EXECUTIVE SUMMARY 
MATES III Final Report

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Executive Summary 

The Multiple Air Toxics Exposure Study III (MATES III) is a monitoring and evaluation study 

conducted in the South Coast Air Basin (Basin). The study is a follow on to previous air toxics 

studies in the Basin and is part of the South Coast Air Quality Management District (SCAQMD) 

Governing Board Environmental Justice Initiative. 

The MATES III Study consists of several elements. These include a monitoring program, an 

updated emissions inventory of toxic air contaminants, and a modeling effort to characterize risk 

across the Basin. The study focuses on the carcinogenic risk from exposure to air toxics. It does 

not estimate mortality or other health effects from particulate exposures. The latter analysis was 

conducted as part of the 2007 Air Quality Management Plan and is not included here. 

A network of ten fixed sites was used to monitor toxic air contaminants once every three days for 

two years. The location of the sites was the same as in the previous MATES II Study to provide 

comparisons over time. The one exception is the West Long Beach site, which was about 2.5 

miles east of the Wilmington location used in MATES II. The locations of the sites are shown in 

Figure ES-1. 

The initial scope of the monitoring was for a one-year period from April 2004 through March 

2005. Due to the heavy rains in the Basin in the fall and winter of this period, there was concern 

that the measurements may not be reflective of typical meteorology. The study was thus 

extended for a second year from April 2005 through March 2006. 

In addition to the fixed sites, five additional locations were monitored for periods of several 

months using moveable monitoring platforms. These microscale sites were chosen to determine 

if there were gradients between communities that would not be picked up by the fixed locations. 

The study also included an update of the toxics emissions inventories for the Basin and computer 

modeling to estimate toxics levels throughout the Basin. This allows estimates of air toxics risks 

in all areas of the Basin, as it is not feasible to conduct monitoring in all areas. 

To provide technical guidance in the design of the study, a Technical Advisory Group was 

formed. The panel of experts from academia, environmental groups, industry, and public 

agencies provided valuable insights on the study design. Components of the study recommended 

by the Advisory Group included monitoring for longer periods at the microscale sites, including 

naphthalene in the monitoring program, and including more up-to-date methods to estimate the 

contribution of diesel exhaust to ambient particulate levels. In the monitoring program, over 30 

air pollutants were measured. These are listed in Table ES-1. These included both gaseous and 

particulate air toxics. 

The monitored and modeled concentrations of air toxics were then used to estimate the 

carcinogenic risks from ambient levels. Annual average concentrations were used to estimate a 

lifetime risk from exposure to these levels, consistent with guidelines established by the Office 

of Environmental Health Hazard Assessment (OEHHA) of the California Environmental 

Protection Agency (EPA). 
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Table ES-1 Substances Measured in MATES III 

Benzene 1,3-Butadiene Carbon Tetrachloride 

Chloroform Dichlorobenzene Methylene Chloride 

MTBE Perchloroethylene 

(Tetrachloroethylene) Dichloroethane 

Dibromoethane Ethyl Benzene Toluene 

Trichloroethylene Xylene Styrene 

Vinyl Chloride Acetaldehyde Formaldehyde 

Acetone Methyl ethyl ketone 

Arsenic Cadmium Hexavalent Chromium 

Copper Lead Manganese 

Nickel Selenium Zinc 

Elemental Carbon Organic Carbon Naphthalene 

PAHs PM10 PM2.5

To assess the potential carcinogenic risk, at least one full year of data is preferred to represent 

exposure potential. Thus, the fixed site data was used to calculate risk estimates and the 

microscale sites used solely to determine any gradients compared to the nearest fixed monitoring 

site. To estimate the risks from the fixed sites, the concentrations measured over each of the two 

years were averaged to estimate exposure. The Huntington Park and Pico Rivera sites did not 

have a full year of data for the second year of the study; thus, only the first year of data was used 

for these two sites. 

In the MATES II Study, elemental carbon (EC) was used as a surrogate for diesel particulate 

levels, as staff determined that this was the best method available during the MATES II Study. 

For the present study, staff used the Chemical Mass Balance (CMB) source apportionment 

technique to estimate the contribution from diesel, as well as from other major source categories, 

to the measured particulate levels. 

Key results of the study are presented below. 

Fixed Site Monitoring 

The carcinogenic risk from air toxics in the Basin, based on the average concentrations at the 

fixed monitoring sites, is about 1,200 per million. This risk refers to the expected number of 

additional cancers in a population of one million individuals that are exposed over a 70-year 

lifetime. Using the MATES III methodology, about 94% of the risk is attributed to emissions 

associated with mobile sources, and about 6% of the risk is attributed to toxics emitted from 

stationary sources, which include industries, and businesses such as dry cleaners and chrome 

plating operations. The average risks from the annual average levels of air toxics calculated 

from the fixed monitoring sites data are shown in Figure ES-2. 

The air toxics risk at the fixed sites ranged from 870 to 1,400 per million. The risk by site 

averaged over the two study years is depicted in Figure ES-3. For the second year of the study, a 

full year of data was not collected at two of the sites (the Huntington Park site access was not 
MATES III Final Report

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extended for the second year; and the Pico Rivera site was moved during the second year 

resulting in several months without data). The second year data include results for only eight 

sites. Sites with higher levels of risk include Burbank, Central Los Angeles, Inland Valley San 

Bernardino, Huntington Park, and West Long Beach. The site with the lowest risk is Anaheim. 

The results indicate that diesel exhaust is the major contributor to air toxics risk, accounting on 

average for about 84% of the total. 

To compare different methods used to estimate diesel particulate levels, the method used in 

MATES II, which was based on the emissions ratios of diesel particulate and elemental carbon 

from a study conducted in the South Coast in the 1980’s, and a method based on the ratio of 

PM2.5 emissions from the 2005 emissions inventory were both calculated. For MATES II, the 

PM10 elemental carbon levels were multiplied by 1.04 to estimate diesel particulate. The 2005 

PM2.5 inventory finds a ratio of diesel particulate to elemental carbon emissions of 1.95. 

Multiplying the PM2.5 elemental carbon levels by the 1.95 ratio gives another estimate of diesel 

particulate. The estimates using these methods compared to using the CMB model are shown in 

Table ES-2. Should one use the same diesel particulate estimation methodology as MATES II, 

there is about a 30% reduction in ambient levels between the two studies. Based on comparisons 

of the three methods to estimate diesel particulate, the method used for MATES II gives the 

lowest estimates of ambient diesel particulate. 

For the CMB model, the estimates were sensitive to the species profile used for gasoline 

vehicles. Table ES-2 shows the range of values using two different gasoline profiles. The 

estimates used for the risk calculations were the midpoint of the range. As shown in the table, 

both the CMB model and the PM2.5 emissions ratio from the 2005 emissions inventory method 

give similar estimates, and both are higher than the MATES II method. Thus the MATES II 

Study method is likely underestimating the levels of diesel particulate. 

Table ES-2 CMB Estimate of Diesel Particulate Compared to Emissions Inventory Ratio 

Methods. 

Estimation Method

MATES III 

Diesel PM 

μg/m3

MATES II Method: 

PM10 EC x 1.04 2.16 

2005 Inventory Method: 

PM2.5 EC x 1.95 3.5 

CMB Method 3.20 – 3.49 

Note: Year 2 includes data for eight sites only. The MATES II diesel particulate was estimated 

at 3.4 μg/m3. 
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Modeling 

Several updates to the modeling platform were included in this study compared to MATES II. 

The model used was the Comprehensive Air Quality Model with Extensions (CAMx). This 

model is consistent with that used in the 2007 Air Quality Management Plan. A grid size of 2 

kilometers was used. 

In addition to using an updated air toxics emissions inventory, an improved geographical 

allocation of diesel emissions was employed. 

The modeling results are shown in Figure ES-4. The grid cell with the highest air toxics risk was 

at the ports. The grid cells near the ports ranged from about 1,100 to 3,700 in a million. In 

addition to the ports, an area of elevated risk is shown near the Central Los Angeles area with 

grid cells ranging from about 1,400 to 1,900 per million. There are also higher levels of risk that 

track transportation corridors and freeways. 

Since the modeling platform and emissions inventory methods are different in MATES III than 

those used in MATES II, the CAMx model was applied to the MATES II time frame for a more 

”apples to apples” assessment. The MATES III methodology was also used to back-cast the 

estimates of air toxics emissions for the MATES II timeframe. Comparing the results, a lesser 

level of carcinogenic risk was estimated across the Basin for MATES III compared to the 

MATES II time period. The model also shows the dominant contribution from mobile sources 

and diesel emissions to air toxics risk in the MATES II timeframe as well. 

For comparison purposes, Table ES-3 shows the estimated population weighted risk across the 

Basin for the MATES III and MATES II periods. The population weighted risk was about 8% 

lower compared to the MATES II period. 

The MATES III modeling analysis represents several improvements over that used in MATES II 

and represents the state-of-science application of regional modeling tools and chemistry applied 

to an updated set of meteorological and emissions data input. 

Table ES-3 Modeled Air Toxics Risk Comparisons Using the CAMx Model 

 MATES III MATES II Change 

Population 

weighted risk 

(per million) 

853 931 -8% 

Figure ES-5 depicts the 1998-99 to 2005 change in air toxics risk for each model grid cell 

estimated from the CAMx simulations. 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. The model comparison shows 

an increase in air toxics risk occurred in the immediate areas encompassing the ports of more 
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than 800 in a million between the two periods. This increase correlates with the increased 

container cargo moving through the ports and increases in goods movement that occurred 

between the MATES II and MATES III time periods. 

Noncancer Assessment 

To assess the potential for noncancer health risks, the monitored average levels were compared 

to the Chronic Reference Exposure Levels (RELs) established by OEHHA. The chronic REL is 

the air concentration at or below which adverse noncancer health effects would not be expected 

in the general population with exposure for at least a significant fraction of a lifetime. In 

general, the measured concentrations of air toxics were below the RELs. 

The exception is formaldehyde. The chronic REL is 3 μg/m3 (2ppb). All of the fixed site 

annual averages were above this concentration, ranging from 2.9 ppb for Anaheim to 4.5 ppb at 

Los Angeles. Formaldehyde effects include eye irritation, injury to nasal tissue, and respiratory 

discomfort. OEHHA, however, is proposing revisions to the RELs for several toxic air 

contaminants. For formaldehyde, the proposed chronic REL is 9 μg/m3 (7 ppb). If the proposed 

level is promulgated, then all sites would be under the chronic REL. 

Caveats and Uncertainty 

One source of uncertainty is that currently there is no technique to directly measure diesel 

particulates, the major contributor to risk in this study, so indirect estimates based on 

components of diesel exhaust must be used. The method chosen to estimate diesel particulate is 

the CMB source apportionment model. This method is a weighted multiple linear regression 

model based on mass balance of each chemical species applied to apportion contributions to 

ambient particulates using measured source profiles. The CMB method accounts for major 

source categories and geographic differences in source contributions and was recommended by 

the Technical Advisory Group. It is staff’s judgment that this is the most appropriate method to 

estimate the ambient levels of diesel particulate matter. 

The MATES II Study used elemental carbon as a surrogate for diesel particulate. Elemental 

carbon, however, is not a unique tracer for diesel, as there are additional emission sources of 

elemental carbon. Using the CMB model takes advantage of the specific profile of chemical 

species emitted from different particulate matter sources. Twenty-three species were used in the 

CMB model to reconcile source contributions to observed ambient concentrations. This results 

in a more robust apportionment of source contributions to ambient particulate matter levels, since 

all major sources of particulate matter and elemental carbon are considered. 

The CMB model uses the profile of chemical tracer chemical species from different source 

categories to estimate the contribution to ambient particulates. Some tracers are unique to a 

given source, such as levoglucosan from biomass burning, whereas other sources show specific 

chemical profiles that can be used to apportion these sources, such as gasoline and diesel 

combustion. The advantage of the CMB model is that it can apportion several sources to 

ambient levels. Additional discussion is provided in Chapter 2 and Appendix VII on the CMB 

methodology. 
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The Positive Matrix Factorization (PMF) model was also evaluated for estimation of diesel 

particulate. The PMF model is an alternating least squares method that estimates source profiles 

and source contributions from the ambient data. Since possible solutions to this model can be 

negative, the procedure uses restrictive functions so that no sample can have a negative source 

contribution and no species can have a negative fraction in any source profile. Estimated source 

profiles are then attributed to specific sources using experienced judgment. However, using the 

MATES III data, the initial attempts at source apportionment found that some source profiles 

could not be interpreted, and some profiles could not be confirmed with confidence. 

Additionally, the statistical parameters of the PMF model performance were outside of the 

bounds used to determine adequate performance of the model. Also, in perusing the literature of 

applications of PMF approach, it was found that substantial amounts of measured data were 

sometimes excluded from the analyses, and an uncertainty parameter for some variables was 

altered to improve the model performance. Staff did not censor any data or alter certain 

parameters in the model in an attempt to improve the model performance statistics. The 

uncertainties used for the ambient measurements were those provided by the laboratory analyses. 

Thus, the PMF method was not pursued. 

When compared to the MATES II method, the CMB model available from the U.S. EPA gives 

higher estimates of diesel particulates. The CMB model estimate for diesel particulate was 

found to be sensitive to the gasoline emissions profile used. To account for this, the midpoint of 

a range of estimates using two different gasoline profiles was used. 

There are also uncertainties in the risk potency values used to estimate lifetime risk of cancer. 

This study used the unit risks for cancer potency established by OEHHA and the annual average 

concentration measured or modeled to calculate risk. This methodology has long been used to 

estimate the relative risks from exposure to air toxics in California and is useful as a yardstick to 

compare potential risks from varied sources and emissions and to assess any changes in risks 

over time that may be associated with changing air quality. 

The estimates of health risks are based on the state of current knowledge, and the process has 

undergone extensive scientific and public review. However, there is uncertainty associated with 

the processes of risk assessment. This uncertainty stems from the lack of data in many areas 

necessitating the use of assumptions. The assumptions are consistent with current scientific 

knowledge, but are often designed to be conservative and on the side of health protection in 

order to avoid underestimation of public health risks. 

As noted in the OEHHA risk assessment guidelines, sources of uncertainty, which may either 

overestimate or underestimate risk, include: (1) extrapolation of toxicity data in animals to 

humans, (2) uncertainty in the estimation of emissions, (3) uncertainty in the air dispersion 

models, and (4) uncertainty in the exposure estimates. Uncertainty may be defined as what is not 

known and may be reduced with further scientific studies. In addition to uncertainty, there is a 

natural range or variability in the human population in such properties as height, weight, and 

susceptibility to chemical toxicants. 

Thus, the risk estimates should not be interpreted as actual rates of disease in the exposed 

population, but rather as estimates of potential risk, based on current knowledge and a number of 
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assumptions. However, a consistent approach to risk assessment is useful to compare different 

sources and different substances to prioritize public health concerns. 

Conclusion 

Compared to previous studies of air toxics in the Basin, this study found a decreasing risk for air 

toxics exposure, with the estimated Basin-wide population-weighted risk down by 8% from the 

analysis done for the MATES II time period. The ambient air toxics data from the ten fixed 

monitoring locations also demonstrated a reduction in air toxic levels and risks. 

Policy Implications 

While there has been improvement in air quality regarding air toxics, the risks are still 

unacceptable and are higher near sources of emissions such as ports and transportation corridors. 

Diesel particulate continues to dominate the risk from air toxics, and the portion of air toxic risk 

attributable to diesel exhaust is increased compared to the MATES II Study. 

The highest air toxics risks are found near the port area, an area near Central Los Angeles, and 

near transportation corridors. The results from this study underscore that a continued focus on 

reduction of toxic emissions, particularly from diesel engines, is needed to reduce air toxics 

exposure. 
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Figure ES-1 Map of MATES III Monitoring Sites 

F

o

Rubidoux

Wilmington

Pico Rivera

Indio

Sun Valley

San Bernardino

Industry

Fixed Sites Temporary Sites

Compton

Burbank

Anaheim

Inland Valley S.B.

Rubidoux

W. Long Beach

N. Long Beach

Pico Rivera

Los Angeles

Huntington Park

Indio

Santa Ana 

Sun Valley

San Bernardino

Commerce

Fixed Sites Temporary Sites
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Figure ES-2 

MATES III Air Toxics Risk

0

200

400

600

800

1000

1200

1400

1600

Anaheim

Burbank

Central LA

Compton

Inland Valley S.B.

Huntington Park

North Long Beach

Pico Rivera

Rubidoux

West Long Beach

Sites Average

Risk per Million

Other

Carbonyls

1,3 Butadiene

Benzene

Diesel PM

* Note: One year of data at Huntington Park and Pico Rivera

*

*

Figure ES-3

MATES III Basinwide Risk

83.6%

4.5%

3.3%

2.9%

5.7%

Diesel PM

Benzene

1,3 Butadiene

Carbonyls

Other

Basinwide Risk: 1194 Per Million

Based on Average at Fixed Monitoring Sites
MATES III 

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Figure ES-4 

MATES III Model Estimated Risk 
MATES III 

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Figure ES-5 

Change in CAMx RTRAC Air Toxics Simulated Risk (per million) from 1998-99 to 200

Using Back-Cast 1998 Emissions and 1998-99 MM5 Generated Meteorological Data Fie