0088 Pasadena 6 10.4 12 8.2 14 2 0.79 -0.2 0.3 - 0074 Reseda 4 12.2 13 7.4 13 0 0.61 -0.4 0.4 - 0090 Santa Clarita 5 9.3 11 4.9 11 0 0.52 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 239 (08/27) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 99 18.2 16 10.3 15 -1 0.56 -3.2 3.5 - Subregional Peak: 10.6 14 -2 0.58 (at cell 71 x  0060 Azusa 6 12.6 13 8.9 14 1 0.70 -0.2 0.3 - 4164 Banning Airport 10 13.5 18 8.8 14 -4 0.66 -0.2 0.3 - 5181 Crestline 14 18.2 16 5.2 13 -3 0.29 -0.5 0.5 - 4158 Elsinore 3 10.2 13 8.9 14 1 0.87 0.0 0.1 - 5197 Fontana 7 14.4 14 9.5 16 2 0.66 -0.3 0.3 - 0591 Glendora 7 13.4 13 9.5 14 1 0.71 -0.1 0.3 - 5212 Mira Loma 10 11.6 13 9.2 15 2 0.79 -0.3 0.3 - 0075 Pomona 7 12.5 13 9.9 15 2 0.79 -0.3 0.4 - 5204 Redlands 9 12.5 15 8.8 16 1 0.71 -0.3 0.3 - 4144 Rubidoux 9 11.0 13 9.5 16 3 0.87 -0.3 0.3 - 5203 San Bernardino 9 14.5 15 9.1 16 1 0.63 -0.4 0.4 - 5175 Upland 8 14.5 14 10.3 15 1 0.71 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 239 (08/27) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 30 9.5 13 7.9 12 -1 0.83 -1.6 1.7 - Subregional Peak: 10.1 14 1 1.06 (at cell 68 x  3176 Anaheim 4 8.4 14 6.8 13 -1 0.81 -0.3 0.3 - 0087 Los Angeles 4 8.8 13 5.8 13 0 0.66 -0.3 0.3 - 3195 Costa Mesa 5 6.9 13 6.2 13 0 0.89 -0.2 0.2 - 3177 La Habra 3 7.8 14 7.4 14 0 0.94 -0.1 0.1 - 0820 LAXH 1 6.1 12 5.3 12 0 0.88 -0.1 0.1 - 0072 Long Beach 4 7.7 14 5.6 13 -1 0.73 -0.2 0.2 - 0084 Lynwood 3 7.6 13 6.2 13 0 0.82 -0.2 0.2 - 3812 Mission Viejo 3 6.4 18 7.9 12 -6 1.23 -0.1 0.3 - 0091 West Los Angeles 3 9.5 13 6.1 12 -1 0.65 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 239 (08/27) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 29 11.4 21 6.5 15 -6 0.57 -3.1 3.1 - Subregional Peak: 9.2 15 -6 0.80 (at cell 84 x  4157 Indio Jackson 15 11.4 21 6.2 14 -7 0.55 -0.4 0.4 - 4137 Palm Springs 14 10.9 19 6.5 15 -4 0.60 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 240 (08/28) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 34 14.2 13 9.6 13 0 0.67 -4.1 4.1 - Subregional Peak: 11.9 14 1 0.84 (at cell 54 x  0069 Burbank 8 14.2 13 9.6 13 0 0.67 -0.3 0.3 - 0088 Pasadena 10 13.6 14 9.2 14 0 0.67 -0.4 0.4 - 0074 Reseda 10 13.8 13 7.1 12 -1 0.52 -0.5 0.5 - 0090 Santa Clarita 6 12.0 12 5.5 12 0 0.46 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 240 (08/28) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 129 15.6 15 10.8 14 -1 0.69 -2.8 3.1 - Subregional Peak: 11.5 14 -1 0.74 (at cell 75 x  0060 Azusa 9 13.8 14 9.2 14 0 0.67 -0.4 0.4 - 4164 Banning Airport 12 10.0 19 10.2 16 -3 1.02 0.0 0.3 - 5181 Crestline 10 13.3 17 5.3 15 -2 0.40 -0.5 0.5 - 4158 Elsinore 10 7.7 12 9.1 15 3 1.18 0.0 0.2 - 5197 Fontana 10 14.1 14 10.2 16 2 0.73 -0.3 0.3 - 0591 Glendora 9 15.6 15 9.8 15 0 0.63 -0.4 0.4 - 5212 Mira Loma 11 12.2 12 9.4 15 3 0.77 -0.3 0.3 - 4149 Perris 4 7.8 17 8.9 17 0 1.14 -0.2 0.2 - 0075 Pomona 9 12.4 12 10.5 15 3 0.85 -0.3 0.3 - 5204 Redlands 12 11.0 16 10.8 14 -2 0.98 -0.1 0.2 - 4144 Rubidoux 11 12.0 13 10.2 16 3 0.85 -0.3 0.3 - 5203 San Bernardino 12 13.3 15 9.9 13 -2 0.74 -0.3 0.3 - 5175 Upland 10 14.9 14 10.6 15 1 0.71 -0.5 0.5 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 240 (08/28) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 36 11.4 13 8.1 14 1 0.71 -2.0 2.1 - Subregional Peak: 9.7 15 2 0.85 (at cell 68 x  3176 Anaheim 6 7.6 15 6.6 13 -2 0.87 -0.2 0.2 - 0087 Los Angeles 7 11.4 13 5.7 13 0 0.50 -0.4 0.4 - 3195 Costa Mesa 2 6.9 13 6.3 13 0 0.91 -0.1 0.1 - 3177 La Habra 3 7.7 15 8.0 14 -1 1.04 -0.1 0.3 - 0820 LAXH 2 6.7 12 5.2 12 0 0.77 -0.2 0.2 - 0072 Long Beach 1 6.6 13 5.5 13 0 0.83 -0.2 0.2 - 0084 Lynwood 2 7.2 13 6.1 12 -1 0.84 -0.2 0.2 - 3812 Mission Viejo 8 8.8 12 8.1 14 2 0.92 -0.1 0.1 - 0091 West Los Angeles 5 10.9 14 6.1 12 -2 0.56 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 240 (08/28) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 19 9.1 10 6.6 12 2 0.73 -2.4 2.4 - Subregional Peak: 10.4 15 5 1.14 (at cell 81 x  4157 Indio Jackson 11 8.3 10 6.6 12 2 0.80 -0.3 0.3 - 4137 Palm Springs 8 9.1 10 5.9 14 4 0.65 -0.4 0.4 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 241 (08/29) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 30 15.2 13 7.1 14 1 0.47 -3.8 3.8 - Subregional Peak: 8.8 14 1 0.58 (at cell 52 x  0069 Burbank 6 8.5 14 6.1 13 -1 0.72 -0.3 0.3 - 0088 Pasadena 6 7.5 14 5.2 14 0 0.69 -0.4 0.4 - 0074 Reseda 9 11.6 13 6.8 13 0 0.59 -0.5 0.5 - 0090 Santa Clarita 9 15.2 13 7.1 14 1 0.47 -0.5 0.5 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 241 (08/29) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 89 10.8 16 10.4 14 -2 0.96 -2.2 2.8 - Subregional Peak: 11.3 15 -1 1.05 (at cell 76 x  0060 Azusa 5 8.2 14 5.7 15 1 0.69 -0.4 0.4 - 4164 Banning Airport 8 8.0 15 10.4 14 -1 1.30 0.0 0.4 - 5181 Crestline 12 10.8 16 8.4 13 -3 0.78 -0.3 0.3 - 4158 Elsinore 9 7.9 14 9.7 13 -1 1.23 0.1 0.2 - 5197 Fontana 6 10.6 14 5.0 13 -1 0.47 -0.4 0.4 - 0591 Glendora 6 9.5 14 6.1 15 1 0.65 -0.4 0.4 - 5212 Mira Loma 9 10.6 11 6.3 14 3 0.60 -0.4 0.4 - 4149 Perris 1 6.2 13 8.8 13 0 1.42 0.4 0.4 -2 0075 Pomona 5 9.7 13 5.8 15 2 0.60 -0.4 0.4 - 5204 Redlands 7 8.5 13 9.6 13 0 1.13 -0.1 0.3 - 4144 Rubidoux 8 9.8 12 6.5 15 3 0.66 -0.3 0.3 - 5203 San Bernardino 7 9.5 12 8.3 13 1 0.87 -0.2 0.2 - 5175 Upland 6 10.5 14 5.5 16 2 0.52 -0.4 0.4 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 241 (08/29) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 13 7.2 15 7.3 12 -3 1.01 -1.5 1.7 - Subregional Peak: 8.8 14 -1 1.22 (at cell 68 x  3176 Anaheim 2 6.7 16 5.1 14 -2 0.76 -0.3 0.3 - 0087 Los Angeles 3 6.7 16 3.9 15 -1 0.59 -0.5 0.5 - 3812 Mission Viejo 5 6.9 11 7.3 12 1 1.06 0.0 0.0 - 0091 West Los Angeles 3 7.2 15 5.2 14 -1 0.72 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 241 (08/29) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 14 8.6 16 7.7 13 -3 0.90 -0.9 1.4 - Subregional Peak: 11.2 11 -5 1.30 (at cell 113 x  4157 Indio Jackson 10 6.9 16 7.7 13 -3 1.12 -0.1 0.2 - 4137 Palm Springs 4 8.6 16 6.6 14 -2 0.76 -0.1 0.1 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubRegional Descriptions  SubRegion 003 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0069 Burbank 53 48 -27.848 461.308  0088 Pasadena 56 47 -11.205 457.021  0074 Reseda 49 48 -48.000 463.105  0090 Santa Clarita 49 52 -48.140 483.357  SubRegion 004 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0060 Azusa 60 47 6.981 456.113  4164 Banning Airport 79 42 104.459 433.527  5181 Crestline 72 49 66.383 468.606  4158 Elsinore 71 37 60.525 405.907  5197 Fontana 68 46 46.811 453.081  0591 Glendora 61 47 13.487 457.010  5212 Mira Loma 67 43 42.938 438.915  4149 Perris 72 39 69.051 417.376  0075 Pomona 63 45 22.598 448.610  5204 Redlands 74 45 76.256 448.189  4144 Rubidoux 69 44 52.093 442.557  5203 San Bernardino 72 46 65.874 453.299  5175 Upland 65 46 31.687 452.125  SubRegion 005 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  3176 Anaheim 60 40 7.422 421.645  0087 Los Angeles 54 45 -22.302 445.563  3195 Costa Mesa 60 37 6.793 405.626  3177 La Habra 59 42 4.359 432.978  0820 LAXH 51 42 -36.352 433.685  0072 Long Beach 55 40 -17.171 421.903  0084 Lynwood 55 42 -19.237 432.753  3812 Mission Viejo 64 36 29.671 400.791  0085 Pico Rivera 57 44 -5.273 442.860  0091 West Los Angeles 52 45 -34.796 447.031  SubRegion 009 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  4157 Indio Jackson 91 38 162.217 411.293  4137 Palm Springs 85 40 132.826 423.133 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 237 (08/25) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 1 6.1 10 6.3 9 -1 1.03 0.2 0.2  Subregional Peak: 7.3 10 0 1.18 (at 48 x 47) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 237 (08/25) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 2 6.3 13 6.2 9 -4 0.98 -0.2 0.2 - Subregional Peak: 7.2 10 -3 1.14 (at 72 x 32) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 237 (08/25) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 4 8.3 10 5.1 10 0 0.61 -2.4 2.4 - Subregional Peak: 6.8 9 -1 0.82 (at 68 x 36) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 238 (08/26) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 2 6.9 11 4.8 10 -1 0.70 -1.9 1.9 - Subregional Peak: 6.8 10 -1 0.99 (at 54 x 50) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 238 (08/26) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 12 8.0 11 8.8 10 -1 1.10 -1.4 1.6 - Subregional Peak: 10.1 10 -1 1.26 (at 78 x 38) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 238 (08/26) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 5 7.4 12 5.7 10 -2 0.77 -2.3 2.3 - Subregional Peak: 8.0 11 -1 1.08 (at 68 x 37) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 238 (08/26) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 1 8.0 12 5.8 10 -2 0.72 -2.3 2.3 - Subregional Peak: 8.8 10 -2 1.10 (at 81 x 43) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 239 (08/27) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 7.7 10 7.0 10 0 0.92 -1.2 1.2 - Subregional Peak: 7.8 10 0 1.01 (at 54 x 49) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 239 (08/27) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 12 13.0 11 8.2 11 0 0.63 -2.9 3.1 - Subregional Peak: 9.1 11 0 0.70 (at 70 x 35) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 239 (08/27) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 3 6.6 10 5.2 10 0 0.79 -1.6 1.6 - Subregional Peak: 8.6 11 1 1.30 (at 68 x 37) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 239 (08/27) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 9.4 15 5.9 10 -5 0.63 -3.5 3.5 - Subregional Peak: 7.7 10 -5 0.82 (at 82 x 44) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 240 (08/28) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 11.3 10 7.3 10 0 0.65 -3.7 3.7 - Subregional Peak: 8.3 10 0 0.74 (at 54 x 49) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 240 (08/28) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 12 12.1 11 9.2 11 0 0.76 -2.6 3.1 - Subregional Peak: 9.4 10 -1 0.77 (at 76 x 44) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 240 (08/28) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 4 8.5 10 6.6 10 0 0.78 -2.2 2.2 - Subregional Peak: 8.6 10 0 1.01 (at 68 x 36) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 240 (08/28) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 7.7 8 5.8 10 2 0.76 -1.7 1.7 - Subregional Peak: 8.4 11 3 1.10 (at 81 x 43) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 241 (08/29) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 10.9 10 6.1 10 0 0.56 -3.5 3.5 - Subregional Peak: 6.4 10 0 0.59 (at 49 x 51) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 241 (08/29) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 12 9.2 22 8.8 10 -12 0.95 -1.9 2.3 - Subregional Peak: 9.3 11 -11 1.01 (at 79 x 38) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 241 (08/29) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 1 6.2 10 6.2 9 -1 0.99 0.0 0.0 - Subregional Peak: 7.5 10 0 1.21 (at 68 x 37) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 241 (08/29) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 6.4 11 7.0 11 0 1.09 0.2 0.4  Subregional Peak: 9.0 11 0 1.41 (at 82 x 44) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0000 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 237  Unpaired Subregional Maximum of 9.5 at Cell 83 x 10 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 237 238 239 240 241 Avg. 237 238 239 240 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0001 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 237  Unpaired Subregional Maximum of -99.0 at Cell -9 x -9 -- Nearest Site: 08 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 237 238 239 240 241 Avg. 237 238 239 240 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0002 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 237  Unpaired Subregional Maximum of 6.4 at Cell 42 x 53 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 237 238 239 240 241 Avg. 237 238 239 240 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0003 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 237  Unpaired Subregional Maximum of 7.8 at Cell 54 x 48 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 237 238 239 240 241 Avg. 237 238 239 240 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 0069 Burbank 7.9 4.3 6.4 7.3 10.8 7.1 6.0 5.8 4.8 7.0 7.3 0088 Pasadena 7.7 5.6 6.9 7.3 10.2 6.5 5.2 4.8 4.6 6.2 6.5 0074 Reseda 9.7 4.7 5.3 7.7 11.3 10.1 6.2 7.0 5.8 6.1 6.3 0090 Santa Clarita 7.8 6.1 4.9 6.6 7.8 10.9 5.6 6.3 5.8 4.6 5.4  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0004 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 237  Unpaired Subregional Maximum of 9.2 at Cell 77 x 48 -- Nearest Site: 52 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 237 238 239 240 241 Avg. 237 238 239 240 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 0060 Azusa 7.8 4.8 6.5 7.7 10.6 6.4 5.2 4.8 4.6 6.1 6.4 4164 Banning Airport 7.7 6.3 7.6 10.6 7.0 7.0 8.0 6.0 8.8 7.8 8.6 5181 Crestline 10.2 5.3 7.4 13.0 11.0 9.2 5.7 5.9 5.8 5.0 4.9 4158 Elsinore 7.1 5.2 7.4 6.7 6.9 7.4 7.5 5.6 7.0 8.2 8.1 5197 Fontana 9.1 4.8 6.8 9.9 11.9 7.8 5.8 5.1 4.9 6.5 8.2 0591 Glendora 8.8 4.9 7.3 8.4 11.8 7.6 5.8 5.2 5.0 6.7 7.2 5212 Mira Loma 8.7 6.3 8.0 10.0 10.6 8.7 6.2 6.2 5.2 6.8 7.4 0075 Pomona 8.3 4.9 7.0 8.8 10.6 7.0 5.6 4.7 5.1 6.4 7.4 5204 Redlands 8.8 5.3 6.8 10.7 10.0 7.6 7.4 5.5 7.1 7.5 9.2 4144 Rubidoux 9.2 5.9 8.0 9.6 10.6 8.7 6.8 6.4 5.9 7.3 8.5 5203 San Bernardino 9.5 5.3 6.9 11.2 11.4 8.3 6.8 5.5 5.9 7.0 9.0 5175 Upland 9.0 4.8 7.0 9.3 12.1 7.7 5.7 5.0 5.0 6.5 7.7 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0005 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 237  Unpaired Subregional Maximum of 8.2 at Cell 69 x 37 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 237 238 239 240 241 Avg. 237 238 239 240 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 3176 Anaheim 6.6 5.9 6.9 6.5 6.3 5.8 4.1 3.4 3.4 4.9 4.6 0087 Los Angeles 7.1 5.8 6.2 6.6 8.5 5.4 4.0 3.5 3.6 4.7 4.6 3195 Costa Mesa 6.3 6.5 6.1 5.9 5.1 4.5 5.2 4.8 5.3 5.4 5.5 0820 LAXH 7.1 7.1 5.6 5.0 5.2 4.3 4.8 5.1 4.7 5.0 4.7 0072 Long Beach 6.0 6.0 5.2 5.4 4.7 4.3 4.1 3.7 3.9 4.5 4.5 3812 Mission Viejo 7.1 5.2 7.4 5.5 7.6 6.2 5.9 4.2 5.7 6.8 6.6 0091 West Los Angeles 7.3 8.3 7.1 6.5 7.5 5.4 4.8 4.7 4.3 5.2 5.2  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0006 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 237  Unpaired Subregional Maximum of 9.2 at Cell 82 x 11 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 237 238 239 240 241 Avg. 237 238 239 240 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0007 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 237  Unpaired Subregional Maximum of 6.0 at Cell 44 x 66 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 237 238 239 240 241 Avg. 237 238 239 240 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0008 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 237  Unpaired Subregional Maximum of -99.0 at Cell -9 x -9 -- Nearest Site: 08 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 237 238 239 240 241 Avg. 237 238 239 240 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0009 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 237  Unpaired Subregional Maximum of 8.4 at Cell 87 x 45 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 237 238 239 240 241 Avg. 237 238 239 240 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 4157 Indio Jackson 7.7 3.6 5.7 9.4 7.2 6.4 6.1 5.9 6.1 5.9 5.8 4137 Palm Springs 7.9 5.9 8.0 9.4 7.7 6.4 5.7 4.9 5.8 5.9 5.7 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubRegional Descriptions  SubRegion 003 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0069 Burbank 53 48 -27.848 461.308  0088 Pasadena 56 47 -11.205 457.021  0074 Reseda 49 48 -48.000 463.105  0090 Santa Clarita 49 52 -48.140 483.357  SubRegion 004 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0060 Azusa 60 47 6.981 456.113  4164 Banning Airport 79 42 104.459 433.527  5181 Crestline 72 49 66.383 468.606  4158 Elsinore 71 37 60.525 405.907  5197 Fontana 68 46 46.811 453.081  0591 Glendora 61 47 13.487 457.010  5212 Mira Loma 67 43 42.938 438.915  4149 Perris 72 39 69.051 417.376  0075 Pomona 63 45 22.598 448.610  5204 Redlands 74 45 76.256 448.189  4144 Rubidoux 69 44 52.093 442.557  5203 San Bernardino 72 46 65.874 453.299  5175 Upland 65 46 31.687 452.125  SubRegion 005 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  3176 Anaheim 60 40 7.422 421.645  0087 Los Angeles 54 45 -22.302 445.563  3195 Costa Mesa 60 37 6.793 405.626  3177 La Habra 59 42 4.359 432.978  0820 LAXH 51 42 -36.352 433.685  0072 Long Beach 55 40 -17.171 421.903  0084 Lynwood 55 42 -19.237 432.753  3812 Mission Viejo 64 36 29.671 400.791  0085 Pico Rivera 57 44 -5.273 442.860  0091 West Los Angeles 52 45 -34.796 447.031  SubRegion 009 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  4157 Indio Jackson 91 38 162.217 411.293  4137 Palm Springs 85 40 132.826 423.133 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 195 (07/14) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 15 8.6 14 9.3 14 0 1.09 -0.3 1.3 - Subregional Peak: 11.4 15 1 1.33 (at cell 51 x  0069 Burbank 1 6.1 15 6.0 15 0 0.98 0.0 0.0 - 0088 Pasadena 2 7.4 17 4.4 16 -1 0.60 -0.4 0.4 - 0074 Reseda 4 8.6 14 9.0 14 0 1.05 0.0 0.1 - 0090 Santa Clarita 8 8.6 13 9.3 14 1 1.09 0.0 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 195 (07/14) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 64 10.0 14 10.8 15 1 1.08 -0.6 1.5 - Subregional Peak: 11.6 15 1 1.16 (at cell 70 x  4164 Banning Airport 10 8.5 14 7.9 14 0 0.93 -0.2 0.2 - 5181 Crestline 6 10.0 14 8.3 15 1 0.83 -0.1 0.1 - 4158 Elsinore 8 9.0 12 10.8 15 3 1.20 0.1 0.2 - 5197 Fontana 4 7.7 14 6.1 14 0 0.79 -0.2 0.2 - 0591 Glendora 1 6.6 14 5.2 14 0 0.79 -0.2 0.2 - 5212 Mira Loma 6 8.4 14 7.1 13 -1 0.85 -0.1 0.2 - 4149 Perris 4 6.6 17 9.4 13 -4 1.42 0.3 0.3 - 0075 Pomona 2 7.0 14 4.5 13 -1 0.64 -0.4 0.4 - 5204 Redlands 6 8.7 13 9.3 15 2 1.07 0.0 0.3 - 4144 Rubidoux 8 8.4 13 8.7 13 0 1.04 -0.1 0.1 - 5203 San Bernardino 6 8.5 12 8.9 15 3 1.05 -0.1 0.2 - 5175 Upland 3 8.4 14 5.0 13 -1 0.59 -0.4 0.4 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 195 (07/14) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 2 7.7 16 4.4 16 0 0.57 -2.7 2.7 - Subregional Peak: 11.0 14 -2 1.43 (at cell 68 x  3176 Anaheim 1 6.2 16 4.4 16 0 0.71 -0.3 0.3 - 0087 Los Angeles 1 7.7 16 4.2 16 0 0.54 -0.5 0.5 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 195 (07/14) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 5 8.9 14 6.8 13 -1 0.76 -1.7 1.7 - Subregional Peak: 18.2 13 -1 2.04 (at cell 106 x  4137 Palm Springs 5 8.9 14 6.8 13 -1 0.76 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 196 (07/15) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 14 9.1 16 11.3 15 -1 1.24 0.8 1.1  Subregional Peak: 12.7 16 0 1.40 (at cell 51 x  0088 Pasadena 1 6.6 15 5.6 15 0 0.85 -0.1 0.1  0074 Reseda 6 8.2 15 9.0 14 -1 1.09 0.1 0.1  0090 Santa Clarita 7 9.1 16 11.3 15 -1 1.24 0.1 0.2  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 196 (07/15) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 88 15.8 14 13.9 14 0 0.88 0.3 1.8  Subregional Peak: 15.4 15 1 0.98 (at cell 77 x  4164 Banning Airport 12 11.6 16 13.0 16 0 1.12 -0.1 0.1  5181 Crestline 13 15.8 14 11.5 14 0 0.73 -0.3 0.3  4158 Elsinore 9 9.1 15 10.8 16 1 1.18 0.2 0.2  5197 Fontana 8 9.2 12 10.8 12 0 1.17 0.0 0.2  0591 Glendora 1 6.4 16 5.4 16 0 0.85 -0.2 0.2  5212 Mira Loma 7 8.1 16 9.7 11 -5 1.20 0.2 0.2  4149 Perris 5 8.4 16 11.4 15 -1 1.35 0.4 0.4  0075 Pomona 2 6.6 16 7.7 15 -1 1.17 0.1 0.1  5204 Redlands 8 11.3 13 13.9 14 1 1.23 0.2 0.2  4144 Rubidoux 8 8.3 16 11.8 12 -4 1.42 0.3 0.3  5203 San Bernardino 8 11.9 13 12.7 14 1 1.07 0.0 0.1  5175 Upland 7 7.5 13 8.5 11 -2 1.13 0.0 0.1 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 196 (07/15) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 6 6.8 18 5.3 15 -3 0.78 -2.1 2.1 - Subregional Peak: 11.5 14 -4 1.68 (at cell 68 x  0820 LAXH 6 6.8 18 5.3 15 -3 0.78 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 196 (07/15) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 25 11.2 16 9.7 16 0 0.86 -0.8 1.9 - Subregional Peak: 16.0 13 -3 1.43 (at cell 105 x  4157 Indio Jackson 12 8.9 19 9.7 16 -3 1.08 0.1 0.2 - 4137 Palm Springs 13 11.2 16 8.6 12 -4 0.77 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 197 (07/16) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 32 17.3 14 12.4 14 0 0.72 -0.7 1.8 - Subregional Peak: 14.7 15 1 0.85 (at cell 51 x  0069 Burbank 7 9.0 12 10.7 14 2 1.19 0.1 0.1 - 0088 Pasadena 6 8.7 13 10.5 15 2 1.21 0.1 0.2 - 0074 Reseda 9 10.7 15 10.1 15 0 0.94 0.0 0.1 - 0090 Santa Clarita 10 17.3 14 12.4 14 0 0.72 -0.2 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 197 (07/16) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 119 16.6 15 14.1 15 0 0.85 -0.6 1.9 - Subregional Peak: 15.6 14 -1 0.94 (at cell 76 x  0060 Azusa 5 9.9 14 9.1 16 2 0.92 0.0 0.2 - 4164 Banning Airport 15 13.4 17 14.1 15 -2 1.05 -0.1 0.1 - 5181 Crestline 14 16.6 15 10.7 15 0 0.65 -0.3 0.3 - 4158 Elsinore 11 10.4 17 13.8 15 -2 1.33 0.4 0.4 - 5197 Fontana 8 13.5 16 10.4 16 0 0.77 -0.2 0.2 - 0591 Glendora 6 11.2 14 8.9 16 2 0.79 -0.1 0.1 - 5212 Mira Loma 9 12.2 14 11.1 15 1 0.91 0.0 0.2 - 4149 Perris 10 12.6 14 13.2 15 1 1.05 0.2 0.2 - 0075 Pomona 7 10.8 14 9.9 15 1 0.91 0.0 0.1 - 5204 Redlands 9 14.6 15 13.2 15 0 0.91 0.0 0.1 - 4144 Rubidoux 8 13.0 14 11.6 15 1 0.89 0.0 0.2 - 5203 San Bernardino 9 15.6 15 12.4 14 -1 0.80 -0.2 0.2 - 5175 Upland 8 12.7 15 9.8 15 0 0.77 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 197 (07/16) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 4 6.6 14 7.9 13 -1 1.20 0.9 0.9  Subregional Peak: 13.3 15 1 2.01 (at cell 68 x  0087 Los Angeles 1 6.4 12 7.5 12 0 1.18 0.2 0.2  0091 West Los Angeles 3 6.6 14 7.9 13 -1 1.20 0.1 0.1  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 197 (07/16) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 27 13.9 18 8.8 14 -4 0.64 -3.0 3.2 - Subregional Peak: 17.8 14 -4 1.28 (at cell 107 x  4157 Indio Jackson 11 10.6 20 8.8 14 -6 0.83 -0.2 0.2 - 4137 Palm Springs 16 13.9 18 8.3 12 -6 0.60 -0.4 0.4 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 198 (07/17) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 33 16.5 14 12.2 13 -1 0.74 -1.9 2.5 - Subregional Peak: 15.7 14 0 0.95 (at cell 52 x  0069 Burbank 5 11.0 13 12.2 13 0 1.11 0.1 0.1 - 0088 Pasadena 6 11.0 13 11.2 14 1 1.02 0.0 0.1 - 0074 Reseda 9 12.9 12 11.1 13 1 0.86 -0.2 0.2 - 0090 Santa Clarita 13 16.5 14 11.6 13 -1 0.70 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 198 (07/17) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 137 16.3 15 15.0 15 0 0.92 0.0 1.5  Subregional Peak: 15.6 15 0 0.96 (at cell 72 x  0060 Azusa 7 12.3 13 12.1 14 1 0.98 0.1 0.2  4164 Banning Airport 17 14.2 13 13.2 15 2 0.93 -0.2 0.3  5181 Crestline 13 14.5 15 11.6 16 1 0.80 -0.2 0.2  4158 Elsinore 12 13.9 15 12.9 14 -1 0.93 0.0 0.1  5197 Fontana 10 14.5 15 13.1 14 -1 0.90 0.1 0.2  0591 Glendora 8 13.7 14 13.0 15 1 0.95 0.1 0.1  5212 Mira Loma 9 13.5 14 11.4 16 2 0.84 0.0 0.2  4149 Perris 14 10.1 16 12.1 14 -2 1.20 0.2 0.2  0075 Pomona 7 13.2 13 12.5 16 3 0.95 0.1 0.1  5204 Redlands 11 13.9 15 15.0 15 0 1.08 0.1 0.1  4144 Rubidoux 9 13.4 15 12.2 13 -2 0.91 0.1 0.2  5203 San Bernardino 11 16.3 15 14.5 14 -1 0.89 0.0 0.1  5175 Upland 9 13.9 15 13.8 14 -1 0.99 0.1 0.1 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 198 (07/17) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 19 8.9 13 9.9 15 2 1.12 1.1 1.4  Subregional Peak: 12.5 14 1 1.41 (at cell 68 x  3176 Anaheim 5 6.7 11 9.9 13 2 1.47 0.2 0.3  0087 Los Angeles 2 7.8 13 8.4 12 -1 1.07 0.0 0.0  3177 La Habra 4 8.2 12 9.9 15 3 1.21 0.2 0.2  0084 Lynwood 1 6.1 12 8.5 12 0 1.40 0.4 0.4  3812 Mission Viejo 7 8.9 13 9.7 12 -1 1.08 0.2 0.2  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 198 (07/17) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 42 10.9 10 7.9 17 7 0.73 -3.0 3.0 - Subregional Peak: 12.8 15 5 1.17 (at cell 81 x  4157 Indio Jackson 20 10.9 10 7.9 17 7 0.73 -0.3 0.3 - 4137 Palm Springs 22 10.7 9 6.1 17 8 0.57 -0.4 0.4 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 199 (07/18) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 32 17.1 14 8.9 13 -1 0.52 -3.4 3.4 - Subregional Peak: 11.9 13 -1 0.70 (at cell 59 x  0069 Burbank 5 7.6 16 6.6 13 -3 0.87 -0.1 0.1 - 0088 Pasadena 5 7.7 12 6.5 14 2 0.84 -0.2 0.2 - 0074 Reseda 12 11.5 14 8.1 13 -1 0.71 -0.5 0.5 - 0090 Santa Clarita 10 17.1 14 8.9 13 -1 0.52 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 199 (07/18) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 118 14.4 16 14.0 15 -1 0.97 -0.8 1.6 - Subregional Peak: 15.2 15 -1 1.06 (at cell 76 x  0060 Azusa 5 7.5 13 7.0 14 1 0.93 0.0 0.1 - 4164 Banning Airport 18 14.4 16 13.2 16 0 0.91 -0.2 0.2 - 5181 Crestline 10 12.3 13 12.8 15 2 1.04 0.1 0.1 - 4158 Elsinore 11 12.9 15 12.6 14 -1 0.97 -0.1 0.1 - 5197 Fontana 7 11.9 15 10.0 13 -2 0.84 -0.1 0.2 - 0591 Glendora 6 8.4 13 7.8 14 1 0.93 0.0 0.1 - 5212 Mira Loma 9 11.3 15 9.6 13 -2 0.85 -0.2 0.3 - 4149 Perris 12 10.4 15 11.6 14 -1 1.11 0.0 0.2 - 0075 Pomona 5 9.1 14 8.4 14 0 0.93 -0.1 0.1 - 5204 Redlands 10 12.7 14 14.0 15 1 1.10 -0.1 0.2 - 4144 Rubidoux 9 11.9 15 11.9 13 -2 1.00 -0.1 0.3 - 5203 San Bernardino 10 11.9 16 13.4 14 -2 1.12 -0.1 0.2 - 5175 Upland 6 11.3 14 9.0 13 -1 0.80 -0.1 0.1 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 199 (07/18) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 35 11.7 16 9.4 13 -3 0.80 -2.2 2.8 - Subregional Peak: 15.5 13 -3 1.32 (at cell 105 x  4157 Indio Jackson 17 8.6 9 9.4 13 4 1.09 -0.1 0.3 - 4137 Palm Springs 18 11.7 16 7.3 12 -4 0.62 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 200 (07/19) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 23 12.4 14 11.3 14 0 0.91 -1.1 1.4 - Subregional Peak: 13.4 15 1 1.08 (at cell 52 x  0069 Burbank 2 6.4 15 7.3 14 -1 1.14 0.1 0.1 - 0088 Pasadena 3 7.6 15 6.7 15 0 0.89 -0.1 0.1 - 0074 Reseda 7 10.1 16 8.4 13 -3 0.84 -0.1 0.2 - 0090 Santa Clarita 11 12.4 14 11.3 14 0 0.91 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 200 (07/19) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 71 13.3 15 15.8 14 -1 1.18 1.2 1.9  Subregional Peak: 17.3 15 0 1.30 (at cell 75 x  0060 Azusa 3 6.9 14 6.5 16 2 0.95 -0.1 0.1  4164 Banning Airport 9 7.4 11 10.7 12 1 1.45 0.3 0.4  5181 Crestline 14 13.3 15 13.9 16 1 1.05 0.0 0.1  4158 Elsinore 3 6.8 9 9.0 10 1 1.32 0.3 0.3  5197 Fontana 5 9.4 15 8.7 15 0 0.93 -0.1 0.1  0591 Glendora 5 8.4 15 8.2 17 2 0.98 -0.1 0.2  5212 Mira Loma 5 9.5 14 11.1 14 0 1.17 0.1 0.2  0075 Pomona 5 8.3 15 9.3 15 0 1.12 0.1 0.2  5204 Redlands 8 11.4 15 15.8 14 -1 1.38 0.4 0.4  4144 Rubidoux 5 9.8 14 13.0 15 1 1.33 0.3 0.3  5203 San Bernardino 6 11.3 15 13.2 15 0 1.16 0.4 0.4  5175 Upland 3 9.0 15 8.1 15 0 0.90 -0.2 0.2  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 200 (07/19) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 2 6.4 16 8.3 17 1 1.30 1.7 1.7  Subregional Peak: 11.6 14 -2 1.81 (at cell 81 x  4137 Palm Springs 2 6.4 16 8.3 17 1 1.30 0.3 0.3 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubRegional Descriptions  SubRegion 003 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0069 Burbank 53 48 -27.848 461.308  0088 Pasadena 56 47 -11.205 457.021  0074 Reseda 49 48 -48.000 463.105  0090 Santa Clarita 49 52 -48.140 483.357  SubRegion 004 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0060 Azusa 60 47 6.981 456.113  4164 Banning Airport 79 42 104.459 433.527  5181 Crestline 72 49 66.383 468.606  4158 Elsinore 71 37 60.525 405.907  5197 Fontana 68 46 46.811 453.081  0591 Glendora 61 47 13.487 457.010  5212 Mira Loma 67 43 42.938 438.915  4149 Perris 72 39 69.051 417.376  0075 Pomona 63 45 22.598 448.610  5204 Redlands 74 45 76.256 448.189  4144 Rubidoux 69 44 52.093 442.557  5203 San Bernardino 72 46 65.874 453.299  5175 Upland 65 46 31.687 452.125  SubRegion 005 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  3176 Anaheim 60 40 7.422 421.645  0087 Los Angeles 54 45 -22.302 445.563  3195 Costa Mesa 60 37 6.793 405.626  3177 La Habra 59 42 4.359 432.978  0820 LAXH 51 42 -36.352 433.685  0072 Long Beach 55 40 -17.171 421.903  0084 Lynwood 55 42 -19.237 432.753  3812 Mission Viejo 64 36 29.671 400.791  0085 Pico Rivera 57 44 -5.273 442.860  0091 West Los Angeles 52 45 -34.796 447.031  SubRegion 009 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  4157 Indio Jackson 91 38 162.217 411.293  4137 Palm Springs 85 40 132.826 423.133 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 195 (07/14) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 2 7.0 10 7.0 10 0 1.00 0.4 0.4  Subregional Peak: 8.0 11 1 1.15 (at 54 x 53) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 195 (07/14) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 7 7.7 10 8.5 10 0 1.10 -0.5 0.7 - Subregional Peak: 9.1 10 0 1.18 (at 71 x 35) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 195 (07/14) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 1 6.9 10 6.0 10 0 0.87 -0.9 0.9 - Subregional Peak: 10.8 9 -1 1.57 (at 104 x 13) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 196 (07/15) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 2 7.9 11 9.1 11 0 1.15 0.8 0.8  Subregional Peak: 10.7 11 0 1.35 (at 51 x 55) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 196 (07/15) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 10 14.3 12 11.3 11 -1 0.79 0.7 1.7  Subregional Peak: 12.8 11 -1 0.90 (at 77 x 45) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 196 (07/15) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 1 6.3 14 5.2 11 -3 0.83 -1.1 1.1 - Subregional Peak: 10.1 10 -4 1.61 (at 68 x 37) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 196 (07/15) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 9.4 10 8.7 10 0 0.93 -0.3 1.7 - Subregional Peak: 11.8 10 0 1.25 (at 105 x 13) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 197 (07/16) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 14.1 11 10.5 11 0 0.75 -0.5 1.3  Subregional Peak: 12.4 12 1 0.88 (at 52 x 55) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 197 (07/16) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 13.8 12 12.2 11 -1 0.88 -0.4 1.4 - Subregional Peak: 13.4 11 -1 0.97 (at 75 x 41) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 197 (07/16) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 11.6 13 8.3 10 -3 0.72 -2.6 2.6 - Subregional Peak: 11.9 11 -2 1.02 (at 81 x 43) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 198 (07/17) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 14.2 10 9.4 9 -1 0.66 -1.3 2.0 - Subregional Peak: 12.4 11 1 0.87 (at 53 x 53) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 198 (07/17) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 13.2 11 13.1 11 0 0.99 0.2 0.9  Subregional Peak: 13.6 11 0 1.03 (at 76 x 45) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 198 (07/17) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 3 7.1 10 8.4 10 0 1.18 1.4 1.4  Subregional Peak: 10.6 10 0 1.49 (at 68 x 37) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 198 (07/17) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 9.4 7 7.5 11 4 0.79 -2.5 2.5 - Subregional Peak: 11.3 11 4 1.20 (at 81 x 43) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 199 (07/18) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 12.7 11 7.4 10 -1 0.58 -2.7 2.7 - Subregional Peak: 10.4 11 0 0.82 (at 59 x 50) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 199 (07/18) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 12.0 11 11.7 11 0 0.97 -0.4 0.7 - Subregional Peak: 13.2 12 1 1.10 (at 76 x 48) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 199 (07/18) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 10.6 10 8.4 11 1 0.79 -1.4 2.3 - Subregional Peak: 12.5 10 0 1.17 (at 105 x 13) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 200 (07/19) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 2 10.6 10 9.0 12 2 0.85 -1.2 1.2 - Subregional Peak: 10.3 12 2 0.97 (at 52 x 56) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 200 (07/19) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 11 11.0 12 12.6 11 -1 1.14 1.6 1.6  Subregional Peak: 13.2 11 -1 1.20 (at 74 x 47) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0000 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 195  Unpaired Subregional Maximum of 9.6 at Cell 87 x 6 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 195 196 197 198 199 Avg. 195 196 197 198 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0001 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 195  Unpaired Subregional Maximum of 6.3 at Cell 32 x 69 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 195 196 197 198 199 Avg. 195 196 197 198 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0002 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 195  Unpaired Subregional Maximum of 8.9 at Cell 49 x 53 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 195 196 197 198 199 Avg. 195 196 197 198 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0003 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 195  Unpaired Subregional Maximum of 9.9 at Cell 52 x 55 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 195 196 197 198 199 Avg. 195 196 197 198 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 0069 Burbank 7.2 4.4 4.5 7.6 7.5 6.4 6.7 5.2 6.0 8.3 8.8 0088 Pasadena 7.1 5.3 4.5 7.1 8.1 6.2 5.9 4.0 4.6 8.0 8.4 0074 Reseda 8.5 6.1 6.8 8.9 10.9 9.9 7.8 6.9 7.2 9.2 9.4 0090 Santa Clarita 11.1 7.0 7.9 14.1 14.2 12.7 8.7 7.0 9.1 10.5 9.1  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0004 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 195  Unpaired Subregional Maximum of 11.5 at Cell 76 x 46 -- Nearest Site: 52 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 195 196 197 198 199 Avg. 195 196 197 198 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 0060 Azusa 7.2 4.9 4.6 7.0 8.6 6.0 6.3 4.1 4.8 7.6 9.8 4164 Banning Airport 10.2 7.2 10.3 12.0 13.2 12.0 10.4 7.1 10.2 12.1 11.7 5181 Crestline 11.5 7.3 14.3 13.8 12.5 10.2 9.6 6.6 9.3 8.9 10.0 4158 Elsinore 8.9 7.7 7.7 8.4 11.9 11.7 10.1 8.5 9.6 12.2 11.5 5197 Fontana 9.2 5.8 8.0 10.8 11.4 8.7 8.2 4.8 8.5 8.8 11.6 0591 Glendora 7.8 4.7 4.8 7.8 9.8 6.9 7.0 4.4 5.5 8.1 10.9 5212 Mira Loma 8.5 7.1 7.0 9.6 10.6 9.5 8.3 6.1 8.5 9.3 10.3 4149 Perris 9.0 6.0 6.8 10.4 9.6 9.3 10.1 8.1 9.9 12.0 11.4 0075 Pomona 7.9 5.2 5.5 8.2 9.9 6.9 7.2 3.9 6.8 7.8 10.9 5204 Redlands 10.2 6.8 9.4 12.0 12.3 11.9 11.0 6.3 11.3 11.3 13.1 4144 Rubidoux 8.9 7.5 7.6 10.0 10.8 10.2 9.6 6.7 9.7 10.2 11.4 5203 San Bernardino 10.1 7.0 9.9 12.4 12.9 10.5 10.3 6.0 10.5 10.5 12.6 5175 Upland 8.4 5.8 6.8 9.6 11.2 8.1 7.5 4.2 7.4 7.9 11.6 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulatioSubregion 0005 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 195 th Unpaired Subregional Maximum of 10.5 at Cell 69 x 37 -- Nearest Site: 4158  - - - - - Observed - - - - - - - - - - Simulated - - - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY D ID Description Avg. 195 196 197 198 199 Avg. 195 196 197 198 1---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- -3176 Anaheim 6.1 4.8 4.5 5.0 6.1 4.9 5.6 4.2 5.4 6.6 7.3 43177 La Habra 6.2 3.8 3.3 4.6 6.2 4.0 5.7 3.2 5.6 7.0 7.8 40820 LAXH 6.3 3.9 6.3 5.3 5.0 4.4 5.0 4.2 5.2 6.1 5.6 43812 Mission Viejo 7.1 3.8 4.5 4.6 7.1 4.9 7.0 5.9 6.3 7.2 8.4 6 * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulatioSubregion 0006 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 195 th Unpaired Subregional Maximum of 10.3 at Cell 70 x 36 -- Nearest Site: 4158  - - - - - Observed - - - - - - - - - - Simulated - - - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY D ID Description Avg. 195 196 197 198 199 Avg. 195 196 197 198 1---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulatioSubregion 0007 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 195 th Unpaired Subregional Maximum of 6.7 at Cell 41 x 68 -- Nearest Site: 0090  - - - - - Observed - - - - - - - - - - Simulated - - - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY D ID Description Avg. 195 196 197 198 199 Avg. 195 196 197 198 1---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulatioSubregion 0008 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 195 th Unpaired Subregional Maximum of 8.6 at Cell 73 x 58 -- Nearest Site: 5181  - - - - - Observed - - - - - - - - - - Simulated - - - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY D ID Description Avg. 195 196 197 198 199 Avg. 195 196 197 198 1---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulatioSubregion 0009 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 195 th Unpaired Subregional Maximum of 10.6 at Cell 105 x 13 -- Nearest Site: 4157  - - - - - Observed - - - - - - - - - - Simulated - - - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY D ID Description Avg. 195 196 197 198 199 Avg. 195 196 197 198 1---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- -4157 Indio Jackson 8.3 5.2 7.4 9.5 8.9 7.5 7.9 6.6 8.7 8.3 7.5 84137 Palm Springs 9.6 6.9 9.4 11.6 9.4 10.6 7.0 6.0 7.4 7.6 5.9 6
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubRegional Descriptions  SubRegion 003 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0069 Burbank 53 48 -27.848 461.308  0088 Pasadena 56 47 -11.205 457.021  0074 Reseda 49 48 -48.000 463.105  0090 Santa Clarita 49 52 -48.140 483.357  SubRegion 004 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0060 Azusa 60 47 6.981 456.113  4164 Banning Airport 79 42 104.459 433.527  5181 Crestline 72 49 66.383 468.606  4158 Elsinore 71 37 60.525 405.907  5197 Fontana 68 46 46.811 453.081  0591 Glendora 61 47 13.487 457.010  5212 Mira Loma 67 43 42.938 438.915  4149 Perris 72 39 69.051 417.376  0075 Pomona 63 45 22.598 448.610  5204 Redlands 74 45 76.256 448.189  4144 Rubidoux 69 44 52.093 442.557  5203 San Bernardino 72 46 65.874 453.299  5175 Upland 65 46 31.687 452.125  SubRegion 005 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  3176 Anaheim 60 40 7.422 421.645  0087 Los Angeles 54 45 -22.302 445.563  3195 Costa Mesa 60 37 6.793 405.626  3177 La Habra 59 42 4.359 432.978  0820 LAXH 51 42 -36.352 433.685  0072 Long Beach 55 40 -17.171 421.903  0084 Lynwood 55 42 -19.237 432.753  3812 Mission Viejo 64 36 29.671 400.791  0085 Pico Rivera 57 44 -5.273 442.860  0091 West Los Angeles 52 45 -34.796 447.031  SubRegion 009 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  4157 Indio Jackson 91 38 162.217 411.293  4137 Palm Springs 85 40 132.826 423.133 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 137 (05/17) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 2 6.2 15 5.0 15 0 0.81 -1.3 1.3 - Subregional Peak: 6.8 14 -1 1.10 (at cell 53 x  0090 Santa Clarita 2 6.2 15 5.0 15 0 0.81 -0.2 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 137 (05/17) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 10 7.3 16 6.9 14 -2 0.95 -1.3 1.4 - Subregional Peak: 7.7 15 -1 1.06 (at cell 79 x  4164 Banning Airport 4 7.3 16 6.9 14 -2 0.95 -0.1 0.2 - 5212 Mira Loma 2 6.5 15 4.8 15 0 0.74 -0.3 0.3 - 4144 Rubidoux 4 7.0 15 5.4 13 -2 0.77 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 137 (05/17) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 12 7.2 16 6.4 15 -1 0.88 -0.9 0.9 - Subregional Peak: 7.0 15 -1 0.97 (at cell 82 x  4157 Indio Jackson 7 6.8 17 6.1 16 -1 0.90 -0.1 0.1 - 4137 Palm Springs 5 7.2 16 6.4 15 -1 0.88 -0.1 0.1 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 138 (05/18) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 15 7.6 14 5.6 12 -2 0.74 -1.9 1.9 - Subregional Peak: 6.6 14 0 0.87 (at cell 54 x  0069 Burbank 1 6.3 15 4.7 15 0 0.75 -0.3 0.3 - 0074 Reseda 7 7.0 14 4.9 14 0 0.70 -0.3 0.3 - 0090 Santa Clarita 7 7.6 14 5.6 12 -2 0.74 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 138 (05/18) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 78 9.3 16 7.8 14 -2 0.84 -2.0 2.1 - Subregional Peak: 9.2 15 -1 0.99 (at cell 79 x  4164 Banning Airport 11 8.8 16 7.8 14 -2 0.89 -0.2 0.2 - 5181 Crestline 6 9.3 16 6.1 14 -2 0.66 -0.3 0.3 - 4158 Elsinore 9 8.1 15 6.1 12 -3 0.75 -0.2 0.2 - 5197 Fontana 7 8.2 14 5.1 13 -1 0.62 -0.3 0.3 - 0591 Glendora 5 6.5 15 5.0 15 0 0.76 -0.3 0.3 - 5212 Mira Loma 8 8.0 14 5.0 12 -2 0.63 -0.4 0.4 - 4149 Perris 4 6.7 15 6.2 14 -1 0.93 -0.2 0.2 - 0075 Pomona 3 6.7 13 5.0 15 2 0.75 -0.3 0.3 - 5204 Redlands 5 8.1 16 7.0 14 -2 0.86 -0.2 0.2 - 4144 Rubidoux 9 8.9 14 5.7 13 -1 0.64 -0.4 0.4 - 5203 San Bernardino 7 8.4 15 6.2 13 -2 0.74 -0.3 0.3 - 5175 Upland 4 7.1 14 4.5 13 -1 0.64 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 138 (05/18) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 8 6.6 14 5.0 16 2 0.76 -1.8 1.8 - Subregional Peak: 6.4 13 -1 0.97 (at cell 66 x  3176 Anaheim 4 6.5 13 4.7 14 1 0.72 -0.3 0.3 - 3812 Mission Viejo 1 6.2 16 5.0 16 0 0.81 -0.2 0.2 - 0091 West Los Angeles 3 6.6 14 4.8 14 0 0.73 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 138 (05/18) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 22 8.9 13 8.5 15 2 0.96 -0.4 0.7 - Subregional Peak: 10.8 13 0 1.22 (at cell 107 x  4157 Indio Jackson 10 8.9 13 8.5 15 2 0.96 -0.1 0.1 - 4137 Palm Springs 12 7.6 12 7.4 15 3 0.98 0.0 0.1 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 139 (05/19) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 14 9.6 15 6.0 12 -3 0.62 -2.7 2.7 - Subregional Peak: 7.5 14 -1 0.78 (at cell 55 x  0069 Burbank 4 9.6 15 5.5 13 -2 0.58 -0.4 0.4 - 0088 Pasadena 4 8.6 15 5.4 14 -1 0.63 -0.4 0.4 - 0074 Reseda 3 9.6 12 5.3 13 1 0.55 -0.3 0.3 - 0090 Santa Clarita 3 7.6 12 6.0 12 0 0.79 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 139 (05/19) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 100 10.7 16 8.6 14 -2 0.80 -3.3 3.3 - Subregional Peak: 8.9 15 -1 0.84 (at cell 79 x  0060 Azusa 5 8.2 15 5.2 14 -1 0.63 -0.4 0.4 - 4164 Banning Airport 10 9.5 17 8.6 14 -3 0.90 -0.2 0.2 - 5181 Crestline 6 10.7 16 6.2 14 -2 0.58 -0.3 0.3 - 4158 Elsinore 9 9.6 18 6.2 11 -7 0.65 -0.3 0.3 - 5197 Fontana 8 10.2 14 5.3 16 2 0.52 -0.5 0.5 - 0591 Glendora 7 8.9 16 5.4 15 -1 0.61 -0.4 0.4 - 5212 Mira Loma 10 9.3 11 5.4 15 4 0.58 -0.4 0.4 - 4149 Perris 4 10.7 17 5.6 16 -1 0.53 -0.5 0.5 - 0075 Pomona 6 9.3 16 5.7 15 -1 0.61 -0.4 0.4 - 5204 Redlands 9 8.5 16 7.3 13 -3 0.86 -0.3 0.3 - 4144 Rubidoux 9 10.3 14 6.0 11 -3 0.58 -0.4 0.4 - 5203 San Bernardino 10 10.1 15 6.2 13 -2 0.62 -0.4 0.4 - 5175 Upland 7 8.8 16 5.2 15 -1 0.59 -0.5 0.5 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 139 (05/19) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 20 8.4 13 5.8 14 1 0.68 -2.8 2.8 - Subregional Peak: 6.1 13 0 0.73 (at cell 66 x  3176 Anaheim 3 7.4 15 4.0 14 -1 0.54 -0.5 0.5 - 0087 Los Angeles 3 7.9 14 4.5 13 -1 0.56 -0.5 0.5 - 3177 La Habra 1 7.1 15 4.3 15 0 0.60 -0.4 0.4 - 0820 LAXH 1 6.5 13 4.7 13 0 0.72 -0.3 0.3 - 0072 Long Beach 2 6.4 14 4.2 13 -1 0.66 -0.4 0.4 - 0084 Lynwood 2 6.3 13 4.5 13 0 0.71 -0.3 0.3 - 3812 Mission Viejo 5 8.3 14 5.8 14 0 0.69 -0.3 0.3 - 0091 West Los Angeles 3 8.4 13 5.2 13 0 0.62 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 139 (05/19) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 23 9.4 17 9.3 14 -3 0.99 -0.7 1.4 - Subregional Peak: 13.2 12 -5 1.40 (at cell 109 x  4157 Indio Jackson 9 9.2 11 9.3 14 3 1.01 0.1 0.2 - 4137 Palm Springs 14 9.4 17 7.8 12 -5 0.83 -0.2 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 140 (05/20) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 8 8.5 13 5.7 12 -1 0.67 -2.0 2.0 - Subregional Peak: 7.8 14 1 0.91 (at cell 55 x  0069 Burbank 3 8.1 14 5.6 13 -1 0.69 -0.3 0.3 - 0088 Pasadena 3 7.3 14 5.1 14 0 0.71 -0.3 0.3 - 0074 Reseda 2 8.5 13 5.7 12 -1 0.67 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 140 (05/20) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 95 10.4 13 8.0 14 1 0.77 -2.3 2.4 - Subregional Peak: 9.1 15 2 0.87 (at cell 78 x  0060 Azusa 3 7.0 14 4.7 14 0 0.68 -0.3 0.3 - 4164 Banning Airport 12 8.9 12 8.0 14 2 0.90 -0.1 0.2 - 5181 Crestline 11 10.4 13 6.6 13 0 0.64 -0.4 0.4 - 4158 Elsinore 6 7.8 10 6.4 12 2 0.81 -0.2 0.2 - 5197 Fontana 8 8.1 14 5.5 15 1 0.68 -0.4 0.4 - 0591 Glendora 4 8.6 15 5.0 15 0 0.58 -0.4 0.4 - 5212 Mira Loma 9 8.1 13 5.0 15 2 0.61 -0.4 0.4 - 0075 Pomona 6 6.9 16 5.3 14 -2 0.77 -0.3 0.3 - 5204 Redlands 10 8.2 15 7.6 13 -2 0.93 -0.2 0.2 - 4144 Rubidoux 10 10.1 10 5.9 11 1 0.59 -0.4 0.4 - 5203 San Bernardino 10 9.3 15 6.8 12 -3 0.73 -0.3 0.3 - 5175 Upland 6 7.9 16 5.2 15 -1 0.65 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 140 (05/20) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 5 7.4 16 5.5 15 -1 0.74 -1.8 1.8 - Subregional Peak: 6.5 13 -3 0.88 (at cell 66 x  0087 Los Angeles 1 6.5 13 4.3 13 0 0.67 -0.3 0.3 - 3812 Mission Viejo 2 7.4 16 5.5 15 -1 0.74 -0.3 0.3 - 0091 West Los Angeles 2 7.0 13 5.4 14 1 0.77 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 140 (05/20) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 16 9.2 11 7.4 12 1 0.81 -1.8 1.8 - Subregional Peak: 11.1 12 1 1.21 (at cell 110 x  4157 Indio Jackson 9 9.2 11 7.4 12 1 0.81 -0.2 0.2 - 4137 Palm Springs 7 8.8 12 6.6 12 0 0.75 -0.2 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 141 (05/21) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 31 11.0 14 7.4 13 -1 0.67 -2.6 2.6 - Subregional Peak: 10.7 15 1 0.97 (at cell 55 x  0069 Burbank 7 8.1 16 7.4 13 -3 0.91 -0.3 0.3 - 0088 Pasadena 8 8.9 14 6.8 14 0 0.77 -0.4 0.4 - 0074 Reseda 8 8.3 12 7.2 13 1 0.87 -0.2 0.2 - 0090 Santa Clarita 8 11.0 14 6.4 13 -1 0.58 -0.4 0.4 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 141 (05/21) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 93 12.7 16 10.1 14 -2 0.80 -1.4 1.8 - Subregional Peak: 11.4 15 -1 0.90 (at cell 72 x  0060 Azusa 7 9.0 14 6.7 15 1 0.75 -0.3 0.3 - 4164 Banning Airport 7 8.3 16 9.2 15 -1 1.10 0.0 0.1 - 5181 Crestline 12 12.7 16 8.0 15 -1 0.63 -0.3 0.3 - 4158 Elsinore 8 8.2 14 10.1 14 0 1.23 0.2 0.2 - 5197 Fontana 7 11.1 15 7.3 14 -1 0.66 -0.2 0.2 - 0591 Glendora 5 9.7 14 7.0 15 1 0.72 -0.2 0.2 - 5212 Mira Loma 9 9.9 13 7.2 13 0 0.73 -0.2 0.2 - 4149 Perris 5 9.1 15 9.0 14 -1 0.99 0.0 0.1 - 0075 Pomona 4 9.2 13 7.0 15 2 0.77 -0.2 0.2 - 5204 Redlands 7 10.4 16 8.9 14 -2 0.85 0.0 0.1 - 4144 Rubidoux 10 11.1 14 8.1 14 0 0.73 -0.2 0.2 - 5203 San Bernardino 6 12.3 15 8.3 15 0 0.67 -0.2 0.2 - 5175 Upland 6 10.3 14 7.0 15 1 0.68 -0.2 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 141 (05/21) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 30 10.0 15 8.7 14 -1 0.87 -2.4 2.6 - Subregional Peak: 9.4 15 0 0.94 (at cell 67 x  3176 Anaheim 2 6.3 14 5.7 14 0 0.91 -0.3 0.3 - 0087 Los Angeles 7 8.4 16 5.3 13 -3 0.63 -0.5 0.5 - 3195 Costa Mesa 4 6.9 14 6.4 14 0 0.92 -0.3 0.3 - 0072 Long Beach 3 6.4 16 4.4 16 0 0.69 -0.5 0.5 - 0084 Lynwood 3 7.0 15 5.1 14 -1 0.73 -0.3 0.3 - 3812 Mission Viejo 5 7.4 13 8.7 14 1 1.17 0.1 0.1 - 0091 West Los Angeles 6 10.0 15 5.5 12 -3 0.55 -0.5 0.5 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 141 (05/21) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 22 9.6 18 7.1 17 -1 0.74 -1.1 1.3 - Subregional Peak: 9.7 12 -6 1.01 (at cell 110 x  4157 Indio Jackson 11 7.9 20 7.1 13 -7 0.90 -0.1 0.2 - 4137 Palm Springs 11 9.6 18 7.1 17 -1 0.74 -0.2 0.2 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 142 (05/22) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 39 16.4 14 8.9 13 -1 0.54 -4.5 4.5 - Subregional Peak: 11.2 15 1 0.68 (at cell 55 x  0069 Burbank 9 13.7 13 8.9 13 0 0.65 -0.4 0.4 - 0088 Pasadena 10 14.5 13 8.1 14 1 0.56 -0.5 0.5 - 0074 Reseda 11 11.2 12 7.5 12 0 0.67 -0.5 0.5 - 0090 Santa Clarita 9 16.4 14 6.1 14 0 0.37 -0.4 0.4 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 142 (05/22) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 151 16.0 15 14.7 15 0 0.92 -2.6 2.9 - Subregional Peak: 15.0 15 0 0.94 (at cell 74 x  0060 Azusa 9 14.5 14 8.0 15 1 0.55 -0.5 0.5 - 4164 Banning Airport 16 12.1 15 11.7 17 2 0.96 -0.1 0.2 - 5181 Crestline 13 15.7 15 13.6 15 0 0.87 -0.2 0.2 - 4158 Elsinore 10 10.1 14 12.4 14 0 1.23 0.1 0.1 - 5197 Fontana 12 15.0 15 12.3 13 -2 0.82 -0.4 0.4 - 0591 Glendora 10 16.0 15 8.4 15 0 0.53 -0.4 0.4 - 5212 Mira Loma 12 13.2 13 11.7 13 0 0.89 -0.3 0.3 - 4149 Perris 11 9.7 15 10.7 15 0 1.11 0.0 0.2 - 0075 Pomona 10 14.0 14 9.2 12 -2 0.66 -0.4 0.4 - 5204 Redlands 14 13.0 15 14.7 15 0 1.13 -0.2 0.3 - 4144 Rubidoux 12 14.4 13 13.2 14 1 0.92 -0.3 0.3 - 5203 San Bernardino 13 14.9 15 14.2 14 -1 0.96 -0.3 0.3 - 5175 Upland 9 13.5 14 9.9 13 -1 0.74 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 142 (05/22) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 55 12.5 14 10.0 14 0 0.80 -2.8 2.9 - Subregional Peak: 11.9 12 -2 0.96 (at cell 68 x  3176 Anaheim 9 8.0 13 6.1 14 1 0.77 -0.4 0.4 - 0087 Los Angeles 8 12.1 13 6.2 13 0 0.52 -0.5 0.5 - 3195 Costa Mesa 7 6.9 17 6.8 12 -5 0.99 -0.2 0.2 - 3177 La Habra 8 8.0 12 7.0 11 -1 0.87 -0.2 0.2 - 0084 Lynwood 6 11.1 13 5.9 13 0 0.53 -0.4 0.4 - 3812 Mission Viejo 9 12.5 14 10.0 14 0 0.80 -0.2 0.2 - 0091 West Los Angeles 8 11.4 12 6.8 13 1 0.59 -0.4 0.4 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 142 (05/22) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 34 12.7 18 8.7 13 -5 0.69 -2.6 3.0 - Subregional Peak: 11.0 16 -2 0.87 (at cell 92 x  4157 Indio Jackson 14 10.2 20 8.7 13 -7 0.86 -0.2 0.3 - 4137 Palm Springs 20 12.7 18 7.7 15 -3 0.60 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 143 (05/23) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 28 11.4 15 8.3 13 -2 0.73 -2.4 2.4 - Subregional Peak: 9.8 15 0 0.86 (at cell 53 x  0069 Burbank 6 7.0 12 6.5 12 0 0.93 -0.2 0.2 - 0088 Pasadena 4 7.1 13 5.9 13 0 0.84 -0.2 0.2 - 0074 Reseda 9 9.4 16 7.5 13 -3 0.80 -0.4 0.4 - 0090 Santa Clarita 9 11.4 15 8.3 13 -2 0.73 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 143 (05/23) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 113 13.0 15 11.2 13 -2 0.86 -1.5 2.1 - Subregional Peak: 11.9 13 -2 0.91 (at cell 77 x  0060 Azusa 4 8.6 14 5.9 15 1 0.69 -0.3 0.3 - 4164 Banning Airport 15 13.0 15 11.2 13 -2 0.86 -0.2 0.2 - 5181 Crestline 18 11.6 15 8.6 13 -2 0.74 -0.4 0.4 - 4158 Elsinore 9 8.8 11 11.0 13 2 1.25 0.2 0.3 - 5197 Fontana 7 10.6 13 8.1 12 -1 0.76 -0.3 0.3 - 0591 Glendora 5 9.6 14 6.2 15 1 0.65 -0.3 0.3 - 5212 Mira Loma 8 9.2 14 8.2 12 -2 0.89 -0.2 0.2 - 4149 Perris 9 9.8 12 10.4 13 1 1.06 0.1 0.2 - 0075 Pomona 6 8.2 13 6.6 12 -1 0.80 -0.3 0.3 - 5204 Redlands 9 10.1 12 10.9 13 1 1.08 0.0 0.1 - 4144 Rubidoux 8 10.4 14 9.1 12 -2 0.87 -0.2 0.2 - 5203 San Bernardino 9 10.0 13 10.2 13 0 1.02 -0.1 0.1 - 5175 Upland 6 9.5 14 7.0 12 -2 0.74 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 143 (05/23) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 8 8.0 15 5.2 12 -3 0.65 -3.3 3.3 - Subregional Peak: 9.1 12 -3 1.14 (at cell 68 x  0091 West Los Angeles 8 8.0 15 5.2 12 -3 0.65 -0.5 0.5 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 143 (05/23) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 40 11.4 16 9.0 14 -2 0.79 -2.4 2.6 - Subregional Peak: 11.3 14 -2 0.99 (at cell 106 x  4157 Indio Jackson 19 10.1 18 9.0 14 -4 0.89 -0.3 0.3 - 4137 Palm Springs 21 11.4 16 7.8 16 0 0.68 -0.3 0.3 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 144 (05/24) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0003 SubRegion 10 8.8 15 7.8 13 -2 0.88 -1.4 1.4 - Subregional Peak: 9.2 14 -1 1.04 (at cell 52 x  0074 Reseda 5 7.7 13 6.4 12 -1 0.83 -0.2 0.2 - 0090 Santa Clarita 5 8.8 15 7.8 13 -2 0.88 -0.2 0.2 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 144 (05/24) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0004 SubRegion 90 10.6 15 9.6 15 0 0.91 -1.7 2.1 - Subregional Peak: 9.9 14 -1 0.94 (at cell 77 x  0060 Azusa 3 6.6 14 5.8 15 1 0.88 -0.2 0.2 - 4164 Banning Airport 13 10.6 15 9.6 15 0 0.91 -0.2 0.2 - 5181 Crestline 13 9.5 16 7.0 13 -3 0.74 -0.4 0.4 - 4158 Elsinore 9 7.7 11 9.1 14 3 1.18 0.1 0.2 - 5197 Fontana 6 8.1 15 5.8 12 -3 0.71 -0.4 0.4 - 0591 Glendora 5 7.4 15 5.7 15 0 0.78 -0.2 0.2 - 5212 Mira Loma 7 8.4 12 6.2 15 3 0.73 -0.2 0.2 - 4149 Perris 6 7.7 14 8.8 13 -1 1.15 0.1 0.2 - 0075 Pomona 5 7.6 14 4.1 12 -2 0.54 -0.4 0.4 - 5204 Redlands 6 8.8 14 8.5 13 -1 0.96 -0.1 0.2 - 4144 Rubidoux 7 9.2 12 7.0 12 0 0.76 -0.3 0.3 - 5203 San Bernardino 6 8.6 15 7.5 13 -2 0.87 -0.2 0.2 - 5175 Upland 4 7.2 14 4.3 13 -1 0.60 -0.4 0.4 - * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 144 (05/24) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0005 SubRegion 1 6.1 18 2.4 18 0 0.39 -3.7 3.7 - Subregional Peak: 7.8 14 -4 1.28 (at cell 68 x  0091 West Los Angeles 1 6.1 18 2.4 18 0 0.39 -0.6 0.6 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 Simula Statistics were calculated for the 24-hour period of DOY 144 (05/24) 2005  Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm)  ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B ---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- -----  0009 SubRegion 27 9.5 13 8.2 14 1 0.86 -1.8 2.0 - Subregional Peak: 12.6 14 1 1.33 (at cell 106 x  4157 Indio Jackson 12 8.1 13 8.2 14 1 1.01 -0.1 0.2 - 4137 Palm Springs 15 9.5 13 6.4 11 -2 0.67 -0.3 0.3 -
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubRegional Descriptions  SubRegion 003 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0069 Burbank 53 48 -27.848 461.308  0088 Pasadena 56 47 -11.205 457.021  0074 Reseda 49 48 -48.000 463.105  0090 Santa Clarita 49 52 -48.140 483.357  SubRegion 004 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  0060 Azusa 60 47 6.981 456.113  4164 Banning Airport 79 42 104.459 433.527  5181 Crestline 72 49 66.383 468.606  4158 Elsinore 71 37 60.525 405.907  5197 Fontana 68 46 46.811 453.081  0591 Glendora 61 47 13.487 457.010  5212 Mira Loma 67 43 42.938 438.915  4149 Perris 72 39 69.051 417.376  0075 Pomona 63 45 22.598 448.610  5204 Redlands 74 45 76.256 448.189  4144 Rubidoux 69 44 52.093 442.557  5203 San Bernardino 72 46 65.874 453.299  5175 Upland 65 46 31.687 452.125  SubRegion 005 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  3176 Anaheim 60 40 7.422 421.645  0087 Los Angeles 54 45 -22.302 445.563  3195 Costa Mesa 60 37 6.793 405.626  3177 La Habra 59 42 4.359 432.978  0820 LAXH 51 42 -36.352 433.685  0072 Long Beach 55 40 -17.171 421.903  0084 Lynwood 55 42 -19.237 432.753  3812 Mission Viejo 64 36 29.671 400.791  0085 Pico Rivera 57 44 -5.273 442.860  0091 West Los Angeles 52 45 -34.796 447.031  SubRegion 009 Contains the Following Sites:  Site Site Description Xcell Ycell XPos(km) YPos(km)  ---- -------------------------------- ------ ------ --------- ---------  4157 Indio Jackson 91 38 162.217 411.293  4137 Palm Springs 85 40 132.826 423.133 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 137 (05/17) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 2 6.1 11 5.9 9 -2 0.97 -0.7 0.7 - Subregional Peak: 6.8 11 0 1.11 (at 79 x 38) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 137 (05/17) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 6.4 11 5.8 10 -1 0.91 -0.6 0.6 - Subregional Peak: 6.2 14 3 0.97 (at 84 x 35) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 138 (05/18) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 2 6.8 11 5.0 10 -1 0.73 -1.8 1.8 - Subregional Peak: 5.7 10 -1 0.83 (at 61 x 58) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 138 (05/18) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 9 8.0 10 6.9 10 0 0.87 -1.7 1.7 - Subregional Peak: 8.0 11 1 1.00 (at 79 x 38) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 138 (05/18) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 8.2 10 7.6 10 0 0.93 -0.2 0.3 - Subregional Peak: 8.2 9 -1 1.00 (at 106 x 12) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 139 (05/19) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 3 6.7 10 4.8 10 0 0.72 -2.2 2.2 - Subregional Peak: 5.9 11 1 0.89 (at 58 x 50) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 139 (05/19) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 9.5 11 7.1 10 -1 0.75 -2.7 2.7 - Subregional Peak: 8.0 10 -1 0.84 (at 79 x 38) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 139 (05/19) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 1 6.7 11 4.5 10 -1 0.67 -2.2 2.2 - Subregional Peak: 5.3 10 -1 0.78 (at 68 x 37) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 139 (05/19) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 8.5 12 8.4 10 -2 0.99 -0.2 0.9 - Subregional Peak: 9.5 9 -3 1.12 (at 108 x 13) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 140 (05/20) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 10 9.6 11 7.0 9 -2 0.74 -2.1 2.1 - Subregional Peak: 7.8 10 -1 0.82 (at 78 x 33) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 140 (05/20) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 8.7 10 6.7 9 -1 0.77 -1.6 1.6 - Subregional Peak: 9.2 9 -1 1.06 (at 109 x 12) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 141 (05/21) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 8.7 11 5.8 10 -1 0.66 -2.3 2.3 - Subregional Peak: 8.3 12 1 0.95 (at 59 x 51) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 141 (05/21) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 11.2 13 8.6 10 -3 0.77 -1.1 1.6 - Subregional Peak: 9.4 11 -2 0.84 (at 72 x 35) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 141 (05/21) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 4 7.4 11 6.6 11 0 0.88 -1.6 1.7 - Subregional Peak: 7.8 11 0 1.05 (at 68 x 37) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 141 (05/21) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 7.7 14 6.5 10 -4 0.85 -0.7 0.7 - Subregional Peak: 8.3 9 -5 1.09 (at 110 x 10) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 142 (05/22) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 4 11.4 10 6.5 10 0 0.57 -4.5 4.5 - Subregional Peak: 8.6 11 1 0.76 (at 58 x 49) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 142 (05/22) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 13 14.5 12 11.1 10 -2 0.77 -2.4 2.7 - Subregional Peak: 11.6 10 -2 0.80 (at 73 x 47) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 142 (05/22) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 7 9.8 10 7.0 10 0 0.71 -2.7 2.7 - Subregional Peak: 9.7 9 -1 0.99 (at 68 x 37) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 142 (05/22) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 10.9 15 7.8 10 -5 0.72 -2.5 2.5 - Subregional Peak: 9.5 11 -4 0.87 (at 81 x 43) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 143 (05/23) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 3 9.5 11 6.4 10 -1 0.68 -2.3 2.3 - Subregional Peak: 7.4 11 0 0.77 (at 53 x 55) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 143 (05/23) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 12 10.9 10 9.6 9 -1 0.88 -1.0 1.6 - Subregional Peak: 10.3 9 -1 0.95 (at 76 x 42) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 143 (05/23) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0005 SubRegion 1 7.1 12 4.7 10 -2 0.66 -2.4 2.4 - Subregional Peak: 8.0 8 -4 1.13 (at 68 x 37) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 143 (05/23) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 10.8 11 8.5 10 -1 0.78 -2.1 2.1 - Subregional Peak: 9.5 11 0 0.88 (at 106 x 12) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 144 (05/24) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0003 SubRegion 2 7.6 11 6.4 10 -1 0.85 -1.3 1.3 - Subregional Peak: 7.4 11 0 0.98 (at 52 x 55) NSt
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 144 (05/24) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0004 SubRegion 10 9.2 11 8.1 10 -1 0.88 -1.0 1.4 - Subregional Peak: 8.5 10 -1 0.92 (at 76 x 41) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaStatistics were calculated for the 24-hour period of DOY 144 (05/24) 2005 Included were data-pairs with observed concentrations above a threshold of 6.0 (pphm); Avera ------- Peak Concentrations -------- --- Comparisons w Observed Predicted Time Peak Mean Mean Site Description No Value Time Value Time Lag Ratio Bias Error B---- ------------------------ ---- ------ ---- ------ ---- ---- ----- ----- ----- -0009 SubRegion 2 8.9 12 7.4 10 -2 0.84 -1.3 1.3 - Subregional Peak: 8.8 9 -3 1.00 (at 105 x 13) NSt * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0000 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 137  Unpaired Subregional Maximum of 7.7 at Cell 108 x 11 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 137 138 139 140 141 Avg. 137 138 139 140 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0001 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 137  Unpaired Subregional Maximum of -99.0 at Cell -9 x -9 -- Nearest Site: 08 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 137 138 139 140 141 Avg. 137 138 139 140 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0002 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 137  Unpaired Subregional Maximum of 6.6 at Cell 49 x 54 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 137 138 139 140 141 Avg. 137 138 139 140 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0003 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 137  Unpaired Subregional Maximum of 8.2 at Cell 59 x 50 -- Nearest Site: 00 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 137 138 139 140 141 Avg. 137 138 139 140 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 0069 Burbank 7.6 4.3 5.2 6.4 5.4 7.1 5.0 4.6 4.4 4.4 4.7 0088 Pasadena 8.6 4.4 5.3 6.5 5.3 8.0 4.5 4.0 3.9 3.9 4.1 0074 Reseda 7.6 5.2 6.3 6.7 5.1 7.3 5.4 5.0 4.5 4.8 5.0 0090 Santa Clarita 8.7 5.5 6.8 5.7 4.0 8.7 5.5 5.0 5.0 5.3 5.1 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0004 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 137  Unpaired Subregional Maximum of 9.2 at Cell 68 x 48 -- Nearest Site: 51 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 137 138 139 140 141 Avg. 137 138 139 140 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 0060 Azusa 8.6 4.2 5.4 6.3 5.0 7.2 4.6 4.1 4.1 3.9 3.9 4164 Banning Airport 8.5 6.1 7.5 9.0 7.3 7.2 7.8 5.9 6.9 7.1 7.0 5181 Crestline 9.9 5.2 7.1 7.9 9.6 11.2 6.6 4.9 5.4 5.6 5.9 4158 Elsinore 7.4 5.3 7.2 7.1 6.2 7.3 7.4 5.7 5.6 5.8 5.7 5197 Fontana 8.4 5.1 6.7 8.5 7.3 8.1 5.7 4.3 4.6 4.7 4.9 0591 Glendora 8.1 4.7 5.9 7.4 6.2 7.3 4.9 4.4 4.3 4.2 4.2 5212 Mira Loma 8.3 5.6 7.3 8.4 7.6 7.9 5.9 4.7 4.4 4.8 4.6 4149 Perris 7.1 4.6 6.1 7.1 4.1 6.6 7.3 5.6 5.7 6.0 6.0 0075 Pomona 7.7 4.5 5.9 7.4 5.9 6.5 5.0 4.2 4.3 4.3 4.4 5204 Redlands 8.1 4.6 6.8 7.5 7.6 7.9 7.2 5.1 5.8 5.8 6.4 4144 Rubidoux 8.9 6.1 8.0 9.5 8.8 8.9 6.5 4.9 4.9 5.3 5.3 5203 San Bernardino 8.7 4.8 6.9 8.3 8.5 8.5 6.7 4.8 5.3 5.4 5.9 5175 Upland 8.1 4.3 5.9 7.5 6.3 7.5 5.1 4.1 4.2 4.2 4.3  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0005 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 137  Unpaired Subregional Maximum of 8.8 at Cell 69 x 37 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 137 138 139 140 141 Avg. 137 138 139 140 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 3176 Anaheim 7.5 5.2 5.9 5.7 4.7 5.8 4.1 3.9 3.5 3.2 3.2 0087 Los Angeles 8.4 4.6 4.9 4.8 4.1 6.9 3.9 3.8 3.6 3.5 3.6 3195 Costa Mesa 6.2 4.5 5.0 4.7 3.8 6.0 5.2 5.2 5.3 4.7 4.9 3177 La Habra 7.4 3.7 4.6 3.7 3.1 4.7 4.2 3.8 3.8 3.8 3.8 0084 Lynwood 8.2 4.2 4.4 4.4 3.6 5.6 4.2 4.0 4.0 3.7 3.9 3812 Mission Viejo 7.2 4.8 5.4 6.7 5.5 6.4 5.5 4.8 4.9 4.5 4.5 0091 West Los Angeles 7.8 4.8 5.4 4.9 4.8 7.4 4.6 4.6 4.3 4.3 4.6 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0006 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 137  Unpaired Subregional Maximum of 9.0 at Cell 70 x 36 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 137 138 139 140 141 Avg. 137 138 139 140 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0007 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 137  Unpaired Subregional Maximum of -99.0 at Cell -9 x -9 -- Nearest Site: 08 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 137 138 139 140 141 Avg. 137 138 139 140 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- ---  * * * Model Performance Evaluation * * *  Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0008 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 137  Unpaired Subregional Maximum of 7.4 at Cell 80 x 60 -- Nearest Site: 51 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 137 138 139 140 141 Avg. 137 138 139 140 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 
 * * * Model Performance Evaluation * * * 

 Pollutant: O3 (pphm) Project: CAMx v4.4 SimulaSubregion 0009 Spatially Paired Average 8-Hour Concentrations above 6.0 pphm for DOY 137  Unpaired Subregional Maximum of 8.1 at Cell 107 x 12 -- Nearest Site: 41 - - - - - Observed - - - - - - - - - - Simulated - - Site Site Site DOY DOY DOY DOY DOY Site DOY DOY DOY DOY  ID Description Avg. 137 138 139 140 141 Avg. 137 138 139 140 ---- ------------------------ --- --- --- --- --- --- --- --- --- --- --- 4157 Indio Jackson 7.9 6.4 8.2 7.7 8.7 6.7 7.3 5.7 7.6 8.4 6.7 4137 Palm Springs 8.5 6.4 7.0 8.5 7.5 7.7 6.7 5.8 7.1 7.3 6.3 
ATTACHMENT-3 

Draft Modeling Protocol 
 

DRAFT 

MODELING PROTOCOL 

FOR OZONE AND PARTICULATE MATTER MODELING 

IN SUPPORT OF THE SOUTH COAST AIR QUALITY 

MANAGEMENT DISTRICT 2007 AIR QUALITY 

MANAGEMENT PLAN UPDATE 

Draft Report 

May 9, 2006 

Jointly Prepared by:

California Air Resources Board 

Planning & Technical Support Division 

P.O. Box 2815 

Sacramento, CA 95812 

and 

South Coast Air Quality Management District 

Planning, Rule Development and Area Sources 

21865 Copley Drive 

Diamond Bar, CA 91765 
 

Send Comments to:

Kevin Durkee 

South Coast Air Quality Management District 

kdurkee@aqmd.gov

Contributors:

Mark Bassett 

Joseph Cassmassi 

John DaMassa 

Kevin Durkee 

Bruce Jackson 

Bong-Mann Kim 

Satoru Mitsutomi 

Xinqiu Zhang 
 

TABLE OF CONTENTS 

TABLE OF CONTENTS......................................................................................liii 

LIST OF FIGURES ..............................................................................................liii 

LIST OF TABLES................................................................................................liii 

LIST OF ACRONYMS ........................................................................................liii 

INTRODUCTION ................................................................................................ 53 

Background ................................................................................................................................ 53

Regulatory Modeling Requirements and Guidance................................................................ 53

AQMP Ozone Modeling History in the South Coast Air Basin ............................................. 53

AQMP PM Modeling History in the South Coast Air Basin.................................................. 53

2007 AQMP Modeling Analysis Goals...................................................................................... 53

Ozone Design Value Determination....................................................................................... 53

Overview of the Modeling Analysis........................................................................................... 53

2007 AQMP Schedule................................................................................................................ 53

AQMP Modeling Technical Oversight....................................................................................... 53

MODEL SELECTION.......................................................................................... 53 

Meteorological Model ................................................................................................................ 53

Background ............................................................................................................................ 53

Previous AQMP Applications ................................................................................................ 53

2007 AQMP Meteorological Modeling Approach ................................................................. 53

Air Quality Model ...................................................................................................................... 53

Background ............................................................................................................................ 53

2007 AQMP Air Quality Modeling Approach ....................................................................... 53

MODELING DOMAIN........................................................................................ 53 

Meteorological Modeling Domain ............................................................................................. 53

Ozone Modeling Domain ........................................................................................................... 53

PM Modeling Domain................................................................................................................ 53

HORIZONTAL AND VERTICAL GRID RESOLUTION ................................. 53 

Horizontal Grid Resolution ........................................................................................................ 53

Vertical Resolution..................................................................................................................... 53

Meteorological Modeling ....................................................................................................... 53

Air Quality Modeling ............................................................................................................. 53

EPISODE SELECTION ....................................................................................... 53 

Ozone Episodes.......................................................................................................................... 53

August 3-7, 1997 (Sunday – Thursday).................................................................................. 53

June 3-7, 2004 (Thursday – Monday) .................................................................................... 53

August 4-8, 2004 (Wednesday – Sunday) .............................................................................. 53

May 17-24, 2005 (Tuesday – Tuesday).................................................................................. 53

July 14-19, 2005 (Thursday – Tuesday)................................................................................. 53

August 25-29, 2005 (Thursday – Monday) ............................................................................ 53

Possible Seasonal Ozone Episode: Summer 1997................................................................. 53

Ozone Episode Statistical Ranking ............................................................................................ 53

PM Episodes............................................................................................................................... 53

Annual PM: January 1 – December 31, 2005........................................................................ 53

Episodic PM10/2.5: October 19-25, 2005 & March 6-12, 2005 ........................................... 53

INITIAL AND BOUNDARY CONDITIONS ..................................................... 53 

Initial Conditions........................................................................................................................ 53

Boundary Conditions.................................................................................................................. 53

METEOROLOGICAL INPUTS........................................................................... 53 

Meteorological Input Evaluation and Technical Review ........................................................... 53

Qualitative Analyses............................................................................................................... 53
 

Quantitative Analyses............................................................................................................. 53

EMISSION INVENTORY INPUTS .................................................................... 53 

Emissions Characterization ........................................................................................................ 53

Point Sources.......................................................................................................................... 53

Area Sources .......................................................................................................................... 53

On-Road Mobile Sources ....................................................................................................... 53

Other Mobile Sources............................................................................................................. 53

Biogenic Emissions ................................................................................................................ 53

Organic Gas Speciation .......................................................................................................... 53

Day-Specific Emissions ......................................................................................................... 53

Emissions Quality Assurance..................................................................................................... 53

Emission Projections .................................................................................................................. 53

AIR QUALITY MODEL PERFORMANCE EVALUATION ............................ 53 

Statistical and Graphical Analyses ............................................................................................. 53

Subregional Performance ....................................................................................................... 53

Multi-Species Evaluations...................................................................................................... 53

Aloft Comparisons ................................................................................................................. 53

Acceptable Model Performance ............................................................................................. 53

Sensitivity Analyses ................................................................................................................... 53

Diagnostic Simulations........................................................................................................... 53

USE OF THE MODEL RESULTS....................................................................... 53 

Attainment Demonstration ......................................................................................................... 53

Relative Reduction Factors..................................................................................................... 53

Carrying Capacity Estimation .................................................................................................... 53

REFERENCES ..................................................................................................... 53 
 

LIST OF FIGURES 

FIGURE 1 Nested MM5 Domains ............................................................................................... 53

FIGURE 2 The Fine-Scale (5 km) MM5 Domain........................................................................ 53

FIGURE 3 2007 AQMP Ozone Modeling Domain ..................................................................... 53

FIGURE 4 2007 AQMP PM Modeling Domain, inside the Ozone Modeling Domain ............... 53

LIST OF TABLES 

TABLE 1 National Ambient Air Quality Standards Compliance Status in the South Coast Air 

Basin....................................................................................................................................... 53

TABLE 2 Ozone Design Value (ppb) for Each Station, 2000-2004 ............................................ 53

TABLE 3 Summary of Proposed 2007 AQMP Model Selection and Application ...................... 53

TABLE 4 Tentative 2007 AQMP Schedule................................................................................. 53

TABLE 5 Vertical Structure for the MM5 Meteorological Model............................................... 53

TABLE 6 Vertical Structures for the CAMx Ozone and PM Simulations................................... 53

TABLE 7 Summary of Ozone Episodes to be Simulated for the 2007 AQMP............................ 53

TABLE 8 Ozone Episode Characterization.................................................................................. 53

TABLE 9 Highest 24-Hour Averaged SSI PM2.5 Concentration in 2005................................... 53

TABLE 10 SAPRC-99 Chemical Mechanism Species ................................................................ 53

TABLE 11 Proposed Meteorological Input Performance Benchmarks ....................................... 53

TABLE 12 Performance Goals for 1-Hour Ozone....................................................................... 53
 
 

LIST OF ACRONYMS 

Several acronyms are used in the modeling protocol document. For 

convenience, the acronyms used are listed below to aid the reader. 

AAMA – American Automobile Manufacturer's Association

AGL – Above Ground Level

AQMD – Air Quality Management District

AQMP – Air Quality Management Plan 

AQMPAG Air Quality Management Plan Advisory Group

AUSPEX – Atmospheric Utility Signatures, Predictions, and 

Experiments 

AVHRR – Advanced Very High Resolution Radiometer 

BEIS – Biogenic Emission Inventory System 

CAA – Clean Air Act Amendment of 1990 

CAMx – Comprehensive Air-Quality Model with Extensions 

CARB – California Air Resources Board 

CBM – Carbon Bond Mechanism 

CCAA – California Clean Air Act 

CEFS – California Emission Forecasting System 

CMAQ – Community Multi-scale Air Quality (model) 

CO – Carbon Monoxide 

COG – Council of Governments 

DARS – Data Attribute Rating System 

DWM – Diagnostic Wind Model 

DTIM – Direct Travel Impact Model 

EIWG – Emission Inventory Working Group 

EKMA – Empirical Kinetics Modeling Approach 

EMFAC – Emission Factor (model) 

FCM – Flexible Chemical Mechanism 

FDDA – Four-Dimensional Data Assimilation 

GAP – Geographical Approach to Protection of Biological 

Diversity 

GCM – Global Climate Model 

ICAPCD – Imperial County Air Pollution Control District 

IOP – Intensive Operation Period 

LIDAR – Light Detection and Ranging 

MDAQMD – Mojave Desert Air Quality Management District 

MM5 – Mesoscale Meteorological Model (5th generation) 

MWG – Modeling Working Group 

NAAQS – National Ambient Air Quality Standard 

NDVI – Normalized Difference Vegetative Index 
 

NOx – Nitrogen Oxides 

NO2 – Nitrogen Dioxide 

PDT – Pacific Daylight Time 

PM – Particulate Matter 

PM10 – Particulate Matter less than 10 microns equivalent 

aerodynamic diameter 

PM2.5 – Particulate Matter less than 2.5 microns equivalent 

aerodynamic diameter 

PMcourse – PM10 – PM2.5 

PMfine – PM2.5 

RADM – Regional Acid Deposition Model 

RECLAIM – Regional Clean Air Incentives Market 

ROG – Reactive Organic Gases 

RRF – Relative Reduction Factor 

SANDAG – San Diego Association of Governments

SAPRC – State Air Pollution Research Center 

SAQM – SARMAP Air Quality Model 

SARMAP – SJVAQS/AUSPEX Regional Model Adaptation Project 

SBCAG – Santa Barbara County Association of Governments 

SBCAPCD – Santa Barbara County Air Pollution Control District 

SCAB – South Coast Air Basin

SCAG – Southern California Association of Governments

SCAQMD – South Coast Air Quality Management District 

SCAQS – Southern California Air Quality Study 

SCE – Southern California Edison 

SCOS97 – Southern California Ozone Study (1997) 

SDCAPCD – San Diego County Air Pollution Control District 

SIP – State Implementation Plan 

SJVAQS – San Joaquin Valley Air Quality Study 

SOx – Sulfur Oxides 

STMPRAG – Scientific, Technical, Modeling and Peer Review 

Advisory Group 

TOG – Total Organic Gases 

UAM – Urban Airshed Model 

USEPA – United States Environmental Protection Agency 

UTM – Universal Transverse Mercator 

VCAPCD – Ventura County Air Pollution Control District 

VMT – Vehicle Miles Traveled 

VOC – Volatile Organic Compound 

WSPA – Western States Petroleum Association 
KRD: DRAFTModelingProtocol.doc 3/2/2007 1

INTRODUCTION 

The federal Clean Air Act (CAA) requires areas with unhealthy levels of 

ozone , carbon monoxide, nitrogen dioxide, sulfur dioxide, and inhalable 

particulate matter to develop plans, known as State Implementation Plans 

(SIPs), describing how they will attain national ambient air quality 

standards (NAAQS). The 2007 Air Quality Management Plan (AQMP or 

Plan) for the South Coast Air Basin (Basin) will meet the SIP update 

requirements for this area, demonstrating NAAQS attainment. The federal 

Clean Air Act (CAA) requires the use of photochemical grid models that 

are approved by the Unites States Environmental Protection Agency 

(USEPA) to perform the attainment demonstration. This document 

addresses the air quality modeling protocol for the 2007 AQMP, as 

developed through a joint cooperative effort between the staff of the South 

Coast Air Quality Management District (AQMD or District) and the 

California Air Resources Board (CARB), with technical oversight from the 

Scientific, Technical, Modeling and Peer Review Advisory Group 

(STMPRAG). 

The objective of this modeling protocol is to define the methodology to be 

used for simulating the formation and transport of ozone and particulate 

matter in the Basin, including: 

• the model(s) to be used; 

• the modeling domain; 

• the horizontal and vertical grid resolution; 

• the annual PM period and ozone and PM episodes to be simulated; 

• the model input data, including meteorology, emissions, initial 

conditions; and lateral and top boundary conditions; 

• the process for model performance evaluation. 

In addition, the protocol outlines the attainment demonstration process, 

including a review of the California Clean Air Act (CCAA) requirements. 

This protocol document is intended to be dynamic and will be updated in 

response to reviewer comments and to reflect the results of new 

information that will emerge during the AQMP modeling process. 

In order to devote the maximum resources practicable to the development 

of the District's 2007 AQMP, the Executive Officers of CARB and AQMD 

have agreed to jointly develop the emissions and air quality modeling 

needed to determine the carrying capacity and attainment demonstration for 

the ozone and PM standards. The technical staffs of both agencies are 

working closely together to plan and carry out the necessary work for the 
KRD: DRAFTModelingProtocol.doc 3/2/2007 2

AQMP and are committed to intensive and timely coordination to ensure 

that it is based on the soundest science possible. Both agencies agree that 

their staffs will collaborate on this work such that the product will be 

mutually acceptable modeling analyses for use in the 2007 Plan. 

Background 

Regulatory Modeling Requirements and Guidance

The 1990 amendments to the federal CAA set new deadlines for attainment 

based on the severity of the pollution problem and launched a 

comprehensive planning process for attaining the NAAQS. The 

promulgation of the new national eight-hour ozone standard and the fine 

particulate matter (PM2.5) NAAQS in 1997 required additional statewide 

air quality planning efforts. In response to new federal regulations, SIPs 

must also address ways to improve visibility in national parks and 

wilderness areas. SIPs demonstrating attainment of the federal ozone 

standard must be adopted by the local air districts and CARB, and 

submitted to the USEPA by June 15, 2007. 

USEPA's guidelines on air quality modeling previously recommended the 

use of the Urban Airshed Model (UAM) for attainment demonstrations 

involving entire urban areas. However, USEPA revised its 

recommendation (USEPA, 2001a) to no longer include a recommended air 

quality model for ozone. Instead, USEPA recommends that air quality 

models proposed for an ozone attainment demonstration be subjected to 

model performance evaluations to demonstrate that they are appropriate for 

attainment demonstration purposes. 

USEPA issued the Guideline for Regulatory Applications of the Urban 

Airshed Model (USEPA, 1991) and Guidance on the Use of Modeled 

Results to Demonstrate Attainment of 1-hour Ozone NAAQS (USEPA, 

1996) to assist states in preparing the attainment demonstration required by 

the CAA. In addition, the CARB Technical Guidance Document: 

Photochemical Modeling (CARB, 1992) provides photochemical modeling 

guidance for use by the districts to ensure the technical validity of the 

modeling results. Most recently, USEPA has finalized attainment 

demonstration guidance for the 8-hour ozone NAAQS (USEPA, 2005). 

The ozone modeling protocol in this document is based on these guideline 

documents. Guidance for the PM portion of the modeling protocol utilizes 

the Draft Guidance for Demonstrating Attainment of Air Quality Goals for 

PM2.5 and Regional Haze (USEPA, 2001b). 
KRD: DRAFTModelingProtocol.doc 3/2/2007 3

Under the federal Clean Air Act of 1990 (CAA), the South Coast Air Basin 

(Basin) was classified as an “extreme” nonattainment area for 1-hour 

ozone. Section 182(c)(2)(A) of the CAA set November 15, 1994 as the 

deadline for submission of a SIP to demonstrate attainment of the NAAQS 

for ambient 1-hour ozone of 0.125 parts per million (ppm) by December 

2010. AQMD satisfied that CAA requirement with the submittal of the 

1994 AQMP in September 1994. A subsequent revision was submitted to 

USEPA in February 1997. This was amended in 1999 to revise the Basin 

ozone portion of the 1997 AQMP due to its partial approval/disapproval by 

USEPA. The 2003 AQMP took advantage of information obtained from 

the 1997 Southern California Ozone Study (SCOS97) and emissions 

inventory enhancements. It updated the attainment demonstration for the 

ozone and PM10 particulate matter NAAQS, replaced the 1997 attainment 

demonstration for the CO NAAQS, and updated the maintenance plan for 

the NO2 NAAQS that the Basin has met since 1992. In 2005, AQMD 

submitted a CO attainment request and maintenance plan to CARB and 

USEPA; approval of this is pending. 

In July 1997, the USEPA established new ozone NAAQS of 0.085 ppm 

based on an 8-hour average measurement. Due to legal challenges, the 

final form of the ozone NAAQS has been implemented in two phases. The 

Phase 1 ozone implementation rule, finalized on June 15, 2004, defined the 

classification scheme for 8-hour ozone nonattainment areas and revoked the 

1-hour ozone NAAQS, while requiring states to maintain control programs 

which were included in their state implementation plans (SIP) for the 1-

hour standard. Fifteen areas in California were designated that violate the 

federal 8-hour ozone standard. Each nonattainment area's classification and 

attainment deadline is based on the severity of its ozone problem. Southern 

California’s nonattainment areas and attainment deadlines are: South Coast 

Air Basin (2021); Coachella Valley (2013); Ventura County (2010); 

Western Mojave Desert (2010); Antelope Valley (2010); San Diego (2009-

2014); and Imperial County (2007). 

The Phase 2 ozone rule, adopted November 9, 2005, described the actions 

that states must take to reduce ground level ozone and set the deadline for 

ozone SIP submittal of June 2007. The AQMD began air quality modeling 

analyses related to the 8-hour ozone standard during the 1997 AQMP, prior 

to the final NAAQS implementation. This analysis effort was continued for 

the 2003 AQMP. The 2007 AQMP modeling will expand the 8-hour ozone 

analysis and include an attainment demonstration for the current form of 

the NAAQS. The 2007 AQMP will include an analysis of 1-hour ozone to 
KRD: DRAFTModelingProtocol.doc 3/2/2007 4

provide additional milestones for progress of ongoing control programs and 

for continuity with previous efforts. 

AQMP Ozone Modeling History in the South Coast Air Basin

The first Air Quality Management Plan (AQMP) for the Basin was 

produced in 1979 as part of a revision to California's SIP. The 1979 AQMP 

indicated that it would not be possible to achieve the federal 1-hour ozone 

air quality standard of 0.12 ppm by 1982. Because the emission controls 

discussed in the 1979 AQMP would not be fully effective until after 1982, 

CARB and USEPA granted an extension to 1987 for achievement of the 

standard. As part of that extension, a revision to the AQMP was performed 

by the AQMD in 1982 which included a new series of modeling analyses to 

address concerns regarding the original 1979 modeling analysis. 

For both the 1979 and 1982 AQMP revisions, the city-specific Empirical 

Kinetics Modeling Approach (EKMA) was applied. The 1979 AQMP used 

the city-specific EKMA procedures then in existence. The 1982 AQMP 

revision used a more sophisticated version of the EKMA procedures and 

also contained sensitivity analyses (Appendix VI-A of the 1982 AQMP 

revision). The UAM was used in conjunction with the EKMA analyses to 

evaluate the effect of applying all feasible control measures by 1987 

(Appendix VI-E of the 1982 AQMP revision). On the basis of those 

modeling studies, it was determined that hydrocarbon reductions on the 

order of 75 percent or greater would be required to attain the federal 

standard by 1987, given a forecasted 23 percent reduction in oxides of 

nitrogen. Forecasted emission data indicated that only a 33 percent 

hydrocarbon reduction could be expected by 1987. Issues raised during the 

1979 and 1982 AQMP revisions highlighted the need to use a threedimensional, photochemical model such as the UAM to better understand 

the complex interactions between precursor emissions, meteorology, and 

the formation of ozone in the Basin. 

For the 1989 AQMP revision, the UAM was applied to a single, multiday, 

ozone episode to demonstrate attainment of the National Ambient Air 

Quality Standard (NAAQS) for ozone. It was determined from the 

modeling analysis that hydrocarbon and oxides of nitrogen emission 

reductions of more than 80 percent would be needed in order to attain the 1-

hour ozoneNAAQS by the year 2007. The 1989 AQMP revision outlined 

three levels of controls (identified as Tiers I, II, and III) that separated the 

proposed control measures by known and proven technologies from those 

technologies anticipated to be available within the next 20 years. 
KRD: DRAFTModelingProtocol.doc 3/2/2007 5

For the 1991 AQMP, the AQMD used the UAM to further assess the 

effectiveness of the three tiers of control measures in reducing ambient 

ozone levels. To complement the single, multiday ozone episode used for 

the 1989 AQMP revision, two additional ozone episodes were modeled to 

investigate the effect of projected emission reductions on future ozone 

concentrations during a wider variety of meteorological conditions. 

Additional evaluations of model performance, including new graphical 

procedures and subregional performance statistics, were used to ensure 

adequate representation of the physical and chemical processes that 

influence ozone formation in the Basin. 

A number of improvements were made to the modeling analysis for the 

1994 AQMP. Growth factors for population and vehicle miles traveled 

(VMT) were revised to reflect the 1990 Census data and the economic 

climate of the early 1990s, and improved transportation modeling was 

considered. The modeling analysis benefited from a number of AQMD, 

CARB, and SCAG studies that improved the area source emission 

inventory (Appendix III-A). On-road, mobile emission estimates were 

improved with the use of the latest CARB emission factors program, 

EMFAC7F. Five ozone episodes were simulated to evaluate control 

strategy effectiveness. In addition to the June 5-7, 1985, episode used in 

the 1989 AQMP, and the two Southern California Air Quality Study 

(SCAQS) episodes (August 26-28, 1987, and June 23-25, 1987) added for 

the 1991 AQMP analysis, two additional episodes (July 13-15, 1987, a 

SCAQS episode, and September 7-9, 1987) were simulated for the 1994 

AQMP. In this manner, control strategy decisions were based on a range of 

meteorological conditions, thereby reducing uncertainty in the control 

strategy’s effectiveness. It was determined that hydrocarbon and oxides of 

nitrogen emission reductions on the order of 80 and 60 percent, 

respectively, would be needed in order to attain the NAAQS. 

Based on the AQMD’s experience with the five ozone episodes used in 

preparing the 1994 AQMP, it was decided to drop the June 1985 

meteorological episode for the 1997 AQMP. The AQMD believed that the 

1987 meteorological episodes were satisfactorily evaluated. Since the 1985 

meteorological episode was based on routinely monitored data, it was 

believed that the 1987 SCAQS episodes provided improved performance. 

In October 1998, AQMD provided to the USEPA a “weight of evidence” 

analysis that indicated that even without the June 1985 episode, a viable 

ozone attainment demonstration could be made. 

As a result of intense interest for aerometric databases to support regional

ozone modeling, a large-scale field measurement program was carried out 
KRD: DRAFTModelingProtocol.doc 3/2/2007 6

in southern California during the Summer of 1997 to collect sufficient 

aerometric data to allow data analysts and modelers to characterize and 

simulate ozone formation and fate in the region. Several agencies and 

others participated during the planning and operational phases of the field 

study, including CARB, USEPA, the local air districts, the US Navy, the 

US Marines, and the marine industry. The 1997 Southern California Ozone 

Study, or SCOS97, occurred over a four month period from June 15 

through October 15, 1997 and captured several episodic ozone days. 

The 2003 AQMP updated the attainment demonstration for the federal 

standards for ozone and PM10; replaced the 1997 attainment demonstration 

for the federal CO standard and provided a basis for a maintenance plan for 

CO for the future; and updated the maintenance plan for the federal NO2 

standard that the Basin has met since 1992. New ozone episodes, including 

these from SCOS97, were included as complementary or replacement 

episodes in the 2003 AQMP. This revision to the AQMP also addressed 

several state and federal planning requirements and incorporated significant 

new scientific data, primarily in the form of updated emissions inventories, 

ambient measurements, new meteorological episodes and new air quality 

modeling tools. This revision pointed to the need for additional emission 

reductions (beyond those incorporated in the 1997/99 Plan) from all 

sources, specifically those under the jurisdiction of CARB and the USEPA 

which account for approximately 80 percent of the ozone precursor 

emissions in the Basin. 

The 2007 AQMP modeling effort focuses primarily on recent ozone 

episodes in 2004 and 2005. These periods better reflect emissions 

conditions following the reformulation of gasoline in California. The 

August 1997 episode from SCOS97 will be retained for continuity with the 

previous AQMP analyses. The 2007 AQMP will be consistent with and 

will build upon the modeling approaches taken in the previous SIP efforts 

for the South Coast Air Basin, utilizing the latest tools and technical 

guidance. 

AQMP PM Modeling History in the South Coast Air Basin

PM is a multicomponent pollutant including inorganic species such as 

sulfate, nitrate, ammonium, sodium, chloride, and organic compounds, 

elemental carbon, and a variety of trace metals. The PM10 modeling 

analysis shows that the annual average PM10 concentration is the 

controlling factor for attainment of the federal PM10 standards in the 

future. Although there were several PM10 modeling tools, there had been 

no single reliable annual PM10 model available to address the 
KRD: DRAFTModelingProtocol.doc 3/2/2007 7

multicomponent nature of the PM10. Therefore, a multi-pronged modeling 

methodology was employed to assess regional PM10 and demonstrate 

future compliance with the federal PM standards. 

For the 1989, l991, and 1994 AQMP, the Chemical Mass Balance (CMB) 

model for primary and secondary organic carbon and the Particle-In-Cell 

(PIC) model for sulfate and nitrate were used for annual PM10 analysis. 

And speciated linear rollback (SLR) was used for maximum 24-hour PM10 

analysis. 

For 1997 AQMP, a new annual PM10 modeling methodology, the 

UAM/LC model, was developed and applied. The Urban Airshed Model 

(UAM) (Ames, et al., 1985; and Morris, et al., 1990a, 1990b) was used as a 

host air quality model and the parameterized linear chemistry (LC) module 

was incorporated into the UAM. UAM was adapted to address the 

formation of particulate nitrate, sulfate, and ammonium and handling of 

primary particles by replacing the UAM standard chemical mechanism with 

the parameterized linear chemistry module. UAM/LC, unlike the PIC 

model, addresses the 3-dimensional aspects of transport and diffusion, 

varying mixing height, ammonia emissions change, and particulate nitrate 

concentrations. However, the UAM/LC model cannot handle secondary 

organic carbon because the current parameterized linear chemistry does not 

include organic chemistry. Secondary organic carbon is treated separately 

by the CMB model. 

For the 2003 AQMP, UAM/LC model was further enhanced to include 

secondary organic carbon and PM2.5 partition. The resulting UAMAEROLT model, for the first time, provided a more robust, stand-alone platform 

for primary and secondary annual PM2.5 and PM10 simulations. 

2007 AQMP Modeling Analysis Goals 

The 2007 AQMP modeling will focus primarily on the 8-hour ozone and 

the annual and 24-hour PM2.5 NAAQS attainment demonstration and 

reasonable further progress. The applicable NAAQS, along with the 

current attainment status of the South Coast Air Basin and recent design 

values, are presented in Table 1. Although the 1-hour federal standard was 

revoked in 2005, the analysis of 1-hour ozone will be retained as a 

benchmark of progress toward meeting the former 1-hour ozone NAAQS, 

as well as toward the State of California ozone standards. In addition to the 

PM2.5 NAAQS attainment demonstration, the particulate modeling 

analysis will include annual and 24-hour PM10 attainment demonstrations. 
KRD: DRAFTModelingProtocol.doc 3/2/2007 8

Further, the 2007 AQMP modeling will address maintenance plans for 

Carbon Monoxide (CO) and Nitrogen Dioxide (NO2). 

The modeling effort may also include initial modeling strategy 

development toward demonstrating attainment of the inhalable coarse 

particle (PM10-2.5) NAAQS and a stricter PM2.5 NAAQS recently 

proposed by USEPA. The proposed standards are: 

• PM10-2.5: 98th percentile 24-hour PM10-2.5 in a year, averaged over 3 

years not to exceed 70.4 μg/m3

; no annual standard; 

• PM2.5: 98th percentile 24-hour PM2.5 in a year, averaged over 3 years 

not to exceed 35.4 μg/m3

; no change to annual standard. 
KRD: DRAFTModelingProtocol.doc 3/2/2007 9

TABLE 1 

National Ambient Air Quality Standards Compliance Status in the South 

Coast Air Basin

8-Hour Ozone 24-Hour PM2.5 Annual PM2.5 

Standard 

3-year average of 

the 4th highest 

concentration not 

to exceed 0.084 

ppm 

3-year average of 

the 98th percentile 

of 24-hour 

concentrations not 

to exceed 65.4 

μg/m3

3-year average of 4 

quarterly averages 

not to exceed 15.04 

μg/m3

Classification 

Severe-17 

[may petition for 

Extreme] 

Non-Attainment Non-Attainment 

Attainment 

Date 

2021 

[2024, if Extreme] 

2015 2015 

Design Value 0.127 ppm 

(2002-2004) 

67 μg/m3

(2002-2004) 

24.8 μg/m3

(2002-2004) 

24-Hour PM10 Annual PM10 

Standard 

3-year average of 

the 99th percentile 

of 24-hour 

concentrations not 

to exceed 154 

μg/m3

3-year average of 4 

quarterly averages 

not to exceed 50.4 

μg/m3

Classification Serious 

Non-Attainment 

Serious 

Non-Attainment 

Attainment 

Date 2006 2006 

Design Value 159 μg/m3

(2002-2004) 

57 μg/m3

(2002-2004)
KRD: DRAFTModelingProtocol.doc 3/2/2007 10

Ozone Design Value Determination

Since the base year emissions are for 2004, air quality data from the three 

overlapping 3-year periods from 2000 through 2004 were used for 

calculation of the 8-hour ozone design values for each AQMD air 

monitoring station. These are shown in Table 2, along with the Relative 

Reduction Factors (RRF) needed. Per USEPA guidance, the design value 

averages are truncated (not rounded). 

TABLE 2 

Ozone Design Value (ppb) for Each Station, 2000-2004 

(Average of the 4th highest 8-hour station concentration in each 3-year period) 

Station 

2000-2002 

Design 

Value 

2001-2003

Design 

Value 

2002-2004

Design 

Value 

Current 

Design Value 

(DVC) 

RRF 

Required 

AZUS 102.3 101.0 101.0 101.43 0.8284 

BURK 91.7 91.3 91.3 91.43 0.9190 

LGBH 61.7 60.7 60.7 61.03 

RESE 93.3 106.3 106.3 101.97 0.8235 

POMA 89.7 96.7 96.7 94.37 0.8898 

LYNN 51.0 53.3 53.3 52.53 

PICO 80.3 79.0 79.0 79.43 

CELA 79.3 78.3 78.3 78.63 

PASA 96.3 95.3 95.3 95.63 0.8787 

SCLR 113.3 126.7 126.7 122.23 0.6874 

WSLA 69.3 73.3 73.3 71.97 

HAWT 69.3 71.0 71.0 70.43 

GLEN 110.7 114.3 114.3 113.10 0.7427 

ANAH 69.7 71.7 71.7 71.03 

LAHB 75.7 74.7 74.7 75.03 

CSTA 67.3 71.3 71.3 69.97 

MSVJ 80.0 82.7 82.7 81.80 

PLSP 105.3 108.3 108.3 107.30 0.7829 

RIVR 108.0 112.7 112.7 111.13 0.7561 

PERI 114.0 115.7 115.7 115.13 0.7298 

INDI 92.3 96.7 96.7 95.23 0.8824 

ELSI 104.3 109.0 109.0 107.43 0.7821 

UCRI 113.3 117.3 117.3 115.97 0.7241 

BNAP 110.3 118.7 118.7 115.90 0.7248 

UPLA 114.0 113.0 113.0 113.33 0.7414 

CRES 129.0 131.7 131.7 130.80 0.6422 

FONT 112.3 123.0 123.0 119.43 0.7035 

SNBO 114.7 118.7 118.7 117.37 0.7155 
KRD: DRAFTModelingProtocol.doc 3/2/2007 11

RDLD 120.0 128.3 128.3 125.53 0.6693 

MLOM 103.0 106.0 106.0 105.00 0.8000 

RHIS 130.3 136.7 136.7 134.57 0.6241 

Overview of the Modeling Analysis 

The analysis techniques currently recommended for attainment 

demonstrations using air quality models have changed significantly from 

those used in past demonstrations. In Guidance on the Use of Models and 

Other Analyses in Attainment Demonstration for the 8-hour Ozone NAAQS

(USEPA, 2005), USEPA recommends that the air quality models be used in 

a relative sense in concert with observed air quality data rather than 

applying the air quality model in a deterministic sense. The Relative 

Reduction Factor (RRF) which takes the ratio of future to present predicted 

air quality is multiplied to an “ambient design value” to demonstrate 

attainment. The proposed ozone modeling analysis is comprised of the 

following tasks: 

• Identify potential, new ozone meteorological episodes to be used. 

These episodes should represent the different meteorological conditions 

that are conducive to ozone formation in the Basin. 

• Among the widely accepted state-of-the-science ozone models, CAMx 

was selected for the attainment demonstration. CMAQ may be 

employed in the sensitivity analysis and weight-of-evidence section as a 

supportive modeling tool. 

• Develop model inputs. This task includes evaluation of the raw data 

and of the model input files developed from them. The input files will 

be evaluated using graphical and other techniques. 

• Simulate each episode with the proposed ozone models. This task 

includes a separate performance evaluation for each episode and each 

model. Documentation of the simulation results and performance 

evaluations will be provided. 

• Project ozone air quality with proposed control measures in effect for 

the years 2007, 2010, 2014, and 2020. This task includes the required 

attainment demonstration using RRF. Model projections for the year 

2007 are necessary since that is the year that the CAA requires 

attainment for severe-17 areas, such as the Coachella Valley and 

Mojave Desert Ozone Nonattainment Areas. Ozone air quality 

projections to 2020 will be used to demonstrate that the control strategy 

maintains the ozone NAAQS and to establish emission budgets needed 

for conformity purposes. 
KRD: DRAFTModelingProtocol.doc 3/2/2007 12

The work to do the foregoing tasks will be divided between the AQMD and 

CARB staffs and they will fully share all analyses, model inputs and 

outputs, findings, and conclusions. Consensus on each component of the 

analysis shall be reached before proceeding with subsequent components. 

In the event of technical disagreement on any of the work elements, the 

AQMD and CARB staffs shall attempt to reach consensus on a mutually 

acceptable approach. In the event that consensus cannot be reached, the 

disagreement will be elevated to the Executive Officers for resolution. 

Table 3 summarizes the model selection and application elements for the 

2007 AQMP and the changes from the 2003 AQMP modeling. 
KRD: DRAFTModelingProtocol.doc 13 

TABLE 3 

Summary of Proposed 2007 AQMP Model Selection and Application

2007 AQMP Element 2003 AQMP Element Selection Process/Issues/C

Ozone Dispersion Platform: CAMx Chemistry: SAPRC99 

Ozone Dispersion Platform: UAM Chemistry: SAPRC99 

• Peer Group Recommendation t

mass-consistent model/chemis

• Integrates with numerical weat• CAMx used by several agencie

development and supported by 

• Option for one atmosphere mo• Alternates CMAQ: Emissions 

extensive CALGRID: performwith no one-atmosphere model

PM10/PM2.5 Annual and Episodic Dispersion Platform: CAMx Chemistry: 

• AERO-LT with CB-IV • Enhanced CFI scheme 

with CB-IV 

• Optional One Atmosphere 

Aerosol chemistry 

PM10/PM2.5 Dispersion Platform: UAM Chemistry: AERO-LT with CBIV 

• CAMx PM dispersion consiste

discussion above. 

• Installed SCAQMD version of 

CAMx code (V4.20). 

• Enhanced CAMx two section C

It will be compared with AERO

Meteorology 

• MM5/4DDA • Hybrid MM5/CALMET • MM5 initialized using 

NCEP data 

Meteorology 

• CALMET Objective 

Analysis 

• Hybrid MM5/CALMET 

• EPA has expressed concerns ab

approach 

• MM5/4DDA is more mass con

capture localize wind impacts Fernando Valley) 

• Testing several land use assum

prognostic model to optimize wvertical mixing/diffusivity field

• Using Environ’s and Aerospac

performance evaluation softwa
KRD: DRAFTModelingProtocol.doc 14 

• Where possible take advantage 

observation field data (e.g. 3D-

Domain/ CoordinatesSCOS97 Meteorology: Lambert Conformal Emissions and Model application: UTM Ozone: 16 layers PM10/2.5: 8 layers 

Domain SCOS97 Meteorology: UTM Emissions and Model application: UTM Ozone & PM10 5-layers 

• Maintained the SCOS97 doma

inventories require coordinate 

adjust from statewide modeling are to biogenic and CEDARS o
KRD: DRAFTModelingProtocol.doc 15 

TABLE 3 (Continued) 

2007 AQMP Element 2003 AQMP Element Selection Process/Issues/C

Emissions Inventories 

• 2002 Base year • Enhanced aircraft/airport 

and shipping inventories 

• POLA/POLB updates • EMFAC2007 

o gross adjustments o “focused” 

inventories 

o Final public model 

• Adjustments to fugitive 

PM10/PM2.5 categories 

Emissions Inventories 

• 1997 Ozone base year & 

1995 PM10 base year 

• Updated aircraft/airport 

and shipping inventories 

• EMFAC2002V2.01 

 (major effort to develop 

surrogates for area sources) 

• 2002 Inventory will be used to 

2000 and project inventories milestone years 

• Waiting on SCAGS’ growth e

2004 RTP which is expected tfrom the 2007 RTP. 

• Episodic temperature and hum

to CARB for biogenic emissio

• CARB is adjusting temperatur

inventory development 

• Gridded inventories awaiting f

road model output and supplem

• No weekend trip model output 

SCAG 

• CARB will develop a “weeken

VMT based on Caltrans in-ro

Air Quality Model Performance Ozone

• Assess model performance 

based on both 1-hour and 8-hour statistics 

• 60 ppb threshold (both 

indices) 

• Weight of Evidence 

Analysis 

• Mid-Course simulations 

PM10/PM2.5 (annual and episodic) 

• Base statistics at speciation 

Air Quality Model Performance Use EPA recommendations for 1-hour ozone and outline for PM10 and CO. Ozone

• Mid-Course 2002 

simulation 

• Comparative relative 

reduction for UAM/CAMx/CMAQ per Peer Advisory Group Recommendation 

PM10

• Will review thresholds and ge

used for ozone performanc

• Conduct sensitivity simulation

mass, VOC/NOx ratios, emissand weekend vs. weekday), am
KRD: DRAFTModelingProtocol.doc 16 

sites 

• Weight of evidence 

analysis 

• Mid-Course simulations 

Analyzed “hot spot” grid cell emissions 

Relative Reduction Factors RRF: sites specific applied to 3-year average of the design value (PM2.5 and ozone)

Relative Reduction Factors Tested for ozone and PM10 but not applied 
KRD: DRAFTModelingProtocol.doc 17 

TABLE 3 (Continued) 

2007 AQMP Element 2003 AQMP Element Selection Process/Issues/C

Episode Selection Ozone

• 1997 August 3-7 • 1997 Seasonal: 

August 

• 2004 June 3-7 • 2004 August 4-8 • 2005 May 17-24 • 2005 July 14-19 • 2005 August 25-29 

PM10/2.5

• Annual 2005 (January 

– December) 

• 2005 October 19-25 • 2005 March 6-12 

Episode Selection Ozone

• 1997 August 4-7 

PM10/2.5

• January – December 

1995 

• Episodic: Rollback 

CO

• 1997 October 31- 

November 1 

• Meteorological episodes in

post California Fuel reform

• MATES-III meteorologica

development concurrent wdevelopment 

• Contract with Aerospace to 

observations data and MMusing (satellite ingest and 3

Initial/Boundary Conditions Ozone

• EPA recommended 

boundary conditions 

• 40 ppb ozone top profiled 

to lower layers 

PM10/2.5

• Monthly varying 

emissions generated 

Initial/Boundary Conditions Ozone 

• Use EPA 

recommended boundary conditions 

• Per SCOS97 sampling 

tested 60 ppb ozone aloft 

PM10

• Will test varying top boundary • Review alternate approaches f

boundary conditions 
KRD: DRAFTModelingProtocol.doc 18 

boundary conditions (simulate model with zero boundary conditions and let model generate boundary -- using 3-5 grid cells from model domain boundary as representative of boundary) 

Monthly varying boundary conditions based on coastal monitoring site data

1/4/2006 
KRD: DRAFTModelingProtocol.doc 19 

 3/2/2007 

2007 AQMP Schedule 

The schedule of 2007 AQMP modeling efforts is driven by the regulatory 

deadlines for SIP submittal to USEPA, which is June 15, 2007 for 8-Hour Ozone. 

Table 4 outlines the tentative schedule of events leading up to the SIP submittal. 

TABLE 4 

Tentative 2007 AQMP Schedule 

Task Due Date 

Episode Selection January 2006 

Air Quality and Meteorological Data Preparation January 2006 

Emission Inventory Preparation April 2006 

Performance Evaluation May 2006 

Control Strategy Development May 2006 

Attainment Demonstration June 2006 

Draft SIP Documents September 2006 

District Board Approval of Final SIP November 2006 

CARB Board Approval of Final SIP February 2007 

SIP Submittal to USEPA June 15, 2007 

[Add EIR Schedule, 

Alternative Modeling, 

Public Workshops] 

AQMP Modeling Technical Oversight 

The AQMD Governing Board has established several advisory groups to assist 

with technical oversight and scientific community and business involvement in air 

quality programs. The mission of the Air Quality Management Plan Advisory 

Group (AQMPAG), whose membership is appointed by the Board, is to review the 

overall aspects of a draft air quality management plan and to make 

recommendations concerning emission inventories, modeling, control measures, 

and socioeconomic impacts. Tasks of the AQMPAG, include: 

• Provide review and comments on (1) studies relevant to advancing scientific 

and technical knowledge in support of AQMP preparation; (2) emissions 

inventory development and modeling approaches; (3) the development of new 

and revised control measures, including on-and off-road mobile sources; (4) 

socioeconomic data and evaluations. 

• Foster coordinated approaches toward overall attainment strategies. 

• Assist in resolving key technical issues. 
KRD: DRAFTModelingProtocol.doc 20 

 3/2/2007 

In addition, the AQMD Governing Board has established a more focused technical 

oversight committee to review the technical aspects of the ongoing modeling 

analyses. Since the late 1980’s the AQMD has had socioeconomic and modeling 

working groups, when the Governing Board passed a resolution to form the 

Modeling Working Group (MWG) during the adoption of the 1989 AQMP 

revision. The MWG, comprised of individuals with photochemical and aerosol 

modeling expertise, provided oversight and technical consensus on AQMP 

modeling issues. In 1997, the MWG was reconstituted as the Scientific, 

Technical, and Modeling Peer Review Advisory Group (STMPRAG). The 

STMPRAG role expands upon that of the MWG and includes experts in 

socioeconomic assessment and human health, providing review of AQMD 

modeling, monitoring and related scientific issues. 

The STMPRAG assists AQMD in resolving technical issues related to air quality 

and socio-economic modeling by providing ongoing technical review and 

consensus of procedures and analyses. The objectives of the STMPRAG are as 

follows: 

• Suggest methods to gather and process meteorological, aerometric and 

emission data with a specific focus on air quality modeling. 

• Provide technical guidance to the air quality modeling efforts, with an 

emphasis on ozone and particulate matter. Some specific areas of technical 

guidance include: (1) Formulation of modeling approaches; (2) Selection and 

development of appropriate modeling techniques; and (3) Identification of 

model performance evaluation methods. 

• Review and provide comments on the AQMP modeling procedures and 

analyses. 

• Make recommendations on future modeling resource requirements (i.e., 

staffing and computational needs). 

• Recommend methods for interpretation of modeling results. 

• Provide a linkage between the air quality and socio-economic modeling 

communities, emphasizing the importance of future growth and economic 

factors on future air quality attainment demonstrations. 

The STMPRAG consists of approximately 20 members appointed by the 

Governing Board, with representatives from USEPA, CARB, Southern California 

Association of Governments (SCAG), the California Small Business Aliance 

(CSBA), Southern California Edison (SCE), Western States Petroleum 

Association (WSPA), and technical experts from universities and consultant firms. 
KRD: DRAFTModelingProtocol.doc 21 

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Finally, as progress is made and products are available, interim results will be 

shared with the interested public at appropriate times and locations. 
KRD: DRAFTModelingProtocol.doc 22 

 3/2/2007 

 MODEL SELECTION 

Meteorological Model 

Background

Air quality models require three-dimensional, meteorological inputs. The key 

parameters are winds, mixing heights, temperature, and insolation. The windfields 

describe the transport and dispersion of pollutants. Mixing heights define the 

vertical extent of pollutant mixing near the surface. Temperature and insolation 

fields influence emission rates and the rates of chemical transformation. Because 

meteorological measurements can be made only at discrete locations, 

meteorological models are required to develop the 3-dimensional fields required 

by air quality models. 

The meteorological models used to generate these three-dimensional fields are 

generally of three types: objective, diagnostic or prognostic. Objective models are 

the least sophisticated meteorological models. These models rely on interpolation 

of observations. Obtaining a reasonable field requires sufficient observations to 

accurately represent the atmosphere. This is especially true for windfields. In 

areas with complex terrain and bodies of water, such as the proposed modeling 

domain, the meteorology can be quite complex, and a successful objective analysis 

would require an extremely large number of observations. 

Diagnostic models rely both on observations and constraints based on physical 

concepts such as the conservation of mass. A diagnostic wind model can simulate 

thermally induced circulations and the effects of surface friction. One example of 

this type of model is the Diagnostic Wind Model (DWM) which is distributed by 

the USEPA. For the DWM, the user first defines an initial-guess mean wind field 

that can be representative of synoptic scale patterns. The domain mean wind is 

then adjusted for the effects of terrain. Available observations are then used to 

develop meteorological fields using objective analysis. The initial guess and the 

objective analysis are then combined using a weighting function based on distance 

from observations. A criticism of diagnostic models is that the fields produced are 

not consistent from one hour to the next. Since the processes which create the 

wind, temperature, and mixing height fields are relatively independent, these 

models are also criticized for not being thermodynamically consistent between the 

meteorological parameter fields. 

Prognostic models are the most sophisticated of the meteorological models. They 

are based on principles of atmospheric physics, i.e., conservation of mass, 

momentum, energy and moisture. As a result, they are computationally intensive. 

The use of four dimensional data assimilation (FDDA) or observational nudging – 
KRD: DRAFTModelingProtocol.doc 23 

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where observations are introduced to the model as an additional forcing term – is 

typically used in areas of complex meteorology to improve the accuracy of the 

outputs. Another approach is objective combination, in which observations are 

introduced after the model has estimated a value. Prognostic models are capable 

of explicitly incorporating many of the physical flow processes important in the 

domain. However, prognostic models have historically had problems estimating 

fine-scale flow features due to the limited resolution of datasets used for 

describing geographic features. 

Previous AQMP Applications

In the past, CARB and AQMD have utilized prognostic, diagnostic, and objective 

models to generate meteorological inputs for modeling. The National Center for 

Atmospheric Research’s prognostic, non-hydrostatic Mesoscale Model (MM5) 

was applied for modeling in support of attainment planning in the San Joaquin 

Valley. The SCAQMD also has experience with the SAIMM prognostic model. 

Diagnostic models (WIND2D, WIND3D, DWM) have been applied in the 

Sacramento area and in southern California to prepare meteorological input fields 

for the application of photochemical models in those areas. CARB and AQMD 

conducted a review of CALMET, which may be viewed as an improved version of 

the DWM and which is being distributed through the USEPA for air quality 

modeling applications. The CALMET model has an added feature that allows a 

hybrid meteorological field to be developed by merging the results from a 

prognostic model, such as the National Center for Atmospheric Research 

Mesoscale Model Version 5 (MM5), with an objective or diagnostic analysis 

characteristic of the CALMET model. This hybrid approach has the potential to 

take advantage of the prognostic capabilities of MM5 in areas of the domain 

where meteorological measurements are few, and utilizing measurements in an 

objective analysis where there are many. 

2007 AQMP Meteorological Modeling Approach

The SCOS97 field study generated a dataset with a relatively high spatial density 

of meteorological observations. While this dataset suggests that an 

objective/diagnostic model could be adequate to develop the meteorological 

parameter fields required for air quality modeling of the August SCOS97 episode, 

there are large portions of the modeling domain—such as over the ocean or the 

inland desert—where there are few observations. The approach for the 2007 

AQMP modeling will be to use the MM5 prognostic model with a 5 km grid 

resolution. The meteorological boundary conditions for MM5 are generated using 

the output from a Global Climate Model (GCM) with a relatively coarse grid of 45 

km. The MM5 prognostic model uses more accurate and complete physics than 

the diagnostic models used previously. The MM5 has relatively good replication 
KRD: DRAFTModelingProtocol.doc 24 

 3/2/2007 

of meteorological features of the Basin, such as the coastal eddies, Santa Ana 

winds, recirculation, & strong inversions. 

The recent air quality models are designed to use inputs from the prognostic 

models, such as MM5, and the use of such a model is strongly encouraged by 

USEPA. In the past, the use of MM5 meteorological fields in air quality models 

has brought limited success in the prediction of peak ozone concentrations that 

result from extreme meteorological conditions and complex distribution of 

precursor emissions. However, the prediction of ozone with MM5 meteorological 

fields on most days is comparable to the results using other models. Since the air 

quality model will be employed in more of a relative sense for the 2007 AQMP, 

with the use off relative reduction factors instead of peak concentration 

comparisons, the MM5 is an appropriate choice for the AQMP modeling. The 

premise is that the magnitude of RRF will reflect the ozone concentration resulting 

from the various meteorological episode classifications. With the use of the MM5 

meteorological model, the AQMP modeling effort will move closer to the “one 

atmosphere” air quality modeling perspective (i.e., ozone and fine particles 

simulated with the same model). The successful application of this prognostic 

model is critical for the development of multipollutant control strategies. 

Several MM5 initialization fields and data ingest options are also being explored 

for the 2007 AQMP modeling effort: 

• MM5 model initialized with the National Centers for Environmental Prediction 

(NCEP) 12 km ETA/North American Model (NAM); 

• MM5 model with Aerospace Corp 3DVAR forecast fields; 

• Weather Research and Forecasting (WRF) community model using Aerospace 

Corporation 3DVAR; 

• MM5 model with NCEP database of upper air and surface observations and the 

1degree by 1 degree Global Tropospheric Analysis 

• Above method of MM5 with NCEP database and Global Tropospheric 

Analysis and four-dimensional data assimilation (4DDA) of AQMD station 

meteorological data (this method is more mass consistent, but may be difficult 

to capture localized wind impacts (e.g., transport to San Fernando Valley); 

• Hybrid CALMET with MM5 as background field 

To supplement the MM5 meteorological modeling, the CALMET/MM5 hybrid 

meteorological model will be used to bolster the sensitivity analyses and weightof-evidence discussions. The RRF can be adjusted or supported by the air quality 

modeling results using this alternative hybrid meteorological field. In this 

approach, the parameter fields will be overlaid using a weighting scheme that is 

based on the proximity to meteorological observations. The resultant fields 
KRD: DRAFTModelingProtocol.doc 25 

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benefit from the capabilities of the prognostic model in those areas of the 

modeling domain with few observations (such as offshore, in complex terrain, and 

in the desert areas), and benefit from the objective analysis component of the 

diagnostic model to force the fields to agree with observations. To develop the 

hybrid fields, the fields developed using CALMET and MM5 will need to be 

mapped into common horizontal and vertical coordinate domains. The CALMET 

model code is structured to facilitate this mapping. 

Air Quality Model 

Background

The air quality model employed for previous AQMP efforts, the Urban Airshed 

Model (UAM-IV (USEPA 1990), is widely acknowledged to have characteristics 

which limit its utility when applied to large modeling domains or to domains that 

are not geographically uniform. In addition, much of the science in the model is 

outdated, and both the USEPA and CARB are no longer recommending that 

model for most analyses. Several photochemical models have been developed to 

improve upon the UAM-IV. Among those models, CAMx and CMAQ were 

widely accepted models as the state of the science models that include the most 

up-to-date chemical mechanisms, physics and the efficient numerical algorithms. 

The following summarizes the current models. 

• CALGRID 

The CALGRID model (Yamartino et. al, 1989) was developed for CARB in 

the late 1980's. The model has been applied by various air pollution agencies 

around the world. It is modular to allow the user to substitute various types of 

wind fields and chemical mechanisms. CALGRID incorporates refined 

treatments of numerical advection, vertical transport and dispersion, and dry 

deposition. The model can be exercised with either the Carbon Bond IV (CBIV) or SAPRC chemical mechanisms, and contains highly efficient chemical 

integration routines. The vertical structure of the atmosphere can be optionally 

defined relative to a mixing height field, similar to the UAM, or can be based 

on fixed layer heights and a derived mixing height. 

• Models-3 

Models-3 (USEPA, 1998a) is a flexible software system designed for 

applications ranging from regulatory and policy analysis to understanding the 

complex interactions of atmospheric chemistry and physics. The Models-3 

system is a framework that allows the user to go from developing model inputs 

to visualizing results all in one package. At the heart of the current version of 

Models-3 is the Community Multi-scale Air Quality (CMAQ) Model. The 

capabilities of CMAQ include urban to regional scale air quality simulation of 
KRD: DRAFTModelingProtocol.doc 26 

 3/2/2007 

ozone, acid deposition, visibility and fine particles. CMAQ is a modular 

system capable of using output from the MM5 prognostic meteorological 

model, along with the CB-IV, RADM-2, or SAPRC-99 chemical mechanisms. 

The CMAQ model also includes a plume-in-grid module, vertical and 

horizontal growth due to turbulence and shear, a choice of advection schemes 

and a cloud- module to simulate precipitating and non-precipitating clouds. 

Since the Models-3 system is relatively new, some implementation and 

application problems are likely. 

• SARMAP Air Quality Model (SAQM) 

SAQM (Chang, et. al, 1997) is a three-dimensional non-hydrostatic model 

based upon the Regional Acid Deposition Model (RADM) (Chang et. al 1987, 

1990). However, SAQM includes a number of improvements over RADM, 

including: a fixed vertical coordinate system that is compatible with MM5; a 

horizontal coordinate system defined in a Lambert-Conformal projection that 

accounts for curvature of the Earth; a mass conservation module for 

compatibility with non-hydrostatic meteorological inputs; the Bott advection 

scheme (Bott 1989a, 1989b) to reduce numerical diffusion and increase 

numerical accuracy; two-way nesting, and the capability to use either the CBIV or SAPRC chemical mechanisms. A version of SAQM with plume-in-grid 

treatment is also available. 

• Urban Airshed Model-Flexible Chemical Mechanism (UAM-FCM) 

The UAM-FCM (Kumar et. al, 1995) is an alternate version of the UAM-IV 

that has been enhanced to allow the flexibility to incorporate any Carbon 

Bond- or SAPRC-type chemical mechanism. The FCM allows incorporation 

of reaction-specific photolysis rates. In addition, the UAM-FCM has a 

generalized methodology to solve the set of differential equations that is 

mechanism independent. However, the meteorological dispersion algorithms 

are the same as in UAM-IV. 

• Urban Airshed Model-Variable (UAM-V) 

The UAM-V (Systems Applications International, 1996) is an updated version 

of the Urban Airshed Model (UAM-IV) which incorporates many 

state-of-the-art enhancements in chemical mechanisms, meteorological models 

and the representation of emissions. Perhaps the most significant additions are: 

an updated CB-IV mechanism to include aqueous phase chemistry; 

plume-in-grid capabilities; an improved dry deposition algorithm; and an 

improved plume rise algorithm. Other enhancements over UAM-IV include 

allowing the user a fixed vertical structure as opposed to one that is relative to 

the diffusion break, the ability to use three dimensional inputs from prognostic 

models and two-way grid nesting. However, the present non-public domain 

status of UAM-V may preclude regulatory usage. The model developers have 
KRD: DRAFTModelingProtocol.doc 27 

 3/2/2007 

indicated that the model could be made available for any party to review if the 

party agrees that the use of the model would be solely for the review of the 

AQMP. 

• Comprehensive Air-Quality Model with Extensions (CAMx) 

CAMx (Environ, 1997) contains a number of advanced features, including grid 

nesting, sub-grid scale plume-in-grid simulation, alternative numerical 

advection solvers and the ability to use alternative chemical mechanisms. In 

addition it has the ability to tag emissions so that at the end of the simulation 

one can determine the sources of emissions impacting a particular receptor. 

Since CAMx is a relatively new model, thus there is a relatively short history 

of experience applying the model. 

2007 AQMP Air Quality Modeling Approach

CAMx will be the primary air quality model for the attainment demonstration. 

This dispersion platform integrates well with numerical meteorological model 

output and it will be run using both the prognostic (MM5) and hybrid 

(CALMET/MM5) meteorological fields. The application of the MM5 and CAMx 

modeling system for both ozone and particulate matter simulation will bring 

AQMD closer to the “one atmosphere” modeling concept, where ozone and 

particulates are simulated in the same model. CMAQ model may also be run as a 

supporting model in the sensitivity analysis discussion. 

The ozone air quality models will be run using the SAPRC (Carter 1999, 2001) 

chemical mechanism, based on chemical reactivity scales. At its meeting on 

October 8, 1999, CARB’s Reactivity Scientific Advisory Committee (chaired by 

Dr. John Seinfeld, with participation by other members Dr. Roger Atkinson, Dr. 

Jack Calvert, Dr. Harvey Jeffries, Dr. Jana Milford, and Dr. Armistead Russell) 

discussed a peer review of the SAPRC-99 mechanism conducted by Dr. William 

Stockwell. Members of the committee agreed that the peer review was excellent, 

that SAPRC-99 was a state-of-the-art chemical mechanism, and they approved the 

peer review. The Committee then unanimously recommended that SAPRC-99, as 

the most up-to-date mechanism available, be used for SIP modeling. 

The particulate matter air quality model will use CAMx with the AERO-LT/CBIV chemical mechanism and the enhanced two-section CFI aerosol scheme with 

CV-IV. The AQMD version of the AERO-LT chemistry and the enhanced 

version of the CAMx CFI scheme have been installed in the latest CAMx code and 

comparative analyses will be presented. Advisory group recommendations have 

been to move toward a state-of-the-art, mass-consistent model and chemistry. 

This system will integrate well with numerical weather model output and with also 

use the MM5 model for meteorological fields. 
KRD: DRAFTModelingProtocol.doc 28 

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KRD: DRAFTModelingProtocol.doc 29 

 3/2/2007 

MODELING DOMAIN 

Meteorological Modeling Domain 

Nested domains of 15 km and 5 km are defined within MM5 to simulate 

meteorological fields for the fine grid scale of the modeling domain. The 

modeling domain for MM5 is defined in a Lambert-Conformal projection with 

two parallels to account for curvature of the Earth within the modeling domain 

over such a large region. Figure 1 shows the nested MM5 domains. Figure 2 

shows the finest scale (interior) MM5 domain, covering most of southern 

California. The vertical structure of MM5 is defined in a terrain-following, 

“sigma” coordinate system based upon a normalized pressure index. The 30 

vertical layers defined for MM5 to approximately 15,000 m above ground level 

(AGL) can be transformed to fit the requirements of any air quality model. The 

MM5 meteorological fields are converted from Lambert-Conformal projection to 

UTM coordinates for input into the air quality models. 
KRD: DRAFTModelingProtocol.doc 30 

 3/2/2007 

FIGURE 1 

Nested MM5 Domains 

The horizontal grid resolution of the outermost domain is 45 km, for the middle domain 

is 15 km, and for the fine scale domain is 5 km. 
KRD: DRAFTModelingProtocol.doc 31 

 3/2/2007 

-10

-10

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000

1000 1000

1000

FIGURE 2 

The Fine-Scale (5 km) MM5 Domain. 

Ozone Modeling Domain 

The proposed ozone regional modeling domain is that previously developed for 

the modeling of the SCOS97 field study episodes, encompassing a 600 km wide 

by 160 km area, as shown in Figure 3. Specifically, the UTM Zone 11 coordinates 

of the domain are 150-700 km UTM East and 3580-3950 km UTM North. This 

corresponds to 100 by 74 grid cells at 5 km grid spacing. The vertical modeling 

domain will extend to a height of approximately 5,000 m AGL for a more 

complete representation of atmospheric processes. This will contain observed 

high ozone concentrations aloft and allow three-dimensional wind flow patterns 

near elevated terrain features to be represented, providing accurate representation 

of pollutant transport and recirculation. This same domain will be used for all of 

the ozone episodes. 
KRD: DRAFTModelingProtocol.doc 32 

 3/2/2007 

San Luis

Obispo Co.

Santa

Barbara Co.

Kern Co.

Ventura

Co.

Orange

 Co.

Imperial

Co.

Los

Angeles Co.

Riverside Co.

San Diego

Co.

San

Bernardino

Co.

Northern Mexico

FIGURE 3 

2007 AQMP Ozone Modeling Domain 

The ozone modeling domain encompasses much of southern California, as 

follows: all of the South Coast Air Basin (including Orange County and the nondesert portions of Los Angeles, Riverside and San Bernardino Counties), the 

Coachella Valley and San Diego County; the California-Mexico border regions; 

most of Imperial County; most of the inland deserts; and almost all of the South 

Central Coast Air Basin (excepting a small piece of San Luis Obispo County). 

This large domain minimizes the influence of boundary conditions on simulation 

results and allows the effects of recirculation and interbasin transport to be better 

represented by the meteorological and photochemical model simulations. It also 

eliminates the need to define boundary concentrations between the air basins and it 

extends far enough offshore to contain wind flow patterns conducive to over-water 

recirculation. 

PM Modeling Domain 

The modeling domain for the particulate matter modeling will be smaller than the 

ozone domain, encompassing a 325 km wide by 200 km area, as shown in Figure 

4. This corresponds to 65 by 40 grid cells at 5 km grid resolution. The reduced 

domain is due in part to the computational resource and time constraints of 

modeling the full 2005 year for annual PM. In addition, PM SIP modeling is not 
KRD: DRAFTModelingProtocol.doc 33 

 3/2/2007 

needed in the southernmost counties of California and adequate ammonia 

emissions inventories are not available from many areas surrounding the South 

Coast Air Basin. 

FIGURE 4 

2007 AQMP PM Modeling Domain, inside the Ozone Modeling Domain 
KRD: DRAFTModelingProtocol.doc 34 

 3/2/2007 

 HORIZONTAL AND VERTICAL GRID RESOLUTION

Horizontal Grid Resolution 

The horizontal grid resolution plays an important role in the modeling process. 

Large grid resolution tends to smooth emission gradients and meteorological 

inputs, which in turn leads to a smoothing of the resulting concentration fields. In 

general, the resolution should be sufficiently small to pick up emission gradients 

in urban areas and be consistent with the major terrain features which may affect 

the air flow. In the past, photochemical models have been applied in California 

with horizontal grid resolutions ranging from 2 x 2 km to 8 x 8 km. The specific 

grid resolution chosen was primarily dependent on the size of the modeling 

domain, computer resources available and the time and money available to carry 

out the simulations. In effect the final resolution was a compromise between the 

accuracy desired and the cost. However, the current generation of high-speed 

computers has minimized cost and resource constraints. 

For the year 2007 AQMP ozone, particulate and meteorological modeling, a 

horizontal grid resolution of 5 km is proposed to be used for the air quality 

modeling. No grid nesting is anticipated. This resolution is consistent with the 

grid resolution used in earlier photochemical modeling studies for the South Coast 

Air Basin and for San Diego. In addition, this will reduce resources needed to 

create gridded emissions, which are based on 5 km grid cells. For the proposed 

ozone modeling domain, use of a 5 km resolution results in a modeling grid with 

110 cells in the east-west direction and 74 cells in the north-south direction. The 

Universal Transverse Mercator (UTM) coordinate system is adopted as the 

primary coordinate system for the air quality modeling. There are variations in 

Lambert-Conformal map projection systems, such as the Normal Sphere (6471 km 

radius) used in MM5, the North American 1927 Clerk 1866 used in CARB’s 

emissions development system, and the Arakawa-C or Arakawa-B variable 

configuration which assign meteorological parameters at grid points or the center 

of the grid. The selection of UTM simplifies translation from one grid system to 

another and the gridded emissions inventory is based on a UTM coordinate 

system. 

Vertical Resolution 

As with the selection of the horizontal grid resolution, the vertical resolution 

defined for air quality modeling domains has been limited by computational 

resources. In addition, available aloft meteorological and air quality databases 

were not sufficient to characterize conditions aloft. As a result, simulation results 

have been limited by a relatively small number of vertical layers within the 
KRD: DRAFTModelingProtocol.doc 35 

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atmospheric boundary layer, resulting in poor representation of the stratification of 

the atmosphere. The ability to better simulate the vertical structure of the 

atmosphere has improved significantly due to the increased availability of 

measurements aloft (including radar wind profilers and aircraft measurements), the 

emergence of higher-speed computers, and our increased experience with 

diagnostic and prognostic meteorological models. 

Meteorological Modeling

For the terrain-following MM5 model, the proposed vertical layer consists of 34 

layers to a height of over 15,000 meters AGL, as shown in Table 5. For input into 

the air quality model, the 34 layers are reduced to match the vertical resolution of 

the ozone or particulate matter air quality model. 
KRD: DRAFTModelingProtocol.doc 36 

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TABLE 5 

Vertical Structure for the MM5 Meteorological Model 

Layer # Sigma P0 (Pa) Height (m)* Depth (m)* 

34 0.000 10000 15674 2004 

33 0.050 14500 13670 1585 

32 0.100 19000 12085 1321 

31 0.150 23500 10764 1139 

30 0.200 28000 9625 1004 

29 0.250 32500 8621 900 

28 0.300 37000 7720 817 

27 0.400 41500 6903 750 

26 0.300 46000 6163 693 

25 0.450 50500 6461 645 

24 0.500 55000 4816 604 

23 0.550 59500 4212 568 

22 0.600 64000 3644 536 

21 0.650 68500 3108 508 

20 0.700 73000 2600 388 

19 0.740 76600 2212 282 

18 0.770 79300 1930 274 

17 0.800 82000 1657 178 

16 0.820 83800 1478 175 

15 0.840 85600 1303 172 

14 0.860 87400 1130 169 

13 0.880 89200 961 167 

12 0.900 91000 794 82 

11 0.910 91900 712 82 

10 0.920 92800 631 81 

9 0.930 93700 550 80 

8 0.940 94600 469 80 

7 0.950 95500 389 79 

6 0.960 96400 310 78 

5 0.970 97300 232 78 

4 0.980 98200 154 39 

3 0.985 98650 115 39 

2 0.990 99100 77 38 

1 0.995 99550 38 38 

0 1.000 100000 0 0 

* The vertical coordinate system for MM5 is based on a normalized pressure 

scale. The above layer heights were calculated from sea level using standard 

conditions. Layer heights are lower relative to ground level as terrain height 

increases.
KRD: DRAFTModelingProtocol.doc 37 

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Air Quality Modeling

For sufficient vertical representation of the atmosphere, 16 vertical layers will be 

used for the CAMx ozone modeling, to a top height of nearly 5000 m AGL. Five 

of the layers will be below 500 m AGL (the nominal height of the summer 

afternoon mixing height within the Los Angeles coastal plain). The computational 

resources required for the annual particulate matter modeling necessitate a 

reduction in the number of layers used in the CAMx model for particulates. For 

this, eight vertical layers will used to a top height of approximately 5000 m AGL. 

The proposed vertical structure for the ozone and PM models are shown in Table 

6, along side of the MM5 vertical structure. 
KRD: DRAFTModelingProtocol.doc 38 

 3/2/2007 

TABLE 6 

Vertical Structures for the CAMx Ozone and PM Simulations 

with Corresponding MM5 Meteorological Model Layers 

MM5 Vertical Layer Heights 

(34) 

Ozone Model Layers 

(16) 

PM Model Layers 

(8) 

No. Sigma Height 

(m 

AGL) 

Depth 

(m) 

Height 

(m AGL)

Depth 

(m) 

Height 

(m 

AGL) 

Depth 

(m) 

... ... ... ... 

24 0.500 4816 604 4816 1172 4816 2216 

23 0.550 4212 568 

22 0.600 3644 536 3644 1044 

21 0.650 3108 508 

20 0.700 2600 388 2600 670 2600 670 

19 0.740 2212 282 

18 0.770 1930 274 1930 274 1930 627 

17 0.800 1657 178 1657 178 

16 0.820 1478 175 1478 175 

15 0.840 1303 172 1303 172 1303 508 

14 0.860 1130 169 1130 169 

13 0.880 961 167 961 167 

12 0.900 794 82 794 164 794 325 

11 0.910 712 82 

10 0.920 631 81 631 161 

9 0.930 550 80 

8 0.940 469 80 469 159 469 315 

7 0.950 389 79 

6 0.960 310 78 310 156 

5 0.970 232 78 

4 0.980 154 39 154 78 154 116 

3 0.985 115 39 

2 0.990 77 38 77 38 

1 0.995 38 38 38 38 38 38 

0 1.000 0 0 
KRD: DRAFTModelingProtocol.doc 39 

 3/2/2007 

EPISODE SELECTION 

Ozone Episodes 

Five ozone episodes were simulated for the 2003 AQMP: June 24-25, 1987; 

August 27-28, 1987; August 3-7, 1997; September 26-29, 1997; and July 13-18, 

1998. To maintain continuity with the last plan submittal, the model performance 

for the August 1997 episode will be reevaluated using updated emission data and 

modeling protocols. Five new recent episode periods from 2004 and 2005 will 

evaluated to better represent current conditions, including those associated with 

the reformulation of gasoline in the past several years. The six episodes are 

outlined in Table 7 and briefly described below. 
KRD: DRAFTModelingProtocol.doc 40 

 3/2/2007 

TABLE 7 

Summary of Ozone Episodes to be Simulated for the 2007 AQMP 

Episode 

Peak 1-Hr. 

Ozone 

Peak 8-Hr. 

Ozone Notes 

August 3-7, 1997 

(Sunday – Thursday) 

0.187 ppm 

Tuesday, August 5

 at Rubidoux 

0.117 ppm 

Tue.& Wed., 

August 5 & 6 

SCOS97 intensive 

measurement 

episode. Primary 

modeling episode 

from 2003 AQMP. 

Before California 

fuel reformulation. 

June 3-7, 2004 

(Thursday – Monday) 

0.163 ppm 

Saturday, June 5 

 at Crestline 

0.145 ppm 

Saturday, June 5 

 at Crestline 

2004 Basin 

maximum 1-hour 

and 8-hour ozone 

concentrations. 

August 4-8, 2004 

(Wednesday – Sunday) 

0.156 ppm 

Saturday, August 7

 at Banning 

0.124 ppm 

Saturday, August 7

 at Crestline 

May 17 -24, 2005 

(Tuesday – Tuesday) 

0.164 ppm 

Sunday, May 22 

 at Santa Clarita 

0.145 ppm 

Sunday, May 22 

 at Crestline 

2005 Basin 

maximum 8-hour 

ozone concentration. 

July 14-19, 2005 

(Thursday – Tuesday) 

0.173 ppm 

Saturday, July 16 

at Santa Clarita 

0.143ppm 

Friday, July 15 

 at Crestline 

August 25-29, 2005 

(Thursday – Monday) 

0.182 ppm 

Saturday, Aug. 27

 at Crestline 

0.130 ppm 

Saturday, Aug. 27 

 at Crestline 

2005 Basin 

maximum 1-hour 

ozone concentration. 
KRD: DRAFTModelingProtocol.doc 41 

 3/2/2007 

August 3-7, 1997 (Sunday – Thursday)

The episode period of August 3-7, 1997 was selected to provide continuity with 

the previous AQMP modeling effort. This episode was the primary modeling 

episode for the 2003 AQMP and it is representative of the most extreme 

meteorological conditions conducive to the highest ozone concentrations in the 

Basin. Unlike the more recent ozone episodes, the peak concentrations during this 

period did not occur on a weekend. Model input data supporting the August 1997 

simulations were derived from intensive field monitoring that occurred during the 

1997 Southern California Ozone Study (SCOS97). The SCOS97 study benefited 

from state-of-the art upper air wind and temperature monitoring and recently 

developed advances in particulate and oxides of nitrogen sampling technology. 

The August 1997 episode included the peak ozone concentrations measured in the 

South Coast Air Basin during SCOS97 that were not associated with an 

exceptional event. A peak 1-hour ozone concentration of 0.187 ppm was 

measured at the AQMD Metropolitan Riverside County (Rubidoux) air monitoring 

station on Tuesday, August 5 and peak 8-hour concentrations of 0.117 ppm were 

measured on Tuesday, August 5 and Wednesday, August 6. High ozone 

concentrations were also observed in the Mojave Desert Air Basin (1-hour peak of 

0.140 ppm) and in Ventura County (1-hour peak of 0.130 ppm, 8-hour peak of 

0.115 ppm). 

The August 1997 meteorological episode began on Sunday, August 3 under a 

ridge of high pressure aloft with 500 mb heights measured in excess of 5900 m 

each day. Weak onshore flow gave way to stagnant winds through the middle of 

the episode. Winds observed on August 5th, illustrate a classic “south route” 

transport regime that has been identified as characteristic of past severe Basin 

ozone meteorological episodes. Beginning late on August 6 and continuing into 

August 7, a well-defined coastal eddy developed that contributed to southerly flow 

and transport northward toward Ventura County. Peak inland afternoon 

temperatures crested over 100 degrees Fahrenheit on each day during the episode 

and downtown Los Angeles consistently reached the mid to upper 90’s. The 

excessive regional surface temperatures and stagnant flow also contributed to a 

massive wildfire in the mountainous portions of eastern Ventura and southeastern 

Santa Barbara counties during the later part of the episode.

Ozone air quality reached the California Ozone Health Advisory level (0.150 ppm 

or higher) on two day during the episode at Redlands, San Bernardino, Rubidoux 

and Mira Loma. The peak observed value of 0.187 ppm occurred on the August 5 

at Rubidoux. Eleven locations exceeded the federal 1-hour ozone standard. Areas 

such as Azusa, Pasadena, Glendora and Santa Clarita that routinely experience 

higher values of ozone during episodic conditions were spared the brunt of the 
KRD: DRAFTModelingProtocol.doc 42 

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impact due to excessive daytime heating that deepened the mixed layer. Overall, 

The peak concentrations in the Basin reached 0.140 ppm on the August 4 in the 

Central San Bernardino Mountains, 0.187 ppm at Rubidoux on August 5, 0.170 

ppm and 0.150 ppm on August 6 and 7, respectively, in the Central San 

Bernardino Mountains. On August 6, ozone transport was observed through the 

Newhall pass to the Santa Clarita area and concentrations rose in Reseda and 

Ventura County as the coastal eddy developed.

June 3-7, 2004 (Thursday – Monday)

• Peak 1-hour Ozone: 0.163 ppm on Saturday, June 5 at Crestline 

(2004 Basin max 1-hour ozone) 

• Peak 8-hour Ozone: 0.145 ppm on Saturday, June 5 at Crestline 

(2004 Basin max 8-hour ozone) 

August 4-8, 2004 (Wednesday – Sunday)

• Peak 1-hour Ozone: 0.156 ppm on Saturday, August 7 at Banning 

• Peak 8-hour Ozone: 0.124 ppm on Saturday, August 7 at Crestline 

May 17-24, 2005 (Tuesday – Tuesday)

• Peak 1-hour Ozone: 0.164 ppm on Sunday, May 22 at Santa Clarita 

• Peak 8-hour Ozone: 0.145 ppm on Sunday, May 22 at Crestline 

(2005 Basin max 8-hour ozone) 

July 14-19, 2005 (Thursday – Tuesday)

• Peak 1-hour Ozone: 0.173 ppm on Saturday, July 16 at Santa Clarita 

• Peak 8-hour Ozone: 0.143 ppm on Friday, July 15 at Crestline 

The morning of July 13, 2005 had a low, strong temperature inversion layer in the 

Basin, which continued for several days, and hot weather except at the immediate 

coast. Skies were mostly clear, except for low clouds and fog offshore an at the 

coastline for most of the day. Ozone levels were starting to increase in the inland 

valley areas. The inland valley areas remained hot on July 14 while the coast 

remained much cooler with coastal low clouds and fog. On July 15, high 

pressures aloft, centered over the western U.S. deserts, helped to keep inland 

temperatures hot. Excessive heat warnings were in effect for many desert areas. 

The marine layer deepened a little with increased onshore flow, bringing night and 

morning low clouds and fog into the coastal valleys and transporting ozone and 

ozone precursors towards the Inland Empire with a 8-hour ozone peaking at 

Crestline (0.143 ppm). Skies in the Basin were mostly sunny with haze. On July 

16, the hot inland temperatures continued while coastal low cloud and fog in the 

morning clearing in the afternoon. .On July 17, the strong inversion layer 

continued along with the hot temperatures in the inland valley areas. Only the 
KRD: DRAFTModelingProtocol.doc 43 

 3/2/2007 

immediate coastal strip will escaped the hot weather due to low clouds and fog 

along the coastline and offshore. With strong high pressure aloft over the west 

coast, temperature will remain hot on July 18 and through the week with an 

excessive heat advisory and record temperature possible in some areas on 

Monday, July 18. A lower temperature inversion confined morning low clouds 

and fog to the coast, with hazy sunshine elsewhere. Little change occurred on July 

19 as inland heating likely caused the inversion to break in the afternoon inland. 

August 25-29, 2005 (Thursday – Monday)

• Peak 1-hour Ozone: 0.182 ppm on Saturday, August 27 at Crestline 

(2005 Basin max 1-hour ozone) 

• Peak 8-hour Ozone: 0.130 ppm on Friday, August 27 at Crestline 

Possible Seasonal Ozone Episode: Summer 1997

Ozone Episode Statistical Ranking 

For the 2003 AQMP ozone attainment demonstration a statistical model was 

developed to characterize the ozone meteorological episodes selected for regional 

modeling evaluation. The statistical model related degree of ozone meteorological 

episode severity relative to the long term trend (1981-2002). Multi-variate 

regression was conducted using the Basin 1-hour average maximum ozone 

concentration and surface and upper air meteorological data for 1996 to generate 

an ozone prediction equation. This equation was applied to the air quality and 

meteorological data for the 22-year period to predict Basin daily maximum ozone 

and establish a daily ranking. The multiple linear regression analysis is discussed 

in Appendix V of the 2003 AQMP. 

The statistical evaluation used in the 2003 AQMP used the daily maximum 1-hour 

ozone as the dependent variable to characterize the meteorological episodes. The 

meteorological conditions that give rise to higher 8-hour average concentrations 

are essentially a subset of those giving rise to peak 1-hour concentration. CART 

pattern recognition analysis (Cassmassi, 1998) demonstrated that the 

meteorological conditions that lead to high 1-hour average concentrations were the 

same as those for peak 8-hour concentrations. In addition, station specific 

correlations between maximum 1- and 8-hour average ozone concentrations 

generally explain more than 95 percent of the variance in the data. Given the 

consistency between the meteorological profiles contributing to both maximum 1- 
KRD: DRAFTModelingProtocol.doc 44 

 3/2/2007 

and 8-hour average concentrations, it was assumed that the algorithm used to rank 

episodes in the 2003 AQMP would be applicable for ranking the 8-hour episodes. 

The 1997 episode ranking was taken directly from the 2003 AQMP. The 

statistical characterization was then extended to the 2004 and 2005 candidate 

episodes and their predicted daily maximum concentrations were compared to the 

22-year distribution to determine relative rank. Table 6 summarizes the analysis. 

Eleven of the 13 days ranked above the 95th percentile in episode severity with 

only August 6, 2004 failing to rank in the 90th percentile. The daily maximum 8-

hour ozone averages were averaged by episode and compared to the 4th highest 

ozone value in the Basin (99th percentile) for each of the modeling years. The 

1997 episode was a match for the annual design value while the 2004 and 2005 

episodes bracketed the annual design values, each depicting episodes that were 

more or less severe than the design. The overall distribution listed in Table 8 may 

be enhanced at a later date if a seasonal modeling application is determined to be 

viable. 
KRD: DRAFTModelingProtocol.doc 45 

 3/2/2007 

TABLE 8 

Ozone Episode Characterization 

Ranking Applied to Historical 22-Year Period (1981-2002) 

Episode Rank Percentile 8-Hour Max 

Ozone 

(PPB) 

Episode 

Average 

(PPB) 

Annual 4th

Highest 

Station 

(PPB) 

8/5/97 198 98 124 

8/6/97 203 97 130 

127 127 

San 

Bernardino 

6/5/04 83 99 148 

6/6/04 524 93 127 

138 

8/6/04 1009 87 94 

8/7/04 331 96 127 

111 

116 

Crestline 

5/21/05 389 95 112 

5/22/05 50 99 145 

129 

7/16/05 22 99 141 

7/17/05 15 99 141 

7/18/05 73 99 127 

136 

8/27/05 160 98 130 

8/28/05 138 98 121 

126 

125 

Crestline 

PM Episodes 

Annual particulate matter modeling will cover the entire year of 2005, taking 

advantage of additional speciated particulate measurements and meteorological 

data archived in association with the Multiple Air Toxics Exposure Study III 

(MATES-III) in the South Coast Air Basin. In addition, two PM2.5 episodes in 

2005 will be modeled for 24-hour NAAQS compliance: October 19-25 and March 

6-12, 2005. These two days were chosen since they were the highest PM2.5 

episodes in 2005 that were not influenced by exceptional events. Both episode 

periods exhibited multiple-day buildups in the Beta Attenuation Monitor (BAM) 

continuous PM2.5 monitoring and affected multiple stations. Only July 5 had a 

higher PM2.5 concentration, but it was associated with fireworks on the night of 

July 4. Table 9 shows the days in 2005 with the highest Size Selective Inlet (SSI) 

sampler PM2.5 concentrations and the associated 24-hour BAM PM2.5 and SSI 

PM10 concentrations. 
KRD: DRAFTModelingProtocol.doc 46 

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TABLE 9 

Highest 24-Hour Averaged SSI PM2.5 Concentration in 2005 

with BAM PM2.5 and SSI PM10 Concentrations 

Date Station 

SSI PM2.5

(μg/m3) 

BAM PM2.5

(μg/m3) 

SSI PM10 

(μg/m3) 

July 5, 2005 Azusa 132.7 

October 22, 2005 San Bernardino 106.3 

October 22, 2005 Rubidoux 98.7 120.6 123/124 

October 22, 2005 Fontana 96.8 

October 23, 2005 Rubidoux 95.9 117.9 

October 22, 2005 Riverside 95.0 

October 22, 2005 Ontario 87.8 

October 21, 2005 Rubidoux 82.1 98.5 

July 5, 2005 Rubidoux 79.9 102.0 

March 10, 2005 Downtown LA 73.7 88.2 

March 11, 2005 Downtown LA 67.6 84.7 70 

Annual PM: January 1 – December 31, 2005

• AQMP database development concurrent with MATES-III 

• Peak Annual Average PM2.5: 23.3 μg/m3

 at Rubidoux 

• Peak Annual Average PM10: 52.2 μg/m3 at Rubidoux 

Episodic PM10/2.5: October 19-25, 2005 & March 6-12, 2005

• Peak 24-Hour PM2.5 was 132.7 μg/m3 at Azusa on July 5, 2005 

(due to Independence Day fireworks) 

• Second Peak 24-Hour Average PM2.5: 106.3 μg/m3 at San Bernardino on October 

22, 2005 

• Rubidoux exceeded the 24-hour PM2.5 standard on the most days in 2005 (8 days) 

• Peak 24-Hour Average PM10: 131 μg/m3

 at South Long Beach on May 4, 2005 

• Second Peak 24-Hour Average PM10: 123 μg/m3 at Rubidoux on October 22, 2005 

• No 24-Hour NAAQS violations were measured in the Basin in 2005 
KRD: DRAFTModelingProtocol.doc 47 

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INITIAL AND BOUNDARY CONDITIONS 

Previous ozone modeling results in southern California proved sensitive to initial 

and boundary concentrations of air pollutants. This reflected the physical 

processes of recirculation of pollutants within southern California and the 

transport of pollutants from one air basin to another. However, because of the 

three-dimensional nature of transport and recirculation, it is difficult to take field 

study measurements that are adequate to determine boundary conditions. 

Ozonesonde measurements made during SCOS97 have shown high concentrations 

of ozone at heights above 3,000 m AGL. The modeling domain developed for the 

SCOS97 episodes, which will be used for the 2007 AQMP, has been expanded 

both horizontally and vertically from that of earlier studies in an attempt to 

minimize the influence of boundary conditions. With the boundaries extending 

horizontally well into the desert areas an over the ocean and vertically to 5000 m, 

the effects of recirculation and interbasin transport will be better represented by 

the meteorological and photochemical model simulations. 

The sensitivity of the model simulations to initial and boundary conditions will be 

extensively examined with sensitivity analyses. Chemical species concentration 

measurements, where available from the SCOS97 field study archive and the 

PAMS measurements, will be used to check the initial and boundary conditions 

for reasonableness. For the large areas of the study domain in which there are few 

such measurements, initial and boundary conditions are often assigned 

“background” values based on the minimum concentrations measured from 

monitoring sites where measurements are available. The use of larger-domain air 

quality models to provide the initial, top and lateral boundary concentrations will 

also be explored. Speciated gridded pollutant and precursor profiles from the 36 

km grid CMAQ model used for the WRAP visibility modeling is currently being 

evaluated to provide the initial and boundary conditions. The boundary profiles 

will vary with time and height level, as well as location, while the top boundary 

concentration will vary by time and grid location. 

Initial Conditions 

Initial conditions in the air quality models define the spatial distribution of 

chemical species concentrations throughout the 3-dimensional modeling domain at 

the time at which the air quality model simulation begins. There are two 

limitations inherent in defining initial conditions. The first is that chemical 

species concentrations are only measured at discrete locations and, for some 

species, for discrete time periods. In particular, observed VOC data is sparse 

although some PAMS monitoring stations data are available. Therefore, observed 

concentrations must be extrapolated to estimate concentrations throughout the 
KRD: DRAFTModelingProtocol.doc 48 

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modeling domain. The second limitation is that observed chemical species 

concentrations may not represent chemical equilibrium, especially since not all 

important chemical species are measured explicitly. 

To minimize the importance of initial conditions on air quality model simulation 

results, the simulation is frequently started at some time interval before the period 

of interest. Historically, this “spin-up” time interval has ranged between 8 and 72 

hours. For the 2007 AQMP episodes, the modeling period starts early in the 

morning (typically 0000 PDT) of the day before the first day of interest for spinup. This allows a full diurnal cycle of sunlight for air quality model to reach 

chemical equilibrium. Since most of the modeling episodes encompass several 

days, the day with the worst air quality is typically well into the simulation. 

Boundary Conditions 

The top and lateral boundary conditions in the air quality models are the chemical 

species concentrations on the study domain boundaries and represent the 

concentrations for the air mass moving into the modeling domain. Unlike initial 

conditions which need to be defined only for the beginning of the simulation, 

boundary conditions must be defined for each hour of an air quality model 

simulation on the 2-dimensional, vertical planes on each of the horizontal 

boundaries of the domain and at the top of the modeling domain. 

Ideally, the modeling domain boundaries are placed so remotely that simulation 

results are insensitive to boundary conditions. Even for the large SCOS97 

modeling domain, the influence of boundary conditions on the simulation results 

may be problematic. Beyond the northern boundary, emissions from central 

California could have an impact on the domain. To the south, emissions from 

Mexico could have an impact. The western boundary is over the Pacific Ocean, 

where recirculation may be an issue. 

Also, the determination of vertical profiles of chemical species is problematic. 

During SCOS97, ozone concentrations aloft were measured by launching balloonborne ozonesondes. The measurements indicated that there are layers of high 

ozone ranging 60 to 80 ppb at near 3000 m. Prescribing a 60 ppb ozone 

concentration aloft in the model would contribute to high ozone concentrations at 

the surface due to advection or vertical diffusion. Ideally boundary conditions 

would be determined from measured chemical species concentrations, but these 

are rarely available for the most of the episode days or in all locations needed. 

For the 2007 AQMP, AQMD proposes to use relatively clean initial and boundary 

conditions, based on the results of a larger domain model, the WRAP CMAQ 

visibility simulations. The SAPRC species for the initial and boundary conditions 
KRD: DRAFTModelingProtocol.doc 49 

 3/2/2007 

are shown in Table 10 for the ozone modeling. The use of relatively clean 

boundary conditions could significantly impact the predicted peak ozone 

concentration which results in poor model performance for ozone peak prediction. 

However, the use of clean boundary condition minimizes the uncertainty in futureyear model predictions. The calculated RRF should only reflect the impact of 

anthropogenic emissions reductions. Also, as the future year air quality becomes 

close to background concentrations, the treatment of boundary conditions may be 

problematic, particularly in 8-hour ozone attainment demonstration. A part of the 

air quality model evaluation process, sensitivity analysis and weight of evidence 

analysis will be to assess the influence of boundary and initial concentrations on 

simulation results and RRF. 
KRD: DRAFTModelingProtocol.doc 50 

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TABLE 10 

SAPRC-99 Chemical Mechanism Species 

Species Species 

ACET ISPD 

ALK1 MEK 

ALK2 MEOH 

ALK3 METH 

ALK4 MGLY 

ALK5 MPAN 

ARO1 MVK 

ARO2 NO 

BACL NO2 

BALD NOXY 

CCHO NPHE 

CO O3 

CO2H OLE1 

CO3H OLE2 

COOH PAN 

CRES PAN2 

DCB1 PBZN 

DCB2 PHEN 

DCB3 PROD 

ETHE RC2H 

GLY RC3H 

HC2H RCHO 

HC2H RNO3 

HCHO ROOH 

HNO3 SO2 

HNO4 SULF 

HO2H TERP 

HONO XN 

ISOP 
KRD: DRAFTModelingProtocol.doc 51 

 3/2/2007 

METEOROLOGICAL INPUTS 

Meteorological Input Evaluation and Technical Review 

The quality of the meteorological inputs can have a profound influence on the 

accuracy of the simulations concentrations of ozone, PM and other pollutants by 

the air quality models. It is therefore essential that the products of the 

meteorological models undergo a rigorous evaluation. By evaluating the flow 

characteristics of the wind fields, as well as the representativeness of the 

temperature, relative humidity and mixing height fields, the uncertainty in the air 

quality simulations can be minimized. AQMD and CARB staff will consider both 

qualitative and quantitative analyses in judging the meteorological fields and in 

reaching consensus on the appropriateness of those fields for use in the 2007 

AQMP. Graphical and statistical analysis software is available to facilitate the 

meteorological input field evaluation. 

The use of routine and special study monitoring data and model analysis archives 

provides a robust data set for comparing and analyzing the simulated 

meteorological fields. Some of the available data sets include: 

• Routine surface meteorological network data, including: 

 South Coast AQMD (~32 stations), 

 Ventura County APCD, 

 San Diego County APCD, 

 Mojave Desert/Antelope Valley APCD, 

 NOAA/FAA Stations (METAR obs), 

 California Remote Access Weather Stations (RAWS), 

 California Irrigation Management Information System (CIMIS) 

Stations; 

• Special study meteorological station data, such that from the Multiple Air 

Toxics Exposure Study III (MATES-III) project during part of 2004 and all of 

2005; 

• Marine buoy data from National Data Buoy Center (NDBC); 

• Routine National Weather Service and military radiosonde observation 

(RAOB) data, including the stations at Miramar MCAS, Point Mugu NAS, 

San Nicolas Island NAS, Vandenberg AFB, Edwards AFB, China Lake NAS, 

Oakland, Mercury/Desert Rock, and Tucson; 

• Southern California radar wind and temperature profiling network, including 

stations operated by: 

 South Coast AQMD (Los Angeles International Airport, Ontario 

International Airport and Moreno Valley), 

 Ventura County APCD (Simi Valley) 
KRD: DRAFTModelingProtocol.doc 52 

 3/2/2007 

 San Diego County APCD (Pt. Loma, Valley Center or Miramar) 

 NOAA project and SCOS97 profilers, when available (e.g., Goleta, San 

Clemente Island, Santa Catalina Island during SCOS97). 

• National Center for Environmental Prediction (NCEP) gridded observational 

databases and model analysis fields, including: 

 NCEP ds353.4 ADP Global Upper Air Observations database, 

 NCEP ds464.0 ADP Global Surface Observations database, 

 NCEP ds083.2 Global Tropospheric Analyses, 1 degree x 1 degree 

gridded database, 

 NCEP ETA-12 km model forecast fields, 

 NCEP ETA-40 km Model Forecast Fields, 

 NCEP EDAS-40 km Gridded Data; 

• Aerospace Corporation MM5/3-Dimensional Variational Analysis System 

(3DVAR) archives (incorporating surface, upper-air, ships, buoys, aircraft and 

satellite observations) 

Qualitative Analyses

The qualitative analysis of modeled wind fields includes an evaluation of the gross 

circulation features in the modeling region to determine if the model is replicating 

those essential features (Mulberg, 1995, Lolk and Douglas, 1996). Such features 

include areas of convergence and divergence, eddy circulations, land/sea breezes, 

slope flows, and transport corridors. Since the modeling domain includes large 

overwater areas it is also necessary to evaluate offshore flows as well. Key 

features of the windfield are areas of convergence and divergence. These features 

result in vertical velocities which can transport pollutants upward (in the case of 

convergence) or bring pollutants from aloft down to the surface (with divergence). 

The evaluation will include a review of the convergence and divergence zones in 

the simulated windfield, and their impact on realistic vertical velocities, to 

determine agreement with measurements or conceptual models in terms of 

location, timing, and extent. 

Synoptic forcing and mesoscale flow characteristics can sometimes result in eddy 

circulations. In the SCOS97 domain two key eddy features are prevalent: the 

Catalina Eddy (named since its center is often near Santa Catalina Island), and the 

Gaviota Eddy in the Santa Barbara Channel (Smith, et. al., 1984). Both eddy 

circulations are important transport mechanisms; they are capable of transporting 

precursors and aged ozone concentrations onshore and northward to Santa Clarita 

and sometimes Ventura and Santa Barbara Counties. Exceedances of the ozone 

standards are often observed with the presence of an eddy circulation and the deep 

of the marine layer that accompanies a mature coastal eddy can end an ozone 

episode. The timing of the onset, persistence, and spatial extent of eddy 

circulations, are a critical part of the windfield validation. 
KRD: DRAFTModelingProtocol.doc 53 

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Land/sea breeze circulations are another important flow feature. The sea breeze is 

one method whereby pollutants generated in the Los Angeles Basin are 

transported eastward. That is, the strength of the sea breeze will determine how 

far precursors and ozone generated near the coast will be transported inland. 

Errors in the timing of the sea breeze can cause precursor emissions to be 

transported to the wrong locations instead of inland where peak concentrations are 

observed. It is essential that the onset of the sea and land breezes simulated by the 

model be compared to observations for reasonableness. 

The onshore portion of the 2007 AQMP modeling domains includes areas of 

complex terrain. Slope flows are important as a recirculation mechanism that may 

influence ozone concentrations. Slope flows are probably the most challenging 

feature for prognostic meteorological models, due to the sparse observational data 

in complex terrain and these models have a tendency to overdo the speed of the 

slope flows. A proposed qualitative approach is to determine if wind speeds 

estimated by the model appear to be reasonable in areas of complex terrain. 

As a qualitative and quantitative evaluation of the windfields, wind speeds are 

proposed to be statistically summarized and plotted by site and globally 

throughout the domain (Seaman et. al., 1995, Bigler-Engler et. al., 1996). 

Temporal plots for key sites will be examined to determine agreement with 

observations. Quantitative techniques will make use of statistical measures such 

as the mean gross error and mean bias to compare modeled and measured wind 

speeds (Mulberg, 1995). 

Some of the methods being explored for the meteorological modeling incorporate 

observations, thus reasonably good agreement should be expected near those 

observation sites where data was used as input to the model. In order to diagnose 

the impact that incorporation of the observations has on the meteorological 

models, it may be useful to consider withholding some observations when 

executing the models to have an independent set of observations for comparison. 

The sites withheld should have some relation to the sites used to provide some 

assurance in the results from the comparison. This diagnostic evaluation is 

proposed to be conducted once acceptable meteorological fields have been 

prepared. 

Temperature fields will also be examined. At the surface, qualitative analyses will 

include an examination of the diurnal and spatial variation of estimated and 

observed temperatures, as well as consistency of the gridded data within regions.. 

The interface at the coastline will be examined for the expected gradients between 

the ocean and the land. Mean bias and mean gross error statistics will also be 

calculated to provide quantitative measures of performance. In addition, the 
KRD: DRAFTModelingProtocol.doc 54 

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vertical temperature profiles generated by the models will be compared to those 

observed at rawinsonde sites and boundary layer wind and temperature profiler 

locations. The vertical temperature profile influences the stability characteristics 

of the modeling domain which significantly affects vertical mixing. The 

evaluation will include temporal and spatial evaluations of simulated vertical 

temperatures and mixing as compared to those estimated from observed soundings 

and profiler data. The timing of the onset and breakup of the inversion will also 

be evaluated, as this phenomenon has a profound effect on estimated ozone 

concentrations. 

Quantitative Analyses

ENVIRON Corporation International (Emery, et al., 2001) proposed performance 

benchmarks and developed a statistical analysis software package, called 

METSTAT, to statistically and graphically analyze the meteorological fields. 

METSTAT is publicly available and widely used by the modeling community. It 

can read the MM5 output files and the observational data, and then calculate the 

following statistics: mean observation, mean prediction, bias error, gross error, 

root mean square error (RMSE), systematic root mean square error (RMSEs), 

unsystematic root mean square error (RMSEu), and index of agreement (IOA). It 

should be noted that the statistical evaluations are influenced by the number of 

stations and the duration of sampling period. The benchmark statistics will be 

applied to all observational stations available and to specific geographic groupings 

(e.g., coastal, mid-Basin, inland areas). Both daily and hourly statistics will be 

compiled for each modeled period. 

Meeting the METSTAT benchmarks provides assurance that the model 

performance is comparable with performance achieved in the past. METSTAT 

can be used as a screening tool to identify the periods when the performance is 

poor that require further analysis. These statistics can also be used to identify 

stations where performance is consistently poor. Table 11 shows the proposed 

performance benchmarks for the meteorological inputs for the 2007 AQMP air 

quality modeling. In addition, temporal plots will provide direct comparison of 

modeled meteorological parameters at grid points corresponding to observational 

stations. 

TABLE 11 

Proposed Meteorological Input Performance Benchmarks 

Parameter Benchmark 

Wind Speed Total RMSE ≤ 2.0 m/s 

Wind Speed Bias ≤ ±0.5 m/s 
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Wind Speed IOA ≥ 0.6 

Wind Direction Gross Error ≤ 30 degrees 

Wind Direction Bias ≤ ±10 deg 

Temperature Gross Error ≤ 2.0 K 

Temperature Bias ≤ ±0.5 K 

Temperature IOA ≥ 0.8 

Humidity Gross Error ≤ 2 g/Kg 

Humidity Bias ≤ ±1.0 g/Kg 

Humidity IOA ≥ 0.6 

[These benchmarks may be too stringent for MM5, especially Temperature. These 

may need to be reevaluated after seeing more results.] 
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EMISSION INVENTORY INPUTS 

Ozone episodes occurring in 1997, 2004, and 2005 will be simulated for the 2007 

AQMP. Gridded, hourly base year emissions inventories, including CO, NOx, 

SOx, and TOG emsissions, for those years are needed for photochemical ozone 

modeling. The 2005 base year particulate matter emissions will also be needed to 

support inputs needed for aerosol modeling. The information needed to complete 

the emission inventory for the modeling region is obtained from the local air 

pollution control districts, transportation planning agencies and CARB. For the 

2007 AQMP, the 2002 base year emissions will be used. The statewide emissions 

inventory will be gridded to the modeling domain. The 2002 emissions will be 

backcasted to the 1997 episode year and grown to the 2004 and 2005 episode 

years. Specific month and day-of-week emissions will be estimated from the 

annual average emissions, based on temperature corrections derived from ambient 

measurements. The emissions will also be grown to the attainment milestone and 

demonstration years of 2005, 2010, 2020 and, possibly 2015 and 2030. 

Adjustments to the 2002 base year inventory for the 2007 AQMP will likely 

reflect the following changes from the 2003 AQMP inventory: 

• Overall emissions inventory changes will likely include higher VOCs, lower 

NOx and lower CO emissions. New temperature and relative humidity profiles 

will be used for annual inventory adjustments. 

• The stationary source inventory will reflect that the actual 2002 emissions were 

mostly lower than 2003 AQMP-projected emissions. 

• The mobile source inventory will be projected with EMFAC Gross 

Adjustments (to be provided by Spring 2006). It will reflect increased VOC 

and NOx emissions from the 2003 AQMP inventory. Key areas of mobile 

source inventory adjustment include: 

 Truck Distribution/VMT/deterioration rate; 

 Ethanol & evaporatives and permeation issues; 

 Modified temperature distribution. 

• For the particulate matter emissions categories, the new USEPA fugitive 

PM10/PM2.5 ratio will be evaluated and applied. 

• Temperature and humidity corrections will be applied to the biogenic 

inventory. 

Other potential emissions inventory changes will possibly result from improved 

inventories for ports, the Alameda Corridor, shipping, aircraft and airports. The 

2007 AQMP on-road emissions will be based on technical-adjustments to the 

SCAG 2004 Regional Transportation Plan. No weekend trip model will be 

available from SCAG, so CARB will develop a “weekend” overlay to mimic 
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VMT based on California Department of Transportation (Caltrans) in-road counter 

data. Air quality modeling analyses will stress emissions sensitivity runs, since 

the spatial distribution of emissions will be critical to model performance due to 

the use of Relative Reduction Factors (RRFs) instead of peak concentration 

performance metrics. 

Emissions Characterization 

Point Sources

Characterizing anthorpogenic point source emission is the responsibility of the 

local air districts. Emission inventories for point sources (including RECLAIM 

facilities) are compiled by local districts and reported to CARB. If annual 

emissions for a facility fall below 10 tons/year (this cutoff varies with district) the 

source is included in the area source inventory. Point sources are allocated to grid 

cells using the location that is stored as part of the point source emission database. 

Temporal codes which describe hours of operation are also included in the 

emission database. Factors are also stored to convert annual average emissions to 

a specific month and day of week. Point sources have been inventoried for 2002. 

SCAQMD’s point source inventory for 2002 includes an update to locations 

(UTM coordinates) and stack parameters. Point source emissions will be 

estimated using the CARB California Emission Forecast System (Johnson, 1997) 

for the modeling episode base years and future years. 

Area Sources

Area sources are comprised of emission source types that are difficult to inventory 

individually. Examples are architectural coatings, residential water heating, 

gasoline stations and off-road mobile sources not included in the CARB 

OFFROAD model. The area sources include point sources smaller than 10 tons 

per year and area surrogates are used for sources such as consumer products. 

Districts and CARB share responsibility for estimating area source emissions 

according to a long-standing division of categories. CARB, 1997b describes 

methodologies used to estimate emissions from area sources. Factors are also 

included that allow estimates of specific month and day of week emissions from 

annual average emissions. Temporal codes which describe hours of operation are 

also included in the area source emission database. Area source categories have 

been inventoried for 2002. Emissions for the modeling episode base years and 

future years will be grown using CARB emission forecasting system. 
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On-Road Mobile Sources

On-road mobile source inventories are prepared using vehicle activity data from 

transportation planning agencies. The majority of travel is reflected in 

transportation plans developed by: 

• Southern California Association of Governments (SCAG); 

• San Diego Association of Governments (SANDAG); 

• Santa Barbara County Association of Governments (SBCAG); and 

• Kern Council of Governments (Kern COG). 

Travel data for areas not covered by the transportation planning agencies are 

extracted from the California Statewide Planning Model maintained by the 

California Department of Transportation. Emission factors for on-road mobile 

sources will ultimately be estimated using the CARB EMFAC2007 emission 

factor model. However, the release of EMFAC2007 will likely be concurrent with 

the 2007 SIP submittal, so the modeling will proceed using the 2002 base year 

emissions inventory from the 2003 AQMP with gross EMFAC adjustments based 

on CARB technical documentation. DTIM4 will use both the emission factors and 

travel activity data to produce hourly gridded emission estimates for the SCOS97 

region. 

CARB is leading the effort to acquire all travel data needed for this modeling 

study. The network and travel activity data provided by transportation planning 

agencies is developed for peak and off-peak time periods, which will be processed 

into 24 hourly data sets. Day-specific traffic count data will be used to calibrate 

DTIM4 inputs for development of day-specific on-road mobile source emissions. 

CARB will use the network and travel activity data to produce gridded DTIM4 

inventories for episode days. 

Other Mobile Sources

Area source emissions from most categories of off-road mobile sources will be 

estimated using the CARB off-road mobile source emission model (OFFROAD). 

OFFROAD covers more than 12 off-road categories, including lawn and garden 

equipment, small utility and construction equipment, as well as farm equipment. 

Categories not estimated by OFFROAD will be covered under “area sources”. 

However, specific emissions for aircraft, marine vessels, and locomotives will be 

provided through separate special studies. OFFROAD will produce gridded 

emission inventories for each calendar year desired. The OFFROAD model will 

have the capability to estimate exhaust, starting, and evaporative emissions for 

differing spatial and temporal conditions. 
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Biogenic Emissions

The derivation of a gridded natural biogenic emission inventory requires data sets 

describing the spatial distributions of plant species, biomass, and emission factors 

that define rates of hydrocarbon emissions for each plant species. The Biogenic 

Emission Inventory System (BEIS 2.3) (USEPA, 1995) model, distributed by the 

USEPA for this purpose, is one source of these data sets for areas throughout the 

United States. However, the BEIS model has been shown to have limited use in 

California because of poor spatial resolution within the referenced data sets and a 

simplified scheme for assigning emission factors (e.g., Jackson, et al., 1996). The 

development of a gridded biogenic emission inventory for the SCOS97 domain 

will benefit from research conducted within California that describes the needed 

data sets in more detail than is defined within the BEIS model (Benjamin et. al., 

1998). 

CARB, in consultation with researchers at UCLA, developed a methodology to 

complete a gridded biogenics inventory for the SCOS97 modeling domain. The 

methodology involves the use of: (1) gridded plant species maps using the GAP 

data base (Davis et. al., 1995), an inventory of biomass diversity for the United 

States; (2) biomass distribution, determined using published correlations between 

biomass and Normalized Difference Vegetative Index (NDVI), an index of 

relative “greenness” from Advanced Very High Resolution Radiometer (AVHRR) 

satellite remote sensing data sets; (3) emission factors of isoprene, monoterpenes, 

methyl butenol, and other VOCs for various plant species known to exist within 

the modeling domain using taxonomic relationships between the plant species 

(Benjamin et. al., 1996). The gridded biogenic inventory, including the gridded 

plant species, biomass distribution and emission factor databases, are combined 

with ambient temperature and radiation data to produce gridded hourly emissions 

of isoprene, monoterpenes, methyl butenol, and other VOCs. 

Organic Gas Speciation

Organic gas speciation profiles are applied to all categories of TOG emissions to 

obtain estimates for each organic gas species emitted in the modeling region. 

CARB maintains a database of current profiles that are routinely updated to reflect 

recent information. The most recent updates were for gasoline exhaust and 

evaporation, diesel exhaust and jet engine exhaust. The CARB publication 

Identification of VOC Species Profiles (CARB, 1991) documents the organic gas 

profiles. 

Day-Specific Emissions

Emissions from many sources vary from day to day. Evaporative emissions from 

vehicles and vegetation increase with ambient temperature. Exhaust emissions are 
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also a function of ambient temperature. Increased air conditioning demands on 

hot days also lead to increased emissions from electrical generation. Hourly 

surface temperatures for episode days are interpolated to each grid cell and are 

used in estimating emissions from vegetation and on-road mobile sources. 

Criteria pollutant emissions from approximately 80 major point sources will also 

be estimated hourly for each specific episode day. Each district has acquired data 

from major point sources for the episode days and is developing day-specific point 

source inventories for those years. The districts also collect information on 

variances, temporary breakdowns and shutdowns. DTIM4 will be run to develop 

mobile source inventories for several episode days, including weekend days. 

Where feasible, wildfire emissions will be estimated. Emissions from large ships 

in the shipping lanes are also estimated, using ship activity data (for commercial 

vessels) from shipping ports, ship-specific engine characteristics data, and the 

latest emission factors. Emissions from aircraft will be estimated using aircraft 

activity data, including hourly landing, takeoff, approach, climbout and cruise 

emission. This type of information will allow development of temporally and 

spatially resolved emission estimates. 

Emissions Quality Assurance 

CARB has provided specific guidelines to assist state and local agencies in 

implementing uniform and systematic approaches for collecting, compiling, and 

reporting emission inventory data. A comprehensive quality control and quality 

assurance plan was prepared to ensure good quality practices during development 

of the 2002 and future year emission inventories. These procedures include: 

quality control checks for collecting non-emission data, updating activity data, and 

using appropriate emission factors for calculating emissions; emission calculation 

methodology; quality assurance evaluation using the Data Attribute Rating System 

(DARS); and quality review of the entire inventory. The DARS program, 

originally developed by the USEPA, will be used as an additional quality 

assurance tool to quantify the relative accuracy of the annual emission inventories. 

CARB has also provided the districts with a variety of quality assurance reports to 

aid in the review of inventory data important for modeling. These reports were 

intended to provide checks on the accuracy of the emission calculations, stack 

data, facility location data, temporal data, devices data, process data, etc. 

Emission Projections 

Future year emissions form the basis for an air quality emission reduction target. 

Future year emissions for area and point sources are projected by accounting for 

growth and control, generally using growth and control factors applied to the base 
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year (2002) emissions. Control factors are derived based on adopted measures. 

Growth factors are derived from socioeconomic and demographic data provided 

by districts and local agencies, and CARB-sponsored research factors elsewhere. 

Area source and offroad emissions are gridded using the appropriate surrogates as 

used for 2002. Gridded future year surrogates for the entire modeling domain 

region and also being prepared for milestone and attainment demonstration years. 

Surrogates for other years can be interpolated as needed. 

Future year traffic activity and network data are also prepared by local planning 

agencies. EMFAC will give estimates of future year emission factors. DTIM4 

uses future year emission factors and network travel data to obtain gridded future 

year on-road mobile emissions. DTIM4 inputs for future years are being compiled 

and prepared. Ambient temperatures that occurred during 2002 are also used in 

calculating future year emissions for each episode day. 

Biogenic emissions will not change for future years. Even though there may be a 

shift in farm or landscaping plans and species, the capability does not exist to 

incorporate any potential changes into the inventory. Seep emissions will also 

remain constant in future year inventories. 
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AIR QUALITY MODEL PERFORMANCE EVALUATION 

It is a well established tenet of the modeling community that for an air quality 

modeling simulation to give reliable results, it must be capable of giving the right 

answers for the right reasons. That is, not only must the model be capable of 

reproducing observed air pollution measurements with a reasonable level of 

accuracy, but it must also pass a series of prescribed tests designed to ensure that 

the apparently accurate results are not produced by a combination of compensating 

errors. Several tests on the modeling simulations, both at the surface and aloft are 

proposed to be conducted as part of the model performance evaluation. Both 

precursor and secondary species will be evaluated, in addition to 1-hour and 8-

hour ozone, PM10 and PM2.5 for each episode and model variation. Statistical 

and graphical analyses will compare simulated concentration to measured values, 

throughout the domain and by geographic region. Diagnostic simulations will be 

used to analyze the sensitivity of the model to the input parameters and 

assumptions. This performance evaluation should allow a determination that the 

model is working properly. The following evaluation tools are based on previous 

modeling practices, the CARB photochemical modeling guidance (CARB 1992), 

and the USEPA attainment demonstration guidance for ozone (USEPA, 2005) and 

particulate matter (USEPA, 2001b). 

Statistical and Graphical Analyses 

The model performance evaluation effort will include both graphical and statistical 

analyses. These will compare simulated pollutant concentrations with measured 

values from the routine air monitoring stations and special study sites, including 

the PAMS stations. The statistical evaluations for the particulate matter modeling 

will focus primarily on comparisons to the speciated particulate data from the 

MATES-III study. The graphical analyses will include time series plots showing 

temporal variations, contour plots showing spatial variations, scatter plots showing 

tendencies for over- or under- estimation, and residual plots showing the 

distribution of the differences between observed and predicted concentrations. 

The statistical analyses will examine the accuracy of peak estimates (both paired 

and unpaired in time and space), mean normalized bias, mean absolute gross error, 

and mean absolute normalized gross error. The statistical performance criteria 

outlined in the CARB guidance document for Class B or better ozone performance 

will be used to guide the determination of acceptable model performance. These 

statistical criteria will be used as a criterion for acceptable model performance. 

However, other analyses (graphical, multi-species, aloft comparisons and the 

diagnostic simulations) will also be used to determine acceptable model 

performance, and ultimately a conclusion that the model is working properly must 
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be made considering the evidence from all of the analyses. Table 12 shows some 

of the statistical performance goals for the ozone simulations. 

TABLE 12 

Performance Goals for 1-Hour Ozone 

Statistic for 1-Hour 

Ozone 

Criteria 

(%) Comparison Basis 

Normalized Gross Bias ≤ ±15 Paired in space and time 

Normalized Gross Error ≤ 35 Paired in space (+2 grid cells) and 

time 

Peak Prediction 

Accuracy 

≤ ±20 Unpaired in space and time 

Subregional Performance

The performance tests will be evaluated for the entire domain, by district or air 

basin, and for several geographic subregional zones to ensure that the domainwide statistics do not mask subregional issues with the simulation. Since the 

modeling domains are very large, six geographic zones are proposed to be 

evaluated for model performance: San Fernando Valley, west (or coastal) Basin, 

mid-Basin, San Gabriel Valley, east Basin, and Coachella Valley. The same 

statistical acceptance criteria will be used for the subregions as for the entire 

domain. 

Multi-Species Evaluations

To be useful for planning or other purposes, an air quality model must be able to 

replicate measured concentrations with reasonable accuracy. However, it is also 

important to compare estimated and measured concentrations of precursors and 

secondary species, to establish confidence that the chemistry is being simulated 

properly. The important ozone precursors are NO, NOx, HONO, and organic gas 

species; important secondary species are HNO3 and PAN. Organic gas 

concentrations will be lumped according to the scheme employed by each model’s 

chemical mechanism. Comparisons will be made for each of the estimated 

precursor species and lumped organic gas species, for each monitoring location. 

In addition, comparisons will also be made for NOx, and total ROG. 

The multi-species comparisons may reveal modeling issues that were not obvious 

from the direct ozone comparison. Many of the precursor species have a 

secondary component as well. Concentrations of primary pollutants tend to have 

higher gradients than do secondary species. This makes it more difficult to 
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assume that a measured concentration of a primary pollutant represents a grid cell 

average. For these reasons it is probably unreasonable to expect the same 

accuracy in replicating precursor concentrations as for ozone concentrations. 

Thus, use of a specific statistical error or bias criterion is not recommended. 

These comparisons should be viewed as more qualitative, to uncover potential 

problems in precursor and secondary performance. 

Aloft Comparisons

Aloft air quality measurement data for the 2004 and 2005 episodes is minimal. 

The vertical profile of the chemical species will be evaluated qualitatively and a 

more quantitative analysis will be conducted whenever observational data are 

available. For the SCOS97 August 1997 episode, more extensive the upper air 

measurements are available. The concentrations of selected air pollutants were 

measured above the ground using aircraft, balloons and LIDAR. The primary 

component of these measurements is the oxidant concentrations measured with 

ozonesondes to a height of 5,000 m AGL. Ozonesondes were flown at seven sites, 

at 6-hour intervals, for selected episode days. Also, four aircraft were flown up to 

three times per day and an ozone LIDAR was operated continuously on selected 

episode days. 

When air quality data aloft is available, the performance of air quality model 

simulations above the ground will be determined by quantitatively comparing 

simulated oxidant and ozone concentrations with measurements, at reasonable 

close times and locations. Measured concentration profiles will be averaged for 

the vertical layer increments corresponding to those of the air quality model. Due 

to the vertical resolution of the air quality models, the vertical resolution of the 

aloft comparisons is likely to be somewhat inconclusive and the evaluation will be 

of a more qualitative nature. 

In addition to measuring ozone, three of the SCOS97 aircraft measured oxides of 

nitrogen and collected samples for later hydrocarbon analysis. Comparisons 

between these precursor data and concentrations simulated using the air quality 

models will also be made. However, there are relatively few samples and because 

an aircraft is not in one grid cell for an hour, comparisons may not be consistent 

with modeled concentrations. Comparisons to see if any large discrepancies exist 

between modeled and measured concentrations aloft will be made. 

Acceptable Model Performance

While it is expected that acceptable model performance can be achieved for the 

ozone and particulate episodes, this is not always feasible given the regulatory 

deadlines for plan submittals. While the modeling results of some episodes may 

not meet all the performance goals, the episode can still be used for carrying 
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capacity and attainment demonstration purposes assuming the relative reduction 

factors reflect the change in emission reduction. The RRF will be extensively 

evaluated with sensitivity analyses and such issues will be described in the weightof-evidence discussions. 

Sensitivity Analyses 

Diagnostic Simulations

Several diagnostic or investigative simulations will be employed to further 

determine the fidelity of the model results. These sensitivity analyses will help 

evaluate potential concerns regarding such factors as emissions mass, VOC/NOx 

ratios, ammonia mass, and emissions timing, including daily and weekend vs. 

weekday emissions. The diagnostic simulations that are anticipated help evaluate 

model sensitivity and performance will include the following: 

• Zero emissions – all anthropogenic and biogenic emissions will be set to zero 

to test the model’s sensitivity to emissions and to ensure that the base case 

results are influenced appropriately by the emission inputs. 

• Double anthropogenic emissions – all anthropogenic emissions will be 

doubled to test the model's sensitivity to increased man-made emissions. In 

addition, as separate tests of anthropogenic emissions affects, only mobile 

source emissions will be doubled and only stationary source emissions will be 

doubled. 

• Emissions adjusted based on uncertainty analysis results – The 

anthropogenic emissions estimate include various inherent uncertainties 

because of the nature of human activity, such as the possibility that some VOC 

sources could not be accounted and uncertainty in the spatial distribution of the 

emission sources. The adjustment factors will be developed based on the 

ambient VOC species adjusted within the bounds of the uncertainty. Various 

emissions estimate scenarios will be tested to diagnose model sensitivity and 

performance. 

• Zero biogenic emissions – biogenic emissions will be set to zero to test the 

model’s sensitivity to biogenic emissions. 

• Zero surface deposition – deposition will be turned off for all species to 

examine the effects of dry deposition on ozone estimations. 

• Reduced wind speeds – reducing the wind speeds by 50% is proposed to test 

the model’s sensitivity to that parameter. However, it is possible that the 

resulting wind fields will not be dynamically consistent, so these results will 

need to be approached with caution. 
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• Zero and estimated or measured boundary and initial conditions – A range of 

boundary and initial conditions will be analyzed to test the sensitivity of the 

models to these inputs. The modeling results using the following initial and 

boundary conditions will be analyzed: (1) the boundary conditions at the top 

and sides of the modeling domain and the three-dimensional initial conditions 

will be set to zero; (2) the observed air quality data is interpolated for the 

initializations hours, using data from PAMS and other measurements as 

available to prepare estimated speciated initial and boundary profiles; (3) a 

range of boundary and initial conditions will be evaluated, based on the larger 

scale WRAP modeling results. 

• Grid cell averaging sensitivity – For the attainment demonstration, relative 

reduction factors (RRF) will be calculated using 9-cell (15 km by 15 km) 

averages. As a sensitivity run, 1-cell (5 km by 5 km), 4-cell (10 km by 10 km) 

and 16-cell (20 km by 20 km) averages will be examined. 
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USE OF THE MODEL RESULTS 

Attainment Demonstration 

The modeling results are anticipated to be used for estimating carrying capacities 

and demonstrating future attainment of the NAAQS. For the attainment 

demonstration, the years 2007, 2010, 2014 and 2021 will be simulated with the 

proposed control measures (the control strategy) for 8-hour ozone NAAQS 

attainment. Attainment of the revoked 1-hour ozone NAAQS will also be 

demonstrated for the future year 2010 as a milestone and to show reasonable 

further progress. The years 2006, 2010, 2015 and 2020 will be simulated to 

demonstrate the particulate matter NAAQS attainment. In the past the use of the 

model results for these goals has been contingent upon acceptable base case model 

performance for the episodes simulated. That is, only episodes for which the 

model is judged to be operating properly and which meet the model performance 

acceptance criteria will be used. 

Weight-of-evidence discussions will also factor into the attainment demonstration 

by providing supportive analyses to confirm or compliment the modeling 

assessment. Examples of the weight-of-evidence considerations may include: 

trend analyses, sensitivity modeling analyses (e.g., altered emissions scenarios), 

hot spot grid evaluations, and statistical analyses. Special analyses may also be 

targeted to problem locations, for example, incorporating the Rubidoux study 

results. 

Relative Reduction Factors

Historically, AQMD developed the carrying capacity and attainment 

demonstration for ozone based on a set of specific control measures that was 

projected to achieve the 1-hour ozone NAAQS for all modeled episodes. The 

USEPA 8-hour ozone guidance (USEPA, 2005) and draft particulate matter 

guidance (USEPA, 2001b) recommend the use of relative reduction factors 

(RRFs) as part of the attainment demonstration process, assuming that satisfactory 

base year model performance is established. The RRF is a non-dimensional factor 

that incorporates design period monitoring data, using the 3-year average of the 

design value, directly into the attainment test along with the ratio of future to 

current year model predictions. The RRF is defined as the ratio of the future daily 

maximum concentration predicted near a monitor (averaged over multiple days) to 

the baseline daily maximum concentration predicted near the monitor (averaged 

over the same days). 

The RRF are site specific and will be based on the 9-cell average (15 km by 15 

km) for multiple episodes. Areas with severe or higher nonattainment status 
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require a minimum of 15 simulated days. It allows the model to be used in a 

relative, rather than absolute, sense to reduce uncertainty in the predictions. The 

use of RRFs also potentially address two problems in model applications that tend 

to result in underestimation of emission reductions needed to attain standards. The 

first problem is that modeled episodes usually have ozone concentrations lower 

than the design value. The second problem is that simulation results have 

historically exhibited a tendency towards underestimation of observed 

concentrations. By utilizing monitored data along with model estimations, RRFs 

address both problems. 

However, there may be some limitations in using RRFs, especially for 1-hour 

ozone. Examples of such situations include: 

• Measured ozone concentrations at some sites and for some episodes may differ 

substantially from design values for those sites. That is, each available ozone 

episode will not be representative of design value conditions at all sites. In 

such instances it may not be reasonable to include the non-representative sites 

in the RRF analysis. 

• Model performance typically varies considerably between sites and episodes in 

a domain. The reported ozone performance measures (such as peak prediction 

accuracy, bias, and gross error) may not capture this variation. Thus it may not 

be reasonable to include sites which have poor model performance for a given 

episode. 

Some characteristics of RRFs include the following: 

• More robust analysis due to multiple episodes; 

• Less reliant on peak concentration performance statistics; 

• Allows for episodic, seasonal or annual composite application; 

• Can be site specific; 

• Directly applied to design values so unusually adverse years weigh heavily; 

• Weekend/weekday differences may not be adequately characterized; 

• More applicable to 8-hour than 1-hour ozone; 

• Not applied for previous AQMPs 

Carrying Capacity Estimation 

A traditional use of models for planning has been the estimation of carrying 

capacities for ozone precursors. This is typically achieved by exercising the 

model with a series of across-the-board precursor emission reductions from the 

future year baseline, from which an ozone isopleth (“EKMA”) diagram is 

constructed. The metric used for the isopleth diagram can be one of several, such 
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as peak 1-hour or 8-hour ozone concentrations within the modeling domain or 

subregion, number of grid cells above the standard, or one of many population 

exposure metrics. Since the carrying capacity for each precursor is based on 

across-the-board emission changes, rather than source- and location-specific 

controls as would be specified in a plan, it should only be viewed as an initial 

estimate for determining the emissions reductions necessary for attainment. 

For the 2007 AQMP, ozone isopleth diagrams for the following air quality metrics 

will be constructed by episode: 

• Peak 1-hour ozone concentration for the domain. 

• Population exposure for 1-hour ozone concentrations. 

• Peak 8-hour ozone concentration for the domain. This information will serve 

as an indicator of the need for potential additional precursor emission 

reductions to meet the 8-hour ozone NAAQS. 
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Carter, W.P.L., D. Luo, I.L. Malkina, and J.A. Pierce. 1993. An Experimental and 

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ATTACHMENT-4 

Summary of Preliminary Critiques of Peer Reviewers 
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Draft AQMP Appendix V

(December 16, 2006 Version)

Peer Review Summary of Comments

Scientific, Technical & Modeling Peer 

Review Advisory Group Meeting

February 2007

General Appendix V Comments

• Ozone modeling methodology is state-of-the-art.

• Ozone modeling performance is quite good.

• PM modeling methodology is solid but a more complete description

of the CAMx PM model, including a description of each sub-model is 

desirable.

• Some concerns of PM model predictions of ammonium, sulfate and 

nitrate. These depend on the ammonia emissions inventory, the 

generation of nitric acid in CB4 and the CAMx thermodynamic 

module.

• How were boundary conditions treated between the large scale and

the nested model (Page V-1-6)? For example, were nested grid 

values relaxed to large-scale values using a few rows? Also, did the 

vertical layers match between the large scale and the nested grids? 

 
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General Appendix V Comments (cont.)

• Define “Severe-17 nonattainment” (Page V-1-1)

• It seems inconsistent to use different meteorology and chemistry

algorithms to study ozone versus PM2.5 (Table V-1-1). It would be 

useful to have a short discussion explaining why this was done.

• Clarify whether future-year and base-year model predictions in the 

RRF equation are an average over the model domain versus over a 

specified region versus over a specific location and whether they are 

time-averaged values versus values at a single time. (Page V-1-4)

• What is the temperature-correction algorithm used to adjust mobile 

emissions (either a reference or an equation)? (Page V-1-10)

• The time series CO figure curves should fit into the entire figure 

rather than be scrunched near the bottom (e.g., instead of a max

vertical axis of 6000 ppb, use 2000 ppb for most figures). Same with 

other chemicals. (Page 319 ff ?)

General Appendix V Comments (cont.)

• “...vertical structure was increased to 11 layers (compared with the

5-layer analysis of UAMAERO-LT), but less than the 19 layers used 

for the MM5 simulations (Page V-1-6)” My concern is that mapping 

the MM5 vertical gridding onto the CAMx gridding will introduce 

substantial error in the results.
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General Appendix V Comments (cont.)

Emissions Control Suggestions

• Consider a rule to restrict heavy-duty truck access to the ports of 

Los Angeles and Long Beach and nearby distribution terminals to 

allow only new and/or retrofitted clean diesel engines. The ports are 

a magnet for diesel trucks, and the environmental burden of rapidly 

growing freight movement on nearby neighborhoods is 

disproportionate and unfair.

• Consider a rule to require use of new/retrofitted diesel equipment at 

construction sites in the South Coast Air Basin, once more stringent 

standards for off-road diesel engine emissions take effect in 2015.

• Strengthen rules to control other sources of primary PM2.5 including 

wood smoke, meat charbroiling at restaurants, etc.

• After major successes in control of light-duty motor vehicle VOC 

emissions during the 1990s, attention seems to have turned to other 

issues. To further advance the control of air toxics, VOC mass 

emissions and reactivity, and secondary organic aerosol 

contributions to PM2.5, consider further reductions in the aromatic 

content of California gasoline. This could help reduce the air quality 

impact of both on-road and off-road gasoline engine emissions.

General Appendix V Comments (cont.)

Episode Selection

• Ozone planning should be matched to meteorological conditions that lead to the 

“design value” (i.e., the 4th highest ozone day in each of 3 consecutive years). As 

noted in the modeling protocol document, the 4th highest daily maximum value out of 

365 days corresponds to the 99th percentile of the annual distribution. There is no 

discussion of the high O3 summers of 1998 and 2003; why were they excluded from 

the analysis? The modeling protocol document (page 40) states that 11 out of 13 of 

the days considered in the AQMP are at the 95th percentile or higher; this 

undershoots the requirement to consider conditions corresponding to the 99th 

percentile from 3 consecutive years. Even if 2004 and 2005 “bracket the annual 

design value [shouldn’t the design value be based on 2003-05?]”, it is possible that 

inclusion of the 4th highest day from 2003 would increase emission control 

requirements.

• I don’t understand why the phase-out of MTBE and switch to ethanol in California 

gasoline is relevant to episode selection for ozone modeling. This fuel switch 

occurred 2003-04, but I expect small effects on emissions compared to the much

larger Phase 2 reformulated gasoline changes that took effect 1995-96.

• A major field measurement program (MATES III) focusing on the composition of 

particulate matter in the South Coast Air Basin was conducted during 2005. Staff 

efforts to develop needed emissions, meteorological, and other data for this timeframe 

will be helpful in the analysis of MATES data. Likewise, MATES will provide useful 

aerometric data to support air quality modeling. However, since the applicable air 

quality standard for PM2.5 requires consideration of a 3-year average, was 2005 

cleaner, dirtier, or typical relative to 2003-05?
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General Appendix V Comments (cont.)

Emission Inventory

• Maps showing spatial distributions of VOC, NOx, SO2, NH3, and PM2.5 

emissions should be developed and analyzed. Have anthropogenic 

emissions been inventoried for the entire modeling domain? Also I 

wonder if in-transit emissions from ships have been included; 

traditionally only the in-port emissions have been inventoried. 

Emissions from shipping lanes are likely a significant source of NOx, 

SO2, and PM.

• An emission inventory question needing more work is the description of 

heavy-duty diesel truck activity and emissions. How were the spatial 

and temporal patterns of diesel truck activity estimated on weekdays? 

Setting the truck fraction to a constant proportion of total vehicle travel 

in each grid cell and hour is not accurate. Truck traffic follows different 

spatial and temporal patterns; for example, there should be hot-spots of 

truck travel near the ports, and long-haul truck traffic takes place almost 

entirely on highways. This is important as one of the major emission 

control programs that will affect air quality in future years is more 

stringent standards on heavy-duty truck emissions.

General Appendix V Comments (cont.)

Emission Inventory (cont.)

• For schedule reasons, the 2007 AQMP modeling was conducted using a 

motor vehicle emission inventory developed prior to the latest release of 

California’s on-road vehicle emission inventory model (EMFAC2007). 

Heavy-duty truck activity and NOx emission rates were significantly 

revised in EMFAC2007. Are these revisions to diesel emissions 

captured at least approximately in the AQMP?

• An important uncertainty in the emission inventory is the amount of offroad mobile source activity, specifically heavy-duty diesel engines used 

in construction and agriculture. Kean et al. (J. A&WMA 50, 1929-1939, 

2000) found that some major categories of off-road engine activity may 

be overstated in the U.S. by a factor of about 2. Curently on-road and 

off-road engine emissions are estimated separately. While the dividing 

line between on-road and off-road fuel use may be difficult to draw 

clearly, the sum should be easier to estimate and compare to known 

total diesel fuel production/supply to the California market.

• The modeling protocol document mentions briefly CARB’s library of 

organic gas emission speciation profiles. Similar information for 

particulate matter and NOx emissions is missing. I am concerned that a 

10% NO2 fraction and a 2% nitrous acid (HONO) fraction in all direct 

sources of NOx emissions may be too high.
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General Appendix V Comments (cont.)

Boundary Conditions

• It is not clear from the materials received if/how a vertical 

concentration profile of pollutants was specified along the lateral 

boundaries of the modeling domain. From ozone soundings at 

Trinidad Head (northern California coastal site), we know that there 

are vertical gradients in ozone from ~20 ppb at the surface to 40-50 

ppb above the planetary boundary layer. Over the ocean, stable 

stratification is expected in the marine boundary layer. This could 

allow large vertical concentration gradients to develop for pollutants 

that are soluble/reactive at the ocean surface. Surface observations 

at coastal or offshore sites may therefore not represent the true 

inflow concentrations along the western boundary of the modeling

domain, especially aloft.

PM Modeling Comments

• Predicted ammonium at Compton, LA & Pico Rivera exceed 

Rubidoux. Ammonium not well correlated with sulfate, except at 

Compton (Table V-2-10a).

• Nitrate not correlated with amonium, except at Pico Rivera (Table V2-10b).

• Why is predicted annual average PM2.5 largest at LA, Compton and

Pico Rivera (Table V-2-10g)?

• OC is substantially underpredicted at Fontana (Figure V-2-11d).

• EC is underpredicted everywhere, except Long Beach (Figures V-2-

12a through -12e). This suggests that the emissions inventory is 

underestimating EC. Cross-check emissions from diesel fleet with 

the NOx inventory from the fleet.

• Predicted annual average PM2.5 at Big Bear is curiously low in 

relation to the measured value (Table V-2-11). Make sure this is not 

an indication of a larger problem. Also, Ontario, San Bernardino and 

Riverside-Magnolia are higher than observed.
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PM Modeling Comments (cont)

• It is not clear whether a two-mode particle size aerosol module is 

accurate enough to predict aerosol physical processes (Page V-1-

5). Why was this method chosen instead of the size-resolved 

method?

• “The peak PM2.5 24-hour average concentration...occurred on 

October 22, 2005” (Page V-1-7). This date is a typical date for a 

Santa Ana wind. If a Santa Ana wind was occurring, this might be

mentioned. Does the model treat natural soildust emissions and/or 

would it be able to account for high PM during Santa Ana conditions 

or does it rely solely on anthropogenic sources?

• “The coarse portion of the PM10 is assumed to be held constant in

this analysis” (Page V-1-8). Do you mean PM10-PM2.5 is held 

constant? How was the constant value determined?

• Were aerosol and cloud effects on UV radiation accounted for in the 

simulation of ozone with CAMx? (Page V-1-8)

PM Modeling Comments (cont)

• How are sea-spray chemicals treated in the model (Na+, Ca2+, K+, 

Mg2+, Cl-, etc.). Since these components can form a significant 

portion of PM10 and a portion of PM2.5 in Los Angeles, they would 

appear relevant. Are they added as “crustal?” (Page V-2-1)

• Figure V-2-2 shows the components of PM2.5 mass (Page V-2-4). 

Does the “blank” capture mass that is not speciated? Please clarify.

• Please provide the dates of each quarter. (Page V-2-6)

• Please provide the relative humidity at which the aerosol water 

content was determined for. (Page V-2-6, Figure V-2-3a and related 

figures)

• Based on Eq. V-2-1, it seems that OC (organic carbon) should be 

called (OM) organic matter, since OM contains noncarbon elements 

in addition to pure OC. (Page V-2-13)

• The calculation of bonded water and, thus, of OC, depends 

significantly on the relative humidity. Also, bonded water is a

function of Na+ and Cl- as well as the other components. This 

should be mentioned. (Page V-2-13)
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PM Modeling Comments (cont)

• “The boundary and top concentration input files were created on a

month by month basis. ” How were top-boundary values 

incorporated into the model? Were they outside-model values 

treated during downward inflow or were they really fixed top-modellayer values. If the latter, mass must not have been conserved 

during vertical transport. Please discuss. (Page V-2-17) 

• Similarly, for the lateral boundaries, were specified mixing ratios 

values just outside the model domain used for inflow or were they 

values fixed at inside of the boundary? (Page V-2-17) 

• Top and lateral boundary values should change diurnally due to 

chemistry. Keeping the values constant may provide a source of 

error. This should be discussed here. (Page V-2-17) 

• The use of 4-5 significant digits in the boundary condition values 

gives the appearance of too much confidence in those values. 

(Page V-2-18, Table V-2-6) 

• Why was a lower limit placed on the vertical diffusivity (1 m2/s)? 

Does the code fail at a lower diffusivity? This is quite a high

minimum. (Page V-2-19) 

PM Modeling Comments (cont)

• Define “controlled” emissions. What controls, specifically? (Page V2-19)

• There is little discussion about how the future emission inventories 

were developed. This is discussed more in the protocol but could be 

expanded on briefly here. (Page V-2-19) 

• “A nearest cell average of predicted concentrations is typically used 

when comparing...to station measurements.” Using bilinear 

interpolation to the exact location is a more physically correct

method and has been used in several studies. A comment about 

this option would be beneficial. (Page V-2-24)

• Are the statistics based on hourly comparisons? Is there a lower 

cutoff value for comparisons? The table should also include a 

column (or state in the caption) the number of comparisons that 

were made for each city. (Page V-2-25, Tables V-2-10a-...) 

• Are the normalized bias and error fractions or mass concentrations? 

I would suggest using normalize gross error as a percent = 100% * 

(1/N) * sum(abs(Pi-Oi)/Oi), where N=number of observations, Oi = 

ith observation, Pi=ith paired-in-time-and-space prediction, and the 

sum is over all comparisons. (Page V-2-25, Tables V-2-10a-...)
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PM Modeling Comments (cont)

• For the yearly simulations, how frequently was the model restarted 

from initial conditions (or was the model run for a year straight)? 

(Page P. V-2-31)

• Table V-2-11 is not such a useful table since a comparison of two 

annual concentrations is a bias rather than an error comparison 

(Thus the column, “Percentage prediction error” is mislabeled and 

should be “Percentage prediction bias”). The normalized bias will 

be less than the normalized gross error, so including a normalized 

gross error, where the comparisons are paired in time (as well as 

space), would be beneficial. (Page V-2-47)

• “NOx reductions are approximately three time more effective...” Is 

this true at low NH4+ levels as well as at current NH4+ levels? 

(Page V-2-50)

• “Figure V-2-14 presents the grid cell extrapolated of 2005 PM2.5 

annual design values.” I do not understand what this sentence and 

figure are showing. Similarly, the description for Table V-2-14 is 

unclear as are the descriptions for Tables V-2-15a.... More 

description in the text or table captions would be helpful. (Page V-2-

61)

PM Modeling Comments (cont)

• It is difficult to distill what information is important from these tables. 

Can the key information be summarized? (Tables V-2-16a...)

• “Future year predictions of maximum and second maximum 24-hour 

average PM10 are calculated using the site specific ratio between 

annual PM2.5 calculated for 2005 and 2015.” Why not just use 

information from 2015 simulations directly? Why is it necessary to 

apply a ratio? 2015 simulations could be initialized with similar 

meteorology as 2005. (Page V-3-1)

• “Visual range in 2021 is estimated... (Page V-3-6).” How is visual 

range being calculated? The standard Koschmieder equation for 

visual range (3.912/bext) differs significantly from a practical

prevailing visibility equation based on a fit to data (1.9/bext) (e.g., 

Griffing, 1980, Atmos. Environ, 14, 577).

• Light extinction depends significantly on liquid water content of 

aerosol particles. Page V-3-7, Tables V-3-2 and V-3-3 do not 

appear to include liquid water (or if they do, they must be at a

constant RH). More discussion is needed.

• Why is the extinction due to sulfate 0 (Page V-3-7, Table V-3-3)?
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PM Modeling Comments (cont)

• Page V-3-8, Table V-3-4 estimates significant reductions in PM 

concentrations but Table V-2-7 indicates only an 18% reduction in 

PM2.5 emissions in 2020 under controlled conditions relative to 

2005. Is something missing from Table V-3-4?

• Why is PM10 being discussed instead of PM-coarse (PM10-2.5)? 

(Page V-1-8)

• Page V-2-3 to V-2-5: Three points:

– (1) the total mass differs from the sum of the component masses.

This is common and should be addressed in the discussion 

especially since uncertainty was just discussed a few pages 

earlier.

– (2) The metals content seems unusually high. I’m more used to 

ng/m3 concentrations of metals. Any explanation for this?

– (3) The sulfate seems very high, considering the current fuel 

sulfur levels. Are there data from San Nicholas or a coastal 

location – I would like to know how much of this sulfate is 

background or long range transport and how much is associated 

with marine shipping?

PM Modeling Comments (cont)

• Page V-2-13 to V-2-14 (Sandwich): Of course, all the error in mass 

measurement then goes into the estimate of OC using this method.

A context would help: What will this Sandwich estimated OC value 

be used for?

• Page V.2.15: “The vertical structure for the CAMx modeling was 

increased to 8 layers of height dependent varying depth (compared 

with the 5-layer analysis of UAMAERO-LT) but less than the 19 

layers used for the MM5 simulations in effort to conserve 

computational resources.” This statement disagrees with the one 

above (Page V-1-6) but agrees with the main document regarding 

vertical layers. Are the 11 layers for ozone whereas the 8 layers are 

for PM?

• Page V-2-22 (VMT Capping): Capping depends on whether the 

source of the silt is related to the vehicle traffic. Some of the silt is 

from airborne or waterborne dust, which may make sense to cap, 

but much is from brake and tire wear which will increase with VMT 

(although brake wear may not increase as much as hybrids continue 

to increase their market penetration).
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PM Modeling Comments (cont)

• Page V-2-25 (PM2.5 Component Species Performance Evaluation 

for the MATES-III Sites): The agreements are good but possibly the 

average agreement is good but the agreement during peak episodes

is not as good or better. How do these look?

• Page V-2-50: “the proposed strategy focuses on the reductions of 

SOx and primary PM2.5 through cleaner marine fuels and extensive 

diesel trap retrofits respectively.” Is marine fuel sulfur content within 

the SCAQMD jurisdiction? The state’s? Even if the local fuel sold 

has the lower sulfur content, there is no guarantee that ships will buy 

this more expensive fuel and they will unlikely be using it as they 

come into port.

• Page V-2-51, Table V-2-12: How can SOx reductions have twice the 

PM2.5 impact of primary PM2.5 emissions? Most of SOx is SO2, 

much of which will not be converted to sulfate within the basin. The 

sulfate will have water and ammonium associated with it, but is that 

enough to overcome the fraction of sulfate produced?

Ozone Modeling Comments

• Ozone is underpredicted for weekend episode on:

– 7/15 – 7/17 at Crestline (Figure V-4-17b),

– 7/16 – 7/18 at Fontana (Figure V-4-17c),

– 7/16 – 7/19 at Santa Clarita and San Bernardino (Figure V-4-

17g).

• Sensitivity analyses should address the possibility that an inaccurate 

weekend emissions inventory caused this underprediction.

• What is the effect of this underprediciton on the RRFs derived for 

these sites?
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Ozone Modeling Comments (cont.)

• “...a minimum observed concentration...exceeds 70 ppb...” Is this 

averaged over 8 hours, 1 hour, or is it instantaneous? (Page V-1-10)

• It would be useful to see how accurate the model is in predicting the 

peak at the exact location of the peak (using bilinear interpolation 

from four surrounding grid cells in the model to estimate the value at 

the exact location of the peak) in addition to seeing whether the 

model predicted the peak within 15 km. (Page V-1-11)

• “Overall per-capita exposure to ambient ozone...” Does the 

exposure model account for the 3-D modeled ozone concentration in 

a grid cell multiplied by the population in the grid cell? A discussion 

of how exposure is calculated would be useful. Also, ozone health 

effects begin to occur above 35 ppbv, so shouldn’t an exposure 

model account for such concentrations as well as those above the

state standard? (Page V-4-6)

• “Minimum vertical diffusivity set at 1 m2/sec. (Page V-4-17, Table V4-6).” Again, this limit appears to be arbitrary and may result in 

over-diffusion.

Ozone Modeling Comments (cont.)

• How is photolysis treated (Page V-4-17, Table V-4-6)? How above 

cloud effects on photolysis and on gas/particle processing?

• For future years, the boundary values could increase due to longrange transport of pollutants (e.g., growth of emissions from Asia) as 

well as decrease due to lower local emissions (Page V-4-21). The 

effects of long-range transport of pollution from Asia is not discussed 

in the AQMD. This is increasingly thought to be important, 

particularly in April for PM but also year around.

• The Gross errors for MM5 with data assimilation appear quite large 

(particularly for temperature and wind direction) (Page V-4-22, Table 

V-4-8). Is data assimilation providing any benefit relative to no data 

assimilation? If so this might be stated.

• Normalized gross errors should be paired exactly in space and time 

(e.g., using bilinear interpolation) rather than within 2 grid cells and 

time (Page V-4-27). This would make comparisons of error statistics 

with evaluations from other models consistent. It would also make 

the statistic consistent with the normalized gross bias (which are 

stated to be paired in time and space although my guess is that 

bilinear interpolation was not used for that either).
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Ozone Modeling Comments (cont.)

• Using a cutoff of 60 ppb for ozone statistics is also inconsistent with 

several studies that use 40 ppbv as the cutoff. (Page V-4-27)

• Page V-4-12: “Cassmassi (1998) used Classification and 

Regression Tree analysis (CART) to determine whether the 

conceptual model for a 1-hour ozone episode differed from the 

meteorological profile characterizing an 8-hour average ozone 

episode in the Basin.” For analyzing single particle mass spec data, 

we found that ART2a was easier to understand and employ than 

CART.

• Page V-4-21: “For the future year scenarios, the boundary, region 

top and ambient air quality concentrations were rolled back based 

on the percentage reduction in emissions from 2002 base year to 

the projected emissions levels for future year of the simulation (2009, 

2012, or 2020).” How sensitive are the peak basin predictions to the 

boundary conditions, especially the top ones? Rolling them back in 

proportion to the emissions reductions ignores the inevitable 

increase in background from Asia over the coming years.

• Page V-4-27: Again, I do not know what unpaired statistical 

comparisons really mean. If there is peak agreement but no 

correspondence in space or time, does that really tell us anything 

other than that coincidences happen sometimes?

Meteorological Model Comments

• Was the NCEP reanalysis used at 2.5 degrees or 1 degree 

resolution? (Page V-1-6)

• How frequently were MM5 fields fed into CAMx? (Page V-1-10)
ATTACHMENT-5 

2014 Control Measures Basin PM2.5 Attainment 
Run Date: 8/16/2007 1:53:51 PM

(PC-CEPA V. 4.2/ May 2001)

C:\AQMP2007\CF0207\CM3-0607\cf2014-060607.txt

C:\AQMP2007\CF0207\CM3-0607\master-060607.txt

C:\AQMP2007\dump0906\xz011607\ems14ocs.txt

C:\AQMP2007\CF0207\CM3-0607\scen4-060607-noltm.txt

C:\AQMP2007\CF0207\CM3-0507\impact-051107.txt

Year 2014 Emission Reductions Excluding Natural Sources by Control Measure 

in the South Coast Air Basin (Annual Average Inventory - Tons/Day)

(A) Reductions Without Overlapping/Double-Counting With Other Control Measures (1)

(Reductions - Tons/Day)

Measure Name VOC NOx CO SOx PM10 PM2.5

BA-LSI ARB Baseline Adjustment for large spark-ignited engines [NOX] 0.00 2.40 0.00 0.00 0.00 0.00

BA-CONS ARB Baseline Adjustment for Consumer Products [VOC] 4.50 0.00 0.00 0.00 0.00 0.00

BCM-03 Emission Red. from Wood Burning Fireplaces and Wood Stoves 0.00 0.00 0.00 0.00 1.05 1.01

BCM-05 Reductions from Under-fired Charbroilers [PM] 0.00 0.00 0.00 0.00 1.08 1.07

CMB-01 Nox Reduction from Non-Reclaim Ovens, Dryers and Furnaces 0.00 3.48 0.00 0.00 0.00 0.00

CMB-02 Reduction SOx Reductions 0.00 0.00 0.00 2.89 0.00 0.00

CMB-03 NOx Reductions from Residential Space Heaters [NOx] 0.00 0.79 0.00 0.00 0.00 0.00

CTS-01 Industrial Lubricants [VOC] 1.87 0.00 0.00 0.00 0.00 0.00

FUG-02 Emission Red. from Gasoline Transfer and Dispensing Facilities [V 3.71 0.00 0.00 0.00 0.00 0.00

MCS-01N Facility Modernization [NOx] 0.00 1.59 0.00 0.00 0.00 0.00

MCS-01P Facility Modernization [PM] 0.00 0.00 0.00 0.00 0.43 0.38

MCS-01V Facility Modernization [VOC] 2.02 0.00 0.00 0.00 0.00 0.00

MCS-05 Non-Dairy Livestock Waste [VOC,NH3] 0.75 0.00 0.00 0.00 0.00 0.00

EGM-01N Emission Reductions from New & Re-Development Projects 0.00 0.00 0.00 0.00 0.00 0.00

EGM-01P Emission Reductions from New & Re-Development Projects [PM] 0.00 0.00 0.00 0.00 0.00 0.00

EGM-01V Emission Reductions from New & Re-Development Projects 0.00 0.00 0.00 0.00 0.00 0.00

FLX-02P Petroleum Refinery Pilot Program [PM] 0.00 0.00 0.00 0.00 0.48 0.44

FLX-02V Petroleum Refinery Pilot Program [VOC] 0.74 0.00 0.00 0.00 0.00 0.00

ARB-ON1 Smog Check Enhancements [VOC,NOX,PM] 10.09 12.55 0.00 0.00 0.21 0.19

ARB-ON2 Expand Vehicle Retirement [VOC,NOX,PM] 2.84 2.49 0.00 0.00 0.06 0.05

ARB-ON3 Modifications to Reformulated Gasoline Program [VOC] 3.72 0.00 0.00 0.00 0.00 0.00

ARB-ON4 Cleaner In-Use Heavy-Duty Trucks [VOC,NOX,PM] 5.13 47.14 0.00 0.00 3.26 3.00

ARB-ON5 Port Truck Modernization [NOX,PM] 0.00 1.98 0.00 0.00 0.54 0.50

ARB-OFF1 Marine Vessels - Fuel, Aux. & Main Eng. [VOC,NOX,PM] 0.00 38.53 0.00 19.98 2.77 2.70

ARB-OFF2 Accel. Intro. Of Cleaner Line-Haul Loco. [VOC,NOX,PM] 0.70 4.30 0.00 0.00 0.22 0.20

ARB-OFF3 Clean Up Existing Harbor Craft [VOC,NOX,PM] 0.00 4.60 0.00 0.00 0.21 0.20

ARB-OFF4 Cleaner In-Use Off-Road Equipment [VOC,NOX,PM] 2.72 10.52 0.00 0.00 2.72 2.50

ARB-OFF5 New Emis Stds for Recreational Boats [VOC,NOX] 2.85 0.25 0.00 0.00 0.00 0.00

ARB-OFF6 Expanded Off-Road Rec. Veh Ems Stds [VOC] 1.85 0.00 0.00 0.00 0.00 0.00

ARB-CONS Consumer Products [VOC] 12.93 0.00 0.00 0.00 0.00 0.00

MOB-05 AB 923 Light-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.77 0.36 11.16 0.00 0.00 0.00

MOB-06 AB 923 Med-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.46 0.48 5.55 0.00 0.00 0.00

SCONRD-1* Accelerated Penetration of ATPEVs and ZEVs [VOC,NOX,CO,PM] 0.40 0.92 11.78 0.00 0.05 0.04

SCONRD-3* Further Emis. Red. from Heavy-Duty Vehicles [VOC,NOX,CO,PM] 0.00 24.89 0.00 0.00 1.35 1.24

SCONRD-4* Further Emis. Red. from Port Trucks [NOX,PM] 0.00 5.99 0.00 0.00 0.02 0.02

SCOFRD-1* Construction/Industrial Fleet Modernization [VOC,NOX] 2.88 14.14 0.00 0.00 0.00 0.00

SCOFRD-2* Cargo Handling Equipment [NOX,PM] 0.00 1.08 0.00 0.00 0.02 0.02

SCOFRD-3* Further Ems. Red. From Locomotives [NOX,PM] 0.00 10.95 0.00 0.00 0.45 0.41

SCOFRD-6* Accelerated Turnover Pleasure Craft [VOC,NOX,PM] 2.89 1.06 0.00 0.00 0.84 0.63

SCFUEL-1* California Phase III Reformulation Gasoline [NOX,SOX] 0.00 0.00 0.00 1.35 0.00 0.00

SCFUEL-2* Greater Use of Diesel Fuel Alt. & Reformulation [NOX,SOX,PM] 0.00 3.98 0.00 0.05 0.25 0.23

Grand Total (Net) 63.80 194.49 28.49 24.27 16.00 14.84
Year 2014 Emission Reductions Excluding Natural Sources by Control Measure in the South Coast Air Basin (Annual 

Average Inventory - Tons/Day)

(B) Reductions With Overlapping/Double-Counting With Other Control Measures (2)

(Reductions - Tons/Day)

Measure Name VOC NOx CO SOx PM10 PM2.5

BA-LSI ARB Baseline Adjustment for large spark-ignited engines 0.00 2.40 0.00 0.00 0.00 0.00

BA-CONS ARB Baseline Adjustment for Consumer Products [VOC] 4.50 0.00 0.00 0.00 0.00 0.00

BCM-03 Emission Red. from Wood Burning Fireplaces and Wood 0.00 0.00 0.00 0.00 1.05 1.01

BCM-05 Reductions from Under-fired Charbroilers [PM] 0.00 0.00 0.00 0.00 1.08 1.07

CMB-01 Nox Reduction from Non-Reclaim Ovens, Dryers and 0.00 3.48 0.00 0.00 0.00 0.00

CMB-02 Reduction SOx Reductions 0.00 0.00 0.00 2.89 0.00 0.00

CMB-03 NOx Reductions from Residential Space Heaters [NOx] 0.00 0.79 0.00 0.00 0.00 0.00

CTS-01 Industrial Lubricants [VOC] 1.87 0.00 0.00 0.00 0.00 0.00

FUG-02 Emission Red. from Gasoline Transfer and Dispensing 3.71 0.00 0.00 0.00 0.00 0.00

MCS-01N Facility Modernization [NOx] 0.00 1.59 0.00 0.00 0.00 0.00

MCS-01P Facility Modernization [PM] 0.00 0.00 0.00 0.00 0.43 0.38

MCS-01V Facility Modernization [VOC] 2.02 0.00 0.00 0.00 0.00 0.00

MCS-05 Non-Dairy Livestock Waste [VOC,NH3] 0.75 0.00 0.00 0.00 0.00 0.00

EGM-01N Emission Reductions from New & Re-Development 0.00 0.00 0.00 0.00 0.00 0.00

EGM-01P Emission Reductions from New & Re-Development 0.00 0.00 0.00 0.00 0.00 0.00

EGM-01V Emission Reductions from New & Re-Development 0.00 0.00 0.00 0.00 0.00 0.00

FLX-02P Petroleum Refinery Pilot Program [PM] 0.00 0.00 0.00 0.00 0.48 0.44

FLX-02V Petroleum Refinery Pilot Program [VOC] 0.74 0.00 0.00 0.00 0.00 0.00

ARB-ON1 Smog Check Enhancements [VOC,NOX,PM] 10.09 12.55 0.00 0.00 0.21 0.19

ARB-ON2 Expand Vehicle Retirement [VOC,NOX,PM] 3.03 2.74 0.00 0.00 0.06 0.05

ARB-ON3 Modifications to Reformulated Gasoline Program [VOC] 3.96 0.00 0.00 0.00 0.00 0.00

ARB-ON4 Cleaner In-Use Heavy-Duty Trucks [VOC,NOX,PM] 5.13 47.14 0.00 0.00 3.26 3.00

ARB-ON5 Port Truck Modernization [NOX,PM] 0.00 2.75 0.00 0.00 1.19 1.09

ARB-OFF1 Marine Vessels - Fuel, Aux. & Main Eng. [VOC,NOX,PM] 0.00 38.53 0.00 19.98 2.77 2.70

ARB-OFF2 Accel. Intro. Of Cleaner Line-Haul Loco. [VOC,NOX,PM] 0.70 4.30 0.00 0.00 0.22 0.20

ARB-OFF3 Clean Up Existing Harbor Craft [VOC,NOX,PM] 0.00 4.60 0.00 0.00 0.21 0.20

ARB-OFF4 Cleaner In-Use Off-Road Equipment [VOC,NOX,PM] 2.72 10.52 0.00 0.00 2.72 2.50

ARB-OFF5 New Emis Stds for Recreational Boats [VOC,NOX] 2.90 0.25 0.00 0.00 0.00 0.00

ARB-OFF6 Expanded Off-Road Rec. Veh Ems Stds [VOC] 1.88 0.00 0.00 0.00 0.00 0.00

ARB-CONS Consumer Products [VOC] 12.93 0.00 0.00 0.00 0.00 0.00

MOB-05 AB 923 Light-Duty High-Emitter Id. 0.87 0.41 11.16 0.00 0.00 0.00

MOB-06 AB 923 Med-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.51 0.53 5.55 0.00 0.00 0.00

SCONRD-1* Accelerated Penetration of ATPEVs and ZEVs 0.45 1.05 11.89 0.00 0.05 0.04

SCONRD-3* Further Emis. Red. from Heavy-Duty Vehicles 0.00 42.42 0.00 0.00 4.05 3.72

SCONRD-4* Further Emis. Red. from Port Trucks [NOX,PM] 0.00 11.42 0.00 0.00 0.20 0.18

SCOFRD-1* Construction/Industrial Fleet Modernization [VOC,NOX] 3.62 15.85 0.00 0.00 0.00 0.00

SCOFRD-2* Cargo Handling Equipment [NOX,PM] 0.00 1.08 0.00 0.00 0.02 0.02

SCOFRD-3* Further Ems. Red. From Locomotives [NOX,PM] 0.00 14.32 0.00 0.00 0.63 0.58

SCOFRD-6* Accelerated Turnover Pleasure Craft [VOC,NOX,PM] 3.13 1.09 0.00 0.00 0.84 0.63

SCFUEL-1* California Phase III Reformulation Gasoline [NOX,SOX] 0.00 0.00 0.00 1.35 0.00 0.00

SCFUEL-2* Greater Use of Diesel Fuel Alt. & Reformulation 0.00 6.35 0.00 0.05 0.64 0.59

Grand Total (with potential overlapping) 65.48 226.18 28.61 24.27 20.10 18.62
EMISSION SUMMARY FOR

(POINT, AREA, MOBILE SOURCE, AND OFF-ROAD MV)

Baseline Emissions VOC NOx CO SOx PM10 PM2.5

 

 Point source 37.71 8.69 54.15 1.99 10.09 8.85

 Area source 218.83 41.16 123.68 2.47 236.24 59.69

 RECLAIM 0.00 26.51 0.00 11.76 0.00 0.00

 

 Total Stationary 256.54 76.36 177.83 16.23 246.33 68.54

 

 On-road 144.06 292.24 1392.93 2.22 24.01 16.83

 Off-road 117.11 263.06 936.79 22.30 17.33 15.25

 Aircraft 9.99 21.95 69.16 2.08 1.03 1.01

 

 TOTAL 527.69 653.62 2576.71 42.83 288.70 101.62

 

 

EMISSION REDUCTIONS 

 

 Point source 2.76 1.34 0.00 0.00 0.91 0.82

 Area source 23.74 4.17 0.00 0.00 2.13 2.08

 RECLAIM 0.00 0.00 0.00 2.89 0.00 0.00

 

 Total Stationary 26.51 5.51 0.00 2.89 3.05 2.91

 

 On-road 22.06 98.58 28.49 1.31 5.54 5.10

 Off-road 15.24 90.40 0.00 20.06 7.41 6.84

 Aircraft 0.00 0.00 0.00 0.00 0.00 0.00

 

 TOTAL 63.80 194.49 28.49 24.27 16.00 14.84

 

 

REMAINING EMISSIONS 

 

 Point source 34.94 7.35 54.15 1.99 9.18 8.03

 Area source 195.09 36.99 123.68 2.47 234.10 57.60

 RECLAIM 0.00 26.51 0.00 8.87 0.00 0.00

 

 Total Stationary 230.03 70.85 177.83 13.34 243.28 65.63

 

 On-road 122.00 193.66 1364.44 0.91 18.48 11.73

 Off-road 101.87 172.66 936.79 2.24 9.91 8.41

 Aircraft 9.99 21.95 69.16 2.08 1.03 1.01

 

 TOTAL 463.89 459.13 2548.22 18.56 272.70 86.78

 

 

 NSR/Set-Aside 5.00 -1.20 0.00 0.00 0.00 0.00

 

 Public Funding 0.00 -4.20 0.00 0.00 0.00 -0.10

 

 GRAND TOTAL (T/D) 468.89 453.73 2548.22 18.56 272.70 86.68

 

 Mobility Adjustments (3) 0.00 0.00 0.00 0.00 0.00 0.00

 
(1) Emission reductions for individual measures were estimated based on the sequence of listing

 contained here. When the sequence changes, reductions from each measure could be affected,

 but the net total remain the same. The purpose of this table is to estimate

 total emission reductions without overlapping or double-counting between measures.

(2) Emission reductions for individual measures were estimated in the absence of other measures.

 Therefore, the sequence of listing does not affect the reduction estimates. The purpose of 

 this table is to provide emission reduction estimates for Appendix IV control measure

 summary tables as well as cost effectiveness analysis.

(3) Mobility Adjustment includes TCM-01, ATT-01, ATT-02, ATT-05 and adjustments are reflected 

 in the CEPA baseline beyond year 2000. 

*For the purpose of attainment demonstration, these mobile source measures were selected to achieve the additional 

 63 tons per day of NOx reductions needed by 2014 for PM2.5 attainment. However, CARB can implement any 

 combination of strategies to achieve the needed reductions. 
ATTACHMENT-6 

2017 Control Measures For Coachella Valley Ozone Attainment 
Run Date: 8/22/2007 4:29:10 PM

(PC-CEPA V. 4.2/ May 2001)

C:\AQMP2007\CF0207\CM3-0607\cf2017-060607.txt

C:\AQMP2007\CF0207\CM3-0607\master-060607.txt

C:\AQMP2007\dump0906\xz011607cv\ems17cv.txt

C:\AQMP2007\CF0207\CM3-0607\scen4-060607-noltm.txt

C:\AQMP2007\CF0207\CM3-0507\impact-051107.txt

Year 2017 Emission Reductions Excluding Natural Sources by Control Measure 

in Coachella Valley (Planning Inventory - Tons/Day)

(A) Reductions Without Overlapping/Double-Counting With Other Control Measures (1)

( eductions Tons/Day R - )

Measure Name VOC NOx CO NO2

BA-LSI ARB Baseline Adjustment for large spark-ignited engines NOX] [ 0.00 0.02 0.00 0.02

BA-CONS ARB Baseline Adjustment for Consumer Products [VOC] 0.14 0.00 0.00 0.00

BCM-03 Emission Red. from Wood Burning Fireplaces and Wood Stoves 0.00 0.00 0.00 0.00

BCM-05 Reductions from Under-fired Charbroilers [PM] 0.00 0.00 0.00 0.00

CMB-01 Nox Reduction from Non-Reclaim Ovens, Dryers and F rnaces u 0.00 0.10 0.00 0.10

CMB-03 NOx Reductions from Residential Space Heaters [NOx] 0.00 0.01 0.00 0.07

CTS-01 Industrial Lubricants [VOC] 0.07 0.00 0.00 0.00

FUG-02 Emission Red. from Gasoline Transfer and Dispensing Facilities [V 0.09 0.00 0.00 0.00

MCS-01N Facility Modernization [NOx] 0.00 0.05 0.00 0.04

MCS-01P Facility Modernization [PM] 0.00 0.00 0.00 0.00

MCS-01V Facility Modernization [VOC] 0.00 0.00 0.00 0.00

MCS-05 Non-Dairy Livestock Waste [VOC,NH3] 0.00 0.00 0.00 0.00

EGM-01N Emission Reductions from New & Re-Development Projects [NOx] 0.00 0.00 0.00 0.00

EGM-01P Emission Reductions from New & Re-Development Projects [PM] 0.00 0.00 0.00 0.00

EGM-01V Emission Reductions from New & Re-Development Projects [VOC] 0.00 0.00 0.00 0.00

FLX-02P Petroleum Refinery Pilot Program [PM] 0.00 0.00 0.00 0.00

FLX-02V Petroleum Refinery Pilot Program [VOC] 0.00 0.00 0.00 0.00

ARB-ON1 Smog Check Enhancements [VOC,NOX,PM] 0.33 0.29 0.00 0.30

ARB-ON2 Expand Vehicle Retirement [VOC,NOX,PM] 0.06 0.05 0.00 0.05

ARB-ON3 Modifications to Reformulated Gasoline Program [VOC] 0.16 0.00 0.00 0.00

ARB-ON4 Cleaner In-Use Heavy-Duty Trucks [VOC,NOX,PM] 0.52 3.98 0.00 4.07

ARB-ON5 Port Truck Modernization [NOX,PM] 0.00 0.25 0.00 0.26

ARB-OFF1 Marine Vessels - Fuel, Aux. & Main Eng. [VOC,NOX,PM] 0.00 0.00 0.00 0.00

ARB-OFF2 Accel. Intro. Of Cleaner Line-Haul Loco. [VOC,NOX,PM] 0.10 0.63 0.00 0.60

ARB-OFF3 Clean Up Existing Harbor Craft [VOC,NOX,PM] 0.00 0.00 0.00 0.00

ARB-OFF4 Cleaner In-Use Off-Road Equipment [VOC,NOX,PM] 0.05 0.19 0.00 0.19

ARB-OFF5 New Emis Stds for Recreational Boats [VOC,NOX] 0.10 0.01 0.00 0.00

ARB-OFF6 Expanded Off-Road Rec. Veh Ems Stds [VOC] 0.14 0.00 0.00 0.00

ARB-CONS Consumer Products [VOC] 0.40 0.00 0.00 0.00

MOB-05 AB 923 Light-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.03 0.01 0.35 0.01

MOB-06 AB 923 Med-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.01 0.01 0.11 0.01

SCONRD-1* Accelerated Penetration of ATPEVs and ZEVs [VOC,NOX,CO,PM] 0.05 0.11 1.11 0.11

SCONRD-3* Further Emis. Red. from Heavy-Duty Vehicles [VOC,NOX,CO,PM] 0.00 1.94 0.00 1.99

SCONRD-4* Further Emis. Red. from Port Trucks [NOX,PM] 0.00 0.41 0.00 0.41

SCOFRD-1* Construction/Industrial Fleet Modernization [VOC,NOX] 0.05 0.53 0.00 0.54

SCOFRD-2* Cargo Handling Equipment [NOX,PM] 0.00 0.00 0.00 0.00

SCOFRD-3* Further Ems. Red. From Locomotives [NOX,PM] 0.00 1.11 0.00 1.06

SCOFRD-6* Accelerated Turnover Pleasure Craft [VOC,NOX,PM] 0.20 0.11 0.00 0.03

SCFUEL-1* California Phase III Reformulation Gasoline [NOX,SOX] 0.00 0.00 0.00 0.00

SCFUEL-2* Greater Use of Diesel Fuel Alt. & Reformulation [NOX,SOX,PM] 0.00 0.21 0.00 0.21

Grand Total (Net) 2.52 10.02 1.57 10.08
Year 2017 Emission Reductions Excluding Natural Sources by Control Measure 

in Coachella Valley (Planning Inventory - Tons/Day)

(B) Reductions With Overlapping/Double-Counting With Other Control Measures (2)

( eductions Tons/Day R - )

Measure Name VOC NOx CO NO2

BA-LSI ARB Baseline Adjustment for large spark-ignited engines NOX] [ 0.00 0.02 0.00 0.02

BA-CONS ARB Baseline Adjustment for Consumer Products [VOC] 0.14 0.00 0.00 0.00

BCM-03 Emission Red. from Wood Burning Fireplaces and Wood Stoves 0.00 0.00 0.00 0.00

BCM-05 Reductions from Under-fired Charbroilers [PM] 0.00 0.00 0.00 0.00

CMB-01 Nox Reduction from Non-Reclaim Ovens, Dryers and F rnaces u 0.00 0.10 0.00 0.10

CMB-03 NOx Reductions from Residential Space Heaters [NOx] 0.00 0.01 0.00 0.07

CTS-01 Industrial Lubricants [VOC] 0.07 0.00 0.00 0.00

FUG-02 Emission Red. from Gasoline Transfer and Dispensing Facilities [V 0.09 0.00 0.00 0.00

MCS-01N Facility Modernization [NOx] 0.00 0.05 0.00 0.04

MCS-01P Facility Modernization [PM] 0.00 0.00 0.00 0.00

MCS-01V Facility Modernization [VOC] 0.00 0.00 0.00 0.00

MCS-05 Non-Dairy Livestock Waste [VOC,NH3] 0.00 0.00 0.00 0.00

EGM-01N Emission Reductions from New & Re-Development Projects [NOx] 0.00 0.00 0.00 0.00

EGM-01P Emission Reductions from New & Re-Development Projects [PM] 0.00 0.00 0.00 0.00

EGM-01V Emission Reductions from New & Re-Development Projects [VOC] 0.00 0.00 0.00 0.00

FLX-02P Petroleum Refinery Pilot Program [PM] 0.00 0.00 0.00 0.00

FLX-02V Petroleum Refinery Pilot Program [VOC] 0.00 0.00 0.00 0.00

ARB-ON1 Smog Check Enhancements [VOC,NOX,PM] 0.33 0.29 0.00 0.30

ARB-ON2 Expand Vehicle Retirement [VOC,NOX,PM] 0.07 0.06 0.00 0.06

ARB-ON3 Modifications to Reformulated Gasoline Program [VOC] 0.17 0.00 0.00 0.00

ARB-ON4 Cleaner In-Use Heavy-Duty Trucks [VOC,NOX,PM] 0.52 3.98 0.00 4.07

ARB-ON5 Port Truck Modernization [NOX,PM] 0.00 0.35 0.00 0.36

ARB-OFF1 Marine Vessels - Fuel, Aux. & Main Eng. [VOC,NOX,PM] 0.00 0.00 0.00 0.00

ARB-OFF2 Accel. Intro. Of Cleaner Line-Haul Loco. [VOC,NOX,PM] 0.10 0.63 0.00 0.60

ARB-OFF3 Clean Up Existing Harbor Craft [VOC,NOX,PM] 0.00 0.00 0.00 0.00

ARB-OFF4 Cleaner In-Use Off-Road Equipment [VOC,NOX,PM] 0.05 0.19 0.00 0.19

ARB-OFF5 New Emis Stds for Recreational Boats [VOC,NOX] 0.10 0.01 0.00 0.00

ARB-OFF6 Expanded Off-Road Rec. Veh Ems Stds [VOC] 0.15 0.00 0.00 0.00

ARB-CONS Consumer Products [VOC] 0.40 0.00 0.00 0.00

MOB-05 AB 923 Light-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.03 0.02 0.35 0.02

MOB-06 AB 923 Med-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.01 0.02 0.11 0.02

SCONRD-1* Accelerated Penetration of ATPEVs and ZEVs [VOC,NOX,CO,PM] 0.06 0.12 1.13 0.13

SCONRD-3* Further Emis. Red. from Heavy-Duty Vehicles [VOC,NOX,CO,PM] 0.00 2.88 0.00 2.95

SCONRD-4* Further Emis. Red. from Port Trucks [NOX,PM] 0.00 0.72 0.00 0.74

SCOFRD-1* Construction/Industrial Fleet Modernization [VOC,NOX] 0.07 0.60 0.00 0.61

SCOFRD-2* Cargo Handling Equipment [NOX,PM] 0.00 0.00 0.00 0.00

SCOFRD-3* Further Ems. Red. From Locomotives [NOX,PM] 0.00 1.53 0.00 1.46

SCOFRD-6* Accelerated Turnover Pleasure Craft [VOC,NOX,PM] 0.22 0.11 0.00 0.03

SCFUEL-1* California Phase III Reformulation Gasoline [NOX,SOX] 0.00 0.00 0.00 0.00

SCFUEL-2* Greater Use of Diesel Fuel Alt. & Reformulation [NOX,SOX,PM] 0.00 0.37 0.00 0.37

Grand Total (with potential overlapping) 2.58 12.05 1.59 12.13
EMISSION SUMMARY FOR

(POINT, AREA, MOBILE SOURCE, AND OFF-ROAD MV)

BASELINE EMISSIONS

VOC NOx CO NO2

 

 Point source 0.63 0.40 0.16 0.40

 Area source 7.70 0.90 2.43 1.24

 RECLAIM 0.00 0.00 0.00 0.00

 

 Total Stationary 8.33 1.30 2.58 1.64

 

 On-road 4.99 17.15 35.23 17.58

 Off-road 4.33 5.53 19.97 5.00

 Aircraft 0.43 2.53 6.17 2.53

 

 TOTAL 18.08 26.52 63.96 26.75

 

 

EMISSION REDUCTIONS 

 

 Point source 0.00 0.02 0.00 0.02

 Area source 0.71 0.13 0.00 0.18

 RECLAIM 0.00 0.00 0.00 0.00

 

 Total Stationary 0.72 0.16 0.00 0.21

 

 On-road 1.09 7.22 1.57 7.39

 Off-road 0.71 2.64 0.00 2.48

 Aircraft 0.00 0.00 0.00 0.00

 

 TOTAL 2.52 10.02 1.57 10.08

 

 

REMAINING EMISSIONS 

 

 Point source 0.63 0.38 0.16 0.38

 Area source 6.98 0.77 2.43 1.05

 RECLAIM 0.00 0.00 0.00 0.00

 

 Total Stationary 7.61 1.15 2.58 1.43

 

 On-road 3.90 9.93 33.67 10.19

 Off-road 3.62 2.89 19.97 2.52

 Aircraft 0.43 2.53 6.17 2.53

 

 TOTAL 15.56 16.50 62.39 16.67

 

 

 NSR/Set-Aside 0.00 0.00 0.00 0.00

 

 Public Funding 0.00 0.00 0.00 0.00

 

 GRAND TOTAL (T/D) 15.56 16.50 62.39 16.67

 

 Mobility Adjustments (3) 0.00 0.00 0.00 0.00

 
(1) Emission reductions for individual measures were estimated based on the sequence of listing

 contained here. When the sequence changes, reductions from each measure could be affected,

 but the net total remain the same. The purpose of this table is to estimate

 total emission reductions without overlapping or double-counting between measures.

(2) Emission reductions for individual measures were estimated in the absence of other measures.

 Therefore, the sequence of listing does not affect the reduction estimates. The purpose of 

 this table is to provide emission reduction estimates for Appendix IV control measure

 summary tables as well as cost effectiveness analysis.

(3) Mobility Adjustment includes TCM-01, ATT-01, ATT-02, ATT-05 and adjustments are reflected 

 in the CEPA baseline beyond year 2000. 

*For the purpose of attainment demonstration in the South Coast Air Basin, these mobile source measures were selected to achieve the additional 

 63 tons per day of NOx reductions needed by 2014 for PM2.5 attainment. The corresponding Coachella Valley emission reductions 

 for these measures in 2017 are provided here. However, CARB can implement any combination of strategies to achieve 

 the needed reductions. 
ATTACHMENT-7 

2017 Control Measures For Basin Ozone Attainment 
Run Date: 8/16/2007 11:42:24 AM

(PC-CEPA V. 4.2/ May 2001)

C:\AQMP2007\CF0207\CM3-0607\cf2017-060607.txt

C:\AQMP2007\CF0207\CM3-0607\master-060607.txt

C:\AQMP2007\dump0906\xz011607\ems17ocs.txt

C:\AQMP2007\CF0207\CM3-0607\scen4-060607-noltm.txt

C:\AQMP2007\CF0207\CM3-0507\impact-051107.txt

Year 2017 Emission Reductions Excluding Natural Sources by Control Measure in the South Coast Air Basin (Planning 

Inventory - Tons/Day)

(A) Reductions Without Overlapping/Double-Counting With Other Control Measures (1)

( eductions Tons/Day R - )

Measure Name VOC NOx CO NO2

BA-LSI ARB Baseline Adjustment for large spark-ignited engines NOX] [ 0.00 2.09 0.00 2.22

BA-CONS ARB Baseline Adjustment for Consumer Products [VOC] 4.60 0.00 0.00 0.00

BCM-03 Emission Red. from Wood Burning Fireplaces and Wood Stoves 0.00 0.00 0.00 0.00

BCM-05 Reductions from Under-fired Charbroilers [PM] 0.00 0.00 0.00 0.00

CMB-01 Nox Reduction from Non-Reclaim Ovens, Dryers and F rnaces u 0.00 3.84 0.00 3.84

CMB-03 NOx Reductions from Residential Space Heaters [NOx] 0.00 0.56 0.00 2.68

CTS-01 Industrial Lubricants [VOC] 1.91 0.00 0.00 0.00

FUG-02 Emission Red. from Gasoline Transfer and Dispensing Facilities [V 3.82 0.00 0.00 0.00

MCS-01N Facility Modernization [NOx] 0.00 1.93 0.00 1.70

MCS-01P Facility Modernization [PM] 0.00 0.00 0.00 0.00

MCS-01V Facility Modernization [VOC] 4.63 0.00 0.00 0.00

MCS-05 Non-Dairy Livestock Waste [VOC,NH3] 0.69 0.00 0.00 0.00

EGM-01N Emission Reductions from New & Re-Development Projects [NOx] 0.00 0.00 0.00 0.00

EGM-01P Emission Reductions from New & Re-Development Projects [PM] 0.00 0.00 0.00 0.00

EGM-01V Emission Reductions from New & Re-Development Projects [VOC] 0.00 0.00 0.00 0.00

FLX-02P Petroleum Refinery Pilot Program [PM] 0.00 0.00 0.00 0.00

FLX-02V Petroleum Refinery Pilot Program [VOC] 1.19 0.00 0.00 0.00

ARB-ON1 Smog Check Enhancements [VOC,NOX,PM] 9.47 9.96 0.00 11.22

ARB-ON2 Expand Vehicle Retirement [VOC,NOX,PM] 2.26 1.92 0.00 2.17

ARB-ON3 Modifications to Reformulated Gasoline Program [VOC] 4.19 0.00 0.00 0.00

ARB-ON4 Cleaner In-Use Heavy-Duty Trucks [VOC,NOX,PM] 4.14 36.83 0.00 38.79

ARB-ON5 Port Truck Modernization [NOX,PM] 0.00 1.56 0.00 1.63

ARB-OFF1 Marine Vessels - Fuel, Aux. & Main Eng. [VOC,NOX,PM] 0.00 43.38 0.00 43.38

ARB-OFF2 Accel. Intro. Of Cleaner Line-Haul Loco. [VOC,NOX,PM] 0.72 4.65 0.00 4.65

ARB-OFF3 Clean Up Existing Harbor Craft [VOC,NOX,PM] 0.00 4.08 0.00 4.08

ARB-OFF4 Cleaner In-Use Off-Road Equipment [VOC,NOX,PM] 2.25 8.19 0.00 8.33

ARB-OFF5 New Emis Stds for Recreational Boats [VOC,NOX] 4.08 0.42 0.00 0.11

ARB-OFF6 Expanded Off-Road Rec. Veh Ems Stds [VOC] 2.62 0.00 0.00 0.00

ARB-CONS Consumer Products [VOC] 13.23 0.00 0.00 0.00

MOB-05 AB 923 Light-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.78 0.48 13.46 0.54

MOB-06 AB 923 Med-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.54 0.60 6.76 0.64

SCONRD-1* Accelerated Penetration of ATPEVs and ZEVs [VOC,NOX,CO,PM] 1.56 3.93 44.48 4.47

SCONRD-3* Further Emis. Red. from Heavy-Duty Vehicles [VOC,NOX,CO,PM] 0.00 15.81 0.00 16.62

SCONRD-4* Further Emis. Red. from Port Trucks [NOX,PM] 0.00 2.51 0.00 2.63

SCOFRD-1* Construction/Industrial Fleet Modernization [VOC,NOX] 2.39 23.60 0.00 24.02

SCOFRD-2* Cargo Handling Equipment [NOX,PM] 0.00 0.84 0.00 0.84

SCOFRD-3* Further Ems. Red. From Locomotives [NOX,PM] 0.00 9.88 0.00 9.88

SCOFRD-6* Accelerated Turnover Pleasure Craft [VOC,NOX,PM] 12.44 5.81 0.00 1.49

SCFUEL-1* California Phase III Reformulation Gasoline [NOX,SOX] 0.00 0.00 0.00 0.00

SCFUEL-2* Greater Use of Diesel Fuel Alt. & Reformulation [NOX,SOX,PM] 0.00 3.14 0.00 3.15

Grand Total (Net) 77.53 186.01 64.69 189.08
Year 2017 Emission Reductions Excluding Natural Sources by Control Measure in the South Coast Air Basin (Planning 

Inventory - Tons/Day)

(B) Reductions With Overlapping/Double-Counting With Other Control Measures (2)

( eductions Tons/Day R - )

Measure Name VOC NOx CO NO2

BA-LSI ARB Baseline Adjustment for large spark-ignited engines NOX] [ 0.00 2.09 0.00 2.22

BA-CONS ARB Baseline Adjustment for Consumer Products [VOC] 4.60 0.00 0.00 0.00

BCM-03 Emission Red. from Wood Burning Fireplaces and Wood Stoves 0.00 0.00 0.00 0.00

BCM-05 Reductions from Under-fired Charbroilers [PM] 0.00 0.00 0.00 0.00

CMB-01 Nox Reduction from Non-Reclaim Ovens, Dryers and F rnaces u 0.00 3.84 0.00 3.84

CMB-03 NOx Reductions from Residential Space Heaters [NOx] 0.00 0.56 0.00 2.68

CTS-01 Industrial Lubricants [VOC] 1.91 0.00 0.00 0.00

FUG-02 Emission Red. from Gasoline Transfer and Dispensing Facilities [V 3.82 0.00 0.00 0.00

MCS-01N Facility Modernization [NOx] 0.00 1.93 0.00 1.70

MCS-01P Facility Modernization [PM] 0.00 0.00 0.00 0.00

MCS-01V Facility Modernization [VOC] 4.63 0.00 0.00 0.00

MCS-05 Non-Dairy Livestock Waste [VOC,NH3] 0.69 0.00 0.00 0.00

EGM-01N Emission Reductions from New & Re-Development Projects [NOx] 0.00 0.00 0.00 0.00

EGM-01P Emission Reductions from New & Re-Development Projects [PM] 0.00 0.00 0.00 0.00

EGM-01V Emission Reductions from New & Re-Development Projects [VOC] 0.00 0.00 0.00 0.00

FLX-02P Petroleum Refinery Pilot Program [PM] 0.00 0.00 0.00 0.00

FLX-02V Petroleum Refinery Pilot Program [VOC] 1.19 0.00 0.00 0.00

ARB-ON1 Smog Check Enhancements [VOC,NOX,PM] 9.47 9.96 0.00 11.22

ARB-ON2 Expand Vehicle Retirement [VOC,NOX,PM] 2.42 2.11 0.00 2.39

ARB-ON3 Modifications to Reformulated Gasoline Program [VOC] 4.44 0.00 0.00 0.00

ARB-ON4 Cleaner In-Use Heavy-Duty Trucks [VOC,NOX,PM] 4.14 36.83 0.00 38.79

ARB-ON5 Port Truck Modernization [NOX,PM] 0.00 2.17 0.00 2.26

ARB-OFF1 Marine Vessels - Fuel, Aux. & Main Eng. [VOC,NOX,PM] 0.00 43.38 0.00 43.38

ARB-OFF2 Accel. Intro. Of Cleaner Line-Haul Loco. [VOC,NOX,PM] 0.72 4.65 0.00 4.65

ARB-OFF3 Clean Up Existing Harbor Craft [VOC,NOX,PM] 0.00 4.08 0.00 4.08

ARB-OFF4 Cleaner In-Use Off-Road Equipment [VOC,NOX,PM] 2.25 8.19 0.00 8.33

ARB-OFF5 New Emis Stds for Recreational Boats [VOC,NOX] 4.15 0.42 0.00 0.11

ARB-OFF6 Expanded Off-Road Rec. Veh Ems Stds [VOC] 2.68 0.00 0.00 0.00

ARB-CONS Consumer Products [VOC] 13.23 0.00 0.00 0.00

MOB-05 AB 923 Light-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.88 0.54 13.46 0.61

MOB-06 AB 923 Med-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.60 0.66 6.76 0.71

SCONRD-1* Accelerated Penetration of ATPEVs and ZEVs [VOC,NOX,CO,PM] 1.78 4.46 45.16 5.08

SCONRD-3* Further Emis. Red. from Heavy-Duty Vehicles [VOC,NOX,CO,PM] 0.00 27.03 0.00 28.48

SCONRD-4* Further Emis. Red. from Port Trucks [NOX,PM] 0.00 4.50 0.00 4.70

SCOFRD-1* Construction/Industrial Fleet Modernization [VOC,NOX] 2.99 26.46 0.00 26.92

SCOFRD-2* Cargo Handling Equipment [NOX,PM] 0.00 0.84 0.00 0.84

SCOFRD-3* Further Ems. Red. From Locomotives [NOX,PM] 0.00 12.96 0.00 12.96

SCOFRD-6* Accelerated Turnover Pleasure Craft [VOC,NOX,PM] 13.44 5.97 0.00 1.53

SCFUEL-1* California Phase III Reformulation Gasoline [NOX,SOX] 0.00 0.00 0.00 0.00

SCFUEL-2* Greater Use of Diesel Fuel Alt. & Reformulation [NOX,SOX,PM] 0.00 5.15 0.00 5.23

Grand Total (with potential overlapping) 80.05 208.76 65.37 212.71
EMISSION SUMMARY FOR

(POINT, AREA, MOBILE SOURCE, AND OFF-ROAD MV)

BASELINE EMISSIONS

VOC NOx CO NO2

 

 Point source 45.23 10.05 57.66 10.08

 Area source 225.49 31.53 231.28 46.85

 RECLAIM 0.00 27.23 0.00 27.23

 

 Total Stationary 270.72 68.82 288.94 84.16

 

 On-road 129.18 231.52 1136.72 251.59

 Off-road 138.59 253.82 788.67 239.38

 Aircraft 10.96 24.29 74.29 24.29

 

 TOTAL 549.45 578.45 2288.63 599.42

 

 

EMISSION REDUCTIONS 

 

 Point source 5.82 1.78 0.00 1.78

 Area source 24.25 4.16 0.00 6.14

 RECLAIM 0.00 0.00 0.00 0.00

 

 Total Stationary 30.08 5.94 0.00 7.92

 

 On-road 21.26 75.20 64.69 80.40

 Off-road 26.20 104.87 0.00 100.76

 Aircraft 0.00 0.00 0.00 0.00

 

 TOTAL 77.53 186.01 64.69 189.08

 

 

REMAINING EMISSIONS 

 

 Point source 39.41 8.27 57.66 8.30

 Area source 201.24 27.37 231.28 40.71

 RECLAIM 0.00 27.23 0.00 27.23

 

 Total Stationary 240.65 62.87 288.94 76.24

 

 On-road 107.93 156.32 1072.03 171.19

 Off-road 112.39 148.96 788.67 138.62

 Aircraft 10.96 24.29 74.29 24.29

 

 TOTAL 471.92 392.44 2223.93 410.34

 

 

 NSR/Set-Aside 5.00 -1.20 0.00 -1.20

 

 Public Funding 0.00 -4.20 0.00 -4.20

 

 GRAND TOTAL (T/D) 476.92 387.04 2223.93 404.94

 

 Mobility Adjustments (3) 0.00 0.00 0.00 0.00

 
(1) Emission reductions for individual measures were estimated based on the sequence of listing

 contained here. When the sequence changes, reductions from each measure could be affected,

 but the net total remain the same. The purpose of this table is to estimate

 total emission reductions without overlapping or double-counting between measures.

(2) Emission reductions for individual measures were estimated in the absence of other measures.

 Therefore, the sequence of listing does not affect the reduction estimates. The purpose of 

 this table is to provide emission reduction estimates for Appendix IV control measure

 summary tables as well as cost effectiveness analysis.

(3) Mobility Adjustment includes TCM-01, ATT-01, ATT-02, ATT-05 and adjustments are reflected 

 in the CEPA baseline beyond year 2000. 

*For the purpose of attainment demonstration, these mobile source measures were selected to achieve the additional 

 63 tons per day of NOx reductions needed by 2014 for PM2.5 attainment. The corresponding emission reductions 

 for these measures in 2017 are provided here. However, CARB can implement any combination of strategies to achieve 

 the needed reductions. 
ATTACHMENT-8 

2023 Control Measures For Basin Ozone Attainment (Annual) 
Run Date: 8/21/2007 12:28:06 PM

(PC-CEPA V. 4.2/ May 2001)

C:\AQMP2007\CF0207\CM3-0607\cf2023-060607.txt

C:\AQMP2007\CF0207\CM3-0607\master-060607.txt

C:\AQMP2007\dump0906\xz011607\ems23ocs.txt

C:\AQMP2007\CF0207\CM3-0607\scen4-060607-wbx.txt

C:\AQMP2007\CF0207\CM3-0507\impact-051107.txt

Year 2023 Emission Reductions Excluding Natural Sources by Control Measure 

in the South Coast Air Basin (Annual Average Inventory - Tons/Day)

(A) Reductions Without Overlapping/Double-Counting With Other Control Measures (1)

(Reductions - Tons/Day)

Measure Name VOC NOx CO SOx PM10 PM2.5

BA-LSI ARB Baseline Adjustment for large spark-ignited engines NOX] [ 0.00 1.96 0.00 0.00 0.00 0.00

BA-CONS ARB Baseline Adjustment for Consumer Products [VOC] 4.80 0.00 0.00 0.00 0.00 0.00

BCM-03 Emission Red. from Wood Burning Fireplaces and Wood Stoves 0.00 0.00 0.00 0.00 1.64 1.58

BCM-05 Reductions from Under-fired Charbroilers [PM] 0.00 0.00 0.00 0.00 1.17 1.16

CMB-01 Nox Reduction from Non-Reclaim Ovens, Dryers and Furnaces 0.00 3.84 0.00 0.00 0.00 0.00

CMB-02 Reduction SOx Reductions 0.00 0.00 0.00 2.89 0.00 0.00

CMB-03 NOx Reductions from Residential Space Heaters [NOx] 0.00 3.34 0.00 0.00 0.00 0.00

CTS-01 Industrial Lubricants [VOC] 2.00 0.00 0.00 0.00 0.00 0.00

FUG-02 Emission Red. from Gasoline Transfer and Dispensing Facilities [V 4.06 0.00 0.00 0.00 0.00 0.00

MCS-01N Facility Modernization [NOx] 0.00 1.98 0.00 0.00 0.00 0.00

MCS-01P Facility Modernization [PM] 0.00 0.00 0.00 0.00 1.91 1.70

MCS-01V Facility Modernization [VOC] 7.99 0.00 0.00 0.00 0.00 0.00

MCS-05 Non-Dairy Livestock Waste [VOC,NH3] 0.61 0.00 0.00 0.00 0.00 0.00

EGM-01N Emission Reductions from New & Re-Development Projects 0.00 0.79 0.00 0.00 0.00 0.00

EGM-01P Emission Reductions from New & Re-Development Projects PM] [ 0.00 0.00 0.00 0.00 5.23 0.52

EGM-01V Emission Reductions from New & Re-Development Projects 0.53 0.00 0.00 0.00 0.00 0.00

FLX-02P Petroleum Refinery Pilot Program [PM] 0.00 0.00 0.00 0.00 0.48 0.44

FLX-02V Petroleum Refinery Pilot Program [VOC] 1.64 0.00 0.00 0.00 0.00 0.00

ARB-ON1 Smog Check Enhancements [VOC,NOX,PM] 7.28 7.24 0.00 0.00 0.21 0.19

ARB-ON2 Expand Vehicle Retirement [VOC,NOX,PM] 0.54 0.23 0.00 0.00 0.07 0.06

ARB-ON3 Modifications to Reformulated Gasoline Program [VOC] 2.09 0.00 0.00 0.00 0.00 0.00

ARB-ON4 Cleaner In-Use Heavy-Duty Trucks [VOC,NOX,PM] 1.70 18.24 0.00 0.00 1.08 0.99

ARB-ON5 Port Truck Modernization [NOX,PM] 0.00 6.99 0.00 0.00 0.33 0.30

ARB-OFF1 Marine Vessels - Fuel, Aux. & Main Eng. [VOC,NOX,PM] 0.00 70.67 0.00 29.50 4.20 4.10

ARB-OFF2 Accel. Intro. Of Cleaner Line-Haul Loco. [VOC,NOX,PM] 1.90 15.60 0.00 0.00 0.61 0.56

ARB-OFF3 Clean Up Existing Harbor Craft [VOC,NOX,PM] 0.00 5.91 0.00 0.00 0.32 0.29

ARB-OFF4 Cleaner In-Use Off-Road Equipment [VOC,NOX,PM] 1.92 14.01 0.00 0.00 1.42 1.30

ARB-OFF5 New Emis Stds for Recreational Boats [VOC,NOX] 12.17 1.51 0.00 0.00 0.00 0.00

ARB-OFF6 Expanded Off-Road Rec. Veh Ems Stds [VOC] 4.89 0.00 0.00 0.00 0.00 0.00

ARB-CONS Consumer Products [VOC] 13.69 0.00 0.00 0.00 0.00 0.00

MOB-05 AB 923 Light-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.67 0.42 13.00 0.00 0.01 0.01

MOB-06 AB 923 Med-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.59 0.66 6.20 0.00 0.00 0.00

SCONRD-1* Accelerated Penetration of ATPEVs and ZEVs [VOC,NOX,CO,PM] 1.93 4.66 53.83 0.00 0.39 0.36

SCONRD-3* Further Emis. Red. from Heavy-Duty Vehicles [VOC,NOX,CO,PM] 0.00 5.84 0.00 0.00 0.21 0.19

SCONRD-4* Further Emis. Red. from Port Trucks [NOX,PM] 0.00 0.00 0.00 0.00 0.00 0.00

SCOFRD-1* Construction/Industrial Fleet Modernization [VOC,NOX] 1.32 15.24 0.00 0.00 0.00 0.00

SCOFRD-2* Cargo Handling Equipment [NOX,PM] 0.00 0.55 0.00 0.00 0.01 0.01

SCOFRD-3* Further Ems. Red. From Locomotives [NOX,PM] 0.00 3.26 0.00 0.00 0.11 0.10

SCOFRD-6* Accelerated Turnover Pleasure Craft [VOC,NOX,PM] 7.78 5.75 0.00 0.00 5.31 4.01

SCFUEL-1* California Phase III Reformulation Gasoline [NOX,SOX] 0.00 0.00 0.00 1.47 0.00 0.00

SCFUEL-2* Greater Use of Diesel Fuel Alt. & Reformulation [NOX,SOX,PM] 0.00 4.32 0.00 0.11 0.28 0.26

SCLTM-03 Further Reduction from Consumer Products [VOC] 20.03 0.00 0.00 0.00 0.00 0.00

LTM-04 Phase II Gasoline Fuels [VOC,NOX] 6.28 6.66 0.00 0.00 0.00 0.00

LTM-05 Phase II Diesel Fuel Alternatives [NOX,SOX,PM] 0.00 10.32 0.00 0.20 0.54 0.49

SCLTM1-2 Fu ther Reductions from On-Roa r d and Off-Road Mobile Sources 0.00 171.76 0.00 0.00 0.00 0.00

Grand Total (Net) 106.41 381.75 73.03 34.16 25.53 18.65
Year 2023 Emission Reductions Excluding Natural Sources by Control Measure in the South Coast Air Basin (Annual 

Average Inventory - Tons/Day)

(B) Reductions With Overlapping/Double-Counting With Other Control Measures (2)

(Reductions - Tons/Day)

Measure Name VOC NOx CO SOx PM10 PM2.5

BA-LSI ARB Baseline Adjustment for large spark-ignited engines 0.00 1.96 0.00 0.00 0.00 0.00

BA-CONS ARB Baseline Adjustment for Consumer Products [VOC] 4.80 0.00 0.00 0.00 0.00 0.00

BCM-03 Emission Red. from Wood Burning Fireplaces and Wood 0.00 0.00 0.00 0.00 1.64 1.58

BCM-05 Reductions from Under-fired Charbroilers [PM] 0.00 0.00 0.00 0.00 1.17 1.16

CMB-01 Nox Reduction from Non-Reclaim Ovens, Dryers and 0.00 3.84 0.00 0.00 0.00 0.00

CMB-02 Reduction SOx Reductions 0.00 0.00 0.00 2.89 0.00 0.00

CMB-03 NOx Reductions from Residential Space Heaters [NOx] 0.00 3.34 0.00 0.00 0.00 0.00

CTS-01 Industrial Lubricants [VOC] 2.00 0.00 0.00 0.00 0.00 0.00

FUG-02 Emission Red. from Gasoline Transfer and Dispensing 4.06 0.00 0.00 0.00 0.00 0.00

MCS-01N Facility Modernization [NOx] 0.00 1.98 0.00 0.00 0.00 0.00

MCS-01P Facility Modernization [PM] 0.00 0.00 0.00 0.00 1.91 1.70

MCS-01V Facility Modernization [VOC] 7.99 0.00 0.00 0.00 0.00 0.00

MCS-05 Non-Dairy Livestock Waste [VOC,NH3] 0.61 0.00 0.00 0.00 0.00 0.00

EGM-01N Emission Reductions from New & Re-Development 0.00 0.79 0.00 0.00 0.00 0.00

EGM-01P Emission Reductions from New & Re-Development 0.00 0.00 0.00 0.00 5.23 0.52

EGM-01V Emission Reductions from New & Re-D velopment e 0.53 0.00 0.00 0.00 0.00 0.00

FLX-02P Petroleum Refinery Pilot Program [PM] 0.00 0.00 0.00 0.00 0.48 0.44

FLX-02V Petroleum Refinery Pilot Program [VOC] 1.64 0.00 0.00 0.00 0.00 0.00

ARB-ON1 Smog Check Enhancements [VOC,NOX,PM] 7.28 7.24 0.00 0.00 0.21 0.19

ARB-ON2 Expand Vehicle Retirement [VOC,NOX,PM] 0.57 0.25 0.00 0.00 0.07 0.06

ARB-ON3 Modifications to Reformulated Gasoline Program [VOC] 2.19 0.00 0.00 0.00 0.00 0.00

ARB-ON4 Cleaner In-Use Heavy-Duty Trucks [VOC,NOX,PM] 1.70 18.24 0.00 0.00 1.08 0.99

ARB-ON5 Port Truck Modernization [NOX,PM] 0.00 8.67 0.00 0.00 0.50 0.46

ARB-OFF1 Marine Vessels - Fuel, Aux. & Main Eng. [VOC,NOX,PM] 0.00 70.67 0.00 29.50 4.20 4.10

ARB-OFF2 Accel. Intro. Of Cleaner Line-Haul Loco. [VOC,NOX,PM] 1.90 15.60 0.00 0.00 0.61 0.56

ARB-OFF3 Clean Up Existing Harbor Craft [VOC,NOX,PM] 0.00 5.91 0.00 0.00 0.32 0.29

ARB-OFF4 Cleaner In-Use Off-Road Equipment [VOC,NOX,PM] 1.92 14.25 0.00 0.00 1.42 1.30

ARB-OFF5 New Emis Stds for Recreational Boats [VOC,NOX] 12.32 1.51 0.00 0.00 0.00 0.00

ARB-OFF6 Expanded Off-Road Rec. Veh Ems Stds [VOC] 4.94 0.00 0.00 0.00 0.00 0.00

ARB-CONS Consumer Products [VOC] 13.69 0.00 0.00 0.00 0.00 0.00

MOB-05 AB 923 Light-Duty High-Emitter Id. 0.73 0.47 13.00 0.00 0.01 0.01

MOB-06 AB 923 Med-Duty High-Emitter Id. [VOC,NO ,CO,PM] X 0.63 0.70 6.20 0.00 0.00 0.00

SCONRD-1* Accelerated Penetration of ATPEVs and ZEVs 2.14 5.24 54.92 0.00 0.40 0.37

SCONRD-3* Further Emis. Red. from Heavy-Duty Vehicles 0.00 9.70 0.00 0.00 0.39 0.36

SCONRD-4* Further Emis. Red. from Port Trucks [NOX,PM] 0.00 0.00 0.00 0.00 0.00 0.00

SCOFRD-1* Construction/Industrial Fleet Modernization [VOC,NOX] 1.72 22.19 0.00 0.00 0.00 0.00

SCOFRD-2* Cargo Handling Equipment [NOX,PM] 0.00 0.55 0.00 0.00 0.01 0.01

SCOFRD-3* Further Ems. Red. From Locomotives [NOX,PM] 0.00 10.55 0.00 0.00 0.41 0.38

SCOFRD-6* Accelerated Turnover Pleasure Craft [VOC,NOX,PM] 11.85 6.76 0.00 0.00 5.31 4.01

SCFUEL-1* California Phase III Reformulation Gasoline [NOX,SOX] 0.00 0.00 0.00 1.47 0.00 0.00

SCFUEL-2* Greater Use of Diesel Fuel Alt. & Reformulation 0.00 7.05 0.00 0.11 0.59 0.54

SCLTM-03 Further Reduction from Consumer Products [VOC] 22.89 0.00 0.00 0.00 0.00 0.00

LTM-04 Phase II Gasoline Fuels [VOC,NOX] 7.65 8.52 0.00 0.00 0.00 0.00

LTM-05 Phase II Diesel Fuel Alternatives [NOX,SOX,PM] 0.00 17.63 0.00 0.25 1.23 1.13

SCLTM1-2 Further Reductions from n-Roa O d and Off-Road Mobile Sources 0.00 319.50 0.00 0.00 0.00 0.00

Grand Total (with potential overlapping) 115.75 563.10 74.13 34.21 27.20 20.19
EMISSION SUMMARY FOR

(POINT, AREA, MOBILE SOURCE, AND OFF-ROAD MV)

Baseline Emissions VOC NOx CO SOx PM10 PM2.5

 

 Point source 41.72 9.47 57.87 2.10 10.91 9.56

 Area source 234.49 38.39 128.19 2.67 255.07 63.84

 RECLAIM 0.00 26.51 0.00 11.76 0.00 0.00

 

 Total Stationary 276.21 74.37 186.06 16.53 265.98 73.40

 

 On-road 99.13 164.07 837.54 2.42 23.63 16.04

 Off-road 107.25 238.56 1034.26 33.41 16.94 14.60

 Aircraft 13.08 29.34 85.03 2.69 1.19 1.17

 

 TOTAL 495.67 506.34 2142.90 55.05 307.74 105.21

 

 

EMISSION REDUCTIONS 

 

 Point source 9.63 1.71 0.00 0.00 2.40 2.14

 Area source 45.72 7.48 0.00 0.00 8.07 3.29

 RECLAIM 0.00 0.00 0.00 2.89 0.00 0.00

 

 Total Stationary 55.35 9.18 0.00 2.89 10.47 5.43

 

 On-road 18.18 136.99 73.03 1.58 2.83 2.60

 Off-road 32.88 213.77 0.00 29.69 12.23 10.62

 Aircraft 0.00 21.80 0.00 0.00 0.00 0.00

 

 TOTAL 106.41 381.75 73.03 34.16 25.53 18.65

 

 

REMAINING EMISSIONS 

 

 Point source 32.10 7.76 57.87 2.10 8.52 7.41

 Area source 188.77 30.91 128.19 2.67 247.00 60.55

 RECLAIM 0.00 26.51 0.00 8.87 0.00 0.00

 

 Total Stationary 220.86 65.18 186.06 13.64 255.51 67.97

 

 On-road 80.95 27.08 764.51 0.84 20.80 13.43

 Off-road 74.37 24.79 1034.26 3.72 4.70 3.98

 Aircraft 13.08 7.54 85.03 2.69 1.19 1.17

 

 TOTAL 389.26 124.59 2069.87 20.89 282.21 86.55

 

 

 NSR/Set-Aside 5.00 -1.20 0.00 0.00 0.00 0.00

 

 Public Funding 0.00 -6.20 0.00 0.00 0.00 -0.20

 

 GRAND TOTAL (T/D) 394.26 117.19 2069.87 20.89 282.21 86.35

 

 Mobility Adjustments (3) 0.00 0.00 0.00 0.00 0.00 0.00

 
(1) Emission reductions for individual measures were estimated based on the sequence of listing

 contained here. When the sequence changes, reductions from each measure could be affected,

 but the net total remain the same. The purpose of this table is to estimate

 total emission reductions without overlapping or double-counting between measures.

(2) Emission reductions for individual measures were estimated in the absence of other measures.

 Therefore, the sequence of listing does not affect the reduction estimates. The purpose of 

 this table is to provide emission reduction estimates for Appendix IV control measure

 summary tables as well as cost effectiveness analysis.

(3) Mobility Adjustment includes TCM-01, ATT-01, ATT-02, ATT-05 and adjustments are reflected 

 in the CEPA baseline beyond year 2000. 

*For the purpose of attainment demonstration, these mobile source measures were selected to achieve the additional 

 63 tons per day of NOx reductions needed by 2014 for PM2.5 attainment. The corresponding emission reductions 

 for these measures in 2023 are provided here. However, CARB can implement any combination of strategies to achieve 

 the needed reductions. 
ATTACHMENT-9 

2023 Control Measures For Basin Ozone Attainment (Planning) 
Run Date: 8/21/2007 12:28:06 PM

(PC-CEPA V. 4.2/ May 2001)

C:\AQMP2007\CF0207\CM3-0607\cf2023-060607.txt

C:\AQMP2007\CF0207\CM3-0607\master-060607.txt

C:\AQMP2007\dump0906\xz011607\ems23ocs.txt

C:\AQMP2007\CF0207\CM3-0607\scen4-060607-wbx.txt

C:\AQMP2007\CF0207\CM3-0507\impact-051107.txt

Year 2023 Emission Reductions Excluding Natural Sources by Control Measure in the South Coast Air Basin (Planning 

Inventory - Tons/Day)

(A) Reductions Without Overlapping/Double-Counting With Other Control Measures (1)

( eductions Tons/Day R - )

Measure Name VOC NOx CO NO2

BA-LSI ARB Baseline Adjustment for large spark-ignited engines NOX] [ 0.00 1.91 0.00 2.03

BA-CONS ARB Baseline Adjustment for Consumer Products [VOC] 4.80 0.00 0.00 0.00

BCM-03 Emission Red. from Wood Burning Fireplaces and Wood Stoves 0.00 0.00 0.00 0.00

BCM-05 Reductions from Under-fired Charbroilers [PM] 0.00 0.00 0.00 0.00

CMB-01 Nox Reduction from Non-Reclaim Ovens, Dryers and F rnaces u 0.00 4.11 0.00 4.11

CMB-03 NOx Reductions from Residential Space Heaters [NOx] 0.00 1.15 0.00 5.54

CTS-01 Industrial Lubricants [VOC] 2.00 0.00 0.00 0.00

FUG-02 Emission Red. from Gasoline Transfer and Dispensing Facilities [V 4.06 0.00 0.00 0.00

MCS-01N Facility Modernization [NOx] 0.00 2.18 0.00 1.95

MCS-01P Facility Modernization [PM] 0.00 0.00 0.00 0.00

MCS-01V Facility Modernization [VOC] 9.16 0.00 0.00 0.00

MCS-05 Non-Dairy Livestock Waste [VOC,NH3] 0.61 0.00 0.00 0.00

EGM-01N Emission Reductions from New & Re-Development Projects [NOx] 0.00 0.78 0.00 0.80

EGM-01P Emission Reductions from New & Re-Development Projects [PM] 0.00 0.00 0.00 0.00

EGM-01V Emission Reductions from New & Re-Development Projects [VOC] 0.63 0.00 0.00 0.00

FLX-02P Petroleum Refinery Pilot Program [PM] 0.00 0.00 0.00 0.00

FLX-02V Petroleum Refinery Pilot Program [VOC] 1.64 0.00 0.00 0.00

ARB-ON1 Smog Check Enhancements [VOC,NOX,PM] 7.49 6.92 0.00 7.83

ARB-ON2 Expand Vehicle Retirement [VOC,NOX,PM] 0.54 0.22 0.00 0.24

ARB-ON3 Modifications to Reformulated Gasoline Program [VOC] 2.50 0.00 0.00 0.00

ARB-ON4 Cleaner In-Use Heavy-Duty Trucks [VOC,NOX,PM] 1.69 18.32 0.00 19.16

ARB-ON5 Port Truck Modernization [NOX,PM] 0.00 7.04 0.00 7.27

ARB-OFF1 Marine Vessels - Fuel, Aux. & Main Eng. [VOC,NOX,PM] 0.00 70.67 0.00 70.67

ARB-OFF2 Accel. Intro. Of Cleaner Line-Haul Loco. [VOC,NOX,PM] 1.90 15.60 0.00 15.60

ARB-OFF3 Clean Up Existing Harbor Craft [VOC,NOX,PM] 0.00 5.91 0.00 5.91

ARB-OFF4 Cleaner In-Use Off-Road Equipment [VOC,NOX,PM] 1.90 13.89 0.00 14.14

ARB-OFF5 New Emis Stds for Recreational Boats [VOC,NOX] 17.74 2.40 0.00 0.61

ARB-OFF6 Expanded Off-Road Rec. Veh Ems Stds [VOC] 6.40 0.00 0.00 0.00

ARB-CONS Consumer Products [VOC] 13.69 0.00 0.00 0.00

MOB-05 AB 923 Light-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.71 0.40 12.70 0.46

MOB-06 AB 923 Med-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.56 0.64 6.26 0.68

SCONRD-1* Accelerated Penetration of ATPEVs and ZEVs [VOC,NOX,CO,PM] 2.07 4.46 52.58 5.07

SCONRD-3* Further Emis. Red. from Heavy-Duty Vehicles [VOC,NOX,CO,PM] 0.00 5.87 0.00 6.12

SCONRD-4* Further Emis. Red. from Port Trucks [NOX,PM] 0.00 0.00 0.00 0.00

SCOFRD-1* Construction/Industrial Fleet Modernization [VOC,NOX] 1.31 15.11 0.00 15.37

SCOFRD-2* Cargo Handling Equipment [NOX,PM] 0.00 0.55 0.00 0.55

SCOFRD-3* Further Ems. Red. From Locomotives [NOX,PM] 0.00 3.26 0.00 3.26

SCOFRD-6* Accelerated Turnover Pleasure Craft [VOC,NOX,PM] 12.57 9.08 0.00 2.32

SCFUEL-1* California Phase III Reformulation Gasoline [NOX,SOX] 0.00 0.00 0.00 0.00

SCFUEL-2* Greater Use of Diesel Fuel Alt. & Reformulation [NOX,SOX,PM] 0.00 4.40 0.00 4.38

SCLTM-03 Further Reduction from Consumer Products [VOC] 20.03 0.00 0.00 0.00

LTM-04 Phase II Gasoline Fuels [VOC,NOX] 7.39 6.59 0.00 6.94

LTM-05 Phase II Diesel Fuel Alternatives [NOX,SOX,PM] 0.00 10.52 0.00 10.46

SCLTM1-2 Fu ther Reductions from On-Roa r d and Off-Road Mobile Sources 0.00 172.48 0.00 174.62

Grand Total (Net) 121.37 384.48 71.54 386.10
Year 2023 Emission Reductions Excluding Natural Sources by Control Measure in the South Coast Air Basin (Planning 

Inventory - Tons/Day)

(B) Reductions With Overlapping/Double-Counting With Other Control Measures (2)

( eductions Tons/Day R - )

Measure Name VOC NOx CO NO2

BA-LSI ARB Baseline Adjustment for large spark-ignited engines NOX] [ 0.00 1.91 0.00 2.03

BA-CONS ARB Baseline Adjustment for Consumer Products [VOC] 4.80 0.00 0.00 0.00

BCM-03 Emission Red. from Wood Burning Fireplaces and Wood Stoves 0.00 0.00 0.00 0.00

BCM-05 Reductions from Under-fired Charbroilers [PM] 0.00 0.00 0.00 0.00

CMB-01 Nox Reduction from Non-Reclaim Ovens, Dryers and F rnaces u 0.00 4.11 0.00 4.11

CMB-03 NOx Reductions from Residential Space Heaters [NOx] 0.00 1.15 0.00 5.54

CTS-01 Industrial Lubricants [VOC] 2.00 0.00 0.00 0.00

FUG-02 Emission Red. from Gasoline Transfer and Dispensing Facilities [V 4.06 0.00 0.00 0.00

MCS-01N Facility Modernization [NOx] 0.00 2.18 0.00 1.95

MCS-01P Facility Modernization [PM] 0.00 0.00 0.00 0.00

MCS-01V Facility Modernization [VOC] 9.16 0.00 0.00 0.00

MCS-05 Non-Dairy Livestock Waste [VOC,NH3] 0.61 0.00 0.00 0.00

EGM-01N Emission Reductions from New & Re-Development Projects [NOx] 0.00 0.78 0.00 0.80

EGM-01P Emission Reductions from New & Re-Development Projects [PM] 0.00 0.00 0.00 0.00

EGM-01V Emission Reductions from New & Re-Development Projects [VOC] 0.63 0.00 0.00 0.00

FLX-02P Petroleum Refinery Pilot Program [PM] 0.00 0.00 0.00 0.00

FLX-02V Petroleum Refinery Pilot Program [VOC] 1.64 0.00 0.00 0.00

ARB-ON1 Smog Check Enhancements [VOC,NOX,PM] 7.49 6.92 0.00 7.83

ARB-ON2 Expand Vehicle Retirement [VOC,NOX,PM] 0.58 0.24 0.00 0.27

ARB-ON3 Modifications to Reformulated Gasoline Program [VOC] 2.60 0.00 0.00 0.00

ARB-ON4 Cleaner In-Use Heavy-Duty Trucks [VOC,NOX,PM] 1.69 18.32 0.00 19.16

ARB-ON5 Port Truck Modernization [NOX,PM] 0.00 8.74 0.00 9.02

ARB-OFF1 Marine Vessels - Fuel, Aux. & Main Eng. [VOC,NOX,PM] 0.00 70.67 0.00 70.67

ARB-OFF2 Accel. Intro. Of Cleaner Line-Haul Loco. [VOC,NOX,PM] 1.90 15.60 0.00 15.60

ARB-OFF3 Clean Up Existing Harbor Craft [VOC,NOX,PM] 0.00 5.91 0.00 5.91

ARB-OFF4 Cleaner In-Use Off-Road Equipment [VOC,NOX,PM] 1.90 14.13 0.00 14.37

ARB-OFF5 New Emis Stds for Recreational Boats [VOC,NOX] 17.94 2.40 0.00 0.61

ARB-OFF6 Expanded Off-Road Rec. Veh Ems Stds [VOC] 6.48 0.00 0.00 0.00

ARB-CONS Consumer Products [VOC] 13.69 0.00 0.00 0.00

MOB-05 AB 923 Light-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.77 0.45 12.70 0.51

MOB-06 AB 923 Med-Duty High-Emitter Id. [VOC,NOX,CO,PM] 0.60 0.68 6.26 0.72

SCONRD-1* Accelerated Penetration of ATPEVs and ZEVs [VOC,NOX,CO,PM] 2.28 5.01 53.66 5.70

SCONRD-3* Further Emis. Red. from Heavy-Duty Vehicles [VOC,NOX,CO,PM] 0.00 9.74 0.00 10.18

SCONRD-4* Further Emis. Red. from Port Trucks [NOX,PM] 0.00 0.00 0.00 0.00

SCOFRD-1* Construction/Industrial Fleet Modernization [VOC,NOX] 1.71 21.99 0.00 22.38

SCOFRD-2* Cargo Handling Equipment [NOX,PM] 0.00 0.55 0.00 0.55

SCOFRD-3* Further Ems. Red. From Locomotives [NOX,PM] 0.00 10.55 0.00 10.55

SCOFRD-6* Accelerated Turnover Pleasure Craft [VOC,NOX,PM] 19.18 10.69 0.00 2.73

SCFUEL-1* California Phase III Reformulation Gasoline [NOX,SOX] 0.00 0.00 0.00 0.00

SCFUEL-2* Greater Use of Diesel Fuel Alt. & Reformulation [NOX,SOX,PM] 0.00 7.14 0.00 7.18

SCLTM-03 Further Reduction from Consumer Products [VOC] 22.89 0.00 0.00 0.00

LTM-04 Phase II Gasoline Fuels [VOC,NOX] 9.10 8.78 0.00 8.50

LTM-05 Phase II Diesel Fuel Alternatives [NOX,SOX,PM] 0.00 17.84 0.00 17.95

SCLTM1-2 Further Reductions from n-Roa O d and Off-Road Mobile Sources 0.00 323.03 0.00 321.61

Grand Total (with potential overlapping) 133.70 569.51 72.61 566.44
EMISSION SUMMARY FOR

(POINT, AREA, MOBILE SOURCE, AND OFF-ROAD MV)

BASELINE EMISSIONS

VOC NOx CO NO2

 

 Point source 48.47 10.65 60.13 10.68

 Area source 236.06 31.02 236.91 46.92

 RECLAIM 0.00 27.23 0.00 27.23

 

 Total Stationary 284.53 68.89 297.03 84.83

 

 On-road 103.19 161.32 824.43 174.19

 Off-road 135.17 246.02 850.98 231.35

 Aircraft 13.08 29.34 85.03 29.34

 

 TOTAL 535.98 505.57 2057.47 519.71

 

 

EMISSION REDUCTIONS 

 

 Point source 10.80 2.07 0.00 2.07

 Area source 45.82 5.39 0.00 9.56

 RECLAIM 0.00 0.00 0.00 0.00

 

 Total Stationary 56.62 7.46 0.00 11.62

 

 On-road 19.08 134.79 71.54 145.39

 Off-road 45.68 220.43 0.00 207.29

 Aircraft 0.00 21.80 0.00 21.80

 

 TOTAL 121.37 384.48 71.54 386.10

 

 

REMAINING EMISSIONS 

 

 Point source 37.67 8.58 60.13 8.61

 Area source 190.25 25.62 236.91 37.37

 RECLAIM 0.00 27.23 0.00 27.23

 

 Total Stationary 227.92 61.43 297.03 73.21

 

 On-road 84.11 26.53 752.89 28.80

 Off-road 89.50 25.59 850.98 24.06

 Aircraft 13.08 7.54 85.03 7.54

 

 TOTAL 414.60 121.10 1985.93 133.61

 

 

 NSR/Set-Aside 5.00 -1.20 0.00 -1.20

 

 Public Funding 0.00 -6.20 0.00 -6.20

 

 GRAND TOTAL (T/D) 419.60 113.70 1985.93 126.21

 

 Mobility Adjustments (3) 0.00 0.00 0.00 0.00

 
(1) Emission reductions for individual measures were estimated based on the sequence of listing

 contained here. When the sequence changes, reductions from each measure could be affected,

 but the net total remain the same. The purpose of this table is to estimate

 total emission reductions without overlapping or double-counting between measures.

(2) Emission reductions for individual measures were estimated in the absence of other measures.

 Therefore, the sequence of listing does not affect the reduction estimates. The purpose of 

 this table is to provide emission reduction estimates for Appendix IV control measure

 summary tables as well as cost effectiveness analysis.

(3) Mobility Adjustment includes TCM-01, ATT-01, ATT-02, ATT-05 and adjustments are reflected 

 in the CEPA baseline beyond year 2000. 

*For the purpose of attainment demonstration, these mobile source measures were selected to achieve the additional 

 63 tons per day of NOx reductions needed by 2014 for PM2.5 attainment. The corresponding emission reductions 

 for these measures in 2023 are provided here. However, CARB can implement any combination of strategies to achieve 

 the needed reductions.