### EXECUTIVE SUMMARYMATES III Final Report

ES-1 

### Executive Summary
The Multiple Air Toxics Exposure Study III (MATES I II) is a monitoring and evaluation study conducted in the South Coast Air Basin (Basin). Th e 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 contaminan ts, and a modeling effort to characterize risk across the Basin. The study focuses on the carcino genic 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 Managemen t Plan and is not included here.

A network of ten fixed sites was used to monitor to xic 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 We st 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-y ear period from April 2004 through March 2005. Due to the heavy rains in the Basin in the f all and winter of this period, there was concern that the measurements may not be reflective of typi cal meteorology. The study was thus extended for a second year from April 2005 through March 2006.
In addition to the fixed sites, five additional loc ations 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 wo uld not be picked up by the fixed locations.
The study also included an update of the toxics emi ssions inventories for the Basin and computer modeling to estimate toxics levels throughout the B asin. 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, enviro nmental groups, industry, and public agencies provided valuable insights on the study de sign. Components of the study recommended by the Advisory Group included monitoring for longe r periods at the microscale sites, including naphthalene in the monitoring program, and includin g more up-to-date methods to estimate the contribution of diesel exhaust to ambient particula te 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 tox ics were then used to estimate the carcinogenic risks from ambient levels. Annual ave rage concentrations were used to estimate a lifetime risk from exposure to these levels, consis tent with guidelines established by the Office of Environmental Health Hazard Assessment (OEHHA) o f the California Environmental Protection Agency (EPA).MATES III Final Report

ES-2 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 PM 10 PM 2.5

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 gradi ents 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 Hunt ington 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 us ed 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 i ndividuals that are exposed over a 70-year lifetime. Using the MATES III methodology, about 9 4% 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 b usinesses such as dry cleaners and chrome plating operations. The average risks from the ann ual average levels of air toxics calculated from the fixed monitoring sites data are shown in F igure 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 Fi gure ES-3. For the second year of the study, a full year of data was not collected at two of the s ites (the Huntington Park site access was notMATES III Final Report

ES-3 extended for the second year; and the Pico Rivera s ite was moved during the second year resulting in several months without data). The sec ond year data include results for only eight sites. Sites with higher levels of risk include Bu rbank, 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 maj or contributor to air toxics risk, accounting on average for about 84% of the total.
To compare different methods used to estimate diese l particulate levels, the method used in MATES II, which was based on the emissions ratios o f diesel particulate and elemental carbon from a study conducted in the South Coast in the 19 80’s, and a method based on the ratio of PM 2.5 emissions from the 2005 emissions inventory were b oth calculated. For MATES II, the PM 10 elemental carbon levels were multiplied by 1.04 to estimate diesel particulate. The 2005 PM 2.5 inventory finds a ratio of diesel particulate to e lemental carbon emissions of 1.95. Multiplying the PM 2.5 elemental carbon levels by the 1.95 ratio gives an other estimate of diesel particulate. The estimates using these methods com pared to using the CMB model are shown in Table ES-2. Should one use the same diesel particu late estimation methodology as MATES II, there is about a 30% reduction in ambient levels be tween 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 usi ng two different gasoline profiles. The estimates used for the risk calculations were the m idpoint of the range. As shown in the table, both the CMB model and the PM 2.5 emissions ratio from the 2005 emissions inventory method give similar estimates, and both are higher than th e MATES II method. Thus the MATES II Study method is likely underestimating the levels o f diesel particulate.
Table ES-2 CMB Estimate of Diesel Particulate Comp ared to Emissions Inventory Ratio Methods.

Estimation Method MATES III Diesel PM μ g/m3

MATES II Method: PM 10 EC x 1.04 2.16

2005 Inventory Method: PM 2.5 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 μ g/m 3

.MATES III Final Report

ES-4 Modeling
Several updates to the modeling platform were inclu ded in this study compared to MATES II. The model used was the Comprehensive Air Quality Mo del 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 emission s 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 mi llion. 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 metho dology 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 dom inant contribution from mobile sources and diesel emissions to air toxics risk in the MATE S II timeframe as well.
For comparison purposes, Table ES-3 shows the estim ated 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 d ata input.

Table ES-3 Modeled Air Toxics Risk Comparisons Usin g 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 a ir 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 good s movement. The model comparison shows an increase in air toxics risk occurred in the imme diate areas encompassing the ports of moreMATES III Final Report

ES-5 than 800 in a million between the two periods. Thi s increase correlates with the increased container cargo moving through the ports and increa ses 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) est ablished by OEHHA. The chronic REL is the air concentration at or below which adverse non cancer health effects would not be expected in the general population with exposure for at leas t 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 μ g/m3 (2ppb). All of the fixed site annual averages were above this concentration, rang ing from 2.9 ppb for Anaheim to 4.5 ppb at Los Angeles. Formaldehyde effects include eye irri tation, injury to nasal tissue, and respiratory discomfort. OEHHA, however, is proposing revisions to the RELs for several toxic air contaminants. For formaldehyde, the proposed chron ic REL is 9 μ g/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 i s 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 met hod 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 specie s applied to apportion contributions to ambient particulates using measured source profiles . The CMB method accounts for major source categories and geographic differences in sou rce contributions and was recommended by the Technical Advisory Group. It is staff’s judgme nt that this is the most appropriate method to estimate the ambient levels of diesel particulate m atter. The MATES II Study used elemental carbon as a surro gate 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 advant age of the specific profile of chemical species emitted from different particulate matter s ources. Twenty-three species were used in the CMB model to reconcile source contributions to obse rved ambient concentrations. This results in a more robust apportionment of source contributi ons to ambient particulate matter levels, since all major sources of particulate matter and element al carbon are considered.
The CMB model uses the profile of chemical tracer c hemical 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 bur ning, whereas other sources show specific chemical profiles that can be used to apportion the se 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.MATES III Final Report

ES-6 The Positive Matrix Factorization (PMF) model was a lso 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. Si nce 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 fra ction in any source profile. Estimated source profiles are then attributed to specific sources us ing experienced judgment. However, using the MATES III data, the initial attempts at source appo rtionment found that some source profiles could not be interpreted, and some profiles could n ot be confirmed with confidence.
Additionally, the statistical parameters of the PMF model performance were outside of the bounds used to determine adequate performance of th e model. Also, in perusing the literature of applications of PMF approach, it was found that sub stantial amounts of measured data were sometimes excluded from the analyses, and an uncert ainty parameter for some variables was altered to improve the model performance. Staff di d not censor any data or alter certain parameters in the model in an attempt to improve th e model performance statistics. The uncertainties used for the ambient measurements wer e 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 m odel estimate for diesel particulate was found to be sensitive to the gasoline emissions pro file used. To account for this, the midpoint of a range of estimates using two different gasoline p rofiles was used.
There are also uncertainties in the risk potency va lues used to estimate lifetime risk of cancer. This study used the unit risks for cancer potency e stablished 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 to xics in California and is useful as a yardstick to compare potential risks from varied sources and emi ssions 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 stat e 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 assumpti ons are consistent with current scientific knowledge, but are often designed to be conservativ e and on the side of health protection in order to avoid underestimation of public health ris ks.
As noted in the OEHHA risk assessment guidelines, s ources of uncertainty, which may either overestimate or underestimate risk, include: (1) ex trapolation of toxicity data in animals to humans, (2) uncertainty in the estimation of emissi ons, (3) uncertainty in the air dispersion models, and (4) uncertainty in the exposure estimat es. Uncertainty may be defined as what is not known and may be reduced with further scientific st udies. In addition to uncertainty, there is a natural range or variability in the human populatio n 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 ri sk, based on current knowledge and a number ofMATES III Final Report

ES-7 assumptions. However, a consistent approach to ris k assessment is useful to compare different sources and different substances to prioritize publ ic health concerns.

Conclusion
Compared to previous studies of air toxics in the B asin, this study found a decreasing risk for air toxics exposure, with the estimated Basin-wide popu lation-weighted risk down by 8% from the analysis done for the MATES II time period. The am bient 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 reg arding air toxics, the risks are still unacceptable and are higher near sources of emissio ns such as ports and transportation corridors. Diesel particulate continues to dominate the risk f rom air toxics, and the portion of air toxic risk attributable to diesel exhaust is increased compare d to the MATES II Study.
The highest air toxics risks are found near the por t area, an area near Central Los Angeles, and near transportation corridors. The results from th is study underscore that a continued focus on reduction of toxic emissions, particularly from die sel engines, is needed to reduce air toxics exposure.MATES III Final Report

ES-8 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

Comm erce

Fixed Sites Temporary SitesMATES III Final Report

ES-9 Figure ES-2

MATES III Air Toxics Risk

0 200 400 600 800 1000 1200 1400 1600

Anahe i m Burbank

Central LA Compt

o n

I nla nd Va l le y S .B. Hunt ingt on Pa r k
Nort h Lo n g Beac h Pico Rivera

R

ubido ux

W e st Long Bea

c h Sites Average Risk per Million

Other Carbonyls 1,3 Butadiene Benzene Diesel PM

* Note: One year of data at Huntington Park and Pic o 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 SitesMATES IIIFinal ReportES-10Figure ES-4MATES III Model Estimated RiskMATES IIIFinal ReportES-11Figure ES-5Change in CAMx RTRAC Air Toxics Simulated Risk (permillion) from 1998-99 to 2005Using Back-Cast 1998 Emissions and 1998-99 MM5 Generated Meteorological Data Fields