CHAPTER 4 

REGIONAL MODELING AND EVALUATION 
MATES III Final Report

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Chapter 4. Regional Modeling and Evaluation 

4.1 Introduction 

Regional air quality modeling is used to determine the concentration impact in time and space to 

the community due to emissions from a single or group of known toxic compounds and 

emissions sources. The model simulated concentration contours of toxic compounds are 

translated into a pattern of health risk based upon compound potency risk factors. The regional 

modeling provides a mechanism to disperse the emissions from a variety of source categories as 

well as individual sources to estimate a mass consistent impact throughout the modeling domain. 

This analysis complements the data analytical techniques used to assess concentration and risk 

from the data acquired at the fixed monitoring sites. 

Several comments received from reviewers of the Draft MATES III report were directed at the 

regional modeling analysis and evaluation. The key areas addressed: 

 

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

both MATES II and MATES III; 

• The simulation performance 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 suggestions to: 

• 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 document attempts to answer the 

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

document 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 (CAMx) enhanced with 

a reactive tracer modeling capability (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 
MATES III Final Report

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

and destruction of reactive air toxic compounds. 

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. (Figure 4-1 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). 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. 

Figure 4-1 

MATES III Modeling Domain. 

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

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

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

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MATES III Final Report

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

the dispersion profile for the simulations. 

4.2 Background 

In the 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 protracted two-squared kilometer grid domain that overlaid the 

Basin. The analysis relied on the 1998 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. 

4.3 MATES III vs. MATES II: Key Modeling Assumptions 

The MATES II modeling analysis was conducted using the UAM dispersion platform and the 

TOX chemistry package. The UAMTOX model was simulated using diagnostic meteorological 

model output and 1999 emissions data. At the time when the MATES II simulations were 

conducted, UAM was considered a recommended dispersion platform by U.S. EPA through their 

modeling guidance documents. The TOX chemistry package was one of a select few chemistry 

packages available for consideration in the analysis. 

The MATES III simulations were conducted using the contemporary CAMx – MM5 coupled 

with the RTRAC chemistry. The decision to move away from UAMTOX for the current 

analysis was twofold: (1) to build upon the advances gained in the 2007 AQMP in annual 

particulate modeling using the peer recommended state-of-the-science modeling tools, and (2) to 

provide analysis consistency with the 2007 AQMP PM2.5 attainment demonstration. (Note: the 

regional modeling analysis presented in this final document differs from that presented in the 

draft to account for modifications made to modeling assumptions, most notably the use of a landuse based vertical dispersion algorithm and changes in EC shipping emissions allocations in 

response to comments received from reviewers). 

It is difficult to fully assess the impact caused by the shift in modeling platforms and chemistry 

modules. Table 4-1 summarizes the major differences in the toxic modeling between the final 

MATES III and MATES II analyses. For example, MM5 model meteorological fields, including 

wind characterization and estimation of vertical diffusion, differ significantly from those created 

using diagnostic approaches and can greatly alter dispersion patterns throughout the modeling 

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MATES III Final Report

domain. Changes to emissions estimation assumptions add to the uncertainty of a direct 

comparison of model simulations. 

Table 4-1 

Summary Comparison of Key Modeling Considerations Between 

MATES III and MATES II 

Parameter MATES III and 1998-99 Backcast MATES II 

Model Platform / 

Chemistry 

CAMx RTRAC UAMTOX 

Meteorology Model 

/Layers 

MM5 Prognostic: 29 

layers/CAMx: 8 layers 

Diagnostic Wind Model / 

UAMTOX: 5 layers 

Vertical Diffusion Blackadar PBL to determine 

grid-layer specific vertical 

diffusivity 

Hourly grid specified mixing 

height 

On-Road Truck 

Emissions 

Caltrans/SCAG Truck Model Used passenger vehicle pattern 

Shipping Emissions 

Stack Height 

Emissions spread through 

layers 1 and 2 

Emissions released in layer 1 

(variable size) 

Emissions Inventory 2005 Projection from 2002 

(2007 AQMP) 

1998 Projection from 1997 

(2003 AQMP) 

Mobile Emissions EMFAC2007 EMFAC7G 

To remedy this problem, this analysis provides a newly-generated set of regional modeling 

simulations for the MATES II monitoring period using the CAMx – MM5 coupled with the 

RTRAC chemistry, 1999 back-cast emissions and newly generated 1998-99 meteorological 

fields to facilitate a direct air quality and risk comparison between MATES II and MATES III. 

Development of the new simulations follow the same set of assumptions and model applications 

(where possible) as for the final MATES III analysis. 

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 ocean-going (deep draft) vessels extend above 36 and 

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

layer. 

Second, the diesel particulate emissions profile for marine vessels and ocean-going vessels using 

diesel engines was changed to reflect a lower percentage of elemental carbon contribution to the 

total mass. The initial profile used in the draft MATES III modeling simulations (as well as 

MATES II analysis) was characteristic of an on-road diesel truck profile where elemental carbon 

fraction accounted for more than 20% of the particulate mass. The revised analyses used a 

stationary source large diesel engine profile (which is assumed to be more consistent with the 

large engines operating on ships) that allocated the elemental carbon fraction at approximately 

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MATES III Final Report

6% of the total mass of diesel emissions. 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, arterial 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. 

4.4 Modeling Results 

CAMx RTRAC regional modeling was conducted using MM5 meteorological data and projected 

emissions data for 2005 to simulate annual average concentrations of 19 key compounds 

measured as part of the MATES III monitoring program. Simulated annual average 

concentrations plots for the four toxic compounds that contributed the greatest risk throughout 

the domain (diesel particulate, benzene, 1,3-butadiene and formaldehyde) are depicted in Figures 

4-2 through 4-5. 

Figure 4-2 depicts the projected annual average concentration distribution of diesel particulates 

in the Basin. The highest concentration (10.8 μg/m3

) was simulated to occur in the grid cells 

around the Ports of Los Angeles and Long Beach. A secondary maximum occurs in the Central 

Los Angeles area extending southeast loosely following the Interstate 5 Corridor. In general, the 

distribution of diesel particulates is aligned with the transportation corridors including freeways, 

major arterials and rail right-of-ways. Figures 4-3 and 4-4 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 fuel consumption). The formaldehyde 

profile shown in Figure 4-5 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). 

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MATES III Final Report

Figure 4-2 

Annual Average Concentration Pattern for Diesel PM2.5 

Figure 4-3 

Annual Average Concentration Pattern for Benzene 

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Figure 4-4 

Annual Average Concentration Pattern for 1,3-Butadiene 

Figure 4-5 

Annual Average Concentration Pattern for Total Formaldehyde 

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Table 4-2 provides a summary of the model performance to recreate measured annual average 

concentrations. 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. 

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 particulate concentrations based on 

Chemical Mass Balance (CMB) analysis using ambient measured elemental carbon 

concentrations are discussed later. Measured concentrations of naphthalene were available for 

West Long Beach, Central Los Angeles, and Rubidoux. 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 toward impacts to the coastal communities in 

the heavily transited areas of the Basin. Moreover, the assessment provides a direct comparison 

for model performance evaluation. 

Table 4-2 

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) 

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 

Cr 6 (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 

1,3-Butadiene 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 

* Three station average 

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MATES III Final Report

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 

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, the substitution of one-half level of 

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

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. Table 4-3 summarizes the 2005 MATES III EC2.5 model performance. 

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

using measures of prediction bias and error. An additional useful tool is prediction accuracy 

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

EC2.5 concentrations. 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. PA at seven of the eight MATES III sites meet the PM2.5 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 North Long Beach is overpredicted by 22%. All other sites PA falls 

within ±10 % of observations. 

Analysis of the poor performance at Burbank revolves around the inability of the meteorological 

model to exactly recreate observed winds in an area of complex terrain where the winds are 

required to bifurcate and reverse directions in a short distance. Winds from the southeast 

transport mobile source emissions from the 101 Freeway, Interstate 5, and a major leg of the 

north and southbound commuter and cargo rail systems directly at the Burbank air monitoring 

site. While the MM5 wind fields do an admirable job of turning the sea breeze northward in the 

immediate Burbank area, the simulated resultant flow is from the south and only captures a 

portion of the mobile source impact. In addition, the upwind grid cells adjacent to the south of 

the Burbank grid include the wild land open space of Griffith Park where emissions are limited. 

(A detailed discussion of model performance is presented in Appendix IX). 

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MATES III Final Report

Table 4-3 

MATES III 2005 EC2.5 Model Performance 

Location 

EC2.5

Observed 

(μg/m3

) 

Modeled 

Observed 

Days 

(μg/m3

) 

Prediction 

Accuracy 

Mean 

Bias 

(μg/m3

) 

Mean 

Error 

(μg/m3

) 

Normalized 

Mean Bias 

(μg/m3

) 

Normalized 

Mean Error 

(μg/m3

) 

Anaheim 1.41 1.35 -4 -0.06 0.54 0.39 0.61 

Burbank 2.04 1.03 -50 -1.02 1.11 -0.31 0.48 

Compton 1.76 1.88 7 0.12 0.61 0.39 0.52 

Inland Valley San 

Bernardino. 2.18 1.77 -19 -0.41 0.91 0.09 0.56 

Long Beach 1.40 1.71 21 0.30 0.61 0.54 0.64 

Central L.A. 1.93 2.04 6 0.11 0.76 0.39 0.58 

Rubidoux 1.69 1.32 -22 -0.38 0.74 0.09 0.58 

West Long Beach 2.07 2.14 3 0.07 0.79 0.33 0.53 

All Stations 1.86 1.70 -9 -0.17 0.77 0.23 0.54 

4.5 Estimation of Risk 

Figure 4-6 depicts the distribution of risk estimated from the predicted annual average 

concentrations of the key toxic compounds. 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 4-7 provides the CAMx RTRAC simulated air toxics risk for the 1998-99 period (using 

back-cast 1998 emissions and 1998-99 MM5 generated meteorological data fields). Figure 4-8 

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 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 

cancer risk of 853 in a million. (The Basin average risk included all populated over land cells 

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MATES III Final Report

that reside within the Basin portion of the modeling domain). The MATES II Basin average risk 

was 981 per million as determined from the UAMTOX modeling analysis. However, when 

Basin population-weighted average risk is recalculated for the 1998-99 MATES II period using 

CAMx RTRAC modeling platform the comparable Basin average risk is 931 per million. A 

direct comparison of Basin risk calculated using the CAMx RTRAC simulations between 

MATES II and MATES III shows an 8% reduction. The 8% reduction in Basin risk can be 

attributed to several factors, most notably changes in emissions and spatial allocation between 

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

appreciable difference was observed in the meteorological dispersion potential. 

Regional risk from non-diesel sources (Figure 4-9) 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 south of Downtown Los 

Angeles. Selected elevated grid cells are also evident in the east Basin with values of up to 1,000 

in one million. 

Figure 4-10 provides a focused 2005 estimated air toxics risk in the Ports area. Table 4-4 

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 toxics risk estimates 

for the grid cells categorized as “Basin minus 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 toxic risk 

levels by 6.2%, 14.8%, and 15.46% respectively. 

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MATES III 

4-12 

Figure 4-6 

2005 MATES III CAMx RTRAC Simulated Air Toxic Risk 
MATES III 

Figure 4-7

1998-99 MATES II CAMx RTRAC Simulated Air Toxic Risk 

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MATES III 

Figure 4-8 

Change in CAMx RTRAC Simulated Air Toxics Risk (per million) from the 1998-99 to 2

 (using back-cast 1998 emissions and 1998-99 MM5 generated meteorological data field

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MATES III 

Figure 4-9 

MATES III 2005 Simulated Air Toxic Risk-No Diesel

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MATES III Final Report

4-16 

Figure 4-10 

 2005 Ports Area MATES III Simulated Air Toxic Risk 

Table 4-4 

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 
MATES III Final Report

Figures 4-11 through 4-14 provide close-up depictions of risk to Central Los Angeles, Mira 

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

Table 4-5 provides the county breakdown of air toxics risk to the affected population. 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 railyards or intermodal facilities. 

Comparison of the county-wide population-weighted 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 east Basin and associated increases in mobile source 

emissions has resulted in a nominal increase in population-weighted risk for Riverside County. 

Similarly, San Bernardino County risk levels improved only marginally. 

Table 4-5 

County-Wide Population-Weighted Risk 

Region MATES III MATES II* 

 

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 

* CAMx RTRAC Simulations 

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Figure 4-11 

2005 Central Los Angeles MATES III Simulated Air Toxic Risk 

Figure 4-12 

2005 Mira Loma/Colton MATES III Simulated Air Toxic Risk 

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Figure 4-13 

2005 Central Orange County MATES III Simulated Air Toxic Risk 

Figure 4-14 

2005 West Los Angeles MATES III Simulated Air Toxic Risk 

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Table 4-6 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 from air toxics to the population. The next three highest 

contributors included benzene, 1,3-butadiene and hexavalent chromium. 

Table 4-6 

2005 MATES III Risk from Simulated Individual Toxic Air Contaminants 

Toxic 

Compound 

 

Risk Factor 

( μg/m3

) 

Peak 

Annual 

Average 

Concentration 

Population 

Weighted 

Annual 

Average 

Concentration 

Units Cumulative 

Risk 

(per million) 

% 

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 

6 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 

Table 4-7 provides the simulated air toxics risk at each of the eight stations (evaluated in Table 

4-2) 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 

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MATES III Final Report

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

the estimated diesel concentrations at those sites. 

Table 4-7 

 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 

8-Station Average Modeled 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 

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 non-diesel portion of the simulated risk can be directly compared to risk calculated from the 

toxic compound measurements. Figure 4-15 presents a comparison of the model simulated and 

measurement estimated non-diesel risk at each monitoring site, as well as the eight-station 

average. Simulated non-diesel 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 

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 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 

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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. 

4.6 Evaluation 

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

RTRAC for the 2005 MATES III period was estimated to be 8% lower than estimated (931 in a 

million) for 1998-99 when the same modeling platforms and year specific meteorology are 

evaluated. This is loosely compared to a 17% reduction in average population-weighted risk 

(981) estimated for the 1998-99 MATES II analysis 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 toward southeastern Los Angeles. 

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 4-15 

2005 MATES III Simulated vs. Measured Concentrations for Non-Diesel Air Toxics Risk 

The average simulated Basin air toxics 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 back-cast 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. 

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4-23 

4.7 References 

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

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