APPENDIX IX 

MATES III 

FINAL REPORT 

Regional Modeling Analyses 

Authors

Joe Cassmassi 

Xinqiu Zhang 

Satoru Mitsutomi 

Sang-Mi Lee 
MATES III Final Report

Appendix IX-1 

Appendix IX 

Regional Modeling Analyses

Introduction 

The MATES III regional modeling analysis is presented in Chapter 4 of the main document. 

This Appendix provides the analyses to complement and support the regional modeling 

demonstration. These include: characterization and validation of the meteorological input data, 

development of the MATES III modeling emissions inventory, discussion of the development of 

the boundary conditions, model performance, and risk. 

Several comments received from reviewers of the draft MATES III report were directed to the 

regional modeling analysis and evaluation. The key areas addressed follow: 

 

• The need for a direct comparison between the regional modeling analyses generated for 

both MATES II and MATES III; 

• The simulation performance of elemental carbon (EC2.5) compared with observations 

measured during the MATES III monitoring program; and 

• The adequacy of the comparison of simulated risk to risk calculated based on monitored 

data at the MATES III sites. 

Several additional comments suggested modifications to the modeling assumptions including 

model configuration and specific emissions allocation. These included the following 

suggestions: 

• Modify (increase) the number of layers in the model domain; 

• Evaluate alternate methodologies to calculate vertical dispersion; and 

• Review the emissions inventory, in particular the percentage apportionment of EC 

emissions released from ships. 

The regional modeling analysis and evaluation presented in this report attempts to answer the 

key issues and suggestions identified through the review process. Most noteworthy, this 

Appendix presents a newly-generated recreation of the MATES II modeling analysis that is 

consistent in model application, inventory development and modeling assumptions to the 

MATES III analysis described in the following sections. 

For MATES III, the Comprehensive Air Quality Model with Extensions enhanced with a 

reactive tracer modeling capability (CAMx RTRAC, Environ, 2006) provided the dispersion 

modeling platform and chemistry used to simulate annual impacts of both gaseous and aerosol 

toxic compounds in the Basin. The version of the RTRAC “probing tool” in CAMx used in the 

modeling simulations includes an air toxics chemistry module that is used to treat the formation 

and destruction of reactive air toxic compounds. 
MATES III Final Report

Appendix IX-2 

Modeling was conducted on a domain that encompassed the Basin and the coastal shipping lanes 

located in the Southern California Bight portions of the Basin using a grid size of two-squared 

kilometers. An updated version of the 2007 AQMP emissions inventory for model year 2005, 

which included detailed source profiles of air toxic sources, provided mobile and stationary 

source input for the MATES III CAMx RTRAC simulations. An additional back-cast of the 

2007 AQMP emissions inventory was generated for 1998 to project emissions for use in the new 

simulation covering the MATES II monitoring period. 

Grid-based, hourly meteorological fields generated from the MM5 (PSU/NCAR 2004) 

mesoscale meteorological model using four dimensional data assimilation, and National Weather 

Service model initializations for April 1998 through March 1999 and all days in 2005 provided 

the dispersion profile for the simulations. 

Background 

MATES III regional modeling analyses relied on the CAMx RTRAC model to simulate annual 

impacts of both gaseous and aerosol toxic compounds in the Basin. In the 2000 MATES II 

analysis, the Urban Airshed Model with TOX (UAMTOX) chemistry was used to simulate the 

advection and accumulation of toxic compound emissions throughout the Basin. UAMTOX was 

simulated for a two-squared kilometer grid domain that overlaid the Basin. The analysis relies 

on the 1997-98 emissions projection from the 1997 AQMP and meteorological data fields for 

1997-98 generated from objective analysis using a diagnostic wind model. These tools were 

consistent with those used in both the 1997 and 2003 AQMP attainment demonstrations. 

Peer review of the 2003 AQMP modeling strongly suggested that future AQMP attainment 

demonstrations utilize more state-of-the-sciences tools that utilize updated chemistry modules, 

improved dispersion algorithms, and mass consistent meteorological data. The recommendations 

were placed in action for the 2007 AQMP where the dispersion platform moved from UAM to 

CAMx and the diagnostic wind meteorological model was replaced by MM5 prognostic model. 

CAMx coupled with MM5 input using the “one atmosphere” gaseous and particulate chemistry 

was used to simulate both episodic ozone and annual concentrations of PM2.5.. 

The original plan for MATES III was to replicate the analysis conducted for the 1998-99 field 

program using the UAMTOX model and diagnostic meteorological model. The theory was to 

enable a true apples-to-apples comparison of the current and previous modeling analyses. The 

plan was modified prior to adoption of the 2007 AQMP to take into account the advances in 

annual particulate modeling that was conducted as part of the 2007 PM2.5 attainment 

demonstration. Given the extensive effort in the 2007 AQMP to simulate particulates, using the 

peer recommended state-of-the-science art modeling tools, it was decided that a better 

comparison linking the AQMP PM2.5 projections to the base year toxics analysis would be more 

complementary and up-to-date. As such, the MATES III simulations were conducted using the 

CAMx – MM5 coupled with the RTRAC chemistry. 
MATES III Final Report

Appendix IX-3 

CAMx Modeling Domain 

Modeling was conducted on a domain that encompassed the South Coast Air Basin and the 

coastal shipping lanes located in the Southern California Bight portions of the Basin using a grid 

size of two-squared kilometers. (Figure IX-1 depicts the MATES III modeling domain. The 

shaded portion of the grid area represents the extension of the domain beyond that used for 

MATES II). Concentrations simulated for a specific location in the domain consisted of ninecell distance weighted average. 

Figure IX-1 

MATES III Modeling Domain 

(Shaded area highlights the grid extension to the MATES II modeling domain). 

Development of Meteorological Fields 

The Penn State/National Center for Atmospheric Research Mesoscale Model 5 (MM5) was 

employed to produce meteorological fields for the CAMx RTRAC 2005 MATES III and 1998-

99 back-cast of the MATES II regional modeling analyses. 
MATES III Final Report

Appendix IX-4 

MATES III air monitoring spanned a three-year calendar period from April 2004 through March 

of 2006. The regional toxic modeling analysis was conducted for data sampled during the oneyear period including January 1, through December 31, 2005. The MATES II monitoring period 

included April 1, 1998 through March 31, 1999. 

Meteorological Outlook of Year 2005 

The beginning of year 2005 was characterized as anomalously above-average precipitation in 

Southern California. A pronounced split-flow configuration was evident over western North 

America, with one branch of the westerlies entering the continent over northern British Columbia 

and the other entering over the Baja Peninsula. These conditions were associated with a 

southward shift of the main jet stream and storm track across the western United States. These 

resulted in significantly above-average precipitation in Southern California, Southwest, and the 

western inter-mountain regions of the U.S. Southern California experienced above-average 

precipitation during the period of October 2004 to May 2005. During summer months – July and 

August, 500 hectopascal (hPa) geopotential heights were above-average level over the western 

U.S., which led to well above-average temperatures in the area, which was situated beneath a 

very persistent upper-level ridge. Fall and winter months returned close to climatology when 

North America generally experienced below average precipitation in the west and above average 

rainfall in the southeastern U.S. 

When comparing the meteorology between 2005 to the MATES II monitoring period of April 

1998-March 1999, two issues stand out. The MATES II period was drier than MATES III but 

over the course of the period experienced less stagnation. Using a statistical analysis developed 

for the 1997 AQMP that evaluates pollution dispersion potential based on the presence and 

strength of temperature inversions, 2005 was very close to average despite having greater rainfall 

than 1998-99. Using the same measure, 1998-1999 was slightly above average for dispersion 

potential but experienced a milder winter with less storm activity. This is borne out through 

Basin statistics of measurable rainfall, where 2005 experienced a greater frequency of days 

having measurable rainfall in Downtown Los Angeles by 30% (43 versus 33 days) and total 

rainfall measured at USC by 182% (26.0 versus 14.1 inches). The additional rainfall may have 

suppressed the amount of re-entrained or fugitive dust that contributes to concentration 

measurements of EC. 

MM5 Numerical Model Configuration 

Penn State/National Center for Atmospheric Research Mesoscale Model 5 (MM5) was employed 

to produce meteorological fields for CAMx RTRAC simulations. The MM5 simulations were 

comprised of three nested domains of which horizontal grid distances of 18, 6, and 2 km 

respectively. The relative sizes and locations of each domain are given in Figure IX-2. The 

innermost domain spans 254 km X 164 km in east-west and north-south directions, respectively, 

which overlaps the CAMx domain by two additional rows and columns in each lateral boundary. 

The initial guess field and lateral boundary values for the outermost domain were extracted from 

the operational NCEP Eta 218 grid (12km) grid analysis for the 2005 simulations and the 212 

grid (40 km) analysis output for the 1998-99 simulation. Figure IX-3 depicts the grid specific 

terrain file used in the MM5 simulations. 
MATES III Final Report

Appendix IX-5 

The databases contain variables of air temperature, geopotential height, heat flux, humidity, 

precipitable water, sea level pressure, shortwave radiation, snow water equivalent, surface air 

temperature, surface winds, thermal infrared, upper level winds, vertical wind, and vorticity at 

each isobaric level of 1000, 975, 950, 925, 900, 875, 850, 800, 750, 700, 650, 600, 550, 500, 

450, 400, 350, 300, 275, 250, 225, 200, 175, 150, 100, 50 hPa. (Refer to 

http://dss.ucar.edu/datasets/ds609.2 for further dataset information). 

Four dimensional data assimilation (FDDA) was conducted by utilizing National Weather 

Service (NWS) twice-daily sounding data and hourly surface measurements taken within the 

domain. Each simulation was conducted for a 6-day period with the first 24 hours of spin up 

period. The detailed configuration and physical options used in the MM5 simulation are listed in 

Table IX-1. 

Figure IX-2. 

The relative locations and sizes of three MM5 nested domains. 
MATES III Final Report

Appendix IX-6 

Table IX-1 

MM5 configuration 

Component 2005 1998-99 

Number of grids (127 X 82) in east-west and 

north-south respectively 

(127 X 82) in east-west and northsouth respectively 

Number of vertical 

layers 

29 layers with the lowest layer 

being approximately at 20 m agl. 

29 layers with the lowest layer 

being approximately at 20 m agl. 

Initial and boundary 

values 

ETA 218 grid (12 km grid 

distance) analysis field 

Eta 212 grid (40 kim grid distance) 

analysis field 

Boundary layer 

scheme 

Blackadar Blackadar 

Soil model Five-layer soil model Five-layer soil model 

Cumulus 

parameterization 

Explicit Explicit 

Micro physics Simple ice Simple ice 

Radiation Cloud radiation Cloud radiation 

Four dimensional data 

analysis 

Analysis nudging with NWS 

surface and upper air 

measurements 

Analysis nudging with NWS 

surface and upper air 

measurements 

Figure IX-3

The topography and the county boundaries of the MM5 computational domain. 
MATES III Final Report

Appendix IX-7 

Meteorological Model Performance 

The MM5 performance was extensively evaluated using NWS surface measurements and 

Environ’s METSTAT (ENVIRON, 2001) statistical software to compute mean, bias, gross error, 

root mean square error (RMSE), and index of agreement. 

Figure IX-4 shows the time series of hourly observed and predicted temperature at 2 m above 

ground level (agl) for September 2005. The model successfully resolved overall cooling and 

warming trend induced by synoptic scale motions, while daily maximum and minimum 

temperatures were slightly over and underpredicted, respectively. This can be partly attributed to 

inaccurate representation of surface characteristics such as soil moisture content and land use 

category. 

Observed/Predicted Temperature

280

285

290

295

300

305

310

 9/ 1 9/ 3 9/ 5 9/ 7 9/ 9 9/11 9/13 9/15 9/17 9/19 9/21 9/23 9/25 9/27 9/29

K

ObsTemp PrdTemp 

FIGURE IX-4 

Time series of observed and predicted temperature at 2 m above ground level for September, 

2005. The data are hourly average observations of all available measurements within the domain 

and the corresponding predictions. 

In all, the model has less than 2 degrees of bias and gross error and approximately 2 degrees of 

RMSE, which are approximately equivalent to MM5 performance for 2007 Air Quality 

Management Plan (AQMP) modeling case (Figure IX-5). Wind speed turned out to be underpredicted by less than 1 m s-1. In general, all conventional surface parameters including wind 

speed, direction, temperature and water vapor mixing ratio showed good agreement with the 

observations (Figures IX-6 and IX-7). 
MATES III Final Report

Appendix IX-8 

Observed/Predicted Temperature

286

288

290

292

294

296

298

300

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/ 25 9/ 27 9/29 

K

Temprt r Mean OBS Temprt r Mean PRD

Bias/Gross Error Temperature

- 2

- 1

0

1

2

3

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/ 25 9/ 27 9/29 

K

Temprt r Bias Temprt r Gross Error

RMSE Temperature

0

0.5

1

1.5

2

2.5

3

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/ 25 9/ 27 9/29 

K

Temprt r RMSE Temprt r Sys RMSE Temprt r Unsys RMSE

IOA Temperature

0

0.2

0.4

0.6

0.8

1

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/ 25 9/ 27 9/29 

Temprt r IOA

Figure IX-5 

Daily averaged (a) mean, (b) bias and gross error, (c) root mean square error, and (d) index of 

agreement for observed and predicted temperature at 2 m agl. 
MATES III Final Report

Appendix IX-9 

Observed/Predicted Windspeed

0

1

2

3

4

5

6

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/ 25 9/ 27 9/ 29 

m/s

Wind Spd Mean OBS Wind Spd Mean PRD

Bias/Gross Error Windspeed

- 2

- 1

0

1

2

3

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/ 25 9/ 27 9/ 29 

m/s

Wind Spd Bias Wind Spd Gross Error

RMSE Windspeed

0

1

2

3

4

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/ 25 9/ 27 9/ 29 

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

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/ 25 9/ 27 9/ 29 

Wind Spd IOA

Observed/Predicted Wind Direction

0

6 0

12 0

18 0

240

300

360

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/ 25 9/ 27 9/ 29 

deg

Wind Dir Mean OBS Wind Dir Mean PRD

Bias/Gross Error Wind Direction

-90

-60

-30

0

3 0

6 0

9 0

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/ 25 9/ 27 9/ 29 

deg

Wind Dir Bias Wind Dir Gross Error

Figure IX-6 

Daily averaged (a) mean, (b) bias and gross error, (c) root mean square error, and (d) index of 

agreement for observed and predicted wind speed. (e) Mean and (f) bias and gross error of wind 

direction are presented as well.
MATES III Final Report

Appendix IX-10 

Observed/Predicted Humidity

0

2

4

6

8

10

12

14

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/25 9/27 9/29 

g/kg

Humdit y Mean OBS Humdit y Mean PRD

Bias/Gross Error Humidity

- 5

- 4

- 3

- 2

- 1

0

1

2

3

4

5

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/25 9/27 9/29 

g/kg

Humdit y Bias Humdit y Gross Error

RMSE Humidity

0

1

2

3

4

5

6

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/25 9/27 9/29 

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

 9/ 01 9/ 03 9/ 05 9/ 07 9/ 09 9/ 11 9/ 13 9/ 15 9/ 17 9/ 19 9/ 21 9/ 23 9/25 9/27 9/29 

Humdit y IOA

Figure IX-7 

Daily averaged (a) mean, (b) bias and gross error, (c) root mean square error, and (d) index of 

agreement for observed and predicted wind speed. (e) Mean and (f) bias and gross error of wind 

direction are presented as well. 
MATES III Final Report

Appendix IX-11 

Wind Rose Comparison 

While the METSTAT evaluation is a useful tool to assess the performance of the regional MM5 

simulations, it is important to examine the capability to recreate observed annual local scale wind 

patterns. To assess the local scale flow, wind roses were generated from the hourly average 2005 

MM5 model output for the 2 km-squared grid cell housing the MATES III monitoring sites and 

the monitoring data for those sites. An exact replication of the measured winds was not expected 

in the analysis. However, comparison of the modeled and measured annual average wind roses 

offers a visual comparison of the fit of the simulation to the local scale and assists in the 

evaluation of the CAMx RTRAC simulation performance. 

Figures IX-8a through IX-8f depict the 2005 annual wind roses for Anaheim, Burbank, Inland 

Valley San Bernardino, North Long Beach, Central Los Angeles, and Rubidoux. (Figure IX-9 

provides the 2005 MM5 generated wind roses for Compton and West Long Beach). Subtle 

nuances between the simulated and observed winds are observed at all stations. In general, wind 

speeds are slightly higher for the MM5 simulation. The directional frequencies are reasonably 

well-captured at most sites, with an offset in the primary wind vector of less than one sector 

(22.5 degrees). It is important to note that the local emissions sources (particularly ground level) 

directly upwind of the monitoring site have a significant impact to the measured concentration 

profile. As such, a minor one-sector difference in the simulated wind direction may impact the 

CAMx RTRAC performance. This is the case at Burbank, where the simulated winds are offset 

from the observed winds to the south by more than 45 degrees. 

The Burbank monitoring station is located in the southeast corner of the San Fernando Valley. 

The thermally forced sea breeze that drives into the San Fernando Valley is channeled by the 

unique terrain features which cause the flow to back almost 90 degrees from a southwesterly 

trajectory in the coastal plain to south easterly at the monitoring station. While the MM5 

simulation accomplishes the element of backing the wind flow in the Burbank area, the 

simulation is currently not capable of reversing the flow to the degree observed. As discussed in 

a following section, this feature does have an impact on the CAMx RTRAC simulation 

performance at Burbank. (Ongoing sensitivity analyses are currently being conducted to 

evaluate the MM5 simulation sensitivity to improved local land use and soil moisture 

characterization to overcome this shortfall. The results of these sensitivity analyses will be 

incorporated in future simulations). 
MATES III Final Report

Appendix IX-12 

0

45

90

135

180

225

270

315

0% 5% 10% 15% 20% 25%

WIND SPEED (m/sec)

>0 - 2

>2 - 5

>5 - 10

>10 - 15

>15

MATES-3 MM5: Anaheim 0

45

90

135

180

225

270

315

Anaheim: Annual

0% 5% 10% 15% 20% 25%

Frequency

Wind Speed 

 (MPH)

>0 - 2.1

>2.1 - 3.6

>3.6 - 5.7

>5.7 - 8.8

>8.8

Figure IX-8a. 

2005 MM5 Simulated and Observed Annual Hourly Averaged Wind Roses at Anaheim. 

0

45

90

135

180

225

270

315

0% 5% 10% 15% 20% 25%

WIND SPEED (m/sec)

>0 - 2

>2 - 5

>5 - 10

>10 - 15

>15

MATES-3 MM5: Burbank 0

45

90

135

180

225

270

315

Burbank: Annual

0% 4% 8% 12% 16% 20%

Frequency

Wind Speed 

 (MPH)

>0 - 2.1

>2.1 - 3.6

>3.6 - 5.7

>5.7 - 8.8

>8.8

Figure IX-8b. 

2005 MM5 Simulated and Observed Annual Hourly Averaged Wind Roses at Burbank. 
MATES III Final Report

Appendix IX-13 

0

45

90

135

180

225

270

315

0% 10% 20% 30% 40%

WIND SPEED (m/sec)

>0 - 2

>2 - 5

>5 - 10

>10 - 15

>15

MATES-3 MM5: 

Inland Valley S.B. 0

45

90

135

180

225

270

315

Inland Valley S.B.

0% 4% 8% 12% 16%

Frequency

Wind Speed 

 (MPH)

>0 - 2.1

>2.1 - 3.6

>3.6 - 5.7

>5.7 - 8.8

>8.8

Figure IX-8c. 

2005 MM5 Simulated and Observed Annual Hourly Averaged Wind Roses at Inland Valley S.B. 

0

45

90

135

180

225

270

315

0% 4% 8% 12% 16%

WIND SPEED (m/sec)

>0 - 2

>2 - 5

>5 - 10

>10 - 15

>15

MATES-3 MM5: LongBeach 0

45

90

135

180

225

270

315

Long Beach: Annual

0% 5% 10% 15% 20% 25%

Frequency

Wind Speed 

 (MPH)

>0 - 2.1

>2.1 - 3.6

>3.6 - 5.7

>5.7 - 8.8

>8.8

Figure IX-8d. 

2005 MM5 Simulated and Observed Annual Hourly Averaged Wind Roses at North Long 

Beach. 
MATES III Final Report

Appendix IX-14 

0

45

90

135

180

225

270

315

0% 5% 10% 15% 20% 25%

WIND SPEED (m/sec)

>0 - 2

>2 - 5

>5 - 10

>10 - 15

>15

MATES-3 MM5: Central LA 0

45

90

135

180

225

270

315

Central LA: Annual

0% 4% 8% 12% 16% 20%

Frequency

Wind Speed 

 (MPH)

>0 - 2.1

>2.1 - 3.6

>3.6 - 5.7

>5.7 - 8.8

>8.8

Figure IX-8e. 

2005 MM5 Simulated and Observed Annual Hourly Averaged Wind Roses at 

Central Los Angeles. 

0

45

90

135

180

225

270

315

0% 10% 20% 30% 40% 50%

WIND SPEED (m/sec)

>0 - 2

>2 - 5

>5 - 10

>10 - 15

>15

MATES-3 MM5: Rubidoux 0

45

90

135

180

225

270

315

Riverside: Annual

0% 5% 10% 15% 20% 25%

Frequency

Wind Speed 

 (MPH)

>0 - 2.1

>2.1 - 3.6

>3.6 - 5.7

>5.7 - 8.8

>8.8

Figure IX-8f. 

2005 MM5 Simulated and Observed Annual Hourly Averaged Wind Roses at Rubidoux. 
MATES III Final Report

Appendix IX-15 

0

45

90

135

180

225

270

315

0% 4% 8% 12% 16% 20%

WIND SPEED (m/sec)

>0 - 2

>2 - 5

>5 - 10

>10 - 15

>15

MATES-3 MM5: Compton 0

45

90

135

180

225

270

315

0% 4% 8% 12%

WIND SPEED (m/sec)

>0 - 2

>2 - 5

>5 - 10

>10 - 15

>15

MATES-3 MM5: 

West Long Beach

Figure IX-9. 

2005 MM5 Simulated Annual Hourly Averaged Wind Roses at 

Compton and West Long Beach. 

Vertical Dispersion 

The initial CAMx RTRAC simulations were conducted using a vertical structure of eight layers, 

the CMAQ vertical stability parameterization, and a minimum value for vertical diffusivity (KV) 

of 1.0 m2/sec. In the development phase of the meteorological data sets, the MM5 output was 

subjected to a variety of combinations of mixing schemes (CMAQ and the O’Brien 70 [OB70], 

O’Brien, 1970) using varying default minimum values of vertical diffusivity. The analysis 

evaluated CAMx RTRAC performance for EC2.5 for both an eight and 16 vertical layer modeling 

structure. (Note: the MM5 simulations were conducted using a 29 layer vertical structure). 

CAMx RTRAC EC2.5 simulation performance was nearly identical for both layer structures using 

the CMAQ dispersion option using a minimum KV of 1.0 m2

/sec. The OB70 scheme resulted in 

overprediction at key sites (both layer structures) as did the CMAQ scheme using 16 layers and a 

minimum KV of 0.1 m2

/sec. All of the combinations, regardless of layer structure or minimum 

KV, resulted in overprediction at Long Beach and West Long Beach and underprediction to 

varying degrees at Rubidoux and Inland Valley San Bernardino. Since there was little difference 

between CMAQ dispersion option using a minimum KV of 1.0 m2

/sec for either the eight or 16 

layer structures, the eight-layer structure using the CMAQ scheme and a minimum KV of 1.0 

m

2

/sec was selected to reduce computational demand. 

Comments received from reviewers after release of the draft MATES III analysis focused on the 

underprediction of EC2.5 in the eastern portion of the Basin. Additional sensitivity simulations 

using ENVIRON’s KV-Patch software (Environ, 2006) were conducted to attempt to improve 

the simulation performance. Briefly, KV-Patch was used to assign a minimum value of KV (0.1 
MATES III Final Report

Appendix IX-16 

m

2

/sec) to individual grid cells based on land use specification. The results of the application are 

summarized in Table IX-2 where the simulation performance is presented as a ratio of the 

observed EC2.5 concentration measurement at each monitoring site. 

The eight-layer simulation using the KV-Patch option and a minimum 0.1 m2/sec value of KV 

labeled as interim improved the model performance in the east Basin while only having a 

nominal impact on the performance in the coastal zone. The 16-layer simulation using a 0.1 

m

2

/sec value of KV also resulted in improved performance in the east Basin but at the 

degradation of performance in the coastal plain. As a result of the additional sensitivity analyses, 

the vertical dispersion profile used in the final MATES III CAMx RTRAC simulations relied on 

an eight-layer structure using the CMAQ scheme overlaid with the KV-Patch option set at 0.1 

m

2

/sec value of KV. 

MATES III Modeling Emissions 

An updated version of the 2007 AQMP emissions inventory for model year 2005, which 

included detailed source profiles of AB2588 air toxic sources, provided mobile and stationary 

source input for the MATES III CAMx RTRAC simulations. Mobile source emissions were 

adjusted for time-of-day and day-of-week travel patterns based on CalTrans weigh-in-motion 

data profiles. Table IX-3 lists the January weekday daily diesel emissions projected for 2005 and 

back-cast for 1998. (A comprehensive breakdown of the planning VOC, NOx, CO, SO2 and 

particulate emissions for 2005 used in the MATES III simulation is provided in Chapter 3 and 

Appendix XIII). Table IX-3 also includes the MATES II TSP diesel emissions for 1998 for 

comparison. 

A comparison of the MATES III (2007 AQMP) 2005 projection of the weekday PM2.5 diesel 

emissions shows a 4.8% reduction in emissions from the back-cast for 1998. The most 

significant area of diesel particulate matter emissions growth occurs in the shipping categories 

associated with goods movement. MATES III back-casts of the weekday 1998 TSP diesel 

inventory using the 2007 AQMP inventory were almost 21% higher than the corresponding 

MATES II values. 

Figures IX-10a through IX-10x provides the grid based weekday modeling emissions for 

selected toxic pollutant and precursor emissions categories. 

MATES III vs. MATES II: Key Emissions Modeling Assumptions 

Three changes to emissions data preparation were implemented in the MATES III modeling. 

First, emissions from vessels in the shipping lanes were assumed emitted into the first two 

vertical modeling layers to better estimate plume rise from the hot stack emissions. Combined 

stack heights and plume rise for typical oceangoing (deep draft) vessels extend above 36 and 

below 73 meters (WRAP, 2007). MATES II held shipping emissions in the first vertical UAM 

layer. 
MATES III Final Report

Appendix IX-16 

TABLE IX-2 

Simulated Annual Average EC2.5 Using Selected Vertical Dispersion Profiles and Layer Struct

Dispersion Scheme CMAQ O’Bri

Option/Location Observed Draft Interim Test Test Test Test Test Layer Structure Surface 8 8 16 16 16 8 8 Minimum KV (m2/sec) N/A 1.0 0.1 1.0 0.1 0.1 0.1 0.1 KV-Patch Used N/A No Yes No No Yes Yes No Anaheim 1.00 1.03 1.07 1.01 1.57 1.10 1.21 1.77 Burbank 1.00 0.53 0.54 0.54 0.73 0.57 0.61 0.78 Compton 1.00 1.12 1.15 1.10 1.76 1.18 1.29 1.97 Inland Valley S.B. 1.00 0.72 0.88 0.73 1.12 0.88 1.00 1.28 Huntington Park 1.00 0.94 0.96 0.92 1.44 0.98 1.07 1.62 North Long Beach 1.00 1.42 1.47 1.41 2.13 1.51 1.63 2.38 Central Los Angeles 1.00 1.09 1.11 1.06 1.59 1.12 1.26 1.83 Pico Rivera 1.00 0.76 0.85 0.77 1.21 0.89 0.95 1.33 Rubidoux 1.00 0.60 0.84 0.64 0.98 0.89 0.93 1.00 West Long Beach 1.00 1.22 1.26 1.17 1.61 1.26 1.38 1.82 
MATES III Final Report

Appendix IX-17 

 

Table IX-3 

January Weekday MATES III Diesel/EC Modeling Emissions (TPD) 

Compound MATES III MATES II 

2005 1998 (Back-cast) 1998 

 PM2.5 TSP PM2.5 TSP PM2.5 TSP 

Total Diesel 26.19 28.47 27.42 29.81 N/A 23.56 

EC 14.12 18.9 14.68 19.89 N/A 25.87 

 

DPM 

On-road 9.52 10.35 10.81 11.35 N/A 11.95 

Off-road 11.02 11.97 12.29 11.36 N/A 8.08 

Ships 4.28 4.65 2.75 2.99 N/A 2.59 

Trains 0.86 0.94 0.79 0.86 N/A 0.53 

Stationary 0.51 0.55 0.78 0.85 N/A 0.41 

FIGURE IX-10a 

Weekday average emissions pattern for Total Diesel PM2.5.
MATES III Final Report

Appendix IX-18 

FIGURE IX-10b 

Weekday average emissions pattern for Elemental Carbon. 

FIGURE IX-10c 

Weekday average emissions pattern for On-Road Diesel PM2.5.
MATES III Final Report

Appendix IX-19 

FIGURE IX-10d 

Weekday average emissions pattern for Off-Road Diesel PM2.5.

FIGURE IX-10e 

Weekday average emissions pattern Diesel PM2.5 from Ships. 
MATES III Final Report

Appendix IX-20 

FIGURE IX-10f 

Weekday average emissions pattern Diesel PM2.5 from Trains. 

FIGURE IX-10g 

Weekday average emissions pattern Diesel PM2.5 from Stationary Sources. 
MATES III Final Report

Appendix IX-21 

FIGURE IX-10h 

Weekday average VOC emissions pattern. 

FIGURE IX-10i 

Weekday average NOx emissions pattern. 
MATES III Final Report

Appendix IX-22 

 

FIGURE IX-10j 

Weekday average CO emissions pattern. 

FIGURE IX-10k 

Weekday average emissions pattern for Acetaldehyde. 
MATES III Final Report

Appendix IX-23 

FIGURE IX-10l 

Weekday average Arsenic emissions pattern.

FIGURE IX-10m 

Weekday average Benzene emissions pattern. 
MATES III Final Report

Appendix IX-24 

 

FIGURE IX-10n 

Weekday average 1,3 Butadiene emissions pattern. 

 

FIGURE IX-10o 

Weekday average Cadmium PM2.5 emissions pattern. 
MATES III Final Report

Appendix IX-25 

FIGURE IX-10p 

Weekday average Chromium PM2.5 emissions pattern. 

FIGURE IX-10q 

Weekday average Hexavalent Chromium PM2.5 emissions pattern. 
MATES III Final Report

Appendix IX-26 

FIGURE IX-10r 

Weekday average Lead PM2.5 emissions pattern. 

FIGURE IX-10s 

Weekday average Methylene Chloride emissions pattern. 
MATES III Final Report

Appendix IX-27 

FIGURE IX-10t 

Weekday average Naphthalene emissions pattern. 

 

FIGURE IX-10u 

Weekday average Nickel PM2.5 emissions pattern. 
MATES III Final Report

Appendix IX-28 

FIGURE IX-10v 

Weekday average Nickel emissions pattern. 

FIGURE IX-10w 

Weekday average Perchloroethylene emissions pattern. 
MATES III Final Report

Appendix IX-29 

FIGURE IX-10x 

Weekday average Trichloroethylene emissions pattern. 

Table IX-4 summarizes the impact of using the revised emissions profile where CAMx RTRAC 

simulation overprediction of EC2.5 at Long Beach, West Long Beach and Compton was lessened 

without adversely impacting performance at the remaining sites. The total diesel mass 

emissions from this source category were not impacted by the revision. 

The third modification impacted the distribution of truck movement throughout the Basin. At 

the time of MATES II, no heavy-duty truck movement profile was available to characterize the 

truck distribution and travel on freeways, arterials, and major streets. Truck travel was assigned 

the travel model characteristics designated for light-duty passenger vehicle travel. MATES III 

directly incorporated the output of the heavy-duty truck demand model to provide a more 

realistic characterization of weekday travel. Weekend travel was assigned the same routes but at 

substantially lowered demand. 

A brief assessment of the changes made to the modeling emissions from MATES II to MATES 

III showed that for diesel 97% of the grids exhibited net changes of 10 kg/ day or less. The 

maximum change in grid level emissions ranged from -81 kg/day to 120 kg/day. (A positive 

number indicates an increase in emissions from the MATES II inventory to MATES III). 

Overall, the shift in the emissions pattern from MATES II to MATES III reflects relatively small 

increments of emissions increase or decrease. Refinements to travel patterns and shipping result 

in more clearly defined offshore shipping routes and enhanced diesel emissions along Interstate 5 

and 710. Reductions in diesel emissions are noted in southwestern San Bernardino and 

northwestern Riverside Counties. 
MATES III Final Report

Appendix IX-30 

TABLE IX-4 

Simulated Impact of Revised Marine EC2.5 Emissions Profile 

Location Observed Initial* Interim* Final* 

Anaheim 1.00 1.03 1.07 0.94 

Burbank 1.00 0.53 0.54 0.50 

Compton 1.00 1.12 1.15 1.04 

Inland Valley San Bernardino 1.00 0.72 0.88 0.84 

Huntington Park 1.00 0.94 0.96 0.91 

North Long Beach 1.00 1.42 1.47 1.26 

Central Los Angeles 1.00 1.09 1.11 1.06 

Pico Rivera 1.00 0.76 0.85 0.80 

Rubidoux 1.00 0.60 0.84 0.80 

West Long Beach 1.00 1.22 1.26 1.04 

* Ratio of Simulated to Observed EC2.5 at Measurement Site 

Boundary and Initial Conditions 

The MATES III boundaries differed significantly from those used in MATES II. Overall, the 

concentrations were lower; and, unlike MATES II, the boundary conditions were not uniform. 

The boundaries along the eastern and western portions of the modeling domain were sectioned 

into thirds, and the north and south boundaries were apportioned into fifths. Each section of the 

four boundaries was assigned a unique value. Table IX-5 provides the boundary assignments. 

The western and southern boundaries were scaled to show a diminishing concentration as the 

southwest corner of the modeling domain was approached. The overland boundaries residing 

over populated areas or grid cells in major transportation corridors were assigned higher 

boundary concentrations compared with those cells over water or over mountains or desert areas. 

The majority of the values of the boundary and initial conditions were extracted from the 2005 

annual PM2.5 simulations used for the 2007 AQMP compliance demonstration. Boundary 

conditions for EC and diesel particulate were generated from model simulations using the larger 

SCOS97 modeling grid and a clean boundary assumption. (The MATES III grid is a subset of 

the SCOS97 modeling grid which encompasses 550 km in the east-west direction and 370 km in 

the north-south direction). 
MATES III Final Report

Appendix IX-31 

TABLE IX-5 

Boundary Conditions for Gaseous Compounds (PPM): North and East Boundaries 

 Compound North East 

 N1 N2 N3 N4 N5 E1 E2 E3 

NO 0.00017 0.00022 0.0002 0.00022 0.0002 0.00016 0.00016 0.00016 

NO2 0.0028 0.0038 0.0038 0.00431 0.00395 0.00298 0.00297 0.00298 

O3 0.05 0.05 0.049 0.05 0.05 0.05 0.05 0.05 

OLE 0.0007 0.00082 0.00106 0.00115 0.0012 0.001393 0.001393 0.001393 

PAR 0.019 0.021 0.023 0.023 0.0239 0.02571 0.02571 0.02571 

TOL 0.00023 0.0003 0.00033 0.00032 0.00036 0.00038 0.00038 0.00038 

XYL 0.00009 0.000116 0.00011 0.00009 0.000109 0.000112 0.000112 0.000112 

FORM 0.002 0.0021 0.0021 0.00203 0.00201 0.00238 0.00238 0.00238 

ALD2 0.001 0.0012 0.00132 0.00136 0.0014 0.00163 0.00163 0.00163 

ETH 0.00041 0.000542 0.000636 0.0006 0.00061 0.0006 0.0006 0.0006 

CRES 0.000007 0.000007 0.000007 0.000007 0.000007 0.000009 0.000009 0.000009 

MGLY 0.000001 0.000001 0.000001 0.000001 0.000001 0.000001 0.000001 0.000001 

OPEN 0.000002 0.000002 0.000002 0.000002 0.000002 0.000003 0.000003 0.000003 

PNA 0.00001 0.00001 0.000012 0.000011 0.000011 0.000008 0.000008 0.000008 

NXOY 0.00007 0.00008 0.000095 0.000103 0.000115 0.00007 0.00007 0.00007 

PAN 0.00059 0.00058 0.000565 0.00054 0.00054 0.0005 0.0005 0.0005 

CO 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 

HONO 0.000002 0.000003 0.000003 0.000003 0.000003 0.000004 0.000004 0.000004 

H2O2 0.0018 0.0017 0.00165 0.0016 0.00165 0.00187 0.00187 0.00187 

MEOH 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 

ETOH 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 

ISOP 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 

BENZ 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 

BUTA 0.0000037 0.0000037 0.0000037 0.0000037 0.0000037 0.0000037 0.0000037 0.0000037 

PACET 0.0001 0.00012 0.000132 0.000136 0.00014 0.000163 0.000163 0.000163 

HCHO 0.0002 0.00021 0.00021 0.000203 0.000201 0.000238 0.000238 0.000238 

SACET 0.00045 0.00054 0.0006 0.00061 0.00063 0.000735 0.000735 0.000735 

SFORM 0.0009 0.00095 0.00095 0.00092 0.000945 0.00107 0.00107 0.00107 

PDIC 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 

MCHL 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 

PERC 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 

TCE 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 

NAPH 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 
MATES III Final Report

Appendix IX-32 

TABLE IX-5 (Continued) 

Boundary Conditions for Gaseous Compounds (PPM): West and South Boundaries 

 Compound West South 

 W1 W2 W3 S1 S2 S3 S4 S5 

NO 0.000128 0.00035 0.000325 0.00014 0.00028 0.00039 0.000585 0.00052 

NO2 0.00103 0.00311 0.00317 0.00115 0.002 0.00426 0.0077 0.00664 

O3 0.044 0.044 0.047 0.045 0.046 0.045 0.044 0.047 

OLE 0.000069 0.000155 0.000389 0.00007 0.0001 0.000365 0.000928 0.001248 

PAR 0.0108 0.0182 0.0204 0.011 0.015 0.0221 0.03485 0.0349 

TOL 0.000096 0.000183 0.000213 0.00012 0.00017 0.00038 0.000855 0.0008 

XYL 0.000031 0.000073 0.000081 0.00004 0.00007 0.000165 0.000381 0.000352 

FORM 0.000637 0.00098 0.00167 0.00061 0.00073 0.00105 0.00173 0.00222 

ALD2 0.000242 0.000422 0.000687 0.00024 0.0003 0.00058 0.00114 0.00139 

ETH 0.000099 0.000175 0.000343 0.0001 0.00015 0.000349 0.000658 0.000827 

CRES 0.000004 0.000006 0.000006 0.000004 0.000006 0.00001 0.000019 0.000019 

MGLY 0.000001 0.000001 0.000001 0.000001 0.000001 0.000001 0.000001 0.000001 

OPEN 0.000001 0.0000015 0.000001 0.000001 0.000002 0.000003 0.000005 0.000005 

PNA 0.000004 0.000006 0.000009 0.000004 0.000004 0.000008 0.000013 0.000016 

NXOY 0.00005 0.00006 0.000048 0.00005 0.0001 0.000125 0.000134 0.000112 

PAN 0.0003 0.000413 0.00051 0.0003 0.00034 0.000427 0.000565 0.000657 

CO 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 

HONO 0.000002 0.000005 0.000004 0.000002 0.000003 0.000005 0.000007 0.000006 

H2O2 0.00114 0.00127 0.00163 0.0011 0.0012 0.0013 0.00145 0.00168 

MEOH 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 

ETOH 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 

ISOP 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 0.0001 

BENZ 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 0.0002 

BUTA 0.0000037 0.0000037 0.0000037 0.0000037 0.0000037 0.0000037 0.0000037 0.0000037 

PACET 0.0000242 0.000042 0.0000687 0.000024 0.00003 0.000058 0.000114 0.000139 

HCHO 0.0000637 0.000098 0.000167 0.000063 0.000073 0.000105 0.000173 0.000222 

SACET 0.000109 0.00019 0.000618 0.000108 0.000135 0.00026 0.000501 0.000625 

SFORM 0.000285 0.00044 0.0015 0.000275 0.00032 0.000475 0.00078 0.001 

PDIC 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 

MCHL 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 

PERC 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 

TCE 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 

NAPH 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 0.00001 
MATES III Final Report

Appendix IX-33 

TABLE IX-5 (Continued) 

Boundary Conditions for Particulate Compounds (μg/m3): North and East Boundaries 

Compound North (Fine) East (Fine) 

 N1 N2 N3 N4 N5 E1 E2 E3 

AR 0.00004 0.0001 0.000144 0.0004 0.0004 0.00034 0.0002 0.000192 

CD 0.000013 0.00003 0.0000425 0.000125 0.000125 0.000108 0.0000625 0.00006 

CR 0.0001 0.00025 0.00034 0.001 0.001 0.00085 0.0005 0.00048 

CR6 0.00001 0.00002 0.00002 0.00008 0.0001 0.00007 0.000045 0.000045 

DPMa 0.078 0.117 0.085 0.3 0.29 0.104 0.075 0.084 

DPMb 0.029 0.068 0.093 0.222 0.188 0.15 0.108 0.088 

DPMc 0.0017 0.0041 0.005 0.0127 0.0123 0.0103 0.0055 0.00475 

DPMd 0.0014 0.0034 0.0044 0.035 0.037 0.0075 0.0084 0.0123 

DPMe 0.0088 0.01 0.011 0.0075 0.0055 0.005 0.0037 0.00246 

DSL 0.119 0.2 0.2 0.58 0.503 0.278 0.201 0.192 

EC 0.059 0.11 0.128 0.3 0.283 0.154 0.124 0.125 

NI 0.000056 0.00014 0.00019 0.00056 0.00056 0.000476 0.00028 0.000269 

OC 0.011 0.22 0.255 0.61 0.66 0.336 0.257 0.25 

PB 0.00017 0.000425 0.00056 0.0017 0.0017 0.001445 0.00085 0.000817 

 North (Coarse) East (Coarse) 

 N1 N2 N3 N4 N5 E1 E2 E3 

ARC 0.00005 0.00012 0.00022 0.0004 0.0004 0.000276 0.00016 0.000152 

CDC 0.000014 0.00004 0.0000688 0.000125 0.000125 0.000086 0.00005 0.000048 

CR6C 0.000001 0.000001 0.000001 0.00001 0.00001 0.000005 0.000005 0.000005 

CRC 0.00012 0.0003 0.00055 0.001 0.001 0.00069 0.0004 0.00038 

DPMaC 0.005 0.0072 0.005 0.017 0.016 0.0045 0.003 0.0034 

DPMbC 0.0013 0.0027 0.006 0.0084 0.006 0.00625 0.00429 0.003 

DPMcC 0.00003 0.00007 0.00011 0.00017 0.00016 0.000235 0.00011 0.00014 

DPMdC 0.00006 0.00013 0.0005 0.0028 0.0023 0.00033 0.00037 0.0006 

DPMeC 0.0005 0.00041 0.0004 0.00022 0.00018 0.00025 0.00016 0.0001 

DSLC 0.008 0.01 0.0124 0.028 0.025 0.0116 0.008 0.0072 

ECC 0.011 0.023 0.034 0.072 0.071 0.036 0.029 0.0319 

NIC 0.000067 0.00017 0.00031 0.00056 0.00056 0.000386 0.000216 0.000213 

OCC 0.07 0.15 0.25 0.36 0.29 0.261 0.154 0.135 

PBC 0.0002 0.00051 0.00093 0.0017 0.0017 0.00117 0.00068 0.000646 
MATES III Final Report

Appendix IX-34 

TABLE IX-5 (Continued) 

Boundary Conditions for Particulate Compounds (μg/m3): West and South Boundaries 

West (Fine) South (Fine) 

 W1 W2 W3 S1 S2 S3 S4 S5 

AR 0.000002 0.000022 0.000032 0.000004 0.00014 0.00016 0.00044 0.00056 

CD 6.3E-07 6.88E-06 0.00001 0.0000013 0.000043 0.00005 0.0001375 0.0002 

CR 0.000005 0.000055 0.00008 0.00001 0.00034 0.0004 0.0011 0.0016 

CR6 0.0000005 0.00001 0.00001 0.000001 0.00006 0.00007 0.00017 0.0002 

DPMa 0.00016 0.00494 0.0078 0.00025 0.0013 0.003 0.096 0.143 

DPMb 0.00034 0.0048 0.012 0.00055 0.0025 0.005 0.097 0.165 

DPMc 0.015 0.0211 0.02 0.0245 0.0185 0.0216 0.025 0.0166 

DPMd 0.000125 0.00125 0.00142 0.00014 0.00032 0.0005 0.00327 0.006 

DPMe 0.0001 0.0015 0.0058 0.00013 0.00036 0.00058 0.0031 0.0055 

DSL 0.0155 0.033 0.047 0.0255 0.023 0.031 0.219 0.335 

EC 0.006 0.043 0.05 0.0097 0.019 0.028 0.134 0.196 

NI 0.0000028 0.0000308 0.000045 0.0000056 0.00019 0.000226 0.000616 0.000896 

OC 0.011 0.026 0.043 0.018 0.0175 0.025 0.223 0.377 

PB 0.0000085 0.0000935 0.000126 0.000017 0.000578 0.00068 0.00187 0.00272 

 West (Coarse) South (Coarse) 

 W1 W2 W3 S1 S2 S3 S4 S5 

ARC 0.0000006 0.000006 0.000026 0.0000004 0.000002 0.000008 0.00016 0.00028 

CDC 0.0000002 1.88E-06 0.000008 1.3E-07 0.0000006 0.0000025 0.00005 0.0001 

CR6C 1E-08 0.0000001 0.0000005 0.000001 0.000001 0.000001 0.000001 0.000005 

CRC 0.0000015 0.000015 0.000065 0.000001 0.000005 0.00002 0.0004 0.0008 

DPMaC 0.00001 0.00039 0.00055 0.000015 0.00007 0.00017 0.0065 0.0086 

DPMbC 0.00002 0.00034 0.00082 0.00003 0.00013 0.00027 0.0065 0.0094 

DPMcC 0.001 0.0015 0.00139 0.0015 0.00096 0.0011 0.00125 0.00063 

DPMdC 0.00001 0.00009 0.0001 0.00001 0.00002 0.00003 0.00021 0.00032 

DPMeC 0.000005 0.0001 0.00042 0.00001 0.00002 0.00003 0.0002 0.00018 

DSLC 0.001 0.0024 0.0032 0.0015 0.0012 0.0016 0.0146 0.019 

ECC 0.00036 0.0036 0.0065 0.0005 0.0011 0.0022 0.036 0.055 

NIC 8.4E-07 0.0000084 0.000036 5.6E-07 0.0000028 0.0000112 0.000224 0.000448 

OCC 0.0014 0.011 0.035 0.0019 0.0041 0.0079 0.236 0.392 

PBC 2.55E-06 0.0000255 0.00011 0.0000017 0.0000085 0.000034 0.00068 0.00136 
MATES III Final Report

Appendix IX-35 

Modeling Results 

The performance of the CAMx regional modeling simulation for the 2005 emissions and 

meteorology is summarized through model performance statistics and graphically through time 

series displays and bivariate plots of key projected pollutant concentrations. Summarized in 

Table IX-6 are the toxic components observed and simulated concentrations and the prediction 

accuracy (PA) measured as the percentage difference between the mean annual observed and 

simulated concentrations. 

2005 CAMx RTRAC Simulation 

Simulated annual average EC2.5 was the compound used to assess overall model performance for 

the 2005 MATES III period at the eight sites having a full year’s sampling. The analysis used 

annual average EC2.5 model performance to provide consistency with the 2007 AQMP annual 

average PM2.5 attainment demonstration modeling assessment. While the 2007 EC2.5 AQMP 

modeling was conducted on a coarser grid (5 kilometer squared), it was expected that the 

summary performance of the CAMx RTRAC 2005 MATES III simulation should be consistent, 

but not identical. 

In general, EC2.5 performs well in the simulation. The EC2.5 performance is comparable to that 

observed in the 2007 AQMP annual PM2.5 attainment demonstration. Performance for several of 

the minor toxic components varies. This in part can be attributed to very low measured 

concentrations nearing levels of detection, uncertainties in the emissions inventory and model 

performance in recreating dispersion patterns. Adding to the uncertainty is the nine-cell distance 

weighted averaging to recreate a measurement made at a discreet location. 

EPA guidance (U.S. EPA, 2006) recommends evaluating gaseous and particulate modeling 

performance using measures of prediction bias and error. PA goals of ±20% for ozone and 

±30% for individual components of PM2.5 or PM10 have been used to assess simulation 

performance in previous modeling attainment demonstrations. 

Table IX-7 provides the CAMx performance for EC2.5 at the eight MATES III monitoring sites 

that have complete monitoring records for 2005. Three of the eight sites (Burbank, Inland 

Valley San Bernardino, and Rubidoux) underpredict the annual average EC2.5 concentration. 

The greatest tendency for overprediction is at North Long Beach. The mean error of the 

simulated versus measured concentrations ranges from 0.54 μg/m3

 to 1.11 μg/m3. PA at seven 

of the eight MATES III sites meets the particulate goal with only Burbank exhibiting a large 

degree (50%) of underprediction of the annual average concentration. Of the remaining sites, 

Inland Valley San Bernardino, and Rubidoux are underpredicted by 19 and 22%, respectively 

and Long Beach is overpredicted by 22%. All other sites PA falls within ±10% of observations. 

Table IX-8 provides the CAMx RTRAC performance for Benzene at the eight MATES III 

monitoring sites that have complete monitoring records for 2005. Benzene model performance is 

included in the evaluation because of the confidence in the benzene measurement data based on 

the long-term monitoring conducted in the Basin and throughout California. With the exceptions 

of Burbank and Compton, the remaining sites achieve a PA of less than 20%. The simulation 

bias is mixed and is generally less than 0.1 ppb (with the exceptions of Burbank and Compton). 
MATES III Final Report

Appendix IX-36 

The time series fit of the simulated EC2.5 concentrations to measurements for each station is 

depicted in Figures IX-11a through IX-11h and in the cumulative eight-site combined bivariate 

plot shown in Figure IX-12. The time series depiction of the measured and simulated EC2.5 echo 

the statistical evaluation whereby concentrations are underpredicted throughout the year at 

Burbank and Riverside, with the greatest margin occurring in the fall and early winter periods. 

Similarly, EC2.5 at Inland Valley San Bernardino is underpredicted in the second half of the year. 

The time series for the other sites show a general tendency to nominally overpredict in the 

summer but capture the trend in the fall and winter. 

In Figure IX-12, the EC2.5 predictions for the eight sites combined show an overall tendency 

towards underprediction. However a large percent of the predictions are within 30% of the 

measured concentrations. 

1998-99 CAMx RTRAC Simulation 

Table IX-9 and Table IX-10 provide a comparison of the 2005 and 1998-99 model performance 

for EC2.5 and benzene, respectively. The tables provide comparisons of the performance of the 

mean annual CAMx RTRAC simulated EC2.5 and benzene and the annual average concentrations 

based on the monitoring data. Performance solely for days when observations were conducted 

was not calculated for the 1998-99 simulation. Listed in each table are PA, mean error, and 

absolute error. The 1998-99 CAMx RTRAC evaluation includes simulation performance at 

Huntington Park and Pico Rivera in the assessment. 

The 1998-99 CAMx RTRAC model simulations were developed using the same procedures and 

methodologies as the 2005 simulation. Overall, the 1998-99 simulated annual average 

concentrations tended to underpredict observed mean concentrations. 

As presented in Table IX-8, the EC2.5 1998-99 simulation depicts a systematic bias towards 

underprediction. In addition, prediction accuracy degrades compared to the 2005 simulation 

with only three of eight stations meeting the ±30% goal. The ratio of the 1998-99 average 

absolute error to the average observed concentration was over 36% compared to a similar ratio 

for 2005 valued at 17%. (Note: the mix of stations is different for the two periods). 

The 1998-99 simulation performance for benzene, (depicted in Table IX-9), is also degraded 

compared to the 2005 simulations, however, to a lesser degree than for EC2.5. While the average 

bias for the 1998-99 simulation trends towards underprediction, several coastal metropolitan sites 

are well-simulated. The poorest performing site for PA and bias in both simulations 1998-99 and 

2005 is Compton. The ratio of the 1998-99 average absolute error to the average observed 

concentration was 29% compared to a similar ratio for 2005, valued at 17%. 

Discussion of Simulation Uncertainties 

It is difficult to assign incremental degrees of uncertainty to the model simulations. Both 

simulation periods required emissions projections from the 2002 base-year inventory. A 

significant amount of effort was taken in the development of the 2002 to 2005 emissions 

projections, particularly for the mobile source inventory as a component in the development of 

the 2007 AQMP. The 1998-99 back-cast of the emissions data used the same projection 
MATES III Final Report

Appendix IX-37 

protocol as the forward projection from 2002 to 2005. The simulation used the 1998 reported 

point source emissions and mobile source emissions based on EMFAC 2007. 

There are several areas where incremental uncertainty in the back-cast of the emissions can take 

place. Traffic patterns, spatial vehicle age distributions and marine vessel activities all changed 

from 1998 to 2005. Weigh-in-motion (WIM) traffic count data has been used in the 2003 and 

2007 AQMPs to help better define weekday and weekend traffic patterns. The WIM data used in 

the analysis is more contemporary with the 2002-2005 time frames and was not changed in the 

development of the 1998-99 diurnal traffic patterns. Also, the greater number of older, higher 

emitting cars and their distribution throughout the Basin may have added to the uncertainty in the 

1998 mobile source emissions estimate. Finally, detailed shipping surveys, including port calls 

and route assignment for oceangoing vessels and marine craft, were conducted for the 

development of the 2003 and 2007 AQMPs. Uncertainties arise in the back-casts of the 1998 

activities contributing to the estimation of these emissions. 

As previously discussed, a general assessment of the meteorological profiles of the two 

monitoring periods suggests that the dispersion potentials were comparable but not identical. 

The meteorological input fields generated from the MM5 simulations followed the same protocol 

with the exceptions of the grid resolution of the analysis initialization simulations and the day 

specific data used in the FDDA analysis. Finally, both simulations use the same initial and 

boundary conditions. 

Simulation Evaluation Averaged Over the Monitoring Network 

For this comparison, the monitored data for six stations are combined to provide an estimate of 

average basin-wide conditions for the two sampling periods: 2005 and 1998-99. Table IX-11 

summarizes the network average measured and predicted pollutant concentrations at the six sites. 

Two stations in 2005, Huntington Park and Pico Rivera, did not have complete measurement 

records for the full 12 months and were excluded from the analysis. Similarly, complete 

measurements for Compton and West Long Beach were not available for 1998-99. CAMx 

RTRAC simulated pollutant concentrations for the six stations that have complete data for the 

two measurement periods were calculated from the grid data using the distance weighted ninecell average. No direct measurements of PM2.5 diesel were available for comparison to simulate 

annual average concentrations. However, estimates of diesel concentrations based on Chemical 

Mass Balance (CMB) analysis using ambient measured elemental carbon concentrations are 

discussed later. Measured concentrations of naphthalene were available for Central Los Angeles 

and Riverside. Each of the four counties is represented by at least one station. The six stations’ 

average measured and simulated concentrations provide an estimate of the regional profile but 

with a bias towards impacts to the coastal communities in the heavily transited areas of the 

Basin. Moreover, the assessment provides a direct comparison for model performance 

evaluation. 

In general, 2005 model simulated particulate EC2.5, EC10, hexavalent chromium and PM2.5 nickel 

average annual toxic compound concentrations compared well with the measured annual average 

values. The majority of gaseous components were well-simulated with the sole exception of 

acetaldehyde which is underpredicted. Arsenic and TSP lead exhibit the greatest tendency for 
MATES III Final Report

Appendix IX-38 

overprediction. Cadmium, and PM2.5 lead concentrations tend to be underpredicted. In general, 

the concentrations of the gaseous compounds are closely recreated. 

For 1998-99, there exists a general tendency for underprediction. Hexavalent chromium and 

nickel average annual toxic compound concentrations are exceptions that are closely matched to 

observations. Aside from the uncertainties associated with the modeling analyses, some 

uncertainty in prediction accuracy is introduced into the analysis through the measurement and 

analysis programs. The 1998-99 data samples were measured and analyzed by different agencies 

(AQMD and ARB) and their laboratories. In addition, to the substitution of one-half level of 

detection for data measured below the detection limit also adds to the uncertainty in the analysis. 

Simulation Estimated Spatial Concentration Fields 

Figures IX-13a through IX-13u depict the CAMx projected annual average concentration 

distributions of selected toxic compounds as well as the impacts of five emissions categories of 

diesel particulates in the Basin. In general, the distribution of diesel particulates follows the 

major arterials. However, localized hot spots with annual average concentrations to 4.8 μg/m3

are observed in the Central Los Angeles area and 8.5 μg/m3

 at the Ports of Los Angeles and 

North Long Beach. Figures IX-13h and IX-13i provide the distributions of benzene and 1,3-

butadiene, respectively, whereby the toxic compounds are almost uniformly distributed 

throughout the Basin (reflecting patterns of light-duty vehicle fuel consumption). The 

formaldehyde profile (Figure IX-13j) depicts higher concentrations in the heavily-traveled 

western and central Basin, with additional hot spots in the downwind areas of the Basin that are 

impacted by higher levels of ozone formation (Santa Clarita and Crestline). 
MATES III 

Appendix IX-39 

Table IX-6 

2005 Station Observed and CAMx Simulated MATES III Annual Average Concentrations 

Compound Units Anaheim Burbank Compton 

 Obs Model PA Obs Model PA Obs Model PA Ob

1,3 Butadiene ppb 0.09 0.09 9 0.15 0.07 56 0.19 0.15 19 0.Acetaldehyde ppb 1.28 1.04 19 1.94 1.02 47 1.57 1.04 34 1.As (TSP) ηg/m3 0.44 1.91 333 0.74 1.49 102 0.66 3.41 417 0.As (2.5) ηg/m3 0.50 0.76 52 0.52 0.51 2 0.46 2.14 363 0.Benzene ppb 0.44 0.50 15 0.71 0.47 34 0.80 0.57 29 0.Cd (TSP) ηg/m3 1.58 0.59 63 1.49 0.38 74 1.42 0.98 31 1.Cd (2.5) ηg/m3 1.63 0.32 80 1.30 0.21 84 1.70 0.71 58 1.Cr6 (TSP) ηg/m3 0.16 0.17 2 0.18 0.11 35 0.31 0.19 38 0.EC10 μg/m3 1.60 1.82 13 2.35 1.35 42 1.84 2.34 27 2.EC2.5 μg/m3 1.41 1.35 4 2.04 1.03 50 1.76 1.88 7 2.Formaldehyde ppb 2.96 2.97 0 3.84 2.85 26 3.14 3.18 1 3.Methylene Chloride ppb 0.24 0.36 54 0.34 0.27 20 0.29 0.39 33 0.Naphthalene ppb Ni (TSP) ηg/m3 3.93 3.13 20 3.75 2.05 45 6.02 7.97 32 3.Ni (2.5) ηg/m3 4.31 1.71 60 3.72 1.12 70 4.50 5.87 30 3.Pb (TSP ) ηg/m3 3.06 8.80 188 3.12 5.49 76 3.06 8.14 166 3.Pb (2.5) ηg/m3 3.57 1.96 45 4.66 1.17 75 5.84 2.40 59 8.p-Dichlorobenzene ppb 0.03 0.09 174 0.04 0.07 95 0.07 0.11 62 0.Perchloroethylene ppb 0.06 0.10 60 0.10 0.10 1 0.12 0.13 11 0.Trichloroethylene ppb 0.03 0.03 17 0.05 0.02 53 0.03 0.06 87 0.
MATES III 

Appendix IX-40 

Table IX-6 (Continued) 

2005 Station Observed and CAMx Simulated MATES III Annual Average Concentrations 

Compound Units Huntington Park (Less than 12 Months) North Long Beach Central Los Angeles 

(L

 Obs Model PA Obs Model PA Obs Model PA Ob

1,3 Butadiene ppb 0.21 0.25 21 0.10 0.10 2 0.12 0.13 5 0.Acetaldehyde ppb 1.58 1.13 28 1.26 1.11 12 1.78 1.31 26 1.As (2.5) ηg/m3 1.46 10.67 629 0.65 2.21 241 0.66 3.95 496 1.As (TSP) ηg/m3 1.27 8.79 593 0.51 0.90 77 0.51 1.52 197 1.Benzene ppb 0.83 0.62 25 0.50 0.57 13 0.59 0.69 16 0.Cd (2.5) ηg/m3 1.46 1.04 28 1.65 0.88 46 1.43 0.82 43 1.Cd (TSP) ηg/m3 2.18 0.67 69 1.27 0.65 49 1.39 0.47 66 1.Cr6 (TSP) ηg/m3 0.23 0.38 62 0.18 0.18 4 0.18 0.26 42 0.EC10 μg/m3 2.54 3.03 19 1.81 2.25 24 2.05 2.67 30 2.EC2.5 μg/m3 2.28 2.29 0 1.40 1.71 21 1.93 2.04 6 2.Formaldehyde ppb 3.70 3.69 0 3.50 3.36 4 4.23 4.10 3 3.Methylene Chloride ppb 0.39 0.51 31 0.62 0.34 45 0.38 0.58 53 0.Naphthalene ppb 205.33 149.51 27Ni (2.5)) ηg/m3 5.54 6.59 19 6.64 8.77 32 4.87 4.91 1 4.Ni (TSP) ηg/m3 2.59 4.11 59 4.15 5.83 40 4.33 2.99 31 3.Pb (2.5 ) ηg/m3 3.14 13.07 316 3.26 7.67 135 3.04 10.09 232 3.Pb (TSP) ηg/m3 7.74 5.48 29 4.32 1.87 57 4.67 2.14 54 6.p-Dichlorobenzene ppb 0.08 0.13 68 0.03 0.09 184 0.04 0.12 234 0.Perchloroethylene ppb 0.11 0.16 48 0.05 0.10 110 0.06 0.13 125 0.Trichloroethylene ppb 0.04 0.06 67 0.03 0.05 88 0.03 0.03 0 0.
MATES III 

Appendix IX-41 

Table IX-6 (Continued) 

2005 Station Observed and CAMx Simulated MATES III Annual Average Concentrations 

Compound Units Rubidoux West Long Beach 

 Obs Model PA Obs Model PA 

1,3 Butadiene Ppb 0.09 0.09 5 0.12 0.09 22Acetaldehyde Ppb 1.67 1.09 35 1.41 1.08 23As (2.5) ηg/m3 0.82 1.96 139 0.71 2.33 227As (TSP) ηg/m3 0.45 0.56 26 0.47 0.99 113Benzene Ppb 0.44 0.44 2 0.53 0.60 14Cd (2.5) ηg/m3 1.54 0.57 63 1.46 1.32 9Cd (TSP) ηg/m3 1.46 0.32 78 1.47 1.08 27Cr6 (TSP) ηg/m3 0.39 0.14 65 0.26 0.17 34EC10 μg/m3 2.06 1.74 15 2.30 2.57 12EC2.5 μg/m3 1.69 1.32 22 2.07 2.14 3Formaldehyde Ppb 3.44 3.01 13 3.34 3.25 3Methylene Chloride Ppb 0.33 0.21 37 0.20 0.29 43Naphthalene Ppb 151.73 81.42 46 188.68 96.08 49Ni (2.5)) ηg/m3 3.73 3.31 11 10.55 17.36 65Ni (TSP) ηg/m3 3.57 2.17 39 7.45 10.96 47Pb (2.5 ) ηg/m3 3.12 7.26 132 3.17 7.17 126Pb (TSP) ηg/m3 6.31 1.78 72 4.50 2.36 47p-Dichlorobenzene Ppb 0.04 0.06 58 0.03 0.10 191Perchloroethylene Ppb 0.03 0.08 130 0.05 0.09 100Trichloroethylene Ppb 0.02 0.03 38 0.04 0.04 0
MATES III 

Appendix IX-42 

Table IX-7 

 2005 Simulation Performance Statistics for PM2.5 Elemental Carbon 

Location Observed (μg/m3) Samples Predicted (μg/m3) PA Mean Bias (μg/m3) Mean Error (μg/m3) Normalized Mean Bias (μg/m3) No

Me

(

Anaheim 1.41 120 1.35 4 -0.06 0.54 0.39 Burbank 2.04 119 1.03 50 -1.02 1.11 -0.31 Compton 1.76 115 1.88 7 0.12 0.61 0.39 Inland Valley S.B. 2.18 117 1.77 19 -0.41 0.91 0.09 North Long Beach 1.40 107 1.71 21 0.30 0.61 0.55 Central L.A. 1.93 117 2.04 6 0.11 0.76 0.39 Rubidoux 1.69 119 1.32 22 -0.38 0.74 0.09 West Long Beach 2.07 114 2.14 3 0.07 0.79 0.33 

Table IX-8 

2005 Simulation Performance Statistics for Benzene 

Location Observed (μg/m3) Samples Predicted (μg/m3) PA Mean Bias (μg/m3) Mean Error (μg/m3) Normalized Mean Bias (μg/m3) No

Me

(

Anaheim 0.439 115 0.504 15 0.064 0.213 0.597 Burbank 0.709 121 0.466 34 -0.243 0.344 -0.072 Compton 0.796 117 0.567 29 -0.229 0.388 0.105 Inland Valley S.B. 0.492 117 0.438 11 -0.054 0.169 0.092 North Long Beach 0.504 118 0.571 13 0.066 0.213 0.485 Central L.A. 0.588 119 0.685 16 0.097 0.249 0.469 Rubidoux 0.435 119 0.442 2 0.007 0.16 0.267 West Long Beach 0.525 119 0.598 14 0.073 0.214 0.603 
MATES III 

Appendix IX-43 

Table IX-9 

Comparative Simulation Performance Statistics for EC 

 1998-99 2005 

 Location 

Observed 

Days 

(μg/m3) 

Modeled 

All 

Days 

(μg/m3) PA 

Bias 

(μg/m3)

Absolute 

Error 

(μg/m3) 

Observed 

Days 

(μg/m3) 

Modeled 

All 

Days 

(μg/m3) PA 

Anaheim 2.30 2.12 8 -0.18 0.18 1.41 1.35 4 Burbank 3.19 1.59 50 -1.6 1.6 2.04 1.05 49 Compton 1.76 1.87 6 Inland Valley S.B. 3.10 1.84 41 -1.26 1.26 2.18 1.82 17 Huntington Park 4.35 2.73 37 -1.62 1.62 North Long Beach 2.54 2.41 5 -0.13 0.13 1.4 1.82 30 Central L.A. 3.53 2.74 22 -0.79 0.79 1.93 2.08 8 Pico Rivera 4.35 2.14 51 -2.21 2.21 Rubidoux 3.39 1.39 59 -2.00 2.00 1.69 1.36 20 West Long Beach 2.07 2.16 4 Average 3.34 2.12 34 -1.22 1.22 1.81 1.69 17 
MATES III 

Appendix IX-44 

Table IX-10 

Comparative Simulation Performance Statistics for Benzene 

 1998-99 2005 

 Location 

Observed 

Days 

(ppb) 

Modeled 

All 

Days 

(ppb) PA 

 Bias 

(ppb) 

Absolute 

Error 

(ppb) 

Observed 

Days 

(ppb) 

Modeled 

All 

Days 

(ppb) PA 

(

Anaheim 1.05 0.81 23 -0.24 0.24 0.44 0.51 15 Burbank 1.26 0.52 59 -0.74 0.74 0.71 0.47 33 -Compton 1.8 0.84 53 -0.96 0.96 0.8 0.57 29 -Inland Valley S.B. 0.74 0.56 24 -0.18 0.18 0.49 0.45 9 -Huntington Park 1.65 1.05 36 -0.6 0.6 0.63 North Long Beach 0.83 0.85 2 0.02 0.02 0.5 0.57 15 Central L.A. 1.01 1.07 6 0.06 0.06 0.59 0.69 17 Pico Rivera 0.89 0.88 1 -0.01 0.01 0.60 Rubidoux 0.87 0.52 40 -0.35 0.35 0.44 0.45 2 West Long Beach 1.27 1.15 9 -0.12 0.12 0.53 0.60 12 Average 1.14 0.83 25 -0.31 0.33 0.56 0.55 17 -
MATES III Final Report

Appendix IX-45 

Figure IX-11a 

EC2.5 Time Series: Simulated Vs. Measured at Anaheim. 

Figure IX-11b 

EC2.5 Time Series: Simulated Vs. Measured at Burbank. 

Figure IX-11c 

EC2.5 Time Series: Simulated Vs. Measured at Compton. 

Anaheim EC2.5

0

2

4

6

8

10

2 26 50 74 98 122 146 170 194 218 242 266 290 314 338 362

 [ug/m3]

 Observed Predicted

Burbank EC 2.5

0

2

4

6

8

10

2 26 50 74 98 122 146 170 194 218 242 266 290 314 338 362

 [ug/m3]

 Observed Predicted

Compton EC2.5 

0

2

4

6

8

10

2 26 50 74 98 122 146 170 194 218 242 266 290 314 338 362

 [ug/m3]

 Observed Predicted
MATES III Final Report

Appendix IX-46 

Figure IX-11d 

EC2.5 Time Series: Simulated Vs. Measured at Inland Valley San Bernardino. 

Figure IX-11e 

EC2.5 Time Series: Simulated Vs. Measured at North Long Beach. 

Figure IX-11f 

EC2.5 Time Series: Simulated Vs. Measured at Central Los Angeles. 

Inland Valley S.B. EC2.5

0

2

4

6

8

10

2 26 50 74 98 122 146 170 194 218 242 266 290 314 338 362

 [ug/m3]

Observed Predicted

North Long Beach EC2.5

0

2

4

6

8

10

2 26 50 74 98 122 146 170 194 218 242 266 290 314 338 362

 [ug/m3]

Observed Predicted

Central Los Angeles. EC2.5 

0

2

4

6

8

10

2 26 50 74 98 122 146 170 194 218 242 266 290 314 338 362

 [ug/m3]

Observed Predicted
MATES III Final Report

Appendix IX-47 

Figure IX-11g 

EC2.5 Time Series: Simulated Vs. Measured at Rubidoux. 

Figure IX-11h 

EC2.5 Time Series: Simulated Vs. Measured at West Long Beach. 

Rubidoux EC 2.5

0

2

4

6

8

10

2 26 50 74 98 122 146 170 194 218 242 266 290 314 338 362

 [ug/m3]

Observed Predicted

West Long Beach EC2.5

0

2

4

6

8

10

2 26 50 74 98 122 146 170 194 218 242 266 290 314 338 362

 [ug/m3]

 Observed Predicted
MATES III Final Report

Appendix IX-48 

Scatter Plot of Predicted vs. Observed Concentrations

EC

0

1

2

3

4

5

6

7

8

9

10

0 1 2 3 4 5 6 7 8 9 10

Observed [ug/m3]

Predicted [ug/m3]

Figure IX-12 

EC2.5 Bivariate Scatter Plot Simulated Vs. Measured All Stations. 
MATES III Final Report

Appendix IX-49 

Table IX-11 

Toxic Compounds Simulated and Measured: 

Six-Station Annual Average Concentrations 

2005 MATES III and 1998-99 CAMx RTRAC Analyses 

2005 MATES III 1998-99 MATES II 

(CAMx RTRAC Simulation) 

Toxic 

Compound 

Units 

Measured 

Annual 

Average 

Simulated 

Annual 

Average 

Measured 

Annual 

Average 

Simulated 

Annual Average 

EC2.5 μg/m3 1.78 1.58 N/A N/A 

EC10 μg/m3 2.04 2.05 3.01 2.03 

Cr6 (TSP) ηg/m3 0.22 0.21 0.18 0.17 

As (2.5) ηg/m3 0.5 0.92 N/A N/A 

As (TSP) ηg/m3 0.68 2.46 1.79 3.00 

Cd (2.5) ηg/m3 1.46 0.49 N/A N/A 

Cd (TSP) ηg/m3 1.56 0.78 6.57 1.00 

Ni (2.5)) ηg/m3 3.93 3.65 N/A N/A 

Ni (TSP) ηg/m3 4.44 5.82 7.51 6.83 

Pb (2.5 ) ηg/m3 5.41 2.60 N/A N/A 

Pb (TSP) ηg/m3 10.64 8.68 22.72 10.00 

Benzene Ppb 0.53 0.52 0.97 0.75 

Perchloroethylene Ppb 0.06 0.09 0.27 0.18 

p-Dichlorobenzene Ppb 0.03 0.08 0.12 0.06 

Methylene Chloride Ppb 0.35 0.32 0.70 0.54 

Trichloroethylene Ppb 0.03 0.03 0.10 0.05 

1,3Butadiene Ppb 0.1 0.09 0.29 0.13 

Formaldehyde Ppb 3.61 3.26 4.00 3.75 

Acetaldehyde Ppb 1.64 1.12 1.81 1.26 

Naphthalene Ppb 0.02* 0.01 N/A 0.02 

* Two station average 
MATES III Final Report

Appendix IX-50 

FIGURE IX-13a 

CAMx simulated 2005 annual average Diesel PM2.5. 

FIGURE IX-13b 

CAMx simulated 2005 annual average Elemental Carbon PM2.5. 
MATES III Final Report

Appendix IX-51 

FIGURE IX-13c 

CAMx simulated 2005 annual average On-Road Diesel PM2.5. 

FIGURE IX-13d 

CAMx simulated 2005 annual average Off-Road Diesel PM2.5. 
MATES III Final Report

Appendix IX-52 

FIGURE IX-13e 

CAMx simulated 2005 annual average Diesel from Ships PM2.5. 

FIGURE IX-13f 

CAMx simulated 2005 annual average Diesel from Trains PM2.5. 
MATES III Final Report

Appendix IX-53 

FIGURE IX-13g 

CAMx simulated 2005 annual average Diesel from Stationary Sources PM2.5. 

FIGURE IX-13h 

CAMx simulated 2005 annual average Benzene. 
MATES III Final Report

Appendix IX-54 

FIGURE IX-13i 

CAMx simulated 2005 annual average 1,3 Butadiene. 

FIGURE IX-13j 

CAMx simulated 2005 annual average for Total Formaldehyde. 
MATES III Final Report

Appendix IX-55 

FIGURE IX-13k 

CAMx simulated 2005 annual average Acetaldehyde. 

FIGURE IX-13l 

CAMx simulated 2005 annual average Arsenic PM2.5. 
MATES III Final Report

Appendix IX-56 

FIGURE IX-13m 

CAMx simulated 2005 annual average Cadmium PM2.5. 

FIGURE IX-13n 

CAMx simulated 2005 annual average Chromium PM2.5. 
MATES III Final Report

Appendix IX-57 

FIGURE IX-13o 

CAMx simulated 2005 annual average Lead PM2.5. 

FIGURE IX-13p 

CAMx simulated 2005 annual average Methylene Chloride. 
MATES III Final Report

Appendix IX-58 

FIGURE IX-13q 

CAMx simulated 2005 annual average Naphthalene. 

FIGURE IX-13r 

CAMx simulated 2005 annual average Nickel PM2.5. 
MATES III Final Report

Appendix IX-59 

FIGURE IX-13s 

CAMx simulated 2005 annual average p-Dichlorobenzene. 

FIGURE IX-13t 

CAMx simulated 2005 annual average Perchloroethylene. 
MATES III Final Report

Appendix IX-60 

FIGURE IX-13u 

CAMx simulated 2005 annual average Trichloroethylene. 

Estimation of Risk 

Figure IX-14 depicts the distribution of risk estimated from the predicted annual average 

concentrations of the key toxic compounds. (Figure IX-14 is presented twice, first in shaded 

black and white, then in color). Risk is calculated for each grid cell as follows: 

Risk i,j = Σ Concentration i,j,k X Risk Factor i,j,k

Where i,j is the grid cell (easting, northing) and k is the toxic compound. 

The grid cell having the maximum simulated risk of 3,693 was located in the Ports of Los 

Angeles and Long Beach. More specifically, the grids having the top 25 estimated risk values in 

2005 were located in cells around the ports area. The cell having the highest risk outside of the 

port area occurred in South Los Angeles as part of a cluster of grids that extended from Central 

Los Angeles to the southeast, following Interstate 5. Other elevated areas included the eastern 

Basin near the communities of Colton, Inland Valley San Bernardino, and San Bernardino. As 

with the MATES II analysis, areas projected to have higher risk followed transportation 

corridors, including freeways and railways. 

Figure IX-15 provides the CAMx RTRAC simulated risk for the 1998-99 period (using back-cast 

1998 emissions and 1998-99 MM5 generated meteorological data fields). Figure IX-16 depicts 

the 1998-99 to 2005 change in risk estimated from the CAMx RTRAC simulations. The greatest 

increase in risk occurred in the port area. Overall, air toxics risk improves to varying levels in 
MATES III Final Report

Appendix IX-61 

most of the Basin with the exceptions of the areas directly downwind of the Ports and those areas 

heavily impacted by activities associated with goods movement. Risk increases of more than 

800 in a million between the two periods were noted in the immediate areas encompassing the 

ports. 

The 2005 Basin average population weighted risk summed for the toxic components yielded a 

lifetime estimated cancer risk of 853 in a million. (The Basin average risk included all populated 

over-land cells that reside within the Basin portion of the modeling domain). The MATES III 

Basin population weighted average risk is approximately 87% of the MATES II Basin average 

risk (981 per million) determined from the UAMTOX modeling analysis. However, when Basin 

population weighted average risk is recalculated for the 1998-99 MATES II period based on the 

CAMx RTRAC simulations the comparable Basin average risk is 931 per million. A direct 

comparison of Basin population weighted risk calculated using the CAMx RTRAC simulations 

shows an 8% improvement between 1998-99 and 2005. The 8% reduction in Basin risk can be 

attributed to several factors most notably changes in quantity and spatial allocation of emissions 

between 1998 and 2005. While weather profile between the two monitoring periods varied, no 

appreciable difference was observed in the meteorological dispersion potential. 

Figures IX-17a through IX-17f depict risk associated with diesel and its specific emissions 

categories. Figure I-17 provides the Basin risk excluding the contribution of diesel particulates. 

(Again, Figures IX-16a through IX-17 are presented twice, first in shaded black and white, then 

in color). On and off-road diesel impacts are spread throughout the Basin following the 

transportation corridors and off-road facilities such as the intermodal transfer sites. The shipping 

impacts are concentrated in the vicinity of the Ports of Los Angeles and Long Beach and the 

adjacent downwind communities. The shipping lanes to the northwest and southeast following 

the coastline and Asia-bound are clearly depicted. Risk impacts from rail travel/transport and 

stationary sources range from over 200 to 500 in one million respectively. 

Regional risk from nondiesel sources (Figure IX-18) is also uniformly distributed throughout the 

Basin, with values typically ranging from 100 to 300 in one million. Several elevated grid cells 

are apparent with risk estimated upwards of 400 in one million in the coastal plain encompassing 

Los Angeles International Airport and the heavily industrialized areas of south of Downtown Los 

Angeles. Selected elevated grid cells are also evident in the east Basin with localized risk values 

of up to 1,000 in one million. 
MATES III 

Appendix IX-62 

FIGURE IX-14 

2005 MATES III CAMx RTRAC Simulated Air Toxic Risk. 
MATES III 

Appendix IX-63 

FIGURE IX-14 (Repeated) 

2005 MATES III CAMx RTRAC Simulated Air Toxic Risk. 
MATES III 

Appendix IX-64 

FIGURE IX-15 

1998-99 CAMx RTRAC Simulated Air Toxic Risk. 
MATES III 

Appendix IX-65 

FIGURE IX-15 (Repeated) 

1998-99 CAMx RTRAC Simulated Air Toxic Risk. 
MATES III 

Appendix IX-66 

FIGURE IX-16 

Change in CAMx RTRAC simulated risk from the 1998-99 to 2005 

 (using back-cast 1998 emissions and 1998-99 MM5 generated meteorological data fields)
MATES III 

Appendix IX-67 

FIGURE IX-17a 

MATES III Risk from Diesel. 
MATES III 

Appendix IX-68 

FIGURE IX-17a (Repeated) 

MATES III Risk from Diesel.
MATES III 

Appendix IX-69 

FIGURE IX-17b 

MATES III Simulated Risk from On-Road Diesel. 
MATES III 

Appendix IX-70 

FIGURE IX-17b (Repeated) 

MATES III Simulated Risk from On-Road Diesel. 
MATES III 

Appendix IX-71 

FIGURE IX-17c 

MATES III Simulated Risk from Off-road Diesel (including rail yards but excluding trains and s
MATES III 

Appendix IX-72 

FIGURE IX-17c (Repeated) 

MATES III Simulated Risk from Off-road Diesel (including rail yards but excluding trains and s
MATES III 

Appendix IX-73 

FIGURE IX-17d 

MATES III Simulated Risk from Ship Diesel. 
MATES III 

Appendix IX-74 

FIGURE IX-17d (Repeated) 

MATES III Simulated Risk from Ship Diesel. 
MATES III 

Appendix IX-75 

FIGURE IX-17e 

MATES III Simulated Risk from Trains (Excluding Rail Yards). 
MATES III 

Appendix IX-76 

FIGURE IX-17e (Repeated) 

MATES III Simulated Risk from Trains (Excluding Rail Yards). 
MATES III 

Appendix IX-77 

FIGURE IX-17f 

MATES III Simulated Risk from Stationary Diesel. 
MATES III 

Appendix IX-78 

FIGURE IX-17f (Repeated) 

MATES III Simulated Risk from Stationary Diesel. 
MATES III 

Appendix IX-79 

FIGURE IX-18 

MATES III Simulated Risk No-Diesel. 
MATES III 

Appendix IX-80 

FIGURE IX-18 (Repeated) 

MATES III Simulated Risk No-Diesel.
MATES III Final Report

Appendix IX-81 

Figure IX-19 provides a focused 2005 estimated air toxics risk in the Ports area. Table IX-12 

provides a summary risk estimated for the Basin, for the Ports area, and for the Basin excluding 

the Ports area. For this assessment, the Ports area includes the populated cells roughly bounded 

by the Interstate 405 to the north, San Pedro to the west, Balboa Harbor to the east and Pt. 

Fermin to the south. The 2005 average population weighted air toxics risk in the Ports area (as 

defined above) was 1,415 in one million. The Basin average population weighted air toxics risk, 

excluding the grid cells in the Ports area, valued 816 in one million. (It is important to note that 

the downwind impacts resulting from Port area activities are reflected in the air toxics risk 

estimates for the grid cells categorized as “Basin excluding Ports”). A similar calculation based 

on the CAMx RTRAC simulations for 1998-99 indicated that the Ports area air toxics risk was 

1,208; and the Basin, minus the Ports area, was 912 in one million. Overall, the Ports area 

experienced an approximate 17% increase in risk, while the average population weighted risk in 

other areas of the Basin decreased by about 11%. 

As a sensitivity analysis, simulations were generated to examine the hypothesis “what would the 

Basin toxics risk profile in 2005 be if no-growth occurred in the goods movement sector from 

1998?” To attempt to answer this question, heavy-duty truck transport, shipping, port and rail 

operation activity levels associated with goods movement were held at 1998 levels. The impacts 

of fleet turnover and control measure implementation were allowed to go forward through 2005 

to develop the hypothetical emissions inventory. The results of the sensitivity test indicated that 

the Ports area, Basin, and Basin excluding the Ports areas would experience lower air toxic risk 

levels by 6.2%, 14.8%, and 15.4% respectively. 

Figures IX-20 through IX-23 provide close up depictions of air toxics risk to Central Los 

Angeles, Mira Loma/Colton, Central Orange County and West Los Angeles areas, respectively. 

Figure IX-19 

2005 Ports area MATES III Simulated Air Toxic Risk. 
MATES III Final Report

Appendix IX-82 

Table IX-12 

Basin and Port Area Population Weighted Risk 

MATES III MATES II* 

Region 

2005 

Population 

Average 

Risk 

(Per 

Million) 

1998 

Population 

Average 

Risk 

(Per 

Million) 

Average 

Percentage 

Change in 

Risk 

Basin 15,662,620 853 14,404,993 931 -8 

Ports Area 959,761 1,415 911,834 1207 17 

Basin Excluding Ports 

Area 14,702,859 816 13,493,159 912 

-11 

* CAMx RTRAC Simulations 

County Risk Assessment 

Table IX-13 provides the county breakdown of air toxics risk to the affected population for 2005 

MATES III and the 1998-99 MATES II CAMx RTRAC simulations. As presented in the spatial 

distribution, Los Angeles County bears the greatest average risk at 951 per one million person 

population. Orange County has the second highest number of projected risk at 781 per one 

million person population. Risk in the Eastern Basin is lower. The estimated risk for San 

Bernardino is 712 per million, and Riverside was estimated to have the lowest population 

weighted risk at 485. It should be noted that these are county-wide averages and individual 

communities could have higher risks than the average if they are near emissions sources, such as 

rail yards or intermodal facilities. 

Comparison of the county-wide population weighted air toxics risk shows that the greatest 

reduction occurred in Los Angeles County. Reductions in emissions from mobile sources 

including benzene, 1,3 butadiene, and diesel particulate have contributed to the improved 

county-wide risk. A similar profile is evident in Orange County. Despite across-the-board 

improvements in measured toxic air quality from MATES II (with the sole exception of 

hexavalent chromium at Rubidoux), population growth in the Eastern Basin and associated 

increases in mobile source emissions have resulted in a nominal increase in population-weighted 

risk for Riverside County. Similarly, San Bernardino County risk levels improved only 

marginally. 
MATES III Final Report

Appendix IX-83 

Table IX-13 

County-Wide Population Weighted Air Toxic Risk 

MATES III MATES II 

CAMx RTRAC 

Simulations 

Region 

 

2005 

Population 

Average 

Risk 

(Per 

Million) 

1998 

Population 

Average 

Risk 

(Per 

Million) 

Average 

Percentage 

Change in 

Risk 

Los Angeles 9,887,127 951 9,305,726 1,047 -9 

Orange 2,764,620 781 2,579,794 833 -6 

Riverside 1,548,031 485 1,249,554 478 2 

San Bernardino 1,462,842 712 1,269,919 725 -2 

SCAB 15,662,620 853 14,404,993 931 -8 

Figure IX-20 

2005 Central Los Angeles MATES III Simulated Air Toxic Risk. 
MATES III Final Report

Appendix IX-84 

Figure IX-21 

2005 Mira Loma/Colton MATES III Simulated Air Toxic Risk. 

Figure IX-22 

2005 Central Orange County MATES III Simulated Air Toxic Risk. 
MATES III Final Report

Appendix IX-85 

Figure IX-23 

2005 West Los Angeles MATES III Simulated Air Toxic Risk. 

Risk from Key Compounds 

Table IX-14 provides the Basin average breakdown of risk associated with each of the key 

compounds simulated in the analysis. Diesel particulate ranked highest as the toxic compound 

contributing to the overall risk to the population. The next three highest contributors included 

benzene, 1,3 butadiene, and hexavalent chromium. Formaldehyde, acetaldehyde and arsenic 

each contribute approximately 1% of the risk while the remaining compounds combined 

accounted for less than 3% of the total. 

Network Risk Evaluation 

Table IX-15 provides the CAMx RTRAC simulated risk at each of the eight stations for the three 

main toxic compounds and the remaining aggregate based on the regional modeling. Risk is 

calculated using the predicted concentrations of each toxic component for the specific 

monitoring station location (based on a nine-cell weighted average concentration). The summary 

also provides the comparison between simulated average risk for the eight stations combined and 

the average risk calculated using the annual toxic compound measurements and the estimated 

diesel concentrations at those sites. 
MATES III Final Report

Appendix IX-86 

Table IX-14 

2005 MATES III Risk from Simulated Individual Toxic Compounds 

Compound 

 

Risk Factor 

( μg/m3

) 

Highest Grid 

Cell 

Concentration 

Population 

Weighted 

Annual 

Average 

Concentration 

Units 

Population 

Weighted 

Risk 

(per million) 

Percent 

Contribution 

Diesel 3.00E-04 11.70 2.35 μg/m3

 703.76 82.5 

Benzene 2.90E-05 1.15 0.48 ppb 44.53 5.2 

1,3 Butadiene 1.70E-04 2.32 0.081 ppb 30.45 3.6 

Hexavalent Chromium 1.50E-01 0.003 0.00016 μg/m3 23.41 2.7 

Primary 

Formaldehyde 6.00E-06 4.89 1.60 ppb 11.78 1.4 

Secondary 

Formaldehyde 6.00E-06 1.60 1.30 ppb 9.61 1.1 

Arsenic 3.30E-03 0.022 0.0024 μg/m3

 7.97 0.9 

p-Dichlorobenzene 1.10E-05 0.208 0.076 ppb 5.01 0.6 

Secondary 

Acetaldehyde 2.70E-06 0.766 0.67 ppb 3.25 0.4 

Perchloroethylene 5.90E-06 0.370 0.92 ppb 3.67 0.4 

Napthalene 3.40E-05 0.046 0.017 ppb 3.10 0.4 

Cadmium 4.20E-03 0.009 0.00054 μg/m3

 2.28 0.2 

Primary Acetaldehyde 2.70E-06 0.917 0.35 ppb 1.72 0.2 

Methylene Chloride 1.00E-06 1.062 0.29 ppb 1.02 0.1 

Nickel 2.60E-04 0.298 0.0035 μg/m3

 0.90 0.1 

Trichloroethylene 2.00E-06 0.340 0.029 ppb 0.31 < 0.1 

Lead 1.20E-05 0.104 0.0075 μg/m3

 0.09 <0.1 

The highest simulated risk was estimated for West Long Beach followed by Los Angeles, North 

Long Beach and Compton. The lowest modeled risk was simulated at Burbank. As previously 

discussed, simulation performance at Burbank showed a tendency for underprediction, and this 

feature appears to be translated to the risk calculation. 

The nondiesel portion of the simulated risk can be directly compared to risk calculated from the 

toxic compound measurements. Figure IX-24 presents a comparison of the model simulated and 

measurement estimated nondiesel risk at each monitoring site as well as the eight-station 

average. Simulated nondiesel risk is within 30% of measurements at all stations with the sole 

exception of Burbank. In general, there appears to be no geographical bias in model 
MATES III Final Report

Appendix IX-87 

performance and the simulated eight-station average risk is essentially equal to the risk estimated 

from the measurements. 

Simulated total risk includes the contribution of diesel particulates; and, taken as an eight-station 

average, the modeled risk is 1,166 in a million. The eight-station average simulated risk is 

approximately 6% lower than the risk calculated from the measured toxic compound 

concentrations, and the estimates of diesel concentrations using the emissions based factor (1.95) 

applied to the EC2.5 average concentration. When the model simulated risk is compared to the 

measurement calculated risk including the range of CMB estimated diesel concentrations, the 

eight-station average risk was nominally less than the lower projection of the range based on 

measurement data. The eight-station simulated risk based on the CAMx RTRAC analyses was 

approximately 10% lower than the average of the CMB estimated diesel risk based on the two 

source profiles. 

Table IX-15 

Comparison of Network Averaged CAMX RTRAC 2005 Modeled Risk to Measured Risk at the 

Eight MATES III Sites 

2005 MATES III CAMX RTRAC Simulation 

Location Benzene 1,3 

Butadiene Others Diesel Total 

Anaheim 47 31 75 900 1,054 

Burbank 44 25 64 613 746 

Compton 52 54 94 950 1,150 

Inland Valley San Bernardino 41 25 121 734 922 

North Long Beach 53 36 84 1,282 1,455 

Central Los Angeles 64 47 115 1,256 1,482 

Rubidoux 42 33 70 700 845 

West Long Beach 55 30 86 1,501 1,672 

Simulated 8-Station Average 50 35 89 992 1,166 

8-Station MATES III Average 

Measured (EC2.5 * 1.95 for Diesel) 53 34 83 1,070 1,240 

8-Station Average Measured 

(with range of CMB Diesel risk ) 53 34 83 1,004– 1,120 

1,174 – 

1,290 

8-Station Average Measured 

(average of CMB Diesel risk ) 53 34 83 1,062 1,232 
MATES III Final Report

Appendix IX-88 

0

50

100

150

200

250

300

Anaheim Burbank Compton Inland

Valley

S.B.

North

Long

Beach

Los

Angeles

Rubidoux West

Long

Beach

8-Station

Average

Risk Per Million

Observed Estimated

Figure IX-24 

2005 MATES III Simulated Vs. Measured Compounds NonDiesel Air Toxics Risk. 

Evaluation 

The population weighted average Basin air toxic risk (853 per million) simulated using CAMx 

RTRAC for the 2005 MATES III period was estimated to be 8% lower than that estimated for 

1998-99 (931 in a million) when the same modeling platforms and year-specific meteorology are 

evaluated. This is loosely compared to a 13% reduction in average population weighted risk 

estimated for the 1998-99 MATES II analysis (981 in a million) using the UAMTOX modeling 

platform. The areas of the Basin having maximum risk continued to be the Ports of Los Angeles 

and Long Beach with a secondary maximum occurring in an area starting in South Los Angeles 

and extending towards southeastern Los Angeles. 

The average simulated Basin risk for the 2005 MATES III data is 8% lower than the comparable 

average risk estimated for the 1998 MATES II analysis. Using the 2007 AQMP inventory backcast methodology, the percentage reduction in diesel mass emissions from 1998 to 2005 is 

approximately 5%. However, emissions reductions of benzene (36%), 1,3-butadiene (31%), 

arsenic (20%) and hexavalent chromium (85%) contribute greatly to the overall reduction in 

2005 simulated risk. A general assessment of the observed meteorological profile suggests that 

the two monitoring periods were comparable in dispersion potential. 
MATES III Final Report

Appendix IX-89 

References 

ENVIRON, Inc., 2008, CAMx User’s Guide Version 4.5. ENVIRON. Novato, CA 94945 

ENVIRON, Inc., 2005, “METSTAT software for MM5 version 3 (02/11/05),” ENVIRON. 

Novato, CA 94945, http://www.camx.com/down/support.php 

ENVIRON, Inc., 2006, ”KVPATCH software for CAMx,” ENVIRON. Novato, CA 94945, 

http://www.camx.com/down/support.php 

J.J. O’Brien, 1970, A note on the vertical structure of the eddy exchange coefficient in the 

planetary boundary layer. J. Atmos. Sci., 27, 1213-1215 

PSU/NCAR Mesoscale Model (MM5) 2004, http://www.mmm.ucar.edu/mm5/mm5-home.html 

WRAP, 2007, Western Regional Air Partnership, Technical Support System, Emissions Method, 

Offshore Emissions, http://vista.cira.colostate.edu/

U.S. EPA, 2006,” Guidance on Use of Modeled and Other Analyses for Demonstrating 

Attainment of Air Quality Goals for Ozone, PM2.5 and Regional Haze NAAQS,” U.S. EPA, 

Office of Air Quality Planning and Standards, Emissions, Monitoring, and Analysis Division, 

Air Quality Modeling Group, Research Triangle Park, North Carolina, September, 2006