2008 PM2.5 Plan 

Chapter 3 

 

What is Needed to Demonstrate Attainment? 
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Chapter 3: What is Needed to Demonstrate 

Attainment?

3.1 INTRODUCTION 

This chapter describes what is needed to demonstrate that the San Joaquin Valley will 

attain the federal air quality standards for PM2.5 in accordance with federally mandated 

timelines. As required by EPA Guidance, computer modeling and supplemental 

analysis are used to determine the quantity of emissions reductions needed from 

sources within the District to demonstrate attainment of the standards. The scope of the 

effort faced by the District to establish a plan sufficient to attain the standards is defined 

by the local challenges and jurisdictional limitations. 

3.2 CHALLENGES 

Figure 3-1 San Joaquin Valley Topography

The District must overcome 

difficult physical environment 

and regulatory challenges to 

attain the PM2.5 air quality 

standards. Natural conditions 

including climate, weather 

(meteorology), chemical 

reactions and physical 

processes create an 

atmospheric environment that 

forms and retains particulates 

in the Valley. Improving air 

quality is made more difficult 

by population growth that 

comes with inherent emission 

increases and jurisdictional 

limits that restrict the 

comprehensiveness of District 

efforts. 

San Joaquin

 Stanislaus

 Merced Madera 

 Fresno 

Tulare Kings 

Kern
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3.2.1 Natural Conditions 

The topography and climate in the San Joaquin Valley create ideal conditions for 

trapping and holding directly emitted PM2.5 within the Valley and generating additional 

PM2.5 from precursor emissions. PM2.5 emissions and precursors may be retained 

within the Valley for several days, recirculating within the Valley and accumulating to 

unhealthy levels. 

The San Joaquin Valley Air Basin (SJVAB) (Figure 3-1) is a continuous inter-mountain 

valley encompassing nearly 25,000 square miles. On the western edge of the Valley is 

the Coast Mountain range with peaks reaching 5,020 feet. On the east side of the 

Valley is the Sierra Nevada range with some peaks exceeding 14,000 feet. The 

Tehachapi Mountains that form the southern boundary of the Valley include peaks over 

6,000 feet and contain mountain passes to the Los Angeles basin and the Mojave 

Desert. The surrounding mountain ranges hinder the movement of air and block 

removal (dispersion) to other areas by minimizing wind flows into and out of the air 

basin, causing pollutants and precursors to be retained within the Valley. 

The local climate produces extensive seasonal variations in particulate levels through 

differences in atmospheric conditions that affect the types of emissions, emission rates, 

and atmospheric formation of particles from precursor emissions. Long periods with 

little or no rainfall during summer months result in desiccation (extreme dryness) of soils 

along roadways, increasing emissions from traffic movement. Limited rainfall during the 

summer reduces the frequency of events that clear emissions from the local area. 

Winter brings rainfall, but also creates an atmospheric environment that forms more 

ammonium nitrate particulates. During winter, some types of cold winter fog events are 

linked to atmospheric chemistry that forms additional secondary particulates. The cold 

weather also induces the public to increase residential wood combustion use that adds 

further emissions to the atmosphere (though Rule 4901, Wood Burning Fireplaces and 

Wood Burning Heaters, prohibits fireplace use when the PM2.5 air quality is forecast to 

be unhealthy). 

The SJVAB has an "inland Mediterranean" climate, which is characterized by hot, dry 

summers and cool, rainy winters. The SJVAB averages over 260 sunny days per year 

(District 2003). During summer months, the SJVAB is influenced almost continuously 

from a weather pattern referred to as the “Pacific High” which is a semi-permanent 

subtropical high-pressure belt often located off the west coast of North America. Major 

storms and region-wide precipitation are not typical when this pressure cell is dominant. 

The descending air in this cell compresses, raising temperatures and lowering the 

relative humidity. This belt of high pressure migrates north and south seasonally. In 

winter, the influence of the Pacific High is intermittent, giving rise to alternate periods of 

stormy, unsettled weather and periods of stable, rainless conditions. Due to the 

influence of these air movement patterns, air pollutants are generally transported from 

the north to the south in the summer and in a reverse flow in the winter. Analysis of 

wind flow shows that during the winter months, the mean flow is through the Valley from 

the southeast. By mid-spring, coastal breezes enter the Valley from the northwest, 
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which reverses the airflow pattern. In summer the northwest to southeast airflow is at 

its strongest. In the fall and winter, average wind speeds range from five to nine miles 

per hour; however, very light winds occur from twenty to forty percent of the time. 

Precipitation in the SJVAB is confined primarily to the winter months with nearly ninety 

percent of the annual precipitation in the SJVAB falling between the months of 

November through April. Average annual rainfall for the entire SJVAB is about ten 

inches on the valley floor. Annual rainfall totals vary from north to south, with northern 

counties experiencing as much as eleven inches of rainfall and southern counties 

experiencing as little as four inches per year (District 2003). North-south and east-west 

regional differences exist, with higher rainfall occurring in the northern and eastern parts 

of the SJVAB. Historical evaluations have correlated increased annual rainfall to 

decreased PM10 concentrations. 

3.2.2 Meteorology 

Meteorology plays an important role in determining the levels of air pollution in the 

Valley and is a key parameter to understanding and predicting PM2.5 concentrations. 

Meteorological data are used to assess the potential for air pollution to accumulate in 

certain locations. Pertinent meteorological parameters include wind speed and 

direction, ambient atmospheric temperature at different elevations above the ground, 

precipitation and mixing height (the elevation in the atmosphere into which the 

emissions will freely mix and disperse). 

Meteorological patterns affect PM2.5 by directly affecting emissions (e.g. temperature 

linked evaporation rates), influencing secondary particle formation (aerosol chemistry) 

and controlling the rate at which pollution dissipates (wind induced dispersion or 

inversion restricted flow). The valley floor is characterized by warm to hot, dry 

summers and cooler winters. Winter temperatures in the SJVAB are generally mild, 

though temperatures will drop below freezing occasionally. Surface temperatures are 

dependent on elevation, with colder temperatures on the mountain ridges both east and 

west of the valley floor. Fall and winter meteorological conditions contribute to 

increased PM2.5 formation shifting from dominance by primary particles to secondary 

particles. Secondary particles formed from gases by atmospheric processes are a 

major portion of the PM2.5 during colder, wetter periods from mid November through 

early February. Colder, frequently stagnant conditions occurring in December and 

January favor formation of ammonium nitrate, and these months usually experience the 

highest levels of PM2.5. During the winter months, the Valley frequently experiences 

variable winds of less than 10 mph. Low wind speeds, combined with low-lying 

inversion layers in the winter and increased secondary particle formation, establish a 

situation conducive to the formation and accumulation of PM2.5. 

Meteorological factors that restrict horizontal and vertical air movement of air masses 

are important factors in air quality. Horizontal movement spreads the pollutants over a 

wider geographic area. Winds carry emissions away from the area of emissions, 
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dispersing the emissions and keeping concentrations low. Emissions accumulate if 

wind speed is zero or stagnates and recirculates over a small area. Vertical mixing 

height is reduced when an inversion layer is present. An inversion layer is a layer of air 

warmer than the layer below it. Cooler air below the inversion layer cannot rise through 

the warmer layer. The warmer layer aloft prevents the usual rising airflow that 

disperses emissions from the ground. Air contaminants accumulate near the ground as 

emissions continue to be released into this cooler layer near the surface. 

3.2.3 Horizontal Mixing (Transport) 

Horizontal mixing, or transport, is also important in the dispersal of air pollutants. The 

greater the velocity of wind in the mixing layer, the greater the amount of mixing 

(dispersion) and transport of pollutants. Winds (at ground level or at higher altitudes) 

transport pollutants from other basins into the Valley, within the Valley to areas 

downwind, and from the Valley into other regions. Studying transport increases 

understanding of how pollution from other areas may impact the Valley as well as how 

pollution originating in Valley areas may impact other places within and beyond the 

Valley. Evaluation with improved emissions inventories, improved databases on 

meteorological behavior and atmospheric chemistry, and improved grid-based 

photochemical models all contribute to ongoing studies that enhance our understanding 

of pollutant transport. Future District plans will incorporate any significant advances in 

knowledge regarding transport as it becomes available from ARB and other agencies. 

The amount of pollution transported from other areas into the Valley varies. PM2.5 

originating from other air basins has not been quantified. During winter, the low wind 

speeds associated with high particulate levels generally reflect concentrations formed 

from local emissions. However, wildfires, Santa Ana winds, and offshore flow introduce 

particulates and precursors into the Valley at different times during the year. PM2.5 

readings in the SJVAB are most severe during the fall and winter periods when wind 

speed and direction are not conducive to interregional transport. Monitoring and 

speciation techniques currently available are not able to identify the origin of PM2.5 

sources with sufficient detail to indicate if the SJVAB is experiencing transport from 

outside the air basin. Transport of some PM2.5 precursors has been studied as part of 

ozone transport evaluation, identifying transport of ozone and ozone precursors from 

and to other air basins surrounding the SJVAB. The transport of ozone was 

documented during the summer when the highest ozone readings are more likely to 

occur. This transport includes precursors of ozone and PM2.5; however, the amount of 

PM2.5 that could be generated in the SJVAB from such transport has not been 

quantified. Pollution from areas outside of the Valley may or may not contribute to high 

PM2.5 levels within the Valley. 

Transport can also move Valley pollution into other air basins. PM2.5 going to other air 

basins from the SJVAB has not been quantified. During the daytime, heated air rises 

into the mountains and transports ozone and other pollutants up the Sierra Nevada, 

Tehachapi, and Coastal Mountains. According to the ARB, the Valley’s pollution can 
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affect ozone air quality in the broader Sacramento area, the Great Basin valleys, the 

mountain counties, the Mojave Desert, and the north central and south central coasts, 

depending on meteorological conditions (ARB 2001). ARB assesses transport corridors 

for ozone but is not required to perform a similar assessment for particulates. Transport 

of particulates and precursors was evaluated as part of the California Regional 

Particulate Air Quality Study (CRPAQS) research program. A specific findings 

document has not been prepared to quantify the magnitude of transport between the 

major air districts; however, preliminary findings did identify that there may be occasions 

of some transport of particles and/or precursors from the SJVAB to the Bay Area in 

winter. A more detailed accounting of inter-basin transport between Bay Area, SJVAB 

and Sacramento Air Basin may be developed as part of final synthesis documents at 

the completion of the CRPAQS project. 

Precursors and directly emitted particulates originating in the SJVAB are also 

transported within the Valley. Local emissions are thought to be more responsible for 

the Valley’s worst ozone and particulate air quality. Some SJVAB pollution is not 

transported into other basins, but remains and recirculates into other parts of the Valley. 

At night during the summer, cooler drainage winds from the surrounding mountains 

prevent exit of the air at the southern end of the SJVAB causing a recirculation airflow 

pattern known as the Fresno eddy. The eddy circulates pollutants in a counterclockwise 

pattern and returns polluted air to urban areas where more precursors are added the 

next day. Throughout the Valley, some of the pollutants transported to higher altitudes 

from daytime heating return to the Valley floor at night because of drainage winds from 

the mountains. During the winter, flow patterns at the Valley floor may become 

completely stagnant, keeping emissions within a few miles (or tens of miles) of the 

originating sources for several days. 

3.2.4 Vertical Mixing and Inversion Layers 

In general, the air at ground level is warmed by sunlight and activity, causing it to rise 

and carry emissions aloft. This rising air pattern mixes the fresh emissions with air at 

higher elevations, dispersing the emissions and reducing the concentration of directly 

emitted PM2.5 and precursors. However, in the San Joaquin Valley a temperature 

inversion layer frequently blocks the normal rising air dispersion pattern. Temperature 

inversions are a reversal of the “normal” decrease in atmosphere temperature with 

increasing height above the Earth’s surface. Inversions reflect conditions in which 

temperature increases with height (Figure 3-2). 

Vertical mixing decreases at the base of the inversion, also known as the mixing height. 

PM2.5 is trapped below the mixing height, remaining more concentrated than when it is 

allowed to mix more freely into higher elevation air. This contributes to higher PM2.5 

concentrations in the SJVAB. 
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Figure 3-2 Vertical Dispersion, With and Without Temperature Inversion 

Strong temperature inversions occur throughout the SJVAB in the summer, fall, and 

winter. Inversions are more persistent (stable) in the SJVAB during the winter months, 

when inversions occur from 50 to 1,000 feet above the SJVAB floor. The challenge this 

creates for the Valley is that in the absence of an inversion layer, emissions will not 

accumulate to levels that are harmful to health. However, if an inversion layer forms the 

same level of emissions may create localized areas with high PM2.5 concentrations. 

Predicting the strength, elevation and duration of the inversion is based on regional 

meteorological models supplemented by a few vertical air profiler sites providing local 

data. The District uses this information to prepare daily forecasts of air quality and 

advises the public when conditions are projected to cause poor air quality. Additionally, 

the district manages agricultural and prescribed burning and residential wood 

combustion curtailments to avoid adding smoke emissions. when conditions are 

unfavorable. 

3.2.5 Fog Effects on PM2.5 

Particles that become fog droplets by absorbing water vapor are subsequently removed 

by gravitational settling. Fog episodes cause a net removal of PM by wet deposition. 

However, fog also provides an aqueous medium for formation of sulfate particulate. 

The net effect of a fog episode depends on the pre-fog concentrations of particulate 

precursors and availability of oxidants that are involved in the chemistry of particle 

formation, and the duration of the fog event. 

+/- Sulfate is both produced and removed by fog. The end result of a fog event may 

be either increase or decrease in the monitored levels of PM2.5 sulfate. Sulfate 

particulate is removed by wet deposition during fog; however, fog droplets provide the (b) without inversion (a) inversion 
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3-7 

aqueous medium for the production of sulfates and the production of additional sulfate 

particulate by chemical reactions. The fog may over-balance the wet removal and 

actually increase the amount of sulfate PM2.5 in the atmosphere. Whether sulfate 

formation in fog exceeds sulfate removal by fog settling will vary from site to site, 

depending on the duration of event and concentrations of available reactants to form 

additional sulfate particulate matter. 

- Nitrate and ammonium are partially removed by fog. Nitrate and ammonia gases in 

the atmosphere may be reduced by half through fog wet deposition. 

- Secondary Organic Aerosol (SOA) formation (formation of organic carbon particulate 

from photochemical oxidation reactions of precursor gases) is reduced by decreased 

photochemical activity in circumstances where sunlight is reduced by fog or cloud 

cover. Clouds and fog reduce the photochemical production of secondary organic 

aerosols by a factor of two or three from the maximum clear sky conditions because of 

reduced availability of photons. The thermodynamic interactions between fog droplets 

and SOA are unknown. 

3.2.6 Urban and Rural Comparison and Atmospheric Chemistry for PM2.5 

The major effects of urban emissions are observed in the winter where primary 

emissions typically contribute more to PM2.5 at the urban sites than at the rural sites. 

In urban areas, directly emitted PM2.5 levels are dominated by motor vehicle and tire 

and brake wear emissions, entrained particulate from roadways, and carbon from 

residential wood combustion in winter. Precursors to secondary PM2.5 formed from 

atmospheric processes are dominated by urban emissions of nitrogen oxides (NOx), 

sulfur dioxide SO2 and VOC; however the reactions of these precursors to form particles 

are dominated by concentrations of nitric acid (HNO3), a secondary compound formed 

from atmospheric reactions. Ammonia (NH3) emissions are largest in rural areas. 

 

Total oxidized nitrogen is higher in the urban areas. NOx in urban areas is ten times 

more abundant than in rural areas. Ammonia is more abundant in Bakersfield than at 

the other core sites. SO2 was also more abundant in the cities than rural areas. Gasphase organic concentrations exhibited strong diurnal fluctuations in the urban areas. 

District monitoring sites are not dominated by emissions from a single large facility or 

group of facilities. No direct link has been found between a specific locally observed 

source of emission activity and high PM2.5 at a single monitoring site on a consistent 

basis. The observed PM2.5 levels represent aggregated urban emissions with regional 

contributions. In winter, the urban residential and traffic monitor sites show higher 

concentrations than sites near industrial areas. 

Ammonium nitrate is the main component of PM2.5 during the winter in the San Joaquin 

Valley. As supported by modeling evaluation, ammonium nitrate formation is limited by 

the availability of nitric acid, formed from urban NOx and hydrocarbon reactions. The 

formation of ammonium nitrate is limited by the availability of atmospheric 
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concentrations of nitric acid (HNO3), a secondary compound that forms from emission of 

NOx interacting with hydrocarbons and OH radicals released from the hydrocarbons by 

photochemical reactions. Ammonia (NH3) is abundant throughout the Valley and does 

not act as a limiting precursor. A large fraction of nitrates were associated with the 

particulate phase; only 18-25% of nitrate existed in the gas phase as nitric acid. 

Independent corroboration of key aspects of ammonia contribution to particulate in the 

San Joaquin Valley is provided through scientific analysis conducted by other 

researchers. For example: an article by Battye, et al1 identifies ammonia from motor 

vehicle exhaust as a major contributor to particulates during winter months with a 

reduced role for agricultural sources during this time period. This article has important 

implications for determining which sources of precursors contribute the most to 

ammonium nitrate particulate concentrations in the winter. 

Secondary organic aerosols (SOA) contribute to a significant fraction of PM2.5. SOA is 

organic carbon particulate formed in the photochemical oxidation of anthropogenic and 

biogenic VOC precursor gases. Aromatic compounds are believed to be efficient SOA 

producers contributing to this secondary particulate. 

Annual PM2.5 is dominated by winter concentrations, and urban sites have more 

carbon. According to the Desert Research Institute (DRI): 

“For most of the sites within the SJV, 50 – 75% of the annual average PM2.5 

concentration could be attributed to a high PM2.5 period occurring from 

November to January. At non-urban sites, the elevated PM2.5 was driven by 

secondary NH4NO3. The temperature, RH [relative humidity], and stability of the 

valley boundary layer in winter are all favorable for the formation of NH4NO3 

from its NH3 and NOx, and VOC precursors. Elevated OM (organic matter, 

organic carbon compounds) exacerbates air quality mostly at urban sites. This is 

consistent with the winter use of wood fuel for home heating, as well as with 

traffic. This distinct spatial distribution also reflects the difference between 

primary and secondary aerosols. ...The urban sites experienced much higher BC 

(black carbon) concentration than non-urban sites. This suggested that BC 

particles were closely related to urban sources such as traffic, RWC [residential 

wood combustion], and cooking. Multiple spikes of hourly BC were frequently 

observed especially at urban sites, suggesting that those BC originated from 

nearby urban sources. At all urban sites, the morning BC peak was found around 

0600 to 0800 PST and the large evening peak around 2000 PST prolonged 

through the midnight and early morning next day. Non-urban sites did not exhibit 

any distinct diurnal patterns.”2

 

1

 Source: “Evaluation and improvement of ammonia emissions inventories” William Battye, etal, 

Atmospheric Environment 37 (2003) 3873-3883 

2 Source: Initial Data Analysis of Field Program Measurements, DRI Document No. 2497, July 29, 2005 

Judith C. Chow, L..W. Antony Chen, Douglas H. Lowenthal, Prakash Doraiswamy, Kihong Park, Steven 

D. Kohl, Dana L. Trimble, John G. Watson, DESERT RESEARCH INSTITUTE, Division of Atmospheric 

Sciences, 2215 Raggio Parkway, Reno, NV 89512.
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3.2.7 Other Key Findings from Scientific Studies and SJV Evaluations 

The CRPAQS research program has provided a wealth of scientific analysis specifically 

targeted to answer key questions that inform decision-making for effective reduction of 

particulate concentrations in the San Joaquin Valley. The findings cover a wide range 

of technical topics. An extensive list of CRPAQS results documents was included in the 

2006 PM10 Plan, Appendix D (CRPAQS Bibliography), available on the District's 

website at: http://www.valleyair.org/Air_Quality_Plans/docs/Appendix_D.pdf

The information developed by CRPAQS may have value to other areas of the country, 

but in some cases the information discloses how California circumstances are different. 

For example, EPA methods assume a strong relationship between sulfate decrease 

causing a potential and nitrate formation increase. That issue was studied for the SJV 

and found not to be a concern. 

3.2.7.1 Ammonium Nitrate Sensitivity to Sulfate Levels 

According to Kumar and Lurmann: 

“Ammonium nitrate levels are sensitive to changes in sulfate under ammonia 

limited conditions. Sulfate and nitrate compete for ammonia when its supply is 

limited, and the thermodynamics indicates that ammonium preferentially 

associates with sulfate (forming ammonium sulfate or ammonium bisulfate) 

rather than nitrate under ambient conditions. Under ammonia limited conditions, 

reductions in sulfate may not be an effective means to reduce PM mass because 

ammonium sulfate removed from the aerosol is replaced with ammonium nitrate, 

thereby inhibiting significant reduction in PM mass. 

The effects of changes in sulfate levels on ammonium nitrate in the SJV were 

investigated using the eight cases for which isopleth diagrams were constructed. 

These were cases with relative high sulfate levels for the SJV (3 to 4 mg/m3). 

The effects of 50 and 100 percent reduction in sulfates on ammonium nitrate 

concentrations are listed in Table 3-10. The results indicate ammonium nitrate 

concentrations are not sensitive to large changes in sulfate levels. The lack of 

ammonium nitrate sensitivity to sulfate in the SJV is due to the ammonia-rich 

conditions and the low amounts of sulfate compared to nitrate.” 3

 

3 Source: ANALYSIS OF ATMOSPHERIC CHEMISTRY DURING 1995 INTEGRATED MONITORING 

STUDY, STI-997214-1791-FR , Authors: Naresh Kumar, Frederick W. Lurmann, Sonoma Technology, 

Inc., Petaluma, CA; Spyros Pandis, Asif Ansari, Carnegie Mellon University, Pittsburgh, PA, July 1998.
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3.2.7.2 Precursor Relationships and Control Sensitivity 

The issue of limiting precursors and secondary formation products has been extensively 

evaluated for the CRPAQS research program. 

• Particulate NH4NO3 concentrations are limited by the rate of HNO3 formation, 

rather than by the availability of NH3. 

• HNO3 is formed via both daytime photochemistry and aloft nighttime 

chemistry. 

• Secondary organic aerosol formation from VOC emissions may account for 

15% to 25% of the total OC 

• Relatively low non-methane organic compounds (NMOC)/NOx ratios indicate 

the daytime photochemistry is VOC, sunlight, and background-ozone limited 

in winter. This is a nonlinear regime for the gas-phase chemistry.4

According to Lurmann et al.:

“Comparisons of ammonia and nitric acid concentrations indicate that ammonium 

nitrate formation is limited by the availability of nitric acid, rather than ammonia. 

Time-resolved aerosol nitrate data at the surface and on a 90-m tower suggest 

both the daytime and nighttime nitric acid formation pathways are active, and that 

entrainment of aerosol nitrate formed aloft at night may explain the spatial 

homogeneity of nitrate in the San Joaquin Valley. ...This study's analyses 

suggest that reductions in NOx emissions will be more effective in reducing 

secondary ammonium nitrate aerosol concentrations than reductions in ammonia 

emissions. Reductions in VOC emissions will reduce secondary organic aerosol 

concentrations and may reduce ammonium nitrate. ...Comparisons of ammonia 

and nitric acid concentrations show that ammonia is far more abundant than nitric 

acid, which indicates that ammonium nitrate formation is limited by the availability 

of nitric acid, rather than ammonia....The results indicate ammonium nitrate 

formation is ultimately controlled by NOx emission rates and the other species, 

including VOCs and background ozone, which control the rate of NOx oxidation 

in winter, rather than by ammonia emissions.”5

 

The contributing PM2.5 sources have a variety of properties. This makes analysis of 

reductions more difficult consequently complicates the development of effective control 

programs. Nitrates and carbon are the two largest components, and their atmospheric 

behavior is entirely different. According to McCarthy et al.: 

“High concentrations of PM organic carbon (OC) were spatially limited to core 

urban sites while high concentrations of PM ammonium nitrate were regionally 

 

4 Source: Presented to: CRPAQS Data Analysis Workshop, Sacramento, CA, March 9-10, 2004, Tasks 

6.1 and 6.2: Phase Distributions Tasks 6.1 and 6.2: Phase Distributions and Secondary Formation During 

Winter and Secondary Formation During Winter in the San Joaquin Valley in the San Joaquin Valley, 

Presented by: Fred Lurmann, Siana Alcorn, Manidipa Ghosh, Sonoma Technology, Inc., Petaluma, CA 5 Source: Processes Influencing Secondary Aerosol Formation in the San Joaquin Valley During Winter, 

Frederick W. Lurmann, Steven G. Brown, Michael C. McCarthy, and Paul T. Roberts, Sonoma 

Technology, Inc., 1360 Redwood Way, Suite C., Petaluma, CA 94954
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distributed throughout the SJV. Concentrations of PM and its precursors were 

typically lower at the elevated sites surrounding the SJV than at monitoring sites 

located on the SJV floor....At distances more than 50 km from the urban areas, 

OM [organic matter] concentrations typically declined by a factor of three or 

more. Emissions of OM at the urban core are either not rapidly transported to the 

rural sites or are diluted too much to substantially impact rural sites. 

Concentrations of OM at elevated sites were comparable to concentrations at 

rural sites on the Valley floor....Overall, these spatial patterns of OM suggest that 

the impact of emissions was largely confined to the local area and OM 

concentrations were unevenly distributed over the duration of the episode. 

The contrast in spatial variability between the ammonium nitrate and OM 

components of PM2.5 in the SJV winter episodes provides information on the 

spatial extent of the production of ammonium nitrate. PM2.5 OM and ammonium 

nitrate are both subject to the same meteorological transport conditions, yet 

ammonium nitrate concentrations are relatively homogeneous and OM 

concentrations are much higher in the urban source areas. In addition, OM and 

ammonium nitrate components are expected to have the majority of their mass in 

a similar size fraction (PM0.1 to PM1) (Lighty et al., 2000; Hughes et al., 1999; 

Bench et al., 2002) and, therefore, the rates of removal should be approximately 

the same. In summary, the likely explanation for the difference in spatial 

variability is the spatial distribution of the emissions or precursors. Primary OM 

emissions occur predominantly from mobile sources and wood smoke located in 

urban areas. The formation of ammonium nitrate from NOx precursors (Lurmann 

et al., 2004) must occur throughout the SJV to account for its spatial 

homogeneity. 

High concentrations of PM organic carbon were spatially limited to core urban 

sites while high concentrations of PM ammonium nitrate were regionally 

distributed throughout the SJV. The regional homogeneity of ammonium nitrate 

concentrations coupled with the stagnant wind conditions provides evidence that 

production of ammonium nitrate occurs at similar rates throughout the valley. In 

contrast, the OC component of PM indicates that production rates were much 

higher in the urban areas than at rural sites.”6

 

3.2..8 Population Growth 

Increased population, which results in increased vehicle activity and more consumer 

product use, leads to increased pollutant emissions, undermining the progress made by 

regulations. Table 3-1 shows population estimates for the eight counties of the SJVAB 

by county, including projections to 2014. In 2006, 9.9% of California’s population 

resided in the SJVAB (California Department of Finance 2005). Population projections 

 

6 Source: Background and Boundary Conditions for Particulate Matter and Precursors in the San Joaquin 

Valley in Winter (Technical Memorandum STI-902325-2779-TM), Michael C. McCarthy, Hilary R. Hafner, 

Steven G. Brown, Fredrick W. Lurmann, Paul T. Roberts, Sonoma Technology, Inc., 1360 Redwood Way, 

Suite C, Petaluma, CA 94954-1169, July 29, 2005.
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suggest that 11% of California’s total population will reside in the San Joaquin Valley in 

2020. Between 2005 (the base year for this plan) and 2014, the population of the San 

Joaquin Valley will grow by 43%. In contrast, the total population for the State of 

California will grow 24% over the same time period. 

Table 3-1 SJVAB Population by County 

County 2005 2014 

Projection

% Change, 

2005-2014 

Fresno 837,459 1,015,838 33 

Kern a 580,794 718,656 36 

Kings 135,218 167,701 37 

Madera 129,728 163,753 42 

Merced 224,488 310,961 61 

San Joaquin 608,594 844,074 63 

Stanislaus 479,203 596,967 36 

Tulare 384,650 485,889 41 

TOTAL 3,380,134 4,303,839 43 

a Valley portion; Kern County has portions located outside of the San Joaquin Valley Air Basin. 

Source: Developed using Population Trends Reports, California Department of Finance (2005). 

3.2.9 Jurisdictional Limits and Regulatory Authority 

Attainment of air quality standards and the reduction of precursor emissions in the 

SJVAB require the cooperation of local and/or regional, state, and federal governments. 

At the federal level, the EPA is responsible for establishing federal motor vehicle 

emission standards. The EPA is also responsible for reducing emissions from 

locomotives, aircraft, heavy duty vehicles used in interstate commerce, and other 

sources such as off-road engines that are either preempted from state control or best 

regulated at the national level. 

The ARB establishes emission standards for on-road motor vehicles and some off-road 

sources. The ARB also establishes fuel specifications and develops consumer product 

standards for meeting air quality goals in California. Other state agencies such as the 

Department of Pesticide Regulation (DPR), California Department of Transportation 

(CalTrans), and the Bureau of Automotive Repair (BAR) also have responsibility for 

certain emissions sources. 

Districts like the San Joaquin Valley Unified Air Pollution Control District have authority 

to regulate stationary sources and some area sources of emissions. Districts cooperate 

with Regional Metropolitan Planning Organization (MPOs) to develop measures 

affecting local transportation activity that are included in a SIP. In turn, the MPOs 

coordinate the process to identify and evaluate potential control measures and compile 
San Joaquin Valley Unified Air Pollution Control District April 30, 2008

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3-13 

local government commitments that will be included in the local or regional air quality 

plan. 

The primary jurisdiction of the District is therefore limited to just part of the total 

emissions inventory (Figure 3-3). Based on 2005 inventories developed for this plan, 

20% of the total NOx inventory for the SJVAB is under the primary regulatory jurisdiction 

of the District. 

Figure 3-3 NOx Precursor by Source Type 7

 

(Based on Annual Emissions Inventories) 

Oxides of Nitrogen (NOx)

Mobile 

Sources

80%

Stationary

and Area 

Sources

20%

 

Although the responsibility for establishing the tailpipe emissions standards for the 

mobile sources belongs to state and federal governments, additional reductions are 

needed to reach attainment. Therefore, the District is also proposing measures, such 

as trip reduction, green contracting, and enhanced indirect source review, to provide 

additional mobile source emissions reductions for this plan and will continue to use 

incentive programs to accelerate mobile source emissions reductions. 

 

7

 Please note that Mobile Sources includes on-road and off-road sources. For NOx, 67% of the total mobile source 

emissions in 2005 come from on-road sources, and 33% of the total mobile source emissions come from other mobile 

sources. 
San Joaquin Valley Unified Air Pollution Control District April 30, 2008

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3-14 

3.3 MODELING 

The SJVAPCD PM2.5 SIP Modeling Protocol describes the selection of the general 

modeling approach, methods of analysis, and identification of data pertinent to 

supporting modeling analysis. The protocol proposes comprehensive analysis 

combining the results of evaluations, correlated and reconciled to establish by 

preponderance of results (weight of evidence) that all nonattainment areas will be 

adequately addressed. EPA guidance recommends that models be used in a relative 

sense due to their uncertainties and the differences that exist between model input data 

and design values applicable to determine attainment. EPA directs that model results 

and other analysis be combined to establish a confirmed finding of attainment in a 

“weight of evidence” determination, particularly if the predicted future values are close to 

the standard. New approaches recommended by EPA guidance also require special 

processing of speciated data and a Speciated Modeled Attainment Test (SMAT). 

3.3.1 Model Choice 

Annual meteorology has seasonal components, reflected in EPA guidance 

recommending at least quarterly evaluation and analysis. Regional modeling is being 

performed for an entire year on a daily basis that can be processed to monthly or 

quarterly analysis as needed. Receptor modeling, with a speciated rollback approach 

used for the PM10 SIP with monthly meteorological analyses and source identification 

combined into an annual composite, is being updated for the PM2.5 analysis. Prior 

analysis determined that fall and winter seasons are most important for PM10 in the 

San Joaquin Valley and the winter remains the most important for PM2.5 due to 

increased carbon and nitrate particulates. 

• Receptor Modeling Receptor modeling is performed by the District to establish a 

link between observed particulates and contributing emission sources using the 

combined outputs and techniques of several models. Receptor analysis of observed 

events and annual average particulate levels was performed by ARB in consultation 

with the District using the chemical mass balance (CMB) model. The output of this 

model is used in a receptor modeling speciated rollback model developed by the 

District to calculate the effect of predicted emission trends and adopted and 

proposed control measure reductions. The District developed receptor speciated 

rollback as one of its earliest improvements to standard rollback modeling, with 

documented assumptions for the isolation of natural emissions and transport of 

emissions that would not be affected by the control program. The effort to remove 

sampling artifact and non-reactive species has been incorporated into EPA SMAT 

methods to correct similar issues for the regional modeling. The District added a 

spatial area-of-influence element to more accurately reflect the effect of controls on 

contributing sources. Receptor modeling methods used for the PM10 SIP have 

been revised to evaluate PM2.5 by modifying assumptions to address fine particle 

mechanisms and with methodology revisions to reduce uncertainties for the PM2.5 

annual standard. Further revision may occur to incorporate new findings of current 

regional modeling of secondary particle formation. 
San Joaquin Valley Unified Air Pollution Control District April 30, 2008

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This receptor modeling method works well for analysis of directly emitted particles, 

but is less certain in predicting the effect of reductions of secondary precursors 

(gases that form particles in the air that may not produce particles in amounts 

directly proportional to the amount of emissions). The formation of secondary 

particulates has been examined with regional modeling to determine appropriate 

adjustments to predictions of secondary particulates. The receptor modeling 

approach uses direct (linear) assumptions for the connection of emissions changes 

to projected future contributions. This is adjusted to reflect the nonlinear chemistry 

associated with nitrate formation as determined by the regional model. Sulfate 

formation approaches linear relationship and is not adjusted for nonlinear chemistry 

in the receptor modeling. The expected result of linear projection is an overprediction of future concentration. The method anticipates uncertainty in the inputs 

and uses the over-prediction as a safety margin for attainment modeling. The PM10 

receptor modeling resulted in a sizable margin of safety, projecting attainment 

several years after actual compliance was achieved. Comparing the results of 

PM2.5 receptor modeling with regional modeling results and other pertinent 

information is important to develop a weight of evidence approach to determining 

when attainment will be achieved. 

• Regional Modeling EPA guidance expects regional modeling to play a larger role in 

the PM2.5 modeled attainment test. The primary purpose of the regional modeling 

for the PM2.5 SIP is to provide an independent analysis of the reductions needed to 

achieve attainment. Regional photochemical modeling has limitations for depicting 

the dispersion and removal processes that occur in scales finer than the grid 

resolution but provide equilibrium modeling for the most significant contributions to 

observed mass. Regional modeling uses the known emissions inventory in a 

bottom-up analysis that calculates the amount of mass that should be present due to 

the emissions. Using the model to predict mass from a future emissions inventory 

produces the best assessment of nitrate and sulfate levels that can be provided. 

The use of the model results in relationship to the design value provides a 

reasonable estimate of future PM2.5 nitrate and sulfate mass components. 

Regional modeling of secondary particulates has been conducted by ARB using 

several different data sets and models. Results of regional modeling improve 

understanding of particle formation rates and ratios of precursors to particle 

formation, particularly for nitrate particulates. These results have been used in 

conjunction with receptor modeling to enhance the accuracy and reliability of 

predicted effects of emission trends and adopted and proposed control measure 

reductions of secondary precursors. The first regional assessment used the Urban 

Airshed Model, modified to address aerosol chemistry (UAM-AERO). This 

assessment used the IMS-95 dataset (an early component of CRPAQS) to evaluate 

a monitored event of nitrate particulate formation. Regional modeling was also 

conducted for the later 2000-2001 CRPAQS data, providing an update to the PM10 

receptor modeling projections in 2006. A third round of regional modeling with the 

Community Multiscale Air Quality (CMAQ) model has been completed by ARB, has 
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3-16 

been used to develop SMAT projections for the SJV and is undergoing performance 

evaluation. If this provides a different regional photochemistry analysis for nitrate 

formation, the receptor modeling estimates for nitrates will be reviewed. 

3.3.2 Model Application 

ARB is conducting regional modeling, positive matrix factorization (PMF) evaluation for 

2004 to 2006, and chemical mass balance (CMB) modeling for 2005 annual speciation 

data for Fresno and Bakersfield. The District is reevaluating prior receptor modeling 

(CMB and speciated rollback) for the prior PM10 plans (2000 annual evaluations), 

establishing PM2.5 speciation for these analyses and projecting the concentrations from 

2000 to 2005. The District has performed an analysis and receptor projection from 

2005 to 2014 for the PM2.5 speciated versions of the 2000 annual evaluations the new 

2005 PM2.5 CMB speciation for Fresno and Bakersfield and the PMF evaluation. The 

receptor evaluations are relatively consistent for all of these events providing a strong 

weight of evidence comparison. The regional modeling results are not yet available. 

Technical issues are being examined, and revised calculations may be produced for the 

new CMB evaluations to improve profile selection for improved model performance in 

the summer and for PMF regarding the handling and analysis of carbon artifact. Prior 

CMB profile selection was conducted to match the winter dominant sources. Improved 

profile selection is recommended to meet EPA recommendation for at least a quarterly 

evaluation of profile accuracy. Carbon artifact handling in the PMF analysis should use 

the most current and accurate CRPAQS findings. Furthermore, artifact adjustments 

should follow EPA guidance and be included in relative mass comparison rather than be 

excluded from calculations. 

3.3.2.1 PM2.5 Speciation for Annual Rollback Modeling

The speciation data and CMB modeling results for PM10 contain a combination of 

coarse and fine particles. The relationship between PM10 and PM2.5 is not 

proportional; therefore special evaluation is required to develop an appropriate 

speciation set for PM2.5 rollback analysis from the CMB modeling performed for PM10. 

To convert the PM10 annual CMB modeling and rollback analysis to PM2.5, the mass 

distribution must be replaced by PM2.5 speciation data or be calculated by other 

methods from the mass determined by PM10 CMB modeling. The methodology 

includes the following components and considerations: 

• Fresno, Kern, Kings and Tulare counties have 2005 PM2.5 design values that 

exceed the 15 microgram annual standard. Analysis is required for each of these 

counties to determine emission reductions required to achieve compliance. PM2.5 

speciation measurements are collected at Bakersfield, Fresno, Modesto and Visalia. 

Fresno speciation data for PM2.5 covers the period used for the rollback foundation 

annual PM10 CMB analysis (2000-2001). Complete data for Bakersfield and Visalia 

is available for 2002 and thereafter, but is not available for 2000-2001. No PM2.5 

speciation data was collected for Kings County; however, prior PM10 speciation 
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3-17 

analysis and CMB modeling determined that Tulare and Kings County conditions are 

quite similar, allowing use of Tulare County speciation data with minor adjustments. 

The speciation data provides total mass for annual evaluation, nitrates, sulfates, 

geologic material and metals. 

• Natural and regional background for PM2.5 cannot be directly measured and is 

easily identifiable or separable from other measured local contributions. Background 

concentrations have been established in the same manner used to establish 

background values for the PM10 rollback analysis. The significance of background 

levels is that such material will not be affected by the District’s control efforts. Since 

rollback provides a linear projection of effect for reducing emissions, failure to 

exclude background will over-predict the effect of control efforts. All assumptions for 

background are now expressed as percentages of material. The background values 

for geologic material, nitrate and sulfate particulates have been set at 10% of the 

observed concentration instead of a fixed concentration. Dynamic background 

contributions of 10% were too high for use with PM10 due to high deposition rate 

and short average distance of travel; however, PM2.5 has greater travel distance 

and persistence in the atmosphere. 

• Mobile exhaust and tire and brake wear were determined by CMB annual analysis 

for PM10. From the emissions inventory we are able to establish that slightly over 

90% of the mobile exhaust emissions are PM2.5 and approximately half of the tire 

and brake wear material is PM2.5. The mass determined for PM10 rollback has 

been adjusted accordingly to establish a reasonable mass attribution for these 

sources. 

• Fresno annual rollback uses a design value derived from the annual speciation data 

set for the years 2000 and 2001. Fresno annual rollback uses limited elements of 

the annual PM10 CMB analysis, performed for the year 2000 with additional data 

from the first quarter of 2001, to provide mass estimates for motor vehicles and tire 

and brake wear. The modeled contribution for motor vehicles and tire and brake 

wear has been adjusted by factors determined from the emissions inventory to be 

representative of PM2.5 material. The average of 2000 and 2001 PM2.5 speciation 

data is used to provide PM2.5 species for nitrates, sulfates, geologic material and 

unassigned (elements). Organic carbon and vegetative burning is composed 

organic and elemental carbon similar to the motor vehicle emissions but contains 

both large and small particles. The mass for organic carbon and vegetative burning 

has been calculated as the remainder of the annual PM2.5 speciated mass not 

assigned to the other categories. 

• Bakersfield uses the same elements from the annual PM10 analysis but is required 

to use 2002 PM2.5 speciation data as the earliest complete speciation available for 

this purpose. Modeling may be revised or adjusted in other ways if improvements to 

the methodology are identified by technical evaluation. 
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3-18 

• Visalia uses the same elements from the annual PM10 analysis but is required to 

use 2002 PM2.5 speciation data as the earliest complete speciation available for this 

purpose. Modeling may be revised or adjusted in other ways if improvements to the 

methodology are identified by technical evaluation. 

• Kings County uses Visalia speciation data for the year 2002 to establish PM2.5 

mass with adjustment to motor vehicle and tire and brake wear. The PM10 

speciation data was very similar for Kings and Tulare counties in previous years, 

with the exception of fugitive PM10 emissions that are large particles. Motor vehicle 

contributions were similar to Visalia in Hanford but much less in Corcoran. Corcoran 

is the site that sets the design value for Kings County. Prior CMB modeling of the 

same event at both Visalia and Corcoran establishes an approximate ratio of the 

motor vehicle and tire and brake wear contributions at the two sites. Based on this 

evaluation, motor vehicle emissions and tire and brake wear are adjusted to 55% of 

the Visalia concentration to reflect the smaller urban contribution found in Corcoran. 

• CMB results for Fresno and Kern provided by ARB were adjusted by 0.6 micrograms 

reassigned from organic carbon (OC) to unassigned mass as found with earlier CMB 

modeling. Inert material is common in SJV samples and the method of assigning all 

unaccounted mass to OC overestimates that profile. 

3.3.2.2 PM2.5 Methodology Revisions for Annual Receptor Modeling

• Cooking emissions, previously grouped with vegetative burning, are included in 

organic carbon associated with industrial and commercial emissions. 

• The speciated rollback analysis developed by the District provides spatial projection 

of the area of influence of contributions. The PM10 methodology utilized different 

assumptions for contributions dominated by large particles and contributions 

dominated by fine particles, PM2.5 and smaller. The PM10 travel distance 

assumptions for geologic and construction, tire and brake wear and unassigned 

mass utilized large particle assumptions which are modified for the PM2.5 analysis 

to be consistent with travel distance assumptions for other contributions dominated 

by fine particles. Methodology for the defined apportionment of mass to local and 

regional intrabasin transport has been adjusted from a fixed ratio to a mass weighted 

calculation to improve accuracy and correlation to the conceptual model. 

• For categories that are comprised of directly emitted particulates and secondary 

organic aerosol (SOA) formation of organic carbon compounds a default split was 

used for earlier receptor modeling assuming an even split for the two pathways. 

CRPAQS results indicate a maximum of secondary aerosol formation of fifteen 

percent of the observed carbon. The rollback analysis has been revised for this 

updated information. The emissions linkage to SOA is ROG instead of TOG. 

• Nitrate mass will be reevaluated to determine if any adjustments to linear projection 

are required. The 2003 analysis included nonlinearity adjustments obtained from 
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analysis of UAM-AERO regional modeling of CRPAQS IMS-95 data. The variation 

of nitrate chemistry is represented by the monthly variations of CMB modeling for the 

annual, which inherently incorporates the variation in nitrate chemistry throughout 

the year. Regional modeling nitrate nonlinearity adjustments are appropriate for 

episode evaluation but potentially introduce a redundant penalty in the annual 

speciated rollback modeling. The linear projection of annualized rollback already 

includes assessment of the variation of nitrate formation; therefore further 

adjustment with modeling response may constitute a redundant adjustment. The 

comparison of linear model estimation to the projections with regional modeling 

penalties for nonlinear nitrate response will be preserved until technical discussions 

on this matter are complete. 

• Receptor modeling will use the alternate linear estimation assumptions for trapped 

water. Water bonded to ammonium nitrate is approximated as equivalent to twelve 

percent of the mass and water bonded to ammonium sulfate is approximated as 26 

percent of that mass. This method allows the water to remain incorporated in the 

proportional rollback because the trapped water is assumed to be proportional to the 

ammonium nitrate and ammonium sulfate mass. The linear assumption avoids the 

need to handle trapped water as a separate calculation. 

3.3.3 Weight of Evidence 

A weight of evidence approach compares conceptual descriptions, episode 

categorization techniques, adjusted air quality trends, and other analysis to modeling 

results. The purpose of these additional analyses is to provide additional insights into 

the projection of expected future air quality. The Speciated Modeled Attainment Test is 

the primary benchmark for quantifying reduction targets to achieve attainment; however, 

supplemental evaluations may be appropriate if air quality trends or other information 

indicate that the targets will be met with less reduction than indicated or will require 

additional efforts to achieve compliance with the standards. The District has determined 

that the 15 microgram annual standard is more stringent for our air basin than the 1997 

65 microgram daily standard. The new 35 microgram daily standard appears to be 

more stringent than the annual standard but is on a different timeline for planning and 

implementation and has not been used to determine reduction goals for this plan. 

PM2.5 monitoring is a relatively new program; therefore, the historical record of data 

does not provide a sufficient history to evaluate long-term trends and patterns. The 

District and ARB will continue evaluation of data using a variety of statistical methods to 

identify potential key factors. Results of evaluations will be used to improve the 

District’s conceptual understanding of events and may be considered to provide 

substantive data in the process of establishing a weight of evidence finding for 

attainment. 

The PM2.5 receptor modeling examines the 15 microgram per cubic meter annual 

federal standard. When evaluating the 50-microgram annual standard for PM10, an 
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3-20 

uncertainty of one-microgram represented only a two percent variation; however, a onemicrogram uncertainty in the PM2.5 analysis represents a variation that is almost seven 

percent of the total allowed. This sets a very difficult benchmark for accuracy. 

Furthermore, PM2.5 is not a single material but a host of different materials with both 

separate behaviors and dependent interactions. Although there is a solid foundation of 

conceptual understanding, there are many technical issues that remain open questions 

for continued study. The PM2.5 SIP will utilize all completed analyses available at this 

time; however, the District expects emerging technical information to enhance 

understanding of observed events to improve our ability to predict future PM2.5 

concentrations. 

3.3.4 Speciated Modeled Attainment Test 

EPA guidance acknowledges the difficulty in obtaining a data set for modeling that 

exactly matches the current design values and has developed a methodology to break 

down the modeling into the component constituents and use the model response in a 

relative sense to predict the reductions needed to achieve attainment. This Speciated 

Modeled Attainment Test (SMAT) methodology is necessary because the different types 

of materials come from different types of sources and the emissions inventories of these 

sources vary at different rates and have different relationships for the contribution of 

PM2.5 mass. Therefore, the constituent materials that contribute to PM2.5 are not 

directly additive and must be calculated separately and be added together as a final 

step to determine the total PM2.5 mass. ARB will perform SMAT for the regional model 

and the District has developed an implementation of SMAT for the receptor modeling. 

The Speciated Modeled Attainment Test (SMAT) methodology calculates remaining 

mass other than the nitrates and water as organic carbon. This approach is too coarse 

for use for the District. The basis for this method is that most areas of the country do 

not have extensive control programs for geologic material (fugitive dust) or extensive 

emissions from carbon sources subject to direct control (residential wood combustion 

and agricultural burning). Carbon particle size growth and trapped carbon particles 

within nitrate and sulfate particulates that are not measured in the analysis methods are 

further losses not addressed by SMAT. CRPAQS modeling for particle size growth is 

under development but not available at this time. Metals are also not isolated by SMAT 

methods. For any elements not well-supported by the regional model results, receptor 

modeling or other substantive data will be reviewed to establish a weight of evidence 

finding for attainment. 

Model response is used in a relative sense to predict the reductions needed to achieve 

attainment. Speciated Modeled Attainment Test (SMAT) calculations determine the 

amount of reductions needed from the major source categories to achieve compliance 

with federal PM2.5 standards at all monitoring sites. The results of this process predict 

future PM2.5 concentrations that would result from trends and current and proposed 

control programs. EPA guidance identifies how these calculations should be performed 

for a regional model. The District has determined applicability to the receptor analysis. 
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Chapter 3: What is Needed to Demonstrate Attainment? 

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3-21 

The Speciated Modeled Attainment Test (SMAT) methodology is generally applicable 

throughout the country but conflicts with certain important considerations critical to San 

Joaquin Valley Air Basin (SJVAB) assessment. Specific adjustments have been made 

to address technical issues specific to the SJVAB and to provide the most accurate 

means to reflect the effects of emission reductions. 

• The receptor analysis exceeds SMAT requirements by providing extensive 

separation of contributing direct and secondary carbon sources. Secondary 

formation rate information developed by the CRPAQS program is used to quantify 

the secondary aerosol partition. By means of CMB model evaluation, carbon mass, 

along with associated trace metals and other contributions to the source signature, is 

divided between: 

o Motor vehicle emissions, 

o Tire and brake wear, 

o Stationary and area sources carbon mass, and 

o Vegetative burning. 

• The receptor analysis exceeds SMAT requirements that recommend quarterly 

evaluation by performing monthly evaluation and determining that CMB performance 

meets standards on a monthly basis. The annual CMB modeling adjusts speciation 

selections for wood burning to reflect seasonal changes but otherwise uses a 

consistent set of speciation signatures. Performance verification demonstrates that 

the selected profiles are acceptable for identifying and representing the contributing 

sources throughout the year. A further evaluation of CMB performance with 

quarterly optimized profiles will be performed as a corroborative test. 

• The receptor analysis exceeds SMAT requirements by separating the contributions 

of geologic material from other sampling artifacts and unknowns. This is of 

particular importance to the SJV due to the District regulations for control of fugitive 

dust. The benefit of the District programs must be modeled separately from artifacts 

to quantify reductions appropriately. 

• Receptor modeling addresses the SMAT requirement regarding trapped water in 

ammonium nitrates and sulfates using approved alternate linear assumptions. The 

linear assumption avoids the need to consider trapped water as a separate 

calculation. According to the linear assumption, water bonded to ammonium nitrate 

is approximated as equivalent to twelve percent of the ammonium nitrate mass and 

is proportional to the amount of ammonium nitrate particulate mass present. Water 

bonded to ammonium sulfate is approximated as 26 percent of that mass and is 

proportional to the amount of ammonium sulfate particulate mass present. Because 

the amount of trapped water is established by the linear assumption method as 

proportional to the amount of the ammonium related mass contributions, the 

speciated rollback analysis processes the trapped water as an incorporated linear 

component of the ammonium nitrate and ammonium sulfate particulate masses and 

does not establish a separate calculation column. 

Technical note: The SMAT methodology separates out trapped water and 

ammonium, sulfate and nitrate ions. This is necessary in portions of the country 

that are dominated by sulfate emissions. Decreases in sulfate emissions can 
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3-22 

actually cause increase in nitrate formation in areas dominated by sulfates. The 

associated water content of sulfates is much different than for nitrates and can 

require mass recalculation for areas with high sulfates. The SJVAB is dominated 

by ammonium nitrate particulates with low sulfate particulate concentrations; 

therefore this process is of minimal effect on the Valley PM2.5 mass calculation. 

3.4 MODELING RESULTS 

The modeling was conducted with an annual emission inventory PM 2.5 SIP Planning 

Projections - v1.00 RF#994.

Although ambient PM2.5 levels all sites in the Valley must be within the standard for the 

Valley to be redesignated into attainment, some sites already comply with the PM2.5 

standards in force for this plan (annual standard 15, daily standard 65). The revised 

daily standard of 35 has a separate timeline for planning and compliance. 

A speciated modeled attainment test (SMAT) has been completed with receptor 

analysis modeling. The receptor modeling evaluation uses speciated rollback for its 

base calculations and is used in the prescribed relative reduction method fro the 

Speciated Modeled Attainment Test. Variations from EPA methodology that use 

additional information available for the SJVAPCD and to adjust for assumptions 

documented by EPA and others as not appropriate for California are identified in the 

PM2.5 Modeling Protocol. 

Table 3-2 San Joaquin Valley Air Pollution Control District 

PM2.5 Receptor Speciated Modeled Attainment Test 

County 

2005 Design 

Value 

(DV) 

(μg / m3)

Receptor 

Modeled 

SMAT RRF 

2005-2014 

Projected 

Value 2014 

(DV * RRF) 

(μg / m3

)

Predicted 

Compliance Year 

San Joaquin 12.9 Meets Standard Meets Standard

Stanislaus 14.1 Meets Standard Meets Standard

Merced 14.7 Meets Standard Meets Standard

Madera - 

No data, 

unclassified No data, unclassified

Fresno M1 17.2 .721 12.40 2010 

Fresno M2 17.2 .753 12.94 2011 

Fresno PMF 17.2 .707 12.17 2011 

Kings M1 17.2 .770 13.25 2011 

Tulare M1 18.2 .730 13.29 2013 

Kern M1 18.9 .728 13.76 2014 

Kern M2 18.9 .742 14.02 2014 

Kern PMF 18.9 .746 14.09 2014 
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Method 1: 2000 baseline species were projected to 2005 and then the 2005 projected 

species were used for projection to 2014. Due to limited speciation data, Method1 will 

be used for Tulare and Kings. 

Method 2: 2004-2006 species were projected to 2014. This second test is available for 

Fresno and Kern. 

PMF: A receptor projection was also prepared from output of the PMF model for 

Bakersfield and Fresno speciated data. 

A regional model evaluation has been prepared by ARB. Observations from 2000-2001 

were used to prepare the model for performance evaluation. Relative response is 

established for emission inventory years 2005 and 2014. Findings from a SMAT 

evaluation of the regional model shown in table 3-3 compare very closely to the results 

of the receptor SMAT analysis shown in Table 3-2. To maintain public records and 

archives for the PM2.5 SIP, the District has requested a copy of the SMAT calculation 

files developed by ARB for analysis of the regional model output. However, due to the 

size (the previous version received by the District was 54 megabytes) and technical 

nature of these files, the District does not intend to print or distribute these modeling 

analysis files. 

Table 3-3 San Joaquin Valley Air Pollution Control District 

PM2.5 Regional Speciated Modeled Attainment Test 

Reference and future year annual design values for SJV FRM sites 

 determined from the regional model using EPA SMAT procedure

Site Code Speciation 2006 DV 2014 "Controlled" DV

Bakersfield - 5558 California BAC BAC 18.51 14.28 

Bakersfield - 410 E Planz Road BEP BAC 18.86 14.70 

Bakersfield - Golden State BGS BAC 18.64 14.39 

Clovis - N Villa Avenue CLO FSF 16.39 12.72 

Corcoran - Patterson Avenue COP VCS 17.24 13.27 

Fresno - 1st Street FSF FSF 16.68 13.01 

Fresno - Hamilton and Winery FSH FSF 17.16 13.47 

Merced - 2334 M Street MRM M14 14.69 11.76 

Modesto - 14th Street M14 M14 14.10 11.44 

Stockton – Hazelton Street SOH M14 12.93 10.87 

Visalia - N. Church Street VCS VCS 18.20 14.47 

3.4.1 Discussion of Results 

• The four northern SJV counties, San Joaquin, Stanislaus, Merced and Madera, need 

no additional reductions and already meet attainment requirements for the annual 

standard. Table 3-2 lists projected values for 2014 because all counties must meet 
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3-24 

the standard to demonstrate attainment and analysis of Bakersfield does not support 

projection of attainment prior to 2014. 

• Kings County – attainment is projected by 2011 with existing emission reduction 

commitments (Method 1 projection of 2000 PM2.5 species data to 2005 and 

projection from 2005 to 2011 for SMAT). The projected value in 2014 is 13.25 

μg/m3

. Linear projection methods are conservative and, when used for the PM10 

SIP, projected a later attainment date than was actually achieved. 

• Fresno County attainment is projected by 2011 with existing emission reduction 

commitments. Linear projection methods are conservative and, when used for the 

PM10 SIP, projected a later attainment date than was actually achieved. 

o Method 1 projects attainment by 2010 with no margin for error. Method 1 uses 

2000 PM2.5 species data to 2005 and projection from 2005 to 2010 for SMAT 

projected a concentration of exactly fifteen micrograms. The projected value 

in 2014 is 12.40 μg/m3

. 

o Method 2 projects attainment by 2011 for Fresno. Method 2 analysis of 2004-

2006 speciation data, using essentially the same methodology as Method 1 

with modification of secondary aerosol evaluation due to use of a more 

restrictive motor vehicle emission profile. The projected value in 2014 is 

12.94 μg/m3. 

o PMF evaluation projects attainment by 2011. Corroboration is available for 

Fresno County by PMF evaluation. The PMF results were used to prepare a 

SMAT evaluation. The PMF evaluation uses data from 2003 to 2006 for 

evaluation but excludes many samples that fail specified screening criteria. 

Therefore, the PMF data has gaps during the year and may not precisely 

match an annual evaluation due to variations during the year that are not well 

represented. Despite the differences in assumptions and approach, the PMF 

results correlate to Method 1 and Method 2 with a projected value in 2014 of 

12.17 μg/m3. The PMF results confirm and update evaluation of regional 

transport by determining the contribution of aged aerosol. This information 

has been used to update the assumptions for regional transport of nitrate and 

sulfate for Method 1 and Method 2. 

• Tulare County – attainment is projected by 2013 with existing emission reduction 

commitments (Method 1 projection of 2000 PM2.5 species data to 2005 and 

projection from 2005 to 2013 for SMAT). The projected value in 2014 is 13.29 

μg/m3

. Linear projection methods are conservative and, when used for the PM10 

SIP, projected a later attainment date than was actually achieved. 

• Kern County attainment is projected by 2014 with emission reduction commitments. 

Linear projection methods are conservative and, when used for the PM10 SIP, 

projected a later attainment date than was actually achieved. 

o Method 1 projects attainment by 2014. Method 1 uses 2000 PM2.5 species 

data to 2005 and projection from 2005 to 2014 for SMAT projected a 

concentration of 13.76 μg/m3

. 
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o Method 2 projects attainment by 2014. Method 2 analysis of 2004-2006 

speciation data, using essentially the same methodology as Method 1 with 

modification of secondary aerosol evaluation due to use of a more restrictive 

motor vehicle emission profile. The projected value in 2014 is 14.02 μg/m3

. 

o PMF evaluation projects attainment by 2014. Corroboration is available for 

Kern County by PMF evaluation. The PMF results were used to prepare a 

SMAT evaluation. The PMF evaluation uses data from 2003 to 2006 for 

evaluation but excludes many samples that fail specified screening criteria. 

Therefore, the PMF data has gaps during the year and may not precisely 

match an annual evaluation due to variations during the year that are not well 

represented. Despite the differences in assumptions and approach, the PMF 

results correlate to Method 1 and Method 2 with a projected value in 2014 of 

14.09 μg/m3. The PMF results confirm and update evaluation of regional 

transport by determining the contribution of aged aerosol. This information 

has been used to update the assumptions for regional transport of nitrate and 

sulfate for Method 1 and Method 2. 

Regional photochemical and particle modeling has also been completed by ARB. ARB 

confirms a finding of attainment for all monitoring sites in the District by 2014. Table 3.3 

provides projections for the 2014 design value at all District sites that collect federal 

reference method (FRM) PM2.5 monitoring data. The use of this data is required for the 

implementation of the SMAT process that uses the design value established by this 

data with the relative change projected by the model to project the future design value. 

Extensive discussion of the regional modeling approach and documentation of results is 

in Appendix G to this plan. 

It is important to note that both the receptor methods and regional modeling include all 

directly emitted and precursor reductions. All of these reductions have some effect on 

future particulate levels. Directly emitted PM2.5 reductions provide a direct benefit, 

while particulate precursors do not have the same one-to-one relationship. SOx has a 

strong PM2.5 forming potential throughout the year. NOx has a strong particulate 

forming potential during winter months. ROG emissions have a very limited particulate 

contribution by formation of secondary organic aerosol. The technical issues regarding 

precursors have been extensively evaluated and are discussed in the modeling protocol 

(Appendix F) with sensitivity evaluations documented in the receptor analysis modeling 

files. 

Table 3-4 Regional Model Evaluation 

2014 emissions without controls compared to 2014 emissions with controls

Percent of Reduction NOx PM2.5 SOx ROG

Defined State Measures 

(Strategy 4/26/07) 20 5 0 6

District Rules 

(Dft Plan 12/11/07) 4 8 4 0

Total Reduction 24 13 4 6
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Receptor modeling includes the reductions associated with all emission sources. The 

analysis provides separate correlation to PM2.5 contribution for geologic emissions, 

motor vehicle direct and secondary emissions, tire and brake wear particulate, organic 

carbon that is directly emitted or formed as secondary organic aerosol, ammonium 

nitrate particulate that forms from NOx emissions, ammonium sulfate particulate that 

forms from SOx emissions, and vegetative burning emissions from residential wood 

burning, wildfires and agricultural burning. 

An example of the relative contribution to the annual PM2.5 is shown in the following 

figure, which reveals that even after proposed reductions in 2014, all of the categories 

continue to provide measurable contributions to the annual PM2.5 concentration. The 

extensive contribution of ammonium nitrate from NOx remains dominant, but the other 

contributions are collectively half of the annual concentration. 

Figure 3-4 Example annual PM2.5 source contributions, Kern 2014, including 

reductions 

Receptor modeling results were evaluated by the District to determine the importance of 

reductions for particulates and precursors other than reductions of NOx (which reduce 

ammonium nitrate particulate). Each precursor has a different relationship to directly 

emitted or secondary formation of particulate, making it difficult to describe reductions in 

common terms. The easiest approach to identify the importance of other reductions 
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(PM2.5 direct or SO2) with the receptor model is to remove the reductions from the 

analysis and determine how much more NOx reduction would be required to offset 

those reductions. The District analysis evaluated the highest concentration site 

analyzed by the receptor modeling (Kern County – Bakersfield California Street) for both 

the 2005 to 2014 and 2009 to 2014 reductions. The result of this analysis is that without 

the reductions of other PM2.5 and precursors, an additional 172 tons of NOx reduction 

would be needed by 2014 to achieve the same improvement in PM2.5 as provided by 

the other reductions. An additional 40 tons would be needed for the more limited time 

period of 2009 to 2014. This demonstrates that the majority of other reductions (77% of 

the direct and other secondary reductions) are being expeditiously implemented by 

2009. 

3.4.2 Weight of Evidence 

A weight of evidence evaluation is required when the projected future year value is 

close to the standard. Projections of the receptor evaluation predict that Bakersfield will 

have a design value close to the standard in 2014 and projections of the regional model 

predict both Visalia and Bakersfield as having future design values close to the standard 

in 2014. A weight of evidence determination that attainment will be achieved by the 

Plan is established by comparing the evidence provided by air monitoring data, 

technical analysis and the results of various models. The following is a brief weight of 

evidence evaluation by the District that draws upon the extensive weight of evidence 

documentation provided by ARB as Appendix H to this plan. 

• Prior Accuracy of Receptor Evaluation Methodology for PM10: Use of the 

speciated rollback receptor modeling for PM10 established the merits of the method 

and demonstrated a strong correlation to observed improvement. As expected for a 

linear projection, the projected future values are conservative and attainment was 

achieved prior to the projected date. Fourth quarter fine particulate matter 

dominates the annual PM10 evaluations; therefore, much of the PM10 annual 

standard is also a PM2.5 annual evaluation. This establishes a strong probability 

that the receptor evaluation will provide a reliable basis for PM2.5 modeling. 

• Consistency of Method 1 Projection Methodology: The projection of 2000 to 

2014 for the foundation data observations was essentially equal to the values 

predicted by projecting the 2000 data to 2005, resetting the species to the projected 

values for 2005, and projecting the change from 2005 to 2014. This indicates a 

stable relationship between the inventory and the concentration projections. An 

inconsistency in this result would have been unexpected and would have indicated 

greater uncertainty in the connection between the observations and the inventory. 

• Method1 and Method 2 Comparison: Method 1 and Method 2 provide receptor 

analysis based on different years of observations. The species data for the different 

year groups is quite different for carbon sources; however, both evaluations reflect a 

similar response to emissions change for the period from 2005 to 2014, establishing 
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a consistent relative response factor (RRF) for the speciated modeled attainment 

test (SMAT). The raw projected value for Fresno differs for the two evaluations, 

reflecting local changes in vegetative burning and possibly reduction of motor 

vehicle emissions, although motor vehicle emission change is difficult to assess due 

to the use of a different motor vehicle emissions profile in the Method 2 evaluation. 

However, the relative reduction factor response for Fresno remains consistent for 

the two evaluations. Kern County evaluations project similar concentrations as well 

as a similar RRF value while reflecting differences in the attribution of carbon 

sources, at least in part due to the use of the different motor vehicle profile for the 

Method 2 analysis. The relative consistency of 2005 episodes to 2000 episodes 

through relationship to the emissions inventory indicates a strong proportional 

linkage between the receptor modeling PM2.5 concentration and the emissions 

inventory. The strong linkage between the inventory and the observations 

establishes a reliable foundation for using the receptor modeling to establish 

emission reduction targets to achieve attainment. 

• PMF Confirmation of Regional Component Estimates: The PMF analysis 

provides an independent confirmation of regional contributions previously estimated 

for Method 1 and Method 2. The PMF analysis also provides sufficient information 

to establish a receptor evaluation for corroboration with Method 1 and Method 2. 

o The PMF results were used to revise estimation of nitrate and sulfate 

background contributions (particulate inflow from outside the District). The 

PMF evaluation determines the contribution of “aged aerosol” by determining 

the amount of nitrates, sulfates and organic carbon that have reacted with 

inflow of sea salt in the air. This reaction takes time to occur and establishes 

that the emissions are aged rather than fresh local emissions. The 

importance of identifying the amount of inflow contribution is that projected 

changes from District actions and trends in local emissions must be matched 

against the local source emissions and must not be reflected as affecting 

contributions from outside the District. The accuracy of this evaluation 

prevents over-prediction of benefit from local actions. 

o PMF results were used to prepare a receptor evaluation for corroborative 

comparison to the SMAT receptor evaluations for Method 1 and Method 2. 

The PMF analysis uses data from 2003 to 2006 for evaluation, similar to the 

2004 to 2006 period of data used for Method 2, but is required to exclude 

many samples that fail specified screening criteria. Therefore, the PMF data 

has gaps during the year and may not precisely match an annual evaluation 

due to variations during the year, if the variations are not well represented by 

the remaining data. Despite the differences in assumptions, input data 

processing and approach, the SMAT receptor analysis prepared with the PMF 

results correlates closely to Method 1 and Method 2 receptor evaluations. 

The RRF for the PMF receptor evaluations vary from the other methods by 

two percent for Fresno County and less than half a percent for Kern County. 

However, the attribution of contributing sources is quite different, with more 
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mass attributed to nitrate and sulfate particulate and less mass attributed to 

vegetative burning particulate. The differences result in a dissimilar 

emissions response (9 percent difference for NOx reductions in Kern County). 

o The processing of PMF for source identification conducted by ARB excluded 

a specified portion of the measured organic carbon mass due to collection 

with a non-federal reference method (FRM) sampler. Sampler comparison 

was conducted and the regression difference between samplers was 

considered to be a sampler artifact of VOC incorrectly quantified as 

particulate matter. This methodology has been previously accepted as a 

method for PMF to establish sources that correlate well to FRM samplers. 

The removed organic carbon mass was restored to the receptor analysis 

based on review of CRPAQS technical findings that establish a smaller 

estimate for the artifact and guidance for SANDWICH (measured Sulfate, 

Adjusted Nitrate, Derived Water, Inferred Carbonaceous mass Hybrid 

Material Balance Approach) and SMAT data evaluation. With the removed 

organic carbon mass included in the receptor evaluation, the PMF 2003-2006 

results for organic carbon match well with the Method 2 analysis of 2004-

2006 organic carbon. While some of the organic carbon is unquestionably 

sampler artifact from VOC, FRM samplers also collect a smaller amount of 

such artifact. Per EPA guidance for SMAT, artifacts are retained in the 

analysis and compared proportionally. The receptor analysis methodology 

used by the District includes the organic carbon artifact with secondary 

organic aerosol (SOA - also formed from VOC) and projects future 

concentration based on changes in the VOC inventory. The proportional 

change is used in the SMAT evaluation and will reflect the comparable effect 

on FRM sampler mass that is also attributable to secondary organic aerosol 

and retained VOC quantified as particulate matter. 

• Regional Modeling: Regional modeling performed by ARB also projects 

attainment by 2014. Regional model SMAT projections were compared by the 

District to findings provided by receptor modeling Methods 1, Method 2 and PMF. 

All sites were in very close agreement with the largest difference at Visalia. The 

peak value predicted by the regional model is 14.70 μg/m3

 at Bakersfield Planz, a 

site not suitable for receptor evaluation due to a lack of speciation data. The 

regional model prediction for Bakersfield California site is14.28 μg/m3 which 

correlates well with the receptor Kern M2 prediction of 14.02 based on data from 

the same site. The widest variation is at Visalia with a difference of 1.18 

micrograms. Although the models disagree on exact value for Visalia, both 

models predict a 2014 design value that complies with the annual standard. 
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Table 3-5 Regional and Receptor Model Comparison 

Site Code

2014 

Regional 

2014 

Receptor Difference 

Bakersfield - 5558 California BAC 14.28 14.02 0.26 

Corcoran - Patterson Avenue COP 13.27 13.25 0.02 

Fresno - 1st Street FSF 13.01 12.94 0.07 

Visalia - N. Church Street VCS 14.47 13.29 1.18 

• Model Reliability: A receptor model must demonstrate a reliable connection 

between the emission inventory and the observed concentrations. This test has 

been met for both the PM10 and PM2.5 receptor evaluations. Furthermore, the 

District has been using this approach long enough to determine that the method is 

reliable and conservative when estimating reductions required to achieve attainment. 

The regional model is the third effort for regional photochemical modeling of the SJV 

performed by ARB. This approach uses state-of-the-science methods to model 

each day of a fourteen-month period. Performance analysis of the regional model 

for submission to EPA as model documentation is still in progress; however, the 

correlation to receptor modeling gives a strong indication that the model will meet 

the required accuracy requirements. 

• All Contributing Sources Considered: A review of contributing sources indicates 

that both the receptor and regional modeling evaluations are comprehensive. The 

SMAT procedure of EPA guidance calls for evaluation of the major contributing 

sources. This procedure has been followed for the regional modeling and an 

equivalent process was established for the receptor evaluation. Both models use 

the current emissions inventory and common projections of reductions. Evaluation 

in the previous section identifies the importance of including all key sources and 

reductions. Emission Inventories undergo constant review and improvement and the 

California emission inventories are more comprehensive than other states due to 

inclusion of much smaller contributing sources. 

• Air Monitoring Data and Trends: Analysis of recent air quality data and trends is 

included in Appendix H. Significant improvement has occurred from 2001 to 2006 in 

maximum concentration, frequency of higher concentration days and annual design 

value. Changes in chemical composition are strongly related to identified emission 

reductions in recent years providing confirmation and support for current modeling 

methods. Air monitoring data for 2007, which is not yet complete or certified, 

indicates that 2007 might reflect a one-year increase in comparison to the last three 

years. Year-to-year variation is to be expected and is why design values are 

established over a three-year period. The District performed a sensitivity test with 

an estimated design value based on available uncertified data for 2007 and 

determined that the 2014 daily design value would still be far below the required 65 

microgram standard. Evaluation of the top 25% of days modeled by the regional 

model also indicate a projected future design value well below the daily standard 

while the annual projection is very close to the standard. The importance of these 
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evaluations is the finding that attainment of the daily 65 microgram per cubic meter 

standard will be met by less reduction than is required to attain the annual standard. 

The annual standard is a more stringent requirement at this time and establishes the 

reduction goals for this PM2.5 Plan. However, the new 35-microgram standard is 

more restrictive than the fifteen microgram annual standard and is expected to 

establish attainment goals when plans are developed and submitted for that 

standard. 

• Technical analysis: Technical issues are discussed in: 

o Appendix F the SJV PM2.5 SIP Modeling Protocol, 

o Appendix E District Additions to the Conceptual Model 

o Appendix H: Weight of Evidence 

These issues are discussed extensively in the Appendices and briefly at the 

beginning of this Chapter. Evaluation of the technical issues does not contradict 

model projections, but provides insight into why the Valley has high particulate levels 

in comparison to other areas of the country. The modeling approaches followed by 

the District and ARB incorporate and are consistent with our understanding of these 

technical issues. 

• Weight of Evidence Conclusion: Weight of Evidence evaluation concludes that the 

model projections are consistent and project attainment. The importance for the 

weight of evidence analysis of correlation between modeling results that use 

different approaches and data is the finding that all of the modeling approaches are 

in agreement and project attainment by 2014. Both receptor and regional chemicalphotochemical evaluations arrive at the same conclusion and nearly identical values 

for the sites common to both models. 

Supplemental issues reviewed in the weight of evidence evaluation also provide 

support for the projection of attainment by 2014. A review of contributing sources 

indicates that both the receptor and regional modeling evaluations are 

comprehensive. Although there are fluctuations in the annual 24-hour data, it has 

been determined that the annual standard is more restrictive and that attainment of 

the daily 65 microgram per cubic meter standard for this planning process will be 

met with less reduction than is required to attain the annual standard. Technical 

analysis has examined the conceptual model and identified additional considerations 

applicable to the SJV. The technical issues do not contradict model projections; 

rather they provide additional insight into why the Valley has high particulate levels 

in comparison to other areas of the country. 
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3.4.3 Demonstration of Attainment 

Attainment is demonstrated for each site that is projected to have future concentrations 

at or below the federal standards. The predicted PM2.5 concentration may also be 

achieved with different equivalent reductions in individual sources or source categories. 

When the future predicted design value is close to the standard, EPA recommends that 

a weight of evidence analysis be conducted to confirm the projection of attainment. 

Required demonstrations: 

• Attainment of the annual standard 15 μg/m3

 

• Attainment of the prior 24-hour standard 65 μg/m3

• Weight of evidence evaluation if either projection is near the standard 

• Evaluation of unmonitored areas (areas without monitoring sites) 

Attainment of the annual standard is projected by 2014 by the regional photochemical 

model and all receptor evaluations. The predicted value is within one microgram of the 

standard; therefore, a weight of evidence evaluation is appropriate. The predictions of 

these models are compared, along with air monitoring data, trends and other technical 

information, to establish a weight of evidence assurance that attainment will be 

achieved. The weight of evidence evaluation supports acceptance of the regional and 

receptor modeling predictions. Evaluation of the receptor modeling identifies that 

attainment will not occur by 2009 with the expected achievable reductions and will 

require the extensive NOx reductions proposed by ARB for 2014. Reductions achieved 

by the District and current ARB efforts for all directly emitted and secondary particulate 

sources are important to achieving attainment. The proposed NOx reductions for 2014 

would not be sufficient to achieve attainment without these other reductions. The 

strategy for attainment includes reduction of directly emitted PM2.5 (geologic, mobile, 

organic carbon and vegetative burning) as well as reductions from SOx and NOx as 

precursors to ammonium sulfate and ammonium nitrate. Secondary organic aerosol 

particulate formation is also included in the modeling evaluation of motor vehicle and 

organic carbon contributions. 

Attainment of the prior 24-hour 65 microgram standard is projected to occur prior to 

2014 and with much less reductions required than are needed to attain the annual 

standard. This means that the annual standard identifies the amount of reductions 

needed to achieve attainment. ARB used the regional model to evaluate the top 25% of 

days modeled to provide the annual analysis. Based on design values for 2005, ARB 

projected a 2014 value of 45 micrograms or less at all sites. Due to concerns that the 

last two years have experienced slightly higher 24-hour values, the District also 

performed a screening assessment with estimated design values for 2007 (based on 

incomplete and uncertified data). Evaluation by the District projected a 2014 value of 53 

micrograms. Both of these projections are well below the 65 microgram standard and 

do not require a weight of evidence evaluation. 

Unmonitored area evaluation for the year 2014 was conducted by ARB and provides 

confirming evidence for the attainment demonstration. The unmonitored area 
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evaluation requires examination of regional modeling results for the entire Valley. ARB 

has provided a screening assessment produced from the regional model results for the 

year 2014 to determine if any portion of the modeling domain predicts concentrations 

greater than the monitored locations. This initial analysis did not identify any grid 

squares that have higher values. ARB has committed to conduct further evaluation in 

accordance with EPA guidance should this be determined to be necessary; however, 

the screening assessment indicates that it is unlikely that any areas will be identified 

that require subsequent evaluation or temporary monitoring. The District and ARB will 

confer with EPA to ensure that the unmonitored area evaluation provides sufficient 

confirmation for the attainment demonstration. 

3.5 PM2.5 CONSIDERATIONS IN THE OZONE PLAN 

In preparing the 2007 Ozone Plan, the control strategy was developed with utmost 

consideration to future needs for the PM2.5 attainment plan. Sophisticated regional 

PM2.5 modeling for the San Joaquin Valley Air Basin using state of the science tools 

developed with data gathered from the $30 million field programs studying air pollution 

in the San Joaquin Valley was still under development at the time the ozone plan was 

completed and was therefore not available as a tool to establish a combined PM2.5 and 

8-hr ozone plan. The District wanted some indication (order of magnitude estimates) of 

the Valley’s PM2.5 carrying capacity so that the District could gauge the effects of the 

Valley’s 8-hr ozone emission control strategy on PM2.5 attainment. As a result, a 

simplified modeling exercise was conducted by ARB to help estimate the Valley’s 

carrying capacity for PM2.5. Evaluation of the San Joaquin Valley ozone control 

strategy to attain the federal 8-hr ozone standard determined that the ozone plan 

include NOx emissions reductions that are close to what is needed for attainment of the 

1997 PM2.5 standards by the maximum possible statutory attainment date of April 5, 

2015. Based on simplified modeling exercises performed at the time the ozone plan 

was completed, the ozone control strategy was determined to have a design that would 

provide most – if not all - of the reductions needed to attain the PM2.5 annual standard. 

3.6 PM2.5 EFFECT ON THE OZONE PLAN 

Additional actions to achieve the PM2.5 standards by 2015 will accelerate compliance 

with the ozone standard. The reductions of NOx that are valuable for PM2.5 

compliance will support early compliance for the eight-hour ozone standard. Some 

reductions for the PM2.5 plan, such as geologic/soil material reductions, will have no 

material benefit for the ozone plan; however, no actions in the PM2.5 attainment plan 

have been identified that would be detrimental to the ozone strategy. The smoke 

management programs enforced by the District throughout the year were initially 

developed to safeguard air quality during the ozone season and will continue to have 

that effect. The winter management of smoke and residential wood combustion has 

been enhanced to support the additional needs of the PM2.5 attainment strategy. 
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