Appendix A

Ambient	PM2.5	Data	Analysis	

2015 Plan for the 1997 PM2.5 Standard		

SJVUAPCD	

 

 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

Appendix A: Ambient PM2.5 Data Analysis 

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A-1 Appendix A: Ambient PM2.5 Data Analysis 

2015 Plan for the 1997 PM2.5 Standard

Appendix A: Ambient PM2.5 Data Analysis 

The concentration of ambient of particulate matter that is 2.5 microns or less in diameter 

(PM2.5) at any given location in the San Joaquin Valley (Valley) is a function of 

meteorology, the natural environment, atmospheric chemistry, and emissions of directly 

emitted PM2.5 and PM2.5 precursors from regulated and unregulated sources. The 

San Joaquin Valley Air Pollution Control District (District), the California Air Resources 

Board (ARB), and other agencies1 monitor PM2.5 concentrations throughout the 

Valley,2

 using filter-based monitoring (starting in 1999) and real-time concentration 

monitoring (starting in 2002). The U.S. Environmental Protection Agency (EPA) serves 

as the official repository of ambient PM2.5 data and analysis.3

The District uses the collected data to show air quality improvement through the 

standardized design value calculations, using EPA protocols to document basin-wide 

improvement and attainment of the National Ambient Air Quality Standards (NAAQS). 

As shown in this appendix, the design value (DV) data show steady, long-term air 

quality improvement that will lead to the attainment of the 1997 PM2.5 Standard. 

The District also uses the data to evaluate the impact of changing daily, quarterly, and 

annual PM2.5 concentrations on public health. These trend analyses provide the 

District with critical information about how to develop control measures and incentive 

programs that provide the most impact to public health improvements, as guided by the 

District’s Health Risk Reduction Strategy (see Chapter 3). 

This appendix provides the technical details used to evaluate and analyze the District’s 

PM2.5 concentration data as summarized in Chapters 2 of this 2015 Plan for the 1997 

PM2.5 Standard (2015 PM2.5 Plan). It also shows the multiple factors that affect 

ambient PM2.5 concentrations in the Valley (e.g. meteorology, exceptional events) and 

the evidence for air quality improvement through District regulatory actions, including 

the District’s highly successful Rule 4901 (Wood Burning Fireplaces and Wood Burning 

Heaters). 

A.1 PM2.5 CONCENTRATIONS—MEASUREMENT AND INFLUENCES 

The District, ARB, and other agencies manage an extensive air monitoring network 

throughout the Valley. The information obtained from the PM2.5 monitors within this 

network provide the District with necessary information for demonstrating attainment of 

the NAAQS and valuable information for protecting public health throughout the year. 

The monitoring network captures the spatial, seasonal, daily, weekly, and annual 

variations in PM2.5 concentrations throughout the Valley that result from changing 

meteorology, the occurrence of exceptional events (e.g. high winds and wildfires), and 

PM2.5 emissions from regulated and unregulated sources. 

 

1

 Other agencies include the Chukchansi and Tachi Yokut Tribe and the National Park Service. 2 San Joaquin Valley Air Pollution Control District Air Monitoring Network Plan: January 28, 2015 submittal to EPA. 

Available at http://www.valleyair.org/aqinfo/Docs/2014-Air-Monitoring-Network-Plan.pdf 3

 U.S. Environmental Protection Agency: Technology Transfer Network (TTN), Air Quality System (AQS): AQS Web 

Application. (2010). Available at http://www.epa.gov/ttn/airs/airsaqs/aqsweb/
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A-2 Appendix A: Ambient PM2.5 Data Analysis 

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A.1.1 PM2.5 Monitor Types 

The District and ARB use three types of PM2.5 monitors in the Valley: 

 Filter-based Federal Reference Method (FRM) monitors, defined as the 

standard for data collection; 

 Real-time beta-attenuation method (BAM) monitors designated as federal 

equivalent method (FEM) monitors, and hereafter referred to as BAM/FEM 

monitors; 

 Ordinary BAMs, not designated FEM, and hereafter referred to as BAM; and 

 Filter-based speciation monitors, similar to FRM monitors. 

Only FRM and BAM/FEM monitors produce data that is suitable for comparison with the 

NAAQS, and are therefore used for design value calculations. Real-time monitors 

(BAM/FEM and BAM) produce hourly measurements that the District uses every day to 

produce daily air quality forecasts, wood burning declarations, public health 

notifications, and Real-time Air Advisory Network (RAAN) notifications for schools. 

The filter-based speciation monitors operate similarly to the standard FRM monitors; 

however, because of the specific analysis requirements for the different PM2.5 species 

(e.g. metals, silicon, chlorine, organics) multiple filter media are required, hence a multifilter collection system. The evaluation and analysis of multiple PM2.5 species is critical 

to the development of an effective attainment strategy. 

A.1.2 Meteorological Influences on PM2.5 Concentrations 

Particulates in the atmosphere are dispersed by horizontal and vertical mixing within an 

air mass. Wind flow (horizontal mixing) and temperature instability (decreasing 

temperature with height leading to vertical mixing) provides the strongest mechanisms 

for dispersing pollutants. Wind speed can greatly influence the pollutant concentrations 

by horizontally mixing and dispersing pollutants over a large area. Generally, the higher 

the wind speed the lower the PM2.5 concentrations; however, in some cases, excessive 

winds may cause elevated PM2.5 levels as high winds entrain PM10 as well as PM2.5. 

Vertical mixing of the air mass can result from atmospheric instability. A temperature 

inversion, or increasing temperature with increasing height, can inhibit the vertical 

mixing of an air mass, and create a situation in which pollutants remain trapped near the 

surface. Prolonged periods of high pressure and stable conditions with low wind 

speeds can cause stagnant conditions that trap pollutants near the surface. PM2.5 

concentrations increase during these poor dispersion periods. During low pressure 

events, unstable conditions and stronger wind speeds occur. PM2.5 concentrations can 

decrease or increase depending on the strength and characteristics of the low pressure 

system. 
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A-3 Appendix A: Ambient PM2.5 Data Analysis 

2015 Plan for the 1997 PM2.5 Standard

Atmospheric weather patterns influence climate conditions, local meteorology, and 

PM2.5 concentrations. The next section describes the air quality impacts from the 

extreme drought. 

A.1.2.1 Valley Drought 

According to the United States Geologic Survey, California is experiencing its worst 

drought in over a century. The 2013-2014 Winter represented the third consecutive 

year of drought conditions in the Valley, and was by far the driest winter of the three 

years. On January 17, 2014, the Governor of California declared a drought emergency 

for all of California. Figure A-1 is a map produced by the National Drought Mitigation 

Center depicting the extent and severity of the drought affecting California as of 

November 4, 2014. 

Figure A-1 Drought Extent and Severity in California 

A persistently strong high pressure ridge over the eastern Pacific Ocean and the 

western United States effectively blocked weather disturbances from entering California. 

The historic strength and longevity of this high pressure resulted in a lack of rainfall 

throughout the Valley, and California as a whole (Table A-1). 
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Many cities in California, including those in the Valley, had record low rainfall totals 

during 2013 calendar year, with some records that have stood for over 100 years being 

broken. 

Table A-1 2013 Calendar Year Rainfall Totals for Select Valley and California 

Cities 

Region City

1981-2010

Average

(inches)

2013 Total

(inches)

Previous 

Record Low 

(inches)

Previous 

Record 

Year

 Modesto 13.11 4.70 5.70 1929 

 Merced 12.50 3.79 6.00 2007 

Valley Fresno 11.50 3.01 3.55 1947 

 Visalia 10.93 3.47 4.10 1910 

 Bakersfield 6.47 3.43 1.87 1959 

Other parts of 

California 

Sacramento 18.52 5.81 6.67 1976 

San Francisco 23.65 5.59 9.00 1917 

San Jose 14.90 3.80 6.04 1929 

Los Angeles 12.82 3.65 4.08 1953 

San Diego 10.34 5.57 3.41 1953 

A.1.2.2 Exceptional Event Influences on PM2.5 Concentrations 

Valley PM2.5 concentrations are also affected by exceptional events such as wildfires, 

high winds, and fireworks. An exceptional event is defined as that affects air quality; is 

not reasonably controllable or preventable; is caused by either a human activity that is 

unlikely to recur at a particular location or a natural event; and is determined by EPA to 

be an exceptional event.4

 Such events can result in PM2.5 concentration peaks, or 

even extended high-concentration episodes such as summertime wildfires. 

Since exceptional events are not reasonably preventable or controllable, it is 

inappropriate to use data influenced by these events. With proper documentation and 

EPA concurrence, data influenced by exceptional events can be excluded from official 

attainment demonstration design value calculations. Design values, which will be 

discussed fully in Section A.2, represent a three-year average of 24-hour and annual 

mean PM2.5 concentrations. 

Although not every event results in a formal submittal to EPA, the District tracks these 

events and their impact on attainment as part of its ongoing air quality analysis. These 

ongoing efforts help the District to more accurately characterize ambient PM2.5 

concentrations and attainment progress. The District has experienced fireworks activity, 

high wind events, and wildfire events in the past that caused PM2.5 concentrations to 

exceed the PM2.5 Standard. Two examples include a fireworks event in July 2007 and 

a summertime wildfire event in 2008. Analyses presented in the 2012 PM2.5 Plan

illustrated how fireworks and wildfire events can also influence the design value 

calculations and whether or not an area may achieve attainment of the PM2.5 Standard. 

 

4

 Treatment of Air Quality Monitoring Data Influenced by Exceptional Events, 72 Fed. Reg. 55, pp. 13560–13581. 

(2007, March 22). (to be codified in 40 C.F.R. pts. 50 and 51), (40 CFR 50.14) 
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A.2 ATTAINMENT DEMONSTRATION—DESIGN VALUES 

Design values represent the official metric for assessing air quality improvements and 

attainment of the NAAQS per the Federal Clean Air Act and EPA regulations. Design 

value calculations are three-year averages that follow EPA protocols for rounding, 

averaging conventions, data completeness, sampling frequency, data substitutions, and 

data validity. The results provide consistency and transparency to determine basinwide attainment for both components of the 1997 PM2.5 Standard, including the 24-

hour PM2.5 standard of 65 μg/m3 and the annual PM2.5 standard of 15.0 μg/m3. If any 

monitoring site within the air basin has either a 24-hour or annual PM2.5 design value 

higher than the respective standard, then the entire air basin is designated 

nonattainment. 

Table A-2 provides the generalized descriptions of how the 24-hour average and annual 

average design values are calculated for PM2.5. EPA provides detailed guidelines and 

standards for the calculation5

 and data handling6 methodologies. 

 

Table A-2 General PM2.5 Design Value Calculation Methods 

Averaging 

Period Level Calculation Method 

24-hour 65 μg/m3 

Step 1: Determine the 98th percentile value for each year over a 

consecutive three year period.

Step 2: Average the three 98th percentile values.

Step 3: Round the resulting value to the nearest 1.0 μg/m3. 

Step 4: Compare the result to the standard.

Annual 15.0 μg/m3 

Step 1: Calculate the average of each quarter of each year over 

a three year period. 

Step 2: Average the four quarters in a calendar year to 

determine the average for each year. 

Step 3: Average the three annual values. 

Step 4: Round the resulting value to the nearest 0.1 μg/m3. 

Step 5: Compare the result to the standard.

Tables A-3 through A-6 show the trend of the 24-hour average and annual average 

values for each PM2.5 monitoring site in the Valley by year as well as the three-year 

average design values for these metrics through the year 2013. 

24-hour single-year 98th-percentile averages (Table A-3) are used to generate the threeyear average 24-hour design values (Table A-4). Single-year average PM2.5 

concentrations (Table A-5) are used to generate the three-year average annual design 

values (Table A-6). These data are also shown graphically in Figures A-2.1 through A-

 

5

 Interpretation of the National Ambient Air Quality Standards for PM2.5, 40 C.F.R. Pt. 50 Appendix N (2012). 

Available at http://ecfr.gpoaccess.gov/cgi/t/text/textidx?c=ecfr&sid=9bdb7a34dcb75892aef9ee60b74da642&rgn=div9&view=text&node=40:2.0.1.1.1.0.1.18.15&idno=40 6

 Environmental Protection Agency [EPA]: Office of Air Quality Planning and Standards. (1999, April). Guideline on 

Data Handling Conventions for the PM NAAQS (EPA-454/R-99-008). Retrieved from 

http://www.epa.gov/ttn/oarpg/t1/memoranda/pmfinal.pdf
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2.32 for a number of monitoring sites in the Valley. Note that the Fresno-First 

monitoring site was closed in early 2012 and its nearby replacement site of FresnoGarland was opened soon after. To form a continuous data record, these two sites 

were combined to create a Fresno-First/Garland historical record. 

 

Average ambient PM2.5 concentrations vary by monitoring site within the Valley. In 

general, monitoring sites in the northern part of the Valley record the lowest ambient 

PM2.5 concentrations. Currently more Valley air monitoring sites meet the 1997 24-

hour average standard of 65 μg/m3 than the annual average standard of 15.0 μg/m3. 

For 2013, all District sites have met the 1997 24-hour PM2.5 Standard. For the annual 

average PM2.5 Standard, most monitoring sites are showing a downward trend; 

however, the concentrations remain above the annual mean NAAQS. 

. 

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Table A-3 Single Year 24-hour Average PM2.5 98th Percentile Values (μg/m3) 

SJV Monitoring Site 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 

Stockton 79.0 55.0 58.0 50.0 41.0 36.0 44.0 42.0 48.0 61.6 40.4 29.7 Manteca Modesto 100.0 71.0 69.0 69.0 47.0 45.0 55.0 52.0 57.4 53.9 54.5 37.3 Turlock 53.1 43.5* Merced-Coffee 39.9 Merced-M 91.9 60.0 49.3 55.1 44.2 43.0 48.3 43.8 52.7 54.0 45.2 35.5 Madera-City 57.0 Fresno-First 120.0 90.0 75.0 75.0 56.0 52.0 71.0 51.0 67.0 57.4 55.8 48.8 Fresno-Garland Fresno-Winery 64.8 61.5 71.9 49.7 49.4 71.2 55.0 57.4 44.5 48.2 37.0 Clovis 59.2 72.5 71.5 53.2 48.1 52.4 63.0 51.3 60.9 49.0 49.0 44.3 Tranquility 27.7 Corcoran 53.0* 55.1 89.5 65.1 42.2 49.4 74.5 50.1 57.9 47.9 53.4 47.2 Hanford Visalia 114.0 103.0 96.0 70.0 47.0 54.0 65.0 50.0 59.7 62.1 53.9 36.3 Bakersfield-Golden 95.3 93.9 95.9 80.4 51.9 53.9 74.9 64.4 67.7 60.8 68.6 Bakersfield-California 97.4 92.7 94.9 73.0 48.3 61.5 63.2 60.5 73.0 64.5 66.7 53.3 Bakersfield-Planz 76.5 90.6 66.8 47.5 47.6 66.4 64.7 72.2 72.3 65.5 56.2 Table A-4 24-hour Average PM2.5 Design Values (Three-Year Averages, μg/m3), end year listed 

SJV Monitoring Site 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 

Stockton 64 54 50 42 40 41 45 51 50 44 Manteca Modesto 80 70 62 54 49 51 55 54 55 49 Turlock 60 55* Merced-Coffee Merced-M 67 55 50 47 45 45 48 50 51 45 Madera-City Fresno-First 95 80 69 61 60 58 63 58 60 54 Fresno-Garland Fresno-Winery 63 66 61 57 57 59 61 52 50 43 
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SJV Monitoring Site 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 

Clovis 68 66 58 51 55 56 58 54 53 47 Tranquillity Corcoran 66 70 66 52 55 58 61 52 53 49 Hanford Visalia 104 90 71 57 55 56 58 57 59 51 Bakersfield-Golden 95 90 76 62 60 64 69 64 66 Bakersfield-California 95 87 72 61 58 62 66 66 68 62 Bakersfield-Planz 84 78 68 54 54 60 68 70 70 65 Table A-5 Single Year Annual Mean PM2.5 Concentrations (μg/m3) 

SJV Monitoring Site 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 

Stockton 19.7 15.5 13.9 16.7 13.6 13.2 12.5 13.1 12.9 14.4 11.3 10.6 Manteca Modesto 24.9 18.7 15.6 18.7 14.5 13.6 13.9 14.8 15.0 16.0 13.0 12.1 Turlock 16.1 12.5* Merced-Coffee 16.3 Merced-M 22.6 16.7 14.5* 18.7 15.7 15.2 14.1 14.8 15.2 14.9* 13.6 11.2 Madera-City 21.1* Fresno-First 27.6 24.5 19.8 21.5 17.8 16.3 16.7 16.8 18.8 17.4 15.1 13.0 Fresno-Garland Fresno-Winery 18.4 18.6 21.3 17.8 17.0 16.9 17.6 16.8 16.5 14.6 13.4 Clovis 19.8 16.3 18.0 16.2 18.5* 16.4 16.3 16.4 16.4 16.2 18.3 14.7 Tranquillity 7.0* Corcoran 14.3* 16.4 19.2 21.5 16.2 17.4 17.5 16.9 18.4 15.8 17.7 17.9 Hanford Visalia 27.6 23.9 22.5 23.2 18.2 17.0 18.8 18.8 20.4 19.8 16.0 13.6 Bakersfield-Golden 26.2 22.6 21.8 24.1 19.6 18.2 19.1 18.6 19.9 17.9 20.0 Bakersfield-California 23.8 22.5 21.2 22.7 17.1 18.9 18.0 18.7 22.0 21.9 19.0 14.2 Bakersfield-Planz 20.3 20.8 23.5 17.8 17.4 19.8 19.3 21.8 23.5 22.5 17.6 
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Table A-6 Annual PM2.5 Design Values (Three-Year Averages, μg/

m3), end year listed (2011-201

SJV Monitoring Site 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 

Stockton 16.4 15.3 14.7 14.5 13.1 12.9 12.8 13.5 12.9 12.1 Manteca Modesto 19.7 17.7 16.2 15.6 14.0 14.1 14.6 15.3 14.7 13.7 Turlock Merced-Coffee 1Merced-M 17.9* 16.6* 16.3* 16.5 15.0 14.7 14.7 15.0 14.6 13.2 Madera-City Fresno-First 24.0 21.9 19.7 18.6 16.9 16.6 17.4 17.7 17.1 15.2 Fresno-Garland Fresno-Winery 18.5 19.4 19.2 18.7 17.2 17.2 17.1 17.0 16.0 14.9 Clovis 18.0 16.8 17.6 17.0 17.1 16.4 16.4 16.3 17.0 16.4 Tranquillity Corcoran 19.0 19.0 18.4 17.0 17.2 17.6 17.0 17.3 17.1 Hanford Visalia 24.7 23.2 21.3 19.5 18.0 18.2 19.3 19.7 18.8 16.5 Bakersfield-Golden 23.6 22.8 21.8 20.6 19.0 18.6 19.2 18.8 19.3 Bakersfield-California 22.5 22.1 20.3 19.6 18.0 18.5 19.6 20.9 21.0 18.4 Bakersfield-Planz 21.5 20.7 19.6 18.4 18.9 20.3 21.5 22.6 21.2 

Notes for Tables A-3, A-4, A-5, and A-6  Source: U.S. Environmental Protection Agency: Air Quality System 

(AQS): AMP 480 Report, available at http://www.epa.gov/ttn/airs/airsaqs/aqsweb/, January 6, 2015. 

 Empty cell: No data or insufficient data  Asterisk (*): Values do not meet completeness criteria  Double asterisk (**): Value based on 2-year average of 2010-2011, 2009 

had minimal sampling, Value based on 2-year average of 2011-2012, 2010 had minimal sampling 

 Triple asterisk (***): Value based on 2-year average of 2012-2013 
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Figures A-2.1 through A-2.32 24-hour and Annual Design Value Trends 
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A-18 Appendix A: Ambient PM2.5 Data Analysis 

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A.3 AMBIENT PM2.5 CONCENTRATION DATA TRENDS 

Design values summarize data from a monitoring site with just two concentration values 

representing a three-year time period: an annual average and a value representing 24-

hour peaks. These parameters are required for attainment demonstrations, but design 

values alone do not reveal the hourly, daily, weekly, seasonal, and regional PM2.5 

effects on public health, nor do they track air quality improvements within such 

parameters. The District uses data from air monitoring sites to analyze air quality trends 

to provide a deeper understanding of changes in ambient PM2.5 concentrations as they 

relate to the implementation of District programs and to inform the attainment planning 

process and Health Risk Reduction Strategy. 

A.3.1 Days over the 24-Hour PM2.5 Standard 

The number of days over the PM2.5 Standard is another indicator of air quality 

progress. Focusing on historical air monitoring sites from the northern, central, and 

southern portions of the Valley, Figure A-3 shows the trend of the number of days 

above the 1997 standard at the Modesto, Fresno-First/Garland, and BakersfieldCalifornia monitoring sites. These counts have been estimated and normalized to 

account for the varying sampling schedules of the Valley’s 1-in-6-day, 1-in-3-day, and 

daily PM2.5 monitors. 

Design value calculations for the 24-hour Standard use the 98th-percentile concentration 

value from each monitoring site (higher values in the 99th and 100th percentiles are not 

used to account for extreme outliers). Because of this, a region may experience a 

limited number of days over the standard, but still be considered in attainment. 
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Figure A-3 Trend in Days over the 1997 24-Hour PM2.5 Standard 

Note: Years and sites with no data (colored bars) represent zero exceedances. 

As shown in Figure A-3, the Valley has experienced a significant drop in the number of 

exceedances of the 65 μg/m3 standard since the turn of the last century (1999 and 

2000). In 1999, approximately 104 exceedances of this standard occurred between the 

sites of Modesto, Fresno-First/Garland, and Bakersfield-California. Comparing this to 

the 25 exceedances that occurred in 2013, this represents a 76% decrease in the 

number of violations among these sites. 

The District’s emissions reduction strategy, the investment from the regulated industry 

in control technology, and the public’s willingness to make a change for cleaner air have 

all played key roles in the reduction of concentrations over this time period. During the 

winter, with unfavorable stagnant meteorology as experienced during the 2011–2012 

winter season, which has repeated itself each winter since and has created (as of 

2014) the historic three year drought, has contributed greatly to the recent higher than 

expected PM2.5 concentrations and exceedances under identical regulatory controls. 

Similar poor dispersion conditions were experienced during the winter of 1999–2000; 

however, under those similar conditions, the number of exceedances in 2011 and 

onward has been markedly less than the number of exceedances in 1999, which 

strongly suggests a real reduction in emissions. 
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A-20 Appendix A: Ambient PM2.5 Data Analysis 

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A.3.2 Seasonal Trends - 1st and 4th Quarter Averages 

Since the Valley’s highest PM2.5 concentrations occur during the fall and winter 

months, in the 1st and 4th quarters (January through March and October through 

December, respectively), these months tend to have the highest average PM2.5 

concentrations. Observing the trend in these quarterly averages can shed light on how 

the peak of the PM2.5 season is changing over time. 

The data used in this analysis utilizes PM2.5 filter values from 1999 through 2013 

focusing on the 1st and 4th quarters at six sites in the District that tend to have the 

highest concentrations; Clovis, Fresno-First/Garland, Corcoran, Visalia, BakersfieldCalifornia, and Bakersfield-Planz. Note that the Fresno-First monitoring site was closed 

in early 2012 and its nearby replacement site of Fresno-Garland was opened soon after. 

To form a continuous data record, these two sites were combined to create a FresnoFirst/Garland historical record. 

An analysis of the 24-hour PM2.5 historical filter data depicts a general trend of 

reductions in both the average over the quarter (Quarter Average), as well as the 

average over the quarter of the five highest (maximum) values (Top 5 Average). The 

Top 5 Average data demonstrates the episodic nature of PM2.5 pollution, the severity of 

peak PM2.5 episodes, and the public exposure to peak concentrations of PM2.5.

The Quarter Average charts shown below (Figures A-4.1 through A-4.12) indicate that 

all sites are trending downward; averaging 0.8 μg/m3 less PM2.5 per year, collectively. 

In regards to the Top 5 Average (Figures A-5.1 through A-5.12) all but one site are 

trending downward. Clovis is the anomaly showing a slight upward trend. However, 

this may be due to random variation of the data resulting in the unusually high values in 

the first quarter of 2012 and the fourth quarter of 2011 and 2013 that pulls both quarter 

trend lines upward. Without those three data points the trend line would be flat, and not 

significantly increasing or decreasing. Despite Clovis, the overall trend for all of the Top 

5 Average sites is averaging downward at 1.4 μg/m3 less PM2.5 per year. This 

demonstrates the reducing severity of the PM2.5 episodic peaks over time. 

The Quarter Average with the greatest rate of reduction in PM2.5 is almost unanimously 

in the fourth quarter and less so in the first quarter. Conversely, the quarter with the 

greatest rate of reduction in PM2.5 for the Top 5 Average is almost unanimously in the

first quarter and less so in the fourth quarter (except for Clovis). 

In conclusion, the overall quarterly downward trends of both the Quarter Averages and 

the Top 5 Averages are important indicators for attaining the District’s Health-Risk 

Reduction Strategy and the annual average PM2.5 standard. 
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Figures A-4.1 through A-4.12 Quarter Average Trends 
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Figures A-4.1 through A-4.12 Quarter Average Trends 
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Figures A-4.1 through A-4.12 Quarter Average Trends 
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Figures A-5.1 through A-5.12 Collection of Top 5 Average Trends 
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Figures A-5.1 through A-5.12 Collection of Top 5 Average Trends 
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Figures A-5.1 through A-5.12 Collection of Top 5 Average Trends 
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A.3.3 Annual Trends 

The District collects hourly PM2.5 concentration data using real-time monitors. The 

District uses this data every day to produce air quality forecasts, wood burning 

declarations, public health notifications, and Real-time Air Advisory Network (RAAN) 

notifications. 

Based on historical hourly data, the District has compiled long-term diurnal profiles to 

evaluate how PM2.5 concentrations vary throughout the day at each of the Valley 

monitoring sites that measure PM2.5. An analysis of hourly measurements can show 

which portions of the day tend to have the highest and lowest concentrations. 

Understanding such profiles helps in the development of control strategies and 

programs that target activities during times of peak concentrations. 

The long-term diurnal profiles can also indicate how the curve has changed from year to 

year. The District compares relative changes in hourly PM2.5 concentrations from year 

to year at each monitoring site to better understand the implications and effectiveness of 

PM2.5 control measures, especially Rule 4901 (Wood Burning Fireplaces and Wood 

Burning Heaters). Prior to 2003, Rule 4901 called for voluntary wood-burning 

curtailments. Such curtailments became mandatory beginning in the 2003–2004 winter 

season and have since been strengthened twice, once in 2008 and once again in 2014. 

Prior to the 2008-2009 winter season, the Rule was amended to specify that woodburning curtailments would be declared when a PM2.5 concentration of 30 μg/m3

 or 

higher was predicted for a county. Prior to the 2014-15 winter season, the threshold 

was lowered to 20 μg/m3 or higher and contained a tiered system which effectively 

mitigates emissions from residential wood-burning by discouraging, limiting, or 

prohibiting wood burning in fireplaces and other non-EPA certified residential wood 

burning devices during the winter months. 

Figures A-6.1 through A-6.16 show a comparison of the yearly average diurnal profiles 

over time at select real-time monitoring sites within the District’s monitoring network. As 

indicated in profiles A-8.1 through A-8.4, Modesto, Fresno7, Visalia, and Bakersfield 

have a longer history of monitoring PM2.5 than the other sites and clearly illustrate that 

PM2.5 concentrations were much higher prior to the strengthening of Rule 4901. 

 

 

7

 The Fresno-First Street monitor was relocated one block north to Garland Avenue in 2011 and is now the FresnoGarland site. The two sites are considered to be the same site so data from the Fresno-First Street and FresnoGarland sites were combined and used to create the Fresno chart. 
San Joaquin Valley Unified Air Pollution Control District 

A-28 Appendix A: Ambien

 2015 Plan for th

Figures A-6.1 through A-6.16 PM2.5 Diurnal Profiles 
San Joaquin Valley Unified Air Pollution Control District 

A-29 Appendix A: Ambien

 2015 Plan for th

Figures A-6.1 through A-6.16 PM2.5 Diurnal Profiles 
San Joaquin Valley Unified Air Pollution Control District 

A-30 Appendix A: Ambien

 2015 Plan for th

Figures A-6.1 through A-6.16 PM2.5 Diurnal Profiles 
San Joaquin Valley Unified Air Pollution Control District 

A-31 Appendix A: Ambien

 2015 Plan for th

Figures A-6.1 through A-6.16 PM2.5 Diurnal Profiles  *Charts represent complete years of data within the past five years..
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-32 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

A.3.4 PM2.5 Driven Air Quality Index Analysis 

The EPA and the District use the Air Quality Index (AQI) to provide daily information 

about the Valley's air quality, educate the public about how they can protect their health, 

and to inform the public about how unhealthy air may affect them. AQI scales exist for 

all of the criteria pollutants regulated by the Clean Air Act, including PM2.5. The 

current8 24-hour average PM2.5 AQI scale is shown in Table A-7 below. 

Table A-7 PM2.5 AQI Scale 

AQI Category Index 

Values 

Concentration 

(μg/m3, 24-hr average) 

Good 0-50 0 – 12.0 

Moderate 51-100 12.1 – 35.4 

Unhealthy for Sensitive 

Groups (USG) 101-150 35.5 - 55.4 

Unhealthy 151-200 55.5 - 150.4 

Very Unhealthy 201-300 150.5 - 250.4 

Hazardous 301+ 250.5+ 

The District analyzed the trends in the PM2.5 data from the sites with at least two years 

of daily AQI observations based on real-time data. For this analysis, the AQI trends are 

based upon PM2.5 concentrations only, and do not include ozone, PM10, or other 

pollutants. By excluding the other pollutants, the District is able to isolate the change in 

air quality trends related to PM2.5 only. 

Figure A-7 is shown as a reference for interpreting Figures A-8.1 through A-8.11. The 

stacked bars represent the number of days within each year that fell within each of the 

AQI categories (totaling 365 days). Because of regular maintenance or repairs, 

monitors may be non-operational for a day or longer. For years with “missing” days, 

proportional adjustments were made to estimate the missing days so as to provide a full 

year’s data to display. Within each stacked bar, the categories are ordered as Good, 

Moderate, etc. from the bottom up. 

 

8

 CFR Appendix G to Part 58, Uniform Air Quality Index (AQI) and Daily Reporting 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-33 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

Figure A-7 Air Quality Index (AQI) Categories 

For the majority of the Valley sites, the observed AQI data for the 2008–2013 timeframe 

shows an improvement in PM2.5 air quality. This finding is significant and needs to be 

emphasized because this improvement is expressed despite the data being subject to 

the lowered AQI break points, as noted above in Table A-7. Over these five years, the 

frequency of Good AQI days increased, coupled with a decrease in the frequency of the 

Moderate and Unhealthy-for-Sensitive-Groups AQI days. For example, at the FresnoFirst /Garland site, the number of Good days increased from 189 in 2008, to 207 in 

2013. At the same time, the Moderate and USG days decreased from 126 to 103, and 

41 to 31, respectively. 

At the Bakersfield-California site, a similar pattern occurred with the frequency of Good 

AQI days increasing, and the frequency of the Moderate and USG AQI days 

decreasing. For example, the number of Good days increased from 117 in 2008 to 157 

in 2013. At the same time, the Moderate and USG days decreased from 181 to 152, 

and 48 to 27, respectively. 

These improvements over the 2008–2013 timeframe reflect the emissions reductions 

occurring over these five years. A key part of the emissions reductions during this 

period is the District’s Rule 4901 (Wood Burning Fireplaces and Wood Burning 

Heaters), which was strengthened just before the 2008–2009 winter season, lowering 

the curtailment threshold from 65 μg/m3

 to 30 μg/m3. The observed improvement in 

PM2.5 AQI values is partly attributable to the amended wood-burning rule. 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-34 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

Since 2011, the PM2.5 air quality declined at some sites for some years, as compared 

to previous years. Abnormally stagnant meteorology during the winter of 2011–2012, 

which has repeated itself each winter since, has created (as of 2014) the historic three 

year drought and contributed greatly to this PM2.5 deterioration. 

As noted above, over the past several winters, a persistent and strong high pressure 

ridge over the eastern Pacific Ocean and the western United States effectively blocked 

weather disturbances from entering California that would normally have removed and 

replenishment of the valley’s air with clean air. The historic strength and longevity of 

this high pressure resulted in a lack of rainfall and stagnation conditions leading to a 

subsequent increase in the suspended particulate matter in the atmosphere. This 

caused of the exceptionally high PM2.5 concentrations found in the Valley and 

throughout the state of California. Despite these current conditions the general trend 

has been for improving air quality. 

In Figure A-8.12, the data for each site was averaged for all years. In the graph the 

sites are arranged from north to south along the horizontal axis from left to right. This 

shows that the northern sites have more Good AQI days than the southern sites. The 

Stockton-Hazelton and Tracy sites (average between the two is approximately 72% 

Good AQI), and have about 25% more days in the Good AQI category than the Visalia 

and Bakersfield sites which average about 47% Good AQI. 

Figure A-8.13 presents the data by year averaging all the sites together for an overall 

regional view, illustrating that the percentage of Good AQI days is increasing for the 

District as a whole, while the percentage of Moderate AQI days is decreasing 

throughout the District. More specifically (and in terms of days instead of percent) for 

the 11 years between 2003 and 2013, the number of days in the Good AQI category 

increased by 58 days since 2003, while the number of days in the Moderate, USG, and 

Unhealthy AQI categories decreased by 46 days, 11, and 1 day, respectively. This 

finding is significant and needs to be emphasized because this improvement is 

expressed despite the population increase, the two year drought and winter 

atmospheric stagnation periods. 

By observing all of the following figures, it is apparent that the dominant annual PM2.5 

AQI categories are the Good and Moderate categories. The final figure (Figure A-8.14) 

is presented to summarize this observation. The data was averaged for all sites and all 

years (for all years that data that was available for each site). This analysis illustrates 

that for the Valley as a whole, and over the course of the eleven years, that 92% of all 

days (335 days) were within the Good and Moderate AQI categories. Breaking that 

down further shows that the Valley has averaged, 55% Good AQI days (199 days), 37% 

Moderate AQI days (136 days), 6% USG days (23 days), and 2% Unhealthy days (7 

days). 

 
San Joaquin Valley Unified Air Pollution Control District 

A-35 Appendix A: Ambien

 2015 Plan for th

Figures A-8.1 through A-8.4 Number of Days per AQI Category per Year: Stockton-Hazelto

Modesto, and Turlock 
San Joaquin Valley Unified Air Pollution Control District 

A-36 Appendix A: Ambien

 2015 Plan for th

Figures A-8.5 through A-8.8 Number of Days per AQI Category per Year; Merced, Clovis, F

First/Garland, and Hanford 
San Joaquin Valley Unified Air Pollution Control District 

A-37 Appendix A: Ambien

 2015 Plan for th

Figures A-8.9 through A-8.11 Number of Days per AQI Category per Year: Corcoran, Visalia

California 
San Joaquin Valley Unified Air Pollution Control District 

A-38 Appendix A: Ambien

 2015 Plan for th

Figures A-8.12 through A-8.14 PM2.5 AQI Site Average, PM2.5 AQI Year Average, and PM2.5 

All Sites and all Years Combined 

92% of all days are Good to Moderate AQI
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-39 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

A.3.5 Trends in PM2.5 Species 

The NAAQS for particulate matter is established on the basis of the amount of 

particulate matter, by mass (weight) that a filter sampler is able to collect per cubic 

meter of air. Most air monitoring devices for particulate matter report only the mass of 

the particulate matter filtered from the air; however, the mass alone does not tell what 

source the particulate matter may have come from, or provide direct evidence to 

determine whether the State Implementation Plan (SIP) measures are having the 

expected impact on particulate emissions. 

Additional monitoring is conducted with special samplers that collect filters for additional 

analysis of contributing materials (species). The samples collected by speciation 

samplers are subjected to extensive physical and chemical laboratory analysis. The 

data produced from the analysis can be used to evaluate trends in the various materials 

(species) that contribute to particulate emissions and provide information to verify 

source contributions. The speciation data is also used to support some types of 

modeling methods to predict future air quality. The variation of materials that contribute 

to particulate matter shown by samples collected over several years can reveal long 

term trends. The trend information of the materials observed in the air can be 

compared to the expected changes predicted from emissions reductions and modeling. 

A.3.5.1 Valley Speciation Monitoring 

There are four speciation monitors collecting samples in the Valley these are located in 

Bakersfield, Fresno, Modesto and Visalia. The ARB provides the extensive and 

expensive laboratory analysis of the collected speciation filters and compiles the 

resulting data. 

A.3.5.2 Data provided by Speciation Analysis 

Analysis of the filter collected by a speciation sampler reports a variety of contributing 

materials. The largest mass contributions are the focus of SIP measures to reduce 

emissions. However, the contributing source of the material may not be clear because 

many different sources may emit the same common materials. The smaller speciation 

mass categories are important for use as “tracers” or fingerprints to help identify the 

relative contribution of sources. 

The following tables (A-8 and A-9) provide a summary of the different contributing 

materials (species) that are identified by laboratory analysis of the speciation sampler 

filters. 

 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-40 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

Table A-8 Largest Mass Contributions Reported in Speciation Analysis 

Species Name Description 

PM2.5 Speciation Mass Total mass of PM2.5 on the filter 

OC CSN Unadjusted PM2.5 LC TOT (there 

are a variety of different analysis methods 

reporting different fractions of this contribution)

Organic Carbon 

(VOC evaporation, incomplete combustion 

and biogenic) 

EC CSN PM2.5 LC TOT 

(there are a variety of different analysis 

methods reporting different fractions of this 

contribution) 

Elemental Carbon 

(combustion product)

Nitrate (NO3-) Key winter mass contribution to PM2.5 

Sulfate (SO42-) Year-round minor contributor 

Ammonium (NH4+) Connects to both Nitrate and Sulfate 

Soluble Potassium (K+) Shows vegetative burning primarily, some 

industrial contribution 

Soluble Sodium (NA+) Various sources 

Aluminum (Al) Indicator for soil, but also engine wear 

Calcium (Ca) Indicator for soil, but also construction 

Chlorine (Cl) Various sources 

Iron (Fe) Break wear, engine wear, but also soil 

Potassium (K) Various industrial and agricultural sources 

Silicon (Si) Indicator for soil 

Sodium (Na) Various sources 

Sulfur (S) Indicator for some agricultural activities and 

some industrial combustion sources 

Levoglucosan Newer method to show burning, 

sugar released by wood combustion 

 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-41 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

Table A-9 Smaller and Trace Level Mass Contributions Reported in the 

Speciation Analysis 

Small or Moderate Contributing Sources 

Barium (Ba) 

Copper (Cu) 

Tin (Sn) 

Titanium (Ti) 

Zinc (Zn) 

Galactosan (sugar related to wood combustion)

Mannosan (sugar related to wood combustion)

Trace Contributions 

Antimony (Sb) Mercury (Hg) 

Arsenic (As) Molybdenum (Mo) 

Bromine (Br) Nickel (Ni) 

Cadmium (Cd) Niobium (Nb) 

Cerium (Ce) Phosphorus (P) 

Cesium (Cs) Rubidium (Rb) 

Chromium (Cr) Samarium (Sm) 

Cobalt (Co) Scandium (Sc) 

Europium (Eu) Selenium (Se) 

Gallium (Ga) Silver (Ag) 

Gold (Au) Strontium (Sr) 

Hafnium (Hf) Tantalum (Ta) 

Indium (In) Terbium (Tb) 

Iridium (Ir) Tungsten (W) 

Lanthanum (La) Vanadium (V) 

Lead (Pb) Yttrium (Y) 

Manganese (Mn) Zirconium (Zr) 

A.3.5.3 Trends and Findings Provided by Speciation Data 

Speciation samples collected from 2001 through 2013 have been evaluated to 

determine variation of species on each of the collected filters. The resulting data from 

filter analysis has been evaluated to detect trends in the reported species. There are 

limiting factors that affect the trend analysis including: 

 Only the four speciation sampler locations in Bakersfield, Fresno, Modesto and 

Visalia can be evaluated directly from the speciation filter data. These sites are 

representative of the Valley but may not explain every variation in total particulate 

observed at other monitoring locations 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-42 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

 The Fresno speciation sampler was moved to a new, but nearby, location in 

2012. Data appear to be consistent for both locations; therefore, the trend 

evaluation is interpreted as a continuous period of sampling 

 Organic carbon and elemental carbon test methodology has changed during the 

sampling period. Older methodology was used through early 2009. Newer 

methods were introduced in mid-2007 providing two years of comparison data. 

The two methods do not provide comparable data for creation of a long term 

trend analysis for the entire 2001 through 2013 period. Newer methodology 

reports low concentrations with a narrow range of variability which is not ideal for 

trend evaluation. 

Findings from analysis of the speciation data are discussed for the following topics: 

 Trends (multiyear trends in total particulate and major contributing species, 

responsive species and times of year, nonresponsive species and times of year, 

interpretation) 

 Drought impacts (soil as an indicator for drought impact, observed trends, 

implications for the SIP) 

 SIP implications (District strategy effectiveness) 

Trends (multiyear trends in total particulate and major contributing species, responsive 

species and times of year, nonresponsive species and times of year, interpretation) 

 Total particulate: Both the average value recorded at the four sites and the 

peak value recorded at the four sites show clear trends of reduction. Figure A-9 

and A-10 shown below illustrates the total particulate trend in average and 

maximum PM2.5 speciation mass. Each of the four sites shows very similar 

trends to the group analysis. This suggests that all of the Valley sites are 

expected to be experiencing similar trends, despite the lack of speciation filter 

data for confirmation at sites other than the four speciation sampler sites. The 

average of values for the entire year shows improvement from 24 μg/m3 of air to 

16 μg/m3

. Both the Average value and Maximum value analyses show 

improvement from March to October that is approaching the 15 μg/m3

 annual 

standard. However, while improving, the late fall and winter months from 

November through February are proving to be resistant to change, creating 

challenges in the Valley’s journey to attainment of the federal PM2.5 standards. 

 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-43 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

Figure A-9 Average PM2.5 Speciation Mass 

Figure A-10 Maximum PM2.5 Speciation Mass 

The next step in analysis of the particulate trend is to evaluate which types of particulate 

matter are improving and which types are resistant to change. To perform trend 

analysis of the components included in particulate matter requires examining the major 

constituents (species) of particulate matter. Particulate matter can be divided into 

several major constituents: Nitrates, Sulfates, Organic Carbon, Elemental Carbon and 

Geologic material. Nitrates and Sulfates are formed in the atmosphere from gases 

(ammonia, NOx, SOx). Organic carbon is both directly emitted and formed in the 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-44 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

atmosphere. Elemental carbon (from combustion) and geological material (soil related 

plus trace elements) are directly emitted and do not change once emitted. 

 Nitrate: Ammonium nitrate is the largest contributor to particulate matter on an 

annual basis. Ammonium nitrate is a material that forms in the atmosphere from 

materials that are considered to be gases (and would not collect on a filter 

sample) into a material that is considered to be particulate matter and does 

collect on filter samples. However, during the warmer times of year, while 

ammonium nitrate forms in the atmosphere it does not remain as particulate 

matter but evaporates and returns to the component gases. From March through 

October the amount of ammonium nitrate collected on filter samples is very low 

and is not the dominant source of particulate matter. The November through 

February levels of ammonium nitrate are a substantial portion of the total 

particulate mass. Ammonium nitrate is calculated from the speciation data by 

adding the reported amount of nitrate to a calculated portion of the ammonium 

(total reported ammonium minus the portion of ammonium that is involved in 

ammonium sulfate formation). Figure A-11 shown below illustrates the sum of 

ammonium (NH4+) and nitrate (NO3-) speciation mass. 

Figure A-11 Sum of Ammonium (NH4+) and Nitrate (NO3-) Speciation Mass 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-45 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

Evaluation of the trends of the average values observed for ammonium nitrate data do 

show reduction during the 2001 to 2013 period. Figure A-12 shown below illustrates the 

average value ammonium nitrate trend. Both the March to October low values and the 

November to February higher values show reduction when looking at the average 

values observed. This indicates that the reduction measures to reduce nitrogen oxide 

emissions are having an impact on the formation of ammonium nitrate. 

Figure A-12 Average Value Ammonium Nitrate Trend 

 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-46 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

The maximum values of ammonium nitrate observed have not followed the trend 

projected by the average values. March through November maximum value data does 

show an improving trend; however January, February and December data does not 

show the same improvement, as shown in Figure A-13 below. The maximum monthly 

percentage of PM2.5 attributable to ammonium nitrate is shown in Figure A-14 below. 

Figure A-13 Sum of Ammonium (NH4+) and Nitrate (NO3-) Speciation Mass 

Figure A-14 Maximum Monthly Percentage of PM2.5 Attributable to Ammonium 

Nitrate 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-47 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

Because the peak values in January, February and December have not shown a 

proportional reduction to the average emissions reduction and reduction of average 

observed values, it is difficult to determine how much additional reductions will be 

required to sufficiently impact the peak values. An important finding for the SIP is that 

reductions achieved have not been sufficient to achieve the ambient air quality standard 

and a target for additional reductions to achieve that objective is difficult to forecast. 

Another important finding for the SIP is that ammonium nitrate continues to be a 

dominant source of PM2.5, contributing more than half of the particulate observed 

during winter, and must remain a key component for reduction efforts through effective 

reduction of NOx emissions (see Chapter 2). 

The reason that nitrate emission reductions have not achieved the improvement 

predicted by the model may be attributable to a variety of factors. Each of these factors 

may play a partial role. Data is not available at this time to provide a revision to the 

model to account for these factors. The potential factors include but may not be limited 

to: 

o Aqueous atmospheric reactions not currently available for inclusion in the 

model – missing reactions may account for under-prediction of 

atmospheric formation of nitrates in winter 

o Horizontal diffusion parameters appropriate for winter, with diffusion more 

limited than the current 4 kilometer grid representation of mixing used in 

the model – requires field investigation to provide parameters and model 

code enhancement to improve the simulation of observed horizontal 

diffusion 

o Vertical diffusion parameters for winter inversions – requires field 

investigation to provide parameters and model code enhancement to 

improve the simulation of observed vertical diffusion 

o Adjustment of atmospheric chemistry for impacts of drought (lower 

humidity results in higher photochemistry activity which provides radicals 

that promote particulate formation) 

 Sulfate: Ammonium sulfate is a small contributor to particulate matter on an annual 

basis. Ammonium sulfate is a material that forms in the atmosphere from materials 

that are considered to be gases (and would not collect on a filter sample) into a 

material that is considered to be particulate matter and does collect on filter 

samples. Once formed, ammonium sulfate is relatively stable in the atmosphere and 

is removed by deposition to vegetation or soil or by dispersion by gradual horizontal 

dissipation or by being carried to other locations by action of wind. 

Evaluation of the trends of the average values observed for ammonium sulfate data 

do show reduction during the 2001 to 2013 period. Reductions are apparent for 

every month and do not show resistance to improvement in winter except in 

December. The cause of resistance to improvement in December may be due to 

reduced inversion heights and severe episodes of air stagnation. Improvement 

throughout the year indicates that the reduction measures to reduce sulfur oxide 

(SOx) emissions are having an impact on the formation of ammonium sulfate. 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-48 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

Ammonium Sulfate is calculated from the speciation data by adding the reported 

amount of sulfate to a calculated portion of the ammonium (total reported ammonium 

minus the portion of ammonium that is involved in ammonium nitrate formation). 

Figure A-15 shown below illustrates the sum of sulfate and nitrate in the speciation 

mass. 

Figure A-15 Sum of Sulfate ((SO4)

2-) and Nitrate (NO3

-

) Speciation Mass 

 Elemental Carbon (EC) and Organic Carbon (OC): Elemental carbon from 

combustion is a small contributor to PM2.5. Organic carbon from incomplete 

combustion, evaporation and biogenic sources is a large contribution to observed 

levels of PM2.5, particularly during winter months. Elemental carbon reflects 

changes in industrial VOC emissions. Organic carbon reflects changes in 

evaporative VOC emissions and incomplete combustion processes such as 

charbroiling and residential wood combustion. Changes in the atmospheric 

levels of EC and OC are therefore important for evaluating the effectiveness of 

measure in the SIP. 

Laboratory filter sample speciation evaluation methods are used to determine 

how much of the observed carbon is elemental (does not contain oxygen) and 

how much is organic (contains oxygen). The combined processing to determine 

the EC and OC attributions requires discussion of both as a single topic. The 

laboratory methods for determining this apportionment have to use oxygen to 

break down compounds that contain carbon. The use of oxygen makes it difficult 

to determine an accurate measurement of elemental carbon if it is oxidized in the 

analysis process and made to appear to be organic carbon. The test methods 

have undergone several revisions to improve methodology. 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-49 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

The test method for organic carbon and elemental carbon changed during the sampling 

period. Older methodology was used through early 2009. Newer methods were 

introduced in mid-2007 providing two years of comparison data. The two methods do 

not provide comparable data for creation of a long term trend analysis for the entire 

2001 through 2013 period. Newer methodology reports low concentrations with a 

narrow range of variability which is not ideal for trend evaluation. 

The limitations inherent in the test methodology have produced results that EPA does 

not consider reliable. EPA has recommended differencing methods for modeling and 

air monitoring speciation analysis where all easily quantifiable components are 

subtracted from the total PM 2.5 mass and the remainder is considered to be carbon. 

The recommended methodology of assigning carbon to all unknown material is not ideal 

for the 15 μg/m3

 annual standard due to the need for precision. Additionally this 

approach is not ideal for the 24-hour PM2.5 standard in areas like the Valley where 

windblown dust emissions have the potential to produce substantial levels of inert 

material, identifiable only from calculations for tracer compounds that must assume the 

molecular weight of the original material. 

 Geologic Material and Trace Elements: Geologic material is related to windblown 

dust and trace elements contained in soil material, but geologic material also 

includes trace elements related to different sources such as fireworks, engine 

exhaust and tire and brake wear. The amount of geologic material in PM2.5 is 

generally the third largest source following nitrate and organic carbon. SIP 

measures to reduce geologic material have been effective but are beginning to show 

impact from the continuing drought. 

Drought Impacts

Drought related impacts can be assessed by examining the speciation data trends of 

materials commonly found in soil. Drought increases the amount of soil entrained from 

roads, agricultural activities, wind entrainment and other soil disturbances that emit 

particulate into the air. Some uncertainty exists in such a trend analysis because soil is 

not the only source of many of the compounds commonly found in soil. Soils contains, 

in decreasing order, silicon, aluminum, iron, magnesium, calcium, sodium, and 

potassium. The organic fraction of soil also includes phosphorus and sulfur. Additional 

common elements in soil include copper, zinc, manganese, cobalt, chlorine, boron and 

molybdenum. More than eighty elements occur in soils. Most of the other compounds 

not mentioned specifically occur in much smaller quantities. Figure A-16 shown below 

illustrates the increase soil elements that occur during a drought. 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-50 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

Figure A-16 Increase of Soil Elements during a Drought 

Evaluation of major and trace components of PM2.5 reported in the speciation data 

were evaluated for indications of drought impact. Silicon and aluminum provided the 

strongest indication of the recent multiyear drought. Year by year increase is shown 

from 2010 through 2013. As silicon and aluminum are components of soil, and not the 

full mass of soil, the impact of drought on PM2.5 total mass is more than the mass of 

the two tracer compounds. The tracers conservatively show an up to 1 μg/m3 increase 

in PM2.5 mass due to increased soil emissions due to the drought. 

A.3.5.4 SIP Implications (District Strategy Effectiveness) 

Trend analysis of the total mass of PM2.5 shows improvement for the average of 

observed values. Peak values show improvement except for winter months from 

November through February. December and January show strong resistance to 

improvement of peak values. 

 Ammonium nitrate (the largest contributor to winter PM2.5 mass) shows 

improvement in the average of monthly data but also shows resistance to 

improvement of peak values in winter months (December through February). 

Ammonium nitrate continues to be a dominant source of PM2.5, contributing 

more than half of the particulate observed during winter, and must remain a key 

component for reduction efforts. 

 Organic Carbon (the second largest contributor to winter PM2.5 mass) shows 

less improvement than expected. This source category is difficult to assess due 

to limitations of the speciation analysis methods. 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-51 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

 Geologic material (the third largest contributor to winter PM2.5 mass) and trace 

compounds show improvement. However, geologic material is trending upward 

due to drought. 

 Sulfate (a minor contributor) shows improvement. 

 Elemental carbon (a minor contributor) shows improvement. This source 

category is difficult to assess due to limitations of the speciation analysis 

methods. 

 
San Joaquin Valley Unified Air Pollution Control District April 16, 2015

A-52 Appendix A: Ambient PM2.5 Data Analysis 

 2015 Plan for the 1997 PM2.5 Standard 

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